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Sample records for ball python python

  1. The spectacle of the ball python (Python regius)

    DEFF Research Database (Denmark)

    Da Silva, Mari-Ann Otkjær; Heegaard, Steffen; Wang, Tobias

    2014-01-01

    A detailed morphological description of the spectacle of the ball python (Python regius) is provided. The eyes of 21 snakes were examined by light microscopy and/or transmission electron microscopy. Additionally, eyes of nine live snakes were examined using optical coherence tomography (OCT) and ...

  2. Respiratory disease in ball pythons (Python regius) experimentally infected with ball python nidovirus.

    Science.gov (United States)

    Hoon-Hanks, Laura L; Layton, Marylee L; Ossiboff, Robert J; Parker, John S L; Dubovi, Edward J; Stenglein, Mark D

    2018-04-01

    Circumstantial evidence has linked a new group of nidoviruses with respiratory disease in pythons, lizards, and cattle. We conducted experimental infections in ball pythons (Python regius) to test the hypothesis that ball python nidovirus (BPNV) infection results in respiratory disease. Three ball pythons were inoculated orally and intratracheally with cell culture isolated BPNV and two were sham inoculated. Antemortem choanal, oroesophageal, and cloacal swabs and postmortem tissues of infected snakes were positive for viral RNA, protein, and infectious virus by qRT-PCR, immunohistochemistry, western blot and virus isolation. Clinical signs included oral mucosal reddening, abundant mucus secretions, open-mouthed breathing, and anorexia. Histologic lesions included chronic-active mucinous rhinitis, stomatitis, tracheitis, esophagitis and proliferative interstitial pneumonia. Control snakes remained negative and free of clinical signs throughout the experiment. Our findings establish a causal relationship between nidovirus infection and respiratory disease in ball pythons and shed light on disease progression and transmission. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  3. Computed tomography of ball pythons (Python regius) in curled recumbency.

    Science.gov (United States)

    Hedley, Joanna; Eatwell, Kevin; Schwarz, Tobias

    2014-01-01

    Anesthesia and tube restraint methods are often required for computed tomography (CT) of snakes due to their natural tendency to curl up. However, these restraint methods may cause animal stress. The aim of this study was to determine whether the CT appearance of the lungs differs for ball pythons in a curled position vs. tube restraint. Whole body CT was performed on ten clinically healthy ball pythons, first in curled and then in straight positions restrained in a tube. Curved multiplanar reformatted (MPR) lung images from curled position scans were compared with standard MPR lung images from straight position scans. Lung attenuation and thickness were measured at three locations for each scan. Time for positioning and scanning was 12 ± 5 min shorter for curled snakes compared to tube restraint. Lung parenchyma thickness and attenuation declined from cranial to caudal on both straight and curled position images. Mean lung parenchyma thickness was greater in curled images at locations 1 (P = 0.048) and 3 (P = 0.044). Mean lung parenchyma thickness decreased between location 1 and 2 by 86-87% (straight: curled) and between location 1 and 3 by 51-50% (straight: curled). Mean lung attenuation at location 1 was significantly greater on curled position images than tube restraint images (P = 0.043). Findings indicated that CT evaluation of the lungs is feasible for ball pythons positioned in curled recumbency if curved MPR is available. However, lung parenchyma thickness and attenuation in some locations may vary from those acquired using tube restraint. © 2014 American College of Veterinary Radiology.

  4. Development of hemipenes in the ball python snake Python regius.

    Science.gov (United States)

    Leal, Francisca; Cohn, Martin J

    2015-01-01

    Within amniotes, external copulatory organs have undergone extensive morphological diversification. One of the most extreme examples is squamate (lizards and snakes) hemipenes, which are paired copulatory organs that extend from the lateral margins of the cloaca. Here, we describe the development of hemipenes in a basal snake, the ball python (Python regius). Snake hemipenes arise as a pair of lateral swellings on either side of the caudal part of the cloaca, and these paired outgrowths persist to form the left and right hemipenes. In non-squamate amniotes, external genitalia form from paired swellings that arise on the anterior side of the cloaca, which then fuse medially to form a single genital tubercle, the anlagen of the penis or clitoris. Whereas in non-squamate amniotes, Sonic hedgehog (Shh)-expressing cells of the cloacal endoderm form the urethral or sulcus epithelium and are required for phallus outgrowth, the hemipenes of squamates lack an endodermal contribution, and the sulcus does not express Shh. Thus, snake hemipenes differ from the genital tubercles of non-squamate amniotes both in their embryonic origins and in at least part of patterning mechanisms, which raises the possibility that hemipenes may not be direct homologs of the unpaired amniote penis. Nonetheless, we find that some developmental genes show similar expression patterns in snake hemipenes buds and non-squamate genital tubercles, suggesting that homologous developmental mechanisms are involved in aspects of external genital development across amniotes, even when these structures may have different developmental origins and may have arisen independently during evolution.

  5. Hemodynamic consequences of cardiac malformations in two juvenile ball pythons (Python regius).

    Science.gov (United States)

    Jensen, Bjarke; Wang, Tobias

    2009-12-01

    Two cases of bifid ventricles and cardiac malformations in juvenile ball python (Python regius) were investigated by blood pressure measurements and macro- and microscopic sectioning. A study of a normal ball python was included for reference. In both cases, all cardiac chambers were enlarged and abnormally shaped. Internal assessment of the ventricles revealed a pronounced defect of the muscular ridge, which normally is responsible for separating the systemic and pulmonary circuits. Consistent with the small muscular ridge, systolic pressures were identical in the pulmonary and systemic arteries, but, the snakes, nevertheless, lived to reach body weights severalfold of their hatchling weight.

  6. Size, but not experience, affects the ontogeny of constriction performance in ball pythons (Python regius).

    Science.gov (United States)

    Penning, David A; Dartez, Schuyler F

    2016-03-01

    Constriction is a prey-immobilization technique used by many snakes and is hypothesized to have been important to the evolution and diversification of snakes. However, very few studies have examined the factors that affect constriction performance. We investigated constriction performance in ball pythons (Python regius) by evaluating how peak constriction pressure is affected by snake size, sex, and experience. In one experiment, we tested the ontogenetic scaling of constriction performance and found that snake diameter was the only significant factor determining peak constriction pressure. The number of loops applied in a coil and its interaction with snake diameter did not significantly affect constriction performance. Constriction performance in ball pythons scaled differently than in other snakes that have been studied, and medium to large ball pythons are capable of exerting significantly higher pressures than those shown to cause circulatory arrest in prey. In a second experiment, we tested the effects of experience on constriction performance in hatchling ball pythons over 10 feeding events. By allowing snakes in one test group to gain constriction experience, and manually feeding snakes under sedation in another test group, we showed that experience did not affect constriction performance. During their final (10th) feedings, all pythons constricted similarly and with sufficiently high pressures to kill prey rapidly. At the end of the 10 feeding trials, snakes that were allowed to constrict were significantly smaller than their non-constricting counterparts. © 2016 Wiley Periodicals, Inc.

  7. Saccular lung cannulation in a ball python (Python regius) to treat a tracheal obstruction.

    Science.gov (United States)

    Myers, Debbie A; Wellehan, James F X; Isaza, Ramiro

    2009-03-01

    An adult male ball python (Python regius) presented in a state of severe dyspnea characterized by open-mouth breathing and vertical positioning of the head and neck. The animal had copious discharge in the tracheal lumen acting as an obstruction. A tube was placed through the body wall into the caudal saccular aspect of the lung to allow the animal to breathe while treatment was initiated. The ball python's dyspnea immediately improved. Diagnostics confirmed a bacterial respiratory infection with predominantly Providencia rettgeri. The saccular lung (air sac) tube was removed after 13 days. Pulmonary endoscopy before closure showed minimal damage with a small amount of hemorrhage in the surrounding muscle tissue. Respiratory disease is a common occurrence in captive snakes and can be associated with significant morbidity and mortality. Saccular lung cannulation is a relatively simple procedure that can alleviate tracheal narrowing or obstruction, similar to air sac cannulation in birds.

  8. Subspectacular nematodiasis caused by a novel Serpentirhabdias species in ball pythons (Python regius).

    Science.gov (United States)

    Hausmann, J C; Mans, C; Dreyfus, J; Reavill, D R; Lucio-Forster, A; Bowman, D D

    2015-01-01

    Subspectacular nematodiasis was diagnosed in three captive-bred juvenile ball pythons (Python regius) from two unrelated facilities within a 6-month period. The snakes were presented with similar lesions, including swelling of facial, periocular and oral tissues. Bilaterally, the subspectacular spaces were distended and filled with an opaque fluid, which contained nematodes and eggs. Histopathology showed nematodes throughout the periocular tissue, subspectacular space and subcutaneous tissue of the head. The nematodes from both facilities were morphologically indistinguishable and most closely resembled Serpentirhabdias species. Morphological characterization and genetic sequencing indicate this is a previously undescribed rhabdiasid nematode. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Ball python nidovirus: a candidate etiologic agent for severe respiratory disease in Python regius.

    Science.gov (United States)

    Stenglein, Mark D; Jacobson, Elliott R; Wozniak, Edward J; Wellehan, James F X; Kincaid, Anne; Gordon, Marcus; Porter, Brian F; Baumgartner, Wes; Stahl, Scott; Kelley, Karen; Towner, Jonathan S; DeRisi, Joseph L

    2014-09-09

    A severe, sometimes fatal respiratory disease has been observed in captive ball pythons (Python regius) since the late 1990s. In order to better understand this disease and its etiology, we collected case and control samples and performed pathological and diagnostic analyses. Electron micrographs revealed filamentous virus-like particles in lung epithelial cells of sick animals. Diagnostic testing for known pathogens did not identify an etiologic agent, so unbiased metagenomic sequencing was performed. Abundant nidovirus-like sequences were identified in cases and were used to assemble the genome of a previously unknown virus in the order Nidovirales. The nidoviruses, which were not previously known to infect nonavian reptiles, are a diverse order that includes important human and veterinary pathogens. The presence of the viral RNA was confirmed in all diseased animals (n = 8) but was not detected in healthy pythons or other snakes (n = 57). Viral RNA levels were generally highest in the lung and other respiratory tract tissues. The 33.5-kb viral genome is the largest RNA genome yet described and shares canonical characteristics with other nidovirus genomes, although several features distinguish this from related viruses. This virus, which we named ball python nidovirus (BPNV), will likely establish a new genus in Torovirinae subfamily. The identification of a novel nidovirus in reptiles contributes to our understanding of the biology and evolution of related viruses, and its association with lung disease in pythons is a promising step toward elucidating an etiology for this long-standing veterinary disease. Ball pythons are popular pets because of their diverse coloration, generally nonaggressive behavior, and relatively small size. Since the 1990s, veterinarians have been aware of an infectious respiratory disease of unknown cause in ball pythons that can be fatal. We used unbiased shotgun sequencing to discover a novel virus in the order Nidovirales that was

  10. Learning Python

    National Research Council Canada - National Science Library

    Lutz, Mark; Ascher, David

    1999-01-01

    ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv Part I. Getting Started 1. A Python Q&A Session Why Do People Use Python? Is Python a Scripting Language? Okay, But What's the Downside? Who Uses Python Today...

  11. Learning Python

    National Research Council Canada - National Science Library

    Lutz, Mark; Ascher, David

    2004-01-01

    ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv Part I. Getting Started 1. A Python Q&A Session Why Do People Use Python? Is Python a Scripting Language? Okay, But What's the Downside? Who Uses Python Today...

  12. Trypanosoma cf. varani in an imported ball python (Python reginus) from Ghana.

    Science.gov (United States)

    Sato, Hiroshi; Takano, Ai; Kawabata, Hiroki; Une, Yumi; Watanabe, Haruo; Mukhtar, Maowia M

    2009-08-01

    Peripheral blood from a ball python (Python reginus) imported from Ghana was cultured in Barbour-Stoenner-Kelly (BSK) medium for Borrelia spp. isolation, resulting in the prominent appearance of free, and clusters of, trypanosomes in a variety of morphological forms. The molecular phylogenetic characterization of these cultured trypanosomes, using the small subunit rDNA, indicated that this python was infected with a species closely related to Trypanosoma varani Wenyon, 1908, originally described in the Nile monitor lizard (Varanus niloticus) from Sudan. Furthermore, nucleotide sequences of glycosomal glyceraldehyde-3-phosphate dehydrogenase gene of both isolates showed few differences. Giemsa-stained blood smears, prepared from the infected python 8 mo after the initial observation of trypanosomes in hemoculture, contained trypomastigotes with a broad body and a short, free flagellum; these most closely resembled the original description of T. varani, or T. voltariae Macfie, 1919 recorded in a black-necked spitting cobra (Naja nigricollis) from Ghana. It is highly possible that lizards and snakes could naturally share an identical trypanosome species. Alternatively, lizards and snakes in the same region might have closely related, but distinct, Trypanosoma species as a result of sympatric speciation. From multiple viewpoints, including molecular phylogenetic analyses, reappraisal of trypanosome species from a wide range of reptiles in Africa is needed to clarify the relationship of recorded species, or to unmask unrecorded species.

  13. Effect of laser treatment on first-intention incisional wound healing in ball pythons (Python regius).

    Science.gov (United States)

    Cole, Grayson L; Lux, Cassie N; Schumacher, Juergen P; Seibert, Rachel L; Sadler, Ryan A; Henderson, Andrea L; Odoi, Agricola; Newkirk, Kim M

    2015-10-01

    To evaluate effects of laser treatment on incisional wound healing in ball pythons (Python regius). 6 healthy adult ball pythons. Snakes were sedated, a skin biopsy specimen was collected for histologic examination, and eight 2-cm skin incisions were made in each snake; each incision was closed with staples (day 0). Gross evaluation of all incision sites was performed daily for 30 days, and a wound score was assigned. Four incisions of each snake were treated (5 J/cm(2) and a wavelength of 980 nm on a continuous wave sequence) by use of a class 4 laser once daily for 7 consecutive days; the other 4 incisions were not treated. Two excisional skin biopsy specimens (1 control and 1 treatment) were collected from each snake on days 2, 7, 14, and 30 and evaluated microscopically. Scores were assigned for total inflammation, degree of fibrosis, and collagen maturity. Generalized linear models were used to investigate the effect of treatment on each variable. Wound scores for laser-treated incisions were significantly better than scores for control incisions on day 2 but not at other time points. There were no significant differences in necrosis, fibroplasia, inflammation, granuloma formation, or bacterial contamination between control and treatment groups. Collagen maturity was significantly better for the laser-treated incisions on day 14. Laser treatment resulted in a significant increase in collagen maturity at day 14 but did not otherwise significantly improve healing of skin incisions.

  14. Morphological respiratory diffusion capacity of the lungs of ball pythons (Python regius).

    Science.gov (United States)

    Starck, J Matthias; Aupperle, Heike; Kiefer, Ingmar; Weimer, Isabel; Krautwald-Junghanns, Maria-Elisabeth; Pees, Michael

    2012-08-01

    This study aims at a functional and morphological characterization of the lung of a boid snake. In particular, we were interested to see if the python's lungs are designed with excess capacity as compared to resting and working oxygen demands. Therefore, the morphological respiratory diffusion capacity of ball pythons (Python regius) was examined following a stereological, hierarchically nested approach. The volume of the respiratory exchange tissue was determined using computed tomography. Tissue compartments were quantified using stereological methods on light microscopic images. The tissue diffusion barrier for oxygen transport was characterized and measured using transmission electron micrographs. We found a significant negative correlation between body mass and the volume of respiratory tissue; the lungs of larger snakes had relatively less respiratory tissue. Therefore, mass-specific respiratory tissue was calculated to exclude effects of body mass. The volume of the lung that contains parenchyma was 11.9±5.0mm(3)g(-1). The volume fraction, i.e., the actual pulmonary exchange tissue per lung parenchyma, was 63.22±7.3%; the total respiratory surface was, on average, 0.214±0.129m(2); it was significantly negatively correlated to body mass, with larger snakes having proportionally smaller respiratory surfaces. For the air-blood barrier, a harmonic mean of 0.78±0.05μm was found, with the epithelial layer representing the thickest part of the barrier. Based on these findings, a median diffusion capacity of the tissue barrier ( [Formula: see text] ) of 0.69±0.38ml O(2)min(-1)mmHg(-1) was calculated. Based on published values for blood oxygen concentration, a total oxygen uptake capacity of 61.16mlO(2)min(-1)kg(-1) can be assumed. This value exceeds the maximum demand for oxygen in ball pythons by a factor of 12. We conclude that healthy individuals of P. regius possess a considerable spare capacity for tissue oxygen exchange. Copyright © 2012 Elsevier Gmb

  15. Learning Python

    National Research Council Canada - National Science Library

    Lutz, Mark; Ascher, David

    2004-01-01

    ...? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 3 5 6 7 8 11 14 2. How Python Runs Programs Introducing the Python Interpreter Program Execution Execution Model Variations...

  16. Learning Python

    National Research Council Canada - National Science Library

    Lutz, Mark; Ascher, David

    1999-01-01

    ...? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 3 5 6 7 8 11 14 2. How Python Runs Programs Introducing the Python Interpreter Program Execution Execution Model Variations...

  17. The spectacle of the ball python (Python regius): a morphological description.

    Science.gov (United States)

    Da Silva, Mari-Ann O; Heegaard, Steffen; Wang, Tobias; Nyengaard, Jens R; Bertelsen, Mads F

    2014-05-01

    A detailed morphological description of the spectacle of the ball python (Python regius) is provided. The eyes of 21 snakes were examined by light microscopy and/or transmission electron microscopy. Additionally, eyes of nine live snakes were examined using optical coherence tomography (OCT) and Scheimpflug scanning (Pentacam). The spectacle consists of three layers: outer epithelium, stroma and inner epithelium. The outer epithelium is made up of flat basal cells overlaid by keratin, the stroma consists of organized layers of collagen fibrils with interweaving nerve fibers and blood vessels, and the inner epithelium holds squamous cells containing vesicles and microvilli. At the rim of the spectacle, there is a transition zone, where the spectacle merges with the epidermis and dermis of the periocular scales. This zone is characterized by a greater height of the basal cells of the outer epithelium and a less orderly organization of the stroma compared with the spectacle proper. The thickness of the spectacle was uniform throughout. It averaged 96 ± 10 µm in histological specimens and 108 ± 13 µm using OCT. The subspectacular space was extremely narrow in the live snakes; however, the space was visible at the periphery of the spectacle with OCT. Copyright © 2013 Wiley Periodicals, Inc.

  18. Tongue worm (Pentastomida) infection in ball pythons (Python regius) – a case report

    Science.gov (United States)

    Gałęcki, Remigiusz; Sokół, Rajmund; Dudek, Agnieszka

    Tongue worms (Pentastomida) are endoparasites causing pentastomiasis, an invasive disease representing a threat to exotic animals and humans. Animals acquire infection via the alimentary tract. In reptiles, the parasite is present in the lungs, resulting in symptoms from the respiratory system. Pentastomiasis may be asymptomatic, but nonspecific symptoms may occur at high parasite concentrations. Due to the harmful effects of many antiparasitic substances, tongue worm invasion in reptiles remains not fully treatable. Although pentasomiasis is rarely diagnosed in Poland, pentastomids were diagnosed in two ball pythons, who were patients of the “Poliklinika Weterynaryjna” veterinary clinic. They demonstrated problems with the respiratory system and a significant deterioration of health. Fenbendazole at a dose of 100 mg/kg b.w., repeated after 7 days was shown to be effective.

  19. Clinical and histologic effects of intracardiac administration of propofol for induction of anesthesia in ball pythons (Python regius).

    Science.gov (United States)

    McFadden, Michael S; Bennett, R Avery; Reavill, Drury R; Ragetly, Guillaume R; Clark-Price, Stuart C

    2011-09-15

    To assess the clinical differences between induction of anesthesia in ball pythons with intracardiac administration of propofol and induction with isoflurane in oxygen and to assess the histologic findings over time in hearts following intracardiac administration of propofol. Prospective randomized study. 30 hatchling ball pythons (Python regius). Anesthesia was induced with intracardiac administration of propofol (10 mg/kg [4.5 mg/lb]) in 18 ball pythons and with 5% isoflurane in oxygen in 12 ball pythons. Induction time, time of anesthesia, and recovery time were recorded. Hearts from snakes receiving intracardiac administration of propofol were evaluated histologically 3, 7, 14, 30, and 60 days following propofol administration. Induction time with intracardiac administration of propofol was significantly shorter than induction time with 5% isoflurane in oxygen. No significant differences were found in total anesthesia time. Recovery following intracardiac administration of propofol was significantly longer than recovery following induction of anesthesia with isoflurane in oxygen. Heart tissue evaluated histologically at 3, 7, and 14 days following intracardiac administration of propofol had mild inflammatory changes, and no histopathologic lesions were seen 30 and 60 days following propofol administration. Intracardiac injection of propofol in snakes is safe and provides a rapid induction of anesthesia but leads to prolonged recovery, compared with that following induction with isoflurane. Histopathologic lesions in heart tissues following intracardiac injection of propofol were mild and resolved after 14 days.

  20. Development of a technique for contrast radiographic examination of the gastrointestinal tract in ball pythons (Python regius).

    Science.gov (United States)

    Banzato, Tommaso; Russo, Elisa; Finotti, Luca; Zotti, Alessandro

    2012-07-01

    To develop a technique for radiographic evaluation of the gastrointestinal tract in ball pythons (Python regius). 10 ball python cadavers (5 males and 5 females) and 18 healthy adult ball pythons (10 males and 8 females). Live snakes were allocated to 3 groups (A, B, and C). A dose (25 mL/kg) of barium sulfate suspension at 3 concentrations (25%, 35%, and 45% [wt/vol]) was administered through an esophageal probe to snakes in groups A, B, and C, respectively. Each evaluation ended when all the contrast medium had reached the large intestine. Transit times through the esophagus, stomach, and small intestine were recorded. Imaging quality was evaluated by 3 investigators who assigned a grading score on the basis of predetermined criteria. Statistical analysis was conducted to evaluate differences in quality among the study groups. The esophagus and stomach had a consistent distribution pattern of contrast medium, whereas 3 distribution patterns of contrast medium were identified in the small intestine, regardless of barium concentration. Significant differences in imaging quality were detected among the 3 groups. Radiographic procedures were tolerated well by all snakes. The 35% concentration of contrast medium yielded the best imaging quality. Use of contrast medium for evaluation of the cranial portion of the gastrointestinal tract could be a reliable technique for the diagnosis of gastrointestinal diseases in ball pythons. However, results of this study may not translate to other snake species because of variables identified in this group of snakes.

  1. The effects of UV light on calcium metabolism in ball pythons (Python regius).

    Science.gov (United States)

    Hedley, J; Eatwell, K

    2013-10-12

    Despite the popularity of keeping snakes in captivity, there has been limited investigation into the effects of UV radiation on vitamin D levels in snakes. The aim of this study was to investigate the effects of UV-b radiation on plasma 25-hydroxyvitamin D3 levels and ionised calcium concentrations in ball pythons (Python regius). Blood samples were taken from 14 ball pythons, which had never been exposed to UV-b light, to obtain baseline 25-hydroxyvitamin D3 levels and ionised calcium concentrations. Blood samples were then taken again from the same snakes 70 days later after one group (Group 1, n=6 females) were exposed to UV-b radiation daily, and the other group (Group 2, n=5 males and 3 females) were exposed to no UV-b radiation. Mean±sd 25-hydroxyvitamin D3 levels on day 0 in Group 1 were 197±35 nmol/l, and on day 70 were 203.5±13.8 nmol/l. Mean±sd 25-hydroxyvitamin D3 levels in Group 2 on day 0 were 77.7±41.5 nmol/l, and on day 70 were 83.0±41.9 nmol/l. Mean±sd ionised calcium levels at day 0 were 1.84±0.05 mmol/l for Group 1, and on day 70 were 1.78±0.07 mmol/l. Mean±sd ionised calcium levels at day 0 were 1.79±0.07 mmol/l for Group 2, and on day 70 were 1.81±0.05 mmol/l. No association was demonstrated between exposure to UV-b radiation and plasma 25-hydroxyvitamin D3 and ionised calcium concentrations. These results may provide baseline parameters for future studies in this and other snake species to determine ability to utilise UV-b light for vitamin D production.

  2. The influence of mechanical ventilation on physiological parameters in ball pythons (Python regius).

    Science.gov (United States)

    Jakobsen, Sashia L; Williams, Catherine J A; Wang, Tobias; Bertelsen, Mads F

    2017-05-01

    Mechanical ventilation is widely recommended for reptiles during anesthesia, and while it is well-known that their low ectothermic metabolism requires much lower ventilation than in mammals, very little is known about the influence of ventilation protocol on the recovery from anesthesia. Here, 15 ball pythons (Python regius) were induced and maintained with isoflurane for 60min at one of three ventilation protocols (30, 125, or 250mlmin -1 kg -1 body mass) while an arterial catheter was inserted, and ventilation was then continued on 100% oxygen at the specified rate until voluntary extubation. Mean arterial blood pressure and heart rate (HR) were measured, and arterial blood samples collected at 60, 80, 180min and 12 and 24h after intubation. In all three groups, there was evidence of a metabolic acidosis, and snakes maintained at 30mlmin -1 kg -1 experienced an additional respiratory acidosis, while the two other ventilation protocols resulted in normal or low arterial PCO 2 . In general, normal acid-base status was restored within 12h in all three protocols. HR increased by 143±64% during anesthesia with high mechanical ventilation (250mlmin -1 kg -1 ) in comparison with recovered values. Recovery times after mechanical ventilation at 30, 125, or 250mlmin -1 kg -1 were 289±70, 126±16, and 68±7min, respectively. Mild overventilation may result in a faster recovery, and the associated lowering of arterial PCO 2 normalised arterial pH in the face of metabolic acidosis. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Identification of a novel nidovirus in an outbreak of fatal respiratory disease in ball pythons (Python regius).

    Science.gov (United States)

    Uccellini, Lorenzo; Ossiboff, Robert J; de Matos, Ricardo E C; Morrisey, James K; Petrosov, Alexandra; Navarrete-Macias, Isamara; Jain, Komal; Hicks, Allison L; Buckles, Elizabeth L; Tokarz, Rafal; McAloose, Denise; Lipkin, Walter Ian

    2014-08-08

    Respiratory infections are important causes of morbidity and mortality in reptiles; however, the causative agents are only infrequently identified. Pneumonia, tracheitis and esophagitis were reported in a collection of ball pythons (Python regius). Eight of 12 snakes had evidence of bacterial pneumonia. High-throughput sequencing of total extracted nucleic acids from lung, esophagus and spleen revealed a novel nidovirus. PCR indicated the presence of viral RNA in lung, trachea, esophagus, liver, and spleen. In situ hybridization confirmed the presence of intracellular, intracytoplasmic viral nucleic acids in the lungs of infected snakes. Phylogenetic analysis based on a 1,136 amino acid segment of the polyprotein suggests that this virus may represent a new species in the subfamily Torovirinae. This report of a novel nidovirus in ball pythons may provide insight into the pathogenesis of respiratory disease in this species and enhances our knowledge of the diversity of nidoviruses.

  4. Pharmacokinetics of a long-acting ceftiofur formulation (ceftiofur crystalline free acid) in the ball python (Python regius).

    Science.gov (United States)

    Adkesson, Michael J; Fernandez-Varon, Emilio; Cox, Sherry; Martín-Jiménez, Tomás

    2011-09-01

    The objective of this study was to determine the pharmacokinetics of a long-acting formulation of ceftiofur crystalline-free acid (CCFA) following intramuscular injection in ball pythons (Python regius). Six adult ball pythons received an injection of CCFA (15 mg/kg) in the epaxial muscles. Blood samples were collected by cardiocentesis immediately prior to and at 0.5, 1, 2, 4, 8, 12, 18, 24, 48, 72, 96, 144, 192, 240, 288, 384, 480, 576, 720, and 864 hr after CCFA administration. Plasma ceftiofur concentrations were determined by high-performance liquid chromatography. A noncompartmental pharmacokinetic analysis was applied to the data. Maximum plasma concentration (Cmax) was 7.096 +/- 1.95 microg/ml and occurred at (Tmax) 2.17 +/- 0.98 hr. The area under the curve (0 to infinity) for ceftiofur was 74.59 +/- 13.05 microg x h/ml and the elimination half-life associated with the terminal slope of the concentration-time curve was 64.31 +/- 14.2 hr. Mean residence time (0 to infinity) was 46.85 +/- 13.53 hr. CCFA at 15 mg/kg was well tolerated in all the pythons. Minimum inhibitory concentration (MIC) data for bacterial isolates from snakes are not well established. For MIC values of python. For MICs > or =0.5 microg/ml, more frequent dosing or a higher dosage may be required.

  5. Photodermatitis and photokeratoconjunctivitis in a ball python (Python regius) and a blue-tongue skink (Tiliqua spp.).

    Science.gov (United States)

    Gardiner, David W; Baines, Frances M; Pandher, Karamjeet

    2009-12-01

    A male ball python (Python regius) and a female blue tongue skink (Tiliqua spp.) of unknown age were evaluated for anorexia, lethargy, excessive shedding, corneal opacity (python), and weight loss (skink) of approximately three weeks' duration. These animals represented the worst affected animals from a private herpetarium where many animals exhibited similar signs. At necropsy, the python had bilateral corneal opacity and scattered moderate dysecdysis. The skink had mild dysecdysis, poor body condition, moderate intestinal nematodiasis, and mild liver atrophy. Microscopic evaluation revealed epidermal erosion and ulceration, with severe epidermal basal cell degeneration and necrosis, and superficial dermatitis (python and skink). Severe bilateral ulcerative keratoconjunctivitis with bacterial colonization was noted in the ball python. Microscopic findings within the skin and eyes were suggestive of ultraviolet (UV) radiation damage or of photodermatitis and photokeratoconjunctivitis. Removal of the recently installed new lamps from the terrariums of the surviving reptiles resulted in resolution of clinical signs. Evaluation of a sample lamp of the type associated with these cases revealed an extremely high UV output, including very-short-wavelength UVB, neither found in natural sunlight nor emitted by several other UVB lamps unassociated with photokeratoconjunctivitis. Exposure to high-intensity and/or inappropriate wavelengths of UV radiation may be associated with significant morbidity, and even mortality, in reptiles. Veterinarians who are presented with reptiles with ocular and/or cutaneous disease of unapparent cause should fully evaluate the specifics of the vivarium light sources. Further research is needed to determine the characteristics of appropriate and of toxic UV light for reptiles kept in captivity.

  6. Pro Python

    CERN Document Server

    Alchin, Marty

    2010-01-01

    You've learned the basics of Python, but how do you take your skills to the next stage? Even if you know enough to be productive, there are a number of features that can take you to the next level in Python. Pro Python explores concepts and features normally left to experimentation, allowing you to be even more productive and creative. In addition to pure code concerns, Pro Python will develop your programming techniques and approaches, which will help make you a better Python programmer. Not only will this book help your code, it will also help you understand and interact with the many establ

  7. Learning Python

    CERN Document Server

    Lutz, Mark

    2008-01-01

    With this hands-on book, you can master the fundamentals of the core Python language quickly and efficiently, whether you're new to programming or just new to Python. Each chapter is a self-contained lesson that helps you thoroughly understand a key component of Python. Each chapter also contains Brain Builder, a unique section with practical exercises and review quizzes that let you practice new skills and test your understanding as you go

  8. Learning Python

    CERN Document Server

    Lutz, Mark

    2009-01-01

    Google and YouTube use Python because it's highly adaptable, easy to maintain, and allows for rapid development. If you want to write high-quality, efficient code that's easily integrated with other languages and tools, this hands-on book will help you be productive with Python quickly -- whether you're new to programming or just new to Python. It's an easy-to-follow self-paced tutorial, based on author and Python expert Mark Lutz's popular training course. Each chapter contains a stand-alone lesson on a key component of the language, and includes a unique Test Your Knowledge section with p

  9. Programming Python

    CERN Document Server

    Lutz, Mark

    2011-01-01

    If you've mastered Python's fundamentals, you're ready to start using it to get real work done. Programming Python will show you how, with in-depth tutorials on the language's primary application domains: system administration, GUIs, and the Web. You'll also explore how Python is used in databases, networking, front-end scripting layers, text processing, and more. This book focuses on commonly used tools and libraries to give you a comprehensive understanding of Python's many roles in practical, real-world programming. You'll learn language syntax and programming techniques in a clear and co

  10. Evaluation of the histologic reactions to commonly used suture materials in the skin and musculature of ball pythons (Python regius).

    Science.gov (United States)

    McFadden, Michael S; Bennett, R Avery; Kinsel, Michael J; Mitchell, Mark A

    2011-10-01

    To evaluate histologic reactions to 8 suture materials and cyanoacrylate tissue adhesive (CTA) in the musculature and skin of ball pythons. 30 hatchling ball pythons. In each snake, ten 1-cm skin incisions were made (day 0). At 8 sites, a suture of 1 of 8 materials was placed in the epaxial musculature, and the incision was closed with the same material. One incision was closed by use of CTA. No suture material was placed in the tenth incision, which was allowed to heal by second intention (negative control). Snakes (n = 5/group) were euthanized for harvest of treatment-site tissues at days 3, 7, 14, 30, 60, and 90. Skin and muscle sections were examined microscopically and assigned a subjective score (0 to 4) for each of the following: overall severity of inflammation, fibrosis, number of macrophages, number of granulocytes, number of perivascular lymphocytes, and degree of suture fragmentation. Subjective score analysis revealed that CTA did not cause a significant inflammatory response, compared with the negative control. All suture materials caused significantly more inflammation over all time points; for all suture materials, inflammatory response scores were significantly higher than values for the negative control 90 days after implantation. No sutures were completely absorbed by the end of the study period, and several sutures appeared to be in the process of extrusion. In snakes, CTA can be used to close small superficial incisions or lacerations with minimal inflammatory response, and sutures may undergo extrusion from tissues prior to complete absorption.

  11. Python tutorial

    NARCIS (Netherlands)

    G. van Rossum (Guido)

    1995-01-01

    textabstractPython is a simple, yet powerful programming language that bridges the gap between C and shell programming, and is thus ideally suited for ``throw-away programming'' and rapid prototyping. Its syntax is put together from constructs borrowed from a variety of other languages; most

  12. Effects of preoperative administration of butorphanol or meloxicam on physiologic responses to surgery in ball pythons.

    Science.gov (United States)

    Olesen, Mette G; Bertelsen, Mads F; Perry, Steve F; Wang, Tobias

    2008-12-15

    To characterize physiologic responses of ball pythons (Python regius) following a minor surgical procedure and investigate the effects of 2 commonly used analgesics on this response. 15 healthy ball pythons. Snakes were randomly assigned to receive 1 of 3 treatments: meloxicam (0.3 mg/kg [0.14 mg/lb]; n = 5), butorphanol (5 mg/kg [2.3 mg/lb]; 5), or saline (0.9% NaCl) solution (5) before catheterization of the vertebral artery. Plasma concentrations of catecholamines and cortisol, blood pressure, heart rate, and blood gas values were measured at various times for 72.5 hours after catheterization. The 72.5-hour point was defined as baseline. Heart rate of ball pythons increased significantly during the first hour following surgery. Mean plasma epinephrine concentration increased slightly at 2.5 hours after surgery, whereas mean plasma cortisol concentration increased beginning at 1.5 hours, reaching a maximum at 6.5 hours. Mean blood pressure increased within the first hour but returned to the baseline value at 2.5 hours after surgery. After 24.5 hours, blood pressure, heart rate, and plasma hormone concentrations remained stable at baseline values. There were no significant differences in values for physiologic variables between snakes that received saline solution and those that received meloxicam or butorphanol. Measurement of physiologic variables provides a means of assessing postoperative pain in snakes. Meloxicam and butorphanol at the dosages used did not decrease the physiologic stress response and did not appear to provide analgesic effects in ball pythons.

  13. Python essential reference

    CERN Document Server

    Beazley, David M

    2009-01-01

    Python Essential Reference is the definitive reference guide to the Python programming language — the one authoritative handbook that reliably untangles and explains both the core Python language and the most essential parts of the Python library. Designed for the professional programmer, the book is concise, to the point, and highly accessible. It also includes detailed information on the Python library and many advanced subjects that is not available in either the official Python documentation or any other single reference source. Thoroughly updated to reflect the significant new programming language features and library modules that have been introduced in Python 2.6 and Python 3, the fourth edition of Python Essential Reference is the definitive guide for programmers who need to modernize existing Python code or who are planning an eventual migration to Python 3. Programmers starting a new Python project will find detailed coverage of contemporary Python programming idioms.

  14. Learning Python network programming

    CERN Document Server

    Sarker, M O Faruque

    2015-01-01

    If you're a Python developer or a system administrator with Python experience and you're looking to take your first steps in network programming, then this book is for you. Basic knowledge of Python is assumed.

  15. Mastering Python design patterns

    CERN Document Server

    Kasampalis, Sakis

    2015-01-01

    This book is for Python programmers with an intermediate background and an interest in design patterns implemented in idiomatic Python. Programmers of other languages who are interested in Python can also benefit from this book, but it would be better if they first read some introductory materials that explain how things are done in Python.

  16. X Python reference manual

    NARCIS (Netherlands)

    K.S. Mullender (Sjoerd)

    1995-01-01

    textabstractThis document describes the built-in types, exceptions, and functions of the X windows extension to Python. It assumes basic knowledge about the Python language and access to the X windows documentation. For an informal introduction to the language, see the Python Tutorial. The Python

  17. Evaluation of the role of the cyclooxygenase signaling pathway during inflammation in skin and muscle tissues of ball pythons (Python regius).

    Science.gov (United States)

    Sadler, Ryan A; Schumacher, Juergen P; Rathore, Kusum; Newkirk, Kim M; Cole, Grayson; Seibert, Rachel; Cekanova, Maria

    2016-05-01

    OBJECTIVE To determine degrees of production of cyclooxygenase (COX)-1 and -2 and other mediators of inflammation in noninflamed and inflamed skin and muscle tissues in ball pythons (Python regius). ANIMALS 6 healthy adult male ball pythons. PROCEDURES Biopsy specimens of noninflamed skin and muscle tissue were collected from anesthetized snakes on day 0. A 2-cm skin and muscle incision was then made 5 cm distal to the biopsy sites with a CO2 laser to induce inflammation. On day 7, biopsy specimens of skin and muscle tissues were collected from the incision sites. Inflamed and noninflamed tissue specimens were evaluated for production of COX-1, COX-2, phosphorylated protein kinase B (AKT), total AKT, nuclear factor κ-light-chain-enhancer of activated B cells, phosphorylated extracellular receptor kinases (ERKs) 1 and 2, and total ERK proteins by western blot analysis. Histologic evaluation was performed on H&E-stained tissue sections. RESULTS All biopsy specimens of inflamed skin and muscle tissues had higher histologic inflammation scores than did specimens of noninflamed tissue. Inflamed skin specimens had significantly greater production of COX-1 and phosphorylated ERK than did noninflamed skin specimens. Inflamed muscle specimens had significantly greater production of phosphorylated ERK and phosphorylated AKT, significantly lower production of COX-1, and no difference in production of COX-2, compared with production in noninflamed muscle specimens. CONCLUSIONS AND CLINICAL RELEVANCE Production of COX-1, but not COX-2, was significantly greater in inflamed versus noninflamed skin specimens from ball pythons. Additional research into the reptilian COX signaling pathway is warranted.

  18. Learning Python testing

    CERN Document Server

    Arbuckle, Daniel

    2014-01-01

    This book is ideal if you want to learn about the testing disciplines and automated testing tools from a hands-on, conversational guide. You should already know Python and be comfortable with Python 3.

  19. Functional Python programming

    CERN Document Server

    Lott, Steven

    2015-01-01

    This book is for developers who want to use Python to write programs that lean heavily on functional programming design patterns. You should be comfortable with Python programming, but no knowledge of functional programming paradigms is needed.

  20. Head First Python

    CERN Document Server

    Barry, Paul

    2010-01-01

    Ever wished you could learn Python from a book? Head First Python is a complete learning experience for Python that helps you learn the language through a unique method that goes beyond syntax and how-to manuals, helping you understand how to be a great Python programmer. You'll quickly learn the language's fundamentals, then move onto persistence, exception handling, web development, SQLite, data wrangling, and Google App Engine. You'll also learn how to write mobile apps for Android, all thanks to the power that Python gives you. We think your time is too valuable to waste struggling with

  1. Comparison of first-intention healing of carbon dioxide laser, 4.0-MHz radiosurgery, and scalpel incisions in ball pythons (Python regius).

    Science.gov (United States)

    Hodshon, Rebecca T; Sura, Patricia A; Schumacher, Juergen P; Odoi, Agricola; Steeil, James C; Newkirk, Kim M

    2013-03-01

    To evaluate first-intention healing of CO(2) laser, 4.0-MHz radiowave radiosurgery (RWRS), and scalpel incisions in ball pythons (Python regius). 6 healthy adult ball pythons. A skin biopsy sample was collected, and 2-cm skin incisions (4/modality) were made in each snake under anesthesia and closed with surgical staples on day 0. Incision sites were grossly evaluated and scored daily. One skin biopsy sample per incision type per snake was obtained on days 2, 7, 14, and 30. Necrotic and fibroplastic tissue was measured in histologic sections; samples were assessed and scored for total inflammation, histologic response (based on the measurement of necrotic and fibroplastic tissues and total inflammation score), and other variables. Frequency distributions of gross and histologic variables associated with wound healing were calculated. Gross wound scores were significantly greater (indicating greater separation of wound edges) for laser incisions than for RWRS and scalpel incisions at all evaluated time points. Necrosis was significantly greater in laser and RWRS incisions than in scalpel incision sites on days 2 and 14 and days 2 and 7, respectively; fibroplasia was significantly greater in laser than in scalpel incision sites on day 30. Histologic response scores were significantly lower for scalpel than for other incision modalities on days 2, 14, and 30. In snakes, skin incisions made with a scalpel generally had less necrotic tissue than did CO(2) laser and RWRS incisions. Comparison of the 3 modalities on the basis of histologic response scores indicated that use of a scalpel was preferable, followed by RWRS and then laser.

  2. Python geospatial development essentials

    CERN Document Server

    Bahgat, Karim

    2015-01-01

    This book is ideal for Python programmers who are tasked with or wish to make a special-purpose GIS application. Analysts, political scientists, geographers, and GIS specialists seeking a creative platform to experiment with cutting-edge spatial analysis, but who are still only beginners in Python, will also find this book beneficial. Familiarity with Tkinter application development in Python is preferable but not mandatory.

  3. Python penetration testing essentials

    CERN Document Server

    Mohit

    2015-01-01

    If you are a Python programmer or a security researcher who has basic knowledge of Python programming and want to learn about penetration testing with the help of Python, this book is ideal for you. Even if you are new to the field of ethical hacking, this book can help you find the vulnerabilities in your system so that you are ready to tackle any kind of attack or intrusion.

  4. Learning Python design patterns

    CERN Document Server

    Zlobin, Gennadiy

    2013-01-01

    This book takes a tutorial-based and user-friendly approach to covering Python design patterns. Its concise presentation means that in a short space of time, you will get a good introduction to various design patterns.If you are an intermediate level Python user, this book is for you. Prior knowledge of Python programming is essential. Some knowledge of UML is also required to understand the UML diagrams which are used to describe some design patterns.

  5. Python pocket reference

    CERN Document Server

    Lutz, Mark

    2014-01-01

    Updated for both Python 3.4 and 2.7, this convenient pocket guide is the perfect on-the-job quick reference. You’ll find concise, need-to-know information on Python types and statements, special method names, built-in functions and exceptions, commonly used standard library modules, and other prominent Python tools. The handy index lets you pinpoint exactly what you need.

  6. Python data visualization cookbook

    CERN Document Server

    Milovanovic, Igor

    2013-01-01

    This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the co

  7. Adventures in Python

    CERN Document Server

    Richardson, Craig

    2015-01-01

    The complete beginner's guide to Python, for young people whowant to start today Adventures in Python is designed for 11-to 15-year oldswho want to teach themselves Python programming, but don't knowwhere to start. Even if you have no programming experience at all,this easy to follow format and clear, simple instruction will getyou up and running quickly. The book walks you through nineprojects that teach you the fundamentals of programming in general,and Python in particular, gradually building your skills until youhave the confidence and ability to tackle your own projects. Videoclips accom

  8. Python pocket reference

    CERN Document Server

    Lutz, Mark

    2010-01-01

    This is the book to reach for when you're coding on the fly and need an answer now. It's an easy-to-use reference to the core language, with descriptions of commonly used modules and toolkits, and a guide to recent changes, new features, and upgraded built-ins -- all updated to cover Python 3.X as well as version 2.6. You'll also quickly find exactly what you need with the handy index. Written by Mark Lutz -- widely recognized as the world's leading Python trainer -- Python Pocket Reference, Fourth Edition, is the perfect companion to O'Reilly's classic Python tutorials, also written by Mark

  9. Python data analysis

    CERN Document Server

    Idris, Ivan

    2014-01-01

    This book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.

  10. Python library reference

    NARCIS (Netherlands)

    G. van Rossum (Guido)

    1995-01-01

    textabstractPython is an extensible, interpreted, object-oriented programming language. It supports a wide range of applications, from simple text processing scripts to interactive WWW browsers. While the Python Reference Manual describes the exact syntax and semantics of the language, it does not

  11. Python requests essentials

    CERN Document Server

    Chandra, Rakesh Vidya

    2015-01-01

    If you are a Python administrator or developer interested in interacting with web APIs and have a passion for creating your own web applications, this is the book for you. Basic knowledge of Python programming, APIs, and web services will be an advantage.

  12. Want Drugs? Use Python

    OpenAIRE

    Nowotka, Michał; Papadatos, George; Davies, Mark; Dedman, Nathan; Hersey, Anne

    2016-01-01

    We describe how Python can be leveraged to streamline the curation, modelling and dissemination of drug discovery data as well as the development of innovative, freely available tools for the related scientific community. We look at various examples, such as chemistry toolkits, machine-learning applications and web frameworks and show how Python can glue it all together to create efficient data science pipelines.

  13. Scraping EDGAR with Python

    Science.gov (United States)

    Ashraf, Rasha

    2017-01-01

    This article presents Python codes that can be used to extract data from Securities and Exchange Commission (SEC) filings. The Python program web crawls to obtain URL paths for company filings of required reports, such as Form 10-K. The program then performs a textual analysis and counts the number of occurrences of words in the filing that…

  14. Python for Ecology

    Science.gov (United States)

    Python is a high-level scripting language that is becoming increasingly popular for scientific computing. This all-day workshop is designed to introduce the basics of Python programming to ecologists. Some scripting/programming experience is recommended (e.g. familiarity with R)....

  15. Python in a nutshell

    CERN Document Server

    Martelli, Alex; Holden, Steve

    2016-01-01

    Useful in many roles, from design and prototyping to testing, deployment, and maintenance, Python is consistently ranked among today’s most popular programming languages. The third edition of this practical book provides a quick reference to the language—including Python 3.5, 2.7, and highlights of 3.6—commonly used areas of its vast standard library, and some of the most useful third-party modules and packages. Ideal for programmers with some Python experience, and those coming to Python from other programming languages, this book covers a wide range of application areas, including web and network programming, XML handling, database interactions, and high-speed numeric computing. Discover how Python provides a unique mix of elegance, simplicity, practicality, and sheer power.

  16. Python to learn programming

    Science.gov (United States)

    Bogdanchikov, A.; Zhaparov, M.; Suliyev, R.

    2013-04-01

    Today we have a lot of programming languages that can realize our needs, but the most important question is how to teach programming to beginner students. In this paper we suggest using Python for this purpose, because it is a programming language that has neatly organized syntax and powerful tools to solve any task. Moreover it is very close to simple math thinking. Python is chosen as a primary programming language for freshmen in most of leading universities. Writing code in python is easy. In this paper we give some examples of program codes written in Java, C++ and Python language, and we make a comparison between them. Firstly, this paper proposes advantages of Python language in relation to C++ and JAVA. Then it shows the results of a comparison of short program codes written in three different languages, followed by a discussion on how students understand programming. Finally experimental results of students' success in programming courses are shown.

  17. Parallel programming with Python

    CERN Document Server

    Palach, Jan

    2014-01-01

    A fast, easy-to-follow and clear tutorial to help you develop Parallel computing systems using Python. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts and will help you in implementing these techniques in the real world. If you are an experienced Python programmer and are willing to utilize the available computing resources by parallelizing applications in a simple way, then this book is for you. You are required to have a basic knowledge of Python development to get the most of this book.

  18. Pro Python System Administration

    CERN Document Server

    Sileika, R

    2010-01-01

    As time goes on, system administrators are presented with increasingly complicated challenges. In the early days, a team of engineers might have had to look after one or two systems. These days, one engineer can administer hundreds or thousands of systems. System administrators are gradually replacing their tools with more advanced and flexible ones. One of the choices is Python. Structurally, Python is a modern, high-level language with a very clean syntax. Python comes with many built-in libraries that can make automation tasks easier. It also has extensive set of third-party libraries and a

  19. Python geospatial development

    CERN Document Server

    Westra, Erik

    2013-01-01

    This is a tutorial style book that will teach usage of Python tools for GIS using simple practical examples and then show you how to build a complete mapping application from scratch. The book assumes basic knowledge of Python. No knowledge of Open Source GIS is required.Experienced Python developers who want to learn about geospatial concepts, work with geospatial data, solve spatial problems, and build mapbased applications.This book will be useful those who want to get up to speed with Open Source GIS in order to build GIS applications or integrate GeoSpatial features into their existing ap

  20. Python Introduction and Installation

    Directory of Open Access Journals (Sweden)

    William J. Turkel

    2012-07-01

    Full Text Available This first lesson in our section on dealing with Online Sources is designed to get you and your computer set up to start programming. We will focus on installing the relevant software – all free and reputable – and finally we will help you to get your toes wet with some simple programming that provides immediate results. In this opening module you will install the Python programming language, the Beautiful Soup HTML/XML parser, and a text editor. Screencaps provided here come from Komodo Edit, but you can use any text editor capable of working with Python. Here’s a list of other options: Python Editors. Once everything is installed, you will write your first programs, “Hello World” in Python and HTML.

  1. Python profiling 101

    CERN Multimedia

    CERN. Geneva

    2014-01-01

    Python code is much easier to write than C, yet much less efficient. It's often assumed that Python is not performance-oriented and therefore making effort to optimize it doesn't pay off. While in many cases it's true, at a certain moment of a development, especially right before reaching production-ready state, it might turn out that a Python code runs slowly and one needs to find a culprit. In this talk I'll not tell how to make your program faster. Instead, I'll show different techniques to look for the bottlenecks in the code. The presentation will be built around a live demo using real-life Python code.

  2. Python for secret agents

    CERN Document Server

    Lott, Steven F

    2014-01-01

    If you are a Python beginner who is looking to learn the language through interesting projects, this book is for you. A basic knowledge of programming and statistics is beneficial to get the most out of the book.

  3. NEURON and Python.

    Science.gov (United States)

    Hines, Michael L; Davison, Andrew P; Muller, Eilif

    2009-01-01

    The NEURON simulation program now allows Python to be used, alone or in combination with NEURON's traditional Hoc interpreter. Adding Python to NEURON has the immediate benefit of making available a very extensive suite of analysis tools written for engineering and science. It also catalyzes NEURON software development by offering users a modern programming tool that is recognized for its flexibility and power to create and maintain complex programs. At the same time, nothing is lost because all existing models written in Hoc, including graphical user interface tools, continue to work without change and are also available within the Python context. An example of the benefits of Python availability is the use of the xml module in implementing NEURON's Import3D and CellBuild tools to read MorphML and NeuroML model specifications.

  4. Python Switch Statement

    Directory of Open Access Journals (Sweden)

    2008-06-01

    Full Text Available The Python programming language does not have a built in switch/case control structure as found in many other high level programming languages. It is thought by some that this is a deficiency in the language, and the control structure should be added. This paper demonstrates that not only is the control structure not needed, but that the methods available in Python are more expressive than built in case statements in other high level languages.

  5. Manipulating Strings in Python

    Directory of Open Access Journals (Sweden)

    William J. Turkel

    2012-07-01

    Full Text Available This lesson is a brief introduction to string manipulation techniques in Python. Knowing how to manipulate strings plays a crucial role in most text processing tasks. If you’d like to experiment with the following lessons, you can write and execute short programs as we’ve been doing, or you can open up a Python shell / Terminal to try them out on the command line.

  6. NEURON and Python

    OpenAIRE

    Michael Hines; Andrew P Davison; Eilif Muller

    2009-01-01

    The NEURON simulation program now allows Python to be used, alone or in combination with NEURON's traditional Hoc interpreter. Adding Python to NEURON has the immediate benefit of making available a very extensive suite of analysis tools written for engineering and science. It also catalyzes NEURON software development by offering users a modern programming tool that is recognized for its flexibility and power to create and maintain complex programs. At the same time, nothing is lost because ...

  7. mlpy: Machine Learning Python

    OpenAIRE

    Albanese, Davide; Visintainer, Roberto; Merler, Stefano; Riccadonna, Samantha; Jurman, Giuseppe; Furlanello, Cesare

    2012-01-01

    mlpy is a Python Open Source Machine Learning library built on top of NumPy/SciPy and the GNU Scientific Libraries. mlpy provides a wide range of state-of-the-art machine learning methods for supervised and unsupervised problems and it is aimed at finding a reasonable compromise among modularity, maintainability, reproducibility, usability and efficiency. mlpy is multiplatform, it works with Python 2 and 3 and it is distributed under GPL3 at the website http://mlpy.fbk.eu.

  8. Hemodynamic effects of python neuropeptide gamma in the anesthetized python, Python regius.

    Science.gov (United States)

    Skovgaard, Nini; Galli, Gina; Taylor, Edwin W; Conlon, J Michael; Wang, Tobias

    2005-05-15

    The effects of python neuropeptide gamma (NPgamma) on hemodynamic parameters have been investigated in the anesthetized ball python (Python regius). Bolus intra-arterial injections of synthetic python NPgamma (1-300 pmol kg-1) produced a dose-dependent decrease in systemic arterial blood pressure (Psys) concomitant with increases in systemic vascular conductance (Gsys), total cardiac output and stroke volume, but only minor effects on heart rate. The peptide had no significant effect on pulmonary arterial blood pressure (Ppul) and caused only a small increase in pulmonary conductance (Gpul) at the highest dose. In the systemic circulation, the potency of the NK1 receptor-selective agonist [Sar9,Met(0(2))11] substance P was >100-fold greater than the NK2 receptor-selective agonist [betaAla8] neurokinin A-(4-10)-peptide suggesting that the python cardiovascular system is associated with a receptor that resembles the mammalian NK1 receptor more closely than the NK2 receptor. Administration of the inhibitor of nitric oxide synthesis, L-nitro-arginine-methylester (L-NAME; 150 mg kg-1), resulted in a significant (Ppython, but neither nitric oxide nor prostaglandins mediate the vasodilatory action of NPgamma.

  9. Anatomy of the python heart.

    Science.gov (United States)

    Jensen, Bjarke; Nyengaard, Jens R; Pedersen, Michael; Wang, Tobias

    2010-12-01

    The hearts of all snakes and lizards consist of two atria and a single incompletely divided ventricle. In general, the squamate ventricle is subdivided into three chambers: cavum arteriosum (left), cavum venosum (medial) and cavum pulmonale (right). Although a similar division also applies to the heart of pythons, this family of snakes is unique amongst snakes in having intracardiac pressure separation. Here we provide a detailed anatomical description of the cardiac structures that confer this functional division. We measured the masses and volumes of the ventricular chambers, and we describe the gross morphology based on dissections of the heart from 13 ball pythons (Python regius) and one Burmese python (P. molurus). The cavum venosum is much reduced in pythons and constitutes approximately 10% of the cavum arteriosum. We suggest that shunts will always be less than 20%, while other studies conclude up to 50%. The high-pressure cavum arteriosum accounted for approximately 75% of the total ventricular mass, and was twice as dense as the low-pressure cavum pulmonale. The reptile ventricle has a core of spongious myocardium, but the three ventricular septa that separate the pulmonary and systemic chambers--the muscular ridge, the bulbuslamelle and the vertical septum--all had layers of compact myocardium. Pythons, however, have unique pads of connective tissue on the site of pressure separation. Because the hearts of varanid lizards, which also are endowed with pressure separation, share many of these morphological specializations, we propose that intraventricular compact myocardium is an indicator of high-pressure systems and possibly pressure separation.

  10. Python for scientists

    CERN Document Server

    Stewart, John M

    2017-01-01

    Scientific Python is a significant public domain alternative to expensive proprietary software packages. This book teaches from scratch everything the working scientist needs to know using copious, downloadable, useful and adaptable code snippets. Readers will discover how easy it is to implement and test non-trivial mathematical algorithms and will be guided through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the language's capabilities. The author also shows how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. In this new edition, several chapters have been re-written to reflect the IPython notebook style. With an extended index, an entirely new chapter discussing SymPy and a substantial increase in the number of code snippets, researchers and research students will be able to quickly acquire all the skills needed for using Python effectively.

  11. Ascaridosis in captive reticulated python( Python reticulatus ) | Taiwo ...

    African Journals Online (AJOL)

    Two captive reticulated pythons, Python reticulatus, in the Zoological Gardens, University of Ibadan, Ibadan, Nigeria died and were submitted for necropsy at the Diagnostic Laboratory of the Department of Veterinary Pathology, University of Ibadan. Both pythons had been infected with Ascaridia galli for a long period of time ...

  12. Unilateral microphthalmia or anophthalmia in eight pythons (Pythonidae)

    DEFF Research Database (Denmark)

    Da Silva, Mari-Ann Otkjær; Bertelsen, Mads F.; Wang, Tobias

    2015-01-01

    ) with clinically normal right eyes and an abnormal or missing left eye. PROCEDURE: At the time of euthanasia, four of the eight snakes underwent necropsy. Hereafter, the heads of two Burmese pythons and one ball python were examined using μCT, and another Burmese python was subjected to MRI. Following...

  13. Python and AWS Cookbook

    CERN Document Server

    Garnaat, Mitch

    2011-01-01

    If you intend to use Amazon Web Services (AWS) for remote computing and storage, Python is an ideal programming language for developing applications and controlling your cloud-based infrastructure. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author's boto library. You'll find detailed recipes for working with the S3 storage service as well as EC2, the service that lets you design and build cloud applications. Each recipe includes a code solution you can use immediately, along with a discussion of why and how the recipe works. You al

  14. Python for finance

    CERN Document Server

    Yan, Yuxing

    2014-01-01

    Python is a free and powerful tool which can be used to build a financial calculator and price options, and can also explain many trading strategies and test various hypotheses. In addition to that, real-world data can be used to run CAPM (Capital Asset Pricing Model), the Fama-French 3-factor model, estimate VaR (Value at Risk), and estimate spread, illiquidity, and liquidity. This book explores the basics of programming in Python. It is a step-by-step tutorial that will teach you, with the help of concise, practical programs, how to run various statistic tests. With this book, you will learn

  15. Practical Maya programming with Python

    CERN Document Server

    Galanakis, Robert

    2014-01-01

    ""Practical Maya Programming with Python"" is a practical tutorial packed with plenty of examples and sample projects which guides you through building reusable, independent modules and handling unexpected errors. If you are a developer looking to build a powerful system using Python and Maya's capabilities, then this book is for you. Practical Maya Programming with Python is perfect for intermediate users with basic experience in Python and Maya who want to better their knowledge and skills.

  16. Developers@CERN Forums: Python

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    The Developers@CERN Forums second edition took place at the end of May on the topic of Python. How do developers at CERN interact with Python? Which cutting-edge projects are using Python? What were the highlights of this most recent forum?

  17. Python reference manual

    NARCIS (Netherlands)

    G. van Rossum (Guido)

    1995-01-01

    textabstractPython is a simple, yet powerful, interpreted programming language that bridges the gap between C and shell programming, and is thus ideally suited for ``throw-away programming'' and rapid prototyping. Its syntax is put together from constructs borrowed from a variety of other languages;

  18. Python data science essentials

    CERN Document Server

    Boschetti, Alberto

    2015-01-01

    If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills.

  19. Learning robotics using Python

    CERN Document Server

    Joseph, Lentin

    2015-01-01

    If you are an engineer, a researcher, or a hobbyist, and you are interested in robotics and want to build your own robot, this book is for you. Readers are assumed to be new to robotics but should have experience with Python.

  20. Python at CERN

    CERN Multimedia

    Witowski, Sebastian

    2017-01-01

    The Large Hadron Collider at CERN is producing 600 million collisions every second. Only 1 in a million collisions is interesting. It requires a fast programming language to analyze and filter this amount of data. Is Python such a language? No, it’s not. Does it mean there is no place for Python in one of the largest scientific facilities in the world? Quite the contrary. The ease of use and a very low learning curve makes Python a perfect programming language for many physicists and other people without the computer science background. CERN does not only produce large amounts of data. The interesting bits of data have to be stored, analyzed, shared and published. Work of many scientists across various research facilities around the world has to be synchronized. This is the area where Python flourishes. And with CERN’s pursuit to create and use open source software, many interesting projects were born. To facilitate the analysis of data, ROOT framework [https://root.cern.ch/] was created. It’s a C++ fra...

  1. 75 FR 38069 - Injurious Wildlife Species; Listing the Boa Constrictor, Four Python Species, and Four Anaconda...

    Science.gov (United States)

    2010-07-01

    ... Python Species, and Four Anaconda Species as Injurious Reptiles AGENCY: Fish and Wildlife Service... regulations to add Indian python (Python molurus, including Burmese python Python molurus bivittatus), reticulated python (Broghammerus reticulatus or Python reticulatus), Northern African python (Python sebae...

  2. Deep learning with Python

    CERN Document Server

    Chollet, Francois

    2018-01-01

    DESCRIPTION Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects. KEY FEATURES • Practical code examples • In-depth introduction to Keras • Teaches the difference between Deep Learning and AI ABOUT THE TECHNOLOGY Deep learning is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more. AUTHOR BIO Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural ...

  3. Python algorithms mastering basic algorithms in the Python language

    CERN Document Server

    Hetland, Magnus Lie

    2014-01-01

    Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data struc

  4. Mastering object-oriented Python

    CERN Document Server

    Lott, Steven F

    2014-01-01

    This book follows a standard tutorial approach with approximately 750 code samples spread through the 19 chapters. This amounts to over 5,900 lines of code that illustrate each concept.This book is aimed at programmers who have already learned the basics of object-oriented Python and need to write more sophisticated, flexible code that integrates seamlessly with the rest of Python. This book assumes a computer science background, with experience of common Python design patterns.

  5. Installing Python Modules with pip

    OpenAIRE

    Fred Gibbs

    2013-01-01

    This lesson shows you how to download and install Python modules. There are many ways to install external modules, but for the purposes of this lesson, we’re going to use a program called pip. As of Python 2.7.9 and newer, pip is installed by default. This tutorial will be helpful for anyone using older versions of Python (which are still quite common).

  6. Installing Python Modules with pip

    Directory of Open Access Journals (Sweden)

    Fred Gibbs

    2013-05-01

    Full Text Available This lesson shows you how to download and install Python modules. There are many ways to install external modules, but for the purposes of this lesson, we’re going to use a program called pip. As of Python 2.7.9 and newer, pip is installed by default. This tutorial will be helpful for anyone using older versions of Python (which are still quite common.

  7. Beginning Python using Python 2.6 and Python 3.1

    CERN Document Server

    Payne, James

    2010-01-01

    Beginning Python: Using Python 2.6 and Python 3.1 introduces this open source, portable, interpreted, object-oriented programming language that combines remarkable power with clear syntax. This book enables you to quickly create robust, reliable, and reusable Python applications by teaching the basics so you can quickly develop Web and scientific applications, incorporate databases, and master systems tasks on various operating systems, including Linux, MAC OS, and Windows. You’ll get a comprehensive tutorial that guides you from writing simple, basic Python scripts all the way through complex concepts, and also features a reference of the standard modules with examples illustrating how to implement features in the various modules. Plus, the book covers using Python in specific program development domains, such as XML, databases, scientific applications, network programming, and Web development

  8. Pythons in Burma: Short-tailed python (Reptilia: Squamata)

    Science.gov (United States)

    Zug, George R.; Gotte, Steve W.; Jacobs, Jeremy F.

    2011-01-01

    Short-tailed pythons, Python curtus species group, occur predominantly in the Malayan Peninsula, Sumatra, and Borneo. The discovery of an adult female in Mon State, Myanmar, led to a review of the distribution of all group members (spot-mapping of all localities of confirmed occurrence) and an examination of morphological variation in P. brongersmai. The resulting maps demonstrate a limited occurrence of these pythons within peninsular Malaya, Sumatra, and Borneo with broad absences in these regions. Our small samples limit the recognition of regional differentiation in the morphology of P. brongersmai populations; however, the presence of unique traits in the Myanmar python and its strong allopatry indicate that it is a unique genetic lineage, and it is described as Python kyaiktiyo new species.

  9. Python Integration with a Functional DBMS

    OpenAIRE

    Zou, Hanzheng

    2009-01-01

    Python is an Object Oriented programming language and widely used nowadays. This report describes how to extend a functional database system Amos II for integration with Python. Several possibilities are analyzed to combine the Amos II C external interfaces with those of Python. Based on these discussions, new functionality has been added to the Python language by implementing a Python C external module. A basic API called PyAmos, interfacing Python and Amos II, is proposed and implemented in...

  10. Python tools for Visual Studio

    CERN Document Server

    Wang, Cathy

    2014-01-01

    This is a hands-on guide that provides exemplary coverage of all the features and concepts related to PTVS.The book is intended for developers who are aiming to enhance their productivity in Python projects with automation tools that Visual Studio provides for the .Net community. Some basic knowledge of Python programming is essential.

  11. Writing faster Python

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    Did you know that Python preallocates integers from -5 to 257 ? Reusing them 1000 times, instead of allocating memory for a bigger integer, can save you a couple of milliseconds of code’s execution time. If you want to learn more about this kind of optimizations then, … well, probably this presentation is not for you :) Instead of going into such small details, I will talk about more "sane" ideas for writing faster code. After a very brief overview of how to optimize Python code (rule 1: don’t do this; rule 2: don’t do this yet; rule 3: ok, but what if I really want to do this ?), I will show simple and fast ways of measuring the execution time and finally, discuss examples of how some code structures could be improved. You will see: - What is the fastest way of removing duplicates from a list - How much faster your code is when you reuse the built-in functions instead of trying to reinvent the wheel - What is faster than the good ol’ for loop - If the lookup is faster in a list or a set (and w...

  12. EPICS V4 in Python

    International Nuclear Information System (INIS)

    Guobao Shen; Kraimer, M.; Davidsaver, M.

    2012-01-01

    At NSLS-II, Python has been selected as the primary development language for physics applications. Interest in Python as a rapid application development environment continues to grow. Many large experimental scientific facilities have adopted Python for beam commissioning and the operation. The EPICS control system framework has become the de facto standard for the control of large experimental facilities, where it is in use in over 100 facilities. The next version of EPICS (EPICS V4), under active development will extend the support for physics applications, data acquisition, and data analysis. Python support for EPICS V4 will provide an effective framework to address these requirements. This paper presents design, development and status of activities focused on EPICS V4 in Python

  13. Endocardial fibrosarcoma in a reticulated python (Python reticularis).

    Science.gov (United States)

    Gumber, Sanjeev; Nevarez, Javier G; Cho, Doo-Youn

    2010-11-01

    A female, reticulated python (Python reticularis) of unknown age was presented with a history of lethargy, weakness, and distended coelom. Physical examination revealed severe dystocia and stomatitis. The reticulated python was euthanized due to a poor clinical prognosis. Postmortem examination revealed marked distention of the reproductive tract with 26 eggs (10-12 cm in diameter), pericardial effusion, and a slightly firm, pale tan mass (3-4 cm in diameter) adhered to the endocardium at the base of aorta. Based on histopathologic and transmission electron microscopic findings, the diagnosis of endocardial fibrosarcoma was made.

  14. DAL Algorithms and Python

    CERN Document Server

    Aydemir, Bahar

    2017-01-01

    The Trigger and Data Acquisition (TDAQ) system of the ATLAS detector at the Large Hadron Collider (LHC) at CERN is composed of a large number of distributed hardware and software components. TDAQ system consists of about 3000 computers and more than 25000 applications which, in a coordinated manner, provide the data-taking functionality of the overall system. There is a number of online services required to configure, monitor and control the ATLAS data taking. In particular, the configuration service is used to provide configuration of above components. The configuration of the ATLAS data acquisition system is stored in XML-based object database named OKS. DAL (Data Access Library) allowing to access it's information by C++, Java and Python clients in a distributed environment. Some information has quite complicated structure, so it's extraction requires writing special algorithms. Algorithms available on C++ programming language and partially reimplemented on Java programming language. The goal of the projec...

  15. Ultrasonographic anatomy of the coelomic organs of boid snakes (Boa constrictor imperator, Python regius, Python molurus molurus, and Python curtus).

    Science.gov (United States)

    Banzato, Tommaso; Russo, Elisa; Finotti, Luca; Milan, Maria C; Gianesella, Matteo; Zotti, Alessandro

    2012-05-01

    To determine the ultrasonographic features of the coelomic organs of healthy snakes belonging to the Boidae and Pythonidae families. 16 ball pythons (Python regius; 7 males, 8 females, and 1 sexually immature), 10 Indian rock pythons (Python molurus molurus; 5 males, 4 females, and 1 sexually immature), 12 Python curtus (5 males and 7 females), and 8 boa constrictors (Boa constrictor imperator; 4 males and 4 females). All snakes underwent complete ultrasonographic evaluation of the coelomic cavity; chemical restraint was not necessary. A dorsolateral approach to probe placement was chosen to increase image quality and to avoid injury to the snakes and operators. Qualitative and quantitative observations were recorded. The liver, stomach, gallbladder, pancreas, small and large intestines, kidneys, cloaca, and scent glands were identified in all snakes. The hemipenes were identified in 10 of the 21 (48%) male snakes. The spleen was identified in 5 of the 46 (11%) snakes, and ureters were identified in 6 (13%). In 2 sexually immature snakes, the gonads were not visible. One (2%) snake was gravid, and 7 (15%) had small amounts of free fluid in the coelomic cavity. A significant positive correlation was identified between several measurements (diameter and thickness of scent glands, gastric and pyloric walls, and colonic wall) and body length (snout to vent) and body weight. The study findings can be used as an atlas of the ultrasonographic anatomy of the coelomic cavity in healthy boid snakes. Ultrasonography was reasonably fast to perform and was well tolerated in conscious snakes.

  16. Acariasis on pet Burmese python, Python molurus bivittatus in Malaysia.

    Science.gov (United States)

    Mariana, A; Vellayan, S; Halimaton, I; Ho, T M

    2011-03-01

    To identify the acari present on pet Burmese pythons in Malaysia and to determine whether there is any potential public health risk related to handling of the snakes. Two sub-adult Burmese pythons kept as pets for a period of about 6 to 7 months by different owners, were brought to an exotic animal practice for treatment. On a complete medical examination, some ticks and mites (acari) were detected beneath the dorsal and ventral scales along body length of the snakes. Ticks were directly identified and mites were mounted prior to identification. A total of 12 ticks represented by 3 males, 2 females and 7 nymphal stages of Rhipicephalus sanguineus (R. sanguineus) were extracted from the first python while the other one was with 25 female Ophionyssus natricis (O. natricis) mesostigmatid mites. Only adult female mites were found. These mites are common ectoparasites of Burmese pythons. Both the acarine species found on the Burmese pythons are known vectors of pathogens. This is the first record that R. sanguineus has been reported from a pet Burmese python in Malaysia. Copyright © 2011 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

  17. Python for Google app engine

    CERN Document Server

    Pippi, Massimiliano

    2015-01-01

    If you are a Python developer, whether you have experience in web applications development or not, and want to rapidly deploy a scalable backend service or a modern web application on Google App Engine, then this book is for you.

  18. MDSplus objects-Python implementation

    International Nuclear Information System (INIS)

    Fredian, T.; Stillerman, J.; Manduchi, G.

    2010-01-01

    MDSplus is a data acquisition and analysis software package used widely throughout the international fusion research community. During the past year, an important set of enhancements were designed under the project name of 'MDSobjects' which would provide a common, powerful application programming interface (API) to MDSplus in programming languages with object-oriented capabilities. This paper will discuss the Python language implementation of this API and some of the capabilities that this implementation provides for data storage and retrieval using the MDSplus system. We have implemented a new MDSplus Python module which exposes the MDSplus objects features to the language. The internal MDSplus programming language, TDI, has also been enhanced to be able to invoke Python commands from the TDI language. Now that Python is aware of the complex data structures in MDSplus such as Signals, the language becomes a very good candidate for applications ranging from data acquisition device support to analysis and visualization.

  19. Humoral regulation of heart rate during digestion in pythons (Python molurus and Python regius).

    Science.gov (United States)

    Enok, Sanne; Simonsen, Lasse Stærdal; Pedersen, Signe Vesterskov; Wang, Tobias; Skovgaard, Nini

    2012-05-15

    Pythons exhibit a doubling of heart rate when metabolism increases several times during digestion. Pythons, therefore, represent a promising model organism to study autonomic cardiovascular regulation during the postprandial state, and previous studies show that the postprandial tachycardia is governed by a release of vagal tone as well as a pronounced stimulation from nonadrenergic, noncholinergic (NANC) factors. Here we show that infusion of plasma from digesting donor pythons elicit a marked tachycardia in fasting snakes, demonstrating that the NANC factor resides in the blood. Injections of the gastrin and cholecystokinin receptor antagonist proglumide had no effect on double-blocked heart rate or blood pressure. Histamine has been recognized as a NANC factor in the early postprandial period in pythons, but the mechanism of its release has not been identified. Mast cells represent the largest repository of histamine in vertebrates, and it has been speculated that mast cells release histamine during digestion. Treatment with the mast cell stabilizer cromolyn significantly reduced postprandial heart rate in pythons compared with an untreated group but did not affect double-blocked heart rate. While this study indicates that histamine induces postprandial tachycardia in pythons, its release during digestion is not stimulated by gastrin or cholecystokinin nor is its release from mast cells a stimulant of postprandial tachycardia.

  20. Beginning Python from novice to professional

    CERN Document Server

    Hetland, Magnus Lie

    2005-01-01

    ""Beginning Python: From Novice to Professional"" is the most comprehensive book on the Python ever written. Based on ""Practical Python,"" this newly revised book is both an introduction and practical reference for a swath of Python-related programming topics, including addressing language internals, database integration, network programming, and web services. Advanced topics, such as extending Python and packaging/distributing Python applications, are also covered. Ten different projects illustrate the concepts introduced in the book. You will learn how to create a P2P file-sharing applicati

  1. Accessing the VO with Python

    Science.gov (United States)

    Plante, R.; Fitzpatrick, M.; Graham, M.; Tody, D.; Young, W.

    2014-05-01

    We introduce two products for accessing the VO from Python: PyVO and VOClient. PyVO is built on the widely-used Astropy package and is well suited for integrating automated access to astronomical data into highly customizable scripts and applications for data analysis in Python. VOClient is built on a collection of C-libraries and is well suited for integrating with multi-language analysis packages. It also provides a framework for integrating legacy software into the Python environment. In this demo, we will run through several examples demonstrate basic data discovery and retrieval of data. This includes finding archives containing data of interest (VO registry), retrieving datasets (SIA, SSA), and exploring (Cone Search, SLAP). VOClient features some extended capabilities including the ability to communicate to other desktop applications from a script using the SAMP protocol.

  2. Building machine learning systems with Python

    CERN Document Server

    Coelho, Luis Pedro

    2015-01-01

    This book primarily targets Python developers who want to learn and use Python's machine learning capabilities and gain valuable insights from data to develop effective solutions for business problems.

  3. Learning Python with Raspberry Pi

    CERN Document Server

    Bradbury, Alex

    2014-01-01

    The must-have companion guide to the Raspberry Pi User Guide! Raspberry Pi chose Python as its teaching language of choice to encourage a new generation of programmers to learn how to program. This approachable book serves as an ideal resource for anyone wanting to use Raspberry Pi to learn to program and helps you get started with the Python programming language. Aimed at first-time developers with no prior programming language assumed, this beginner book gets you up and running.Covers variables, loops, and functionsAddresses 3D graphics programmingWalks you through programming MinecraftZero

  4. Infestation of Royal Python (Python regius) with ticks Amblyomma ...

    African Journals Online (AJOL)

    The Python/Boa Family is found in most part of tropics. It is a highly domesticated pet and can easily be handled (Cansdale 1962). Snakes are commonly infected by ticks more importantly the hand bodied ticks (Fowler, 1986).However, under captive condition, ticks usually exert a lot of burden on their hosts being carriers of ...

  5. OpenCL programming using Python syntax

    OpenAIRE

    Massimo Di Pierro

    2013-01-01

    We describe ocl, a Python library built on top of p yOpenCL and numpy. It allows programming GPU devices using Python. Python functions which ar e marked up using the provided decorator, are converted into C99/OpenCL and compil ed using the JIT at runtime. This approach lowers the barrier to entry to programming GPU devices since it requires only Python syntax and no external compilation or linkin g steps. The resulting Pyth...

  6. Pybus - A Python Software Bus

    International Nuclear Information System (INIS)

    Lavrijsen, Wim T.L.P.

    2004-01-01

    A software bus, just like its hardware equivalent, allows for the discovery, installation, configuration, loading, unloading, and run-time replacement of software components, as well as channeling of inter-component communication. Python, a popular open-source programming language, encourages a modular design on software written in it, but it offers little or no component functionality. However, the language and its interpreter provide sufficient hooks to implement a thin, integral layer of component support. This functionality can be presented to the developer in the form of a module, making it very easy to use. This paper describes a Pythonmodule, PyBus, with which the concept of a ''software bus'' can be realized in Python. It demonstrates, within the context of the ATLAS software framework Athena, how PyBus can be used for the installation and (run-time) configuration of software, not necessarily Python modules, from a Python application in a way that is transparent to the end-user

  7. Imagining a Stata / Python Combination

    Science.gov (United States)

    Fiedler, James

    2012-01-01

    There are occasions when a task is difficult in Stata, but fairly easy in a more general programming language. Python is a popular language for a range of uses. It is easy to use, has many high ]quality packages, and programs can be written relatively quickly. Is there any advantage in combining Stata and Python within a single interface? Stata already offers support for user-written programs, which allow extensive control over calculations, but somewhat less control over graphics. Also, except for specifying output, the user has minimal programmatic control over the user interface. Python can be used in a way that allows more control over the interface and graphics, and in so doing provide a roundabout method for satisfying some user requests (e.g., transparency levels in graphics and the ability to clear the results window). My talk will explore these ideas, present a possible method for combining Stata and Python, and give examples to demonstrate how this combination might be useful.

  8. Python pocket reference, version 2.4

    CERN Document Server

    Lutz, Mark

    2005-01-01

    Python is optimized for quality, productivity, portability, and integration. Hundreds of thousands of Python developers around the world rely on Python for general-purpose tasks, Internet scripting, systems programming, user interfaces, and product customization. Available on all major computing platforms, including commercial versions of Unix, Linux, Windows, and Mac OS X, Python is portable, powerful and remarkable easy to use. With its convenient, quick-reference format, Python Pocket Reference, 3rd Edition is the perfect on-the-job reference. More importantly, it's now been refreshed

  9. Report on the observed response of Javan lutungs (Trachypithecus auratus mauritius) upon encountering a reticulated python (Python reticulatus).

    Science.gov (United States)

    Tsuji, Yamato; Prayitno, Bambang; Suryobroto, Bambang

    2016-04-01

    We observed an encounter between a reticulated python (Python reticulatus) and a group of wild Javan lutungs (Trachypithecus auratus mauritius) at the Pangandaran Nature Reserve, West Java, Indonesia. A python (about 2 m in length) moved toward a group of lutungs in the trees. Upon seeing the python, an adult male and several adult female lutungs began to emit alarm calls. As the python approached, two adult and one sub-adult female jumped onto a branch near the python and began mobbing the python by shaking the branch. During the mobbing, other individuals in the group (including an adult lutung male) remained nearby but did not participate. The python then rolled into a ball-like shape and stopped moving, at which point the lutungs moved away. The total duration of the encounter was about 40 min, during which time the lutungs stopped feeding and grooming. Group cohesiveness during and after the encounter was greater than that before the encounter, indicating that lutungs adjust their daily activity in response to potential predation risk.

  10. Learning scientific programming with Python

    CERN Document Server

    Hill, Christian

    2015-01-01

    Learn to master basic programming tasks from scratch with real-life scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving onto the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualisation, this textbook also discusses the use of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such as floating-point precision and algorithm stability, and with extensive online resources to support advanced study, this textbook represents a targeted package for students...

  11. Python - All a Scientist Needs

    OpenAIRE

    Lucks, Julius B.

    2008-01-01

    Any cutting-edge scientific research project requires a myriad of computational tools for data generation, management, analysis and visualization. Python is a flexible and extensible scientific programming platform that offered the perfect solution in our recent comparative genomics investigation (J. B. Lucks, D. R. Nelson, G. Kudla, J. B. Plotkin. Genome landscapes and bacteriophage codon usage, PLoS Computational Biology, 4, 1000001, 2008). In this paper, we discuss the challenges of this p...

  12. Steering object-oriented computations with Python

    Energy Technology Data Exchange (ETDEWEB)

    Yang, T.-Y.B.; Dubois, P.F.; Furnish, G. [Lawrence Livermore National Lab., CA (United States); Beazley, D.M. [Utah Univ., Salt Lake City, UT (United States). Dept. of Computer Science

    1996-10-01

    We have described current approaches and future plans for steering C++ application, running Python on parallel platforms, and combination of Tk interface and Python interpreter in steering computations. In addition, there has been significant enhancement in the Gist module. Tk mega widgets has been implemented for a few physics applications. We have also written Python interface to SIJLO, a data storage package used as an interface to a visualization system named MeshTv. Python is being used to control large-scale simulations (molecular dynamics in particular) running on the CM-5 and T3D at LANL as well. A few other code development projects at LLNL are either using or considering Python as their steering shells. In summary, the merits of Python have been appreciated by more and more people in the scientific computation community.

  13. Creating and Viewing HTML Files with Python

    OpenAIRE

    William J. Turkel; Adam Crymble

    2012-01-01

    This lesson uses Python to create and view an HTML file. If you write programs that output HTML, you can use any browser to look at your results. This is especially convenient if your program is automatically creating hyperlinks or graphic entities like charts and diagrams. Here you will learn how to create HTML files with Python scripts, and how to use Python to automatically open an HTML file in Firefox.

  14. Source Code Stylometry Improvements in Python

    Science.gov (United States)

    2017-12-14

    machine learning , random forests, Python 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF...a random forest classifier—implemented in the Python machine- learning library’s Scikit- learn (Pedregosa et al. 2011)—to create a model of how the...feature set for the original and Python stylometry versions is different as are the exact parameters of the learning mechanism. Thus, results are not

  15. Creating and Viewing HTML Files with Python

    Directory of Open Access Journals (Sweden)

    William J. Turkel

    2012-07-01

    Full Text Available This lesson uses Python to create and view an HTML file. If you write programs that output HTML, you can use any browser to look at your results. This is especially convenient if your program is automatically creating hyperlinks or graphic entities like charts and diagrams. Here you will learn how to create HTML files with Python scripts, and how to use Python to automatically open an HTML file in Firefox.

  16. TensorLy: Tensor Learning in Python

    OpenAIRE

    Kossaifi, Jean; Panagakis, Yannis; Pantic, Maja

    2016-01-01

    Tensor methods are gaining increasing traction in machine learning. However, there are scant to no resources available to perform tensor learning and decomposition in Python. To answer this need we developed TensorLy. TensorLy is a state of the art general purpose library for tensor learning. Written in Python, it aims at following the same standard adopted by the main projects of the Python scientific community and fully integrating with these. It allows for fast and straightforward tensor d...

  17. Programming ArcGIS with Python cookbook

    CERN Document Server

    Pimpler, Eric

    2015-01-01

    Programming ArcGIS with Python Cookbook, Second Edition, is written for GIS professionals who wish to revolutionize their ArcGIS workflow with Python. Whether you are new to ArcGIS or a seasoned professional, you almost certainly spend time each day performing various geoprocessing tasks. This book will teach you how to use the Python programming language to automate these geoprocessing tasks and make you a more efficient and effective GIS professional.

  18. Python for Unix and Linux system administration

    CERN Document Server

    Gift, Noah

    2007-01-01

    Python is an ideal language for solving problems, especially in Linux and Unix networks. With this pragmatic book, administrators can review various tasks that often occur in the management of these systems, and learn how Python can provide a more efficient and less painful way to handle them. Each chapter in Python for Unix and Linux System Administration presents a particular administrative issue, such as concurrency or data backup, and presents Python solutions through hands-on examples. Once you finish this book, you'll be able to develop your own set of command-line utilities with Pytho

  19. Internationalization and Localization in Python

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    Internationalization and Localization are increasingly important in an interconnected world. Regardless of that, developers tend to treat them as secondary issues, very often choosing to address them properly when it's already too late. The fact that most programming language standard libraries choose to ignore the matter doesn't help either. In this talk we will present some useful Python libraries and tools that can help you internationalize and localize your code with minimal effort. We will also describe some common pitfalls and problems.

  20. Python 3 for Absolute Beginners

    CERN Document Server

    Hall, Tim

    2009-01-01

    There are many more people who want to study programming other than aspiring computer scientists with a passing grade in advanced calculus. This guide appeals to your intelligence and ability to solve practical problems, while gently teaching the most recent revision of the programming language Python. You can learn solid software design skills and accomplish practical programming tasks, like extending applications and automating everyday processes, even if you have no programming experience at all. Authors Tim Hall and J-P Stacey use everyday language to decode programming jargon and teach Py

  1. A field test of attractant traps for invasive Burmese pythons (Python molurus bivittatus) in southern Florida

    Science.gov (United States)

    Reed, Robert N.; Hart, Kristen M.; Rodda, Gordon H.; Mazzotti, Frank J.; Snow, Ray W.; Cherkiss, Michael; Rozar, Rondald; Goetz, Scott

    2011-01-01

    Context: Invasive Burmese pythons (Python molurus bivittatus) are established over thousands of square kilometres of southern Florida, USA, and consume a wide range of native vertebrates. Few tools are available to control the python population, and none of the available tools have been validated in the field to assess capture success as a proportion of pythons available to be captured. Aims: Our primary aim was to conduct a trap trial for capturing invasive pythons in an area east of Everglades National Park, where many pythons had been captured in previous years, to assess the efficacy of traps for population control. We also aimed to compare results of visual surveys with trap capture rates, to determine capture rates of non-target species, and to assess capture rates as a proportion of resident pythons in the study area. Methods: We conducted a medium-scale (6053 trap nights) experiment using two types of attractant traps baited with live rats in the Frog Pond area east of Everglades National Park. We also conducted standardised and opportunistic visual surveys in the trapping area. Following the trap trial, the area was disc harrowed to expose pythons and allow calculation of an index of the number of resident pythons. Key results: We captured three pythons and 69 individuals of various rodent, amphibian, and reptile species in traps. Eleven pythons were discovered during disc harrowing operations, as were large numbers of rodents.

  2. Extending and embedding the Python interpreter

    NARCIS (Netherlands)

    G. van Rossum (Guido)

    1995-01-01

    textabstractPython is an interpreted, object-oriented programming language. This document describes how to write modules in C or C++ to extend the Python interpreter with new modules. Those modules can define new functions but also new object types and their methods. The document also describes

  3. DeepPy: Pythonic deep learning

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo

    This technical report introduces DeepPy – a deep learning framework built on top of NumPy with GPU acceleration. DeepPy bridges the gap between highperformance neural networks and the ease of development from Python/NumPy. Users with a background in scientific computing in Python will quickly...

  4. On Parallel Software Engineering Education Using Python

    Science.gov (United States)

    Marowka, Ami

    2018-01-01

    Python is gaining popularity in academia as the preferred language to teach novices serial programming. The syntax of Python is clean, easy, and simple to understand. At the same time, it is a high-level programming language that supports multi programming paradigms such as imperative, functional, and object-oriented. Therefore, by default, it is…

  5. Desarrollo CUDA en Java y Python

    OpenAIRE

    Pérez Sánchez, José Alejandro

    2013-01-01

    Análisis de desarrollo paralelo CUDA en lenguajes Java y Python, utilizando JCuda, RootBeer, PyCuda y Anaconda Accelerate. Anàlisi de desenvolupament paral·lel CUDA en llenguatges Java i Python, utilitzant JCuda, RootBeer, PyCuda i Anaconda Accelerate. Bachelor thesis for the Computer science program on Computer architecture and operating systems.

  6. Learning selenium testing tools with Python

    CERN Document Server

    Gundecha, Unmesh

    2014-01-01

    If you are a quality testing professional, or a software or web application developer looking to create automation test scripts for your web applications, with an interest in Python, then this is the perfect guide for you. Python developers who need to do Selenium testing need not learn Java, as they can directly use Selenium for testing with this book.

  7. Optics simulations: a Python workshop

    Science.gov (United States)

    Ghalila, H.; Ammar, A.; Varadharajan, S.; Majdi, Y.; Zghal, M.; Lahmar, S.; Lakshminarayanan, V.

    2017-08-01

    Numerical simulations allow teachers and students to indirectly perform sophisticated experiments that cannot be realizable otherwise due to cost and other constraints. During the past few decades there has been an explosion in the development of numerical tools concurrently with open source environments such as Python software. This availability of open source software offers an incredible opportunity for advancing teaching methodologies as well as in research. More specifically it is possible to correlate theoretical knowledge with experimental measurements using "virtual" experiments. We have been working on the development of numerical simulation tools using the Python program package and we have concentrated on geometric and physical optics simulations. The advantage of doing hands-on numerical experiments is that it allows the student learner to be an active participant in the pedagogical/learning process rather than playing a passive role as in the traditional lecture format. Even in laboratory classes because of constraints of space, lack of equipment and often-large numbers of students, many students play a passive role since they work in groups of 3 or more students. Furthermore these new tools help students get a handle on numerical methods as well simulations and impart a "feel" for the physics under investigation.

  8. TEACHING ALGORITHMIZATION AND PROGRAMMING USING PYTHON LANGUAGE

    Directory of Open Access Journals (Sweden)

    M. Lvov

    2014-07-01

    Full Text Available The article describes requirements to educational programming languages and considers the use of Python as the first programming language. The issues of introduction of this programming language into teaching and replacing Pascal by Python are examined. The advantages of such approach are regarded. The comparison of popular programming languages is represented from the point of view of their convenience of use for teaching algorithmization and programming. Python supports lots of programming paradigms: structural, object-oriented, functional, imperative and aspect-oriented, and learning can be started without any preparation. There is one more advantage of the language: all algorithms are written easily and structurally in Python. Therefore, due to all mentioned above, it is possible to affirm that Python pretends to become a decent replacement for educational programming language PASCAL both at schools and on the first courses of higher education establishments.

  9. Test-beam with Python

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    The talk will show the current implementation of the software tool developed by Silab (Bonn) and Oxford University to analyze test beam data with Mimosa telescope. Data collected from the telescope are merged with hits recorded on pixel detectors with a FE-I4 chips, the official read-out chip of the Atlas Pixel Detector. The software tool used to collect data, pyBAR, is developed with Python as well. The test-beam analysis tool parses the data-sets, recreates the tracks, aligns the telescope planes and allows to investigate the detectors spatial properties with high resolution. This has just allowed to study the properties of brand new devices that stand as possible candidate to replace the current pixel detector in Atlas.

  10. Pyomo optimization modeling in Python

    CERN Document Server

    Hart, William E; Watson, Jean-Paul; Woodruff, David L; Hackebeil, Gabriel A; Nicholson, Bethany L; Siirola, John D

    2017-01-01

    This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. This second edition provides an expanded presentation of Pyomo’s modeling capabilities, providing a broader description of the software that will enable the user to develop and optimize models. Introductory chapters have been revised to extend tutorials; chapters that discuss advanced features now include the new functionalities added to Pyomo since the first edition including generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming. Pyomo is an open source software package fo...

  11. Reflection-Based Python-C++ Bindings

    International Nuclear Information System (INIS)

    Generowicz, Jacek; Lavrijsen, Wim T.L.P.; Marino, Massimo; Mato, Pere

    2004-01-01

    Python is a flexible, powerful, high-level language with excellent interactive and introspective capabilities and a very clean syntax. As such, it can be a very effective tool for driving physics analysis. Python is designed to be extensible in low-level C-like languages, and its use as a scientific steering language has become quite widespread. To this end, existing and custom-written C or C++ libraries are bound to the Python environment as so-called extension modules. A number of tools for easing the process of creating such bindings exist, such as SWIG and Boost. Python. Yet, the process still requires a considerable amount of effort and expertise. The C++ language has few built-in introspective capabilities, but tools such as LCGDict and CINT add this by providing so-called dictionaries: libraries that contain information about the names, entry points, argument types, etc. of other libraries. The reflection information from these dictionaries can be used for the creation of bindings and so the process can be fully automated, as dictionaries are already provided for many end-user libraries for other purposes, such as object persistency. PyLCGDict is a Python extension module that uses LCG dictionaries, as PyROOT uses CINT reflection information, to allow /cwPython users to access C++ libraries with essentially no preparation on the users' behalf. In addition, and in a similar way, PyROOT gives ROOT users access to Python libraries

  12. Python : the holy grail of programming

    CERN Multimedia

    2006-01-01

    From 3 to 5 July, CERN hosted the fifth EuroPython Conference bringing together 300 users of Python, an open source programming language, which is more and more appreciated, especially at CERN. The local organisation of Euopython 2006 was managed by a small team from the PH/SFT group. Above, David Quarrie presenting the use of Python in Atlas analyses. If you visited Building 40 at the beginning of July, you may have come across a long orange and yellow snake. This had no relation with the Football World Championship! It was just the mascot of the fifth EuroPython Conference that saw almost 300 software developers, designers and business people gathering at CERN for the annual meeting of the European Python community. Python is an open source programming language actively used in industry and academia for a wide variety of purposes. As CERN decided to host this conference, it is perhaps not surprising to learn that Python is increasingly used in our Laboratory in both computing and physics application domai...

  13. Beginning programming with Python for dummies

    CERN Document Server

    Mueller, John Paul

    2014-01-01

    Learn Python-the fun and easy way-and get in the programming game today! Python is one of the fastest growing programming languages, and no wonder. It requires three to five times less time than developing in Java, is a great building block for learning both procedural and object-oriented programming concepts, and is an ideal language for data analysis. Beginning Programming with Python For Dummies is the perfect guide to this dynamic and powerful programming language-even if you''ve never coded before! Author John Paul Mueller draws on his vast programming knowledge and experience to guide yo

  14. Building probabilistic graphical models with Python

    CERN Document Server

    Karkera, Kiran R

    2014-01-01

    This is a short, practical guide that allows data scientists to understand the concepts of Graphical models and enables them to try them out using small Python code snippets, without being too mathematically complicated. If you are a data scientist who knows about machine learning and want to enhance your knowledge of graphical models, such as Bayes network, in order to use them to solve real-world problems using Python libraries, this book is for you. This book is intended for those who have some Python and machine learning experience, or are exploring the machine learning field.

  15. Postprandial morphological response of the intestinal epithelium of the Burmese python (Python molurus).

    OpenAIRE

    Lignot, J.H.; Helmstetter, C.; Secor, S.M.

    2005-01-01

    The postprandial morphological changes of the intestinal epithelium of Burmese pythons were examined using fasting pythons and at eight time points after feeding. In fasting pythons, tightly packed enterocytes possess very short microvilli and are arranged in a pseudostratified fashion. Enterocyte width increases by 23% within 24 h postfeeding, inducing significant increases in villus length and intestinal mass. By 6 days postfeeding, enterocyte volume had peaked, following as much as an 80% ...

  16. Training course "Porting code from Matlab to Python"

    OpenAIRE

    Diaz, Sandra; Klijn, Wouter; Deepu, Rajalekshmi; Peyser, Alexander; Oden, Lena

    2017-01-01

    Python is becoming a popular language for scientific applications and is increasingly used for high performance computing. In this course we want to introduce Matlab programmers to the usage of Python. Matlab and Python have a comparable language philosophy, but Python can offer better performance using its optimizations and parallelization interfaces. Python also increases the portability and flexibility (interaction with other open source and proprietary software packages) of solutions, and...

  17. Exploring and Analyzing Network Data with Python

    Directory of Open Access Journals (Sweden)

    John Ladd

    2017-08-01

    Full Text Available This lesson introduces network metrics and how to draw conclusions from them when working with humanities data. You will learn how to use the NetworkX Python package to produce and work with these network statistics.

  18. Exploring and Analyzing Network Data with Python

    OpenAIRE

    John Ladd; Jessica Otis; Christopher N. Warren; Scott Weingart

    2017-01-01

    This lesson introduces network metrics and how to draw conclusions from them when working with humanities data. You will learn how to use the NetworkX Python package to produce and work with these network statistics.

  19. Python for probability, statistics, and machine learning

    CERN Document Server

    Unpingco, José

    2016-01-01

    This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowl...

  20. Python 3 Web Development Beginner's Guide

    CERN Document Server

    Anders, Michel

    2011-01-01

    Part of Packt's Beginner's Guide Series, this book follows a sample application, with lots of screenshots, to help you get to grips with the techniques as quickly as possible. Moderately experienced Python programmers who want to learn how to create fairly complex, database-driven, cross browser compatible web apps that are maintainable and look good will find this book of most use. All key technologies except for Python 3 are explained in detail.

  1. Visualization of the CMS python configuration system

    International Nuclear Information System (INIS)

    Erdmann, M; Fischer, R; Klimkovich, T; Mueller, G; Steggemann, J; Hegner, B; Hinzmann, A

    2010-01-01

    The job configuration system of the CMS experiment is based on the Python programming language. Software modules and their order of execution are both represented by Python objects. In order to investigate and verify configuration parameters and dependencies naturally appearing in modular software, CMS employs a graphical tool. This tool visualizes the configuration objects, their dependencies, and the information flow. Furthermore it can be used for documentation purposes. The underlying software concepts as well as the visualization are presented.

  2. Julia and Python in Astronomy: Better Together

    Science.gov (United States)

    Barbary, Kyle

    2016-03-01

    Astronomers love Python because it is open source, easy to learn, and has a tremendous ecosystem for scientific computing. The Julia programming language has many of those same characteristics. In this talk, I'll discuss the use of Julia in astronomy and the growing ecosystem of astronomy packages, particularly those managed by the JuliaAstro organization (http://JuliaAstro.github.io). Most importantly, I will highlight some areas ripe for collaboration between Python and Julia developers in astronomy.

  3. Visualization of the CMS Python Configuration System

    CERN Document Server

    Erdmann, M; Hegner, B; Hinzmann, A; Klimkovich, T; Muller, G; Steggemann, J

    2010-01-01

    The job configuration system of the CMS experiment is based on the Python programming language. Software modules and their order of execution are both represented by Python objects. In order to investigate and verify configuration parameters and dependencies naturally appearing in modular software, CMS employs a graphical tool. This tool visualizes the configuration objects, their dependencies, and the information flow. Furthermore it can be used for documentation purposes. The underlying software concepts as well as the visualization are presented.

  4. Introduction to Python for CMF Authority Users

    Energy Technology Data Exchange (ETDEWEB)

    Pritchett-Sheats, Lori A. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-03-14

    This talk is a very broad over view of Python that highlights key features in the language used in the Common Model Framework (CMF). I assume that the audience has some programming experience in a shell scripting language (C shell, Bash, PERL) or other high level language (C/C++/ Fortran). The talk will cover Python data types, classes (objects) and basic programming constructs. The talk concludes with slides describing how I developed the basic classes for a TITANS homework assignment.

  5. Python-Based Applications for Hydrogeological Modeling

    Science.gov (United States)

    Khambhammettu, P.

    2013-12-01

    Python is a general-purpose, high-level programming language whose design philosophy emphasizes code readability. Add-on packages supporting fast array computation (numpy), plotting (matplotlib), scientific /mathematical Functions (scipy), have resulted in a powerful ecosystem for scientists interested in exploratory data analysis, high-performance computing and data visualization. Three examples are provided to demonstrate the applicability of the Python environment in hydrogeological applications. Python programs were used to model an aquifer test and estimate aquifer parameters at a Superfund site. The aquifer test conducted at a Groundwater Circulation Well was modeled with the Python/FORTRAN-based TTIM Analytic Element Code. The aquifer parameters were estimated with PEST such that a good match was produced between the simulated and observed drawdowns. Python scripts were written to interface with PEST and visualize the results. A convolution-based approach was used to estimate source concentration histories based on observed concentrations at receptor locations. Unit Response Functions (URFs) that relate the receptor concentrations to a unit release at the source were derived with the ATRANS code. The impact of any releases at the source could then be estimated by convolving the source release history with the URFs. Python scripts were written to compute and visualize receptor concentrations for user-specified source histories. The framework provided a simple and elegant way to test various hypotheses about the site. A Python/FORTRAN-based program TYPECURVEGRID-Py was developed to compute and visualize groundwater elevations and drawdown through time in response to a regional uniform hydraulic gradient and the influence of pumping wells using either the Theis solution for a fully-confined aquifer or the Hantush-Jacob solution for a leaky confined aquifer. The program supports an arbitrary number of wells that can operate according to arbitrary schedules. The

  6. Postprandial increase of oleoylethanolamide mobilization in small intestine of the Burmese python (Python molurus)

    DEFF Research Database (Denmark)

    Astarita, Giuseppe; Rourke, Bryan C; Andersen, Johnnie Bremholm

    2006-01-01

    to the induction of between-meal satiety. Here we examined whether feeding-induced OEA mobilization also occurs in Burmese pythons (Python molurus), a species of ambush-hunting snakes that consumes huge meals after months of fasting and undergoes massive feeding-dependent changes in gastrointestinal hormonal...... release and gut morphology. Using liquid-chromatography/mass-spectrometry (LC/MS), we measured OEA levels in the gastrointestinal tract of fasted (28 days) and fed (48h after feeding) pythons. We observed a nearly 300-fold increase in OEA levels in the small intestine of fed compared to fasted animals......-unsaturated, but not polyunsaturated fatty-acid ethanolamides (FAE) in the small intestine of fed pythons. The identification of OEA and other FAEs in the gastrointestinal tract of Python molurus suggests that this class of lipid messengers may be widespread among vertebrate groups and may represent an evolutionarily ancient means...

  7. SunPy—Python for solar physics

    Science.gov (United States)

    SunPy Community; Mumford, Stuart J.; Christe, Steven; Pérez-Suárez, David; Ireland, Jack; Shih, Albert Y.; Inglis, Andrew R.; Liedtke, Simon; Hewett, Russell J.; Mayer, Florian; Hughitt, Keith; Freij, Nabil; Meszaros, Tomas; Bennett, Samuel M.; Malocha, Michael; Evans, John; Agrawal, Ankit; Leonard, Andrew J.; Robitaille, Thomas P.; Mampaey, Benjamin; Campos-Rozo, Jose Iván; Kirk, Michael S.

    2015-01-01

    This paper presents SunPy (version 0.5), a community-developed Python package for solar physics. Python, a free, cross-platform, general-purpose, high-level programming language, has seen widespread adoption among the scientific community, resulting in the availability of a large number of software packages, from numerical computation (NumPy, SciPy) and machine learning (scikit-learn) to visualization and plotting (matplotlib). SunPy is a data-analysis environment specializing in providing the software necessary to analyse solar and heliospheric data in Python. SunPy is open-source software (BSD licence) and has an open and transparent development workflow that anyone can contribute to. SunPy provides access to solar data through integration with the Virtual Solar Observatory (VSO), the Heliophysics Event Knowledgebase (HEK), and the HELiophysics Integrated Observatory (HELIO) webservices. It currently supports image data from major solar missions (e.g., SDO, SOHO, STEREO, and IRIS), time-series data from missions such as GOES, SDO/EVE, and PROBA2/LYRA, and radio spectra from e-Callisto and STEREO/SWAVES. We describe SunPy's functionality, provide examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing tools already available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy.

  8. SunPy—Python for solar physics

    International Nuclear Information System (INIS)

    Community, The SunPy; Mumford, Stuart J; Freij, Nabil; Bennett, Samuel M; Christe, Steven; Ireland, Jack; Shih, Albert Y; Inglis, Andrew R; Pérez-Suárez, David; Liedtke, Simon; Hewett, Russell J; Mayer, Florian; Hughitt, Keith; Meszaros, Tomas; Malocha, Michael; Evans, John; Agrawal, Ankit; Leonard, Andrew J; Robitaille, Thomas P; Mampaey, Benjamin

    2015-01-01

    This paper presents SunPy (version 0.5), a community-developed Python package for solar physics. Python, a free, cross-platform, general-purpose, high-level programming language, has seen widespread adoption among the scientific community, resulting in the availability of a large number of software packages, from numerical computation (NumPy, SciPy) and machine learning (scikit-learn) to visualization and plotting (matplotlib). SunPy is a data-analysis environment specializing in providing the software necessary to analyse solar and heliospheric data in Python. SunPy is open-source software (BSD licence) and has an open and transparent development workflow that anyone can contribute to. SunPy provides access to solar data through integration with the Virtual Solar Observatory (VSO), the Heliophysics Event Knowledgebase (HEK), and the HELiophysics Integrated Observatory (HELIO) webservices. It currently supports image data from major solar missions (e.g., SDO, SOHO, STEREO, and IRIS), time-series data from missions such as GOES, SDO/EVE, and PROBA2/LYRA, and radio spectra from e-Callisto and STEREO/SWAVES. We describe SunPy's functionality, provide examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing tools already available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy. (paper)

  9. An introduction to Python and computer programming

    CERN Document Server

    Zhang, Yue

    2015-01-01

    This book introduces Python programming language and fundamental concepts in algorithms and computing. Its target audience includes students and engineers with little or no background in programming, who need to master a practical programming language and learn the basic thinking in computer science/programming. The main contents come from lecture notes for engineering students from all disciplines, and has received high ratings. Its materials and ordering have been adjusted repeatedly according to classroom reception. Compared to alternative textbooks in the market, this book introduces the underlying Python implementation of number, string, list, tuple, dict, function, class, instance and module objects in a consistent and easy-to-understand way, making assignment, function definition, function call, mutability and binding environments understandable inside-out. By giving the abstraction of implementation mechanisms, this book builds a solid understanding of the Python programming language.

  10. modlAMP: Python for antimicrobial peptides.

    Science.gov (United States)

    Müller, Alex T; Gabernet, Gisela; Hiss, Jan A; Schneider, Gisbert

    2017-09-01

    We have implemented the lecular esign aboratory's nti icrobial eptides package ( ), a Python-based software package for the design, classification and visual representation of peptide data. modlAMP offers functions for molecular descriptor calculation and the retrieval of amino acid sequences from public or local sequence databases, and provides instant access to precompiled datasets for machine learning. The package also contains methods for the analysis and representation of circular dichroism spectra. The modlAMP Python package is available under the BSD license from URL http://doi.org/10.5905/ethz-1007-72 or via pip from the Python Package Index (PyPI). gisbert.schneider@pharma.ethz.ch. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  11. Python passive network mapping P2NMAP

    CERN Document Server

    Hosmer, Chet

    2015-01-01

    Python Passive Network Mapping: P2NMAP is the first book to reveal a revolutionary and open source method for exposing nefarious network activity. The ""Heartbleed"" vulnerability has revealed significant weaknesses within enterprise environments related to the lack of a definitive mapping of network assets. In Python Passive Network Mapping, Chet Hosmer shows you how to effectively and definitively passively map networks. Active or probing methods to network mapping have traditionally been used, but they have many drawbacks - they can disrupt operations, crash systems, and - most important

  12. Feasibility of Python in teaching programming

    Directory of Open Access Journals (Sweden)

    Rafael Martínez Estévez

    2014-03-01

    Full Text Available Given the diversity of the objectives of the programming courses in the Cuban educational system and the training of teachers, it is not easy to decide the language to be used in each case. The intention of this article is to bring to debate to our context a trend that has been growing in the last decade: Python as a first programming language. The aim of this study is to compile some inter national experiences in the use of Python in introductory programming courses, also analyzing their advantages and disadvantages.

  13. Data Visualization within the Python ecosystem

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    Data analysis is integral to what we do at CERN. Data visualization is at the foundation of this workflow and is also an important part of the python stack. Python's plotting ecosystem offers numerous open source solutions. These solutions can offer ease of use, detailed configuration, interactivity and web readiness. This talk will cover three of the most robust and supported packages, matplotlib, bokeh, and plotly. It aims to provide an overview of these packages. In addition, give suggestions to where these tools might fit in an analysis workflow.

  14. Raspberry Pi cookbook for Python programmers

    CERN Document Server

    Cox, Tim

    2014-01-01

    ""Raspberry Pi Cookbook for Python Programmers"" is written in a Cookbook format, presenting examples in the style of recipes.This allows you to go directly to your topic of interest, or follow topics throughout a chapter to gain a thorough in-depth knowledge.The aim of this book is to bring you a broad range of Python 3 examples and practical ideas which you can develop to suit your own requirements. By modifying and combining the examples to create your own projects you learn far more effectively with a much greater understanding. Each chapter is designed to become a foundation for further e

  15. CSB: a Python framework for structural bioinformatics.

    Science.gov (United States)

    Kalev, Ivan; Mechelke, Martin; Kopec, Klaus O; Holder, Thomas; Carstens, Simeon; Habeck, Michael

    2012-11-15

    Computational Structural Biology Toolbox (CSB) is a cross-platform Python class library for reading, storing and analyzing biomolecular structures with rich support for statistical analyses. CSB is designed for reusability and extensibility and comes with a clean, well-documented API following good object-oriented engineering practice. Stable release packages are available for download from the Python Package Index (PyPI) as well as from the project's website http://csb.codeplex.com. ivan.kalev@gmail.com or michael.habeck@tuebingen.mpg.de

  16. Python for signal processing featuring IPython notebooks

    CERN Document Server

    Unpingco, José

    2013-01-01

    This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to ""experiment and learn"" as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remai

  17. THE PYTHON SHELL FOR THE ORBIT CODE

    Energy Technology Data Exchange (ETDEWEB)

    Shishlo, Andrei P [ORNL; Gorlov, Timofey V [ORNL; Holmes, Jeffrey A [ORNL

    2009-01-01

    A development of a Python driver shell for the ORBIT simulation code is presented. The original ORBIT code uses the SuperCode shell to organize accelerator-related simulations. It is outdated, unsupported, and it is an obstacle to future code development. The necessity and consequences of replacing the old shell language are discussed. A set of core modules and extensions that are currently in PyORBIT are presented. They include particle containers, parsers for MAD and SAD lattice files, a Python wrapper for MPI libraries, space charge calculators, TEAPOT trackers, and a laser stripping extension module.

  18. Next-Generation Web Frameworks in Python

    CERN Document Server

    Daly, Liza

    2007-01-01

    With its flexibility, readability, and maturecode libraries, Python is a naturalchoice for developing agile and maintainableweb applications. Severalframeworks have emerged in the last fewyears that share ideas with Ruby on Railsand leverage the expressive nature of Python.This Short Cut will tell you whatyou need to know about the hottest fullstackframeworks: Django, Pylons, andTurboGears. Their philosophies, relativestrengths, and development status aredescribed in detail. What you won't find out is, "Which oneshould I use?" The short answer is thatall of them can be used to build web appl

  19. Building machine learning systems with Python

    CERN Document Server

    Richert, Willi

    2013-01-01

    This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Python developers who want to learn about and build Machine Learning into their projects, or who want to pro

  20. DeepPy: Pythonic deep learning

    OpenAIRE

    Larsen, Anders Boesen Lindbo

    2016-01-01

    This technical report introduces DeepPy – a deep learning framework built on top of NumPy with GPU acceleration. DeepPy bridges the gap between highperformance neural networks and the ease of development from Python/NumPy. Users with a background in scientific computing in Python will quickly be able to understand and change the DeepPy codebase as it is mainly implemented using high-level NumPy primitives. Moreover, DeepPy supports complex network architectures by letting the user compose mat...

  1. Rapid microsatellite marker development using next generation pyrosequencing to inform invasive Burmese python -- Python molurus bivittatus -- management

    Science.gov (United States)

    Hunter, Margaret E.; Hart, Kristen M.

    2013-01-01

    Invasive species represent an increasing threat to native ecosystems, harming indigenous taxa through predation, habitat modification, cross-species hybridization and alteration of ecosystem processes. Additionally, high economic costs are associated with environmental damage, restoration and control measures. The Burmese python, Python molurus bivittatus, is one of the most notable invasive species in the US, due to the threat it poses to imperiled species and the Greater Everglades ecosystem. To address population structure and relatedness, next generation sequencing was used to rapidly produce species-specific microsatellite loci. The Roche 454 GS-FLX Titanium platform provided 6616 di-, tri- and tetra-nucleotide repeats in 117,516 sequences. Using stringent criteria, 24 of 26 selected tri- and tetra-nucleotide loci were polymerase chain reaction (PCR) amplified and 18 were polymorphic. An additional six cross-species loci were amplified, and the resulting 24 loci were incorporated into eight PCR multiplexes. Multi-locus genotypes yielded an average of 61% (39%–77%) heterozygosity and 3.7 (2–6) alleles per locus. Population-level studies using the developed microsatellites will track the invasion front and monitor population-suppression dynamics. Additionally, cross-species amplification was detected in the invasive Ball, P. regius, and Northern African python, P. sebae. These markers can be used to address the hybridization potential of Burmese pythons and the larger, more aggressive P. sebae.

  2. Programming ArcGIS 10.1 with Python cookbook

    CERN Document Server

    Pimpler, Eric

    2013-01-01

    This book is written in a helpful, practical style with numerous hands-on recipes and chapters to help you save time and effort by using Python to power ArcGIS to create shortcuts, scripts, tools, and customizations.""Programming ArcGIS 10.1 with Python Cookbook"" is written for GIS professionals who wish to revolutionize their ArcGIS workflow with Python. Basic Python or programming knowledge is essential(?).

  3. TensorLy: Tensor Learning in Python

    NARCIS (Netherlands)

    Kossaifi, Jean; Panagakis, Yannis; Pantic, Maja

    2016-01-01

    Tensor methods are gaining increasing traction in machine learning. However, there are scant to no resources available to perform tensor learning and decomposition in Python. To answer this need we developed TensorLy. TensorLy is a state of the art general purpose library for tensor learning.

  4. Python for Education: The Exact Cover Problem

    Directory of Open Access Journals (Sweden)

    2011-06-01

    Full Text Available

    Python implementation of Algorithm X by Knuth is presented.
    Algorithm X finds all solutions to the exact cover problem.
    The exemplary results for pentominoes, Latin squares and Sudoku
    are given.

  5. Julia and Python in Astronomy: Better Together

    OpenAIRE

    Barbary, Kyle

    2016-01-01

    Astronomers love Python because it is open source, easy to learn, and has a tremendous ecosystem for scientific computing. The Julia programming language has many of those same characteristics. In this talk, I discuss Julia, its use in astronomy and the growing ecosystem of astronomy packages, particularly those managed by the JuliaAstro organization (http://JuliaAstro.github.io).

  6. MGtoolkit: A python package for implementing metagraphs

    Science.gov (United States)

    Ranathunga, D.; Nguyen, H.; Roughan, M.

    In this paper we present MGtoolkit: an open-source Python package for implementing metagraphs - a first of its kind. Metagraphs are commonly used to specify and analyse business and computer-network policies alike. MGtoolkit can help verify such policies and promotes learning and experimentation with metagraphs. The package currently provides purely textual output for visualising metagraphs and their analysis results.

  7. PyXNAT: XNAT in Python

    Directory of Open Access Journals (Sweden)

    Yannick eSchwartz

    2012-05-01

    Full Text Available As neuroimaging databases grow in size and complexity, the time researchers spend investigating and managing the data increases to the expense of data analysis. As a result, investigators rely more and more heavily on scripting using high-level languages to automate data management and processing tasks. For this, a structured and programatic access to the data store is necessary. Web services are a first step toward this goal. They however lack in functionality and ease of use because they provide only low level interfaces to databases. We introduce here {PyXNAT}, a Python module that interacts with The Extensible Neuroimaging Archive Toolkit (XNAT through native Python calls across multiple operating systems. The choice of Python enables {PyXNAT} to expose the XNAT Web Services and unify their features with a higher level and more expressive language. {PyXNAT} provides XNAT users direct access to all the scientific packages in Python. Finally {PyXNAT} aims to be efficient and easy to use, both as a backend library to build XNAT clients and as an alternative frontend from the command line.

  8. Python scripting in the Nengo simulator

    Directory of Open Access Journals (Sweden)

    Terrence C Stewart

    2009-03-01

    Full Text Available Nengo is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the Neural Engineering Framework (NEF. This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide 1 more realistic boundary conditions for the neural components, and 2 more realistic sub-components for the larger cognitive models.

  9. Challenges to a molecular approach to prey identification in the Burmese python, Python molurus bivittatus

    Directory of Open Access Journals (Sweden)

    Bryan G. Falk

    2015-11-01

    Full Text Available Molecular approaches to prey identification are increasingly useful in elucidating predator–prey relationships, and we aimed to investigate the feasibility of these methods to document the species identities of prey consumed by invasive Burmese pythons in Florida. We were particularly interested in the diet of young snakes, because visual identification of prey from this size class has proven difficult. We successfully extracted DNA from the gastrointestinal contents of 43 young pythons, as well as from several control samples, and attempted amplification of DNA mini-barcodes, a 130-bp region of COX1. Using a PNA clamp to exclude python DNA, we found that prey DNA was not present in sufficient quality for amplification of this locus in 86% of our samples. All samples from the GI tracts of young pythons contained only hair, and the six samples we were able to identify to species were hispid cotton rats. This suggests that young Burmese pythons prey predominantly on small mammals and that prey diversity among snakes of this size class is low. We discuss prolonged gastrointestinal transit times and extreme gastric breakdown as possible causes of DNA degradation that limit the success of a molecular approach to prey identification in Burmese pythons.

  10. Challenges to a molecular approach to prey identification in the Burmese python, Python molurus bivittatus

    Science.gov (United States)

    Falk, Bryan; Reed, Robert N.

    2015-01-01

    Molecular approaches to prey identification are increasingly useful in elucidating predator–prey relationships, and we aimed to investigate the feasibility of these methods to document the species identities of prey consumed by invasive Burmese pythons in Florida. We were particularly interested in the diet of young snakes, because visual identification of prey from this size class has proven difficult. We successfully extracted DNA from the gastrointestinal contents of 43 young pythons, as well as from several control samples, and attempted amplification of DNA mini-barcodes, a 130-bp region of COX1. Using a PNA clamp to exclude python DNA, we found that prey DNA was not present in sufficient quality for amplification of this locus in 86% of our samples. All samples from the GI tracts of young pythons contained only hair, and the six samples we were able to identify to species were hispid cotton rats. This suggests that young Burmese pythons prey predominantly on small mammals and that prey diversity among snakes of this size class is low. We discuss prolonged gastrointestinal transit times and extreme gastric breakdown as possible causes of DNA degradation that limit the success of a molecular approach to prey identification in Burmese pythons

  11. A New Python Library for Spectroscopic Analysis with MIDAS Style

    Science.gov (United States)

    Song, Y.; Luo, A.; Zhao, Y.

    2013-10-01

    The ESO MIDAS is a system for astronomers to analyze data which many astronomers are using. Python is a high level script language and there are many applications for astronomical data process. We are releasing a new Python library which realizes some MIDAS commands in Python. People can use it to write a MIDAS style Python code. We call it PydasLib. It is a Python library based on ESO MIDAS functions, which is easily used by astronomers who are familiar with the usage of MIDAS.

  12. Transliterating non-ASCII characters with Python

    Directory of Open Access Journals (Sweden)

    Seth Bernstein

    2013-10-01

    Full Text Available This lesson shows how to use Python to transliterate automatically a list of words from a language with a non-Latin alphabet to a standardized format using the American Standard Code for Information Interchange (ASCII characters. It builds on readers’ understanding of Python from the lessons “Viewing HTML Files,” “Working with Web Pages,” “From HTML to List of Words (part 1” and “Intro to Beautiful Soup.” At the end of the lesson, we will use the transliteration dictionary to convert the names from a database of the Russian organization Memorial from Cyrillic into Latin characters. Although the example uses Cyrillic characters, the technique can be reproduced with other alphabets using Unicode.

  13. Gala: A Python package for galactic dynamics

    Science.gov (United States)

    Price-Whelan, Adrian M.

    2017-10-01

    Gala is an Astropy-affiliated Python package for galactic dynamics. Python enables wrapping low-level languages (e.g., C) for speed without losing flexibility or ease-of-use in the user-interface. The API for Gala was designed to provide a class-based and user-friendly interface to fast (C or Cython-optimized) implementations of common operations such as gravitational potential and force evaluation, orbit integration, dynamical transformations, and chaos indicators for nonlinear dynamics. Gala also relies heavily on and interfaces well with the implementations of physical units and astronomical coordinate systems in the Astropy package (astropy.units and astropy.coordinates). Gala was designed to be used by both astronomical researchers and by students in courses on gravitational dynamics or astronomy. It has already been used in a number of scientific publications and has also been used in graduate courses on Galactic dynamics to, e.g., provide interactive visualizations of textbook material.

  14. Python for Collective Intelligence and Collaborative Filtering

    Directory of Open Access Journals (Sweden)

    2010-09-01

    Full Text Available This paper will define the two terms Collective Intelligence and Collaborative Filtering and discuss how these two ideas can be used to create personally relevant filters allowing end users more personalized access to information on their chosen topics of interest.  In addition various mathematical models used to filter data and compare preferences and their corresponding pythonic implementations will be discussed.  Finally a simple example using web API’s and Collective Intelligence algorithms will be demonstrated to provide an idea of the type of things that can be achieved, relatively easily, using python for Collective Intelligence and Collaborative Filtering.  This short abstract will be accompanied by a talk given at PyCon Asia 2010.

  15. Experimentally derived salinity tolerance of hatchling Burmese pythons (Python molurus bivittatus) from the Everglades, Florida (USA)

    Science.gov (United States)

    Hart, Kristen M.; Schofield, Pamela J.; Gregoire, Denise R.

    2012-01-01

    In a laboratory setting, we tested the ability of 24 non-native, wild-caught hatchling Burmese pythons (Python molurus bivittatus) collected in the Florida Everglades to survive when given water containing salt to drink. After a one-month acclimation period in the laboratory, we grouped snakes into three treatments, giving them access to water that was fresh (salinity of 0, control), brackish (salinity of 10), or full-strength sea water (salinity of 35). Hatchlings survived about one month at the highest marine salinity and about five months at the brackish-water salinity; no control animals perished during the experiment. These results are indicative of a "worst-case scenario", as in the laboratory we denied access to alternate fresh-water sources that may be accessible in the wild (e.g., through rainfall). Therefore, our results may underestimate the potential of hatchling pythons to persist in saline habitats in the wild. Because of the effect of different salinity regimes on survival, predictions of ultimate geographic expansion by non-native Burmese pythons that consider salt water as barriers to dispersal for pythons may warrant re-evaluation, especially under global climate change and associated sea-level-rise scenarios.

  16. MGtoolkit: A python package for implementing metagraphs

    Directory of Open Access Journals (Sweden)

    D. Ranathunga

    2017-01-01

    Full Text Available In this paper we present MGtoolkit : an open-source Python package for implementing metagraphs - a first of its kind. Metagraphs are commonly used to specify and analyse business and computer-network policies alike. MGtoolkit can help verify such policies and promotes learning and experimentation with metagraphs. The package currently provides purely textual output for visualising metagraphs and their analysis results.

  17. Towards green aviation with Python at petascale

    OpenAIRE

    Vincent, PE; Witherden, FD; Vermeire; Park, JS; Iyer

    2016-01-01

    Accurate simulation of unsteady turbulent flow is critical for improved design of greener aircraft that are quieter and more fuel-efficient. We demonstrate application of PyFR, a Python based computational fluid dynamics solver, to petascale simulation of such flow problems. Rationale behind algorithmic choices, which offer increased levels of accuracy and enable sustained computation at up to 58% of peak DP-FLOP/s on unstruc- tured grids, will be discussed in the context of modern hardware. ...

  18. Scikit-learn: Machine Learning in Python

    OpenAIRE

    Pedregosa, Fabian; Varoquaux, Gaël; Gramfort, Alexandre; Michel, Vincent; Thirion, Bertrand; Grisel, Olivier; Blondel, Mathieu; Prettenhofer, Peter; Weiss, Ron; Dubourg, Vincent; Vanderplas, Jake; Passos, Alexandre; Cournapeau, David; Brucher, Matthieu; Perrot, Matthieu

    2011-01-01

    International audience; Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic ...

  19. A Practical Python API for Querying AFLOWLIB

    OpenAIRE

    Rosenbrock, Conred W.

    2017-01-01

    Large databases such as aflowlib.org provide valuable data sources for discovering material trends through machine learning. Although a REST API and query language are available, there is a learning curve associated with the AFLUX language that acts as a barrier for new users. Additionally, the data is stored using non-standard serialization formats. Here we present a high-level API that allows immediate access to the aflowlib data using standard python operators and language features. It pro...

  20. MTpy: A Python toolbox for magnetotellurics

    Science.gov (United States)

    Krieger, Lars; Peacock, Jared R.

    2014-01-01

    We present the software package MTpy that allows handling, processing, and imaging of magnetotelluric (MT) data sets. Written in Python, the code is open source, containing sub-packages and modules for various tasks within the standard MT data processing and handling scheme. Besides the independent definition of classes and functions, MTpy provides wrappers and convenience scripts to call standard external data processing and modelling software.

  1. Osteosarcoma in a woma python (Aspidites ramsayi).

    Science.gov (United States)

    Cowan, M L; Monks, D J; Raidal, S R

    2011-12-01

    Osteosarcoma of the axial skeleton in an 18-month-old woma python (Aspidites ramsayi) is described. A subcutaneous mass overlying the costal arches enlarged progressively over a period of 5 months and, in that time, became ulcerated and more invasive of surrounding tissues. A punch biopsy of the lesion under general anaesthesia provided tissue for histopathology and diagnosis of low-grade osteosarcoma. © 2011 The Authors. Australian Veterinary Journal © 2011 Australian Veterinary Association.

  2. Predators in training: operant conditioning of novel behavior in wild Burmese pythons (Python molurus bivitattus).

    Science.gov (United States)

    Emer, Sherri A; Mora, Cordula V; Harvey, Mark T; Grace, Michael S

    2015-01-01

    Large pythons and boas comprise a group of animals whose anatomy and physiology are very different from traditional mammalian, avian and other reptilian models typically used in operant conditioning. In the current study, investigators used a modified shaping procedure involving successive approximations to train wild Burmese pythons (Python molurus bivitattus) to approach and depress an illuminated push button in order to gain access to a food reward. Results show that these large, wild snakes can be trained to accept extremely small food items, associate a stimulus with such rewards via operant conditioning and perform a contingent operant response to gain access to a food reward. The shaping procedure produced robust responses and provides a mechanism for investigating complex behavioral phenomena in massive snakes that are rarely studied in learning research.

  3. Pro Android Python with SL4A Writing Android Native Apps Using Python, Lua, and Beanshell

    CERN Document Server

    Ferrill, Paul

    2011-01-01

    Pro Android Python with SL4A is for programmers and hobbyists who want to write apps for Android devices without having to learn Java first. Paul Ferrill leads you from installing the Scripting Layer for Android (SL4A) to writing small scripts, to more complicated and interesting projects, and finally to uploading and packaging your programs to an Android device. Android runs scripts in many scripting languages, but Python, Lua, and Beanshell are particularly popular. Most programmers know more than one programming language, so that they have the best tool for whatever task they want to accomp

  4. HOPE: Just-in-time Python compiler for astrophysical computations

    Science.gov (United States)

    Akeret, Joel; Gamper, Lukas; Amara, Adam; Refregier, Alexandre

    2014-11-01

    HOPE is a specialized Python just-in-time (JIT) compiler designed for numerical astrophysical applications. HOPE focuses on a subset of the language and is able to translate Python code into C++ while performing numerical optimization on mathematical expressions at runtime. To enable the JIT compilation, the user only needs to add a decorator to the function definition. By using HOPE, the user benefits from being able to write common numerical code in Python while getting the performance of compiled implementation.

  5. Tangent: Automatic Differentiation Using Source Code Transformation in Python

    OpenAIRE

    van Merriënboer, Bart; Wiltschko, Alexander B.; Moldovan, Dan

    2017-01-01

    Automatic differentiation (AD) is an essential primitive for machine learning programming systems. Tangent is a new library that performs AD using source code transformation (SCT) in Python. It takes numeric functions written in a syntactic subset of Python and NumPy as input, and generates new Python functions which calculate a derivative. This approach to automatic differentiation is different from existing packages popular in machine learning, such as TensorFlow and Autograd. Advantages ar...

  6. Improvement of AMGA Python Client Library for Belle II Experiment

    Science.gov (United States)

    Kwak, Jae-Hyuck; Park, Geunchul; Huh, Taesang; Hwang, Soonwook

    2015-12-01

    This paper describes the recent improvement of the AMGA (ARDA Metadata Grid Application) python client library for the Belle II Experiment. We were drawn to the action items related to library improvement after in-depth discussions with the developer of the Belle II distributed computing system. The improvement includes client-side metadata federation support in python, DIRAC SSL library support as well as API refinement for synchronous operation. Some of the improvements have already been applied to the AMGA python client library as bundled with the Belle II distributed computing software. The recent mass Monte- Carlo (MC) production campaign shows that the AMGA python client library is reliably stable.

  7. Machine learning in Python essential techniques for predictive analysis

    CERN Document Server

    Bowles, Michael

    2015-01-01

    Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, d

  8. Re-imagining a Stata/Python Combination

    Science.gov (United States)

    Fiedler, James

    2013-01-01

    At last year's Stata Conference, I presented some ideas for combining Stata and the Python programming language within a single interface. Two methods were presented: in one, Python was used to automate Stata; in the other, Python was used to send simulated keystrokes to the Stata GUI. The first method has the drawback of only working in Windows, and the second can be slow and subject to character input limits. In this presentation, I will demonstrate a method for achieving interaction between Stata and Python that does not suffer these drawbacks, and I will present some examples to show how this interaction can be useful.

  9. Rapid web development using AJAX and Python

    International Nuclear Information System (INIS)

    Dolgert, A; Gibbons, L; Kuznetsov, V

    2008-01-01

    We discuss the rapid development of a large scale data discovery service for the CMS experiment using modern AJAX techniques and the Python language. To implement a flexible interface capable of accommodating several different versions of the DBS database, we used a 'stack' approach. Asynchronous JavaScript and XML (AJAX) together with an SQL abstraction layer, template engine, code generation tool and dynamic queries provide powerful tools for constructing interactive interfaces to large amounts of data. We show how the use of these tools, with rapid development in a modern scripting language, improved the scalability and usability of the the search interface for different user communities

  10. scikit-image: image processing in Python

    Directory of Open Access Journals (Sweden)

    Stéfan van der Walt

    2014-06-01

    Full Text Available scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image. More information can be found on the project homepage, http://scikit-image.org.

  11. scikit-image: image processing in Python.

    Science.gov (United States)

    van der Walt, Stéfan; Schönberger, Johannes L; Nunez-Iglesias, Juan; Boulogne, François; Warner, Joshua D; Yager, Neil; Gouillart, Emmanuelle; Yu, Tony

    2014-01-01

    scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image. More information can be found on the project homepage, http://scikit-image.org.

  12. Computational physics problem solving with Python

    CERN Document Server

    Landau, Rubin H; Bordeianu, Cristian C

    2015-01-01

    The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming. This upper-division text provides an unusually broad survey of the topics of modern computational physics from a multidisciplinary, computational science point of view. Its philosophy is rooted in learning by doing (assisted by many model programs), with new scientific materials as well as with the Python progr

  13. Scikit-spectra: Explorative Spectroscopy in Python

    Directory of Open Access Journals (Sweden)

    Adam Hughes

    2015-06-01

    Full Text Available Scikit-spectra is an intuitive framework for explorative spectroscopy in Python. Scikit-spectra leverages the Pandas library for powerful data processing to provide datastructures and an API designed for spectroscopy. Utilizing the new IPython Notebook widget system, scikit-spectra is headed towards a GUI when you want it, API when you need it approach to spectral analysis. As an application, analysis is presented of the surface-plasmon resonance shift in a solution of gold nanoparticles induced by proteins binding to the gold’s surface. Please refer to the scikit-spectra website for full documentation and support: http://hugadams.github.io/scikit-spectra/

  14. PYTHON-based Physics Analysis Environment for LHCb

    CERN Document Server

    Belyaev, I; Mato, P; Barrand, G; Tsaregorodtsev, A; de Oliveira, E; Tsaregorodtsev, A Yu; De Oliveira, E

    2004-01-01

    BENDER is the PYTHON based physics analysis application for LHCb. It combines the best features of the underlying GAUDI software architecture with the flexibility of the PYTHON scripting language and provides end-users with a friendly physics analysis oriented environment.

  15. Cost versus precision for approximate typing for Python

    NARCIS (Netherlands)

    Fritz, Levin; Hage, J.

    2017-01-01

    In this paper we describe a variation of monotone frameworks that enables us to perform approximate typing of Python, in particular for dealing with some of its more dynamic features such as first-class functions and Python's dynamic class system. We additionally introduce a substantial number of

  16. The zoonotic implications of pentastomiasis in the royal python ...

    African Journals Online (AJOL)

    The parasite was confirmed to be Armillifer spp (Pentastomid); this is the first recorded case of pentastomiasis in the royal python (Python regius) in Nigeria. This report may be an alert of the possibility of on-going zoonotic transmission of pentastomiasis from snake to man, especially in the sub-urban/rural areas of Nigeria ...

  17. SpiceyPy, a Python Wrapper for SPICE

    Science.gov (United States)

    Annex, A.

    2017-06-01

    SpiceyPy is an open source Python wrapper for the NAIF SPICE toolkit. It is available for macOS, Linux, and Windows platforms and for Python versions 2.7.x and 3.x as well as Anaconda. SpiceyPy can be installed by running: “pip install spiceypy.”

  18. pupyMPI - MPI implemented in pure Python

    DEFF Research Database (Denmark)

    Bromer, Rune; Hantho, Frederik; Vinter, Brian

    2011-01-01

    As distributed memory systems have become common, the de facto standard for communication is still the Message Passing Interface (MPI). pupyMPI is a pure Python implementation of a broad subset of the MPI 1.3 specifications that allows Python programmers to utilize multiple CPUs with datatypes...

  19. Pyndri: a Python Interface to the Indri Search Engine

    NARCIS (Netherlands)

    Van Gysel, C.; Kanoulas, E.; de Rijke, M.; Jose, J.M.; Hauff, C.; Altıngovde, I.S.; Song, D.; Albakour, D.; Watt, S.; Tait, J.

    2017-01-01

    We introduce pyndri, a Python interface to the Indri search engine. Pyndri allows to access Indri indexes from Python at two levels: (1) dictionary and tokenized document collection, (2) evaluating queries on the index. We hope that with the release of pyndri, we will stimulate reproducible, open

  20. Reimplementing a Multi-Agent System in Python

    DEFF Research Database (Denmark)

    Villadsen, Jørgen; Jensen, Andreas Schmidt; Ettienne, Mikko Berggren

    2013-01-01

    We provide a brief description of our Python-DTU system, including the overall design, the tools and the algorithms that we used in the Multi-Agent Programming Contest 2012, where the scenario was called Agents on Mars like in 2011. Our solution is an improvement of our Python-DTU system from last...

  1. Reimplementing a Multi-Agent System in Python

    DEFF Research Database (Denmark)

    Villadsen, Jørgen; Jensen, Andreas Schmidt; Ettienne, Mikko Berggren

    2012-01-01

    We provide a brief description of our Python-DTU system, including the overall design, the tools and the algorithms that we used in the Multi-Agent Programming Contest 2012, where the scenario was called Agents on Mars like in 2011. Our solution is an improvement of our Python-DTU system from last...

  2. Expyriment: A Python library for cognitive and neuroscientific experiments

    NARCIS (Netherlands)

    Krause, F.; Lindemann, O.

    2014-01-01

    Expyriment is an open-source and platform-independent lightweight Python library for designing and conducting timing-critical behavioral and neuroimaging experiments. The major goal is to provide a well-structured Python library for script-based experiment development, with a high priority being the

  3. Stimfit: quantifying electrophysiological data with Python

    Directory of Open Access Journals (Sweden)

    Segundo Jose Guzman

    2014-02-01

    Full Text Available Intracellular electrophysiological recordings provide crucial insights into elementary neuronal signals such as action potentials and synaptic currents. Analyzing and interpreting these signals is essential for a quantitative understanding of neuronal information processing, and requires both fast data visualization and ready access to complex analysis routines. To achieve this goal, we have developed Stimfit, a free software package for cellular neurophysiology with a Python scripting interface and a built-in Python shell. The program supports most standard file formats for cellular neurophysiology and other biomedical signals through the Biosig library. To quantify and interpret the activity of single neurons and communication between neurons, the program includes algorithms to characterize the kinetics of presynaptic action potentials and postsynaptic currents, estimate latencies between pre- and postsynaptic events, and detect spontaneously occurring events. We validate and benchmark these algorithms, give estimation errors, and provide sample use cases, showing that Stimfit represents an efficient, accessible and extensible way to accurately analyze and interpret neuronal signals.

  4. Python Program to Select HII Region Models

    Science.gov (United States)

    Miller, Clare; Lamarche, Cody; Vishwas, Amit; Stacey, Gordon J.

    2016-01-01

    HII regions are areas of singly ionized Hydrogen formed by the ionizing radiaiton of upper main sequence stars. The infrared fine-structure line emissions, particularly Oxygen, Nitrogen, and Neon, can give important information about HII regions including gas temperature and density, elemental abundances, and the effective temperature of the stars that form them. The processes involved in calculating this information from observational data are complex. Models, such as those provided in Rubin 1984 and those produced by Cloudy (Ferland et al, 2013) enable one to extract physical parameters from observational data. However, the multitude of search parameters can make sifting through models tedious. I digitized Rubin's models and wrote a Python program that is able to take observed line ratios and their uncertainties and find the Rubin or Cloudy model that best matches the observational data. By creating a Python script that is user friendly and able to quickly sort through models with a high level of accuracy, this work increases efficiency and reduces human error in matching HII region models to observational data.

  5. Writing analytic element programs in Python.

    Science.gov (United States)

    Bakker, Mark; Kelson, Victor A

    2009-01-01

    The analytic element method is a mesh-free approach for modeling ground water flow at both the local and the regional scale. With the advent of the Python object-oriented programming language, it has become relatively easy to write analytic element programs. In this article, an introduction is given of the basic principles of the analytic element method and of the Python programming language. A simple, yet flexible, object-oriented design is presented for analytic element codes using multiple inheritance. New types of analytic elements may be added without the need for any changes in the existing part of the code. The presented code may be used to model flow to wells (with either a specified discharge or drawdown) and streams (with a specified head). The code may be extended by any hydrogeologist with a healthy appetite for writing computer code to solve more complicated ground water flow problems. Copyright © 2009 The Author(s). Journal Compilation © 2009 National Ground Water Association.

  6. SunPy: Solar Physics in Python

    Science.gov (United States)

    Ryan, Daniel; Christe, Steven; Mumford, Stuart; Perez Suarez, David; Ireland, Jack; Shih, Albert Y.; Inglis, Andrew; Liedtke, Simon; Hewett, Russel

    2015-04-01

    SunPy is a community-developed open-source software library for solar physics. It is written in Python, a free, cross-platform, general-purpose, high-level programming language which is being increasingly adopted throughout the scientific community as well as further afield. This has resulted in a wide array of software packages useful for scientific computing, from numerical computation (NumPy, SciPy, etc.), to machine learning (scifitlearn), to visualization and plotting (matplotlib). SunPy aims to provide required specialised software for analysing solar and heliospheric datasets in Python. The current version is 0.5 with 0.6 expected to be released later this year. SunPy provides solar data access through integration with the Virtual Solar Observatory (VSO), the Heliophysics Event Knowledgebase (HEK), and the HELiophysics Integrated Observatory (HELIO) webservices. It supports common data types from major solar missions such as images (SDO/AIA, STEREO, PROBA2/SWAP etc.), time series (GOES/XRS, SDO/EVE, PROBA2/LYRA), and radio spectra (e-Callisto, STEREO/WAVES). SunPy’s code base is publicly available through github.com and can be contributed to by anyone. In this poster we demonstrate SunPy’s functionality and future goals of the project. We also encourage interested users to become involved in further developing SunPy.

  7. A facility for creating Python extensions in C++

    International Nuclear Information System (INIS)

    Dubois, P F

    1998-01-01

    Python extensions are usually created by writing the glue that connects Python to the desired new functionality in the C language. While simple extensions do not require much effort, to do the job correctly with full error checking is tedious and prone to errors in reference counting and to memory leaks, especially when errors occur. The resulting program is difficult to read and maintain. By designing suitable C++ classes to wrap the Python C API, we are able to produce extensions that are correct and which clean up after themselves correctly when errors occur. This facility also integrates the C++ and Python exception facilities. This paper briefly describes our package for this purpose, named CXX. The emphasis is on our design choices and the way these contribute to the construction of accurate Python extensions. We also briefly relate the way CXX's facilities for sequence classes allow use of C++'s Standard Template Library (STL) algorithms on C++ sequences

  8. A student's guide to Python for physical modeling

    CERN Document Server

    Kinder, Jesse M

    2015-01-01

    Python is a computer programming language that is rapidly gaining popularity throughout the sciences. A Student’s Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed. This tutorial focuses on fundamentals and introduces a wide range of useful techniques, including: Basic Python programming and scripting Numerical arrays Two- and three-dimensional graphics Monte Carlo simulations Numerical methods, including solving ordinary differential equations Image processing Animation Numerous code samples and exercises—with solutions—illustrate new ideas as they are introduced. A website that accompanies this guide provides additional resourc...

  9. A modern Python interface for the Generic Mapping Tools

    Science.gov (United States)

    Uieda, L.; Wessel, P.

    2017-12-01

    Figures generated by The Generic Mapping Tools (GMT) are present in countless publications across the Earth sciences. The command-line interface of GMT lends the tool its flexibility but also creates a barrier to entry for begginers. Meanwhile, adoption of the Python programming language has grown across the scientific community. This growth is largely due to the simplicity and low barrier to entry of the language and its ecosystem of tools. Thus, it is not surprising that there have been at least three attempts to create Python interfaces for GMT: gmtpy (github.com/emolch/gmtpy), pygmt (github.com/ian-r-rose/pygmt), and PyGMT (github.com/glimmer-cism/PyGMT). None of these projects are currently active and, with the exception of pygmt, they do not use the GMT Application Programming Interface (API) introduced in GMT 5. The two main Python libraries for plotting data on maps are the matplotlib Basemap toolkit (matplotlib.org/basemap) and Cartopy (scitools.org.uk/cartopy), both of which rely on matplotlib (matplotlib.org) as the backend for generating the figures. Basemap is known to have limitations and is being discontinued. Cartopy is an improvement over Basemap but is still bound by the speed and memory constraints of matplotlib. We present a new Python interface for GMT (GMT/Python) that makes use of the GMT API and of new features being developed for the upcoming GMT 6 release. The GMT/Python library is designed according to the norms and styles of the Python community. The library integrates with the scientific Python ecosystem by using the "virtual files" from the GMT API to implement input and output of Python data types (numpy "ndarray" for tabular data and xarray "Dataset" for grids). Other features include an object-oriented interface for creating figures, the ability to display figures in the Jupyter notebook, and descriptive aliases for GMT arguments (e.g., "region" instead of "R" and "projection" instead of "J"). GMT/Python can also serve as a backend

  10. Programming for computations Python : a gentle introduction to numerical simulations with Python

    CERN Document Server

    Linge, Svein

    2016-01-01

    This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.

  11. Lectin histochemical aspects of mucus function in the oesophagus of the reticulated python (Python reticulatus).

    Science.gov (United States)

    Meyer, W; Luz, S; Schnapper, A

    2009-08-01

    Using lectin histochemistry, the study characterizes basic functional aspects of the mucus produced by the oesophageal epithelium of the Reticulated python (Python reticulatus). Reaction staining varied as related to the two epithelium types present, containing goblet cells and ciliary cells. Remarkable intensities were achieved especially in the luminal mucus layer and the fine mucus covering the epithelial ciliary border for Con A (alpha-D-Man; alpha-D-Glc) as part of neutral glycoproteins, Limax flavus agglutinin (NeuNac = NeuNgc), emphasizing that water binding hyaluronan provides a hydrated interface conductive to the passage of material and UEA-I (alpha-L-Fuc), corroborating the view that fucose-rich highly viscous mucus is helpful against mechanical stress during prey transport.

  12. Ultrasonographic diagnosis of an endocarditis valvularis in a Burmese python (Python molurus bivittatus) with pneumonia.

    Science.gov (United States)

    Schroff, Sandra; Schmidt, Volker; Kiefer, Ingmar; Krautwald-Junghanns, Maria-Elisabeth; Pees, Michael

    2010-12-01

    An 11-yr-old Burmese python (Python molurus bivittatus) was presented with a history of respiratory symptoms. Computed tomography and an endoscopic examination of the left lung were performed and revealed severe pneumonia. Microbiologic examination of a tracheal wash sample and an endoscopy-guided sample from the lung confirmed infection with Salmonella enterica ssp. IV, Enterobacter cloacae, and Klebsiella pneumoniae. Computed tomographic examination demonstrated a hyperattenuated structure within the heart. Echocardiographic examination revealed a hyperechoic mass at the pulmonic valve as well as a dilated truncus pulmonalis. As therapy for pneumonia was ineffective, the snake was euthanized. Postmortem examination confirmed pneumonia and infective endocarditis of the pulmonic valve caused by septicemia with Salmonella enterica ssp. IV. Focal arteriosclerosis of the pulmonary trunk was also diagnosed. The case presented here demonstrates the possible connection between respiratory and cardiovascular diseases in snakes.

  13. Postprandial morphological response of the intestinal epithelium of the Burmese python (Python molurus).

    Science.gov (United States)

    Lignot, Jean-Hervé; Helmstetter, Cécile; Secor, Stephen M

    2005-07-01

    The postprandial morphological changes of the intestinal epithelium of Burmese pythons were examined using fasting pythons and at eight time points after feeding. In fasting pythons, tightly packed enterocytes possess very short microvilli and are arranged in a pseudostratified fashion. Enterocyte width increases by 23% within 24 h postfeeding, inducing significant increases in villus length and intestinal mass. By 6 days postfeeding, enterocyte volume had peaked, following as much as an 80% increase. Contributing to enterocyte hypertrophy is the cellular accumulation of lipid droplets at the tips and edges of the villi of the proximal and middle small intestine, but which were absent in the distal small intestine. At 3 days postfeeding, conventional and environmental scanning electron microscopy revealed cracks and lipid extrusion along the narrow edges of the villi and at the villus tips. Transmission electron microscopy demonstrated the rapid postprandial lengthening of enterocyte microvilli, increasing 4.8-fold in length within 24 h, and the maintaining of that length through digestion. Beginning at 24 h postfeeding, spherical particles were found embedded apically within enterocytes of the proximal and middle small intestine. These particles possessed an annular-like construction and were stained with the calcium-stain Alizarine red S suggesting that they were bone in origin. Following the completion of digestion, many of the postprandial responses were reversed, as observed by the atrophy of enterocytes, the shortening of villi, and the retraction of the microvilli. Further exploration of the python intestine will reveal the underlying mechanisms of these trophic responses and the origin and fate of the engulfed particles.

  14. A Python Calculator for Supernova Remnant Evolution

    Science.gov (United States)

    Leahy, D. A.; Williams, J. E.

    2017-05-01

    A freely available Python code for modeling supernova remnant (SNR) evolution has been created. This software is intended for two purposes: to understand SNR evolution and to use in modeling observations of SNR for obtaining good estimates of SNR properties. It includes all phases for the standard path of evolution for spherically symmetric SNRs. In addition, alternate evolutionary models are available, including evolution in a cloudy ISM, the fractional energy-loss model, and evolution in a hot low-density ISM. The graphical interface takes in various parameters and produces outputs such as shock radius and velocity versus time, as well as SNR surface brightness profile and spectrum. Some interesting properties of SNR evolution are demonstrated using the program.

  15. A primer on scientific programming with Python

    CERN Document Server

    Langtangen, Hans Petter

    2014-01-01

    The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen … does an excellent job of introducing programming as a set of skills in problem solving. ...

  16. A primer on scientific programming with Python

    CERN Document Server

    Langtangen, Hans Petter

    2016-01-01

    The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen … does an excellent job of introducing programming as a set of skills in problem solving. ...

  17. COSMOS: Python library for massively parallel workflows.

    Science.gov (United States)

    Gafni, Erik; Luquette, Lovelace J; Lancaster, Alex K; Hawkins, Jared B; Jung, Jae-Yoon; Souilmi, Yassine; Wall, Dennis P; Tonellato, Peter J

    2014-10-15

    Efficient workflows to shepherd clinically generated genomic data through the multiple stages of a next-generation sequencing pipeline are of critical importance in translational biomedical science. Here we present COSMOS, a Python library for workflow management that allows formal description of pipelines and partitioning of jobs. In addition, it includes a user interface for tracking the progress of jobs, abstraction of the queuing system and fine-grained control over the workflow. Workflows can be created on traditional computing clusters as well as cloud-based services. Source code is available for academic non-commercial research purposes. Links to code and documentation are provided at http://lpm.hms.harvard.edu and http://wall-lab.stanford.edu. dpwall@stanford.edu or peter_tonellato@hms.harvard.edu. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

  18. Reduction of blood oxygen levels enhances postprandial cardiac hypertrophy in Burmese python (Python bivittatus).

    Science.gov (United States)

    Slay, Christopher E; Enok, Sanne; Hicks, James W; Wang, Tobias

    2014-05-15

    Physiological cardiac hypertrophy is characterized by reversible enlargement of cardiomyocytes and changes in chamber architecture, which increase stroke volume and via augmented convective oxygen transport. Cardiac hypertrophy is known to occur in response to repeated elevations of O2 demand and/or reduced O2 supply in several species of vertebrate ectotherms, including postprandial Burmese pythons (Python bivittatus). Recent data suggest postprandial cardiac hypertrophy in P. bivittatus is a facultative rather than obligatory response to digestion, though the triggers of this response are unknown. Here, we hypothesized that an O2 supply-demand mismatch stimulates postprandial cardiac enlargement in Burmese pythons. To test this hypothesis, we rendered animals anemic prior to feeding, essentially halving blood oxygen content during the postprandial period. Fed anemic animals had heart rates 126% higher than those of fasted controls, which, coupled with a 71% increase in mean arterial pressure, suggests fed anemic animals were experiencing significantly elevated cardiac work. We found significant cardiac hypertrophy in fed anemic animals, which exhibited ventricles 39% larger than those of fasted controls and 28% larger than in fed controls. These findings support our hypothesis that those animals with a greater magnitude of O2 supply-demand mismatch exhibit the largest hearts. The 'low O2 signal' stimulating postprandial cardiac hypertrophy is likely mediated by elevated ventricular wall stress associated with postprandial hemodynamics. © 2014. Published by The Company of Biologists Ltd.

  19. PyMOOSE: interoperable scripting in Python for MOOSE

    Directory of Open Access Journals (Sweden)

    Subhasis Ray

    2008-12-01

    Full Text Available Python is emerging as a common scripting language for simulators. This opens up many possibilities for interoperability in the form of analysis, interfaces, and communications between simulators. We report the integration of Python scripting with the Multi-scale Object Oriented Simulation Environment (MOOSE. MOOSE is a general-purpose simulation system for compartmental neuronal models and for models of signaling pathways based on chemical kinetics. We show how the Python-scripting version of MOOSE, PyMOOSE, combines the power of a compiled simulator with the versatility and ease of use of Python. We illustrate this by using Python numerical libraries to analyze MOOSE output online, and by developing a GUI in Python/Qt for a MOOSE simulation. Finally, we build and run a composite neuronal/signaling model that uses both the NEURON and MOOSE numerical engines, and Python as a bridge between the two. Thus PyMOOSE has a high degree of interoperability with analysis routines, with graphical toolkits, and with other simulators.

  20. Python in the NERSC Exascale Science Applications Program for Data

    Energy Technology Data Exchange (ETDEWEB)

    Ronaghi, Zahra; Thomas, Rollin; Deslippe, Jack; Bailey, Stephen; Gursoy, Doga; Kisner, Theodore; Keskitalo, Reijo; Borrill, Julian

    2017-11-12

    We describe a new effort at the National Energy Re- search Scientific Computing Center (NERSC) in performance analysis and optimization of scientific Python applications targeting the Intel Xeon Phi (Knights Landing, KNL) many- core architecture. The Python-centered work outlined here is part of a larger effort called the NERSC Exascale Science Applications Program (NESAP) for Data. NESAP for Data focuses on applications that process and analyze high-volume, high-velocity data sets from experimental/observational science (EOS) facilities supported by the US Department of Energy Office of Science. We present three case study applications from NESAP for Data that use Python. These codes vary in terms of “Python purity” from applications developed in pure Python to ones that use Python mainly as a convenience layer for scientists without expertise in lower level programming lan- guages like C, C++ or Fortran. The science case, requirements, constraints, algorithms, and initial performance optimizations for each code are discussed. Our goal with this paper is to contribute to the larger conversation around the role of Python in high-performance computing today and tomorrow, highlighting areas for future work and emerging best practices

  1. IRISpy: Analyzing IRIS Data in Python

    Science.gov (United States)

    Ryan, Daniel; Christe, Steven; Mumford, Stuart; Baruah, Ankit; Timothy, Shelbe; Pereira, Tiago; De Pontieu, Bart

    2017-08-01

    IRISpy is a new community-developed open-source software library for analysing IRIS level 2 data. It is written in Python, a free, cross-platform, general-purpose, high-level programming language. A wide array of scientific computing software packages have already been developed in Python, from numerical computation (NumPy, SciPy, etc.), to visualization and plotting (matplotlib), to solar-physics-specific data analysis (SunPy). IRISpy is currently under development as a SunPy-affiliated package which means it depends on the SunPy library, follows similar standards and conventions, and is developed with the support of of the SunPy development team. IRISpy’s has two primary data objects, one for analyzing slit-jaw imager data and another for analyzing spectrograph data. Both objects contain basic slicing, indexing, plotting, and animating functionality to allow users to easily inspect, reduce and analyze the data. As part of this functionality the objects can output SunPy Maps, TimeSeries, Spectra, etc. of relevant data slices for easier inspection and analysis. Work is also ongoing to provide additional data analysis functionality including derivation of systematic measurement errors (e.g. readout noise), exposure time correction, residual wavelength calibration, radiometric calibration, and fine scale pointing corrections. IRISpy’s code base is publicly available through github.com and can be contributed to by anyone. In this poster we demonstrate IRISpy’s functionality and future goals of the project. We also encourage interested users to become involved in further developing IRISpy.

  2. galpy: A python LIBRARY FOR GALACTIC DYNAMICS

    International Nuclear Information System (INIS)

    Bovy, Jo

    2015-01-01

    I describe the design, implementation, and usage of galpy, a python package for galactic-dynamics calculations. At its core, galpy consists of a general framework for representing galactic potentials both in python and in C (for accelerated computations); galpy functions, objects, and methods can generally take arbitrary combinations of these as arguments. Numerical orbit integration is supported with a variety of Runge-Kutta-type and symplectic integrators. For planar orbits, integration of the phase-space volume is also possible. galpy supports the calculation of action-angle coordinates and orbital frequencies for a given phase-space point for general spherical potentials, using state-of-the-art numerical approximations for axisymmetric potentials, and making use of a recent general approximation for any static potential. A number of different distribution functions (DFs) are also included in the current release; currently, these consist of two-dimensional axisymmetric and non-axisymmetric disk DFs, a three-dimensional disk DF, and a DF framework for tidal streams. I provide several examples to illustrate the use of the code. I present a simple model for the Milky Way's gravitational potential consistent with the latest observations. I also numerically calculate the Oort functions for different tracer populations of stars and compare them to a new analytical approximation. Additionally, I characterize the response of a kinematically warm disk to an elliptical m = 2 perturbation in detail. Overall, galpy consists of about 54,000 lines, including 23,000 lines of code in the module, 11,000 lines of test code, and about 20,000 lines of documentation. The test suite covers 99.6% of the code. galpy is available at http://github.com/jobovy/galpy with extensive documentation available at http://galpy.readthedocs.org/en/latest

  3. Implementation of quantum game theory simulations using Python

    Science.gov (United States)

    Madrid S., A.

    2013-05-01

    This paper provides some examples about quantum games simulated in Python's programming language. The quantum games have been developed with the Sympy Python library, which permits solving quantum problems in a symbolic form. The application of these methods of quantum mechanics to game theory gives us more possibility to achieve results not possible before. To illustrate the results of these methods, in particular, there have been simulated the quantum battle of the sexes, the prisoner's dilemma and card games. These solutions are able to exceed the classic bottle neck and obtain optimal quantum strategies. In this form, python demonstrated that is possible to do more advanced and complicated quantum games algorithms.

  4. PyFITS, a FITS Module for Python

    Science.gov (United States)

    Barrett, P. E.; Bridgman, W. T.

    PyFITS is a module for reading, writing, and manipulating FITS files using the interactive, object-oriented language, Python. The module is composed of two files: a generic low-level C library for manipulating multidimensional arrays of C-type structures and a high-level Python module. FITS files can be manipulated at several different levels, beginning with the header-data unit at the highest level to rows and columns of binary tables at the lowest level. In addition, header-data units and columns of binary tables are accessible by index or name. PyFITS also interfaces to NumPy, the Python numerical array module.

  5. PyCSP - Communicating Sequential Processes for Python

    DEFF Research Database (Denmark)

    Vinter, Brian; Bjørndalen, John Markus; Anshus, Otto Johan

    The Python programming language is effective for rapidly specifying programs and experimenting with them. It is increasingly being used in computational sciences, and in teaching computer science. CSP is effective for describing concurrency. It has become especially relevant with the emergence...... of commodity multi-core architectures. We are interested in exploring how a combination of Python and CSP can benefit both the computational sciences and the hands-on teaching of distributed and parallel computing in computer science. To make this possible, we have developed PyCSP, a CSP library for Python. Py...

  6. Python as First Textual Programming Language in Secondary Education

    Directory of Open Access Journals (Sweden)

    José Carlos GARCÍA MONSÁLVEZ

    2017-07-01

    Full Text Available With the recent introduction of Programming in the K-12 curricula there is an opportunity to include Computer Science fundamental concepts. This paper presents the origin and evolution of Python as well as their main features that configure it as an ideal programming language. We also review and classify some educational tools in the Python ecosystem. Such tools cover a wide-open spectrum of resources from interactive books to libraries which ease the construction of student elaborated software artefacts. This work presents a multidisciplinary proposal to use the Python programming language in all levels of Secondary Stage.

  7. Report on the ''ESO Python Boot Camp — Pilot Version''

    Science.gov (United States)

    Dias, B.; Milli, J.

    2017-03-01

    The Python programming language is becoming very popular within the astronomical community. Python is a high-level language with multiple applications including database management, handling FITS images and tables, statistical analysis, and more advanced topics. Python is a very powerful tool both for astronomical publications and for observatory operations. Since the best way to learn a new programming language is through practice, we therefore organised a two-day hands-on workshop to share expertise among ESO colleagues. We report here the outcome and feedback from this pilot event.

  8. Python data science handbook essential tools for working with data

    CERN Document Server

    VanderPlas, Jake

    2016-01-01

    For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues.

  9. The mechanical properties of the systemic and pulmonary arteries of Python regius correlate with blood pressures.

    Science.gov (United States)

    van Soldt, Benjamin J; Danielsen, Carl Christian; Wang, Tobias

    2015-12-01

    Pythons are unique amongst snakes in having different pressures in the aortas and pulmonary arteries because of intraventricular pressure separation. In this study, we investigate whether this correlates with different blood vessel strength in the ball python Python regius. We excised segments from the left, right, and dorsal aortas, and from the two pulmonary arteries. These were subjected to tensile testing. We show that the aortic vessel wall is significantly stronger than the pulmonary artery wall in P. regius. Gross morphological characteristics (vessel wall thickness and correlated absolute amount of collagen content) are likely the most influential factors. Collagen fiber thickness and orientation are likely to have an effect, though the effect of collagen fiber type and cross-links between fibers will need further study. © 2015 Wiley Periodicals, Inc.

  10. Transcriptome Analysis of the Response of Burmese Python to Digestion

    DEFF Research Database (Denmark)

    Duan, Jinjie; Sanggaard, Kristian Wejse; Schauser, Leif

    2017-01-01

    Background: Exceptional and extreme feeding behaviour makes the Burmese python (Python bivittatus) an interesting model to study physiological remodelling and metabolic adaptation in response to refeeding after prolonged starvation. In this study, we used transcriptome sequencing of five visceral...... organs during fasting as well as 24h and 48h after ingestion of a large meal to unravel the postprandial changes in Burmese pythons. We first used the pooled data to perform a de novo assembly of the transcriptome and supplemented this with a proteomic survey of enzymes in the plasma and gastric fluid...... in the liver, 114 genes in the stomach, 89 genes in the pancreas and 158 genes in the intestine. We interrogated the function of these genes to test previous hypotheses on the response to feeding. We also used the transcriptome to identify 314 secreted proteins in the gastric fluid of the python. Conclusions...

  11. Adapting the BIMA Image Pipeline for Miriad Using Python

    Science.gov (United States)

    Mehringer, D. M.; Plante, R.

    2004-07-01

    Through our experience using AIPS++ in the BIMA Image Pipeline, we found that a sophisticated scripting environment is crucial for supporting an automated pipeline. Miriad V4, now in development, introduces support for calling Miriad programs from a Python environment (referred to as Pyramid). We are creating processing recipes using Miriad through Python that can be used with the BIMA Image Pipeline. As part of this work, we are prototyping tools that could be integrated into Pyramid. These include two Python classes, UVDataset and Image for examining the contents of Miriad datasets. These simple tools have allowed us to recast our Pipeline using Miriad in only a couple of months. Python recipes are used for such things as determining line-free channels for continuum subtraction and determining if data will benefit from self-calibration. We are currently using the Pipeline to do massive processing of hundreds of tracks of archival data using NCSA's Teraflop IA-32 Linux cluster.

  12. Usage of the Python programming language in the CMS experiment

    International Nuclear Information System (INIS)

    Wilkinson, R; Hegner, B; Jones, C D

    2010-01-01

    Being a highly dynamic language and allowing reliable programming with quick turnarounds, Python is a widely used programming language in CMS. Most of the tools used in workflow management and the GRID interface tools are written in this language. Also most of the tools used in the context of release management: integration builds, release building and deploying, as well as performance measurements are in Python. With an interface to the CMS data formats, rapid prototyping of analyses and debugging is an additional use case. Finally in 2008 the CMS experiment switched to using Python as its configuration language. This paper will give an overview of the general usage of Python in the CMS experiment and discuss which features of the language make it well-suited for the existing use cases.

  13. Enrico: Python package to simplify Fermi-LAT analysis

    Science.gov (United States)

    Sanchez, David; Deil, Christoph

    2015-01-01

    Enrico analyzes Fermi data. It produces spectra (model fit and flux points), maps and lightcurves for a target by editing a config file and running a python script which executes the Fermi science tool chain.

  14. pypet: A Python Toolkit for Data Management of Parameter Explorations

    OpenAIRE

    Robert Meyer; Robert Meyer; Klaus Obermayer

    2016-01-01

    pypet (Python parameter exploration toolkit) is a new multi-platform Python toolkit for managing numerical simulations. Sampling the space of model parameters is a key aspect of simulations and numerical experiments. pypet is designed to allow easy and arbitrary sampling of trajectories through a parameter space beyond simple grid searches.pypet collects and stores both simulation parameters and results in a single HDF5 file.This collective storage allows fast and convenient loading of data f...

  15. Devito: Towards a generic Finite Difference DSL using Symbolic Python

    OpenAIRE

    Lange, Michael; Kukreja, Navjot; Louboutin, Mathias; Luporini, Fabio; Vieira, Felippe; Pandolfo, Vincenzo; Velesko, Paulius; Kazakas, Paulius; Gorman, Gerard

    2016-01-01

    Domain specific languages (DSL) have been used in a variety of fields to express complex scientific problems in a concise manner and provide automated performance optimization for a range of computational architectures. As such DSLs provide a powerful mechanism to speed up scientific Python computation that goes beyond traditional vectorization and pre-compilation approaches, while allowing domain scientists to build applications within the comforts of the Python software ecosystem. In this p...

  16. pypet: A Python Toolkit for Data Management of Parameter Explorations

    OpenAIRE

    Meyer, Robert; Obermayer, Klaus

    2016-01-01

    pypet (Python parameter exploration toolkit) is a new multi-platform Python toolkit for managing numerical simulations. Sampling the space of model parameters is a key aspect of simulations and numerical experiments. pypet is designed to allow easy and arbitrary sampling of trajectories through a parameter space beyond simple grid searches. pypet collects and stores both simulation parameters and results in a single HDF5 file. This collective storage allows fast and convenient loading of data...

  17. Parasite spillover: indirect effects of invasive Burmese pythons

    OpenAIRE

    Miller, Melissa A.; Kinsella, John M.; Snow, Ray W.; Hayes, Malorie M.; Falk, Bryan G.; Reed, Robert N.; Mazzotti, Frank J.; Guyer, Craig; Romagosa, Christina M.

    2017-01-01

    Abstract Identification of the origin of parasites of nonindigenous species (NIS) can be complex. NIS may introduce parasites from their native range and acquire parasites from within their invaded range. Determination of whether parasites are non‐native or native can be complicated when parasite genera occur within both the NIS’ native range and its introduced range. We explored potential for spillover and spillback of lung parasites infecting Burmese pythons (Python bivittatus) in their inv...

  18. Parasite spillover: indirect effects of invasive Burmese pythons.

    Science.gov (United States)

    Miller, Melissa A; Kinsella, John M; Snow, Ray W; Hayes, Malorie M; Falk, Bryan G; Reed, Robert N; Mazzotti, Frank J; Guyer, Craig; Romagosa, Christina M

    2018-01-01

    Identification of the origin of parasites of nonindigenous species (NIS) can be complex. NIS may introduce parasites from their native range and acquire parasites from within their invaded range. Determination of whether parasites are non-native or native can be complicated when parasite genera occur within both the NIS' native range and its introduced range. We explored potential for spillover and spillback of lung parasites infecting Burmese pythons ( Python bivittatus ) in their invasive range (Florida). We collected 498 indigenous snakes of 26 species and 805 Burmese pythons during 2004-2016 and examined them for lung parasites. We used morphology to identify three genera of pentastome parasites, Raillietiella , a cosmopolitan form, and Porocephalus and Kiricephalus , both New World forms. We sequenced these parasites at one mitochondrial and one nuclear locus and showed that each genus is represented by a single species, R. orientalis , P. crotali , and K. coarctatus . Pythons are host to R. orientalis and P. crotali , but not K. coarctatus ; native snakes are host to all three species. Sequence data show that pythons introduced R. orientalis to North America, where this parasite now infects native snakes. Additionally, our data suggest that pythons are competent hosts to P. crotali , a widespread parasite native to North and South America that was previously hypothesized to infect only viperid snakes. Our results indicate invasive Burmese pythons have affected parasite-host dynamics of native snakes in ways that are consistent with parasite spillover and demonstrate the potential for indirect effects during invasions. Additionally, we show that pythons have acquired a parasite native to their introduced range, which is the initial condition necessary for parasite spillback.

  19. CVXPY: A Python-Embedded Modeling Language for Convex Optimization.

    Science.gov (United States)

    Diamond, Steven; Boyd, Stephen

    2016-04-01

    CVXPY is a domain-specific language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax that follows the math, rather than in the restrictive standard form required by solvers. CVXPY makes it easy to combine convex optimization with high-level features of Python such as parallelism and object-oriented design. CVXPY is available at http://www.cvxpy.org/ under the GPL license, along with documentation and examples.

  20. MEG and EEG data analysis with MNE-Python

    Science.gov (United States)

    Gramfort, Alexandre; Luessi, Martin; Larson, Eric; Engemann, Denis A.; Strohmeier, Daniel; Brodbeck, Christian; Goj, Roman; Jas, Mainak; Brooks, Teon; Parkkonen, Lauri; Hämäläinen, Matti

    2013-01-01

    Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals generated by neuronal activity in the brain. Using these signals to characterize and locate neural activation in the brain is a challenge that requires expertise in physics, signal processing, statistics, and numerical methods. As part of the MNE software suite, MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions. All algorithms and utility functions are implemented in a consistent manner with well-documented interfaces, enabling users to create M/EEG data analysis pipelines by writing Python scripts. Moreover, MNE-Python is tightly integrated with the core Python libraries for scientific comptutation (NumPy, SciPy) and visualization (matplotlib and Mayavi), as well as the greater neuroimaging ecosystem in Python via the Nibabel package. The code is provided under the new BSD license allowing code reuse, even in commercial products. Although MNE-Python has only been under heavy development for a couple of years, it has rapidly evolved with expanded analysis capabilities and pedagogical tutorials because multiple labs have collaborated during code development to help share best practices. MNE-Python also gives easy access to preprocessed datasets, helping users to get started quickly and facilitating reproducibility of methods by other researchers. Full documentation, including dozens of examples, is available at http://martinos.org/mne. PMID:24431986

  1. Pycobra: A Python Toolbox for Ensemble Learning and Visualisation

    OpenAIRE

    Guedj, Benjamin; Srinivasa Desikan, Bhargav

    2017-01-01

    We introduce \\texttt{pycobra}, a Python library devoted to ensemble learning (regression and classification) and visualisation. Its main assets are the implementation of several ensemble learning algorithms, a flexible and generic interface to compare and blend any existing machine learning algorithm available in Python libraries (as long as a \\texttt{predict} method is given), and visualisation tools such as Voronoi tessellations. \\texttt{pycobra} is fully \\texttt{scikit-learn} compatible an...

  2. PyROOT: Seamless Melting of C++ and Python

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    With ROOT it's possible to use any C++ library from Python without writing any bindings nor dictionaries: loading the library and injecting the relevant headers in the ROOT C++ interpreter is enough to guarantee interactive usage from within Python. Just in time (JIT) compilation of C++ code and immediate utilisation of C++ entities from within Python is also supported. Thanks to the ROOT type system and C++ interpreter and JIT compiler, complete Python/C++ interoperability is achieved. In this contribution we explain how this mechanism is general enough to make any library written in C or C++ usable from within Python and how concepts such as template metaprogramming are mapped in Python. We review the basics of the JIT compilation capabilities provided by the Clang based ROOT interpreter, Cling, and the way in which some of the information of the Abstract Syntax Tree (AST) built by Clang is stored by the ROOT type system. The way in which ROOT manages the automatic loading of libraries and parsing of neces...

  3. Functional changes with feeding in the gastro-intestinal epithelia of the Burmese python (Python molurus).

    Science.gov (United States)

    Helmstetter, Cécile; Reix, Nathalie; T'Flachebba, Mathieu; Pope, Robert K; Secor, Stephen M; Le Maho, Yvon; Lignot, Jean-Hervé

    2009-09-01

    The morphology of the digestive system in fasting and refed Burmese pythons was determined, as well as the localization of the proton (H(+), K(+)-ATPase) and sodium (Na(+), K(+)-ATPase) pumps. In fasting pythons, oxyntopeptic cells located within the fundic glands are typically non-active, with a thick apical tubulovesicular system and numerous zymogen granules. They become active Immediately after feeding but return to a non-active state 3 days after the Ingestion of the prey. The proton pump, expressed throughout the different fasting/feeding states, is either sequestered in the tubulovesicular system in non-active cells or located along the apical digitations extending within the crypt lumen in active cells. The sodium pump is rapidly upregulated in fed animals and is classically located along the baso-lateral membranes of the gastric oxyntopeptic cells. In the Intestine, it is only expressed along the lateral membranes of the enterocytes, i.e., above the lateral spaces and not along the basal side of the cells. Thus, solute transport within the Intestinal lining is mainly achieved through the apical part of the cells and across the lateral spaces while absorbed fat massively crosses the entire height of the cells and flows into the Intercellular spaces. Therefore, in the Burmese python, the gastrointestinal cellular system quickly upregulates after feeding, due to Inexpensive cellular changes, passive mechanisms, and the progressive activation and synthesis of key enzymes such as the sodium pump. This cell plasticity also allows anticipation of the next fasting and feeding periods.

  4. Renal plasticity in response to feeding in the Burmese python, Python molurus bivittatus.

    Science.gov (United States)

    Esbaugh, A J; Secor, S M; Grosell, M

    2015-10-01

    Burmese pythons are sit-and-wait predators that are well adapted to go long periods without food, yet subsequently consume and digest single meals that can exceed their body weight. These large feeding events result in a dramatic alkaline tide that is compensated by a hypoventilatory response that normalizes plasma pH; however, little is known regarding how plasma HCO3(-) is lowered in the days post-feeding. The current study demonstrated that Burmese pythons contain the cellular machinery for renal acid-base compensation and actively remodel the kidney to limit HCO3(-) reabsorption in the post-feeding period. After being fed a 25% body weight meal plasma total CO2 was elevated by 1.5-fold after 1 day, but returned to control concentrations by 4 days post-feeding (d pf). Gene expression analysis was used to verify the presence of carbonic anhydrase (CA) II, IV and XIII, Na(+) H(+) exchanger 3 (NHE3), the Na(+) HCO3(-) co-transporter (NBC) and V-type ATPase. CA IV expression was significantly down-regulated at 3 dpf versus fasted controls. This was supported by activity analysis that showed a significant decrease in the amount of GPI-linked CA activity in isolated kidney membranes at 3 dpf versus fasted controls. In addition, V-type ATPase activity was significantly up-regulated at 3 dpf; no change in gene expression was observed. Both CA II and NHE3 expression was up-regulated at 3 dpf, which may be related to post-prandial ion balance. These results suggest that Burmese pythons actively remodel their kidney after feeding, which would in part benefit renal HCO3(-) clearance. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Surgical management of maxillary and premaxillary osteomyelitis in a reticulated python (Python reticulatus).

    Science.gov (United States)

    Latney, La'Toya V; McDermott, Colin; Scott, Gregory; Soltero-Rivera, Maria M; Beguesse, Kyla; Sánchez, Melissa D; Lewis, John R

    2016-05-01

    CASE DESCRIPTION A 1-year-old reticulated python (Python reticulatus) was evaluated because of a 2-week history of wheezing and hissing. CLINICAL FINDINGS Rostral facial cellulitis and deep gingival pockets associated with missing rostral maxillary teeth were evident. Tissues of the nares were swollen, resulting in an audible wheeze during respiration. Multiple scars and superficial facial wounds attributed to biting by live prey were apparent. Radiographic examination revealed bilateral, focal, rostral maxillary osteomyelitis. TREATMENT AND OUTCOME Wound irrigation, antimicrobials, and anti-inflammatory drug treatment resulted in reduced cellulitis. A 3-week regimen that included empirical antimicrobial treatment and improved husbandry resulted in resolution of the respiratory sounds and partial healing of bite wounds, but radiographic evaluation revealed progressive maxillary osteomyelitis. Microbial culture of blood yielded scant gram-positive cocci and Bacillus spp, which were suspected sample contaminants. Bilateral partial maxillectomies were performed; microbial culture and histologic examination of resected bone confirmed osteomyelitis with gram-positive cocci. Treatment with trimethoprim-sulfamethoxazole was initiated on the basis of microbial susceptibility tests. Four months later, follow-up radiography revealed premaxillary osteomyelitis; surgery was declined, and treatment with trimethoprim-sulfamethoxazole was reinstituted. Eight months after surgery, the patient was reevaluated because of recurrent clinical signs; premaxillectomy was performed, and treatment with trimethoprim-sulfamethoxazole was prescribed on the basis of microbial culture of bone and microbial susceptibility testing. Resolution of osteomyelitis was confirmed by CT 11 months after the initial surgery. CONCLUSIONS AND CLINICAL RELEVANCE Focal maxillectomies and premaxillectomy were successfully performed in a large python. Surgical management and appropriate antimicrobial treatment

  6. Hearing with an atympanic ear: good vibration and poor sound-pressure detection in the royal python, Python regius

    DEFF Research Database (Denmark)

    Christensen, Christian Bech; Christensen-Dalsgaard, Jakob; Brandt, Christian

    2012-01-01

    are sensitive to sound pressure and (2) snakes are sensitive to vibrations, but cannot hear the sound pressure per se. Vibration and sound-pressure sensitivities were quantified by measuring brainstem evoked potentials in 11 royal pythons, Python regius. Vibrograms and audiograms showed greatest sensitivity...... at low frequencies of 80-160 Hz, with sensitivities of -54 dB re. 1 m s(-2) and 78 dB re. 20 μPa, respectively. To investigate whether pythons detect sound pressure or sound-induced head vibrations, we measured the sound-induced head vibrations in three dimensions when snakes were exposed to sound...... pressure at threshold levels. In general, head vibrations induced by threshold-level sound pressure were equal to or greater than those induced by threshold-level vibrations, and therefore sound-pressure sensitivity can be explained by sound-induced head vibration. From this we conclude that pythons...

  7. Sequencing the genome of the Burmese python (Python molurus bivittatus) as a model for studying extreme adaptations in snakes.

    Science.gov (United States)

    Castoe, Todd A; de Koning, Jason A P; Hall, Kathryn T; Yokoyama, Ken D; Gu, Wanjun; Smith, Eric N; Feschotte, Cédric; Uetz, Peter; Ray, David A; Dobry, Jason; Bogden, Robert; Mackessy, Stephen P; Bronikowski, Anne M; Warren, Wesley C; Secor, Stephen M; Pollock, David D

    2011-07-28

    The Consortium for Snake Genomics is in the process of sequencing the genome and creating transcriptomic resources for the Burmese python. Here, we describe how this will be done, what analyses this work will include, and provide a timeline.

  8. SunPy: Python for Solar Physics

    Science.gov (United States)

    Bobra, M.; Inglis, A. R.; Mumford, S.; Christe, S.; Freij, N.; Hewett, R.; Ireland, J.; Martinez Oliveros, J. C.; Reardon, K.; Savage, S. L.; Shih, A. Y.; Pérez-Suárez, D.

    2017-12-01

    SunPy is a community-developed open-source software library for solar physics. It is written in Python, a free, cross-platform, general-purpose, high-level programming language which is being increasingly adopted throughout the scientific community. SunPy aims to provide the software for obtaining and analyzing solar and heliospheric data. This poster introduces a new major release, SunPy version 0.8. The first major new feature introduced is Fido, the new primary interface to download data. It provides a consistent and powerful search interface to all major data providers including the VSO and the JSOC, as well as individual data sources such as GOES XRS time series. It is also easy to add new data sources as they become available, i.e. DKIST. The second major new feature is the SunPy coordinate framework. This provides a powerful way of representing coordinates, allowing simple and intuitive conversion between coordinate systems and viewpoints of different instruments (i.e., Solar Orbiter and the Parker Solar Probe), including transformation to astrophysical frames like ICRS. Other new features including new timeseries capabilities with better support for concatenation and metadata, updated documentation and example gallery. SunPy is distributed through pip and conda and all of its code is publicly available (sunpy.org).

  9. Nidovirus-Associated Proliferative Pneumonia in the Green Tree Python (Morelia viridis).

    Science.gov (United States)

    Dervas, Eva; Hepojoki, Jussi; Laimbacher, Andrea; Romero-Palomo, Fernando; Jelinek, Christine; Keller, Saskia; Smura, Teemu; Hepojoki, Satu; Kipar, Anja; Hetzel, Udo

    2017-08-09

    In 2014 we observed a noticeable increase in sudden deaths of green tree pythons ( Morelia viridis ). Pathological examination revealed accumulation of mucoid material within airways and lung, associated with enlargement of the entire lung. We performed full necropsy and histological examination on 12 affected green tree pythons from 7 different breeders to characterise the pathogenesis of this "mucinous" pneumonia. By histology we could show a marked hyperplasia of the airway epithelium and of faveolar type II pneumocytes. Since routine microbiological tests failed to identify a causative agent, we studied lung samples of a few diseased snakes by next-generation sequencing (NGS). From the NGS data we could assemble a piece of RNA genome <85% identical to nidoviruses previously identified in ball pythons and Indian pythons. We then employed RT-PCR to demonstrate the presence of the novel nidovirus in all diseased snakes. To attempt virus isolation, we established primary cell cultures of Morelia viridis liver and brain, which we inoculated with lung homogenates of infected individuals. Ultrastructural examination of concentrated cell culture supernatants showed the presence of nidovirus particles, and subsequent NGS analysis yielded the full genome of the novel virus, Morelia viridis nidovirus (MVNV). We then generated an antibody against MVNV nucleoprotein, which we used alongside RNA in situ hybridisation to demonstrate viral antigen and RNA in the affected lungs. This suggests that in natural infection MVNV damages the respiratory tract epithelium which then results in epithelial hyperplasia, most likely as an exaggerated regenerative attempt in association with increased epithelial turnover. Importance Fairly recently novel nidoviruses associated with severe respiratory disease were identified in ball pythons and Indian pythons. Herein we report isolation and identification of a further nidovirus from green tree pythons ( Morelia viridis ) with fatal pneumonia

  10. Predicting size limit of wild blood python (python brongersmai stull, 1938) harvesting in north sumatera

    Science.gov (United States)

    Mangantar Pardamean Sianturi, Markus; Jumilawaty, Erni; Delvian; Hartanto, Adrian

    2018-03-01

    Blood python (Python brongersmai Stull, 1938) is one of heavily exploited wildlife in Indonesia. The high demands on its skin trade have made its harvesting regulated under quota-based setting by the government to prevent over-harvesting. To gain understanding on the sustainability of P. brongersmai in the wild, biological characters of wild-caught specimens were studied. Samples were collected from two slaughterhouses from Rantau Prapat and Langkat. Parameters measured were morphological (Snout-vent length (SVL), body mass, abdomen width) and anatomical characters (Fat classes). Total samples of P. brongersmai in this research were 541 with 269 male and 272 female snakes. Female snakes had the highest proportion of individuals with the best quality of abdominal fat reserves (Class 3). Linear models are built and tested for its significance in relation between fat classes as anatomical characters and morphological characters. All tested morphological characters were significant in female snakes. By using linear equation models, we generate size limit to prioritize harvesting in the future. We suggest the use of SVL and stomach width ranging between 139,7 – 141,5 cm and 24,72 – 25,71 cm respectively to achieve sustainability of P. brongersmai in the wild.

  11. Python-Assisted MODFLOW Application and Code Development

    Science.gov (United States)

    Langevin, C.

    2013-12-01

    The U.S. Geological Survey (USGS) has a long history of developing and maintaining free, open-source software for hydrological investigations. The MODFLOW program is one of the most popular hydrologic simulation programs released by the USGS, and it is considered to be the most widely used groundwater flow simulation code. MODFLOW was written using a modular design and a procedural FORTRAN style, which resulted in code that could be understood, modified, and enhanced by many hydrologists. The code is fast, and because it uses standard FORTRAN it can be run on most operating systems. Most MODFLOW users rely on proprietary graphical user interfaces for constructing models and viewing model results. Some recent efforts, however, have focused on construction of MODFLOW models using open-source Python scripts. Customizable Python packages, such as FloPy (https://code.google.com/p/flopy), can be used to generate input files, read simulation results, and visualize results in two and three dimensions. Automating this sequence of steps leads to models that can be reproduced directly from original data and rediscretized in space and time. Python is also being used in the development and testing of new MODFLOW functionality. New packages and numerical formulations can be quickly prototyped and tested first with Python programs before implementation in MODFLOW. This is made possible by the flexible object-oriented design capabilities available in Python, the ability to call FORTRAN code from Python, and the ease with which linear systems of equations can be solved using SciPy, for example. Once new features are added to MODFLOW, Python can then be used to automate comprehensive regression testing and ensure reliability and accuracy of new versions prior to release.

  12. A Python interface with Narcisse graphics

    Energy Technology Data Exchange (ETDEWEB)

    Motteler, Z.C.

    1996-04-15

    Narcisse is a graphics package developed by our French colleagues at Centre d`Etudes de Limeil Valenton of the Commissariat d`Energie Atomique. Narcisse is quite comprehensive; it can do two-, three-, and four-dimensional plots (the latter meaning that the surface is colored according to the values of an arbitrary function). One can open and send plots to a Narcisse window on a distant machine. Narcisse has a user-friendly graphical user interface (GUI) which, once a graph has appeared, allows the user to change its characteristics interactively. This enables one to find the best appearance for a particular plot without having to graph it repeatedly from the user program. Previously created files in various formats can also be imported directly into the Narcisse GUI and manipulated from there. Narcisse runs independently, as a graphics server. The user program communicates with Narcisse via Unix sockets. This communication is quite low level and very complex. The appearance of a plot is controlled by nearly 150 parameters for determining such things as the color palette, type of shading, axis scales, curve and surface labels, titles, angle and distance of view (for three- and four-dimensional graphs), hidden line removal, etc. Most end users do not wish to spend time learning the tedious details of such interfaces; they would just like to specify data and ask to have it plotted. This paper describes a high level, easy to use graphics interface which hides (as much as possible) the low level details of whatever graphics system is actually being used, so that the low level can be essentially ``plug-and-play.`` Then, whenever a better system becomes available, it should only be necessary to change low level interface routines not normally accessed by ordinary users. Python, with its easy extendability, was ideally suited for this job.

  13. ETE: a python Environment for Tree Exploration.

    Science.gov (United States)

    Huerta-Cepas, Jaime; Dopazo, Joaquín; Gabaldón, Toni

    2010-01-13

    Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale. Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations. ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from http://ete.cgenomics.org.

  14. pyam: Python Implementation of YaM

    Science.gov (United States)

    Myint, Steven; Jain, Abhinandan

    2012-01-01

    pyam is a software development framework with tools for facilitating the rapid development of software in a concurrent software development environment. pyam provides solutions for development challenges associated with software reuse, managing multiple software configurations, developing software product lines, and multiple platform development and build management. pyam uses release-early, release-often development cycles to allow developers to integrate their changes incrementally into the system on a continual basis. It facilitates the creation and merging of branches to support the isolated development of immature software to avoid impacting the stability of the development effort. It uses modules and packages to organize and share software across multiple software products, and uses the concepts of link and work modules to reduce sandbox setup times even when the code-base is large. One sidebenefit is the enforcement of a strong module-level encapsulation of a module s functionality and interface. This increases design transparency, system stability, and software reuse. pyam is written in Python and is organized as a set of utilities on top of the open source SVN software version control package. All development software is organized into a collection of modules. pyam packages are defined as sub-collections of the available modules. Developers can set up private sandboxes for module/package development. All module/package development takes place on private SVN branches. High-level pyam commands support the setup, update, and release of modules and packages. Released and pre-built versions of modules are available to developers. Developers can tailor the source/link module mix for their sandboxes so that new sandboxes (even large ones) can be built up easily and quickly by pointing to pre-existing module releases. All inter-module interfaces are publicly exported via links. A minimal, but uniform, convention is used for building modules.

  15. Scripting MODFLOW model development using Python and FloPy

    Science.gov (United States)

    Bakker, Mark; Post, Vincent E. A.; Langevin, Christian D.; Hughes, Joseph D.; White, Jeremy; Starn, Jeffrey; Fienen, Michael N.

    2016-01-01

    Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy.

  16. pysimm: A Python Package for Simulation of Molecular Systems

    Science.gov (United States)

    Fortunato, Michael; Colina, Coray

    pysimm, short for python simulation interface for molecular modeling, is a python package designed to facilitate the structure generation and simulation of molecular systems through convenient and programmatic access to object-oriented representations of molecular system data. This poster presents core features of pysimm and design philosophies that highlight a generalized methodology for incorporation of third-party software packages through API interfaces. The integration with the LAMMPS simulation package is explained to demonstrate this methodology. pysimm began as a back-end python library that powered a cloud-based application on nanohub.org for amorphous polymer simulation. The extension from a specific application library to general purpose simulation interface is explained. Additionally, this poster highlights the rapid development of new applications to construct polymer chains capable of controlling chain morphology such as molecular weight distribution and monomer composition.

  17. Spectral domain optical coherence tomography imaging of spectacular ecdysis in the royal python (Python regius).

    Science.gov (United States)

    Tusler, Charlotte A; Maggs, David J; Kass, Philip H; Paul-Murphy, Joanne R; Schwab, Ivan R; Murphy, Christopher J

    2015-01-01

    To describe using spectral domain optical coherence tomography (SD-OCT), digital slit-lamp biomicroscopy, and external photography, changes in the ophidian cuticle, spectacle, and cornea during ecdysis. Four normal royal pythons (Python regius). Snakes were assessed once daily throughout a complete shed cycle using nasal, axial, and temporal SD-OCT images, digital slit-lamp biomicroscopy, and external photography. Spectral domain optical coherence tomography (SD-OCT) images reliably showed the spectacular cuticle and stroma, subcuticular space (SCS), cornea, anterior chamber, iris, and Schlemm's canal. When visible, the subspectacular space (SSS) was more distended peripherally than axially. Ocular surface changes throughout ecdysis were relatively conserved among snakes at all three regions imaged. From baseline (7 days following completion of a full cycle), the spectacle gradually thickened before separating into superficial cuticular and deep, hyper-reflective stromal components, thereby creating the SCS. During spectacular separation, the stroma regained original reflectivity, and multiple hyper-reflective foci (likely fragments from the cuticular-stromal interface) were noted within the SCS. The cornea was relatively unchanged in character or thickness throughout all stages of ecdysis. Slit-lamp images did not permit observation of these changes. Spectral domain optical coherence tomography (SD-OCT) provided excellent high-resolution images of the snake anterior segment, and especially the cuticle, spectacle, and cornea of manually restrained normal snakes at all stages of ecdysis and warrants investigation in snakes with anterior segment disease. The peripheral spectacle may be the preferred entry point for diagnostic or therapeutic injections into the SSS and for initiating spectacular surgery. © 2014 American College of Veterinary Ophthalmologists.

  18. Identification par coprologie des helminthes de python regius dans ...

    African Journals Online (AJOL)

    L'étude de la charge helminthique du Python regius a été réalisée de décembre 2007 à juin 2008 dans 4 fermes d'élevage de reptiles installées dans les villes de Bohicon et d'Abomey. Les examens coprologiques ont été réalisés sur 45 pythons. Au total, 10 espèces de nématodes et 1 espèce de cestode ont été ...

  19. Advanced PANIC quick-look tool using Python

    Science.gov (United States)

    Ibáñez, José-Miguel; García Segura, Antonio J.; Storz, Clemens; Fried, Josef W.; Fernández, Matilde; Rodríguez Gómez, Julio F.; Terrón, V.; Cárdenas, M. C.

    2012-09-01

    PANIC, the Panoramic Near Infrared Camera, is an instrument for the Calar Alto Observatory currently being integrated in laboratory and whose first light is foreseen for end 2012 or early 2013. We present here how the PANIC Quick-Look tool (PQL) and pipeline (PAPI) are being implemented, using existing rapid programming Python technologies and packages, together with well-known astronomical software suites (Astromatic, IRAF) and parallel processing techniques. We will briefly describe the structure of the PQL tool, whose main characteristics are the use of the SQLite database and PyQt, a Python binding of the GUI toolkit Qt.

  20. Jet flavor tagging with Deep Learning using Python

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    Besides the part that implements the resulting deep neural net in the ATLAS C++ software framework, a Python framework has been developed to connect HEP data to standard Data Science Python based libraries for Machine Learning. It makes use of HDF5, JSON and Pickle as intermediate data storage format, pandas and numpy for data handling and calculations, Keras for neural net construction and training as well as testing and matplotlib for plotting. It can be seen as an example of taking advantage of outside-HEP software developments without relying on the HEP standard ROOT.

  1. Solving PDEs in Python the FEniCS tutorial I

    CERN Document Server

    Langtangen, Hans Petter

    2016-01-01

    This book offers a concise and gentle introduction to finite element programming in Python based on the popular FEniCS software library. Using a series of examples, including the Poisson equation, the equations of linear elasticity, the incompressible Navier–Stokes equations, and systems of nonlinear advection–diffusion–reaction equations, it guides readers through the essential steps to quickly solving a PDE in FEniCS, such as how to define a finite variational problem, how to set boundary conditions, how to solve linear and nonlinear systems, and how to visualize solutions and structure finite element Python programs. This book is open access under a CC BY license.

  2. Python 3 text processing with NLTK 3 cookbook

    CERN Document Server

    Perkins, Jacob

    2014-01-01

    This book is intended for Python programmers interested in learning how to do natural language processing. Maybe you've learned the limits of regular expressions the hard way, or you've realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basi

  3. A spent fuel assemblies monitoring device by nondestructive analysis 'PYTHON'

    International Nuclear Information System (INIS)

    Saad, M.; Broeskamp, M.; Hahn, H.; Bignan, G.; Boisset, M.; Silie, P.

    1995-01-01

    The monitoring of spent fuel assemblies (16 x 16 UOX) in KWG-reactor pool with the use of non-destructive methods (total Gamma and neutron counting) allow the control of average burn-up and the extremity burn-up. The measurements allow a safety-criticality control before loading the fuel assemblies into the transport casks. A device called PYTHON has been tested and qualified in France. This paper presents a description of the industrial PYTHON device and the results of the measurements. (orig.)

  4. Record length, mass, and clutch size in the nonindigenous Burmese Python, Python bivittatus Kuhl 1820 (Squamata: Pythonidae), in Florida

    Science.gov (United States)

    Krysko, Kenneth L.; Hart, Kristen M.; Smith, Brian J.; Selby, Thomas H.; Cherkiss, Michael S.; Coutu, Nicholas T.; Reichart, Rebecca M.; Nuñez, Leroy P.; Mazzotti, Frank J.; Snow, Ray W.

    2012-01-01

    The Burmese Python, Python bivittatus Kuhl 1820 (Squamata: Pythonidae), is indigenous to northern India,east to southern China, and south to Vietnam and a few islands in Indonesia (Barker and Barker 2008, Reed and Rodda 2009). This species has been introduced since at least 1979 in southern Florida, USA, where it likely began reproducing and became established during the 1980s (Meshaka et al. 2000, Snowet al. 2007b,Kraus 2009, Krysko et al. 2011, Willson et al. 2011). Python bivittatus has been documented in Florida consuming a variety of mammals and birds, and the American Alligator(Alligator mississippiensis) (Snowet al. 2007a, 2007b; Harvey et al. 2008; Rochford et al. 2010b; Holbrook and Chesnes 2011), many of which are protected species. Herein, we provide details on two of the largest known wild P. bivittatus in Florida to date, including current records on length,mass,clutch size, and diet.

  5. The Atomic Simulation Environment - A Python library for working with atoms

    DEFF Research Database (Denmark)

    Larsen, Ask Hjorth; Mortensen, Jens Jørgen; Blomqvist, Jakob

    2017-01-01

    The Atomic Simulation Environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simula- tions. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make...

  6. Double valvular insufficiency in a Burmese python (Python molurus bivittatus, Linnaeus, 1758) suffering from concomitant bacterial pneumonia.

    Science.gov (United States)

    Schilliger, Lionel; Tréhiou-Sechi, Emilie; Petit, Amandine M P; Misbach, Charlotte; Chetboul, Valérie

    2010-12-01

    Ultrasonography, and, to a lesser extent, echocardiography are now well-established, noninvasive, and painless diagnostic tools in herpetologic medicine. Various cardiac lesions have been previously described in reptiles, but valvulopathy is rarely documented in these animals and, consequently, is poorly understood. In this report, sinoatrial and atrioventricular insufficiencies were diagnosed in a 5-yr-old captive dyspneic Burmese python (Python molurus bivittatus) on the basis of echocardiographic and Doppler examination. This case report is the first to document Doppler assessment of valvular regurgitations in a reptile.

  7. The microvasculature of python pit organs: morphology and blood flow microkinetics.

    Science.gov (United States)

    Goris, Richard C; Atobe, Yoshitoshi; Nakano, Masato; Hisajima, Tatsuya; Funakoshi, Kengo; Kadota, Tetsuo

    2003-05-01

    Boid snakes have infrared sensing pits that resemble crotaline pits in electrophysiological function and ultrastructure, but differ in gross morphology, number, and location: boids have three or more simple pits in the labial scales vs a single facial pair with more complex morphology in the crotalines. We studied the morphology of the capillary bed and the microkinetics of blood flow in a boid snake, the ball python, Python regius, and compared them with the already known condition in crotalines. We used a Doppler blood flow recorder in conjunction with an electrocardiograph to measure blood flow and heartbeat, and resin casts, transmission electron microscopy, and laser confocal microscopy to study capillary morphology. Blood flow in response to infrared stimulus was virtually identical in the two taxa, but the morphology of the capillary bed differed drastically. In the ball python pits, the capillary bed consisted of a forest of vertically oriented loops with a characteristic dome at the top in contact with the receptor layer of the fundus. Immunohistochemical staining showed pericytes constricting the capillaries and domes with smooth muscle alpha-actin-labeled processes. Since latency of response was as short as 1 ms, the capillaries were apparently responding under local control to provide both nutrition and cooling to the heat-sensitive receptors. We concluded that mitochondria-filled receptors provided with a swiftly responding cooling system were nature's most efficient way of attaining infrared imaging.

  8. pypet: A Python Toolkit for Data Management of Parameter Explorations

    Directory of Open Access Journals (Sweden)

    Robert Meyer

    2016-08-01

    Full Text Available pypet (Python parameter exploration toolkit is a new multi-platform Python toolkit for managing numerical simulations. Sampling the space of model parameters is a key aspect of simulations and numerical experiments. pypet is designed to allow easy and arbitrary sampling of trajectories through a parameter space beyond simple grid searches.pypet collects and stores both simulation parameters and results in a single HDF5 file.This collective storage allows fast and convenient loading of data for further analyses.pypet provides various additional features such as multiprocessing and parallelization of simulations, dynamic loading of data, integration of git version control, and supervision of experiments via the electronic lab notebook Sumatra. pypet supports a rich set of data formats, including native Python types, Numpy and Scipy data, Pandas DataFrames, and BRIAN(2 quantities. Besides these formats, users can easily extend the toolkit to allow customized data types. pypet is a flexible tool suited for both short Python scripts and large scale projects. pypet's various features, especially the tight link between parameters and results, promote reproducible research in computational neuroscience and simulation-based disciplines.

  9. pypet: A Python Toolkit for Data Management of Parameter Explorations.

    Science.gov (United States)

    Meyer, Robert; Obermayer, Klaus

    2016-01-01

    pypet (Python parameter exploration toolkit) is a new multi-platform Python toolkit for managing numerical simulations. Sampling the space of model parameters is a key aspect of simulations and numerical experiments. pypet is designed to allow easy and arbitrary sampling of trajectories through a parameter space beyond simple grid searches. pypet collects and stores both simulation parameters and results in a single HDF5 file. This collective storage allows fast and convenient loading of data for further analyses. pypet provides various additional features such as multiprocessing and parallelization of simulations, dynamic loading of data, integration of git version control, and supervision of experiments via the electronic lab notebook Sumatra. pypet supports a rich set of data formats, including native Python types, Numpy and Scipy data, Pandas DataFrames, and BRIAN(2) quantities. Besides these formats, users can easily extend the toolkit to allow customized data types. pypet is a flexible tool suited for both short Python scripts and large scale projects. pypet's various features, especially the tight link between parameters and results, promote reproducible research in computational neuroscience and simulation-based disciplines.

  10. Status of parallel Python-based implementation of UEDGE

    Science.gov (United States)

    Umansky, M. V.; Pankin, A. Y.; Rognlien, T. D.; Dimits, A. M.; Friedman, A.; Joseph, I.

    2017-10-01

    The tokamak edge transport code UEDGE has long used the code-development and run-time framework Basis. However, with the support for Basis expected to terminate in the coming years, and with the advent of the modern numerical language Python, it has become desirable to move UEDGE to Python, to ensure its long-term viability. Our new Python-based UEDGE implementation takes advantage of the portable build system developed for FACETS. The new implementation gives access to Python's graphical libraries and numerical packages for pre- and post-processing, and support of HDF5 simplifies exchanging data. The older serial version of UEDGE has used for time-stepping the Newton-Krylov solver NKSOL. The renovated implementation uses backward Euler discretization with nonlinear solvers from PETSc, which has the promise to significantly improve the UEDGE parallel performance. We will report on assessment of some of the extended UEDGE capabilities emerging in the new implementation, and will discuss the future directions. Work performed for U.S. DOE by LLNL under contract DE-AC52-07NA27344.

  11. Cosmic tragedy in Steve Chimombo's The Python | Molande ...

    African Journals Online (AJOL)

    Cosmic tragedy in Steve Chimombo's The Python. Bright Molande. Abstract. No Abstract. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT · AJOL African Journals Online. HOW TO USE AJOL... for Researchers · for Librarians · for Authors · FAQ's · More about ...

  12. Python for Scientific Computing Education: Modeling of Queueing Systems

    Directory of Open Access Journals (Sweden)

    Vladimiras Dolgopolovas

    2014-01-01

    Full Text Available In this paper, we present the methodology for the introduction to scientific computing based on model-centered learning. We propose multiphase queueing systems as a basis for learning objects. We use Python and parallel programming for implementing the models and present the computer code and results of stochastic simulations.

  13. Implementing a Multi-Agent System in Python

    DEFF Research Database (Denmark)

    Ettienne, Mikko Berggren; Vester, Steen; Villadsen, Jørgen

    2012-01-01

    We describe the solution used by the Python-DTU team in the Multi-Agent Programming Contest 2011, where the scenario was called Agents on Mars. We present our auction-based agreement, area controlling and pathfinding algorithms and discuss our chosen strategy and our choice of technology used...

  14. Cost versus Precision for Approximate Typing for Python

    NARCIS (Netherlands)

    Fritz, Levin; Hage, J

    2014-01-01

    In this paper we describe a variation of monotone frameworks that enables us to perform approximate typing of Python, in particular for dealing with some of its more dynamic features such as first-class functions and Python’s dynamic class system. We additionally introduce a substantial number of

  15. The ageing body in Monty Python Live (Mostly)

    DEFF Research Database (Denmark)

    Petersen, Line Nybro

    2018-01-01

    This article analyses representations of the ageing body in the live televised show Monty Python Live (Mostly) (2014). The famous satire group performed in the O2 arena in London, and the show was telecast live in cinemas and aired on television across the world. In the show, the group members, now...

  16. Write Python instead of SQL - an introduction to SQLAlchemy.

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    SQLAlchemy is the most popular ORM and SQL abstraction layer for Python and used by multiple big projects at CERN such as Indico or Invenio. In my talk I'm going to give a short introduction on how to use it.

  17. Aura: A Multi-Featured Programming Framework in Python

    Directory of Open Access Journals (Sweden)

    2010-09-01

    Full Text Available This paper puts forward the design, programming and application of innovative educational software, ‘Aura’ made using Python and PyQt Python bindings. The research paper presents a new concept of using a single tool to relate between syntaxes of various programming languages and algorithms. It radically increases their understanding and retaining capacity, since they can correlate between many programming languages. The software is a totally unorthodox attempt towards helping students who have their first tryst with programming languages. The application is designed to help students understand how algorithms work and thus, help them in learning multiple programming languages on a single platform using an interactive graphical user interface. This paper elucidates how using Python and PyQt bindings, a comprehensive feature rich application, that implements an interactive algorithm building technique, a web browser, multiple programming language framework, a code generator and a real time code sharing hub be embedded into a single interface. And also explains, that using Python as building tool, it requires much less coding than conventional feature rich applications coded in other programming languages, and at the same time does not compromise on stability, inter-operability and robustness of the application.

  18. Fixing the Sorting Algorithm for Android, Java and Python

    NARCIS (Netherlands)

    C.P.T. de Gouw (Stijn); F.S. de Boer (Frank)

    2015-01-01

    htmlabstractTim Peters developed the Timsort hybrid sorting algorithm in 2002. TimSort was first developed for Python, a popular programming language, but later ported to Java (where it appears as java.util.Collections.sort and java.util.Arrays.sort). TimSort is today used as the default sorting

  19. Wyrm: A Brain-Computer Interface Toolbox in Python.

    Science.gov (United States)

    Venthur, Bastian; Dähne, Sven; Höhne, Johannes; Heller, Hendrik; Blankertz, Benjamin

    2015-10-01

    In the last years Python has gained more and more traction in the scientific community. Projects like NumPy, SciPy, and Matplotlib have created a strong foundation for scientific computing in Python and machine learning packages like scikit-learn or packages for data analysis like Pandas are building on top of it. In this paper we present Wyrm ( https://github.com/bbci/wyrm ), an open source BCI toolbox in Python. Wyrm is applicable to a broad range of neuroscientific problems. It can be used as a toolbox for analysis and visualization of neurophysiological data and in real-time settings, like an online BCI application. In order to prevent software defects, Wyrm makes extensive use of unit testing. We will explain the key aspects of Wyrm's software architecture and design decisions for its data structure, and demonstrate and validate the use of our toolbox by presenting our approach to the classification tasks of two different data sets from the BCI Competition III. Furthermore, we will give a brief analysis of the data sets using our toolbox, and demonstrate how we implemented an online experiment using Wyrm. With Wyrm we add the final piece to our ongoing effort to provide a complete, free and open source BCI system in Python.

  20. Duplicating MC-15 Output with Python and MCNP

    Energy Technology Data Exchange (ETDEWEB)

    McSpaden, Alexander Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-08-23

    Two Python scripts have been written that process the output files of MCNP6 into a format that mimics the list-mode output of Los Alamos National Laboratory’s MC-15 and NPOD neutron detection systems. This report details the methods implemented in these scripts and instructions on their use.

  1. Maybe it's not Python that sucks, maybe it's my code

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    Did you know that in Python integers from -5 to 257 are preallocated? Reusing them 1000 times, instead of allocating memory for a bigger integer, saves a whopping 1 millisecond of code's execution time! Isn't that thrilling? Well, before you get that crazy, learn some basic performance tricks that you can start using today.

  2. Building and documenting workflows with python-based snakemake

    NARCIS (Netherlands)

    J. Köster (Johannes); S. Rahmann (Sven)

    2012-01-01

    textabstractSnakemake is a novel workflow engine with a simple Python-derived workflow definition language and an optimizing execution environment. It is the first system that supports multiple named wildcards (or variables) in input and output filenames of each rule definition. It also allows to

  3. OMPC: an Open-Source MATLAB-to-Python Compiler.

    Science.gov (United States)

    Jurica, Peter; van Leeuwen, Cees

    2009-01-01

    Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB((R)), the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB((R))-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB((R)) functions into Python programs. The imported MATLAB((R)) modules will run independently of MATLAB((R)), relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB((R)). OMPC is available at http://ompc.juricap.com.

  4. SunPy: Python for Solar Physics Data Analysis

    Science.gov (United States)

    Hughitt, V. Keith; Christe, S.; Ireland, J.; Shih, A.; Mayer, F.; Earnshaw, M. D.; Young, C.; Perez-Suarez, D.; Schwartz, R.

    2012-05-01

    In recent years, Python, a free cross platform general purpose high-level programming language, has seen widespread adoption among the scientific community resulting in the availability of wide range of software, from numerical computation and machine learning to spectral analysis and visualization. SunPy is a software suite specializing in providing the tools necessary to analyze solar and heliospheric datasets in Python. It provides a free and open-source alternative to the IDL-based SolarSoft (SSW) solar data analysis environment. We present the current capabilities of SunPy which include WCS-aware map objects that allow simple overplotting of data from multiple image FITS files; time-series objects that allow overplotting of multiple lightcurves, and integration with online services such as The Virtual Solar Observatory (VSO) and The Heliophysics Event Knowledgebase (HEK). SunPy also provides functionality that is not currently available in SSW such as advanced time series manipulation routines and support for working with solar data stored using JPEG 2000. We present examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing data analysis tools currently available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy.

  5. Python Source Code Plagiarism Attacks on Introductory Programming Course Assignments

    Science.gov (United States)

    Karnalim, Oscar

    2017-01-01

    This paper empirically enlists Python plagiarism attacks that have been found on Introductory Programming course assignments for undergraduate students. According to our observation toward 400 plagiarism-suspected cases, there are 35 plagiarism attacks that have been conducted by students. It starts with comment & whitespace modification as…

  6. Monty Python e a inversão do platonismo

    Directory of Open Access Journals (Sweden)

    Flavia Pitaluga

    2008-11-01

    Full Text Available O objetivo deste trabalho é analisar os filmes Monty Python and the holy grail (Em busca do cálice sagrado e Monty Python's life of Brian (A vida de Brian à luz das discussões de Gilles Deleuze sobre o sentido na filosofia dos estóicos. A inversão do platonismo e a ascensão à superfície dos simulacros são problemas centrais para compreendermos o humor do grupo. Ao longo da discussão, as questões sobre o lugar do clichê no cinema, o falso e suas potências e a injeção de temporalidade nas produções cinematográficas, uma das características do cinema moderno, serão abordadas. A hipótese destas articulações é que a morte de Deus (crise da Verdade é inseparável da maneira como o indivíduo moderno experimenta o tempo: o cinema moderno, ao fazer "a apresentação direta do tempo" (DELEUZE, 1990, coloca em questão a linearidade e a própria verdade como representáveis. Palavras-chave: simulacro; nonsense; humor; Monty Python Abstract: Monty Python and the inversion of Platonism — The purpose of this paper is to analyze the films "Monty Python and the Holy Grail" and "Monty Python's Life of Brian" in the light of Gilles Deleuze's reflections about meaning in the philosophy of the Stoics. The inversion of Platonism and the rise of simulacra to the surface are keys to understanding the group's humor. This discussion examines questions relating to the role of clichés in motion pictures, the fake and its powers, and the insertion of temporality in film productions as one of the characteristics of modern moviemaking. The hypothesis underpinning these articulations is that the death of God (the crisis of Truth is inseparable from the way in which modern individuals experience time: modern cinema, in its "direct presentation of time" (DELEUZE, 1990, questions linearity and truth itself as being representable. Keywords: simulacrum; nonsense; humor; Monty Python

  7. Emerge - A Python environment for the modeling of subsurface transfers

    Science.gov (United States)

    Lopez, S.; Smai, F.; Sochala, P.

    2014-12-01

    The simulation of subsurface mass and energy transfers often relies on specific codes that were mainly developed using compiled languages which usually ensure computational efficiency at the expense of relatively long development times and relatively rigid software. Even if a very detailed, possibly graphical, user-interface is developed the core numerical aspects are rarely accessible and the smallest modification will always need a compilation step. Thus, user-defined physical laws or alternative numerical schemes may be relatively difficult to use. Over the last decade, Python has emerged as a popular and widely used language in the scientific community. There already exist several libraries for the pre and post-treatment of input and output files for reservoir simulators (e.g. pytough). Development times in Python are considerably reduced compared to compiled languages, and programs can be easily interfaced with libraries written in compiled languages with several comprehensive numerical libraries that provide sequential and parallel solvers (e.g. PETSc, Trilinos…). The core objective of the Emerge project is to explore the possibility to develop a modeling environment in full Python. Consequently, we are developing an open python package with the classes/objects necessary to express, discretize and solve the physical problems encountered in the modeling of subsurface transfers. We heavily relied on Python to have a convenient and concise way of manipulating potentially complex concepts with a few lines of code and a high level of abstraction. Our result aims to be a friendly numerical environment targeting both numerical engineers and physicist or geoscientists with the possibility to quickly specify and handle geometries, arbitrary meshes, spatially or temporally varying properties, PDE formulations, boundary conditions…

  8. Cold-induced mortality of invasive Burmese pythons in south Florida

    Science.gov (United States)

    Mazzotti, Frank J.; Cherkiss, Michael S.; Hart, Kristen M.; Snow, Ray W.; Rochford, Michael R.; Dorcas, Michael E.; Reed, Robert N.

    2011-01-01

    A recent record cold spell in southern Florida (2–11 January 2010) provided an opportunity to evaluate responses of an established population of Burmese pythons (Python molurus bivittatus) to a prolonged period of unusually cold weather. We observed behavior, characterized thermal biology, determined fate of radio-telemetered (n = 10) and non-telemetered (n = 104) Burmese pythons, and analyzed habitat and environmental conditions experienced by pythons during and after a historic cold spell. Telemetered pythons had been implanted with radio-transmitters and temperature-recording data loggers prior to the cold snap. Only one of 10 telemetered pythons survived the cold snap, whereas 59 of 99 (60%) non-telemetered pythons for which we determined fate survived. Body temperatures of eight dead telemetered pythons fluctuated regularly prior to 9 January 2010, then declined substantially during the cold period (9–11 January) and exhibited no further evidence of active thermoregulation indicating they were likely dead. Unusually cold temperatures in January 2010 were clearly associated with mortality of Burmese pythons in the Everglades. Some radio-telemetered pythons appeared to exhibit maladaptive behavior during the cold spell, including attempting to bask instead of retreating to sheltered refugia. We discuss implications of our findings for persistence and spread of introduced Burmese pythons in the United States and for maximizing their rate of removal.

  9. Characterization of carbonic anhydrase XIII in the erythrocytes of the Burmese python, Python molurus bivittatus.

    Science.gov (United States)

    Esbaugh, A J; Secor, S M; Grosell, M

    2015-09-01

    Carbonic anhydrase (CA) is one of the most abundant proteins found in vertebrate erythrocytes with the majority of species expressing a low activity CA I and high activity CA II. However, several phylogenetic gaps remain in our understanding of the expansion of cytoplasmic CA in vertebrate erythrocytes. In particular, very little is known about isoforms from reptiles. The current study sought to characterize the erythrocyte isoforms from two squamate species, Python molurus and Nerodia rhombifer, which was combined with information from recent genome projects to address this important phylogenetic gap. Obtained sequences grouped closely with CA XIII in phylogenetic analyses. CA II mRNA transcripts were also found in erythrocytes, but found at less than half the levels of CA XIII. Structural analysis suggested similar biochemical activity as the respective mammalian isoforms, with CA XIII being a low activity isoform. Biochemical characterization verified that the majority of CA activity in the erythrocytes was due to a high activity CA II-like isoform; however, titration with copper supported the presence of two CA pools. The CA II-like pool accounted for 90 % of the total activity. To assess potential disparate roles of these isoforms a feeding stress was used to up-regulate CO2 excretion pathways. Significant up-regulation of CA II and the anion exchanger was observed; CA XIII was strongly down-regulated. While these results do not provide insight into the role of CA XIII in the erythrocytes, they do suggest that the presence of two isoforms is not simply a case of physiological redundancy. Copyright © 2015. Published by Elsevier Inc.

  10. Food composition influences metabolism, heart rate and organ growth during digestion in Python regius.

    Science.gov (United States)

    Henriksen, Poul Secher; Enok, Sanne; Overgaard, Johannes; Wang, Tobias

    2015-05-01

    Digestion in pythons is associated with a large increase in oxygen consumption (SDA), increased cardiac output and growth in visceral organs assisting in digestion. The processes leading to the large postprandial rise in metabolism in snakes is subject to opposing views. Gastric work, protein synthesis and organ growth have each been speculated to be major contributors to the SDA. To investigate the role of food composition on SDA, heart rate (HR) and organ growth, 48 ball pythons (Python regius) were fed meals of either fat, glucose, protein or protein combined with carbonate. Our study shows that protein, in the absence or presence of carbonate causes a large SDA response, while glucose caused a significantly smaller SDA response and digestion of fat failed to affect metabolism. Addition of carbonate to the diet to stimulate gastric acid secretion did not increase the SDA response. These results support protein synthesis as a major contributor to the SDA response and show that increased gastric acid secretion occurs at a low metabolic cost. The increase in metabolism was supported by tachycardia caused by altered autonomic regulation as well as an increased non-adrenergic, non-cholinergic (NANC) tone in response to all diets, except for the lipid meal. Organ growth only occurred in the small intestine and liver in snakes fed on a high protein diet. Copyright © 2014 Elsevier Inc. All rights reserved.

  11. Xarray: multi-dimensional data analysis in Python

    Science.gov (United States)

    Hoyer, Stephan; Hamman, Joe; Maussion, Fabien

    2017-04-01

    xarray (http://xarray.pydata.org) is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays, which are the bread and butter of modern geoscientific data analysis. Key features of the package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib, Cartopy), out-of-core computation on datasets that don't fit into memory, a wide range of input/output options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. In this contribution we will present the key features of the library and demonstrate its great potential for a wide range of applications, from (big-)data processing on super computers to data exploration in front of a classroom.

  12. Expyriment: a Python library for cognitive and neuroscientific experiments.

    Science.gov (United States)

    Krause, Florian; Lindemann, Oliver

    2014-06-01

    Expyriment is an open-source and platform-independent lightweight Python library for designing and conducting timing-critical behavioral and neuroimaging experiments. The major goal is to provide a well-structured Python library for script-based experiment development, with a high priority being the readability of the resulting program code. Expyriment has been tested extensively under Linux and Windows and is an all-in-one solution, as it handles stimulus presentation, the recording of input/output events, communication with other devices, and the collection and preprocessing of data. Furthermore, it offers a hierarchical design structure, which allows for an intuitive transition from the experimental design to a running program. It is therefore also suited for students, as well as for experimental psychologists and neuroscientists with little programming experience.

  13. xarray: N-D labeled Arrays and Datasets in Python

    Directory of Open Access Journals (Sweden)

    Stephan Hoyer

    2017-04-01

    Full Text Available xarray is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays. Our approach combines an application programing interface (API inspired by pandas with the Common Data Model for self-described scientific data. Key features of the xarray package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib, out-of-core computation on datasets that don’t fit into memory, a wide range of serialization and input/output (I/O options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. xarray, as a data model and analytics toolkit, has been widely adopted in the geoscience community but is also used more broadly for multi-dimensional data analysis in physics, machine learning and finance.

  14. Brian: a simulator for spiking neural networks in Python

    Directory of Open Access Journals (Sweden)

    Dan F M Goodman

    2008-11-01

    Full Text Available Brian is a new simulator for spiking neural networks, written in Python (http://brian.di.ens.fr. It is an intuitive and highly flexible tool for rapidly developing new models, especially networks of single-compartment neurons. In addition to using standard types of neuron models, users can define models by writing arbitrary differential equations in ordinary mathematical notation. Python scientific libraries can also be used for defining models and analysing data. Vectorisation techniques allow efficient simulations despite the overheads of an interpreted language. Brian will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations. With its easy and intuitive syntax, Brian is also very well suited for teaching computational neuroscience.

  15. Probabilistic programming in Python using PyMC3

    Directory of Open Access Journals (Sweden)

    John Salvatier

    2016-04-01

    Full Text Available Probabilistic programming allows for automatic Bayesian inference on user-defined probabilistic models. Recent advances in Markov chain Monte Carlo (MCMC sampling allow inference on increasingly complex models. This class of MCMC, known as Hamiltonian Monte Carlo, requires gradient information which is often not readily available. PyMC3 is a new open source probabilistic programming framework written in Python that uses Theano to compute gradients via automatic differentiation as well as compile probabilistic programs on-the-fly to C for increased speed. Contrary to other probabilistic programming languages, PyMC3 allows model specification directly in Python code. The lack of a domain specific language allows for great flexibility and direct interaction with the model. This paper is a tutorial-style introduction to this software package.

  16. Processing Government Data: ZIP Codes, Python, and OpenRefine

    Directory of Open Access Journals (Sweden)

    Frank Donnelly

    2014-07-01

    Full Text Available While there is a vast amount of useful US government data on the web, some of it is in a raw state that is not readily accessible to the average user. Data librarians can improve accessibility and usability for their patrons by processing data to create subsets of local interest and by appending geographic identifiers to help users select and aggregate data. This case study illustrates how census geography crosswalks, Python, and OpenRefine were used to create spreadsheets of non-profit organizations in New York City from the IRS Tax-Exempt Organization Masterfile. This paper illustrates the utility of Python for data librarians and should be particularly insightful for those who work with address-based data.

  17. A pythonic integrated solution for virtual prototyping of cyclotrons

    International Nuclear Information System (INIS)

    Qin Bin; Yang Jun; Xiong Yongqian; Chen Dezhi; Yu Tiaoqin; Dong Tianlin; Zhang Tianjue; Fan Mingwu

    2007-01-01

    Virtual prototyping (VP) is a novel technique in engineering, which is desired to be applied to cyclotron design and development. Some sub-prototyping components, including beam dynamics, magnet, RF system and control system of cyclotrons, have been developed separately, but an integrated platform which encapsulates these different components is required for global system optimization. Considering that the VP integrated platform is a large-scale software and has numerous loose-coupled components, this paper describes the pythonic approach to implement this platform. By mixing the high-level interpreted Python language and the compiled languages like Fortran/C/C++ in an effective method, this approach can achieve a combination of code efficiency, flexibility and compactness

  18. Understanding network hacks attack and defense with Python

    CERN Document Server

    Ballmann, Bastian

    2015-01-01

    This book explains how to see one's own network through the eyes of an attacker, to understand their techniques and effectively protect against them. Through Python code samples the reader learns to code tools on subjects such as password sniffing, ARP poisoning, DNS spoofing, SQL injection, Google harvesting and Wifi hacking. Furthermore the reader will be introduced to defense methods such as intrusion detection and prevention systems and log file analysis by diving into code.

  19. Python for teaching introductory programming: A quantitative evaluation

    OpenAIRE

    Jayal, A; Lauria, S; Tucker, A; Swift, S

    2011-01-01

    This paper compares two different approaches of teaching introductory programming by quantitatively analysing the student assessments in a real classroom. The first approach is to emphasise the principles of object-oriented programming and design using Java from the very beginning. The second approach is to first teach the basic programming concepts (loops, branch, and use of libraries) using Python and then move on to oriented programming using Java. Each approach was adopted for one academi...

  20. CS Circles: An In-Browser Python Course for Beginners

    OpenAIRE

    Pritchard, David; Vasiga, Troy

    2012-01-01

    Computer Science Circles is a free programming website for beginners that is designed to be fun, easy to use, and accessible to the broadest possible audience. We teach Python since it is simple yet powerful, and the course content is well-structured but written in plain language. The website has over one hundred exercises in thirty lesson pages, plus special features to help teachers support their students. It is available in both English and French. We discuss the philosophy behind the cour...

  1. A Python Engine for Teaching Artificial Intelligence in Games

    OpenAIRE

    Riedl, Mark O.

    2015-01-01

    Computer games play an important role in our society and motivate people to learn computer science. Since artificial intelligence is integral to most games, they can also be used to teach artificial intelligence. We introduce the Game AI Game Engine (GAIGE), a Python game engine specifically designed to teach about how AI is used in computer games. A progression of seven assignments builds toward a complete, working Multi-User Battle Arena (MOBA) game. We describe the engine, the assignments,...

  2. Python as a federation tool for GENESIS 3.0.

    Science.gov (United States)

    Cornelis, Hugo; Rodriguez, Armando L; Coop, Allan D; Bower, James M

    2012-01-01

    The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be 'glued' together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational models

  3. Python as a Federation Tool for GENESIS 3.0

    Science.gov (United States)

    Cornelis, Hugo; Rodriguez, Armando L.; Coop, Allan D.; Bower, James M.

    2012-01-01

    The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be ‘glued’ together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational

  4. PALSE: Python Analysis of Large Scale (Computer) Experiments

    OpenAIRE

    Cazals, Frédéric; Dreyfus, Tom; Malod-Dognin, Noël; Lhéritier, Alix

    2012-01-01

    A tenet of Science is the ability to reproduce the results, and a related issue is the possibility to archive and interpret the raw results of (computer) experiments. This paper presents an elementary python framework addressing this latter goal. Consider a computing pipeline consisting of raw data generation, raw data parsing, and data analysis i.e. graphical and statistical analysis. palse addresses these last two steps by leveraging the hierarchical structure of XML documents. More precise...

  5. Scikit-Learn: Machine Learning in the Python ecosystem

    OpenAIRE

    Louppe, Gilles; Varoquaux, Gaël

    2013-01-01

    The scikit-learn project is an increasingly popular machine learning library written in Python. It is designed to be simple and efficient, useful to both experts and non-experts, and reusable in a variety of contexts. The primary aim of the project is to provide a compendium of efficient implementations of classic, well-established machine learning algorithms. Among other things, it includes classical supervised and unsupervised learning algorithms, tools for model evaluation and selection, a...

  6. Seglearn: A Python Package for Learning Sequences and Time Series

    OpenAIRE

    Burns, David M.; Whyne, Cari M.

    2018-01-01

    Seglearn is an open-source python package for machine learning time series or sequences using a sliding window segmentation approach. The implementation provides a flexible pipeline for tackling classification, regression, and forecasting problems with multivariate sequence and contextual data. This package is compatible with scikit-learn and is listed under scikit-learn Related Projects. The package depends on numpy, scipy, and scikit-learn. Seglearn is distributed under the BSD 3-Clause Lic...

  7. Output Data as an HTML File with Python

    Directory of Open Access Journals (Sweden)

    William J. Turkel

    2012-07-01

    Full Text Available This lesson takes the frequency pairs created in Counting Frequencies and outputs them to an HTML file. Here you will learn how to output data as an HTML file using Python. You will also learn about string formatting. The final result is an HTML file that shows the keywords found in the original source in order of descending frequency, along with the number of times that each keyword appears.

  8. A Community Python Library for Solar Physics (SunPy)

    Science.gov (United States)

    Christe, Steven; Shih, A. Y.; Ireland, J.; Perez-Suarez, D.; Mumford, S.; Hughitt, V. K.; Hewett, R.; Mayer, F.; SunPy Dev Team

    2013-07-01

    Python, a free, cross platform, general purpose, high-level programming language, has seen widespread adoption among the scientific community resulting in the availability of a large range of software, from numerical computation (NumPy, SciPy) and machine learning to spectral analysis and visualization (Matplotlib). SunPy is a data analysis toolkit specializing in providing the software necessary to analyze solar and heliospheric datasets in Python. It aims to provide a free and open-source alternative to the IDL-based SolarSoft (SSW) solar data analysis environment. We present the latest release of SunPy (0.3). This release includes a major refactor of the main SunPy code to improve ease of use for the user as well as a more consistent interface. SunPy provides downloading capability through integration with the Virtual Solar Observatory (VSO) and the the Heliophysics Event Knowledgebase (HEK). It can open image fits files from major solar missions (SDO/AIA, SOHO/EIT, SOHO/LASCO, STEREO) into WCS-aware maps. SunPy provides advanced time-series tools for data from mission such as GOES, SDO/EVE, and Proba2/LYRA as well as support for radio spectra (e.g. e-Callisto). We present examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing data analysis tools already available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy.

  9. Betrayal: radio-tagged Burmese pythons reveal locations of conspecifics in Everglades National Park

    Science.gov (United States)

    Smith, Brian J.; Cherkiss, Michael S.; Hart, Kristen M.; Rochford, Michael R.; Selby, Thomas H.; Snow, Ray W; Mazzotti, Frank J.

    2016-01-01

    The “Judas” technique is based on the idea that a radio-tagged individual can be used to “betray” conspecifics during the course of its routine social behavior. The Burmese python (Python bivittatus) is an invasive constrictor in southern Florida, and few methods are available for its control. Pythons are normally solitary, but from December–April in southern Florida, they form breeding aggregations containing up to 8 individuals, providing an opportunity to apply the technique. We radio-tracked 25 individual adult pythons of both sexes during the breeding season from 2007–2012. Our goals were to (1) characterize python movements and determine habitat selection for betrayal events, (2) quantify betrayal rates of Judas pythons, and (3) compare the efficacy of this tool with current tools for capturing pythons, both in terms of cost per python removed (CPP) and catch per unit effort (CPUE). In a total of 33 python-seasons, we had 8 betrayal events (24 %) in which a Judas python led us to new pythons. Betrayal events occurred more frequently in lowland forest (including tree islands) than would be expected by chance alone. These 8 events resulted in the capture of 14 new individuals (1–4 new pythons per event). Our effort comparison shows that while the Judas technique is more costly than road cruising surveys per python removed, the Judas technique yields more large, reproductive females and is effective at a time of year that road cruising is not, making it a potential complement to the status quo removal effort.

  10. ACPYPE - AnteChamber PYthon Parser interfacE

    Directory of Open Access Journals (Sweden)

    Sousa da Silva Alan W

    2012-07-01

    Full Text Available Abstract Background ACPYPE (or AnteChamber PYthon Parser interfacE is a wrapper script around the ANTECHAMBER software that simplifies the generation of small molecule topologies and parameters for a variety of molecular dynamics programmes like GROMACS, CHARMM and CNS. It is written in the Python programming language and was developed as a tool for interfacing with other Python based applications such as the CCPN software suite (for NMR data analysis and ARIA (for structure calculations from NMR data. ACPYPE is open source code, under GNU GPL v3, and is available as a stand-alone application at http://www.ccpn.ac.uk/acpype and as a web portal application at http://webapps.ccpn.ac.uk/acpype. Findings We verified the topologies generated by ACPYPE in three ways: by comparing with default AMBER topologies for standard amino acids; by generating and verifying topologies for a large set of ligands from the PDB; and by recalculating the structures for 5 protein–ligand complexes from the PDB. Conclusions ACPYPE is a tool that simplifies the automatic generation of topology and parameters in different formats for different molecular mechanics programmes, including calculation of partial charges, while being object oriented for integration with other applications.

  11. Text Mining in Python through the HTRC Feature Reader

    Directory of Open Access Journals (Sweden)

    Peter Organisciak

    2016-11-01

    Full Text Available We introduce a toolkit for working with the 13.6 million volume Extracted Features Dataset from the HathiTrust Research Center. You will learn how to peer at the words and trends of any book in the collection, while developing broadly useful Python data analysis skills. The HathiTrust holds nearly 15 million digitized volumes from libraries around the world. In addition to their individual value, these works in aggregate are extremely valuable for historians. Spanning many centuries and genres, they offer a way to learn about large-scale trends in history and culture, as well as evidence for changes in language or even the structure of the book. To simplify access to this collection the HathiTrust Research Center (HTRC has released the Extracted Features dataset (Capitanu et al. 2015: a dataset that provides quantitative information describing every page of every volume in the collection. In this lesson, we introduce the HTRC Feature Reader, a library for working with the HTRC Extracted Features dataset using the Python programming language. The HTRC Feature Reader is structured to support work using popular data science libraries, particularly Pandas. Pandas provides simple structures for holding data and powerful ways to interact with it. The HTRC Feature Reader uses these data structures, so learning how to use it will also cover general data analysis skills in Python.

  12. ACPYPE - AnteChamber PYthon Parser interfacE.

    Science.gov (United States)

    Sousa da Silva, Alan W; Vranken, Wim F

    2012-07-23

    ACPYPE (or AnteChamber PYthon Parser interfacE) is a wrapper script around the ANTECHAMBER software that simplifies the generation of small molecule topologies and parameters for a variety of molecular dynamics programmes like GROMACS, CHARMM and CNS. It is written in the Python programming language and was developed as a tool for interfacing with other Python based applications such as the CCPN software suite (for NMR data analysis) and ARIA (for structure calculations from NMR data). ACPYPE is open source code, under GNU GPL v3, and is available as a stand-alone application at http://www.ccpn.ac.uk/acpype and as a web portal application at http://webapps.ccpn.ac.uk/acpype. We verified the topologies generated by ACPYPE in three ways: by comparing with default AMBER topologies for standard amino acids; by generating and verifying topologies for a large set of ligands from the PDB; and by recalculating the structures for 5 protein-ligand complexes from the PDB. ACPYPE is a tool that simplifies the automatic generation of topology and parameters in different formats for different molecular mechanics programmes, including calculation of partial charges, while being object oriented for integration with other applications.

  13. DendroPy: a Python library for phylogenetic computing.

    Science.gov (United States)

    Sukumaran, Jeet; Holder, Mark T

    2010-06-15

    DendroPy is a cross-platform library for the Python programming language that provides for object-oriented reading, writing, simulation and manipulation of phylogenetic data, with an emphasis on phylogenetic tree operations. DendroPy uses a splits-hash mapping to perform rapid calculations of tree distances, similarities and shape under various metrics. It contains rich simulation routines to generate trees under a number of different phylogenetic and coalescent models. DendroPy's data simulation and manipulation facilities, in conjunction with its support of a broad range of phylogenetic data formats (NEXUS, Newick, PHYLIP, FASTA, NeXML, etc.), allow it to serve a useful role in various phyloinformatics and phylogeographic pipelines. The stable release of the library is available for download and automated installation through the Python Package Index site (http://pypi.python.org/pypi/DendroPy), while the active development source code repository is available to the public from GitHub (http://github.com/jeetsukumaran/DendroPy).

  14. DREAMTools: a Python package for scoring collaborative challenges.

    Science.gov (United States)

    Cokelaer, Thomas; Bansal, Mukesh; Bare, Christopher; Bilal, Erhan; Bot, Brian M; Chaibub Neto, Elias; Eduati, Federica; de la Fuente, Alberto; Gönen, Mehmet; Hill, Steven M; Hoff, Bruce; Karr, Jonathan R; Küffner, Robert; Menden, Michael P; Meyer, Pablo; Norel, Raquel; Pratap, Abhishek; Prill, Robert J; Weirauch, Matthew T; Costello, James C; Stolovitzky, Gustavo; Saez-Rodriguez, Julio

    2015-01-01

    DREAM challenges are community competitions designed to advance computational methods and address fundamental questions in system biology and translational medicine. Each challenge asks participants to develop and apply computational methods to either predict unobserved outcomes or to identify unknown model parameters given a set of training data. Computational methods are evaluated using an automated scoring metric, scores are posted to a public leaderboard, and methods are published to facilitate community discussions on how to build improved methods. By engaging participants from a wide range of science and engineering backgrounds, DREAM challenges can comparatively evaluate a wide range of statistical, machine learning, and biophysical methods. Here, we describe DREAMTools, a Python package for evaluating DREAM challenge scoring metrics. DREAMTools provides a command line interface that enables researchers to test new methods on past challenges, as well as a framework for scoring new challenges. As of March 2016, DREAMTools includes more than 80% of completed DREAM challenges. DREAMTools complements the data, metadata, and software tools available at the DREAM website http://dreamchallenges.org and on the Synapse platform at https://www.synapse.org.   DREAMTools is a Python package. Releases and documentation are available at http://pypi.python.org/pypi/dreamtools. The source code is available at http://github.com/dreamtools/dreamtools.

  15. DREAMTools: a Python package for scoring collaborative challenges

    Science.gov (United States)

    Cokelaer, Thomas; Bansal, Mukesh; Bare, Christopher; Bilal, Erhan; Bot, Brian M.; Chaibub Neto, Elias; Eduati, Federica; de la Fuente, Alberto; Gönen, Mehmet; Hill, Steven M.; Hoff, Bruce; Karr, Jonathan R.; Küffner, Robert; Menden, Michael P.; Meyer, Pablo; Norel, Raquel; Pratap, Abhishek; Prill, Robert J.; Weirauch, Matthew T.; Costello, James C.; Stolovitzky, Gustavo; Saez-Rodriguez, Julio

    2016-01-01

    DREAM challenges are community competitions designed to advance computational methods and address fundamental questions in system biology and translational medicine. Each challenge asks participants to develop and apply computational methods to either predict unobserved outcomes or to identify unknown model parameters given a set of training data. Computational methods are evaluated using an automated scoring metric, scores are posted to a public leaderboard, and methods are published to facilitate community discussions on how to build improved methods. By engaging participants from a wide range of science and engineering backgrounds, DREAM challenges can comparatively evaluate a wide range of statistical, machine learning, and biophysical methods. Here, we describe DREAMTools, a Python package for evaluating DREAM challenge scoring metrics. DREAMTools provides a command line interface that enables researchers to test new methods on past challenges, as well as a framework for scoring new challenges. As of March 2016, DREAMTools includes more than 80% of completed DREAM challenges. DREAMTools complements the data, metadata, and software tools available at the DREAM website http://dreamchallenges.org and on the Synapse platform at https://www.synapse.org. Availability:  DREAMTools is a Python package. Releases and documentation are available at http://pypi.python.org/pypi/dreamtools. The source code is available at http://github.com/dreamtools/dreamtools. PMID:27134723

  16. VPython: Python plus Animations in Stereo 3D

    Science.gov (United States)

    Sherwood, Bruce

    2004-03-01

    Python is a modern object-oriented programming language. VPython (http://vpython.org) is a combination of Python (http://python.org), the Numeric module from LLNL (http://www.pfdubois.com/numpy), and the Visual module created by David Scherer, all of which have been under continuous development as open source projects. VPython makes it easy to write programs that generate real-time, navigable 3D animations. The Visual module includes a set of 3D objects (sphere, cylinder, arrow, etc.), tools for creating other shapes, and support for vector algebra. The 3D renderer runs in a parallel thread, and animations are produced as a side effect of computations, freeing the programmer to concentrate on the physics. Applications include educational and research visualization. In the Fall of 2003 Hugh Fisher at the Australian National University, John Zelle at Wartburg College, and I contributed to a new stereo capability of VPython. By adding a single statement to an existing VPython program, animations can be viewed in true stereo 3D. One can choose several modes: active shutter glasses, passive polarized glasses, or colored glasses (e.g. red-cyan). The talk will demonstrate the new stereo capability and discuss the pros and cons of various schemes for display of stereo 3D for a large audience. Supported in part by NSF grant DUE-0237132.

  17. BioC implementations in Go, Perl, Python and Ruby.

    Science.gov (United States)

    Liu, Wanli; Islamaj Doğan, Rezarta; Kwon, Dongseop; Marques, Hernani; Rinaldi, Fabio; Wilbur, W John; Comeau, Donald C

    2014-01-01

    As part of a communitywide effort for evaluating text mining and information extraction systems applied to the biomedical domain, BioC is focused on the goal of interoperability, currently a major barrier to wide-scale adoption of text mining tools. BioC is a simple XML format, specified by DTD, for exchanging data for biomedical natural language processing. With initial implementations in C++ and Java, BioC provides libraries of code for reading and writing BioC text documents and annotations. We extend BioC to Perl, Python, Go and Ruby. We used SWIG to extend the C++ implementation for Perl and one Python implementation. A second Python implementation and the Ruby implementation use native data structures and libraries. BioC is also implemented in the Google language Go. BioC modules are functional in all of these languages, which can facilitate text mining tasks. BioC implementations are freely available through the BioC site: http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net/ Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

  18. GAiN: Distributed Array Computation with Python

    Energy Technology Data Exchange (ETDEWEB)

    Daily, Jeffrey A. [Washington State Univ., Pullman, WA (United States)

    2009-05-01

    Scientific computing makes use of very large, multidimensional numerical arrays - typically, gigabytes to terabytes in size - much larger than can fit on even the largest single compute node. Such arrays must be distributed across a "cluster" of nodes. Global Arrays is a cluster-based software system from Battelle Pacific Northwest National Laboratory that enables an efficient, portable, and parallel shared-memory programming interface to manipulate these arrays. Written in and for the C and FORTRAN programming languages, it takes advantage of high-performance cluster interconnections to allow any node in the cluster to access data on any other node very rapidly. The "numpy" module is the de facto standard for numerical calculation in the Python programming language, a language whose use is growing rapidly in the scientific and engineering communities. numpy provides a powerful N-dimensional array class as well as other scientific computing capabilities. However, like the majority of the core Python modules, numpy is inherently serial. Our system, GAiN (Global Arrays in NumPy), is a parallel extension to Python that accesses Global Arrays through numpy. This allows parallel processing and/or larger problem sizes to be harnessed almost transparently within new or existing numpy programs.

  19. User-friendly parallelization of GAUDI applications with Python

    International Nuclear Information System (INIS)

    Mato, Pere; Smith, Eoin

    2010-01-01

    GAUDI is a software framework in C++ used to build event data processing applications using a set of standard components with well-defined interfaces. Simulation, high-level trigger, reconstruction, and analysis programs used by several experiments are developed using GAUDI. These applications can be configured and driven by simple Python scripts. Given the fact that a considerable amount of existing software has been developed using serial methodology, and has existed in some cases for many years, implementation of parallelisation techniques at the framework level may offer a way of exploiting current multi-core technologies to maximize performance and reduce latencies without re-writing thousands/millions of lines of code. In the solution we have developed, the parallelization techniques are introduced to the high level Python scripts which configure and drive the applications, such that the core C++ application code requires no modification, and that end users need make only minimal changes to their scripts. The developed solution leverages from existing generic Python modules that support parallel processing. Naturally, the parallel version of a given program should produce results consistent with its serial execution. The evaluation of several prototypes incorporating various parallelization techniques are presented and discussed.

  20. ELLIPT2D: A Flexible Finite Element Code Written Python

    International Nuclear Information System (INIS)

    Pletzer, A.; Mollis, J.C.

    2001-01-01

    The use of the Python scripting language for scientific applications and in particular to solve partial differential equations is explored. It is shown that Python's rich data structure and object-oriented features can be exploited to write programs that are not only significantly more concise than their counter parts written in Fortran, C or C++, but are also numerically efficient. To illustrate this, a two-dimensional finite element code (ELLIPT2D) has been written. ELLIPT2D provides a flexible and easy-to-use framework for solving a large class of second-order elliptic problems. The program allows for structured or unstructured meshes. All functions defining the elliptic operator are user supplied and so are the boundary conditions, which can be of Dirichlet, Neumann or Robbins type. ELLIPT2D makes extensive use of dictionaries (hash tables) as a way to represent sparse matrices.Other key features of the Python language that have been widely used include: operator over loading, error handling, array slicing, and the Tkinter module for building graphical use interfaces. As an example of the utility of ELLIPT2D, a nonlinear solution of the Grad-Shafranov equation is computed using a Newton iterative scheme. A second application focuses on a solution of the toroidal Laplace equation coupled to a magnetohydrodynamic stability code, a problem arising in the context of magnetic fusion research

  1. Hearing with an atympanic ear: good vibration and poor sound-pressure detection in the royal python, Python regius.

    Science.gov (United States)

    Christensen, Christian Bech; Christensen-Dalsgaard, Jakob; Brandt, Christian; Madsen, Peter Teglberg

    2012-01-15

    Snakes lack both an outer ear and a tympanic middle ear, which in most tetrapods provide impedance matching between the air and inner ear fluids and hence improve pressure hearing in air. Snakes would therefore be expected to have very poor pressure hearing and generally be insensitive to airborne sound, whereas the connection of the middle ear bone to the jaw bones in snakes should confer acute sensitivity to substrate vibrations. Some studies have nevertheless claimed that snakes are quite sensitive to both vibration and sound pressure. Here we test the two hypotheses that: (1) snakes are sensitive to sound pressure and (2) snakes are sensitive to vibrations, but cannot hear the sound pressure per se. Vibration and sound-pressure sensitivities were quantified by measuring brainstem evoked potentials in 11 royal pythons, Python regius. Vibrograms and audiograms showed greatest sensitivity at low frequencies of 80-160 Hz, with sensitivities of -54 dB re. 1 m s(-2) and 78 dB re. 20 μPa, respectively. To investigate whether pythons detect sound pressure or sound-induced head vibrations, we measured the sound-induced head vibrations in three dimensions when snakes were exposed to sound pressure at threshold levels. In general, head vibrations induced by threshold-level sound pressure were equal to or greater than those induced by threshold-level vibrations, and therefore sound-pressure sensitivity can be explained by sound-induced head vibration. From this we conclude that pythons, and possibly all snakes, lost effective pressure hearing with the complete reduction of a functional outer and middle ear, but have an acute vibration sensitivity that may be used for communication and detection of predators and prey.

  2. OzPythonPlex: An optimised forensic STR multiplex assay set for the Australasian carpet python (Morelia spilota).

    Science.gov (United States)

    Ciavaglia, Sherryn; Linacre, Adrian

    2018-03-02

    Reptile species, and in particular snakes, are protected by national and international agreements yet are commonly handled illegally. To aid in the enforcement of such legislation, we report on the development of three 11-plex assays from the genome of the carpet python to type 24 loci of tetra-nucleotide and penta-nucleotide repeat motifs (pure, compound and complex included). The loci range in size between 70 and 550 bp. Seventeen of the loci are newly characterised with the inclusion of seven previously developed loci to facilitate cross-comparison with previous carpet python genotyping studies. Assays were optimised in accordance with human forensic profiling kits using one nanogram template DNA. Three loci are included in all three of the multiplex reactions as quality assurance markers, to ensure sample identity and genotyping accuracy is maintained across the three profiling assays. Allelic ladders have been developed for the three assays to ensure consistent and precise allele designation. A DNA reference database of allele frequencies is presented based on 249 samples collected from throughout the species native range. A small number of validation tests are conducted to demonstrate the utility of these multiplex assays. We suggest further appropriate validation tests that should be conducted prior to the application of the multiplex assays in criminal investigations involving carpet pythons. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. The big squeeze: scaling of constriction pressure in two of the world's largest snakes, Python reticulatus and Python molurus bivittatus.

    Science.gov (United States)

    Penning, David A; Dartez, Schuyler F; Moon, Brad R

    2015-11-01

    Snakes are important predators that have radiated throughout many ecosystems, and constriction was important in their radiation. Constrictors immobilize and kill prey by using body loops to exert pressure on their prey. Despite its importance, little is known about constriction performance or its full effects on prey. We studied the scaling of constriction performance in two species of giant pythons (Python reticulatus and Python molurus bivittatus) and propose a new mechanism of prey death by constriction. In both species, peak constriction pressure increased significantly with snake diameter. These and other constrictors can exert pressures dramatically higher than their prey's blood pressure, suggesting that constriction can stop circulatory function and perhaps kill prey rapidly by over-pressurizing the brain and disrupting neural function. We propose the latter 'red-out effect' as another possible mechanism of prey death from constriction. These effects may be important to recognize and treat properly in rare cases when constrictors injure humans. © 2015. Published by The Company of Biologists Ltd.

  4. Programski jezik MicroPython na mikrokrmilnikih ARM Cortex-M4

    OpenAIRE

    Brajnik, Mark

    2017-01-01

    V sklopu diplomske naloge je narejen pregled programskega jezika MicroPython in primerjava z najpogosteje uporabljenima programskima jezikoma za mikrokrmilnike. MicroPython smo uporabili za programiranje razvojne plošče Nucleo L476RG. Opravili smo namestitev MicroPython strojno-programske opreme na razvojno ploščo Nucleo L476RG, primerjali hitrost izvajanja programske kode z Arduinom Uno ter prikazali uporabo MicroPythona in Arduina na primerih sledilnega robota in PID krmiljenja elektromotor...

  5. Schopnosti překladačů programovacího jazyka Python

    OpenAIRE

    Pala, Ondřej

    2015-01-01

    PALA, Ondřej. Ability of compilers programming language Python. Brno, 2015. Diploma thesis. Mendel university in Brno. Diploma thesis rate ability of selected compilers programming language Python. First path of thesis is focused to programming language Python and principle of working compilers. Second path is focused to creating testing tasks, defining eva-luation criterias of compilers and testing compilers without testing tasks.

  6. Working with and Visualizing Big Data Efficiently with Python for the DARPA XDATA Program

    Science.gov (United States)

    2017-08-01

    CPUs and GPUs. - Dask: Parallelizes generic Python and extends NumPy, Pandas, and Scikit- learn with parallel variants. - Bokeh: Create...interface technologies. Focus was on being able to use an accessible language like Python , which domain experts can easily learn , for these...applications without requiring the user to learn web-specific technologies such as javascript and CSS. • Numba allows Python users to effectively use

  7. PyEEG: an open source Python module for EEG/MEG feature extraction.

    Science.gov (United States)

    Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

    2011-01-01

    Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.

  8. MongoDB and Python Patterns and processes for the popular document-oriented database

    CERN Document Server

    O'Higgins, Niall

    2011-01-01

    Learn how to leverage MongoDB with your Python applications, using the hands-on recipes in this book. You get complete code samples for tasks such as making fast geo queries for location-based apps, efficiently indexing your user documents for social-graph lookups, and many other scenarios. This guide explains the basics of the document-oriented database and shows you how to set up a Python environment with it. Learn how to read and write to MongoDB, apply idiomatic MongoDB and Python patterns, and use the database with several popular Python web frameworks. You'll discover how to model your

  9. First record of invasive Burmese Python oviposition and brooding inside an anthropogenic structure

    Science.gov (United States)

    Hanslowe, Emma; Falk, Bryan; Collier, Michelle A. M.; Josimovich, Jillian; Rahill, Thomas; Reed, Robert

    2016-01-01

    We discovered an adult female Python bivittatus (Burmese Python) coiled around a clutch of 25 eggs in a cement culvert in Flamingo, FL, in Everglades National Park. To our knowledge, this is the first record of an invasive Burmese Python laying eggs and brooding inside an anthropogenic structure in Florida. A 92% hatch-success rate suggests that the cement culvert provided suitable conditions for oviposition, embryonic development, and hatching. Given the plenitude of such anthropogenic structures across the landscape, available sites for oviposition and brooding may not be limiting for the invasive Burmese Python population.

  10. pyhector: A Python interface for the simple climate model Hector

    Energy Technology Data Exchange (ETDEWEB)

    N Willner, Sven; Hartin, Corinne; Gieseke, Robert

    2017-04-01

    Pyhector is a Python interface for the simple climate model Hector (Hartin et al. 2015) developed in C++. Simple climate models like Hector can, for instance, be used in the analysis of scenarios within integrated assessment models like GCAM1, in the emulation of complex climate models, and in uncertainty analyses. Hector is an open-source, object oriented, simple global climate carbon cycle model. Its carbon cycle consists of a one pool atmosphere, three terrestrial pools which can be broken down into finer biomes or regions, and four carbon pools in the ocean component. The terrestrial carbon cycle includes primary production and respiration fluxes. The ocean carbon cycle circulates carbon via a simplified thermohaline circulation, calculating air-sea fluxes as well as the marine carbonate system (Hartin et al. 2016). The model input is time series of greenhouse gas emissions; as example scenarios for these the Pyhector package contains the Representative Concentration Pathways (RCPs)2. These were developed to cover the range of baseline and mitigation emissions scenarios and are widely used in climate change research and model intercomparison projects. Using DataFrames from the Python library Pandas (McKinney 2010) as a data structure for the scenarios simplifies generating and adapting scenarios. Other parameters of the Hector model can easily be modified when running the model. Pyhector can be installed using pip from the Python Package Index.3 Source code and issue tracker are available in Pyhector's GitHub repository4. Documentation is provided through Readthedocs5. Usage examples are also contained in the repository as a Jupyter Notebook (Pérez and Granger 2007; Kluyver et al. 2016). Courtesy of the Mybinder project6, the example Notebook can also be executed and modified without installing Pyhector locally.

  11. Unbinned likelihood maximisation framework for neutrino clustering in Python

    Energy Technology Data Exchange (ETDEWEB)

    Coenders, Stefan [Technische Universitaet Muenchen, Boltzmannstr. 2, 85748 Garching (Germany)

    2016-07-01

    Albeit having detected an astrophysical neutrino flux with IceCube, sources of astrophysical neutrinos remain hidden up to now. A detection of a neutrino point source is a smoking gun for hadronic processes and acceleration of cosmic rays. The search for neutrino sources has many degrees of freedom, for example steady versus transient, point-like versus extended sources, et cetera. Here, we introduce a Python framework designed for unbinned likelihood maximisations as used in searches for neutrino point sources by IceCube. Implementing source scenarios in a modular way, likelihood searches on various kinds can be implemented in a user-friendly way, without sacrificing speed and memory management.

  12. El lenguaje de programación Python

    OpenAIRE

    Ivet Challenger-Pérez; Yanet Díaz-Ricardo; Roberto Antonio Becerra-García

    2014-01-01

    El software libre se ha convertido en uno de los movimientos tecnológicos de mayor auge en el siglo XXI. Para su desarrollo ha sido necesario contar con un grupo de herramientas que hagan óptima su utilización y sean fáciles de aprender. Python es un lenguaje de programación que cumple con lo planteado y se viene perfilando como una opción recomendada para el desarrollo de software libre. En este artículo se realizó un análisis de sus características fundamentales, así como de los principales...

  13. The fast azimuthal integration Python library: pyFAI.

    Science.gov (United States)

    Ashiotis, Giannis; Deschildre, Aurore; Nawaz, Zubair; Wright, Jonathan P; Karkoulis, Dimitrios; Picca, Frédéric Emmanuel; Kieffer, Jérôme

    2015-04-01

    pyFAI is an open-source software package designed to perform azimuthal integration and, correspondingly, two-dimensional regrouping on area-detector frames for small- and wide-angle X-ray scattering experiments. It is written in Python (with binary submodules for improved performance), a language widely accepted and used by the scientific community today, which enables users to easily incorporate the pyFAI library into their processing pipeline. This article focuses on recent work, especially the ease of calibration, its accuracy and the execution speed for integration.

  14. The definitive guide to Jython Python for the Java platform

    CERN Document Server

    Juneau, Josh; Ng, Victor; Soto, Leo; Wierzbicki, Frank

    2010-01-01

    Jython is an open source implementation of the high-level, dynamic, object-oriented scripting language Python seamlessly integrated with the Java platform. The predecessor to Jython, JPython, is certified as 100% Pure Java. Jython is freely available for both commercial and noncommercial use and is distributed with source code. Jython is complementary to Java. The Definitive Guide to Jython, written by the official Jython team leads, covers the latest Jython 2.5 (or 2.5.x) from the basics to the advanced features. This book begins with a brief introduction to the language and then journeys thr

  15. An object oriented Python interface for atomistic simulations

    Science.gov (United States)

    Hynninen, T.; Himanen, L.; Parkkinen, V.; Musso, T.; Corander, J.; Foster, A. S.

    2016-01-01

    Programmable simulation environments allow one to monitor and control calculations efficiently and automatically before, during, and after runtime. Environments directly accessible in a programming environment can be interfaced with powerful external analysis tools and extensions to enhance the functionality of the core program, and by incorporating a flexible object based structure, the environments make building and analysing computational setups intuitive. In this work, we present a classical atomistic force field with an interface written in Python language. The program is an extension for an existing object based atomistic simulation environment.

  16. Interfacing of high temperature Z-meter setup using python

    Science.gov (United States)

    Patel, Ashutosh; Sisodia, Shashank; Pandey, Sudhir K.

    2017-05-01

    In this work, we interface high temperature Z-meter setup to automize the whole measurement process. A program is built on open source programming language `Python' which convert the manual measurement process into fully automated process without any cost addition. Using this program, simultaneous measurement of Seebeck coefficient (α), thermal conductivity (κ) and electrical resistivity (ρ), are performed and using all three, figure-of-merit (ZT) is calculated. Developed program is verified by performing measurement over p-type Bi0.36Sb1.45Te3 sample and the data obtained are found to be in good agreement with the reported data.

  17. BiEntropy for Python v. 1.0

    Energy Technology Data Exchange (ETDEWEB)

    2018-03-15

    This Python package provides high-performance implementations of the functions and examples presented in "BiEntropy - The Approximate Entropy of a Finite Binary String" by Grenville J. Croll, presented at ANPA 34 in 2013. https://arxiv.org/abs/1305.0954 According to the paper, BiEntropy is "a simple algorithm which computes the approximate entropy of a finite binary string of arbitrary length" using "a weighted average of the Shannon Entropies of the string and all but the last binary derivative of the string."

  18. Specifying the Behaviour of Python Programs: Language and Basic Examples

    Directory of Open Access Journals (Sweden)

    2010-04-01

    Full Text Available This manuscript describe BeSSY, a function-centric language for formal behavioural specification that requires no more than high-school mathematics on arithmetic, functions, Boolean algebra and sets theory. An object can be modelled as a union of data sets and functions whereas inherited object can be modelled as a union of supersets and a set of object-specific functions. Python list and dictionary operations will be specified in BeSSY for illustration.

  19. Spherical Panorama Visualization of Astronomical Data with Blender and Python

    Science.gov (United States)

    Kent, Brian R.

    2016-06-01

    We describe methodology to generate 360 degree spherical panoramas of both 2D and 3D data. The techniques apply to a variety of astronomical data types - all sky maps, 2D and 3D catalogs as well as planetary surface maps. The results can be viewed in a desktop browser or interactively with a mobile phone or tablet. Static displays or panoramic video renderings of the data can be produced. We review the Python code and usage of the 3D Blender software for projecting maps onto 3D surfaces and the various tools for distributing visualizations.

  20. Rapid Microsatellite Marker Development Using Next Generation Pyrosequencing to Inform Invasive Burmese Python—Python molurus bivittatus—Management

    Directory of Open Access Journals (Sweden)

    Kristen M. Hart

    2013-02-01

    Full Text Available Invasive species represent an increasing threat to native ecosystems, harming indigenous taxa through predation, habitat modification, cross-species hybridization and alteration of ecosystem processes. Additionally, high economic costs are associated with environmental damage, restoration and control measures. The Burmese python, Python molurus bivittatus, is one of the most notable invasive species in the US, due to the threat it poses to imperiled species and the Greater Everglades ecosystem. To address population structure and relatedness, next generation sequencing was used to rapidly produce species-specific microsatellite loci. The Roche 454 GS-FLX Titanium platform provided 6616 di-, tri- and tetra-nucleotide repeats in 117,516 sequences. Using stringent criteria, 24 of 26 selected tri- and tetra-nucleotide loci were polymerase chain reaction (PCR amplified and 18 were polymorphic. An additional six cross-species loci were amplified, and the resulting 24 loci were incorporated into eight PCR multiplexes. Multi-locus genotypes yielded an average of 61% (39%–77% heterozygosity and 3.7 (2–6 alleles per locus. Population-level studies using the developed microsatellites will track the invasion front and monitor population-suppression dynamics. Additionally, cross-species amplification was detected in the invasive Ball, P. regius, and Northern African python, P. sebae. These markers can be used to address the hybridization potential of Burmese pythons and the larger, more aggressive P. sebae.

  1. Interactions between the invasive Burmese python, Python bivittatus Kuhl, and the local mosquito community in Florida, USA.

    Directory of Open Access Journals (Sweden)

    Lawrence E Reeves

    Full Text Available The Burmese python, Python bivittatus Kuhl, is a well-established invasive species in the greater Everglades ecosystem of southern Florida, USA. Most research on its ecological impacts focuses on its role as a predator and its trophic interactions with native vertebrate species, particularly mammals. Beyond predation, there is little known about the ecological interactions between P. bivittatus and native faunal communities. It is likely that established populations of P. bivittatus in southern Florida serve as hosts for native mosquito communities. To test this concept, we used mitochondrial cytochrome c oxidase subunit I DNA barcoding to determine the hosts of blood fed mosquitoes collected at a research facility in northern Florida where captive P. bivittatus and Argentine black and white tegu, Salvator merianae (Duméril and Bibron, are maintained in outdoor enclosures, accessible to local mosquitoes. We recovered python DNA from the blood meals of three species of Culex mosquitoes: Culex erraticus (Dyar and Knab, Culex quinquefasciatus Say, and Culex pilosus (Dyar and Knab. Culex erraticus conclusively (P = 0.001; Fisher's Exact Test took more blood meals from P. bivittatus than from any other available host. While the majority of mosquito blood meals in our sample were derived from P. bivittatus, only one was derived from S. merianae. These results demonstrate that local mosquitoes will feed on invasive P. bivittatus, a recently introduced host. If these interactions also occur in southern Florida, P. bivittatus may be involved in the transmission networks of mosquito-vectored pathogens. Our results also illustrate the potential of detecting the presence of P. bivittatus in the field through screening mosquito blood meals for their DNA.

  2. Interactions between the invasive Burmese python, Python bivittatus Kuhl, and the local mosquito community in Florida, USA

    Science.gov (United States)

    Krysko, Kenneth L.; Gillett-Kaufman, Jennifer L.; Kawahara, Akito Y.; Connelly, C. Roxanne

    2018-01-01

    The Burmese python, Python bivittatus Kuhl, is a well-established invasive species in the greater Everglades ecosystem of southern Florida, USA. Most research on its ecological impacts focuses on its role as a predator and its trophic interactions with native vertebrate species, particularly mammals. Beyond predation, there is little known about the ecological interactions between P. bivittatus and native faunal communities. It is likely that established populations of P. bivittatus in southern Florida serve as hosts for native mosquito communities. To test this concept, we used mitochondrial cytochrome c oxidase subunit I DNA barcoding to determine the hosts of blood fed mosquitoes collected at a research facility in northern Florida where captive P. bivittatus and Argentine black and white tegu, Salvator merianae (Duméril and Bibron), are maintained in outdoor enclosures, accessible to local mosquitoes. We recovered python DNA from the blood meals of three species of Culex mosquitoes: Culex erraticus (Dyar and Knab), Culex quinquefasciatus Say, and Culex pilosus (Dyar and Knab). Culex erraticus conclusively (P = 0.001; Fisher’s Exact Test) took more blood meals from P. bivittatus than from any other available host. While the majority of mosquito blood meals in our sample were derived from P. bivittatus, only one was derived from S. merianae. These results demonstrate that local mosquitoes will feed on invasive P. bivittatus, a recently introduced host. If these interactions also occur in southern Florida, P. bivittatus may be involved in the transmission networks of mosquito-vectored pathogens. Our results also illustrate the potential of detecting the presence of P. bivittatus in the field through screening mosquito blood meals for their DNA. PMID:29342169

  3. Interactions between the invasive Burmese python, Python bivittatus Kuhl, and the local mosquito community in Florida, USA.

    Science.gov (United States)

    Reeves, Lawrence E; Krysko, Kenneth L; Avery, Michael L; Gillett-Kaufman, Jennifer L; Kawahara, Akito Y; Connelly, C Roxanne; Kaufman, Phillip E

    2018-01-01

    The Burmese python, Python bivittatus Kuhl, is a well-established invasive species in the greater Everglades ecosystem of southern Florida, USA. Most research on its ecological impacts focuses on its role as a predator and its trophic interactions with native vertebrate species, particularly mammals. Beyond predation, there is little known about the ecological interactions between P. bivittatus and native faunal communities. It is likely that established populations of P. bivittatus in southern Florida serve as hosts for native mosquito communities. To test this concept, we used mitochondrial cytochrome c oxidase subunit I DNA barcoding to determine the hosts of blood fed mosquitoes collected at a research facility in northern Florida where captive P. bivittatus and Argentine black and white tegu, Salvator merianae (Duméril and Bibron), are maintained in outdoor enclosures, accessible to local mosquitoes. We recovered python DNA from the blood meals of three species of Culex mosquitoes: Culex erraticus (Dyar and Knab), Culex quinquefasciatus Say, and Culex pilosus (Dyar and Knab). Culex erraticus conclusively (P = 0.001; Fisher's Exact Test) took more blood meals from P. bivittatus than from any other available host. While the majority of mosquito blood meals in our sample were derived from P. bivittatus, only one was derived from S. merianae. These results demonstrate that local mosquitoes will feed on invasive P. bivittatus, a recently introduced host. If these interactions also occur in southern Florida, P. bivittatus may be involved in the transmission networks of mosquito-vectored pathogens. Our results also illustrate the potential of detecting the presence of P. bivittatus in the field through screening mosquito blood meals for their DNA.

  4. Multi-Agent Programming Contest 2016 – The Python-DTU Team

    DEFF Research Database (Denmark)

    Villadsen, Jørgen; Halkjær From, Andreas; Jacobi, Salvador

    2018-01-01

    We provide a detailed description of the Python-DTU system, including the overall system design and the tools used in the agent contest.......We provide a detailed description of the Python-DTU system, including the overall system design and the tools used in the agent contest....

  5. Multi-Agent Programming Contest 2011 - The Python-DTU Team

    DEFF Research Database (Denmark)

    Villadsen, Jørgen; Ettienne, Mikko Berggren; Vester, Steen

    We provide a brief description of the Python-DTU system, including the overall design, the tools and the algorithms that we plan to use in the agent contest.......We provide a brief description of the Python-DTU system, including the overall design, the tools and the algorithms that we plan to use in the agent contest....

  6. Multi-Agent Programming Contest 2012 - The Python-DTU Team

    DEFF Research Database (Denmark)

    Villadsen, Jørgen; Jensen, Andreas Schmidt; Ettienne, Mikko Berggren

    We provide a brief description of the Python-DTU system, including the overall design, the tools and the algorithms that we plan to use in the agent contest.......We provide a brief description of the Python-DTU system, including the overall design, the tools and the algorithms that we plan to use in the agent contest....

  7. Data science and complex networks real case studies with Python

    CERN Document Server

    Caldarelli, Guido

    2016-01-01

    This book provides a comprehensive yet short description of the basic concepts of complex network theory and the code to implement this theory. Differently from other books, we present these concepts starting from real cases of study. The application topics span from food webs, to the Internet, the World Wide Web, and social networks, passing through the international trade web and financial time series. The final part is devoted to definition and implementation of the most important network models. We provide information on the structure of the data and on the quality of available datasets. Furthermore, we provide a series of codes to implement instantly what is described theoretically in the book. People knowing the basis of network theory could learn the art of coding in Python by checking our codes and using the online material. In particular, the interactive Python notebook format is used so that the reader can immediately experiment by themselves with the codes present in the manuscript. To this purpose...

  8. Hardware-accelerated interactive data visualization for neuroscience in Python

    Directory of Open Access Journals (Sweden)

    Cyrille eRossant

    2013-12-01

    Full Text Available Large datasets are becoming more and more common in science, particularly in neuroscience where experimental techniques are rapidly evolving. Obtaining interpretable results from raw data can sometimes be done automatically; however, there are numerous situations where there is a need, at all processing stages, to visualize the data in an interactive way. This enables the scientist to gain intuition, discover unexpected patterns, and find guidance about subsequent analysis steps. Existing visualization tools mostly focus on static publication-quality figures and do not support interactive visualization of large datasets.While working on Python software for visualization of neurophysiological data, we developed techniques to leverage the computational power of modern graphics cards for high-performance interactive data visualization. We were able to achieve very high performance despite the interpreted and dynamic nature of Python, by using state-of-the-art, fast libraries such as NumPy, PyOpenGL and PyTables. We present applications of these methods to visualization of neurophysiological data. We believe our tools will be useful in a broad range of domains, in neuroscience and beyond, where there is an increasing need for scalable and fast interactive visualization.

  9. Hardware-accelerated interactive data visualization for neuroscience in Python.

    Science.gov (United States)

    Rossant, Cyrille; Harris, Kenneth D

    2013-01-01

    Large datasets are becoming more and more common in science, particularly in neuroscience where experimental techniques are rapidly evolving. Obtaining interpretable results from raw data can sometimes be done automatically; however, there are numerous situations where there is a need, at all processing stages, to visualize the data in an interactive way. This enables the scientist to gain intuition, discover unexpected patterns, and find guidance about subsequent analysis steps. Existing visualization tools mostly focus on static publication-quality figures and do not support interactive visualization of large datasets. While working on Python software for visualization of neurophysiological data, we developed techniques to leverage the computational power of modern graphics cards for high-performance interactive data visualization. We were able to achieve very high performance despite the interpreted and dynamic nature of Python, by using state-of-the-art, fast libraries such as NumPy, PyOpenGL, and PyTables. We present applications of these methods to visualization of neurophysiological data. We believe our tools will be useful in a broad range of domains, in neuroscience and beyond, where there is an increasing need for scalable and fast interactive visualization.

  10. New Python-based methods for data processing

    International Nuclear Information System (INIS)

    Sauter, Nicholas K.; Hattne, Johan; Grosse-Kunstleve, Ralf W.; Echols, Nathaniel

    2013-01-01

    The Computational Crystallography Toolbox (cctbx) is a flexible software platform that has been used to develop high-throughput crystal-screening tools for both synchrotron sources and X-ray free-electron lasers. Plans for data-processing and visualization applications are discussed, and the benefits and limitations of using graphics-processing units are evaluated. Current pixel-array detectors produce diffraction images at extreme data rates (of up to 2 TB h −1 ) that make severe demands on computational resources. New multiprocessing frameworks are required to achieve rapid data analysis, as it is important to be able to inspect the data quickly in order to guide the experiment in real time. By utilizing readily available web-serving tools that interact with the Python scripting language, it was possible to implement a high-throughput Bragg-spot analyzer (cctbx.spotfinder) that is presently in use at numerous synchrotron-radiation beamlines. Similarly, Python interoperability enabled the production of a new data-reduction package (cctbx.xfel) for serial femtosecond crystallography experiments at the Linac Coherent Light Source (LCLS). Future data-reduction efforts will need to focus on specialized problems such as the treatment of diffraction spots on interleaved lattices arising from multi-crystal specimens. In these challenging cases, accurate modeling of close-lying Bragg spots could benefit from the high-performance computing capabilities of graphics-processing units

  11. Scoria: a Python module for manipulating 3D molecular data.

    Science.gov (United States)

    Ropp, Patrick; Friedman, Aaron; Durrant, Jacob D

    2017-09-18

    Third-party packages have transformed the Python programming language into a powerful computational-biology tool. Package installation is easy for experienced users, but novices sometimes struggle with dependencies and compilers. This presents a barrier that can hinder the otherwise broad adoption of new tools. We present Scoria, a Python package for manipulating three-dimensional molecular data. Unlike similar packages, Scoria requires no dependencies, compilation, or system-wide installation. One can incorporate the Scoria source code directly into their own programs. But Scoria is not designed to compete with other similar packages. Rather, it complements them. Our package leverages others (e.g. NumPy, SciPy), if present, to speed and extend its own functionality. To show its utility, we use Scoria to analyze a molecular dynamics trajectory. Our FootPrint script colors the atoms of one chain by the frequency of their contacts with a second chain. We are hopeful that Scoria will be a useful tool for the computational-biology community. A copy is available for download free of charge (Apache License 2.0) at http://durrantlab.com/scoria/ . Graphical abstract .

  12. Programming biological models in Python using PySB.

    Science.gov (United States)

    Lopez, Carlos F; Muhlich, Jeremy L; Bachman, John A; Sorger, Peter K

    2013-01-01

    Mathematical equations are fundamental to modeling biological networks, but as networks get large and revisions frequent, it becomes difficult to manage equations directly or to combine previously developed models. Multiple simultaneous efforts to create graphical standards, rule-based languages, and integrated software workbenches aim to simplify biological modeling but none fully meets the need for transparent, extensible, and reusable models. In this paper we describe PySB, an approach in which models are not only created using programs, they are programs. PySB draws on programmatic modeling concepts from little b and ProMot, the rule-based languages BioNetGen and Kappa and the growing library of Python numerical tools. Central to PySB is a library of macros encoding familiar biochemical actions such as binding, catalysis, and polymerization, making it possible to use a high-level, action-oriented vocabulary to construct detailed models. As Python programs, PySB models leverage tools and practices from the open-source software community, substantially advancing our ability to distribute and manage the work of testing biochemical hypotheses. We illustrate these ideas using new and previously published models of apoptosis.

  13. A Distributed Python HPC Framework: ODIN, PyTrilinos, & Seamless

    Energy Technology Data Exchange (ETDEWEB)

    Grant, Robert [Enthought, Inc., Austin, TX (United States)

    2015-11-23

    Under this grant, three significant software packages were developed or improved, all with the goal of improving the ease-of-use of HPC libraries. The first component is a Python package, named DistArray (originally named Odin), that provides a high-level interface to distributed array computing. This interface is based on the popular and widely used NumPy package and is integrated with the IPython project for enhanced interactive parallel distributed computing. The second Python package is the Distributed Array Protocol (DAP) that enables separate distributed array libraries to share arrays efficiently without copying or sending messages. If a distributed array library supports the DAP, it is then automatically able to communicate with any other library that also supports the protocol. This protocol allows DistArray to communicate with the Trilinos library via PyTrilinos, which was also enhanced during this project. A third package, PyTrilinos, was extended to support distributed structured arrays (in addition to the unstructured arrays of its original design), allow more flexible distributed arrays (i.e., the restriction to double precision data was lifted), and implement the DAP. DAP support includes both exporting the protocol so that external packages can use distributed Trilinos data structures, and importing the protocol so that PyTrilinos can work with distributed data from external packages.

  14. CMCpy: Genetic Code-Message Coevolution Models in Python.

    Science.gov (United States)

    Becich, Peter J; Stark, Brian P; Bhat, Harish S; Ardell, David H

    2013-01-01

    Code-message coevolution (CMC) models represent coevolution of a genetic code and a population of protein-coding genes ("messages"). Formally, CMC models are sets of quasispecies coupled together for fitness through a shared genetic code. Although CMC models display plausible explanations for the origin of multiple genetic code traits by natural selection, useful modern implementations of CMC models are not currently available. To meet this need we present CMCpy, an object-oriented Python API and command-line executable front-end that can reproduce all published results of CMC models. CMCpy implements multiple solvers for leading eigenpairs of quasispecies models. We also present novel analytical results that extend and generalize applications of perturbation theory to quasispecies models and pioneer the application of a homotopy method for quasispecies with non-unique maximally fit genotypes. Our results therefore facilitate the computational and analytical study of a variety of evolutionary systems. CMCpy is free open-source software available from http://pypi.python.org/pypi/CMCpy/.

  15. Conservative constraints on early cosmology with MONTE PYTHON

    International Nuclear Information System (INIS)

    Audren, Benjamin; Lesgourgues, Julien; Benabed, Karim; Prunet, Simon

    2013-01-01

    Models for the latest stages of the cosmological evolution rely on a less solid theoretical and observational ground than the description of earlier stages like BBN and recombination. As suggested in a previous work by Vonlanthen et al., it is possible to tweak the analysis of CMB data in such way to avoid making assumptions on the late evolution, and obtain robust constraints on ''early cosmology parameters''. We extend this method in order to marginalise the results over CMB lensing contamination, and present updated results based on recent CMB data. Our constraints on the minimal early cosmology model are weaker than in a standard ΛCDM analysis, but do not conflict with this model. Besides, we obtain conservative bounds on the effective neutrino number and neutrino mass, showing no hints for extra relativistic degrees of freedom, and proving in a robust way that neutrinos experienced their non-relativistic transition after the time of photon decoupling. This analysis is also an occasion to describe the main features of the new parameter inference code MONTE PYTHON, that we release together with this paper. MONTE PYTHON is a user-friendly alternative to other public codes like COSMOMC, interfaced with the Boltzmann code CLASS

  16. Novel divergent nidovirus in a python with pneumonia.

    Science.gov (United States)

    Bodewes, Rogier; Lempp, Charlotte; Schürch, Anita C; Habierski, Andre; Hahn, Kerstin; Lamers, Mart; von Dörnberg, Katja; Wohlsein, Peter; Drexler, Jan Felix; Haagmans, Bart L; Smits, Saskia L; Baumgärtner, Wolfgang; Osterhaus, Albert D M E

    2014-11-01

    The order Nidovirales contains large, enveloped viruses with a non-segmented positive-stranded RNA genome. Nidoviruses have been detected in man and various animal species, but, to date, there have been no reports of nidovirus in reptiles. In the present study, we describe the detection, characterization, phylogenetic analyses and disease association of a novel divergent nidovirus in the lung of an Indian python (Python molurus) with necrotizing pneumonia. Characterization of the partial genome (>33 000 nt) of this virus revealed several genetic features that are distinct from other nidoviruses, including a very large polyprotein 1a, a putative ribosomal frameshift signal that was identical to the frameshift signal of astroviruses and retroviruses and an accessory ORF that showed some similarity with the haemagglutinin-neuraminidase of paramyxoviruses. Analysis of genome organization and phylogenetic analysis of polyprotein 1ab suggests that this virus belongs to the subfamily Torovirinae. Results of this study provide novel insights into the genetic diversity within the order Nidovirales. © 2014 The Authors.

  17. An introduction to statistics with Python with applications in the life sciences

    CERN Document Server

    Haslwanter, Thomas

    2016-01-01

    This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis. .

  18. Fatty acids identified in the Burmese python promote beneficial cardiac growth.

    Science.gov (United States)

    Riquelme, Cecilia A; Magida, Jason A; Harrison, Brooke C; Wall, Christopher E; Marr, Thomas G; Secor, Stephen M; Leinwand, Leslie A

    2011-10-28

    Burmese pythons display a marked increase in heart mass after a large meal. We investigated the molecular mechanisms of this physiological heart growth with the goal of applying this knowledge to the mammalian heart. We found that heart growth in pythons is characterized by myocyte hypertrophy in the absence of cell proliferation and by activation of physiological signal transduction pathways. Despite high levels of circulating lipids, the postprandial python heart does not accumulate triglycerides or fatty acids. Instead, there is robust activation of pathways of fatty acid transport and oxidation combined with increased expression and activity of superoxide dismutase, a cardioprotective enzyme. We also identified a combination of fatty acids in python plasma that promotes physiological heart growth when injected into either pythons or mice.

  19. Supersize me: Remains of three white-tailed deer (Odocoileus virginianus) in an invasive Burmese python (Python molurus bivittatus) in Florida

    Science.gov (United States)

    Boback, Scott M.; Snow, Ray W.; Hsu, Teresa; Peurach, Suzanne C.; Dove, Carla J.; Reed, Robert N.

    2016-01-01

    Snakes have become successful invaders in a wide variety of ecosystems worldwide. In southern Florida, USA, the Burmese python (Python molurus bivittatus) has become established across thousands of square kilometers including all of Everglades National Park (ENP). Both experimental and correlative data have supported a relationship between Burmese python predation and declines or extirpations of mid- to large-sized mammals in ENP. In June 2013 a large python (4.32 m snout-vent length, 48.3 kg) was captured and removed from the park. Subsequent necropsy revealed a massive amount of fecal matter (79 cm in length, 6.5 kg) within the snake’s large intestine. A comparative examination of bone, teeth, and hooves extracted from the fecal contents revealed that this snake consumed three white-tailed deer (Odocoileus virginianus). This is the first report of an invasive Burmese python containing the remains of multiple white-tailed deer in its gut. Because the largest snakes native to southern Florida are not capable of consuming even mid-sized mammals, pythons likely represent a novel predatory threat to white-tailed deer in these habitats. This work highlights the potential impact of this large-bodied invasive snake and supports the need for more work on invasive predator-native prey relationships.

  20. PyCOOL — A Cosmological Object-Oriented Lattice code written in Python

    International Nuclear Information System (INIS)

    Sainio, J.

    2012-01-01

    There are a number of different phenomena in the early universe that have to be studied numerically with lattice simulations. This paper presents a graphics processing unit (GPU) accelerated Python program called PyCOOL that solves the evolution of scalar fields in a lattice with very precise symplectic integrators. The program has been written with the intention to hit a sweet spot of speed, accuracy and user friendliness. This has been achieved by using the Python language with the PyCUDA interface to make a program that is easy to adapt to different scalar field models. In this paper we derive the symplectic dynamics that govern the evolution of the system and then present the implementation of the program in Python and PyCUDA. The functionality of the program is tested in a chaotic inflation preheating model, a single field oscillon case and in a supersymmetric curvaton model which leads to Q-ball production. We have also compared the performance of a consumer graphics card to a professional Tesla compute card in these simulations. We find that the program is not only accurate but also very fast. To further increase the usefulness of the program we have equipped it with numerous post-processing functions that provide useful information about the cosmological model. These include various spectra and statistics of the fields. The program can be additionally used to calculate the generated curvature perturbation. The program is publicly available under GNU General Public License at https://github.com/jtksai/PyCOOL. Some additional information can be found from http://www.physics.utu.fi/tiedostot/theory/particlecosmology/pycool/

  1. Digesting pythons quickly oxidize the proteins in their meals and save the lipids for later.

    Science.gov (United States)

    McCue, Marshall D; Guzman, R Marena; Passement, Celeste A

    2015-07-01

    Pythons digesting rodent meals exhibit up to 10-fold increases in their resting metabolic rate (RMR); this increase in RMR is termed specific dynamic action (SDA). Studies have shown that SDA is partially fueled by oxidizing dietary nutrients, yet it remains unclear whether the proteins and the lipids in their meals contribute equally to this energy demand. We raised two populations of mice on diets labeled with either [(13)C]leucine or [(13)C]palmitic acid to intrinsically enrich the proteins and lipids in their bodies, respectively. Ball pythons (Python regius) were fed whole mice (and pureed mice 3 weeks later), after which we measured their metabolic rates and the δ(13)C in the breath. The δ(13)C values in the whole bodies of the protein- and lipid-labeled mice were generally similar (i.e. 5.7±4.7‰ and 2.8±5.4‰, respectively) but the oxidative kinetics of these two macronutrient pools were quite different. We found that the snakes oxidized 5% of the protein and only 0.24% of the lipids in their meals within 14 days. Oxidation of the dietary proteins peaked 24 h after ingestion, at which point these proteins provided ∼90% of the metabolic requirement of the snakes, and by 14 days the oxidation of these proteins decreased to nearly zero. The oxidation of the dietary lipids peaked 1 day later, at which point these lipids supplied ∼25% of the energy demand. Fourteen days after ingestion, these lipids were still being oxidized and continued to account for ∼25% of the metabolic rate. Pureeing the mice reduced the cost of gastric digestion and decreased SDA by 24%. Pureeing also reduced the oxidation of dietary proteins by 43%, but it had no effect on the rates of dietary lipid oxidation. Collectively, these results demonstrate that pythons are able to effectively partition the two primary metabolic fuels in their meals. This approach of uniquely labeling the different components of the diet will allow researchers to examine new questions about

  2. pycalphad: CALPHAD-based Computational Thermodynamics in Python

    Directory of Open Access Journals (Sweden)

    Richard Otis

    2017-01-01

    Full Text Available The pycalphad software package is a free and open-source Python library for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria using the CALPHAD method. It provides routines for reading thermodynamic databases and solving the multi-component, multi-phase Gibbs energy minimization problem. The pycalphad software project advances the state of thermodynamic modeling by providing a flexible yet powerful interface for manipulating CALPHAD data and models. The key feature of the software is that the thermodynamic models of individual phases and their associated databases can be programmatically manipulated and overridden at run-time without modifying any internal solver or calculation code. Because the models are internally decoupled from the equilibrium solver and the models themselves are represented symbolically, pycalphad is an ideal tool for CALPHAD database development and model prototyping.

  3. Leveraging Python to improve ebook metadata selection, ingest, and management

    Directory of Open Access Journals (Sweden)

    Kelly Thompson

    2017-10-01

    Full Text Available Libraries face many challenges in managing descriptive metadata for ebooks, including quality control, completeness of coverage, and ongoing management. The recent emergence of library management systems that automatically provide descriptive metadata for e-resources activated in system knowledge bases means that ebook management models are moving toward both greater efficiency and more complex implementation and maintenance choices. Automated and data-driven processes for ebook management have always been desirable, but in the current environment, they become necessary. In addition to initial selection of a record source, automation can be applied to quality control processes and ongoing maintenance in order to keep manual, eyes-on work to a minimum while providing the best possible discovery and access. In this article, we describe how we are using Python scripts to address these challenges.

  4. PyORBIT: A Python Shell For ORBIT

    International Nuclear Information System (INIS)

    Jean-Francois Ostiguy; Jeffrey Holmes

    2003-01-01

    ORBIT is code developed at SNS to simulate beam dynamics in accumulation rings and synchrotrons. The code is structured as a collection of external C++ modules for SuperCode, a high level interpreter shell developed at LLNL in the early 1990s. SuperCode is no longer actively supported and there has for some time been interest in replacing it by a modern scripting language, while preserving the feel of the original ORBIT program. In this paper, we describe a new version of ORBIT where the role of SuperCode is assumed by Python, a free, well-documented and widely supported object-oriented scripting language. We also compare PyORBIT to ORBIT from the standpoint of features, performance and future expandability

  5. pyIAST: Ideal adsorbed solution theory (IAST) Python package

    Science.gov (United States)

    Simon, Cory M.; Smit, Berend; Haranczyk, Maciej

    2016-03-01

    Ideal adsorbed solution theory (IAST) is a widely-used thermodynamic framework to readily predict mixed-gas adsorption isotherms from a set of pure-component adsorption isotherms. We present an open-source, user-friendly Python package, pyIAST, to perform IAST calculations for an arbitrary number of components. pyIAST supports several common analytical models to characterize the pure-component isotherms from experimental or simulated data. Alternatively, pyIAST can use numerical quadrature to compute the spreading pressure for IAST calculations by interpolating the pure-component isotherm data. pyIAST can also perform reverse IAST calculations, where one seeks the required gas phase composition to yield a desired adsorbed phase composition.

  6. astroplan: An Open Source Observation Planning Package in Python

    Science.gov (United States)

    Morris, Brett M.; Tollerud, Erik; Sipőcz, Brigitta; Deil, Christoph; Douglas, Stephanie T.; Berlanga Medina, Jazmin; Vyhmeister, Karl; Smith, Toby R.; Littlefair, Stuart; Price-Whelan, Adrian M.; Gee, Wilfred T.; Jeschke, Eric

    2018-03-01

    We present astroplan—an open source, open development, Astropy affiliated package for ground-based observation planning and scheduling in Python. astroplan is designed to provide efficient access to common observational quantities such as celestial rise, set, and meridian transit times and simple transformations from sky coordinates to altitude-azimuth coordinates without requiring a detailed understanding of astropy’s implementation of coordinate systems. astroplan provides convenience functions to generate common observational plots such as airmass and parallactic angle as a function of time, along with basic sky (finder) charts. Users can determine whether or not a target is observable given a variety of observing constraints, such as airmass limits, time ranges, Moon illumination/separation ranges, and more. A selection of observation schedulers are included that divide observing time among a list of targets, given observing constraints on those targets. Contributions to the source code from the community are welcome.

  7. A atualidade de A vida de Brian, do Monty Python

    Directory of Open Access Journals (Sweden)

    Leonardo Antunes Cunha

    2014-01-01

    Full Text Available Este artigo desenvolve uma argumentação a respeito da atualidade do filme A vida de Brian, realizado pela trupe britânica Monty Python em 1979. Mais de 30 anos depois, a obra permanece contundente em sua sátira acerca do fanatismo, seja ele religioso ou político. Também se discutem as repercussões e a polêmica levantada pelo filme à época de seu lançamento e que, curiosamente, ainda se repetem quando de novas exibições. Finalmente, o artigo discute a estrutura narrativa do filme, apontando um equilíbrio entre duas matrizes da narrativa cômica no cinema: aquela mais episódica, calcada em esquetes ou piadas, e uma outra mais clássica, baseada em uma intriga bem amarrada.

  8. Python package for model STructure ANalysis (pySTAN)

    Science.gov (United States)

    Van Hoey, Stijn; van der Kwast, Johannes; Nopens, Ingmar; Seuntjens, Piet

    2013-04-01

    methods on a fair basis. We developed and present pySTAN (python framework for STructure Analysis), a python package containing a set of functions for model structure evaluation to provide the analysis of (hydrological) model structures. A selected set of algorithms for optimization, uncertainty and sensitivity analysis is currently available, together with a set of evaluation (objective) functions and input distributions to sample from. The methods are implemented model-independent and the python language provides the wrapper functions to apply administer external model codes. Different objective functions can be considered simultaneously with both statistical metrics and more hydrology specific metrics. By using so-called reStructuredText (sphinx documentation generator) and Python documentation strings (docstrings), the generation of manual pages is semi-automated and a specific environment is available to enhance both the readability and transparency of the code. It thereby enables a larger group of users to apply and compare these methods and to extend the functionalities.

  9. Intraspecific scaling of arterial blood pressure in the Burmese python.

    Science.gov (United States)

    Enok, Sanne; Slay, Christopher; Abe, Augusto S; Hicks, James W; Wang, Tobias

    2014-07-01

    Interspecific allometric analyses indicate that mean arterial blood pressure (MAP) increases with body mass of snakes and mammals. In snakes, MAP increases in proportion to the increased distance between the heart and the head, when the heart-head vertical distance is expressed as ρgh (where ρ is the density of blood, G: is acceleration due to gravity and h is the vertical distance above the heart), and the rise in MAP is associated with a larger heart to normalize wall stress in the ventricular wall. Based on measurements of MAP in Burmese pythons ranging from 0.9 to 3.7 m in length (0.20-27 kg), we demonstrate that although MAP increases with body mass, the rise in MAP is merely half of that predicted by heart-head distance. Scaling relationships within individual species, therefore, may not be accurately predicted by existing interspecific analyses. © 2014. Published by The Company of Biologists Ltd.

  10. A Python Script for Aligning the STIS Echelle Blaze Function

    Science.gov (United States)

    Baer, Malinda; Proffitt, Charles R.; Lockwood, Sean A.

    2018-01-01

    Accurate flux calibration for the STIS echelle modes is heavily dependent on the proper alignment of the blaze function for each spectral order. However, due to changes in the instrument alignment over time and between exposures, the blaze function can shift in wavelength. This may result in flux calibration inconsistencies of up to 10%. We present the stisblazefix Python module as a tool for STIS users to correct their echelle spectra. The stisblazefix module assumes that the error in the blaze alignment is a linear function of spectral order, and finds the set of shifts that minimizes the flux inconsistencies in the overlap between spectral orders. We discuss the uses and limitations of this tool, and show that its use can provide significant improvements to the default pipeline flux calibration for many observations.

  11. Analysis of counting data: Development of the SATLAS Python package

    Science.gov (United States)

    Gins, W.; de Groote, R. P.; Bissell, M. L.; Granados Buitrago, C.; Ferrer, R.; Lynch, K. M.; Neyens, G.; Sels, S.

    2018-01-01

    For the analysis of low-statistics counting experiments, a traditional nonlinear least squares minimization routine may not always provide correct parameter and uncertainty estimates due to the assumptions inherent in the algorithm(s). In response to this, a user-friendly Python package (SATLAS) was written to provide an easy interface between the data and a variety of minimization algorithms which are suited for analyzinglow, as well as high, statistics data. The advantage of this package is that it allows the user to define their own model function and then compare different minimization routines to determine the optimal parameter values and their respective (correlated) errors. Experimental validation of the different approaches in the package is done through analysis of hyperfine structure data of 203Fr gathered by the CRIS experiment at ISOLDE, CERN.

  12. A cross-validation package driving Netica with python

    Science.gov (United States)

    Fienen, Michael N.; Plant, Nathaniel G.

    2014-01-01

    Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill).

  13. Oral flora of Python regius kept as pets.

    Science.gov (United States)

    Dipineto, L; Russo, T P; Calabria, M; De Rosa, L; Capasso, M; Menna, L F; Borrelli, L; Fioretti, A

    2014-05-01

    This study was aimed at evaluating the oral bacterial flora of 60 Python regius kept as pets by culture and biochemical methods. All isolates were also submitted to antimicrobial susceptibility testing using the disc diffusion method. The oral cavity of snakes sampled harboured a wide range of Gram-negative bacteria mainly constituted by Pseudomonas spp., Morganella morganii, Acinetobacter calcoaceticus, Aeromonas hydrophila, but also by Salmonella spp. Staphylococcus spp. was the commonest Gram-positive isolates, and various anaerobic Clostridium species were also found. The most effective antimicrobial agents were enrofloxacin and ciprofloxacin, followed by doxycycline and gentamicin. The oral cavity of snakes sampled harboured a wide range of bacteria. Our results suggest that people who come in contact with snakes could be at risk of infection and should follow proper hygiene practices when handling these reptiles. © 2014 The Society for Applied Microbiology.

  14. Multiple papillomas in a diamond python, Morelia spilota spilota.

    Science.gov (United States)

    Gull, Jessica M; Lange, Christian E; Favrot, Claude; Dorrestein, Gerry M; Hatt, Jean-Michel

    2012-12-01

    A 4-yr-old male diamond python (Morelia spilota spilota) was evaluated for multiple black papillated exophytic skin proliferations and signs of pneumonia. The histopathologic structure of the skin biopsy specimens led to the diagnosis of a benign papilloma-like neoplasia. In this case, papillomavirus DNA could be amplified from a biopsy sample with a broad range polymerase chain reaction. Nested pan-herpes polymerase chain reaction was negative, and herpesvirus inclusion bodies were not found. Because of the histologically benign nature of the papilloma, the skin proliferations were left untreated. Ten mo after the first presentation, the skin lesions had regressed almost completely; 34 mo later, only scars from the biopsies were left.

  15. PyORBIT: A Python Shell For ORBIT

    Energy Technology Data Exchange (ETDEWEB)

    Jean-Francois Ostiguy; Jeffrey Holmes

    2003-07-01

    ORBIT is code developed at SNS to simulate beam dynamics in accumulation rings and synchrotrons. The code is structured as a collection of external C++ modules for SuperCode, a high level interpreter shell developed at LLNL in the early 1990s. SuperCode is no longer actively supported and there has for some time been interest in replacing it by a modern scripting language, while preserving the feel of the original ORBIT program. In this paper, we describe a new version of ORBIT where the role of SuperCode is assumed by Python, a free, well-documented and widely supported object-oriented scripting language. We also compare PyORBIT to ORBIT from the standpoint of features, performance and future expandability.

  16. Python for data analysis data wrangling with Pandas, NumPy, and IPython

    CERN Document Server

    McKinney, Wes

    2017-01-01

    Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib ...

  17. Installing python software packages : the good, the bad and the ugly.

    Energy Technology Data Exchange (ETDEWEB)

    Hart, William Eugene

    2010-11-01

    These slides describe different strategies for installing Python software. Although I am a big fan of Python software development, robust strategies for software installation remains a challenge. This talk describes several different installation scenarios. The Good: the user has administrative privileges - Installing on Windows with an installer executable, Installing with Linux application utility, Installing a Python package from the PyPI repository, and Installing a Python package from source. The Bad: the user does not have administrative privileges - Using a virtual environment to isolate package installations, and Using an installer executable on Windows with a virtual environment. The Ugly: the user needs to install an extension package from source - Installing a Python extension package from source, and PyCoinInstall - Managing builds for Python extension packages. The last item referring to PyCoinInstall describes a utility being developed for the COIN-OR software, which is used within the operations research community. COIN-OR includes a variety of Python and C++ software packages, and this script uses a simple plug-in system to support the management of package builds and installation.

  18. Simplifying the parallelization of scientific codes by a function-centric approach in Python

    International Nuclear Information System (INIS)

    Nilsen, Jon K; Cai Xing; Langtangen, Hans Petter; Hoeyland, Bjoern

    2010-01-01

    The purpose of this paper is to show how existing scientific software can be parallelized using a separate thin layer of Python code where all parallelization-specific tasks are implemented. We provide specific examples of such a Python code layer, which can act as templates for parallelizing a wide set of serial scientific codes. The use of Python for parallelization is motivated by the fact that the language is well suited for reusing existing serial codes programmed in other languages. The extreme flexibility of Python with regard to handling functions makes it very easy to wrap up decomposed computational tasks of a serial scientific application as Python functions. Many parallelization-specific components can be implemented as generic Python functions, which may take as input those wrapped functions that perform concrete computational tasks. The overall programming effort needed by this parallelization approach is limited, and the resulting parallel Python scripts have a compact and clean structure. The usefulness of the parallelization approach is exemplified by three different classes of application in natural and social sciences.

  19. SunPy 0.8 - Python for Solar Physics

    Science.gov (United States)

    Inglis, Andrew; Bobra, Monica; Christe, Steven; Hewett, Russell; Ireland, Jack; Mumford, Stuart; Martinez Oliveros, Juan Carlos; Perez-Suarez, David; Reardon, Kevin P.; Savage, Sabrina; Shih, Albert Y.; Ryan, Daniel; Sipocz, Brigitta; Freij, Nabil

    2017-08-01

    SunPy is a community-developed open-source software library for solar physics. It is written in Python, a free, cross-platform, general-purpose, high-level programming language which is being increasingly adopted throughout the scientific community. Python is one of the top ten most often used programming languages, as such it provides a wide array of software packages, such as numerical computation (NumPy, SciPy), machine learning (scikit-learn), signal processing (scikit-image, statsmodels) to visualization and plotting (matplotlib, mayavi). SunPy aims to provide the software for obtaining and analyzing solar and heliospheric data. This poster introduces a new major release of SunPy (0.8). This release includes two major new functionalities, as well as a number of bug fixes. It is based on 1120 contributions from 34 unique contributors. Fido is the new primary interface to download data. It provides a consistent and powerful search interface to all major data sources provides including VSO, JSOC, as well as individual data sources such as GOES XRS time series and and is fully pluggable to add new data sources, i.e. DKIST. In anticipation of Solar Orbiter and the Parker Solar Probe, SunPy now provides a powerful way of representing coordinates, allowing conversion between coordinate systems and viewpoints of different instruments, including preliminary reprojection capabilities. Other new features including new timeseries capabilities with better support for concatenation and metadata, updated documentation and example gallery. SunPy is distributed through pip and conda and all of its code is publicly available (sunpy.org).

  20. A Python Interface for the Dakota Iterative Systems Analysis Toolkit

    Science.gov (United States)

    Piper, M.; Hutton, E.; Syvitski, J. P.

    2016-12-01

    Uncertainty quantification is required to improve the accuracy, reliability, and accountability of Earth science models. Dakota is a software toolkit, developed at Sandia National Laboratories, that provides an interface between models and a library of analysis methods, including support for sensitivity analysis, uncertainty quantification, optimization, and calibration techniques. Dakota is a powerful tool, but its learning curve is steep: the user not only must understand the structure and syntax of the Dakota input file, but also must develop intermediate code, called an analysis driver, that allows Dakota to run a model. The CSDMS Dakota interface (CDI) is a Python package that wraps and extends Dakota's user interface. It simplifies the process of configuring and running a Dakota experiment. A user can program to the CDI, allowing a Dakota experiment to be scripted. The CDI creates Dakota input files and provides a generic analysis driver. Any model written in Python that exposes a Basic Model Interface (BMI), as well as any model componentized in the CSDMS modeling framework, automatically works with the CDI. The CDI has a plugin architecture, so models written in other languages, or those that don't expose a BMI, can be accessed by the CDI by programmatically extending a template; an example is provided in the CDI distribution. Currently, six Dakota analysis methods have been implemented for examples from the much larger Dakota library. To demonstrate the CDI, we performed an uncertainty quantification experiment with the HydroTrend hydrological water balance and transport model. In the experiment, we evaluated the response of long-term suspended sediment load at the river mouth (Qs) to uncertainty in two input parameters, annual mean temperature (T) and precipitation (P), over a series of 100-year runs, using the polynomial chaos method. Through Dakota, we calculated moments, local and global (Sobol') sensitivity indices, and probability density and

  1. Using Python to Construct a Scalable Parallel Nonlinear Wave Solver

    KAUST Repository

    Mandli, Kyle

    2011-01-01

    Computational scientists seek to provide efficient, easy-to-use tools and frameworks that enable application scientists within a specific discipline to build and/or apply numerical models with up-to-date computing technologies that can be executed on all available computing systems. Although many tools could be useful for groups beyond a specific application, it is often difficult and time consuming to combine existing software, or to adapt it for a more general purpose. Python enables a high-level approach where a general framework can be supplemented with tools written for different fields and in different languages. This is particularly important when a large number of tools are necessary, as is the case for high performance scientific codes. This motivated our development of PetClaw, a scalable distributed-memory solver for time-dependent nonlinear wave propagation, as a case-study for how Python can be used as a highlevel framework leveraging a multitude of codes, efficient both in the reuse of code and programmer productivity. We present scaling results for computations on up to four racks of Shaheen, an IBM BlueGene/P supercomputer at King Abdullah University of Science and Technology. One particularly important issue that PetClaw has faced is the overhead associated with dynamic loading leading to catastrophic scaling. We use the walla library to solve the issue which does so by supplanting high-cost filesystem calls with MPI operations at a low enough level that developers may avoid any changes to their codes.

  2. Python erythrocytes are resistant to α-hemolysin from Escherichia coli.

    Science.gov (United States)

    Larsen, Casper K; Skals, Marianne; Wang, Tobias; Cheema, Muhammad U; Leipziger, Jens; Praetorius, Helle A

    2011-12-01

    α-Hemolysin (HlyA) from Escherichia coli lyses mammalian erythrocytes by creating nonselective cation pores in the membrane. Pore insertion triggers ATP release and subsequent P2X receptor and pannexin channel activation. Blockage of either P2X receptors or pannexin channels reduces HlyA-induced hemolysis. We found that erythrocytes from Python regius and Python molurus are remarkably resistant to HlyA-induced hemolysis compared to human and Trachemys scripta erythrocytes. HlyA concentrations that induced maximal hemolysis of human erythrocytes did not affect python erythrocytes, but increasing the HlyA concentration 40-fold did induce hemolysis. Python erythrocytes were more resistant to osmotic stress than human erythrocytes, but osmotic stress tolerance per se did not confer HlyA resistance. Erythrocytes from T. scripta, which showed higher osmotic resistance than python erythrocytes, were as susceptible to HlyA as human erythrocytes. Therefore, we tested whether python erythrocytes lack the purinergic signalling known to amplify HlyA-induced hemolysis in human erythrocytes. P. regius erythrocytes increased intracellular Ca²⁺ concentration and reduced cell volume when exposed to 3 mM ATP, indicating the presence of a P2X₇-like receptor. In addition, scavenging extracellular ATP or blocking P2 receptors or pannexin channels reduced the HlyA-induced hemolysis. We tested whether the low HlyA sensitivity resulted from low affinity of HlyA to the python erythrocyte membrane. We found comparable incorporation of HlyA into human and python erythrocyte membranes. Taken together, the remarkable HlyA resistance of python erythrocytes was not explained by increased osmotic resistance, lack of purinergic hemolysis amplification, or differences in HlyA affinity.

  3. Korelasi Panjang Ekor Dan Panjang Tubuh Terhadap Jenis Kelamin Ular Sanca Batik (Python Reticulatus

    OpenAIRE

    Raharjo, Slamet; Dionisius M; Mulayni, Guntari Titik; Indarjulianto, Soedarmanto; Tjahajati, Ida

    2008-01-01

    The unique of Python reticulatus has been studied, however the correlation of the length and body weighthaven't studied yet. This objective ofthe research was to study the correlation of the tail and the body length ofPython reticulatus. Ten Python reticulatus, 2 weeks of old, were used in this research. The snakes wereplaced in individually cage at room temperature, consumed I to 2 mice and white mouse weekly and water adlibitum. The tail and body length of the snakes were measured at the be...

  4. GillesPy: A Python Package for Stochastic Model Building and Simulation.

    Science.gov (United States)

    Abel, John H; Drawert, Brian; Hellander, Andreas; Petzold, Linda R

    2016-09-01

    GillesPy is an open-source Python package for model construction and simulation of stochastic biochemical systems. GillesPy consists of a Python framework for model building and an interface to the StochKit2 suite of efficient simulation algorithms based on the Gillespie stochastic simulation algorithms (SSA). To enable intuitive model construction and seamless integration into the scientific Python stack, we present an easy to understand, action-oriented programming interface. Here, we describe the components of this package and provide a detailed example relevant to the computational biology community.

  5. Python 3 ja Windows-järjestelmän tiedot : Tilanseurantaohjelma asiakaskoneelle

    OpenAIRE

    Sirviö, Teemu

    2011-01-01

    Opinnäytetyön toimeksiantajana toimii yritys, jonka vastuulla on asiakkaittensa tietokoneiden ylläpitotyö. Työtä helpottamaan ja kustannuksia laskemaan toimeksiantaja päätti toteuttaa asiakkaiden tietokoneelle asennettavan valvontaohjelmiston. Toimeksiantaja halusi toteuttaa ohjelmiston opinnäytetyönä ja Python-ohjelmointikieltä käyttäen. Työssä käytettiin Python-kielen versiota 3, jonka toimintaa laajennettiin PyWin32- ja Python WMI -moduuleilla. Näistä ensimmäinen tuo tulkin käyttöön Wi...

  6. Rapid application development by KEKB accelerator operators using EPICS/Python

    International Nuclear Information System (INIS)

    Tanaka, M.; Satoh, Y.; Kitabayashi, T.

    2004-01-01

    In the KEKB accelerator facility, the control system is constructed based on the framework of EPICS. By using EPICS/Python API, which is originated from KEK, we can develop an EPICS channel access application based on simple Python technology with only a few knowledge of EPICS channel access protocols. The operator's new tuning ideas are quickly implemented to the control system. In this paper, we introduce the EPICS/Python API and report the effectiveness of rapid application development by the KEKB operators using the API. (author)

  7. Lowering the learning curve for declarative programming: a Python API for the IDP system

    OpenAIRE

    Vennekens, Joost

    2015-01-01

    Programmers may be hesitant to use declarative systems, because of the associated learning curve. In this paper, we present an API that integrates the IDP Knowledge Base system into the Python programming language. IDP is a state-of-the-art logical system, which uses SAT, SMT, Logic Programming and Answer Set Programming tech- nology. Python is currently one of the most widely used (teaching) lan- guages for programming. The first goal of our API is to allow a Python programmer to use the dec...

  8. Myiasis by Megaselia scalaris (Diptera: Phoridae) in a python affected by pulmonitis.

    Science.gov (United States)

    Vanin, S; Mazzariol, S; Menandro, M L; Lafisca, A; Turchetto, M

    2013-01-01

    Myiases are caused by the presence of maggots in vertebrate tissues and organs. Myiases have been studied widely in humans, farm animals, and pets, whereas reports of myiasis in reptiles are scarce. We describe a case of myiasis caused by the Megaselia scalaris (Loew) in an Indian python (Python molurus bivittatus, Kuhl) (Ophida: Boidae). The python, 15 yr old, born and reared in a terrarium in the mainland of Venice (Italy), was affected by diffuse, purulent pneumonia caused by Burkholderia cepacia. The severe infestation of maggots found in the lungs during an autopsy indicated at a myiasis.

  9. The Python ARM Radar Toolkit (Py-ART, a Library for Working with Weather Radar Data in the Python Programming Language

    Directory of Open Access Journals (Sweden)

    Jonathan J Helmus

    2016-07-01

    Full Text Available The Python ARM Radar Toolkit is a package for reading, visualizing, correcting and analysing data from weather radars. Development began to meet the needs of the Atmospheric Radiation Measurement Climate Research Facility and has since expanded to provide a general-purpose framework for working with data from weather radars in the Python programming language. The toolkit is built on top of libraries in the Scientific Python ecosystem including NumPy, SciPy, and matplotlib, and makes use of Cython for interfacing with existing radar libraries written in C and to speed up computationally demanding algorithms. The source code for the toolkit is available on GitHub and is distributed under a BSD license.

  10. PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

    Directory of Open Access Journals (Sweden)

    Forrest Sheng Bao

    2011-01-01

    Full Text Available Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.

  11. The Implementation of a Python Class for Structuring Network Data Collected in a Test Bed

    National Research Council Canada - National Science Library

    Nguyen, Binh Q

    2008-01-01

    This report documents an internally developed Python class that takes in a set of data files and organizes them into effective data structures that are suitable for the subsequent extraction, processing, and analysis...

  12. Biopython: freely available Python tools for computational molecular biology and bioinformatics

    DEFF Research Database (Denmark)

    Cock, Peter J A; Antao, Tiago; Chang, Jeffrey T

    2009-01-01

    SUMMARY: The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments...

  13. Pārskatu ģenerēšanas bibliotēka Python valodai

    OpenAIRE

    Paltovs, Deniss

    2012-01-01

    Kvalifikācijas darba pamatā ir pārskatu ģenerēšanas bibliotēka Python valodai - PythonReports, kura ļauj Python izstrādātajiem no datiem un šablona izveidot izdruku uz ekrāna vai printera. Gala produkts ir vizuālais redaktors, kurš ļauj ērti un uzskatāmi veidot un rediģēt PythonReports šablonus, izmantojot mūsdienu lietotāju saskarnes tehnoloģijas operētājsistēmās ar grafisku lietotāja saskarni. Kvalifikācijas darbs balstās uz iepriekšējo pieredzi, iegūto izmantojot līdzīgus rīkus citās sist...

  14. Developers@CERN Forum | Python at CERN | 30 – 31 May

    CERN Multimedia

    2016-01-01

    The Developers@CERN Forum is an event by developers for developers aimed at promoting knowledge- and experience-sharing (see here). The second forum will take place in the IT auditorium in the afternoons of 30 and 31 May.   With the topic “Python at CERN”, it will consist of a series of talks regarding the Python language, frameworks and tools used at CERN. Are you a Python guru or would you like to learn? Come and share your Python experiences with other developers! Submissions for presentations and workshops are open until 9 May at http://cern.ch/dev-forum. If you would like to stay informed about this or future events, please subscribe to the announcement e-group (just a few e-mails per year) here. 

  15. Homing of invasive Burmese pythons in South Florida: evidence for map and compass senses in snakes

    Science.gov (United States)

    Pittman, Shannon E.; Hart, Kristen M.; Cherkiss, Michael S.; Snow, Ray W.; Fujisaki, Ikuko; Smith, Brian J.; Mazzotti, Frank J.; Dorcas, Michael E.

    2014-01-01

    Navigational ability is a critical component of an animal's spatial ecology and may influence the invasive potential of species. Burmese pythons (Python molurus bivittatus) are apex predators invasive to South Florida. We tracked the movements of 12 adult Burmese pythons in Everglades National Park, six of which were translocated 21–36 km from their capture locations. Translocated snakes oriented movement homeward relative to the capture location, and five of six snakes returned to within 5 km of the original capture location. Translocated snakes moved straighter and faster than control snakes and displayed movement path structure indicative of oriented movement. This study provides evidence that Burmese pythons have navigational map and compass senses and has implications for predictions of spatial spread and impacts as well as our understanding of reptile cognitive abilities. PMID:24647727

  16. PyTrilinos: Recent Advances in the Python Interface to Trilinos

    Directory of Open Access Journals (Sweden)

    William F. Spotz

    2012-01-01

    Full Text Available PyTrilinos is a set of Python interfaces to compiled Trilinos packages. This collection supports serial and parallel dense linear algebra, serial and parallel sparse linear algebra, direct and iterative linear solution techniques, algebraic and multilevel preconditioners, nonlinear solvers and continuation algorithms, eigensolvers and partitioning algorithms. Also included are a variety of related utility functions and classes, including distributed I/O, coloring algorithms and matrix generation. PyTrilinos vector objects are compatible with the popular NumPy Python package. As a Python front end to compiled libraries, PyTrilinos takes advantage of the flexibility and ease of use of Python, and the efficiency of the underlying C++, C and Fortran numerical kernels. This paper covers recent, previously unpublished advances in the PyTrilinos package.

  17. On the Performance of the Python Programming Language for Serial and Parallel Scientific Computations

    Directory of Open Access Journals (Sweden)

    Xing Cai

    2005-01-01

    Full Text Available This article addresses the performance of scientific applications that use the Python programming language. First, we investigate several techniques for improving the computational efficiency of serial Python codes. Then, we discuss the basic programming techniques in Python for parallelizing serial scientific applications. It is shown that an efficient implementation of the array-related operations is essential for achieving good parallel performance, as for the serial case. Once the array-related operations are efficiently implemented, probably using a mixed-language implementation, good serial and parallel performance become achievable. This is confirmed by a set of numerical experiments. Python is also shown to be well suited for writing high-level parallel programs.

  18. Python Scripts for Automation of Current-Voltage Testing of Semiconductor Devices (FY17)

    Science.gov (United States)

    2017-01-01

    ARL-TR-7923 ● JAN 2017 US Army Research Laboratory Python Scripts for Automation of Current- Voltage Testing of Semiconductor ...Laboratory Python Scripts for Automation of Current- Voltage Testing of Semiconductor Devices (FY17) by Bryan H Zhao Oak Ridge Institute for Science...Testing of Semiconductor Devices (FY17) 5a. CONTRACT NUMBER 1120-1120-99 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Bryan H Zhao

  19. PlasmaPy: beginning a community developed Python package for plasma physics

    OpenAIRE

    Murphy, Nicholas A; Huang, Yi-Min; PlasmaPy Community

    2016-01-01

    In recent years, researchers in several disciplines have collaborated on community-developed open source Python packages such as Astropy, SunPy, and SpacePy. These packages provide core functionality, common frameworks for data analysis and visualization, and educational tools. We propose that our community begins the development of PlasmaPy: a new open source core Python package for plasma physics. PlasmaPy could include commonly used functions in plasma physics, easy-to-use plasma simulatio...

  20. Obtaining and processing Daymet data using Python and ArcGIS

    Science.gov (United States)

    Bohms, Stefanie

    2013-01-01

    This set of scripts was developed to automate the process of downloading and mosaicking daily Daymet data to a user defined extent using ArcGIS and Python programming language. The three steps are downloading the needed Daymet tiles for the study area extent, converting the netcdf file to a tif raster format, and mosaicking those rasters to one file. The set of scripts is intended for all levels of experience with Python programming language and requires no scripting by the user.

  1. Environmental DNA (eDNA sampling improves occurrence and detection estimates of invasive burmese pythons.

    Directory of Open Access Journals (Sweden)

    Margaret E Hunter

    Full Text Available Environmental DNA (eDNA methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR for the Burmese python (Python molurus bivittatus, Northern African python (P. sebae, boa constrictor (Boa constrictor, and the green (Eunectes murinus and yellow anaconda (E. notaeus. Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive

  2. Data processing with Pymicra, the Python tool for Micrometeorological Analyses

    Science.gov (United States)

    Chor, T. L.; Dias, N. L.

    2017-12-01

    With the ever-increasing capability of instrumentation of collecting high-frequency turbulence data, micrometeorological experiments are now generating significant amounts of data. Clearly, data processing -- and not data collection anymore -- has become the limiting factor for those very large data sets. The ability of extracting useful scientific information from those experiments, therefore, hinges on tools that (i) are able to process those data effectively and accurately, (ii) are flexible enough to be adapted to the specific requirements of each investigation, and (iii) are robust enough to make data analysis easily reproducible over different sets of large data sets. We have developed a framework for micrometeorological data analysis called Pymicra which does deliver such capabilities while maintaining proximity of the investigator with the data. It is fully written in an open-source, very high level language, Python, which has been gaining widespread acceptance as a scientific tool. It follows the philosophy of "not reinventing the wheel" and, as a result, relies on existing well-established open-source Python packages such as Numpy and Pandas. Thus, minimum effort is needed to program statistics, array processing, Fourier analysis, etc. Among the things that Pymicra does are reading and organizing data from virtually any format, applying common quality control procedures, extracting fluctuations in a number of ways, correcting for sensor drift, automatic calculation of fluid properties (such as air and dry air density), handling of units, calculation of cross-spectra, calculation of turbulent fluxes and scales, and all other features already provided by Pandas (interpolation, statistical tests, handling of missing data, etc.). Pymicra is freely available on Github and the fact that it makes heavy use of high-level programming makes adding and modifying code considerably easy for any scientific programmer, making it straightforward for other scientists to

  3. ObsPy - A Python Toolbox for Seismology - and Applications

    Science.gov (United States)

    Krischer, L.; Megies, T.; Barsch, R.; MacCarthy, J.; Lecocq, T.; Koymans, M. R.; Carothers, L.; Eulenfeld, T.; Reyes, C. G.; Falco, N.; Sales de Andrade, E.

    2017-12-01

    Recent years witnessed the evolution of Python's ecosystem into one of the most powerful and productive scientific environments across disciplines. ObsPy (https://www.obspy.org) is a fully community driven, open-source project dedicated to provide a bridge for seismology into that ecosystem. It is a Python toolbox offering: Read and write support for essentially every commonly used data format in seismology with a unified interface and automatic format detection. This includes waveform data (MiniSEED, SAC, SEG-Y, Reftek, …) as well as station (SEED, StationXML, SC3ML, …) and event meta information (QuakeML, ZMAP, …). Integrated access to the largest data centers, web services, and real-time data streams (FDSNWS, ArcLink, SeedLink, ...). A powerful signal processing toolbox tuned to the specific needs of seismologists. Utility functionality like travel time calculations with the TauP method, geodetic functions, and data visualizations. ObsPy has been in constant development for more than eight years and is developed and used by scientists around the world with successful applications in all branches of seismology. Additionally it nowadays serves as the foundation for a large number of more specialized packages. Newest features include: Full interoperability of SEED and StationXML/Inventory objects Access to the Nominal Response Library (NRL) for easy and quick creation of station metadata from scratch Support for the IRIS Federated Catalog Service Improved performance of the EarthWorm client Several improvements to MiniSEED read/write module Improved plotting capabilities for PPSD (spectrograms, PSD of discrete frequencies over time, ..) Support for.. Reading ArcLink Inventory XML Reading Reftek data format Writing SeisComp3 ML (SC3ML) Writing StationTXT format This presentation will give a short overview of the capabilities of ObsPy and point out several representative or new use cases and show-case some projects that are based on ObsPy, e.g.: seismo

  4. Using Python as a first programming environment for computational physics in developing countries

    Science.gov (United States)

    Akpojotor, Godfrey; Ehwerhemuepha, Louis; Echenim, Myron; Akpojotor, Famous

    2011-03-01

    Python unique features such its interpretative, multiplatform and object oriented nature as well as being a free and open source software creates the possibility that any user connected to the internet can download the entire package into any platform, install it and immediately begin to use it. Thus Python is gaining reputation as a preferred environment for introducing students and new beginners to programming. Therefore in Africa, the Python African Tour project has been launched and we are coordinating its use in computational science. We examine here the challenges and prospects of using Python for computational physics (CP) education in developing countries (DC). Then we present our project on using Python to simulate and aid the learning of laboratory experiments illustrated here by modeling of the simple pendulum and also to visualize phenomena in physics illustrated here by demonstrating the wave motion of a particle in a varying potential. This project which is to train both the teachers and our students on CP using Python can easily be adopted in other DC.

  5. Severe mammal declines coincide with proliferation of invasive Burmese pythons in Everglades National Park

    Science.gov (United States)

    Dorcas, Michael E.; Wilson, John D.; Reed, Robert N.; Snow, Ray W.; Rochford, Michael R.; Miller, Melissa A.; Meshaka, Walter E.; Andreadis, Paul T.; Mazzotti, Frank J.; Romagosa, Christina M.; Hart, Kristen M.

    2012-01-01

    Invasive species represent a significant threat to global biodiversity and a substantial economic burden. Burmese pythons, giant constricting snakes native to Asia, now are found throughout much of southern Florida, including all of Everglades National Park (ENP). Pythons have increased dramatically in both abundance and geographic range since 2000 and consume a wide variety of mammals and birds. Here we report severe apparent declines in mammal populations that coincide temporally and spatially with the proliferation of pythons in ENP. Before 2000, mammals were encountered frequently during nocturnal road surveys within ENP. In contrast, road surveys totaling 56,971 km from 2003–2011 documented a 99.3% decrease in the frequency of raccoon observations, decreases of 98.9% and 87.5% for opossum and bobcat observations, respectively, and failed to detect rabbits. Road surveys also revealed that these species are more common in areas where pythons have been discovered only recently and are most abundant outside the python's current introduced range. These findings suggest that predation by pythons has resulted in dramatic declines in mammals within ENP and that introduced apex predators, such as giant constrictors, can exert significant top-down pressure on prey populations. Severe declines in easily observed and/or common mammals, such as raccoons and bobcats, bode poorly for species of conservation concern, which often are more difficult to sample and occur at lower densities.

  6. Molecular identification of python species: development and validation of a novel assay for forensic investigations.

    Science.gov (United States)

    Ciavaglia, Sherryn A; Tobe, Shanan S; Donnellan, Stephen C; Henry, Julianne M; Linacre, Adrian M T

    2015-05-01

    Python snake species are often encountered in illegal activities and the question of species identity can be pertinent to such criminal investigations. Morphological identification of species of pythons can be confounded by many issues and molecular examination by DNA analysis can provide an alternative and objective means of identification. Our paper reports on the development and validation of a PCR primer pair that amplifies a segment of the mitochondrial cytochrome b gene that has been suggested previously as a good candidate locus for differentiating python species. We used this DNA region to perform species identification of pythons, even when the template DNA was of poor quality, as might be the case with forensic evidentiary items. Validation tests are presented to demonstrate the characteristics of the assay. Tests involved the cross-species amplification of this marker in non-target species, minimum amount of DNA template required, effects of degradation on product amplification and a blind trial to simulate a casework scenario that provided 100% correct identity. Our results demonstrate that this assay performs reliably and robustly on pythons and can be applied directly to forensic investigations where the presence of a species of python is in question. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  7. Hyperopt: a Python library for model selection and hyperparameter optimization

    Science.gov (United States)

    Bergstra, James; Komer, Brent; Eliasmith, Chris; Yamins, Dan; Cox, David D.

    2015-01-01

    Sequential model-based optimization (also known as Bayesian optimization) is one of the most efficient methods (per function evaluation) of function minimization. This efficiency makes it appropriate for optimizing the hyperparameters of machine learning algorithms that are slow to train. The Hyperopt library provides algorithms and parallelization infrastructure for performing hyperparameter optimization (model selection) in Python. This paper presents an introductory tutorial on the usage of the Hyperopt library, including the description of search spaces, minimization (in serial and parallel), and the analysis of the results collected in the course of minimization. This paper also gives an overview of Hyperopt-Sklearn, a software project that provides automatic algorithm configuration of the Scikit-learn machine learning library. Following Auto-Weka, we take the view that the choice of classifier and even the choice of preprocessing module can be taken together to represent a single large hyperparameter optimization problem. We use Hyperopt to define a search space that encompasses many standard components (e.g. SVM, RF, KNN, PCA, TFIDF) and common patterns of composing them together. We demonstrate, using search algorithms in Hyperopt and standard benchmarking data sets (MNIST, 20-newsgroups, convex shapes), that searching this space is practical and effective. In particular, we improve on best-known scores for the model space for both MNIST and convex shapes. The paper closes with some discussion of ongoing and future work.

  8. SPOTting Model Parameters Using a Ready-Made Python Package.

    Directory of Open Access Journals (Sweden)

    Tobias Houska

    Full Text Available The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool, an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI. We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.

  9. photPARTY: Python automated square-aperture photometry

    Science.gov (United States)

    Symons, Teresa A.; Anthony-Twarog, Barbara J.

    2017-01-01

    As CCD’s have drastically increased the amount of information recorded per frame, so too have they increased the time and effort needed to sift through the data. For observations of a single star, information from millions of pixels needs to be distilled into one number: the magnitude. Various computer systems have been used to streamline this process over the years. The CCDPhot photometer, in use at the Kitt Peak 0.9-m telescope in the 1990’s, allowed for user settings and provided real time magnitudes during observation of single stars. It is this level of speed and convenience that inspired the development of the Python-based software analysis system photPARTY, which can quickly and efficiently produce magnitudes for a set of single-star or un-crowded field CCD frames. Seeking to remove the need for manual interaction after initial settings for a group of images, photPARTY automatically locates stars, subtracts the background, and performs square-aperture photometry. Rather than being a package of available functions, it is essentially a self-contained, one-click analysis system, with the capability to process several hundred frames in just a couple of minutes. Results of comparisons against present systems such as IRAF will be presented. The support of the National Science Foundation through grant AST-1211621 is gratefully acknowledged.

  10. Quantiprot - a Python package for quantitative analysis of protein sequences.

    Science.gov (United States)

    Konopka, Bogumił M; Marciniak, Marta; Dyrka, Witold

    2017-07-17

    The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf's law coefficient. We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.

  11. AESOP: A Python Library for Investigating Electrostatics in Protein Interactions.

    Science.gov (United States)

    Harrison, Reed E S; Mohan, Rohith R; Gorham, Ronald D; Kieslich, Chris A; Morikis, Dimitrios

    2017-05-09

    Electric fields often play a role in guiding the association of protein complexes. Such interactions can be further engineered to accelerate complex association, resulting in protein systems with increased productivity. This is especially true for enzymes where reaction rates are typically diffusion limited. To facilitate quantitative comparisons of electrostatics in protein families and to describe electrostatic contributions of individual amino acids, we previously developed a computational framework called AESOP. We now implement this computational tool in Python with increased usability and the capability of performing calculations in parallel. AESOP utilizes PDB2PQR and Adaptive Poisson-Boltzmann Solver to generate grid-based electrostatic potential files for protein structures provided by the end user. There are methods within AESOP for quantitatively comparing sets of grid-based electrostatic potentials in terms of similarity or generating ensembles of electrostatic potential files for a library of mutants to quantify the effects of perturbations in protein structure and protein-protein association. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  12. GOGrapher: A Python library for GO graph representation and analysis.

    Science.gov (United States)

    Muller, Brian; Richards, Adam J; Jin, Bo; Lu, Xinghua

    2009-07-07

    The Gene Ontology is the most commonly used controlled vocabulary for annotating proteins. The concepts in the ontology are organized as a directed acyclic graph, in which a node corresponds to a biological concept and a directed edge denotes the parent-child semantic relationship between a pair of terms. A large number of protein annotations further create links between proteins and their functional annotations, reflecting the contemporary knowledge about proteins and their functional relationships. This leads to a complex graph consisting of interleaved biological concepts and their associated proteins. What is needed is a simple, open source library that provides tools to not only create and view the Gene Ontology graph, but to analyze and manipulate it as well. Here we describe the development and use of GOGrapher, a Python library that can be used for the creation, analysis, manipulation, and visualization of Gene Ontology related graphs. An object-oriented approach was adopted to organize the hierarchy of the graphs types and associated classes. An Application Programming Interface is provided through which different types of graphs can be pragmatically created, manipulated, and visualized. GOGrapher has been successfully utilized in multiple research projects, e.g., a graph-based multi-label text classifier for protein annotation. The GOGrapher project provides a reusable programming library designed for the manipulation and analysis of Gene Ontology graphs. The library is freely available for the scientific community to use and improve.

  13. ObsPy: A Python Toolbox for Seismology

    Science.gov (United States)

    Krischer, Lion; Megies, Tobias; Sales de Andrade, Elliott; Barsch, Robert; MacCarthy, Jonathan

    2017-04-01

    In recent years the Python ecosystem evolved into one of the most powerful and productive scientific environments across disciplines. ObsPy (https://www.obspy.org) is a fully community-driven, open-source project dedicated to providing a bridge for seismology into that ecosystem. It does so by offering Read and write support for essentially every commonly used data format in seismology with a unified interface and automatic format detection. This includes waveform data (MiniSEED, SAC, SEG-Y, Reftek, …) as well as station (SEED, StationXML, …) and event meta information (QuakeML, ZMAP, …). Integrated access to the largest data centers, web services, and real-time data streams (FDSNWS, ArcLink, SeedLink, ...). A powerful signal processing toolbox tuned to the specific needs of seismologists. Utility functionality like travel time calculations with the TauP method, geodetic functions, and data visualizations. ObsPy has been in constant development for more than seven years and is developed and used by scientists around the world with successful applications in all branches of seismology. Additionally it nowadays serves as the foundation for a large number of more specialized packages. This presentation will give a short overview of the capabilities of ObsPy and point out several representative or new use cases. Additionally we will discuss the road ahead as well as the long-term sustainability of open-source scientific software.

  14. PyPSA: Python for Power System Analysis

    Directory of Open Access Journals (Sweden)

    Thomas Brown

    2018-01-01

    Full Text Available Python for Power System Analysis (PyPSA is a free software toolbox for simulating and optimising modern electrical power systems over multiple periods. PyPSA includes models for conventional generators with unit commitment, variable renewable generation, storage units, coupling to other energy sectors, and mixed alternating and direct current networks. It is designed to be easily extensible and to scale well with large networks and long time series. In this paper the basic functionality of PyPSA is described, including the formulation of the full power flow equations and the multi-period optimisation of operation and investment with linear power flow equations. PyPSA is positioned in the existing free software landscape as a bridge between traditional power flow analysis tools for steady-state analysis and full multi-period energy system models. The functionality is demonstrated on two open datasets of the transmission system in Germany (based on SciGRID and Europe (based on GridKit.   Funding statement: This research was conducted as part of the CoNDyNet project, which is supported by the German Federal Ministry of Education and Research under grant no. 03SF0472C. The responsibility for the contents lies solely with the authors

  15. batman: BAsic Transit Model cAlculatioN in Python

    Science.gov (United States)

    Kreidberg, Laura

    2015-11-01

    I introduce batman, a Python package for modeling exoplanet transit light curves. The batman package supports calculation of light curves for any radially symmetric stellar limb darkening law, using a new integration algorithm for models that cannot be quickly calculated analytically. The code uses C extension modules to speed up model calculation and is parallelized with OpenMP. For a typical light curve with 100 data points in transit, batman can calculate one million quadratic limb-darkened models in 30 seconds with a single 1.7 GHz Intel Core i5 processor. The same calculation takes seven minutes using the four-parameter nonlinear limb darkening model (computed to 1 ppm accuracy). Maximum truncation error for integrated models is an input parameter that can be set as low as 0.001 ppm, ensuring that the community is prepared for the precise transit light curves we anticipate measuring with upcoming facilities. The batman package is open source and publicly available at https://github.com/lkreidberg/batman .

  16. Screening_mgmt: a Python module for managing screening data.

    Science.gov (United States)

    Helfenstein, Andreas; Tammela, Päivi

    2015-02-01

    High-throughput screening is an established technique in drug discovery and, as such, has also found its way into academia. High-throughput screening generates a considerable amount of data, which is why specific software is used for its analysis and management. The commercially available software packages are often beyond the financial limits of small-scale academic laboratories and, furthermore, lack the flexibility to fulfill certain user-specific requirements. We have developed a Python module, screening_mgmt, which is a lightweight tool for flexible data retrieval, analysis, and storage for different screening assays in one central database. The module reads custom-made analysis scripts and plotting instructions, and it offers a graphical user interface to import, modify, and display the data in a uniform manner. During the test phase, we used this module for the management of 10,000 data points of various origins. It has provided a practical, user-friendly tool for sharing and exchanging information between researchers. © 2014 Society for Laboratory Automation and Screening.

  17. AstroML: Python-powered Machine Learning for Astronomy

    Science.gov (United States)

    Vander Plas, Jake; Connolly, A. J.; Ivezic, Z.

    2014-01-01

    As astronomical data sets grow in size and complexity, automated machine learning and data mining methods are becoming an increasingly fundamental component of research in the field. The astroML project (http://astroML.org) provides a common repository for practical examples of the data mining and machine learning tools used and developed by astronomical researchers, written in Python. The astroML module contains a host of general-purpose data analysis and machine learning routines, loaders for openly-available astronomical datasets, and fast implementations of specific computational methods often used in astronomy and astrophysics. The associated website features hundreds of examples of these routines being used for analysis of real astronomical datasets, while the associated textbook provides a curriculum resource for graduate-level courses focusing on practical statistics, machine learning, and data mining approaches within Astronomical research. This poster will highlight several of the more powerful and unique examples of analysis performed with astroML, all of which can be reproduced in their entirety on any computer with the proper packages installed.

  18. GOGrapher: A Python library for GO graph representation and analysis

    Directory of Open Access Journals (Sweden)

    Lu Xinghua

    2009-07-01

    Full Text Available Abstract Background The Gene Ontology is the most commonly used controlled vocabulary for annotating proteins. The concepts in the ontology are organized as a directed acyclic graph, in which a node corresponds to a biological concept and a directed edge denotes the parent-child semantic relationship between a pair of terms. A large number of protein annotations further create links between proteins and their functional annotations, reflecting the contemporary knowledge about proteins and their functional relationships. This leads to a complex graph consisting of interleaved biological concepts and their associated proteins. What is needed is a simple, open source library that provides tools to not only create and view the Gene Ontology graph, but to analyze and manipulate it as well. Here we describe the development and use of GOGrapher, a Python library that can be used for the creation, analysis, manipulation, and visualization of Gene Ontology related graphs. Findings An object-oriented approach was adopted to organize the hierarchy of the graphs types and associated classes. An Application Programming Interface is provided through which different types of graphs can be pragmatically created, manipulated, and visualized. GOGrapher has been successfully utilized in multiple research projects, e.g., a graph-based multi-label text classifier for protein annotation. Conclusion The GOGrapher project provides a reusable programming library designed for the manipulation and analysis of Gene Ontology graphs. The library is freely available for the scientific community to use and improve.

  19. Python framework for kinetic modeling of electronically excited reaction pathways

    Science.gov (United States)

    Verboncoeur, John; Parsey, Guy; Guclu, Yaman; Christlieb, Andrew

    2012-10-01

    The use of plasma energy to enhance and control the chemical reactions during combustion, a technology referred to as ``plasma assisted combustion'' (PAC), can result in a variety of beneficial effects: e.g. stable lean operation, pollution reduction, and wider range of p-T operating conditions. While experimental evidence abounds, theoretical understanding of PAC is at best incomplete, and numerical tools still lack in reliable predictive capabilities. In the context of a joint experimental-numerical effort at Michigan State University, we present here an open-source modular Python framework dedicated to the dynamic optimization of non-equilibrium PAC systems. Multiple sources of experimental reaction data, e.g. reaction rates, cross-sections and oscillator strengths, are used in order to quantify the effect of data uncertainty and limiting assumptions. A collisional-radiative model (CRM) is implemented to organize reactions by importance and as a potential means of measuring a non-Maxwellian electron energy distribution function (EEDF), when coupled to optical emission spectroscopy data. Finally, we explore scaling laws in PAC parameter space using a kinetic global model (KGM) accelerated with CRM optimized reaction sequences and sparse stiff integrators.

  20. Gastric adenocarcinoma in a diamond python (Morelia spilota spilota).

    Science.gov (United States)

    Baron, H R; Allavena, R; Melville, L M; Doneley, R J T

    2014-10-01

    A 5-year-old captive male diamond python (Morelia spilota spilota) was presented with a 1-month history of regurgitation and anorexia and discrete coelomic distention. Physical examination revealed a firm, immobile mass at approximately two-thirds of the snout-vent length from the front of the head. Ultrasound-guided fine needle aspirate biopsy of the mass in the region of the stomach showed necrosis with bacterial infiltration and possibly neoplastic changes. A gastroscopy was conducted, but showed grossly normal gastric mucosa, confirmed by biopsy. On exploratory coeliotomy, it was confirmed the mass involved most of the stomach wall and occluded the gastric lumen. The mass was completely excised and based on histopathology, a diagnosis of gastric adenocarcinoma was made. The snake was found dead 12 h postoperatively, but no specific cause of death was found on postmortem examination. Most cases of adenocarcinoma in snakes go undiagnosed. This case report illustrates that the architecture of gastric masses may lead to false-negative gastric biopsy results in snakes with neoplasia. © 2014 Australian Veterinary Association.

  1. A python framework for environmental model uncertainty analysis

    Science.gov (United States)

    White, Jeremy; Fienen, Michael N.; Doherty, John E.

    2016-01-01

    We have developed pyEMU, a python framework for Environmental Modeling Uncertainty analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and scalable to highly-parameterized inverse problems. The framework implements several types of linear (first-order, second-moment (FOSM)) and non-linear uncertainty analyses. The FOSM-based analyses can also be completed prior to parameter estimation to help inform important modeling decisions, such as parameterization and objective function formulation. Complete workflows for several types of FOSM-based and non-linear analyses are documented in example notebooks implemented using Jupyter that are available in the online pyEMU repository. Example workflows include basic parameter and forecast analyses, data worth analyses, and error-variance analyses, as well as usage of parameter ensemble generation and management capabilities. These workflows document the necessary steps and provides insights into the results, with the goal of educating users not only in how to apply pyEMU, but also in the underlying theory of applied uncertainty quantification.

  2. Programming PHREEQC calculations with C++ and Python a comparative study

    Science.gov (United States)

    Charlton, Scott R.; Parkhurst, David L.; Muller, Mike

    2011-01-01

    The new IPhreeqc module provides an application programming interface (API) to facilitate coupling of other codes with the U.S. Geological Survey geochemical model PHREEQC. Traditionally, loose coupling of PHREEQC with other applications required methods to create PHREEQC input files, start external PHREEQC processes, and process PHREEQC output files. IPhreeqc eliminates most of this effort by providing direct access to PHREEQC capabilities through a component object model (COM), a library, or a dynamically linked library (DLL). Input and calculations can be specified through internally programmed strings, and all data exchange between an application and the module can occur in computer memory. This study compares simulations programmed in C++ and Python that are tightly coupled with IPhreeqc modules to the traditional simulations that are loosely coupled to PHREEQC. The study compares performance, quantifies effort, and evaluates lines of code and the complexity of the design. The comparisons show that IPhreeqc offers a more powerful and simpler approach for incorporating PHREEQC calculations into transport models and other applications that need to perform PHREEQC calculations. The IPhreeqc module facilitates the design of coupled applications and significantly reduces run times. Even a moderate knowledge of one of the supported programming languages allows more efficient use of PHREEQC than the traditional loosely coupled approach.

  3. Short telomeres in hatchling snakes: erythrocyte telomere dynamics and longevity in tropical pythons.

    Directory of Open Access Journals (Sweden)

    Beata Ujvari

    Full Text Available BACKGROUND: Telomere length (TL has been found to be associated with life span in birds and humans. However, other studies have demonstrated that TL does not affect survival among old humans. Furthermore, replicative senescence has been shown to be induced by changes in the protected status of the telomeres rather than the loss of TL. In the present study we explore whether age- and sex-specific telomere dynamics affect life span in a long-lived snake, the water python (Liasis fuscus. METHODOLOGY/PRINCIPAL FINDINGS: Erythrocyte TL was measured using the Telo TAGGG TL Assay Kit (Roche. In contrast to other vertebrates, TL of hatchling pythons was significantly shorter than that of older snakes. However, during their first year of life hatchling TL increased substantially. While TL of older snakes decreased with age, we did not observe any correlation between TL and age in cross-sectional sampling. In older snakes, female TL was longer than that of males. When using recapture as a proxy for survival, our results do not support that longer telomeres resulted in an increased water python survival/longevity. CONCLUSIONS/SIGNIFICANCE: In fish high telomerase activity has been observed in somatic cells exhibiting high proliferation rates. Hatchling pythons show similar high somatic cell proliferation rates. Thus, the increase in TL of this group may have been caused by increased telomerase activity. In older humans female TL is longer than that of males. This has been suggested to be caused by high estrogen levels that stimulate increased telomerase activity. Thus, high estrogen levels may also have caused the longer telomeres in female pythons. The lack of correlation between TL and age among old snakes and the fact that longer telomeres did not appear to affect python survival do not support that erythrocyte telomere dynamics has a major impact on water python longevity.

  4. Prioritizing blood flow: cardiovascular performance in response to the competing demands of locomotion and digestion for the Burmese python, Python molurus.

    Science.gov (United States)

    Secor, Stephen M; White, Scott E

    2010-01-01

    Individually, the metabolic demands of digestion or movement can be fully supported by elevations in cardiovascular performance, but when occurring simultaneously, vascular perfusion may have to be prioritized to either the gut or skeletal muscles. Burmese pythons (Python molurus) experience similar increases in metabolic rate during the digestion of a meal as they do while crawling, hence each would have an equal demand for vascular supply when these two actions are combined. To determine, for the Burmese python, whether blood flow is prioritized when snakes are digesting and moving, we examined changes in cardiac performance and blood flow in response to digestion, movement, and the combination of digestion and movement. We used perivascular blood flow probes to measure blood flow through the left carotid artery, dorsal aorta, superior mesenteric artery and hepatic portal vein, and to calculate cardiac output, heart rate and stroke volume. Fasted pythons while crawling experienced a 2.7- and 3.3-fold increase, respectively, in heart rate and cardiac output, and a 66% decrease in superior mesenteric flow. During the digestion of a rodent meal equaling in mass to 24.7% of the snake's body mass, heart rate and cardiac output increased by 3.3- and 4.4-fold, respectively. Digestion also resulted in respective 11.6- and 14.1-fold increases in superior mesenteric and hepatic portal flow. When crawling while digesting, cardiac output and dorsal aorta flow increased by only 21% and 9%, respectively, a modest increase compared with that when they start to crawl on an empty stomach. Crawling did triggered a significant reduction in blood flow to the digesting gut, decreasing superior mesenteric and hepatic portal flow by 81% and 47%, respectively. When faced with the dual demands of digestion and crawling, Burmese pythons prioritize blood flow, apparently diverting visceral supply to the axial muscles.

  5. Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit

    Directory of Open Access Journals (Sweden)

    Morley Chris

    2008-03-01

    Full Text Available Abstract Background Scripting languages such as Python are ideally suited to common programming tasks in cheminformatics such as data analysis and parsing information from files. However, for reasons of efficiency, cheminformatics toolkits such as the OpenBabel toolkit are often implemented in compiled languages such as C++. We describe Pybel, a Python module that provides access to the OpenBabel toolkit. Results Pybel wraps the direct toolkit bindings to simplify common tasks such as reading and writing molecular files and calculating fingerprints. Extensive use is made of Python iterators to simplify loops such as that over all the molecules in a file. A Pybel Molecule can be easily interconverted to an OpenBabel OBMol to access those methods or attributes not wrapped by Pybel. Conclusion Pybel allows cheminformaticians to rapidly develop Python scripts that manipulate chemical information. It is open source, available cross-platform, and offers the power of the OpenBabel toolkit to Python programmers.

  6. SunPy - Python for Solar Physics, Version 0.4

    Science.gov (United States)

    Christe, Steven; Mumford, Stuart; Perez-Suarez, David; Ireland, Jack; Shih, Albert Y.; Inglis, Andrew; Liedtke, Simon; Hewett, Russel

    2014-06-01

    We presents version 0.4 of SunPy, a community-developed Python package for solar physics. Python, a free, cross-platform, general-purpose, high-level programming language, has seen widespread adoption among the scientific community, resulting in the availability of a large number of software packages, from numerical computation NumPy, SciPy and machine learning (scikit-learn) to visualisation and plotting (matplotlib).SunPy is a data-analysis environment specialising in providing the software necessary to analyse solar and heliospheric datasets in Python. SunPy is open-source software (BSD licence) and has an open and transparent development workflow that anyone can contribute to. SunPy provides access to solar data through integration with the Virtual Solar Observatory (VSO), the Heliophysics Event Knowledgebase (HEK), and the HELiophysics Integrated Observatory (HELIO) webservices. It currently supports image data from major solar missions (e.g., SDO, SOHO, STEREO, and IRIS), time-series data from missions such as GOES, SDO/EVE, and PROBA2/LYRA, and radio spectra from e-Callisto and STEREO/SWAVES. We describe SunPy's functionality, provide examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing tools already available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy.

  7. The influence of midazolam on heart rate arises from cardiac autonomic tones alterations in Burmese pythons, Python molurus.

    Science.gov (United States)

    Lopes, Ivã Guidini; Armelin, Vinicius Araújo; Braga, Victor Hugo da Silva; Florindo, Luiz Henrique

    2017-12-01

    The GABA A receptor agonist midazolam is a compound widely used as a tranquilizer and sedative in mammals and reptiles. It is already known that this benzodiazepine produces small to intermediate heart rate (HR) alterations in mammals, however, its influence on reptiles' HR remains unexplored. Thus, the present study sought to verify the effects of midazolam on HR and cardiac modulation in the snake Python molurus. To do so, the snakes' HR, cardiac autonomic tones, and HR variability were evaluated during four different experimental stages. The first stage consisted on the data acquisition of animals under untreated conditions, in which were then administered atropine (2.5mgkg -1 ; intraperitoneal), followed later by propranolol (3.5mgkg -1 ; intraperitoneal) (cardiac double autonomic blockade). The second stage focused on the data acquisition of animals under midazolam effect (1.0mgkg -1 ; intramuscular), which passed through the same autonomic blockade protocol of the first stage. The third and fourth stages consisted of the same protocol of stages one and two, respectively, with the exception that atropine and propranolol injections were reversed. By comparing the HR of animals that received midazolam (second and fourth stages) with those that did not (first and third stages), it could be observed that this benzodiazepine reduced the snakes' HR by ~60%. The calculated autonomic tones showed that such cardiac depression was elicited by an ~80% decrease in cardiac adrenergic tone and an ~620% increase in cardiac cholinergic tone - a finding that was further supported by the results of HR variability analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. GPAW - massively parallel electronic structure calculations with Python-based software

    DEFF Research Database (Denmark)

    Enkovaara, Jussi; Romero, Nichols A.; Shende, Sameer

    2011-01-01

    popular choice. While dynamic, interpreted languages, such as Python, can increase the effciency of programmer, they cannot compete directly with the raw performance of compiled languages. However, by using an interpreted language together with a compiled language, it is possible to have most...... of the productivity enhancing features together with a good numerical performance. We have used this approach in implementing an electronic structure simulation software GPAW using the combination of Python and C programming languages. While the chosen approach works well in standard workstations and Unix...... environments, massively parallel supercomputing systems can present some challenges in porting, debugging and profiling the software. In this paper we describe some details of the implementation and discuss the advantages and challenges of the combined Python/C approach. We show that despite the challenges...

  9. Histamine induces postprandian tachycardia through a direct effect on cardiac H2-receptors in pythons

    DEFF Research Database (Denmark)

    Jensen, Nini Skovgaard; Møller, Kate; Gesser, Hans

    2009-01-01

    The intrinsic heart rate of most vertebrates studied, including humans, is elevated during digestion, suggesting that a non-adrenergic-non-cholinergic factor contributes to the postprandial tachycardia. The regulating factor, however, remains elusive and difficult to identify. Pythons can ingest...... very large meals and digestion is associated with a marked rise in metabolism that is sustained for several days. The metabolic rise causes more than a doubling of heart rate and a four-fold rise in cardiac output. This makes the python an interesting model to investigate the postprandial tachycardia....... We measured blood pressure and heart rate in fasting Python regius, and at 24 and 48h after ingestion of a meal amounting to 25% of body weight. Digestion caused heart rate to increase from 25 to 56 min-1 while blood pressure was unchanged. The postprandial rise in heart rate was partially due...

  10. Pteros 2.0: Evolution of the fast parallel molecular analysis library for C++ and python.

    Science.gov (United States)

    Yesylevskyy, Semen O

    2015-07-15

    Pteros is the high-performance open-source library for molecular modeling and analysis of molecular dynamics trajectories. Starting from version 2.0 Pteros is available for C++ and Python programming languages with very similar interfaces. This makes it suitable for writing complex reusable programs in C++ and simple interactive scripts in Python alike. New version improves the facilities for asynchronous trajectory reading and parallel execution of analysis tasks by introducing analysis plugins which could be written in either C++ or Python in completely uniform way. The high level of abstraction provided by analysis plugins greatly simplifies prototyping and implementation of complex analysis algorithms. Pteros is available for free under Artistic License from http://sourceforge.net/projects/pteros/. © 2015 Wiley Periodicals, Inc.

  11. The atomic simulation environment-a Python library for working with atoms.

    Science.gov (United States)

    Hjorth Larsen, Ask; Jørgen Mortensen, Jens; Blomqvist, Jakob; Castelli, Ivano E; Christensen, Rune; Dułak, Marcin; Friis, Jesper; Groves, Michael N; Hammer, Bjørk; Hargus, Cory; Hermes, Eric D; Jennings, Paul C; Bjerre Jensen, Peter; Kermode, James; Kitchin, John R; Leonhard Kolsbjerg, Esben; Kubal, Joseph; Kaasbjerg, Kristen; Lysgaard, Steen; Bergmann Maronsson, Jón; Maxson, Tristan; Olsen, Thomas; Pastewka, Lars; Peterson, Andrew; Rostgaard, Carsten; Schiøtz, Jakob; Schütt, Ole; Strange, Mikkel; Thygesen, Kristian S; Vegge, Tejs; Vilhelmsen, Lasse; Walter, Michael; Zeng, Zhenhua; Jacobsen, Karsten W

    2017-07-12

    The atomic simulation environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simulations. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make it possible to perform very complex simulation tasks. For example, a sequence of calculations may be performed with the use of a simple 'for-loop' construction. Calculations of energy, forces, stresses and other quantities are performed through interfaces to many external electronic structure codes or force fields using a uniform interface. On top of this calculator interface, ASE provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations.

  12. A Python-based interface to examine motions in time series of solar images

    Science.gov (United States)

    Campos-Rozo, J. I.; Vargas Domínguez, S.

    2017-10-01

    Python is considered to be a mature programming language, besides of being widely accepted as an engaging option for scientific analysis in multiple areas, as will be presented in this work for the particular case of solar physics research. SunPy is an open-source library based on Python that has been recently developed to furnish software tools to solar data analysis and visualization. In this work we present a graphical user interface (GUI) based on Python and Qt to effectively compute proper motions for the analysis of time series of solar data. This user-friendly computing interface, that is intended to be incorporated to the Sunpy library, uses a local correlation tracking technique and some extra tools that allows the selection of different parameters to calculate, vizualize and analyze vector velocity fields of solar data, i.e. time series of solar filtergrams and magnetograms.

  13. A Python package for parsing, validating, mapping and formatting sequence variants using HGVS nomenclature.

    Science.gov (United States)

    Hart, Reece K; Rico, Rudolph; Hare, Emily; Garcia, John; Westbrook, Jody; Fusaro, Vincent A

    2015-01-15

    Biological sequence variants are commonly represented in scientific literature, clinical reports and databases of variation using the mutation nomenclature guidelines endorsed by the Human Genome Variation Society (HGVS). Despite the widespread use of the standard, no freely available and comprehensive programming libraries are available. Here we report an open-source and easy-to-use Python library that facilitates the parsing, manipulation, formatting and validation of variants according to the HGVS specification. The current implementation focuses on the subset of the HGVS recommendations that precisely describe sequence-level variation relevant to the application of high-throughput sequencing to clinical diagnostics. The package is released under the Apache 2.0 open-source license. Source code, documentation and issue tracking are available at http://bitbucket.org/hgvs/hgvs/. Python packages are available at PyPI (https://pypi.python.org/pypi/hgvs). Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

  14. WekaPyScript: Classification, Regression, and Filter Schemes for WEKA Implemented in Python

    Directory of Open Access Journals (Sweden)

    Christopher Beckham

    2016-08-01

    Full Text Available WekaPyScript is a package for the machine learning software WEKA that allows learning algorithms and preprocessing methods for classification and regression to be written in Python, as opposed to WEKA’s implementation language, Java. This opens up WEKA to its machine learning and scientific computing ecosystem. Furthermore, due to Python’s minimalist syntax, learning algorithms and preprocessing methods can be prototyped easily and utilised from within WEKA. WekaPyScript works by running a local Python server using the host’s installation of Python; as a result, any libraries installed in the host installation can be leveraged when writing a script for WekaPyScript. Three example scripts (two learning algorithms and one preprocessing method are presented.

  15. Charming the Snake: Student Experiences with Python Programming as a Data Analysis Tool

    Science.gov (United States)

    Booker, Melissa; Ivers, C. B.; Piper, M.; Powers, L.; Ali, B.

    2014-01-01

    During the past year, twelve high school students and one undergraduate student participated in the NASA/IPAC Teacher Archive Research Program (NITARP) alongside three high school educators and one informal educator, gaining experience in using Python as a tool for analyzing the vast amount of photometry data available from the Herschel and Spitzer telescopes in the NGC 281 region. Use of Python appeared to produce two main positive gains: (1) a gain in student ability to successfully write and execute Python programs for the bulk analysis of data, and (2) a change in their perceptions of the utility of computer programming and of the students’ abilities to use programming to solve problems. We outline the trials, tribulations, successes, and failures of the teachers and students through this learning exercise and provide some recommendations for incorporating programming in scientific learning.

  16. Approaching the largest ‘API’: extracting information from the Internet with Python

    Directory of Open Access Journals (Sweden)

    Jonathan E. Germann

    2018-02-01

    Full Text Available This article explores the need for libraries to algorithmically access and manipulate the world’s largest API: the Internet. The billions of pages on the ‘Internet API’ (HTTP, HTML, CSS, XPath, DOM, etc. are easily accessible and manipulable. Libraries can assist in creating meaning through the datafication of information on the world wide web. Because most information is created for human consumption, some programming is required for automated extraction. Python is an easy-to-learn programming language with extensive packages and community support for web page automation. Four packages (Urllib, Selenium, BeautifulSoup, Scrapy in Python can automate almost any web page for all sized projects. An example warrant data project is explained to illustrate how well Python packages can manipulate web pages to create meaning through assembling custom datasets.

  17. interPopula: a Python API to access the HapMap Project dataset.

    Science.gov (United States)

    Antao, Tiago

    2010-12-21

    The HapMap project is a publicly available catalogue of common genetic variants that occur in humans, currently including several million SNPs across 1115 individuals spanning 11 different populations. This important database does not provide any programmatic access to the dataset, furthermore no standard relational database interface is provided. interPopula is a Python API to access the HapMap dataset. interPopula provides integration facilities with both the Python ecology of software (e.g. Biopython and matplotlib) and other relevant human population datasets (e.g. Ensembl gene annotation and UCSC Known Genes). A set of guidelines and code examples to address possible inconsistencies across heterogeneous data sources is also provided. interPopula is a straightforward and flexible Python API that facilitates the construction of scripts and applications that require access to the HapMap dataset.

  18. Analyzing rasters, vectors and time series using new Python interfaces in GRASS GIS 7

    Science.gov (United States)

    Petras, Vaclav; Petrasova, Anna; Chemin, Yann; Zambelli, Pietro; Landa, Martin; Gebbert, Sören; Neteler, Markus; Löwe, Peter

    2015-04-01

    GRASS GIS 7 is a free and open source GIS software developed and used by many scientists (Neteler et al., 2012). While some users of GRASS GIS prefer its graphical user interface, significant part of the scientific community takes advantage of various scripting and programing interfaces offered by GRASS GIS to develop new models and algorithms. Here we will present different interfaces added to GRASS GIS 7 and available in Python, a popular programming language and environment in geosciences. These Python interfaces are designed to satisfy the needs of scientists and programmers under various circumstances. PyGRASS (Zambelli et al., 2013) is a new object-oriented interface to GRASS GIS modules and libraries. The GRASS GIS libraries are implemented in C to ensure maximum performance and the PyGRASS interface provides an intuitive, pythonic access to their functionality. GRASS GIS Python scripting library is another way of accessing GRASS GIS modules. It combines the simplicity of Bash and the efficiency of the Python syntax. When full access to all low-level and advanced functions and structures from GRASS GIS library is required, Python programmers can use an interface based on the Python ctypes package. Ctypes interface provides complete, direct access to all functionality as it would be available to C programmers. GRASS GIS provides specialized Python library for managing and analyzing spatio-temporal data (Gebbert and Pebesma, 2014). The temporal library introduces space time datasets representing time series of raster, 3D raster or vector maps and allows users to combine various spatio-temporal operations including queries, aggregation, sampling or the analysis of spatio-temporal topology. We will also discuss the advantages of implementing scientific algorithm as a GRASS GIS module and we will show how to write such module in Python. To facilitate the development of the module, GRASS GIS provides a Python library for testing (Petras and Gebbert, 2014) which

  19. SPOTting model parameters using a ready-made Python package

    Science.gov (United States)

    Houska, Tobias; Kraft, Philipp; Breuer, Lutz

    2015-04-01

    The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for

  20. HOPE: A Python just-in-time compiler for astrophysical computations

    Science.gov (United States)

    Akeret, J.; Gamper, L.; Amara, A.; Refregier, A.

    2015-04-01

    The Python programming language is becoming increasingly popular for scientific applications due to its simplicity, versatility, and the broad range of its libraries. A drawback of this dynamic language, however, is its low runtime performance which limits its applicability for large simulations and for the analysis of large data sets, as is common in astrophysics and cosmology. While various frameworks have been developed to address this limitation, most focus on covering the complete language set, and either force the user to alter the code or are not able to reach the full speed of an optimised native compiled language. In order to combine the ease of Python and the speed of C++, we developed HOPE, a specialised Python just-in-time (JIT) compiler designed for numerical astrophysical applications. HOPE focuses on a subset of the language and is able to translate Python code into C++ while performing numerical optimisation on mathematical expressions at runtime. To enable the JIT compilation, the user only needs to add a decorator to the function definition. We assess the performance of HOPE by performing a series of benchmarks and compare its execution speed with that of plain Python, C++ and the other existing frameworks. We find that HOPE improves the performance compared to plain Python by a factor of 2 to 120, achieves speeds comparable to that of C++, and often exceeds the speed of the existing solutions. We discuss the differences between HOPE and the other frameworks, as well as future extensions of its capabilities. The fully documented HOPE package is available at http://hope.phys.ethz.ch and is published under the GPLv3 license on PyPI and GitHub.

  1. The role of python eggshell permeability dynamics in a respiration-hydration trade-off.

    Science.gov (United States)

    Stahlschmidt, Zachary R; Heulin, Benoit; DeNardo, Dale F

    2010-01-01

    Parental care is taxonomically widespread because it improves developmental conditions and thus fitness of offspring. Although relatively simplistic compared with parental behaviors of other taxa, python egg-brooding behavior exemplifies parental care because it mediates a trade-off between embryonic respiration and hydration. However, because egg brooding increases gas-exchange resistance between embryonic and nest environments and because female pythons do not adjust their brooding behavior in response to the increasing metabolic requirements of developing offspring, python egg brooding imposes hypoxic costs on embryos during the late stages of incubation. We conducted a series of experiments to determine whether eggshells coadapted with brooding behavior to minimize the negative effects of developmental hypoxia. We tested the hypotheses that python eggshells (1) increase permeability over time to accommodate increasing embryonic respiration and (2) exhibit permeability plasticity in response to chronic hypoxia. Over incubation, we serially measured the atomic and structural components of Children's python (Antaresia childreni) eggshells as well as in vivo and in vitro gas exchange across eggshells. In support of our first hypothesis, A. childreni eggshells exhibited a reduced fibrous layer, became more permeable, and facilitated greater gas exchange as incubation progressed. Our second hypothesis was not supported, as incubation O(2) concentration did not affect the shells' permeabilities to O(2) and H(2)O vapor. Our results suggest that python eggshell permeability changes during incubation but that the alterations over time are fixed and independent of environmental conditions. These findings are of broad evolutionary interest because they demonstrate that, even in relatively simple parental-care models, successful parent-offspring relationships depend on adjustments made by both the parent (i.e., egg-brooding behavioral shifts) and the offspring (i

  2. Enabling grand-canonical Monte Carlo : extending the flexibility of GROMACS through the GromPy python interface module

    NARCIS (Netherlands)

    Pool, René; Heringa, Jaap; Hoefling, Martin; Schulz, Roland; Smith, Jeremy C; Feenstra, K Anton

    2012-01-01

    We report on a python interface to the GROMACS molecular simulation package, GromPy (available at https://github.com/GromPy). This application programming interface (API) uses the ctypes python module that allows function calls to shared libraries, for example, written in C. To the best of our

  3. Real world instrumentation with Python automated data acquisition and control systems

    CERN Document Server

    Hughes, John

    2010-01-01

    Learn how to develop your own applications to monitor or control instrumentation hardware. Whether you need to acquire data from a device or automate its functions, this practical book shows you how to use Python's rapid development capabilities to build interfaces that include everything from software to wiring. You get step-by-step instructions, clear examples, and hands-on tips for interfacing a PC to a variety of devices. Use the book's hardware survey to identify the interface type for your particular device, and then follow detailed examples to develop an interface with Python and C. O

  4. pyGeno: A Python package for precision medicine and proteogenomics.

    Science.gov (United States)

    Daouda, Tariq; Perreault, Claude; Lemieux, Sébastien

    2016-01-01

    pyGeno is a Python package mainly intended for precision medicine applications that revolve around genomics and proteomics. It integrates reference sequences and annotations from Ensembl, genomic polymorphisms from the dbSNP database and data from next-gen sequencing into an easy to use, memory-efficient and fast framework, therefore allowing the user to easily explore subject-specific genomes and proteomes. Compared to a standalone program, pyGeno gives the user access to the complete expressivity of Python, a general programming language. Its range of application therefore encompasses both short scripts and large scale genome-wide studies.

  5. AutoWIG: automatic generation of python bindings for C++ libraries

    Directory of Open Access Journals (Sweden)

    Pierre Fernique

    2018-04-01

    Full Text Available Most of Python and R scientific packages incorporate compiled scientific libraries to speed up the code and reuse legacy libraries. While several semi-automatic solutions exist to wrap these compiled libraries, the process of wrapping a large library is cumbersome and time consuming. In this paper, we introduce AutoWIG, a Python package that wraps automatically compiled libraries into high-level languages using LLVM/Clang technologies and the Mako templating engine. Our approach is automatic, extensible, and applies to complex C++ libraries, composed of thousands of classes or incorporating modern meta-programming constructs.

  6. Python forensics a workbench for inventing and sharing digital forensic technology

    CERN Document Server

    Hosmer, Chet

    2014-01-01

    Python Forensics provides many never-before-published proven forensic modules, libraries, and solutions that can be used right out of the box. In addition, detailed instruction and documentation provided with the code samples will allow even novice Python programmers to add their own unique twists or use the models presented to build new solutions. Rapid development of new cybercrime investigation tools is an essential ingredient in virtually every case and environment. Whether you are performing post-mortem investigation, executing live triage, extracting evidence from mobile devices or cl

  7. Výuka algoritmizace a programování se zaměřením na programovací jazyk Python

    OpenAIRE

    Kotek, Lukáš

    2013-01-01

    The thesis researches the ability of use of Python programming language in the field of high school education and uses qualitative and quantitative methods of research and finds Python suitable. The thesis also brings theoretical analysis of the Python language, including practical exams in the form of sample programs. It researchs even other programming languages used in education and their suitability for this purpose and compares them with Python programming language. It also finds two mos...

  8. Prospects and limitations of citizen science in invasive species management: A case study with Burmese pythons in Everglades National Park

    Science.gov (United States)

    Falk, Bryan; Snow, Raymond W.; Reed, Robert

    2016-01-01

    Citizen-science programs have the potential to contribute to the management of invasive species, including Python molurus bivittatus (Burmese Python) in Florida. We characterized citizen-science–generated Burmese Python information from Everglades National Park (ENP) to explore how citizen science may be useful in this effort. As an initial step, we compiled and summarized records of Burmese Python observations and removals collected by both professional and citizen scientists in ENP during 2000–2014 and found many patterns of possible significance, including changes in annual observations and in demographic composition after a cold event. These patterns are difficult to confidently interpret because the records lack search-effort information, however, and differences among years may result from differences in search effort. We began collecting search-effort information in 2014 by leveraging an ongoing citizen-science program in ENP. Program participation was generally low, with most authorized participants in 2014 not searching for the snakes at all. We discuss the possible explanations for low participation, especially how the low likelihood of observing pythons weakens incentives to search. The monthly rate of Burmese Python observations for 2014 averaged ~1 observation for every 8 h of searching, but during several months, the rate was 1 python per >40 h of searching. These low observation-rates are a natural outcome of the snakes’ low detectability—few Burmese Pythons are likely to be observed even if many are present. The general inaccessibility of the southern Florida landscape also severely limits the effectiveness of using visual searches to find and remove pythons for the purposes of population control. Instead, and despite the difficulties in incentivizing voluntary participation, the value of citizen-science efforts in the management of the Burmese Python population is in collecting search-effort information.

  9. CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

    Science.gov (United States)

    Rose, B. E. J.

    2015-12-01

    Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

  10. Java vs. Python Coverage of Introductory Programming Concepts: A Textbook Analysis

    Science.gov (United States)

    McMaster, Kirby; Sambasivam, Samuel; Rague, Brian; Wolthuis, Stuart

    2017-01-01

    In this research, we compare two languages, Java and Python, by performing a content analysis of words in textbooks that describe important programming concepts. Our goal is to determine which language has better textbook support for teaching introductory programming courses. We used the TextSTAT program to count how often our list of concept…

  11. 77 FR 3329 - Injurious Wildlife Species; Listing Three Python Species and One Anaconda Species as Injurious...

    Science.gov (United States)

    2012-01-23

    ... are closely related, large- bodied pythons of similar appearance found in sub-Saharan Africa (Reed and..., DeSchauensee's anaconda, green anaconda, and Beni anaconda), five were shown to pose a high risk to the health... opportunistic in expanding their geographic range. Furthermore, since they are a novel (new to the system...

  12. HyDe: a Python Package for Genome-Scale Hybridization Detection.

    Science.gov (United States)

    Blischak, Paul D; Chifman, Julia; Wolfe, Andrea D; Kubatko, Laura S

    2018-03-19

    The analysis of hybridization and gene flow among closely related taxa is a common goal for researchers studying speciation and phylogeography. Many methods for hybridization detection use simple site pattern frequencies from observed genomic data and compare them to null models that predict an absence of gene flow. The theory underlying the detection of hybridization using these site pattern probabilities exploits the relationship between the coalescent process for gene trees within population trees and the process of mutation along the branches of the gene trees. For certain models, site patterns are predicted to occur in equal frequency (i.e., their difference is 0), producing a set of functions called phylogenetic invariants. In this paper we introduce HyDe, a software package for detecting hybridization using phylogenetic invariants arising under the coalescent model with hybridization. HyDe is written in Python, and can be used interactively or through the command line using pre-packaged scripts. We demonstrate the use of HyDe on simulated data, as well as on two empirical data sets from the literature. We focus in particular on identifying individual hybrids within population samples and on distinguishing between hybrid speciation and gene flow. HyDe is freely available as an open source Python package under the GNU GPL v3 on both GitHub (https://github.com/pblischak/HyDe) and the Python Package Index (PyPI: https://pypi.python.org/pypi/phyde).

  13. Magni: A Python Package for Compressive Sampling and Reconstruction of Atomic Force Microscopy Images

    DEFF Research Database (Denmark)

    Oxvig, Christian Schou; Pedersen, Patrick Steffen; Arildsen, Thomas

    2014-01-01

    Magni is an open source Python package that embraces compressed sensing and Atomic Force Microscopy (AFM) imaging techniques. It provides AFM-specific functionality for undersampling and reconstructing images from AFM equipment and thereby accelerating the acquisition of AFM images. Magni also...

  14. Integrating three lake models into a Phytoplankton Prediction System for Lake Taihu (Taihu PPS) with Python

    NARCIS (Netherlands)

    Huang, J.; Gao, J.; Hörmann, G.; Mooij, W.M.

    2012-01-01

    In the past decade, much work has been done on integrating different lake models using general frameworks to overcome model incompatibilities. However, a framework may not be flexible enough to support applications in different fields. To overcome this problem, we used Python to integrate three lake

  15. Qudi: a modular python suite for experiment control and data processing

    DEFF Research Database (Denmark)

    Binder, Jan M.; Stark, Alexander; Tomek, Nikolas

    2017-01-01

    Qudi is a general, modular, multi-operating system suite written in Python 3 for controlling laboratory experiments. It provides a structured environment by separating functionality into hardware abstraction, experiment logic and user interface layers. The core feature set comprises a graphical...

  16. The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism

    DEFF Research Database (Denmark)

    Birkel, Garrett W.; Ghosh, Amit; Kumar, Vinay S.

    2017-01-01

    analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics, proteomics and metabolomics) are urgently needed.Results: The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes...

  17. A Low-Effort Analytics Platform for Visualizing Evolving Flask-Based Python Web Services

    NARCIS (Netherlands)

    Vogel, Patrick; Klooster, Thijs; Andrikopoulos, Vasilios OR Vasileios; Lungu, Micea-Filip

    2017-01-01

    Tens of thousands of web applications are written in Flask, a Python-based web framework. Despite a rich ecosystem of extensions, there is none that supports the developer in gaining insight into the evolving performance of their service. In this paper, we introduce Flask Dashboard, a library that

  18. Implementing a Multi-Agent System in Python with an Auction-Based Agreement Approach

    DEFF Research Database (Denmark)

    Ettienne, Mikko Berggren; Vester, Steen; Villadsen, Jørgen

    2012-01-01

    We describe the solution used by the Python-DTU team in the Multi-Agent Programming Contest 2011, where the scenario was called Agents on Mars. We present our auction-based agreement algorithm and discuss our chosen strategy and our choice of technology used for implementing the system. Finally, we...

  19. Python and Roles of Variables in Introductory Programming: Experiences from Three Educational Institutions

    Science.gov (United States)

    Nikula, Uolevi; Sajaniemi, Jorma; Tedre, Matti; Wray, Stuart

    2007-01-01

    Students often find that learning to program is hard. Introductory programming courses have high drop-out rates and students do not learn to program well. This paper presents experiences from three educational institutions where introductory programming courses were improved by adopting Python as the first programming language and roles of…

  20. eqtools: Modular, extensible, open-source, cross-machine Python tools for working with magnetic equilibria

    Science.gov (United States)

    Chilenski, M. A.; Faust, I. C.; Walk, J. R.

    2017-01-01

    As plasma physics research for fusion energy transitions to an increasing emphasis on cross-machine collaboration and numerical simulation, it becomes increasingly important that portable tools be developed to enable data from diverse sources to be analyzed in a consistent manner. This paper presents eqtools, a modular, extensible, open-source toolkit implemented in the Python programming language for handling magnetic equilibria and associated data from tokamaks. eqtools provides a single interface for working with magnetic equilibrium data, both for handling derived quantities and mapping between coordinate systems, extensible to function with data from different experiments, data formats, and magnetic reconstruction codes, replacing the diverse, non-portable solutions currently in use. Moreover, while the open-source Python programming language offers a number of advantages as a scripting language for research purposes, the lack of basic tokamak-specific functionality has impeded the adoption of the language for regular use. Implementing equilibrium-mapping tools in Python removes a substantial barrier to new development in and porting legacy code into Python. In this paper, we introduce the design of the eqtools package and detail the workflow for usage and expansion to additional devices. The implementation of a novel three-dimensional spline solution (in two spatial dimensions and in time) is also detailed. Finally, verification and benchmarking for accuracy and speed against existing tools are detailed. Wider deployment of these tools will enable efficient sharing of data and software between institutions and machines as well as self-consistent analysis of the shared data.

  1. PyPDB: a Python API for the Protein Data Bank.

    Science.gov (United States)

    Gilpin, William

    2016-01-01

    We have created a Python programming interface for the RCSB Protein Data Bank (PDB) that allows search and data retrieval for a wide range of result types, including BLAST and sequence motif queries. The API relies on the existing XML-based API and operates by creating custom XML requests from native Python types, allowing extensibility and straightforward modification. The package has the ability to perform many types of advanced search of the PDB that are otherwise only available through the PDB website. PyPDB is implemented exclusively in Python 3 using standard libraries for maximal compatibility. The most up-to-date version, including iPython notebooks containing usage tutorials, is available free-of-charge under an open-source MIT license via GitHub at https://github.com/williamgilpin/pypdb, and the full API reference is at http://williamgilpin.github.io/pypdb_docs/html/. The latest stable release is also available on PyPI. wgilpin@stanford.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data

    Science.gov (United States)

    Shah, Abhik; Woolf, Peter

    2009-01-01

    Summary In this paper, we introduce pebl, a Python library and application for learning Bayesian network structure from data and prior knowledge that provides features unmatched by alternative software packages: the ability to use interventional data, flexible specification of structural priors, modeling with hidden variables and exploitation of parallel processing. PMID:20161541

  3. ‘ShruthLaikh’: Employing Python to Develop Vocabulary Enhancing Application

    Directory of Open Access Journals (Sweden)

    2010-09-01

    Full Text Available This paper presents how the power of Python, its various modules and Artificial Intelligence techniques can be integrated into a very useful and effective English spelling-correcting and vocabulary-enhancing application. The objective is to use the Python interface for various functionalities like text to speech, graphical user interface and sqlite3 database to integrate them into a single useful tool. The application is named as “ShruthLaikh”, which is a Hindi word for dictations. It has been demonstrated how this simple yet intelligent tool can help users to absorb word spellings in a very effective manner at the same time enhancing their retaining power. It also proves how Python as a programming language can be utilized effectively for the creation of powerful and user-friendly applications that can assist in more ways than one in revolutionizing the educational scene in nations across the world and the role that Python can play in imparting education in an innovative way.

  4. PyGOLD: a python based API for docking based virtual screening workflow generation.

    Science.gov (United States)

    Patel, Hitesh; Brinkjost, Tobias; Koch, Oliver

    2017-08-15

    Molecular docking is one of the successful approaches in structure based discovery and development of bioactive molecules in chemical biology and medicinal chemistry. Due to the huge amount of computational time that is still required, docking is often the last step in a virtual screening approach. Such screenings are set as workflows spanned over many steps, each aiming at different filtering task. These workflows can be automatized in large parts using python based toolkits except for docking using the docking software GOLD. However, within an automated virtual screening workflow it is not feasible to use the GUI in between every step to change the GOLD configuration file. Thus, a python module called PyGOLD was developed, to parse, edit and write the GOLD configuration file and to automate docking based virtual screening workflows. The latest version of PyGOLD, its documentation and example scripts are available at: http://www.ccb.tu-dortmund.de/koch or http://www.agkoch.de. PyGOLD is implemented in Python and can be imported as a standard python module without any further dependencies. oliver.koch@agkoch.de, oliver.koch@tu-dortmund.de. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  5. A high level interface to SCOP and ASTRAL implemented in Python

    Directory of Open Access Journals (Sweden)

    Saqi Mansoor AS

    2006-01-01

    Full Text Available Abstract Background Benchmarking algorithms in structural bioinformatics often involves the construction of datasets of proteins with given sequence and structural properties. The SCOP database is a manually curated structural classification which groups together proteins on the basis of structural similarity. The ASTRAL compendium provides non redundant subsets of SCOP domains on the basis of sequence similarity such that no two domains in a given subset share more than a defined degree of sequence similarity. Taken together these two resources provide a 'ground truth' for assessing structural bioinformatics algorithms. We present a small and easy to use API written in python to enable construction of datasets from these resources. Results We have designed a set of python modules to provide an abstraction of the SCOP and ASTRAL databases. The modules are designed to work as part of the Biopython distribution. Python users can now manipulate and use the SCOP hierarchy from within python programs, and use ASTRAL to return sequences of domains in SCOP, as well as clustered representations of SCOP from ASTRAL. Conclusion The modules make the analysis and generation of datasets for use in structural genomics easier and more principled.

  6. A high level interface to SCOP and ASTRAL implemented in python.

    Science.gov (United States)

    Casbon, James A; Crooks, Gavin E; Saqi, Mansoor A S

    2006-01-10

    Benchmarking algorithms in structural bioinformatics often involves the construction of datasets of proteins with given sequence and structural properties. The SCOP database is a manually curated structural classification which groups together proteins on the basis of structural similarity. The ASTRAL compendium provides non redundant subsets of SCOP domains on the basis of sequence similarity such that no two domains in a given subset share more than a defined degree of sequence similarity. Taken together these two resources provide a 'ground truth' for assessing structural bioinformatics algorithms. We present a small and easy to use API written in python to enable construction of datasets from these resources. We have designed a set of python modules to provide an abstraction of the SCOP and ASTRAL databases. The modules are designed to work as part of the Biopython distribution. Python users can now manipulate and use the SCOP hierarchy from within python programs, and use ASTRAL to return sequences of domains in SCOP, as well as clustered representations of SCOP from ASTRAL. The modules make the analysis and generation of datasets for use in structural genomics easier and more principled.

  7. Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories

    DEFF Research Database (Denmark)

    Cardoso, Joao; Jensen, Kristian; Lieven, Christian

    2017-01-01

    . It is written in Python and implements state-of-the-art methods for enumerating and prioritizing knock-out, knock-in, over-expression, and down-regulation strategies and combinations thereof. Cameo is an open source software project and is freely available under the Apache License 2.0. A dedicated website...

  8. PyMercury: Interactive Python for the Mercury Monte Carlo Particle Transport Code

    International Nuclear Information System (INIS)

    Iandola, F.N.; O'Brien, M.J.; Procassini, R.J.

    2010-01-01

    Monte Carlo particle transport applications are often written in low-level languages (C/C++) for optimal performance on clusters and supercomputers. However, this development approach often sacrifices straightforward usability and testing in the interest of fast application performance. To improve usability, some high-performance computing applications employ mixed-language programming with high-level and low-level languages. In this study, we consider the benefits of incorporating an interactive Python interface into a Monte Carlo application. With PyMercury, a new Python extension to the Mercury general-purpose Monte Carlo particle transport code, we improve application usability without diminishing performance. In two case studies, we illustrate how PyMercury improves usability and simplifies testing and validation in a Monte Carlo application. In short, PyMercury demonstrates the value of interactive Python for Monte Carlo particle transport applications. In the future, we expect interactive Python to play an increasingly significant role in Monte Carlo usage and testing.

  9. Simulation with Python on transverse modes of the symmetric confocal resonator

    Science.gov (United States)

    Wang, Qing Hua; Qi, Jing; Ji, Yun Jing; Song, Yang; Li, Zhenhua

    2017-08-01

    Python is a popular open-source programming language that can be used to simulate various optical phenomena. We have developed a suite of programs to help teach the course of laser principle. The complicated transverse modes of the symmetric confocal resonator can be visualized in personal computers, which is significant to help the students understand the pattern distribution of laser resonator.

  10. Python-based framework for coupled MC-TH reactor calculations

    International Nuclear Information System (INIS)

    Travleev, A.A.; Molitor, R.; Sanchez, V.

    2013-01-01

    We have developed a set of Python packages to provide a modern programming interface to codes used for analysis of nuclear reactors. Python classes can be classified by their functionality into three groups: low-level interfaces, general model classes and high-level interfaces. A low-level interface describes an interface between Python and a particular code. General model classes can be used to describe calculation geometry and meshes to represent system variables. High-level interface classes are used to convert geometry described with general model classes into instances of low-level interface classes and to put results of code calculations (read by low-interface classes) back to general model. The implementation of Python interfaces to the Monte Carlo neutronics code MCNP and thermo-hydraulic code SCF allow efficient description of calculation models and provide a framework for coupled calculations. In this paper we illustrate how these interfaces can be used to describe a pin model, and report results of coupled MCNP-SCF calculations performed for a PWR fuel assembly, organized by means of the interfaces

  11. Digestive physiology of the Burmese python: broad regulation of integrated performance.

    Science.gov (United States)

    Secor, Stephen M

    2008-12-01

    As an apparent adaptation to predictably long episodes of fasting, the sit-and-wait foraging Burmese python experiences unprecedented regulation of gastrointestinal and cardiovascular performance with feeding and fasting. The ingestion of a meal signals the quiescent gut tissues to start secreting digestive acid and enzymes, to upregulate intestinal brush-border enzymes and nutrient transporters, and to grow. An integrated phenomenon, digestion is also characterized by increases in the mass, and presumably the function, of the heart, pancreas, liver and kidneys. Once digestion is complete, the python's stomach and small intestine rapidly downregulate performance. Much of the modulation of intestinal function can be explained by the 5-fold increase in microvillus length and apical surface area with feeding, and the subsequent shortening of the microvilli after digestion has finished. Digestion for the Burmese python is a relatively expensive endeavor, evident by the as much as a 44-fold increase in metabolic rate and equivalent in cost to as much as 37% of the meal's energy. Their large metabolic response is supported by substantial increases in ventilation and cardiac output and the apparent catabolism of glucose and lipids. Unmatched in the magnitude of its numerous physiological responses to feeding, the Burmese python is a very attractive model for examining the capacities and regulatory mechanisms of physiological performance.

  12. SWMM5 Application Programming Interface and PySWMM: A Python Interfacing Wrapper

    Science.gov (United States)

    In support of the OpenWaterAnalytics open source initiative, the PySWMM project encompasses the development of a Python interfacing wrapper to SWMM5 with parallel ongoing development of the USEPA Stormwater Management Model (SWMM5) application programming interface (API). ...

  13. Old pythons stay fit; effects of haematozoan infections on life history traits of a large tropical predator.

    Science.gov (United States)

    Madsen, Thomas; Ujvari, Beata; Olsson, Mats

    2005-01-01

    We document the impact of blood parasite infections caused by Hepatozoon sp. on water python (Liasis fuscus) life history traits such as growth rates, condition, reproductive output and survival. Individual snakes maintained similar among-year parasite loads. Hepatozoon infections affected python growth rate, i.e. snakes suffering from high infection levels exhibited significantly slower growth compared to individuals with low parasite loads. Our results suggest that the parasites also affected the pythons' nutritional status (condition), as snakes with low condition scores suffered from higher parasite infection levels than snakes with high scores. Furthermore, our data suggest that parasitaemia may affect female reproductive output, as reproductive female pythons harboured lower parasite loads compared to non-reproductive adult females. High levels of parasite infections also affected juvenile python survival, as recaptured snakes harboured significantly lower parasite loads compared to non-recaptured yearling pythons. In our study area, water python have very few natural predators and, hence, experience low mortality rates and commonly reach an age of >15 years. In contrast to results obtained in other studies, parasite loads in larger/older pythons were lower compared to younger snakes, suggesting that only snakes harbouring lower levels of parasitaemia were able to survive to old age. We suggest that a possible cause for the opposing results regarding parasite prevalence and host age may be due to different levels of extrinsic mortality rates and longevity. Long-lived organisms, such as water pythons, may invest relatively more into crucial self-maintenance functions such as parasite defence, compared to short-lived organisms.

  14. GMI-IPS: Python Processing Software for Aircraft Campaigns

    Science.gov (United States)

    Damon, M. R.; Strode, S. A.; Steenrod, S. D.; Prather, M. J.

    2018-01-01

    NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the

  15. Morphological Pulmonary Diffusion Capacity for Oxygen of Burmese Pythons (Python molurus): a Comparison of Animals in Healthy Condition and with Different Pulmonary Infections.

    Science.gov (United States)

    Starck, J M; Weimer, I; Aupperle, H; Müller, K; Marschang, R E; Kiefer, I; Pees, M

    2015-11-01

    A qualitative and quantitative morphological study of the pulmonary exchange capacity of healthy and diseased Burmese pythons (Python molurus) was carried out in order to test the hypothesis that the high morphological excess capacity for oxygen exchange in the lungs of these snakes is one of the reasons why pathological processes extend throughout the lung parenchyma and impair major parts of the lungs before clinical signs of respiratory disease become apparent. Twenty-four Burmese pythons (12 healthy and 12 diseased) were included in the study. A stereology-based approach was used to quantify the lung parenchyma using computed tomography. Light microscopy was used to quantify tissue compartments and the respiratory exchange surface, and transmission electron microscopy was used to measure the thickness of the diffusion barrier. The morphological diffusion capacity for oxygen of the lungs and the anatomical diffusion factor were calculated. The calculated anatomical diffusion capacity was compared with published values for oxygen consumption of healthy snakes, and the degree to which the exchange capacity can be obstructed before normal physiological function is impaired was estimated. Heterogeneous pulmonary infections result in graded morphological transformations of pulmonary parenchyma involving lymphocyte migration into the connective tissue and thickening of the septal connective tissue, increasing thickness of the diffusion barrier and increasing transformation of the pulmonary epithelium into a columnar pseudostratified or stratified epithelium. The transformed epithelium developed by hyperplasia of ciliated cells arising from the tip of the faveolar septa and by hyperplasia of type II pneumocytes. These results support the idea that the lungs have a remarkable overcapacity for oxygen consumption and that the development of pulmonary disease continuously reduces the capacity for oxygen consumption. However, due to the overcapacity of the lungs, this

  16. Molecular cloning and characterization of satellite DNA sequences from constitutive heterochromatin of the habu snake (Protobothrops flavoviridis, Viperidae) and the Burmese python (Python bivittatus, Pythonidae).

    Science.gov (United States)

    Matsubara, Kazumi; Uno, Yoshinobu; Srikulnath, Kornsorn; Seki, Risako; Nishida, Chizuko; Matsuda, Yoichi

    2015-12-01

    Highly repetitive DNA sequences of the centromeric heterochromatin provide valuable molecular cytogenetic markers for the investigation of genomic compartmentalization in the macrochromosomes and microchromosomes of sauropsids. Here, the relationship between centromeric heterochromatin and karyotype evolution was examined using cloned repetitive DNA sequences from two snake species, the habu snake (Protobothrops flavoviridis, Crotalinae, Viperidae) and Burmese python (Python bivittatus, Pythonidae). Three satellite DNA (stDNA) families were isolated from the heterochromatin of these snakes: 168-bp PFL-MspI from P. flavoviridis and 196-bp PBI-DdeI and 174-bp PBI-MspI from P. bivittatus. The PFL-MspI and PBI-DdeI sequences were localized to the centromeric regions of most chromosomes in the respective species, suggesting that the two sequences were the major components of the centromeric heterochromatin in these organisms. The PBI-MspI sequence was localized to the pericentromeric region of four chromosome pairs. The PFL-MspI and the PBI-DdeI sequences were conserved only in the genome of closely related species, Gloydius blomhoffii (Crotalinae) and Python molurus, respectively, although their locations on the chromosomes were slightly different. In contrast, the PBI-MspI sequence was also in the genomes of P. molurus and Boa constrictor (Boidae), and additionally localized to the centromeric regions of eight chromosome pairs in B. constrictor, suggesting that this sequence originated in the genome of a common ancestor of Pythonidae and Boidae, approximately 86 million years ago. The three stDNA sequences showed no genomic compartmentalization between the macrochromosomes and microchromosomes, suggesting that homogenization of the centromeric and/or pericentromeric stDNA sequences occurred in the macrochromosomes and microchromosomes of these snakes.

  17. GMES: A Python package for solving Maxwell’s equations using the FDTD method

    Science.gov (United States)

    Chun, Kyungwon; Kim, Huioon; Kim, Hyounggyu; Jung, Kil Su; Chung, Youngjoo

    2013-04-01

    This paper describes GMES, a free Python package for solving Maxwell’s equations using the finite-difference time-domain (FDTD) method. The design of GMES follows the object-oriented programming (OOP) approach and adopts a unique design strategy where the voxels in the computational domain are grouped and then updated according to its material type. This piecewise updating scheme ensures that GMES can adopt OOP without losing its simple structure and time-stepping speed. The users can easily add various material types, sources, and boundary conditions into their code using the Python programming language. The key design features, along with the supported material types, excitation sources, boundary conditions and parallel calculations employed in GMES are also described in detail. Catalog identifier: AEOK_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOK_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License v3.0 No. of lines in distributed program, including test data, etc.: 17700 No. of bytes in distributed program, including test data, etc.: 89878 Distribution format: tar.gz Programming language: C++, Python. Computer: Any computer with a Unix-like system with a C++ compiler, and a Python interpreter; developed on 2.53 GHz Intel CoreTM i3. Operating system: Any Unix-like system; developed under Ubuntu 12.04 LTS 64 bit. Has the code been vectorized or parallelized?: Yes. Parallelized with MPI directives (optional). RAM: Problem dependent (a simulation with real valued electromagnetic field uses roughly 0.18 KB per Yee cell.) Classification: 10. External routines: SWIG [1], Cython [2], NumPy [3], SciPy [4], matplotlib [5], MPI for Python [6] Nature of problem: Classical electrodynamics Solution method: Finite-difference time-domain (FDTD) method Additional comments: This article describes version 0.9.5. The most recent version can be downloaded at the GMES

  18. Selected regulation of gastrointestinal acid-base secretion and tissue metabolism for the diamondback water snake and Burmese python.

    Science.gov (United States)

    Secor, Stephen M; Taylor, Josi R; Grosell, Martin

    2012-01-01

    Snakes exhibit an apparent dichotomy in the regulation of gastrointestinal (GI) performance with feeding and fasting; frequently feeding species modestly regulate intestinal function whereas infrequently feeding species rapidly upregulate and downregulate intestinal function with the start and completion of each meal, respectively. The downregulatory response with fasting for infrequently feeding snakes is hypothesized to be a selective attribute that reduces energy expenditure between meals. To ascertain the links between feeding habit, whole-animal metabolism, and GI function and metabolism, we measured preprandial and postprandial metabolic rates and gastric and intestinal acid-base secretion, epithelial conductance and oxygen consumption for the frequently feeding diamondback water snake (Nerodia rhombifer) and the infrequently feeding Burmese python (Python molurus). Independent of body mass, Burmese pythons possess a significantly lower standard metabolic rate and respond to feeding with a much larger metabolic response compared with water snakes. While fasting, pythons cease gastric acid and intestinal base secretion, both of which are stimulated with feeding. In contrast, fasted water snakes secreted gastric acid and intestinal base at rates similar to those of digesting snakes. We observed no difference between fasted and fed individuals for either species in gastric or intestinal transepithelial potential and conductance, with the exception of a significantly greater gastric transepithelial potential for fed pythons at the start of titration. Water snakes experienced no significant change in gastric or intestinal metabolism with feeding. Fed pythons, in contrast, experienced a near-doubling of gastric metabolism and a tripling of intestinal metabolic rate. For fasted individuals, the metabolic rate of the stomach and small intestine was significantly lower for pythons than for water snakes. The fasting downregulation of digestive function for pythons is

  19. Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

    Science.gov (United States)

    Lang, Timothy J.

    2015-01-01

    At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python-based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre-existing Python modules as well as to be object-oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25-year history into a common data structure suitable for user-defined analyses. It features rapid, simplified (i.e., one line of code) production of quick-look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication-ready figures. Deconvolution of the polarization-varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real-time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May-June 2014. The second software package is the Marshall Multi-Radar/Multi-Sensor (MRMS) Mosaic Python Toolkit, or MMM-Py for short. MMM-Py was designed to read, analyze, and display three-dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM-Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM-Py can easily stitch multiple tiles together to provide a

  20. PlasmaPy: beginning a community developed Python package for plasma physics

    Science.gov (United States)

    Murphy, Nicholas A.; Huang, Yi-Min; PlasmaPy Collaboration

    2016-10-01

    In recent years, researchers in several disciplines have collaborated on community-developed open source Python packages such as Astropy, SunPy, and SpacePy. These packages provide core functionality, common frameworks for data analysis and visualization, and educational tools. We propose that our community begins the development of PlasmaPy: a new open source core Python package for plasma physics. PlasmaPy could include commonly used functions in plasma physics, easy-to-use plasma simulation codes, Grad-Shafranov solvers, eigenmode solvers, and tools to analyze both simulations and experiments. The development will include modern programming practices such as version control, embedding documentation in the code, unit tests, and avoiding premature optimization. We will describe early code development on PlasmaPy, and discuss plans moving forward. The success of PlasmaPy depends on active community involvement and a welcoming and inclusive environment, so anyone interested in joining this collaboration should contact the authors.

  1. Towards Python-based Domain-specific Languages for Self-reconfigurable Modular Robotics Research

    DEFF Research Database (Denmark)

    Moghadam, Mikael; Johan Christensen, David; Brandt, David

    2013-01-01

    This paper explores the role of operating system and high-level languages in the development of software and domain-specific languages (DSLs) for self-reconfigurable robotics. We review some of the current trends in self-reconfigurable robotics and describe the development of a software system...... for ATRON II which utilizes Linux and Python to significantly improve software abstraction and portability while providing some basic features which could prove useful when using Python, either stand-alone or via a DSL, on a self-reconfigurable robot system. These features include transparent socket...... communication, module identification, easy software transfer and reliable module-to-module communication. The end result is a software platform for modular robots that where appropriate builds on existing work in operating systems, virtual machines, middleware and high-level languages....

  2. Towards Python-based Domain-specific Languages for Self-reconfigurable Modular Robotics Research

    DEFF Research Database (Denmark)

    Moghadam, Mikael; Christensen, David Johan; Brandt, David

    2011-01-01

    This paper explores the role of operating system and high-level languages in the development of software and domain-specific languages (DSLs) for self-reconfigurable robotics. We review some of the current trends in selfreconfigurable robotics and describe the development of a software system...... for ATRON II which utilizes Linux and Python to significantly improve software abstraction and portability while providing some basic features which could prove useful when using Python, either stand-alone or via a DSL, on a selfreconfigurable robot system. These features include transparent socket...... communication, module identification, easy software transfer and reliable module-to-module communication. The end result is a software platform for modular robots that where appropriate builds on existing work in operating systems, virtual machines, middleware and high-level languages....

  3. Creating CAD designs and performing their subsequent analysis using opensource solutions in Python

    Science.gov (United States)

    Iakushkin, Oleg O.; Sedova, Olga S.

    2018-01-01

    The paper discusses the concept of a system that encapsulates the transition from geometry building to strength tests. The solution we propose views the engineer as a programmer who is capable of coding the procedure for working with the modeli.e., to outline the necessary transformations and create cases for boundary conditions. We propose a prototype of such system. In our work, we used: Python programming language to create the program; Jupyter framework to create a single workspace visualization; pythonOCC library to implement CAD; FeniCS library to implement FEM; GMSH and VTK utilities. The prototype is launched on a platform which is a dynamically expandable multi-tenant cloud service providing users with all computing resources on demand. However, the system may be deployed locally for prototyping or work that does not involve resource-intensive computing. To make it possible, we used containerization, isolating the system in a Docker container.

  4. Qualitative: Python Tool for MT Quality Estimation Supporting Server Mode and Hybrid MT

    Directory of Open Access Journals (Sweden)

    Avramidis Eleftherios

    2016-10-01

    Full Text Available We are presenting the development contributions of the last two years to our Python opensource Quality Estimation tool, a tool that can function in both experiment-mode and online web-service mode. The latest version provides a new MT interface, which communicates with SMT and rule-based translation engines and supports on-the-fly sentence selection. Additionally, we present an improved Machine Learning interface allowing more efficient communication with several state-of-the-art toolkits. Additions also include a more informative training process, a Python re-implementation of QuEst baseline features, a new LM toolkit integration, an additional PCFG parser and alignments of syntactic nodes.

  5. Ibmdbpy-spatial : An Open-source implementation of in-database geospatial analytics in Python

    Science.gov (United States)

    Roy, Avipsa; Fouché, Edouard; Rodriguez Morales, Rafael; Moehler, Gregor

    2017-04-01

    As the amount of spatial data acquired from several geodetic sources has grown over the years and as data infrastructure has become more powerful, the need for adoption of in-database analytic technology within geosciences has grown rapidly. In-database analytics on spatial data stored in a traditional enterprise data warehouse enables much faster retrieval and analysis for making better predictions about risks and opportunities, identifying trends and spot anomalies. Although there are a number of open-source spatial analysis libraries like geopandas and shapely available today, most of them have been restricted to manipulation and analysis of geometric objects with a dependency on GEOS and similar libraries. We present an open-source software package, written in Python, to fill the gap between spatial analysis and in-database analytics. Ibmdbpy-spatial provides a geospatial extension to the ibmdbpy package, implemented in 2015. It provides an interface for spatial data manipulation and access to in-database algorithms in IBM dashDB, a data warehouse platform with a spatial extender that runs as a service on IBM's cloud platform called Bluemix. Working in-database reduces the network overload, as the complete data need not be replicated into the user's local system altogether and only a subset of the entire dataset can be fetched into memory in a single instance. Ibmdbpy-spatial accelerates Python analytics by seamlessly pushing operations written in Python into the underlying database for execution using the dashDB spatial extender, thereby benefiting from in-database performance-enhancing features, such as columnar storage and parallel processing. The package is currently supported on Python versions from 2.7 up to 3.4. The basic architecture of the package consists of three main components - 1) a connection to the dashDB represented by the instance IdaDataBase, which uses a middleware API namely - pypyodbc or jaydebeapi to establish the database connection via

  6. BioServices: a common Python package to access biological Web Services programmatically.

    Science.gov (United States)

    Cokelaer, Thomas; Pultz, Dennis; Harder, Lea M; Serra-Musach, Jordi; Saez-Rodriguez, Julio

    2013-12-15

    Web interfaces provide access to numerous biological databases. Many can be accessed to in a programmatic way thanks to Web Services. Building applications that combine several of them would benefit from a single framework. BioServices is a comprehensive Python framework that provides programmatic access to major bioinformatics Web Services (e.g. KEGG, UniProt, BioModels, ChEMBLdb). Wrapping additional Web Services based either on Representational State Transfer or Simple Object Access Protocol/Web Services Description Language technologies is eased by the usage of object-oriented programming. BioServices releases and documentation are available at http://pypi.python.org/pypi/bioservices under a GPL-v3 license.

  7. Automating tasks in protein structure determination with the clipper python module.

    Science.gov (United States)

    McNicholas, Stuart; Croll, Tristan; Burnley, Tom; Palmer, Colin M; Hoh, Soon Wen; Jenkins, Huw T; Dodson, Eleanor; Cowtan, Kevin; Agirre, Jon

    2018-01-01

    Scripting programming languages provide the fastest means of prototyping complex functionality. Those with a syntax and grammar resembling human language also greatly enhance the maintainability of the produced source code. Furthermore, the combination of a powerful, machine-independent scripting language with binary libraries tailored for each computer architecture allows programs to break free from the tight boundaries of efficiency traditionally associated with scripts. In the present work, we describe how an efficient C++ crystallographic library such as Clipper can be wrapped, adapted and generalized for use in both crystallographic and electron cryo-microscopy applications, scripted with the Python language. We shall also place an emphasis on best practices in automation, illustrating how this can be achieved with this new Python module. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

  8. Optimizing Python-based ROOT I/O with PyPy's Tracing JIT

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    The Python programming language allows objects and classes to respond dynamically to the execution environment. Most of this, however, is made possible through language hooks which by definition can not be optimized and thus tend to be slow. The PyPy implementation of Python includes a tracing just in time compiler (JIT), which allows similar dynamic responses but at the interpreter-, rather than the application-level. Therefore, it is possible to fully remove the hooks, leaving only the dynamic response, in the optimization stage for hot loops, if the types of interest are opened up to the JIT. A general opening up of types to the JIT, based on reflection information, has already been developed (cppyy). The work described in this paper takes it one step further by customizing access to ROOT I/O to the JIT, allowing for automatic selective reading, judicious caching, and buffer tuning.

  9. Experiences in Building Python Automation Framework for Verification and Data Collections

    Directory of Open Access Journals (Sweden)

    2010-09-01

    Full Text Available

    This paper describes our experiences in building a Python automation framework. Specifically, the automation framework is used to support verification and data collection scripts. The scripts control various test equipments in addition to the device under test (DUT to characterize a specific performance with a specific configuration or to evaluate the correctness of the behaviour of the DUT. The specific focus on this paper is on documenting our experiences in building an automation framework using Python: on the purposes, goals and the benefits, rather than on a tutorial of how to build such a framework.

  10. STEPS: modeling and simulating complex reaction-diffusion systems with Python

    Directory of Open Access Journals (Sweden)

    Stefan Wils

    2009-06-01

    Full Text Available We describe how the use of the Python language improved the user interface of the program STEPS. STEPS is a simulation platform for modeling and stochastic simulation of coupled reaction-diffusion systems with complex 3-dimensional boundary conditions. Setting up such models is a complicated process that consists of many phases. Initial versions of STEPS relied on a static input format that did not cleanly separate these phases, limiting modelers in how they could control the simulation and becoming increasingly complex as new features and new simulation algorithms were added. We solved all of these problems by tightly integrating STEPS with Python, using SWIG to expose our existing simulation code.

  11. PetClaw: A scalable parallel nonlinear wave propagation solver for Python

    KAUST Repository

    Alghamdi, Amal

    2011-01-01

    We present PetClaw, a scalable distributed-memory solver for time-dependent nonlinear wave propagation. PetClaw unifies two well-known scientific computing packages, Clawpack and PETSc, using Python interfaces into both. We rely on Clawpack to provide the infrastructure and kernels for time-dependent nonlinear wave propagation. Similarly, we rely on PETSc to manage distributed data arrays and the communication between them.We describe both the implementation and performance of PetClaw as well as our challenges and accomplishments in scaling a Python-based code to tens of thousands of cores on the BlueGene/P architecture. The capabilities of PetClaw are demonstrated through application to a novel problem involving elastic waves in a heterogeneous medium. Very finely resolved simulations are used to demonstrate the suppression of shock formation in this system.

  12. Analyzing microtomography data with Python and the scikit-image library.

    Science.gov (United States)

    Gouillart, Emmanuelle; Nunez-Iglesias, Juan; van der Walt, Stéfan

    2017-01-01

    The exploration and processing of images is a vital aspect of the scientific workflows of many X-ray imaging modalities. Users require tools that combine interactivity, versatility, and performance. scikit-image is an open-source image processing toolkit for the Python language that supports a large variety of file formats and is compatible with 2D and 3D images. The toolkit exposes a simple programming interface, with thematic modules grouping functions according to their purpose, such as image restoration, segmentation, and measurements. scikit-image users benefit from a rich scientific Python ecosystem that contains many powerful libraries for tasks such as visualization or machine learning. scikit-image combines a gentle learning curve, versatile image processing capabilities, and the scalable performance required for the high-throughput analysis of X-ray imaging data.

  13. Computed tomography of the lung of healthy snakes of the species Python regius, Boa constrictor, Python reticulatus, Morelia viridis, Epicrates cenchria, and Morelia spilota.

    Science.gov (United States)

    Pees, Michael; Kiefer, Ingmar; Thielebein, Jens; Oechtering, Gerhard; Krautwald-Junghanns, Maria-Elisabeth

    2009-01-01

    Thirty-nine healthy boid snakes representing six different species (Python regius, Boa constrictor, Python reticulatus, Morelia viridis, Epicrates cenchria, and Morelia spilota) were examined using computed tomography (CT) to characterize the normal appearance of the respiratory tissue. Assessment was done subjectively and densitometry was performed using a defined protocol. The length of the right lung was calculated to be 11.1% of the body length, without a significant difference between species. The length of the left lung in proportion to the right was dependent on the species examined. The most developed left lung was in P. regius (81.2%), whereas in B. constrictor, the left lung was vestigial or absent (24.7%). A median attenuation of -814.6 HU and a variability of 45.9 HU were calculated for all species with no significant difference between species. Within the species, a significantly higher attenuation was found for P. regius in the dorsal and cranial aspect of the lung compared with the ventral and caudal part. In B. constrictor, the reduced left lung was significantly hyperattenuating compared with the right lung. Results of this study emphasize the value of CT and provide basic reference data for assessment of the snake lung in these species. Veterinary Radiology &

  14. eblur/dust: a modular Python approach to extinction and scattering

    OpenAIRE

    Lia Corrales

    2016-01-01

    I will present a library of python codes -- github.com/eblur/dust -- which calculate dust scattering and extinction properties from the IR to the X-ray. The modular interface allows for custom defined dust grain size distributions, optical constants, and scattering physics. These codes are currently undergoing a major overhaul to include multiple scattering effects, parallel processing, parameterized grain size distributions beyond power law, and optical constants for different grain...

  15. Transformation of Python Applications into Function-as-a-Service Deployments

    OpenAIRE

    Spillner, Josef

    2017-01-01

    New cloud programming and deployment models pose challenges to software application engineers who are looking, often in vain, for tools to automate any necessary code adaptation and transformation. Function-as-a-Service interfaces are particular non-trivial targets when considering that most cloud applications are implemented in non-functional languages. Among the most widely used of these languages is Python. This starting position calls for an automated approach to transform monolithic Pyth...

  16. Development and Evaluation of a Python Telecare System Based on a Bluetooth Body Area Network

    OpenAIRE

    M. J. Morón; A. Gómez-Jaime; J. R. Luque; E. Casilari

    2011-01-01

    This paper presents a prototype of a telemonitoring system, based on a BAN (Body Area Network) that is integrated by a Bluetooth (BT) pulse oximeter, a GPS (Global Positioning System) unit, and a smartphone. The smartphone is the hardware platform for running a Python software that manages the Bluetooth piconet formed by the sensors. Thus the smartphone forwards the data received from the Bluetooth devices, encoded into JSON (JavaScript Object Notation), to a central server. This server prov...

  17. Approaching the largest ‘API’: extracting information from the Internet with Python

    OpenAIRE

    Jonathan E. Germann

    2018-01-01

    This article explores the need for libraries to algorithmically access and manipulate the world’s largest API: the Internet. The billions of pages on the ‘Internet API’ (HTTP, HTML, CSS, XPath, DOM, etc.) are easily accessible and manipulable. Libraries can assist in creating meaning through the datafication of information on the world wide web. Because most information is created for human consumption, some programming is required for automated extraction. Python is an easy-to-learn progra...

  18. PENGEMBANGAN PROGRAM APLIKASI ENHANCED MACHINE CONTROL DENGAN PYTHON UNTUK METODE INTERPOLASI NEWTON

    OpenAIRE

    Alexander Agung Santoso Gunawan; Jimmy Linggarjati

    2012-01-01

    Nowadays, one of industrial main problems is the flexibility of machines to be customized since they are designed based on certain standard. This research develops software for CNC (Computer Numerically Controlled) machine in order to execute the Newton Interpolation using Python. The platform used in the CNCmachine is EMC (Enhanced Machine Control) and GUI (Graphical User Interface) AXIS on the operating system Linux Ubuntu. The Newton interpolation is used to create a curve based on several...

  19. COMPARISON OF PYTHON (AN OPEN SOURCE PROGRAMMING LANGUAGE) WITH OTHER PROGRAMMING LANGUAGES

    OpenAIRE

    Sushil Kumar*1 & Richa Aggarwal2

    2018-01-01

    Language is a communication tool through which we can communicate with each other like Hindi, English etc any other language. So if we want to communicate with computer, we need computer programming languages. So in computer we have two types of languages, one is low level language which is easily understood by computer but difficult to learn. Second is high level language which is same like English language, not understood by computer but easy to learn. Python is a high level language. This...

  20. RESTRICTIVE CARDIOMYOPATHY AND SECONDARY CONGESTIVE HEART FAILURE IN A MCDOWELL'S CARPET PYTHON (MORELIA SPILOTA MCDOWELLI).

    Science.gov (United States)

    Schilliger, Lionel; Chetboul, Valérie; Damoiseaux, Cécile; Nicolier, Alexandra

    2016-12-01

    Echocardiography is an established and noninvasive diagnostic tool used in herpetologic cardiology. Various cardiac lesions have been previously described in reptiles with the exception of restrictive cardiomyopathy. In this case report, restrictive cardiomyopathy and congestive heart failure associated with left atrial and sinus venosus dilation were diagnosed in a 2-yr-old captive lethargic McDowell's carpet python ( Morelia spilota mcdowelli), based on echocardiographic, Doppler, and histopathologic examinations. This cardiomyopathy was also associated with thrombosis within the sinus venosus.