WorldWideScience

Sample records for burmese python python

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

    Institute of Scientific and Technical Information of China (English)

    Mariana A; Vellayan S; Halimaton I; Ho TM

    2011-01-01

    Objective: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. Methods: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. Results: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. Conclusions: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.

  2. Consumption of bird eggs by invasive Burmese Pythons in Florida

    Science.gov (United States)

    Dove, Carla J.; Reed, Robert N.; Snow, Ray W.

    2012-01-01

    Burmese Pythons (Python molurus bivittatus or P. bivittatus) have been reported to consume 25 species of adult birds in Everglades National Park, Florida (Dove et al. 2011), but until now no records documented this species eating bird eggs. Here we report three recent cases of bird-egg consumption by Burmese Pythons and discuss egg-eating in basal snakes.

  3. Ecological correlates of invasion impact for Burmese pythons in Florida

    Science.gov (United States)

    Reed, R.N.; Willson, J.D.; Rodda, G.H.; Dorcas, M.E.

    2012-01-01

    An invasive population of Burmese pythons (Python molurus bivittatus) is established across several thousand square kilometers of southern Florida and appears to have caused precipitous population declines among several species of native mammals. Why has this giant snake had such great success as an invasive species when many established reptiles have failed to spread? We scored the Burmese python for each of 15 literature-based attributes relative to predefined comparison groups from a diverse range of taxa and provide a review of the natural history and ecology of Burmese pythons relevant to each attribute. We focused on attributes linked to spread and magnitude of impacts rather than establishment success. Our results suggest that attributes related to body size and generalism appeared to be particularly applicable to the Burmese python's success in Florida. The attributes with the highest scores were: high reproductive potential, low vulnerability to predation, large adult body size, large offspring size and high dietary breadth. However, attributes of ectotherms in general and pythons in particular (including predatory mode, energetic efficiency and social interactions) might have also contributed to invasion success. Although establishment risk assessments are an important initial step in prevention of new establishments, evaluating species in terms of their potential for spreading widely and negatively impacting ecosystems might become part of the means by which resource managers prioritize control efforts in environments with large numbers of introduced species.

  4. 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.

  5. 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

  6. 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.

  7. 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. PMID:25139000

  8. A multi-organ transcriptome resource for the Burmese Python (Python molurus bivittatus

    Directory of Open Access Journals (Sweden)

    Mockler Todd C

    2011-08-01

    Full Text Available Abstract Background Snakes provide a unique vertebrate system for studying a diversity of extreme adaptations, including those related to development, metabolism, physiology, and venom. Despite their importance as research models, genomic resources for snakes are few. Among snakes, the Burmese python is the premier model for studying extremes of metabolic fluctuation and physiological remodelling. In this species, the consumption of large infrequent meals can induce a 40-fold increase in metabolic rate and more than a doubling in size of some organs. To provide a foundation for research utilizing the python, our aim was to assemble and annotate a transcriptome reference from the heart and liver. To accomplish this aim, we used the 454-FLX sequencing platform to collect sequence data from multiple cDNA libraries. Results We collected nearly 1 million 454 sequence reads, and assembled these into 37,245 contigs with a combined length of 13,409,006 bp. To identify known genes, these contigs were compared to chicken and lizard gene sets, and to all Genbank sequences. A total of 13,286 of these contigs were annotated based on similarity to known genes or Genbank sequences. We used gene ontology (GO assignments to characterize the types of genes in this transcriptome resource. The raw data, transcript contig assembly, and transcript annotations are made available online for use by the broader research community. Conclusion These data should facilitate future studies using pythons and snakes in general, helping to further contribute to the utilization of snakes as a model evolutionary and physiological system. This sequence collection represents a major genomic resource for the Burmese python, and the large number of transcript sequences characterized should contribute to future research in this and other snake species.

  9. 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 radiotelemetered 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.

  10. Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python)

    OpenAIRE

    Irizarry, Kristopher J. L.; Josep Rutllant

    2016-01-01

    Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism's genome (such as the mouse genome) in order to make physiological inferences about the role of genes and proteins in a less characterized organism's genome (such as the Burmese python). We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 g...

  11. 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

    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...

  12. 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; 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.

  13. 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.

  14. 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.

  15. The Burmese python genome reveals the molecular basis for extreme adaptation in snakes

    OpenAIRE

    Castoe, Todd A.; de Koning, A. P. Jason; Hall, Kathryn T.; Card, Daren C.; Schield, Drew R.; Fujita, Matthew K.; Ruggiero, Robert P.; Degner, Jack F.; Daza, Juan M.; Gu, Wanjun; Reyes-Velasco, Jacobo; Shaney, Kyle J.; Castoe, Jill M.; Samuel E Fox; Poole, Alex W.

    2013-01-01

    The molecular basis of morphological and physiological adaptations in snakes is largely unknown. Here, we study these phenotypes using the genome of the Burmese python (Python molurus bivittatus), a model for extreme phenotypic plasticity and metabolic adaptation. We discovered massive rapid changes in gene expression that coordinate major changes in organ size and function after feeding. Many significantly responsive genes are associated with metabolism, development, and mammalian diseases. ...

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

    Science.gov (United States)

    Hunter, Margaret E; Oyler-McCance, Sara J; Dorazio, Robert M; Fike, Jennifer A; Smith, Brian J; Hunter, Charles T; Reed, Robert N; Hart, Kristen M

    2015-01-01

    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 constrictors

  17. 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

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

    OpenAIRE

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

  19. 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.

  20. Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python)

    Science.gov (United States)

    Rutllant, Josep

    2016-01-01

    Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism's genome (such as the mouse genome) in order to make physiological inferences about the role of genes and proteins in a less characterized organism's genome (such as the Burmese python). We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1) production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2) enhanced assisted reproduction technology for endangered and captive reptiles; and (3) novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value. PMID:27200191

  1. Assessing risks to humans from invasive Burmese pythons in Everglades National Park, Florida, USA

    Science.gov (United States)

    Reed, Robert N.; Snow, Ray W.

    2014-01-01

    Invasive Burmese pythons (Python molurus bivittatus) are now established across a large area of southern Florida, USA, including all of Everglades National Park (NP). The presence of these large-bodied snakes in the continental United States has attracted intense media attention, including regular reference to the possibility of these snakes preying on humans. Over the course of a decade (2003–2012), we solicited reports of apparently unprovoked strikes directed at humans in Everglades NP. We summarize the circumstances surrounding each of the 5 reported incidents, which occurred between 2006 and 2012. All strikes were directed toward biologists moving through flooded wetlands; 2 strikes resulted in minor injury and none resulted in constriction. We consider most of these strikes to be cases of “mistaken identity,” in which the python initiated a strike at a potential prey item but aborted its predatory behavior prior to constriction and ingestion. No strikes are known to have been directed at park visitors despite visitation rates averaging over one million per year during this period. We conclude that while risks to humans should not be completely discounted, the relative risk of a human being killed by a python in Everglades NP appears to be extremely low.

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

    OpenAIRE

    Hart, Kristen M.; Hunter, Margaret E.

    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 ecosyste...

  3. 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.

  4. 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

  5. Python tutorial

    OpenAIRE

    Rossum, van, M.A.J.

    1995-01-01

    Python 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 prominent are influences from ABC, C, Modula-3 and Icon. The Python interpreter is easily extended with new functions and data types implemented in C. Python is also suitable as an extension language for highly custo...

  6. 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

  7. 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

  8. 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. PMID:26205503

  9. Python tutorial

    NARCIS (Netherlands)

    Rossum, G. van

    1995-01-01

    Python 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 prominent are infl

  10. 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

    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 these...

  11. 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.

  12. 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.

  13. X Python reference manual

    OpenAIRE

    Mullender, Sjoerd

    1995-01-01

    This 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 Reference Manual gives a more formal definition of the language. The Python Library Reference describes the built-in and standard modules of Python. This document can be seen as en extension to that document.

  14. X Python reference manual

    NARCIS (Netherlands)

    Mullender, K.S.

    1995-01-01

    This 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 Reference Manu

  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. Mixing Python and Java

    OpenAIRE

    Schreiber, Andreas

    2009-01-01

    Java is being used for many existing applications in a variety of domains. Sometimes it is useful to integrate them with Python. For instance, one may wish to add embedded Python scripting to Java applications, to communicate with separate Python code written for CPython, or use existing Java libraries from Python code. The talk gives an overview of the various techniques, tools, and libraries for bridging Python and Java. In particular, the following implementations are described and com...

  17. Python bindings for libcloudph++

    OpenAIRE

    Jarecka, Dorota; Arabas, Sylwester; Del Vento, Davide

    2015-01-01

    This technical note introduces the Python bindings for libcloudph++. The libcloudph++ is a C++ library of algorithms for representing atmospheric cloud microphysics in numerical models. The bindings expose the complete functionality of the library to the Python users. The bindings are implemented using the Boost.Python C++ library and use NumPy arrays. This note includes listings with Python scripts exemplifying the use of selected library components. An example solution for using the Python ...

  18. 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.

  19. 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.

  20. Python data mining environments

    OpenAIRE

    Mrak, Aleš

    2012-01-01

    In the thesis we compare the systems for data mining that have an interface in the programming language Python. Many open-source systems for data mining and library had implemented their software interfaces to the Python programming language. They choose Python because it is fast and provides object-oriented programming, allows for the integration of other software libraries in Python and is implemented in all major operating systems (Windows, Linux / Unix, OS / 2, Mac, etc..). Our analysis s...

  1. 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

  2. Python bindings for libcloudph++

    CERN Document Server

    Jarecka, Dorota; Del Vento, Davide

    2015-01-01

    This technical note introduces the Python bindings for libcloudph++. The libcloudph++ is a C++ library of algorithms for representing atmospheric cloud microphysics in numerical models. The bindings expose the complete functionality of the library to the Python users. The bindings are implemented using the Boost.Python C++ library and use NumPy arrays. This note includes listings with Python scripts exemplifying the use of selected library components. An example solution for using the Python bindings to access libcloudph++ from Fortran is presented.

  3. 75 FR 38069 - Injurious Wildlife Species; Listing the Boa Constrictor, Four Python Species, and Four Anaconda...

    Science.gov (United States)

    2010-07-01

    ... proposed rule (75 FR 11808) to list the Indian python (Python molurus, including Burmese python Python... proposed rule (75 FR 11808; March 12, 2010), draft economic analysis, draft environmental assessment, and U... comments, please refer to the March 12, 2010, proposed rule (75 FR 11808), available online at...

  4. Python reference manual

    OpenAIRE

    Rossum, van, M.A.J.

    1995-01-01

    Python 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; most prominent are influences from ABC, C, Modula-3 and Icon. The Python interpreter is easily extended with new functions and data types implemented in C. Python is also suitable as an extension language for...

  5. 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.

  6. 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.

  7. 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.

  8. Python high performance programming

    CERN Document Server

    Lanaro, Gabriele

    2013-01-01

    An exciting, easy-to-follow guide illustrating the techniques to boost the performance of Python code, and their applications with plenty of hands-on examples.If you are a programmer who likes the power and simplicity of Python and would like to use this language for performance-critical applications, this book is ideal for you. All that is required is a basic knowledge of the Python programming language. The book will cover basic and advanced topics so will be great for you whether you are a new or a seasoned Python developer.

  9. 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

  10. 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

  11. 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

  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. 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.

  14. 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.

  15. 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)....

  16. Python library reference

    NARCIS (Netherlands)

    Rossum, G. van

    1995-01-01

    Python 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 describe the

  17. Python in Astronomy 2016

    Science.gov (United States)

    Jenness, Tim; Robitaille, Thomas; Tollerud, Erik; Mumford, Stuart; Cruz, Kelle

    2016-04-01

    The second Python in Astronomy conference will be held from 21-25 March 2016 at the University of Washington eScience Institute in Seattle, WA, USA. Similarly to the 2015 meeting (which was held at the Lorentz Center), we are aiming to bring together researchers, Python developers, users, and educators. The conference will include presentations, tutorials, unconference sessions, and coding sprints. In addition to sharing information about state-of-the art Python Astronomy packages, the workshop will focus on improving interoperability between astronomical Python packages, providing training for new open-source contributors, and developing educational materials for Python in Astronomy. The meeting is therefore not only aimed at current developers, but also users and educators who are interested in being involved in these efforts.

  18. 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.

  19. Python - Realizer : Python done in C++ and Qt

    OpenAIRE

    2005-01-01

    Python – Realizer is basically planned to become the original Python done in C++ and Qt class library. This to make it a brand new implemented Python interpreter with a new rapid application development application extending it, for a complete Python system. It is supposed to become the Visual Basic of Python, in a matter of speak with most ideas taken from that environment. At least what it was in earlier edition, before everything got transfer to Visual Studio. It should not includ...

  20. PYTHON: Stata module for using the Python language within Stata

    OpenAIRE

    James Fiedler

    2013-01-01

    This module includes code for the "python_plugin" C plugin, and associated files. The plugin makes the Python language available within Stata, and provides Python functions to interact with Stata data, matrices, macros, and numeric scalars. The plugin can be used through an interactive interpreter or be used to execute Python files. This code is experimental. In particular, that means that it should be used with caution. See python_plugin.pdf for more information.

  1. 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

  2. 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

  3. 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.

  4. Python profiling 101

    CERN Document Server

    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.

  5. 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.

  6. 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.

  7. NEURON and Python

    Directory of Open Access Journals (Sweden)

    Michael Hines

    2009-01-01

    Full Text Available 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 GUI 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.

  8. 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.

  9. 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.

  10. NEURON and Python

    OpenAIRE

    Michael Hines; Davison, Andrew P.; 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 ...

  11. Manipulating Strings in Python

    OpenAIRE

    William J. Turkel; Adam Crymble

    2012-01-01

    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.

  12. Python library reference

    OpenAIRE

    Rossum, van, M.A.J.

    1995-01-01

    Python 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 describe the standard library that is distributed with the language, and which greatly enhances its immediate usability. This library contains built-in modules (written in C) that provide access to system funct...

  13. 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.

  14. Developing Sherpa with Python

    Science.gov (United States)

    Doe, S.; Nguyen, D.; Stawarz, C.; Refsdal, B.; Siemiginowska, A.; Burke, D.; Evans, I.; Evans, J.; McDowell, J.; Houck, J.; Nowak, M.

    2007-10-01

    Sherpa is the general purpose fitting and modeling application for CIAO, the Chandra Interactive Analysis of Observations system. We have modified the original design and implemented a new version in Python. This version will be part of the upcoming CIAO4.0 release. We have previously presented a modular, flexible design for CIAO4.0 with the goal of packaging many models, fitting methods and statistics for analysis of astronomical data. The new design promised to be more robust than the previous Sherpa, and more easily extensible with user-written scripts. (We already see some sign of this, in that there were 50,000 lines of code in the CIAO3.0 implementation; with our new, cleaner design, implemented in Python, only half that number of lines were required.) We present the latest updates to our design, and our progress developing Sherpa. A major feature of this work has been the use of Python to implement the data structures from our design. Each part of Sherpa---models, fitting methods, statistics, and so on---has been implemented as a Python module. We have also developed application code to bind together data, models, statistics, and fitting methods for performing fits to data, as well as a high-level UI that makes it simple for users to read in data, define models, and perform fits. Working in Python has been a great aid in speeding development of Sherpa. We expect that Python will also simplify extending and maintaining the Sherpa code base, as well as making it possible to interoperate with other Python-based astronomy packages. To make Sherpa fully accessible to S--Lang users, we use PySL, a new package that is an interface between Python and S--Lang. Users are now able to import other Python or S--Lang modules to extend Sherpa; in addition, users may write and use scripts of their own, written in either Python or S--Lang.

  15. Python imaging library

    OpenAIRE

    Mágr, Martin

    2008-01-01

    Tato bakalářská práce se zabývá návrhem a implementací editoru grafů, který je propojen s konkrétním informačním systémem protokolem XML-RPC. Aplikace je vytvořena pomocí jazyka Python a jeho grafické knihovny Python Imaging Library. Pro realizaci grafického uživatelského rozhraní je využívána knihovna GTK+ resp. její aplikační programové rozhraní pro Python, PyGTK. This bachelor thesis is engaged in concept and implementation of graph editor, which is connected with concrete information s...

  16. 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.

  17. 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

  18. Twittering with Python

    OpenAIRE

    Schreiber, Andreas

    2009-01-01

    The use of the Web 2.0 service Twitter is growing rapidly. More and more people, projects, companies, organizations, or others are using Twitter to send out a lot of 140 character messages to the world (i.e., their followers). This talk gives an overview of how to use Python for automating Twitter actions, such as sending tweets, viewing tweets of friends, and managing the list of Twitter friends. The various existing Python libraries for accessing the Twitter API are presented and compar...

  19. 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

  20. Developers@CERN Forums: Python

    CERN Document Server

    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?

  1. Marsh rabbit mortalities tie pythons to the precipitous decline of mammals in the Everglades

    OpenAIRE

    McCleery, Robert A.; Sovie, Adia; Reed, Robert N.; Cunningham, Mark W.; Hunter, Margaret E.; Hart, Kristen M.

    2015-01-01

    To address the ongoing debate over the impact of invasive species on native terrestrial wildlife, we conducted a large-scale experiment to test the hypothesis that invasive Burmese pythons (Python molurus bivittatus) were a cause of the precipitous decline of mammals in Everglades National Park (ENP). Evidence linking pythons to mammal declines has been indirect and there are reasons to question whether pythons, or any predator, could have caused the precipitous declines seen across a range o...

  2. Python comme langage scientifique

    OpenAIRE

    Varoquaux, Gaël

    2009-01-01

    Python dispose de nombreux modules de calcul scientifique permettant d'aborder efficament un probleme scientifique. C'est un langage très riche et des outils interactifs permettent de le transformer en un environement de travail complet et facile d'utilisation pour l'informatique scientifique.

  3. MDSplus Objects - Python Implementation

    International Nuclear Information System (INIS)

    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. This document is composed of an abstract followed by the presentation slides. (authors)

  4. Python and computer vision

    Energy Technology Data Exchange (ETDEWEB)

    Doak, J. E. (Justin E.); Prasad, Lakshman

    2002-01-01

    This paper discusses the use of Python in a computer vision (CV) project. We begin by providing background information on the specific approach to CV employed by the project. This includes a brief discussion of Constrained Delaunay Triangulation (CDT), the Chordal Axis Transform (CAT), shape feature extraction and syntactic characterization, and normalization of strings representing objects. (The terms 'object' and 'blob' are used interchangeably, both referring to an entity extracted from an image.) The rest of the paper focuses on the use of Python in three critical areas: (1) interactions with a MySQL database, (2) rapid prototyping of algorithms, and (3) gluing together all components of the project including existing C and C++ modules. For (l), we provide a schema definition and discuss how the various tables interact to represent objects in the database as tree structures. (2) focuses on an algorithm to create a hierarchical representation of an object, given its string representation, and an algorithm to match unknown objects against objects in a database. And finally, (3) discusses the use of Boost Python to interact with the pre-existing C and C++ code that creates the CDTs and CATS, performs shape feature extraction and syntactic characterization, and normalizes object strings. The paper concludes with a vision of the future use of Python for the CV project.

  5. Python reference manual

    NARCIS (Netherlands)

    Rossum, G. van

    1995-01-01

    Python 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; most promin

  6. 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.

  7. 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.

  8. MontePython: Implementing Quantum Monte Carlo using Python

    OpenAIRE

    J.K. Nilsen

    2006-01-01

    We present a cross-language C++/Python program for simulations of quantum mechanical systems with the use of Quantum Monte Carlo (QMC) methods. We describe a system for which to apply QMC, the algorithms of variational Monte Carlo and diffusion Monte Carlo and we describe how to implement theses methods in pure C++ and C++/Python. Furthermore we check the efficiency of the implementations in serial and parallel cases to show that the overhead using Python can be negligible.

  9. 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

  10. 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.

  11. Python for audio signal processing

    OpenAIRE

    Glover, John C.; Lazzarini, Victor; Timoney, Joseph

    2011-01-01

    This paper discusses the use of Python for developing audio signal processing applications. Overviews of Python language, NumPy, SciPy and Matplotlib are given, which together form a powerful platform for scientic computing. We then show how SciPy was used to create two audio programming libraries, and describe ways that Python can be integrated with the SndObj library and Pure Data, two existing environments for music composition and signal processing.

  12. 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).

  13. Activity in PythonPDEVS

    OpenAIRE

    Van Tendeloo Yentl; Vangheluwe Hans

    2014-01-01

    We introduce an activity-enhanced version of PythonPDEVS, a Parallel DEVS simulator. PythonPDEVS supports both sequential and distributed simulation. Both sequential and distributed variants of PythonPDEVS exploit information about computational activity to reduce simulation time. DEVS models can be augmented by the user with domain-specific information about computational load. This information is used by the simulator to improve performance.

  14. 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.

  15. 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

  16. 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...

  17. 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.

  18. Python Introduction and Installation

    OpenAIRE

    William J. Turkel; Adam Crymble

    2012-01-01

    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 ...

  19. Learning Scientific Programming with Python

    Science.gov (United States)

    Hill, Christian

    2016-02-01

    1. Introduction; 2. The core Python language I; 3. Interlude: simple plotting with pylab; 4. The core Python language II; 5. IPython and IPython notebook; 6. NumPy; 7. Matplotlib; 8. SciPy; 9. General scientific programming; Appendix A; Solutions; Index.

  20. 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.

  1. EPICS V4 in Python

    International Nuclear Information System (INIS)

    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

  2. Writing faster Python

    CERN Document Server

    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...

  3. MDSplus objects-Python implementation

    International Nuclear Information System (INIS)

    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.

  4. 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.

  5. Weighted graph algorithms with Python

    OpenAIRE

    Kapanowski, A.; Gałuszka, Ł.

    2015-01-01

    Python implementation of selected weighted graph algorithms is presented. The minimal graph interface is defined together with several classes implementing this interface. Graph nodes can be any hashable Python objects. Directed edges are instances of the Edge class. Graphs are instances of the Graph class. It is based on the adjacency-list representation, but with fast lookup of nodes and neighbors (dict-of-dict structure). Other implementations of this class are also possible. In this work,...

  6. Python Unleashed on Systems Biology

    OpenAIRE

    Christopher R Myers; Gutenkunst, Ryan N.; Sethna, James P.

    2007-01-01

    We have built an open-source software system for the modeling of biomolecular reaction networks, SloppyCell, which is written in Python and makes substantial use of third-party libraries for numerics, visualization, and parallel programming. We highlight here some of the powerful features that Python provides that enable SloppyCell to do dynamic code synthesis, symbolic manipulation, and parallel exploration of complex parameter spaces.

  7. Pynamic: the Python Dynamic Benchmark

    Energy Technology Data Exchange (ETDEWEB)

    Lee, G L; Ahn, D H; de Supinksi, B R; Gyllenhaal, J C; Miller, P J

    2007-07-10

    Python is widely used in scientific computing to facilitate application development and to support features such as computational steering. Making full use of some of Python's popular features, which improve programmer productivity, leads to applications that access extremely high numbers of dynamically linked libraries (DLLs). As a result, some important Python-based applications severely stress a system's dynamic linking and loading capabilities and also cause significant difficulties for most development environment tools, such as debuggers. Furthermore, using the Python paradigm for large scale MPI-based applications can create significant file IO and further stress tools and operating systems. In this paper, we present Pynamic, the first benchmark program to support configurable emulation of a wide-range of the DLL usage of Python-based applications for large scale systems. Pynamic has already accurately reproduced system software and tool issues encountered by important large Python-based scientific applications on our supercomputers. Pynamic provided insight for our system software and tool vendors, and our application developers, into the impact of several design decisions. As we describe the Pynamic benchmark, we will highlight some of the issues discovered in our large scale system software and tools using Pynamic.

  8. 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

  9. Marsh rabbit mortalities tie pythons to the precipitous decline of mammals in the Everglades

    Science.gov (United States)

    McCleery, Robert A.; Sovie, Adia; Reed, Robert N.; Cunningham, Mark W.; Hunter, Margaret E.; Hart, Kristen M.

    2015-01-01

    To address the ongoing debate over the impact of invasive species on native terrestrial wildlife, we conducted a large-scale experiment to test the hypothesis that invasive Burmese pythons (Python molurus bivittatus) were a cause of the precipitous decline of mammals in Everglades National Park (ENP). Evidence linking pythons to mammal declines has been indirect and there are reasons to question whether pythons, or any predator, could have caused the precipitous declines seen across a range of mammalian functional groups. Experimentally manipulating marsh rabbits, we found that pythons accounted for 77% of rabbit mortalities within 11 months of their translocation to ENP and that python predation appeared to preclude the persistence of rabbit populations in ENP. On control sites, outside of the park, no rabbits were killed by pythons and 71% of attributable marsh rabbit mortalities were classified as mammal predations. Burmese pythons pose a serious threat to the faunal communities and ecological functioning of the Greater Everglades Ecosystem, which will probably spread as python populations expand their range.

  10. Marsh rabbit mortalities tie pythons to the precipitous decline of mammals in the Everglades.

    Science.gov (United States)

    McCleery, Robert A; Sovie, Adia; Reed, Robert N; Cunningham, Mark W; Hunter, Margaret E; Hart, Kristen M

    2015-04-22

    To address the ongoing debate over the impact of invasive species on native terrestrial wildlife, we conducted a large-scale experiment to test the hypothesis that invasive Burmese pythons (Python molurus bivittatus) were a cause of the precipitous decline of mammals in Everglades National Park (ENP). Evidence linking pythons to mammal declines has been indirect and there are reasons to question whether pythons, or any predator, could have caused the precipitous declines seen across a range of mammalian functional groups. Experimentally manipulating marsh rabbits, we found that pythons accounted for 77% of rabbit mortalities within 11 months of their translocation to ENP and that python predation appeared to preclude the persistence of rabbit populations in ENP. On control sites, outside of the park, no rabbits were killed by pythons and 71% of attributable marsh rabbit mortalities were classified as mammal predations. Burmese pythons pose a serious threat to the faunal communities and ecological functioning of the Greater Everglades Ecosystem, which will probably spread as python populations expand their range. PMID:25788598

  11. 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.

  12. 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.

  13. Algorithmic synthesis using Python compiler

    Science.gov (United States)

    Cieszewski, Radoslaw; Romaniuk, Ryszard; Pozniak, Krzysztof; Linczuk, Maciej

    2015-09-01

    This paper presents a python to VHDL compiler. The compiler interprets an algorithmic description of a desired behavior written in Python and translate it to VHDL. FPGA combines many benefits of both software and ASIC implementations. Like software, the programmed circuit is flexible, and can be reconfigured over the lifetime of the system. FPGAs have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. This can be achieved by using many computational resources at the same time. Creating parallel programs implemented in FPGAs in pure HDL is difficult and time consuming. Using higher level of abstraction and High-Level Synthesis compiler implementation time can be reduced. The compiler has been implemented using the Python language. This article describes design, implementation and results of created tools.

  14. 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...

  15. 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

  16. 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.

  17. Pybus - A Python Software Bus

    International Nuclear Information System (INIS)

    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

  18. Pybus -- A Python Software Bus

    Energy Technology Data Exchange (ETDEWEB)

    Lavrijsen, Wim T.L.P.

    2004-10-14

    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.

  19. Advanced Python Scripting Using Sherpa

    Science.gov (United States)

    Refsdal, R.; Doe, S.; Nguyen, D.; Siemiginowska, A.; Burke, D.; Evans, J.; Evans, I.

    2011-07-01

    Sherpa is a general purpose modeling and fitting application written in Python. The dynamism of Python allows Sherpa to be a powerful and extensible software package ready for the modern challenges of data analysis. Primarily developed for the Chandra Interactive Analysis of Observations (CIAO) package, it provides a flexible environment for resolving spectral and image properties, analyzing time series, and modeling generic types of data. Complex model expressions are supported using Sherpa's general purpose definition syntax. Sherpa's parameterized data modeling is achieved using robust optimization methods implementing the forward fitting technique. Sherpa includes functions to calculate goodness-of-fit and parameter confidence limits. CPU intensive routines are written in C++/FORTRAN. But since all other data structures are contained in Python modules, users can easily add their own data structures, models, statistics or optimization methods to Sherpa. We will introduce a scripted example that highlights Sherpa's ability to estimate energy and photon flux errors using simulations. The draws from these simulations, accessible as NumPy ndarrays, can be sampled from uni-variate and multi-variate normal distributions and can be binned and visualized with simple high level functions. We will demonstrate how Sherpa can be extended with user-defined model and statistic classes written in Python. Sherpa's open design even allows users to incorporate prior statistics derived from the source model.

  20. 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

  1. 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...

  2. 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...

  3. Prototyping DSU techniques using Python

    OpenAIRE

    Martinez, Sébastien; DAGNAT, Fabien; Buisson, Jérémy

    2013-01-01

    International audience This paper presents PyMoult, a Python library implementing various dynamic software update (DSU) mechanisms. This library aims to provide a prototyping platform for experimenting with DSU and to implement a vast choice of update mechanisms while allowing their combination and customization. We selected different update mechanisms from the literature and implemented them in PyMoult.This paper focuses on how we implemented these mechanisms and discusses the cost of imp...

  4. Counting Word Frequencies with Python

    OpenAIRE

    William J. Turkel; Adam Crymble

    2012-01-01

    Your list is now clean enough that you can begin analyzing its contents in meaningful ways. Counting the frequency of specific words in the list can provide illustrative data. Python has an easy way to count frequencies, but it requires the use of a new type of variable: the dictionary. Before you begin working with a dictionary, consider the processes used to calculate frequencies in a list.

  5. Counting Word Frequencies with Python

    Directory of Open Access Journals (Sweden)

    William J. Turkel

    2012-07-01

    Full Text Available Your list is now clean enough that you can begin analyzing its contents in meaningful ways. Counting the frequency of specific words in the list can provide illustrative data. Python has an easy way to count frequencies, but it requires the use of a new type of variable: the dictionary. Before you begin working with a dictionary, consider the processes used to calculate frequencies in a list.

  6. Extending and embedding the Python interpreter

    OpenAIRE

    Rossum, van, M.A.J.

    1995-01-01

    Python 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 how to embed the Python interpreter in another application, for use as an extension language. Finally, it shows how to compile and link extension modules so that they can be loaded dynamically (at run time) into t...

  7. Implementing Python for DrRacket

    OpenAIRE

    Ramos, Pedro Palma; Leitão, António Menezes

    2014-01-01

    The Python programming language is becoming increasingly popular in a variety of areas, most notably among novice programmers. On the other hand, Racket and other Scheme dialects are considered excellent vehicles for introducing Computer Science concepts. This paper presents an implementation of Python for Racket and the DrRacket IDE. This allows Python programmers to use Racket libraries and vice versa, as well as using DrRacket's pedagogic features. In particular, it allows architects and d...

  8. 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.

  9. 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.

  10. How fast can we make interpreted Python?

    OpenAIRE

    Power, Russell; Rubinsteyn, Alex

    2013-01-01

    Python is a popular dynamic language with a large part of its appeal coming from powerful libraries and extension modules. These augment the language and make it a productive environment for a wide variety of tasks, ranging from web development (Django) to numerical analysis (NumPy). Unfortunately, Python's performance is quite poor when compared to modern implementations of languages such as Lua and JavaScript. Why does Python lag so far behind these other languages? As we show, the very sam...

  11. 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.

  12. 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

  13. Enhanced OpenModelica Python Interface

    OpenAIRE

    Bajracharya, Sudeep

    2016-01-01

    OMPython is a Python library for OpenModelica, which provides a Python interface to OpenModelica. This thesis significantly improves OMPython by an enhanced, more powerful and easier to use API. It presents how a user can use the Python interface to simulate and access Modelica models using Python objects. The enhanced OMPython includes the list of functions that have been implemented such as getXXXNames(), getXXXValues(), setXXXValues(), getXXXOptions(), setXXXOptions(), and simulate(), etc....

  14. Internationalization and Localization in Python

    CERN Document Server

    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.

  15. [Lecture Games] Python programming game

    OpenAIRE

    Johnsen, Andreas Lyngstad; Ushakov, Georgy

    2011-01-01

    Pythia is a programming game that allows the player to change pieces of theirenvironment through use of the programming language Python. The idea is that thegame could be used as a part of teaching simple programming to first year universitystudents. The game should be fun enough for the students to keep playing, teachenough for it to earn a place as a teaching tool, and it should be usable by allstudents. It should also be possible for a teacher to create their own content for theg...

  16. 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

  17. 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.

  18. 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.

  19. Extending and embedding the Python interpreter

    NARCIS (Netherlands)

    Rossum, G. van

    1995-01-01

    Python 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 how to embed

  20. 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. PMID:24970309

  1. Reflection-Based Python-C++ Bindings

    International Nuclear Information System (INIS)

    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

  2. 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...

  3. Test-beam with Python

    CERN Document Server

    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.

  4. The phenotypic flexibility of the visceral organs of pythons during digestion revealed by modern imaging techniques

    DEFF Research Database (Denmark)

    Hansen, Kasper; Lauridsen, Henrik; Nielsen, Tobias Wang; Pedersen, Michael

    Pythons, renowned for their abilities to fast for manybmonths and ingest very large meals, exhibit extreme physiological adaptations to their “sit-and-wait predator” lifestyle. In particular, the size and function of their visceral organs are rapidly up- and downregulated during the transitions...... visceral organs and intestines. Fasting Burmese pythons (Python molurus) were scanned before and at 2, 16, 24, 40, 48, 72 and 132 hours after ingestion of one rat. Acquired images revealed a gradual disappearance of the meal accompanied by an overall expansion of the intestine, shrinking of the gallbladder......, and a 30% increase in heart volume. These immediate responses following ingestion are consistent with previous invasive studies of pythons. In conclusion, our study showed that MRI and CT are capable to repeatedly and non-invasively image the phenotypic flexibility of internal organs in vertebrates....

  5. 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

  6. 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.

  7. Pyception : Teaching Python with a Serious Game

    OpenAIRE

    Laskemoen, Kristian

    2013-01-01

    This thesis set out to study how an online serious game could affect users? motivation on learning Python. One of the projects core goals is to find out whether learning Python is more motivating when having an effortless start through a web based game. A second goal is to find out if Python as a programming language are well suited for a serious game.After the development and implementation of the game, it was performed a user experiment in order to receive feedback. Data from this user expe...

  8. Python GUI Scripting Interface for Running Atomic Physics Applications

    OpenAIRE

    Tahat, Amani; Tahat, Mofleh

    2011-01-01

    We create a Python GUI scripting interface working under Windows in addition to (UNIX/Linux). The GUI has been built around the Python open-source programming language. We use the Python's GUI library that so called Python Mega Widgets (PMW) and based on Tkinter Python module (http://www.freenetpages.co.uk/hp/alan.gauld/tutgui.htm). The new GUI was motivated primarily by the desire of more updated operations, more flexibility incorporating future and current improvements in producing atomic d...

  9. Claims of potential expansion throughout the U.S. by invasive python species are contradicted by ecological niche models.

    Directory of Open Access Journals (Sweden)

    R Alexander Pyron

    Full Text Available BACKGROUND: Recent reports from the United States Geological Survey (USGS suggested that invasive Burmese pythons in the Everglades may quickly spread into many parts of the U.S. due to putative climatic suitability. Additionally, projected trends of global warming were predicted to significantly increase suitable habitat and promote range expansion by these snakes. However, the ecological limitations of the Burmese python are not known and the possible effects of global warming on the potential expansion of the species are also unclear. METHODOLOGY/PRINCIPAL FINDINGS: Here we show that a predicted continental expansion is unlikely based on the ecology of the organism and the climate of the U.S. Our ecological niche models, which include variables representing climatic extremes as well as averages, indicate that the only suitable habitat in the U.S. for Burmese pythons presently occurs in southern Florida and in extreme southern Texas. Models based on the current distribution of the snake predict suitable habitat in essentially the only region in which the snakes are found in the U.S. Future climate models based on global warming forecasts actually indicate a significant contraction in suitable habitat for Burmese pythons in the U.S. as well as in their native range. CONCLUSIONS/SIGNIFICANCE: The Burmese python is strongly limited to the small area of suitable environmental conditions in the United States it currently inhabits due to the ecological niche preferences of the snake. The ability of the Burmese python to expand further into the U.S. is severely limited by ecological constraints. Global warming is predicted to significantly reduce the area of suitable habitat worldwide, underscoring the potential negative effects of climate change for many species.

  10. 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...

  11. Visualization of the CMS python configuration system

    International Nuclear Information System (INIS)

    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.

  12. Teaching programming in Python in primary school

    OpenAIRE

    Prevc, Darja

    2015-01-01

    In this thesis, we present a set of lesson plans with tasks for teaching pupils how to program in Python using the turtle module. The first part discusses the problem of programming in primary schools: we note that programming presents only a small and optional fraction of the elective class about computing. Next we present programming language Python along with characteristics that make it suitable for teaching. We describe its installation and the development environment IDLE. Presentat...

  13. PYTHON IMPLEMENTATION OF VISUAL SECRET SHARING SCHEMES

    OpenAIRE

    Ruxandra Olimid

    2011-01-01

    Visual secret sharing schemes (VSS) represent an important concept of visual cryptography. They permit the sharing of a secret image between multiple participants so that only authorized groups can recover the secret. This paper considers the software implementation of some black-and-white secret images VSS in Python programming language. PIL (Python Imaging Library) provides strong image processing capabilities, making the library suitable for this kind of implementation. We present samples ...

  14. 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.

  15. 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.

  16. 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

  17. Identification and characterization of two closely related unclassifiable endogenous retroviruses in pythons (Python molurus and Python curtus).

    Science.gov (United States)

    Huder, Jon B; Böni, Jürg; Hatt, Jean-Michel; Soldati, Guido; Lutz, Hans; Schüpbach, Jörg

    2002-08-01

    Boid inclusion body disease (BIBD) is a fatal disorder of boid snakes that is suspected to be caused by a retrovirus. In order to identify this agent, leukocyte cultures (established from Python molurus specimens with symptoms of BIBD or kept together with such diseased animals) were assessed for reverse transcriptase (RT) activity. Virus from cultures exhibiting high RT activity was banded on sucrose density gradients, and the RT peak fraction was subjected to highly efficient procedures for the identification of unknown particle-associated retroviral RNA. A 7-kb full retroviral sequence was identified, cloned, and sequenced. This virus contained intact open reading frames (ORFs) for gag, pro, pol, and env, as well as another ORF of unknown function within pol. Phylogenetic analysis showed that the virus is distantly related to viruses from both the B and D types and the mammalian C type but cannot be classified. It is present as a highly expressed endogenous retrovirus in all P. molurus individuals; a closely related, but much less expressed virus was found in all tested Python curtus individuals. All other boid snakes tested, including Python regius, Python reticulatus, Boa constrictor, Eunectes notaeus, and Morelia spilota, were virus negative, independent of whether they had BIBD or not. Virus isolated from P. molurus could not be transmitted to the peripheral blood mononuclear cells of B. constrictor or P. regius. Thus, there is no indication that this novel virus, which we propose to name python endogenous retrovirus (PyERV), is causally linked with BIBD. PMID:12097574

  18. 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.

  19. 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.

  20. 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(?).

  1. Data Visualization within the Python ecosystem

    CERN Document Server

    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.

  2. 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 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 mathematical expressions as directed graphs. The latest version is available at http...

  3. A 3d game in python

    OpenAIRE

    Xu, Minghui

    2014-01-01

    3D game has widely been accepted and loved by many game players. More and more different kinds of 3D games were developed to feed people’s needs. The most common programming language for development of 3D game is C++ nowadays. Python is a high-level scripting language. It is simple and clear. The concise syntax could speed up the development cycle. This project was to develop a 3D game using only Python. The game is about how a cat lives in the street. In order to live, the player need...

  4. 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

  5. Python Ephemeris Module for Radio Astronomy

    Science.gov (United States)

    Kuiper, T. B.

    2013-05-01

    An extension of the Python pyephem module was developed for Deep Space Network (DSN) radio astronomy. The class DSS( ) provides the geodetic coordinates of the DSN stations as well as other properties such as antenna diameter. The class Quasar( ) provides positional data for the sources in the National Radio Astronomy Observatory Very Large Array (NRAO VLA) Calibrator Handbook and flux estimates based the University of Michigan Radio Astronomy Observatory (UMRAO) Database or the VLA Calibrator Handbook. Flux calibration data are also available for the bright planets. Class Pulsar( ) provides the data from the Australia Telescope National Facility (ATNF) Pulsar Catalogue in Python format.

  6. 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

  7. 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

  8. 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

  9. APLpy: Astronomical Plotting Library in Python

    Science.gov (United States)

    Robitaille, Thomas; Bressert, Eli

    2012-08-01

    APLpy (the Astronomical Plotting Library in Python) is a Python module for producing publication-quality plots of astronomical imaging data in FITS format. The module uses Matplotlib, a powerful and interactive plotting package. It is capable of creating output files in several graphical formats, including EPS, PDF, PS, PNG, and SVG. Plots can be made interactively or by using scripts, and can generate co-aligned FITS cubes to make three-color RGB images. It also offers different overlay capabilities, including contour sets, markers with customizable symbols, and coordinate grids, and a range of other useful features.

  10. 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

  11. QGen : A Python to Qt/C++ translator

    OpenAIRE

    2004-01-01

    The thesis covers translating Python code to C++ using Qt as graphics library. The code should be able to be compiled to run on a Sharp Zaurus PDA. Some of the differences between Python and C++ is discussed as well as the techniques used to translate between the languages. The application itself is written in Python.

  12. Python bindings for the open source electromagnetic simulator Meep

    OpenAIRE

    Lambert, Emmanuel; Fiers, Martin; Nizamov, Shavkat; Tassaert, Martijn; Johnson, Steven G.; Bienstman, Peter; Bogaerts, Wim

    2011-01-01

    Meep is a broadly used open source package for finite-difference time-domain electromagnetic simulations. Python bindings for Meep make it easier to use for researchers and open promising opportunities for integration with other packages in the Python ecosystem. As this project shows, implementing Python-Meep offers benefits for specific disciplines and for the wider research community.

  13. The Zoonotic Implications of Pentastomiasis in the Royal Python (Python Regius)

    OpenAIRE

    Ayinmode, AB; Adedokun, AO; Aina, A; Taiwo, V

    2010-01-01

    Pentastomes are worm-like endoparasites of the phylum Pentastomida found principally in the respiratory tract of reptiles, birds, and mammals. They cause a zoonotic disease known as pentastomiasis in humans and other mammals. The autopsy of a Nigerian royal python (Python regius) revealed two yellowish-white parasites in the lungs, tissue necrosis and inflammatory lesions. The parasite was confirmed to be Armillifer spp (Pentastomid); this is the first recorded case of pentastomiasis in the r...

  14. Bactome, I: Python in DNA Fingerprinting

    Directory of Open Access Journals (Sweden)

    2010-09-01

    Full Text Available Bactome is a collection of Python functions to find primers suitable for DNA fingerprinting, determine restriction digestion profile, and analyse the resulting DNA fingerprint features as migration distance of the bands in gel electrophoresis. An actual use case will be presented as a case study. These codes are licensed under Lesser General Public Licence version 3.

  15. 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.

  16. 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.

  17. Python Classes for Numerical Solution of PDE's

    OpenAIRE

    Asif Mushtaq; Trond Kvamsdal; Kare Olaussen

    2015-01-01

    We announce some Python classes for numerical solution of partial differential equations, or boundary value problems of ordinary differential equations. These classes are built on routines in \\texttt{numpy} and \\texttt{scipy.sparse.linalg} (or \\texttt{scipy.linalg} for smaller problems).

  18. 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.

  19. Python code parallelization for ALMA, challenges and alternatives

    OpenAIRE

    Gonzalez, Justo; Taylor, Julian; Castro, Sandra; Kern, Jeff; Knudstrup, Jens; Zampieri, Stefano; Manning, Alisdair

    2015-01-01

    In the last few years development of Python code for science and data reduction purposes has gained significant popularity. ESO in itself uses a Python-based archiving  system for VLT and ALMA data. Also the data reduction suite for ALMA data is python-based. Rapid development is fostered by a big community and a wide range of already available packages. However Python enforces locking mechanisms, to ensure thread safety, that effectively reduce the capacity of Python to use only one cor...

  20. Kompilering av mindre Python-moduler til C++

    OpenAIRE

    2007-01-01

    In order to achieve shorter execution times of Python code, I look at means of compiling Python into C++. To perform this task, I have written a Python compiler, and this compiler generates C++ code from a subset of the Python language. Code generated from this code can in some cases expect to run in about 1/100 of the time used by ordinary Python. I will look at the principles behind this compiler, and look at its (quite readable) generated code. Off the form of this gene...

  1. 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. J. Exp. Zool. 9999A:XX-XX, 2016. © 2016 Wiley Periodicals, Inc. PMID:26847931

  2. Identification and Characterization of Two Closely Related Unclassifiable Endogenous Retroviruses in Pythons (Python molurus and Python curtus)

    OpenAIRE

    Huder, J B; Böni, J; Hatt, Jean-Michel; Soldati, G; Lutz, Hans; Schüpbach, Jörg

    2002-01-01

    Boid inclusion body disease (BIBD) is a fatal disorder of boid snakes that is suspected to be caused by a retrovirus. In order to identify this agent, leukocyte cultures (established from Python molurus specimens with symptoms of BIBD or kept together with such diseased animals) were assessed for reverse transcriptase (RT) activity. Virus from cultures exhibiting high RT activity was banded on sucrose density gradients, and the RT peak fraction was subjected to highly efficient procedures for...

  3. 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. PMID:19473273

  4. The spectacle of the ball python

    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...... 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...

  5. galpy: A Python Library for Galactic Dynamics

    CERN Document Server

    Bovy, Jo

    2014-01-01

    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...

  6. 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.

  7. ParselTongue: AIPS Talking Python

    Science.gov (United States)

    Kettenis, M.; van Langevelde, H. J.; Reynolds, C.; Cotton, B.

    2006-07-01

    After more than 20 years of service, classic AIPS still is the data reduction package of choice for many radio-interferometry projects, especially for VLBI. Its age shows, most prominently in the limited scripting capabilities of its user interface: POPS. ParselTongue is an attempt to make the trusted AIPS algorithms and AIPS data structures available in a modern dynamic programming language: Python. It also provides an environment to do distributed computing to take advantage of modern computing clusters. This makes it suitable for use as a scripting interface for doing complicated data reduction on large data sets. It is also used as a coding platform for the new calibration algorithms that are being developed for the European VLBI Network as part of the ALBUS project. Here we hope to take advantage of Python's extensive support for web-based technologies to automate things like collecting calibration data.

  8. Simulation of Planetary Formation using Python

    Science.gov (United States)

    Bufkin, James; Bixler, David

    2015-03-01

    A program to simulate planetary formation was developed in the Python programming language. The program consists of randomly placed and massed bodies surrounding a central massive object in order to approximate a protoplanetary disk. The orbits of these bodies are time-stepped, with accelerations, velocities and new positions calculated in each step. Bodies are allowed to merge if their disks intersect. Numerous parameters (orbital distance, masses, number of particles, etc.) were varied in order to optimize the program. The program uses an iterative difference equation approach to solve the equations of motion using a kinematic model. Conservation of energy and angular momentum are not specifically forced, but conservation of momentum is forced during the merging of bodies. The initial program was created in Visual Python (VPython) but the current intention is to allow for higher particle count and faster processing by utilizing PyOpenCl and PyOpenGl. Current results and progress will be reported.

  9. matplotlib -- A Portable Python Plotting Package

    Science.gov (United States)

    Barrett, P.; Hunter, J.; Miller, J. T.; Hsu, J.-C.; Greenfield, P.

    2005-12-01

    matplotlib is a portable 2D plotting and imaging package aimed primarily at visualization of scientific, engineering, and financial data. matplotlib can be used interactively from the Python shell, called from python scripts, or embedded in a GUI application (GTK, Wx, Tk, Windows). Many popular hardcopy outputs are supported including JPEG, PNG, PostScript and SVG. Features include the creation of multiple axes and figures per page, interactive navigation, many predefined line styles and symbols, images, antialiasing, alpha blending, date and financial plots, W3C compliant font management and FreeType2 support, legends and tables, pseudocolor plots, mathematical text and more. It works with both numarray and Numeric. The goals of the package, basic architecture, current features (illustrated with examples), and planned enhancements will be described.

  10. Efficient Natural Language Processing with Python

    OpenAIRE

    Martinc, Matej

    2015-01-01

    The thesis deals with a comparison of different tools and libraries for natural language processing in Python programming language. In addition to the most popular library for natural language processing NLTK we thoroughly researched other less known libraries, such as SpaCy, pyNLPl, Pattern and Textblob, and made comparisons between them based on different criteria and practical assignments, such as tokenization, lemmatization, stemming, part of speech tagging, dependency tree building, sear...

  11. Python Scripting in the Nengo Simulator

    OpenAIRE

    Terrence C Stewart; Tripp, Bryan; Eliasmith, Chris

    2009-01-01

    Nengo (http://nengo.ca) 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 mo...

  12. Python scripting in the Nengo simulator

    OpenAIRE

    Terrence C Stewart; Bryan Tripp; Chris Eliasmith

    2009-01-01

    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, ...

  13. Implementation of Kalman Filter with Python Language

    CERN Document Server

    Laaraiedh, Mohamed

    2012-01-01

    In this paper, we investigate the implementation of a Python code for a Kalman Filter using the Numpy package. A Kalman Filtering is carried out in two steps: Prediction and Update. Each step is investigated and coded as a function with matrix input and output. These different functions are explained and an example of a Kalman Filter application for the localization of mobile in wireless networks is given.

  14. 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.

  15. 升级Ubuntu中的Python

    Institute of Scientific and Technical Information of China (English)

    李世川

    2011-01-01

    导读 Python作为当前流行的脚本语言,具有很广的应用范围。Ubuntu系统自带了Python,笔者将Ubuntu 10.10自带的Python2.6.6升级至3.2版本。本文介绍升级过程及后续问题的解决方法。

  16. POPPY: Physical Optics Propagation in PYthon

    Science.gov (United States)

    Perrin, Marshall; Long, Joseph; Douglas, Ewan; Sivaramakrishnan, Anand; Slocum, Christine

    2016-02-01

    POPPY (Physical Optics Propagation in PYthon) simulates physical optical propagation including diffraction. It implements a flexible framework for modeling Fraunhofer and Fresnel diffraction and point spread function formation, particularly in the context of astronomical telescopes. POPPY provides the optical modeling framework for WebbPSF (ascl:1504.007) and was developed as part of a simulation package for JWST, but is available separately and is broadly applicable to many kinds of imaging simulations.

  17. 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).

  18. Python for Large-Scale Electrophysiology

    OpenAIRE

    Spacek, Martin A.; Tim Blanche

    2009-01-01

    Electrophysiology is increasingly moving towards highly parallel recording techniques which generate large data sets. We record extracellularly in vivo in cat and rat visual cortex with 54-channel silicon polytrodes, under time-locked visual stimulation, from localized neuronal populations within a cortical column. To help deal with the complexity of generating and analysing these data, we used the Python programming language to develop three software projects: one for temporally precise visu...

  19. Implementation of Kalman Filter with Python Language

    OpenAIRE

    Laaraiedh, Mohamed

    2009-01-01

    International audience In this paper, we investigate the implementation of a Python code for a Kalman Filter using the Numpy package. A Kalman Filtering is carried out in two steps: Prediction and Update. Each step is investigated and coded as a function with matrix input and output. These different functions are explained and an example of a Kalman Filter application for the localization of mobile in wireless networks is given.

  20. SunPy - Python for Solar Physics

    CERN Document Server

    Community, The SunPy; 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 visualisation and plotting (matplotlib). SunPy is a data-analysis environment specialising 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 mis...

  1. The Virtual Observatory for the Python Programmer

    Science.gov (United States)

    Plante, Raymond L.; Fitzpatrick, M. J.; Graham, M.; Tody, D.; Virtual Astronomical Observatory, US

    2014-01-01

    The web of astronomical data centers that we refer to as the virtual observatory (VO) has led to the development of a variety of web and desktop applications that can discover and download data from most archives around the world. These are made possible by standard interfaces which archives provide and the applications understand that provide a common way to search for information and retrieve discovered datasets. For some applications, retrieving data through the VO is simply an extra feature that enhances the main purpose of the tool. Despite the accessibility to VO data provided by such tools, the VO offers greater flexibility to developers that access the standard services directly within their own software. This applies not only to those who build tools but also to research astronomers that create highly-customized scripts for data analysis. One of the goals of the US Virtual Astronomical Observatory (VAO) project is to make the VO more accessible to both tool developers and astronomer-programmers. To this end, we announce the release of two products with a special focus on supporting access to the VO via Python. PyVO (http://dev.usvao.org/pyvo) is a pure Python library built on Astropy (astropy.org) that can be used to discover data in the VO. In particular, one can search the registry for archives with data, search archives for images and spectra, and query remote catalogs and spectral line databases. While it provides full support for the VO standards, its API is designed to make processing the most common types of queries simple without requiring knowledge about the underlying standards. It also makes available the full power of Astropy for processing tabular information. VOClient (http://dev.usvao.org/voclient), which provides scripting and programming libraries for a variety of languages, also supports Python programming. While the two products share a common API, VOClient provides higher level interfaces that assist with managing data from many

  2. Python for Grid-, Cloud-, and High-Performance-Computing

    OpenAIRE

    Schreiber, Andreas

    2012-01-01

    Python is an accepted high-level scripting language with a growing community in academia and industry. It is used in many scientific applications in many different scientific fields and in more and more industries (for example, in engineering or life science). In all fields, the use of Python for high-performance and parallel computing is increasing. Several organizations and companies are providing tools or support for Python development. This includes libraries for scientific computing, par...

  3. PyMOOSE: Interoperable Scripting in Python for MOOSE

    OpenAIRE

    Subhasis Ray; Bhalla, Upinder S

    2008-01-01

    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 ...

  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. Interactive game programming with Python (CodeSkulptor)

    OpenAIRE

    Ajayi, Richard Olugbenga

    2014-01-01

    Over the years, several types of gaming platforms have been created to encourage a more organised and friendly atmosphere for game lovers in various works of life, culture, and environment. This thesis focuses on the concept of interactive programming using Python. It encourages the use of Python to create simple interactive games applications based on basic human concept and ideas. CodeSkulptor is a browser-based IDE programming environment and uses the Python programming language. O...

  6. A Scalable Interactive Parallel Computing Environment for Python

    OpenAIRE

    Sudarshan Raghunathan

    2012-01-01

    Modern open source high-level languages such as R and Python are.increasingly playing an important role in increasing programmer productivity when programming high-performance computers. In this article, we describe Python Star-P, a high-level interactive parallel programming environment in Python. We discuss the architecture of the environment and the programming model along with a number of examples. We also describe the performance of the examples on .a cluster of multi-core machines. Fina...

  7. Problem Solving Environment for Partial Differential Equations in Python

    OpenAIRE

    2009-01-01

    This master thesis presents a collection of tools for solving partial differential equations using Python. Three different Python modules make up the majority of the thesis. When solving partial differential equations using the finite difference method, the resulting code can get quite complicated, for instance when trying to solve a 3D wave equation with a variable diffusion coefficient. Fdmgen is a Python module that helps solving such equations by generating the code ...

  8. A comparison of existing Python modules of MPI

    OpenAIRE

    2010-01-01

    The Python programming language has gradually gained popularity in the field of scientific computing. Nowadays, Python is considered to be a great programming language for scientific computing and has attracted significant interest among computational scientists. It has shown the advantage of scripting language for scientific programming and moreover for parallel programming. In connection with parallel computing, Python has been used to simplify, in particular, message-passing based paralle...

  9. Solve the Master Equation by Python-An Introduction to the Python Computing Environment

    OpenAIRE

    Fan, Wei; Xu, Yan; Chen, Bing; Ye, Qianqian

    2011-01-01

    A brief introduction to the Python computing environment is given. By solving the master equation encountered in quantum transport, we give an example of how to solve the ODE problems in Python. The ODE solvers used are the ZVODE routine in Scipy and the bsimp solver in GSL. For the former, the equation can be in its complex-valued form, while for the latter, it has to be rewritten to a real-valued form. The focus is on the detailed workflow of the implementation process, rather than on the s...

  10. 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

  11. 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

  12. 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.

  13. Procjena složenosti programa u Python jeziku

    OpenAIRE

    Misra, Sanjay; Cafer, Ferid

    2011-01-01

    U ovom radu formulirana je metrička složenost za jezik Python. Budući je Python objektno orijentiran jezik, postojeća metričnost je u stanju procijeniti bilo koji objektno usmjeren jezik. Potvrđujemo našu metričnost studijom slučaja, usporednom studijom i empirijskom provjerom valjanosti. Studija slučaja je u Python, Java i C ++ jeziku, a rezultati pokazuju da je Python bolji od ostalih objektno orijentiranih jezika. Kasnije smo provjerili metričnost empirijski sa stvarnim projektom, koji je ...

  14. Ureka: A Distribution of Python and IRAF Software for Astronomy

    Science.gov (United States)

    Hirst, P.; Slocum, C.; Turner, J.; Sienkiewicz, M.; Greenfield, P.; Hogan, E.; Simpson, M.; Labrie, K.

    2014-05-01

    As astronomical data processing expands from our historical platforms into modern Python applications, users are faced with installing and maintaining large numbers of heterogeneous dependencies. A handful of scientific Python distributions make installing key packages easy, but don't cater for specific needs such as integration with IRAF. We have therefore recently released a beta version of a new astronomical software distribution for Linux and OSX, known as Ureka. Ureka is based around STScI Python and dependencies, notably Python, NumPy, IRAF, SciPy, AstroPy, Matplotlib and Tk. It also contains data reduction packages for Gemini, HST, JWST and other observatories, alongside various complementary tools.

  15. A postmortem experience of Indian rock python (Python molurus molurus that swallowed a whole barking deer

    Directory of Open Access Journals (Sweden)

    Amam Zonaed Siddiki

    2013-06-01

    Full Text Available The object of this study was to report a post mortem findings of a female Indian Rock Python with a length of 406 cm (13.32 feet and approximate weight of 60 kg (including a whole deer that was swallowed by the python, that was brought to the Teaching Veterinary Hospital, Chittagong Veterinary and Animal Sciences University (CVASU by the Forest Department of Kumira Range Office, Chittagong. The local inhabitants accidently found the python at the forest area of Kumira and they frightenedly injured and killed the snake eventually. The postmortem (PM examination was performed according to standard protocols. Gross examination revealed bloody discharge was come out through mouth and a couple of skin lacerations observed on the right dorso-lateral part of the abdominal region. The whole barrel-shaped body cavity was opened and whole deer (partially decomposed was recovered from the stomach. Furthermore, three fractured ribs were found on right thorax. The PM examination team believes that the possible cause of python death was traumatic injury inflicted by the local people. [Vet World 2013; 6(3.000: 163-165

  16. Rapid web development using AJAX and Python

    International Nuclear Information System (INIS)

    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

  17. TRIPPy: Python-based Trailed Source Photometry

    Science.gov (United States)

    Fraser, Wesley C.; Alexandersen, Mike; Schwamb, Megan E.; Marsset, Michael E.; Pike, Rosemary E.; Kavelaars, JJ; Bannister, Michele T.; Benecchi, Susan; Delsanti, Audrey

    2016-05-01

    TRIPPy (TRailed Image Photometry in Python) uses a pill-shaped aperture, a rectangle described by three parameters (trail length, angle, and radius) to improve photometry of moving sources over that done with circular apertures. It can generate accurate model and trailed point-spread functions from stationary background sources in sidereally tracked images. Appropriate aperture correction provides accurate, unbiased flux measurement. TRIPPy requires numpy, scipy, matplotlib, Astropy (ascl:1304.002), and stsci.numdisplay; emcee (ascl:1303.002) and SExtractor (ascl:1010.064) are optional.

  18. 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

  19. 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.

  20. 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. PMID:25024921

  1. Scikit-learn: Machine Learning in Python

    CERN Document Server

    Pedregosa, Fabian; 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; Duchesnay, Édouard

    2012-01-01

    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 and commercial settings. Source code, binaries, and documentation can be downloaded from http://scikit-learn.sourceforge.net.

  2. PYTHON-based Physics Analysis Environment for LHCb

    CERN Document Server

    Belyaev, I; Mato, P; Barrand, G; Tsaregorodtsev, A; 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.

  3. 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...

  4. pcigale: porting Code Investigating Galaxy Emission to Python

    CERN Document Server

    Roehlly, Yannick; Buat, Véronique; Boquien, Médéric; Ciesla, Laure; Heinis, Sébastien

    2013-01-01

    We present pcigale, the port to Python of CIGALE (Code Investigating Galaxy Emission) a Fortran spectral energy distribution (SED) fitting code developed at the Laboratoire d'Astrophysique de Marseille. After recalling the specifics of the SED fitting method, we show the gains in modularity and versatility offered by Python, as well as the drawbacks compared to the compiled code.

  5. 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

  6. MEG and EEG data analysis with MNE-Python

    Directory of Open Access Journals (Sweden)

    Alexandre eGramfort

    2013-12-01

    Full Text Available Magnetoencephalography and electroencephalography (M/EEG measure the weakelectromagnetic signals generated by neuronal activity in the brain. Using thesesignals to characterize and locate neural activation in the brain is achallenge that requires expertise in physics, signalprocessing, statistics, and numerical methods. As part of the MNE softwaresuite, MNE-Python is an open-sourcesoftware package that addresses this challenge by providingstate-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation offunctional 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 analysispipelines by writing Python scripts.Moreover, MNE-Python is tightly integrated with the core Python libraries for scientificcomptutation (Numpy, Scipy and visualization (matplotlib and Mayavi, as wellas the greater neuroimaging ecosystem in Python via the Nibabel package. The code is provided under the new BSD licenseallowing code reuse, even in commercial products. Although MNE-Python has onlybeen under heavy development for a couple of years, it has rapidly evolved withexpanded 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 ofmethods by other researchers. Full documentation, including dozens ofexamples, is available at http://martinos.org/mne.

  7. 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...

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

    International Nuclear Information System (INIS)

    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

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. 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. PMID:26910233

  14. Python3 Programming Environment Based on Web%基于Web的Python3编程环境

    Institute of Scientific and Technical Information of China (English)

    刘志凯; 张太红; 刘磊; 罗鹏

    2015-01-01

    为了简化编程环境,增强编程体验,提出了一种基于web的python3编程环境。该应用的web环境采用基于python 的 Django框架,通过将 python3代码转换成浏览器可执行的JavaScript 脚本,达到在浏览器中运行python3代码的目的。与传统的python3编程环境相比,该编程环境不用在本地安装部署任何开发环境,即可实现远程编程和代码共享。实验结果表明,该编程环境可行性强,具有良好的稳定性和并发性。%In order to simplify the programming environment, and enhance programming experience, we propose a web-based python3 programming environment. The web environment of this application uses python-based Django framework. This application can achieve the purpose of running python3 code in the browser by convering the python3 code into browser executable JavaScript script. Compared with traditional python3 programming environment, this programming environment can achieve remote programming and code sharing without installing and deploying any development environment locally. Experimental results shows that our programming environment has strong feasibility, good stability and good concurrency.

  15. 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.

  16. DMTCP: bringing interactive checkpoint-restart to Python

    Science.gov (United States)

    Arya, Kapil; Cooperman, Gene

    2015-01-01

    DMTCP (Distributed MultiThreaded CheckPointing) is a mature checkpoint-restart package. It operates in user space without kernel privilege, and adapts to application-specific requirements through plugins. While DMTCP has been able to checkpoint Python and IPython ‘from the outside’ for many years, a Python module has recently been created to support DMTCP. IPython support is included through a new DMTCP plugin. A checkpoint can be requested interactively within a Python session or under the control of a specific Python program. Further, the Python program can execute specific Python code prior to checkpoint, upon resuming (within the original process) and upon restarting (from a checkpoint image). Applications of DMTCP are demonstrated for: (i) Python-based graphics using virtual network client, (ii) a fast/slow technique to use multiple hosts or cores to check one (Cython Behnel S et al 2011 Comput. Sci. Eng. 13 31-39) computation in parallel, and (iii) a reversible debugger, FReD, with a novel reverse-expression watchpoint feature for locating the cause of a bug.

  17. 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.

  18. Simulating X-ray Observations with Python

    CERN Document Server

    ZuHone, John A; Hallman, Eric J; Randall, Scott W; Foster, Adam R; Schmid, Christian

    2014-01-01

    X-ray astronomy is an important tool in the astrophysicist's toolkit to investigate high-energy astrophysical phenomena. Theoretical numerical simulations of astrophysical sources are fully three-dimensional representations of physical quantities such as density, temperature, and pressure, whereas astronomical observations are two-dimensional projections of the emission generated via mechanisms dependent on these quantities. To bridge the gap between simulations and observations, algorithms for generating synthetic observations of simulated data have been developed. We present an implementation of such an algorithm in the yt analysis software package. We describe the underlying model for generating the X-ray photons, the important role that yt and other Python packages play in its implementation, and present a detailed workable example of the creation of simulated X-ray observations.

  19. 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. ...

  20. ScrumPy: metabolic modelling with Python.

    Science.gov (United States)

    Poolman, M G

    2006-09-01

    ScrumPy is a software package used for the definition and analysis of metabolic models. It is written using the Python programming language that is also used as a user interface. ScrumPy has features for both kinetic and structural modelling, but the emphasis is on structural modelling and those features of most relevance to analysis of large (genome-scale) models. The aim is at describing ScrumPy's functionality to readers with some knowledge of metabolic modelling, but implementation, programming and other computational details are omitted. ScrumPy is released under the Gnu Public Licence, and available for download from http://mudshark.brookes.ac.uk/ ScrumPy. PMID:16986321

  1. Astropy: A Community Python Package for Astronomy

    CERN Document Server

    Robitaille, Thomas P; Greenfield, Perry; Droettboom, Michael; Bray, Erik; Aldcroft, Tom; Davis, Matt; Ginsburg, Adam; Price-Whelan, Adrian M; Kerzendorf, Wolfgang E; Conley, Alexander; Crighton, Neil; Barbary, Kyle; Muna, Demitri; Ferguson, Henry; Grollier, Frédéric; Parikh, Madhura M; Nair, Prasanth H; Günther, Hans M; Deil, Christoph; Woillez, Julien; Conseil, Simon; Kramer, Roban; Turner, James E H; Singer, Leo; Fox, Ryan; Weaver, Benjamin A; Zabalza, Victor; Edwards, Zachary I; Bostroem, K Azalee; Burke, D J; Casey, Andrew R; Crawford, Steven M; Dencheva, Nadia; Ely, Justin; Jenness, Tim; Labrie, Kathleen; Lim, Pey Lian; Pierfederici, Francesco; Pontzen, Andrew; Ptak, Andy; Refsdal, Brian; Servillat, Mathieu; Streicher, Ole

    2013-01-01

    We present the first public version (v0.2) of the open-source and community-developed Python package, Astropy. This package provides core astronomy-related functionality to the community, including support for domain-specific file formats such as Flexible Image Transport System (FITS) files, Virtual Observatory (VO) tables, and common ASCII table formats, unit and physical quantity conversions, physical constants specific to astronomy, celestial coordinate and time transformations, world coordinate system (WCS) support, generalized containers for representing gridded as well as tabular data, and a framework for cosmological transformations and conversions. Significant functionality is under active development, such as a model fitting framework, VO client and server tools, and aperture and point spread function (PSF) photometry tools. The core development team is actively making additions and enhancements to the current code base, and we encourage anyone interested to participate in the development of future A...

  2. 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. ...

  3. galpy: A python LIBRARY FOR GALACTIC DYNAMICS

    International Nuclear Information System (INIS)

    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

  4. Neutron Scattering Experiment Automation with Python

    International Nuclear Information System (INIS)

    The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory currently holds the Guinness World Record as the world most powerful pulsed spallation neutron source. Neutrons scattered off atomic nuclei in a sample yield important information about the position, motions, and magnetic properties of atoms in materials. A neutron scattering experiment usually involves sample environment control (temperature, pressure, etc.), mechanical alignment (slits, sample and detector position), magnetic field controllers, neutron velocity selection (choppers) and neutron detectors. The SNS Data Acquisition System (DAS) consists of real-time sub-system (detector read-out with custom electronics, chopper interface), data preprocessing (soft real-time) and a cluster of control and ancillary PCs. The real-time system runs FPGA firmware and programs running on PCs (C++, LabView) typically perform one task such as motor control and communicate via TCP/IP networks. PyDas is a set of Python modules that are used to integrate various components of the SNS DAS system. It enables customized automation of neutron scattering experiments in a rapid and flexible manner. It provides wxPython GUIs for routine experiments as well as IPython command line scripting. Matplotlib and numpy are used for data presentation and simple analysis. We will present an overview of SNS Data Acquisition System and PyDas architectures and implementation along with the examples of use. We will also discuss plans for future development as well as the challenges that have to be met while maintaining PyDas for 20+ different scientific instruments.

  5. Efficiency asynchronous application programming language Python

    OpenAIRE

    Толстікова, О. В.; Національний авіаційний університет; Мирошниченко, І. С.; Національний авіаційний університет; Коцюр, А. Б.; Національний авіаційний університет

    2016-01-01

    Consider tools that implement asynchronous programming in Python and allow more efficient use ofasynchronous programming applications. The efficiency of the module asyncio (PEP 3156) incomparison with classical spivprohramamy Рассмотрены инструменты, которые реализуют асинхронное программирование в языкеPython и позволяют повысить эффективность использования программирования асинхронныхприложений. Показана эффективность работы модуля asyncio (PEP 3156) по сравнению с классическими сопрогра...

  6. galpy: A python LIBRARY FOR GALACTIC DYNAMICS

    Energy Technology Data Exchange (ETDEWEB)

    Bovy, Jo, E-mail: bovy@ias.edu [Institute for Advanced Study, Einstein Drive, Princeton, NJ 08540 (United States)

    2015-02-01

    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.

  7. Neutron Scattering Experiment Automation with Python

    Energy Technology Data Exchange (ETDEWEB)

    Zolnierczuk, Piotr A [ORNL; Riedel, Richard A [ORNL

    2010-01-01

    The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory currently holds the Guinness World Record as the world most powerful pulsed spallation neutron source. Neutrons scattered off atomic nuclei in a sample yield important information about the position, motions, and magnetic properties of atoms in materials. A neutron scattering experiment usually involves sample environment control (temperature, pressure, etc.), mechanical alignment (slits, sample and detector position), magnetic field controllers, neutron velocity selection (choppers) and neutron detectors. The SNS Data Acquisition System (DAS) consists of real-time sub-system (detector read-out with custom electronics, chopper interface), data preprocessing (soft real-time) and a cluster of control and ancillary PCs. The real-time system runs FPGA firmware and programs running on PCs (C++, LabView) typically perform one task such as motor control and communicate via TCP/IP networks. PyDas is a set of Python modules that are used to integrate various components of the SNS DAS system. It enables customized automation of neutron scattering experiments in a rapid and flexible manner. It provides wxPython GUIs for routine experiments as well as IPython command line scripting. Matplotlib and numpy are used for data presentation and simple analysis. We will present an overview of SNS Data Acquisition System and PyDas architectures and implementation along with the examples of use. We will also discuss plans for future development as well as the challenges that have to be met while maintaining PyDas for 20+ different scientific instruments.

  8. galpy: A python Library for Galactic Dynamics

    Science.gov (United States)

    Bovy, Jo

    2015-02-01

    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.

  9. PNet: A Python Library for Petri Net Modeling and Simulation

    Directory of Open Access Journals (Sweden)

    Zhu En Chay

    2016-07-01

    Full Text Available Petri Net is a formalism to describe changes between 2 or more states across discrete time and has been used to model many systems. We present PNet – a pure Python library for Petri Net modeling and simulation in Python programming language. The design of PNet focuses on reducing the learning curve needed to define a Petri Net by using a text-based language rather than programming constructs to define transition rules. Complex transition rules can be refined as regular Python functions. To demonstrate the simplicity of PNet, we present 2 examples – bread baking, and epidemiological models.

  10. Plyades: A Python Library for Space Mission Design

    CERN Document Server

    Eichhorn, Helge

    2016-01-01

    Plyades: A Python Library for Space Mission Design Designing a space mission is a computation-heavy task. Software tools that conduct the necessary numerical simulations and optimizations are therefore indispensable. The usability of existing software, written in Fortran and MATLAB, suffers because of high complexity, low levels of abstraction and out-dated programming practices. We propose Python as a viable alternative for astrodynamics tools and demonstrate the proof-of-concept library Plyades which combines powerful features with Pythonic ease of use.

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

    OpenAIRE

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

    2015-01-01

    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 a...

  12. PyMC: Bayesian Stochastic Modelling in Python

    OpenAIRE

    Anand Patil; David Huard; Fonnesbeck, Christopher J.

    2010-01-01

    This user guide describes a Python package, PyMC, that allows users to efficiently code a probabilistic model and draw samples from its posterior distribution using Markov chain Monte Carlo techniques.

  13. A Python Wrapper Code Generator for Dynamic Libraries

    Directory of Open Access Journals (Sweden)

    2011-06-01

    Full Text Available We introduce a new Python code generator for conveniently and transparently wrapping native dynamic libraries. The presented code generator is used in several projects for scientific collaboration and can be adapted to other projects fairly easily.

  14. Rapid Development of Interferometric Software Using MIRIAD and Python

    CERN Document Server

    Williams, Peter K G; Bower, Geoffrey C

    2012-01-01

    New and upgraded radio interferometers produce data at massive rates and will require significant improvements in analysis techniques to reach their promised levels of performance in a routine manner. Until these techniques are fully developed, productivity and accessibility in scientific programming environments will be key bottlenecks in the pipeline leading from data-taking to research results. We present an open-source software package, miriad-python, that allows access to the MIRIAD interferometric reduction system in the Python programming language. The modular design of MIRIAD and the high productivity and accessibility of Python provide an excellent foundation for rapid development of interferometric software. Several other projects with similar goals exist and we describe them and compare miriad-python to them in detail. Along with an overview of the package design, we present sample code and applications, including the detection of millisecond astrophysical transients, determination and application ...

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

    International Nuclear Information System (INIS)

    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.

  16. Rabacus: A Python Package for Analytic Cosmological Radiative Transfer Calculations

    CERN Document Server

    Altay, Gabriel

    2015-01-01

    We describe Rabacus, a Python package for calculating the transfer of hydrogen ionizing radiation in simplified geometries relevant to astronomy and cosmology. We present example solutions for three specific cases: 1) a semi-infinite slab gas distribution in a homogeneous isotropic background, 2) a spherically symmetric gas distribution with a point source at the center, and 3) a spherically symmetric gas distribution in a homogeneous isotropic background. All problems can accommodate arbitrary spectra and density profiles as input. The solutions include a treatment of both hydrogen and helium, a self-consistent calculation of equilibrium temperatures, and the transfer of recombination radiation. The core routines are written in Fortran 90 and then wrapped in Python leading to execution speeds thousands of times faster than equivalent routines written in pure Python. In addition, all variables have associated units for ease of analysis. The software is part of the Python Package Index and the source code is a...

  17. Pyvolve: A Flexible Python Module for Simulating Sequences along Phylogenies

    OpenAIRE

    Spielman, Stephanie J.; Wilke, Claus O

    2015-01-01

    We introduce Pyvolve, a flexible Python module for simulating genetic data along a phylogeny using continuous-time Markov models of sequence evolution. Easily incorporated into Python bioinformatics pipelines, Pyvolve can simulate sequences according to most standard models of nucleotide, amino-acid, and codon sequence evolution. All model parameters are fully customizable. Users can additionally specify custom evolutionary models, with custom rate matrices and/or states to evolve. This flexi...

  18. Atomic data mining numerical methods, source code SQlite with Python

    OpenAIRE

    Khwaldeh, Ali; Tahat, Amani; Martí Rabassa, Jordi; Tahat, Mofleh

    2013-01-01

    This paper introduces a recently published Python data mining book (chapters, topics, samples of Python source code written by its authors) to be used in data mining via world wide web and any specific database in several disciplines (economic, physics, education, marketing. etc). The book started with an introduction to data mining by explaining some of the data mining tasks involved classification, dependence modelling, clustering and discovery of association rules. The book addressed that ...

  19. Introduction into bi-partite networks in python

    OpenAIRE

    Kasberger, Stefan

    2016-01-01

    This essay and the related computation delivers a comprehensive introduction into the concept of bipartite networks, a class of networks whose nodes are divided into two sets and only the connection between two nodes in different sets is allowed (Easley and Kleinberg, 2010). The analysis and visualization is done in the programming language Python and offers easy to understand first steps in both fields, network analyses and python programming. As data a collaboration network of github users ...

  20. Simulating Evolutionary Games: A Python-Based Introduction

    OpenAIRE

    Alan G. Isaac

    2008-01-01

    This paper is an introduction to agent-based simulation using the Python programming language. The core objective of the paper is to enable students, teachers, and researchers immediately to begin social-science simulation projects in a general purpose programming language. This objective is facilitated by design features of the Python programming language, which we very briefly discuss. The paper has a 'tutorial' component, in that it is enablement-focused and therefore strongly application-...

  1. PyMultiNest: Python interface for MultiNest

    Science.gov (United States)

    Buchner, Johannes

    2016-06-01

    PyMultiNest provides programmatic access to MultiNest (ascl:1109.006) and PyCuba, integration existing Python code (numpy, scipy), and enables writing Prior & LogLikelihood functions in Python. PyMultiNest can plot and visualize MultiNest's progress and allows easy plotting, visualization and summarization of MultiNest results. The plotting can be run on existing MultiNest output, and when not using PyMultiNest for running MultiNest.

  2. MEG and EEG data analysis with MNE-Python

    OpenAIRE

    Alexandre eGramfort; Martin eLuessi; Eric eLarson; Denis A Engemann; Daniel eStrohmeier; Christian eBrodbeck; Roman eGoj; Mainak eJas; Teon eBrooks; Lauri eParkkonen; Matti eHämäläinen

    2013-01-01

    Magnetoencephalography and electroencephalography (M/EEG) measure the weakelectromagnetic signals generated by neuronal activity in the brain. Using thesesignals to characterize and locate neural activation in the brain is achallenge that requires expertise in physics, signalprocessing, statistics, and numerical methods. As part of the MNE softwaresuite, MNE-Python is an open-sourcesoftware package that addresses this challenge by providingstate-of-the-art algorithms implemented in Python tha...

  3. 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

    2013-12-26

    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

  4. L-Py: L-Systems in Python

    OpenAIRE

    Boudon, Frédéric; Pradal, Christophe

    2011-01-01

    Lindenmayer-systems were conceived as a mathematical framework for modeling growth of plants. In this paper, we present L-Py, a simulation package that mixes L-systems construction with the Python high-level modeling language. In addition to this software module, an integrated visual development environment has been developed that facilitates the creation of plant models. In particular, easy to use optimization tools have been integrated. Thanks to Python and its modular approach, this framew...

  5. Python for unified research in econometrics and statistics

    OpenAIRE

    Bilina, Roseline; Lawford, Steve

    2012-01-01

    Python is a powerful high level open source programming language, that is available for multiple platforms. It supports object oriented programming, and has recently become a serious alternative to low level compiled languages such as C. It is easy to learn and use, and is recognized for very fast development times, which makes it suitable for rapid software prototyping as well as teaching purposes. We motivate the use of Python and its free extension modules for high performance stand alone ...

  6. PyCraters: A Python framework for crater function analysis

    OpenAIRE

    Norris, Scott A.

    2014-01-01

    We introduce a Python framework designed to automate the most common tasks associated with the extraction and upscaling of the statistics of single-impact crater functions to inform coefficients of continuum equations describing surface morphology evolution. Designed with ease-of-use in mind, the framework allows users to extract meaningful statistical estimates with very short Python programs. Wrappers to interface with specific simulation packages, routines for statistical extraction of out...

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

    CERN Document Server

    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...

  8. 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; Madsen, Peter Teglberg

    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...

  9. 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

  10. TRIPPy: Trailed Image Photometry in Python

    CERN Document Server

    Fraser, Wesley C; Schwamb, Megan E; Marsset, Michael E; Pike, Rosemary E; Kavelaars, JJ; Bannister, Michele T; Benecchi, Susan; Delsanti, Audrey

    2016-01-01

    Photometry of moving sources typically suffers from reduced signal-to-noise (SNR) or flux measurements biased to incorrect low values through the use of circular apertures. To address this issue we present the software package, TRIPPy: TRailed Image Photometry in Python. TRIPPy introduces the pill aperture, which is the natural extension of the circular aperture appropriate for linearly trailed sources. The pill shape is a rectangle with two semicircular end-caps, and is described by three parameters, the trail length and angle, and the radius. The TRIPPy software package also includes a new technique to generate accurate model point-spread functions (PSF) and trailed point-spread functions (TSF) from stationary background sources in sidereally tracked images. The TSF is merely the convolution of the model PSF, which consists of a moffat profile, and super sampled lookup table. From the TSF, accurate pill aperture corrections can be estimated as a function of pill radius with a accuracy of 10 millimags for hi...

  11. AJAC: Atomic data calculation tool in Python

    International Nuclear Information System (INIS)

    In this work, new features and extensions of a currently used online atomic database management system are reported. A multiplatform flexible computation package is added to the present system, to allow the calculation of various atomic radiative and collisional processes, based on simplifying the use of some existing atomic codes adopted from the literature. The interaction between users and data is facilitated by a rather extensive Python graphical user interface working online and could be installed in personal computers of different classes. In particular, this study gives an overview of the use of one model of the package models (i.e., electron impact collisional excitation model). The accuracy of computing capability of the electron impact collisional excitation in the adopted model, which follows the distorted wave approximation approach, is enhanced by implementing the Dirac R-matrix approximation approach. The validity and utility of this approach are presented through a comparison of the current computed results with earlier available theoretical and experimental results. Finally, the source code is made available under the general public license and being distributed freely in the hope that it will be useful to a wide community of laboratory and astrophysical plasma diagnostics. (interdisciplinary physics and related areas of science and technology)

  12. TRIPPy: Trailed Image Photometry in Python

    Science.gov (United States)

    Fraser, Wesley; Alexandersen, Mike; Schwamb, Megan E.; Marsset, Michaël; Pike, Rosemary E.; Kavelaars, J. J.; Bannister, Michele T.; Benecchi, Susan; Delsanti, Audrey

    2016-06-01

    Photometry of moving sources typically suffers from a reduced signal-to-noise ratio (S/N) or flux measurements biased to incorrect low values through the use of circular apertures. To address this issue, we present the software package, TRIPPy: TRailed Image Photometry in Python. TRIPPy introduces the pill aperture, which is the natural extension of the circular aperture appropriate for linearly trailed sources. The pill shape is a rectangle with two semicircular end-caps and is described by three parameters, the trail length and angle, and the radius. The TRIPPy software package also includes a new technique to generate accurate model point-spread functions (PSFs) and trailed PSFs (TSFs) from stationary background sources in sidereally tracked images. The TSF is merely the convolution of the model PSF, which consists of a moffat profile, and super-sampled lookup table. From the TSF, accurate pill aperture corrections can be estimated as a function of pill radius with an accuracy of 10 mmag for highly trailed sources. Analogous to the use of small circular apertures and associated aperture corrections, small radius pill apertures can be used to preserve S/Ns of low flux sources, with appropriate aperture correction applied to provide an accurate, unbiased flux measurement at all S/Ns.

  13. MTpy: A Python toolbox for magnetotellurics

    Science.gov (United States)

    Krieger, Lars; Peacock, Jared R.

    2014-11-01

    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. In its current state, modules and functions of MTpy work on raw and pre-processed MT data. However, opposite to providing a static compilation of software, we prefer to introduce MTpy as a flexible software toolbox, whose contents can be combined and utilised according to the respective needs of the user. Just as the overall functionality of a mechanical toolbox can be extended by adding new tools, MTpy is a flexible framework, which will be dynamically extended in the future. Furthermore, it can help to unify and extend existing codes and algorithms within the (academic) MT community. In this paper, we introduce the structure and concept of MTpy. Additionally, we show some examples from an everyday work-flow of MT data processing: the generation of standard EDI data files from raw electric (E-) and magnetic flux density (B-) field time series as input, the conversion into MiniSEED data format, as well as the generation of a graphical data representation in the form of a Phase Tensor pseudosection.

  14. 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.

  15. 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.

  16. 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.

  17. 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......CSP presently supports the core CSP abstractions. We introduce the PyCSP library, its implementation, a few performance benchmarks, and show example code using PyCSP. An early prototype of PyCSP has been used in this year's Extreme Multiprogramming Class at the CS department, university of Copenhagen with...

  18. Application of the device database in the Python programming

    International Nuclear Information System (INIS)

    The Device Database has been developed using the relational database in the KEKB accelerator control system. It contains many kinds of parameters of the devices, mainly magnets and magnet power supplies. The parameters consist of the wiring information, the address of the interfaces, the specification of the hardware, the calibration constants, the magnetic field excitation functions and the any other parameters for the device control. These parameters are necessary not only for constructing EPICS IOC database but also for providing information to the high-level application programs, most of which are written in the script languages such as SAD or Python. Particularly Python is often used to access the Device Database. For this purpose, the Python library module that is designed to handle tabular data of the relational database on memory has been developed. The overview of the library module is reported. (author)

  19. A parvovirus isolated from royal python (Python regius) is a member of the genus Dependovirus.

    Science.gov (United States)

    Farkas, Szilvia L; Zádori, Zoltán; Benko, Mária; Essbauer, Sandra; Harrach, Balázs; Tijssen, Peter

    2004-03-01

    Parvoviruses were isolated from Python regius and Boa constrictor snakes and propagated in viper heart (VH-2) and iguana heart (IgH-2) cells. The full-length genome of a snake parvovirus was cloned and both strands were sequenced. The organization of the 4432-nt-long genome was found to be typical of parvoviruses. This genome was flanked by inverted terminal repeats (ITRs) of 154 nt, containing 122 nt terminal hairpins and contained two large open reading frames, encoding the non-structural and structural proteins. Genes of this new parvovirus were most similar to those from waterfowl parvoviruses and from adeno-associated viruses (AAVs), albeit to a relatively low degree and with some organizational differences. The structure of its ITRs also closely resembled those of AAVs. Based on these data, we propose to classify this virus, the first serpentine parvovirus to be identified, as serpentine adeno-associated virus (SAAV) in the genus Dependovirus. PMID:14993638

  20. High performance Python for direct numerical simulations of turbulent flows

    Science.gov (United States)

    Mortensen, Mikael; Langtangen, Hans Petter

    2016-06-01

    Direct Numerical Simulations (DNS) of the Navier Stokes equations is an invaluable research tool in fluid dynamics. Still, there are few publicly available research codes and, due to the heavy number crunching implied, available codes are usually written in low-level languages such as C/C++ or Fortran. In this paper we describe a pure scientific Python pseudo-spectral DNS code that nearly matches the performance of C++ for thousands of processors and billions of unknowns. We also describe a version optimized through Cython, that is found to match the speed of C++. The solvers are written from scratch in Python, both the mesh, the MPI domain decomposition, and the temporal integrators. The solvers have been verified and benchmarked on the Shaheen supercomputer at the KAUST supercomputing laboratory, and we are able to show very good scaling up to several thousand cores. A very important part of the implementation is the mesh decomposition (we implement both slab and pencil decompositions) and 3D parallel Fast Fourier Transforms (FFT). The mesh decomposition and FFT routines have been implemented in Python using serial FFT routines (either NumPy, pyFFTW or any other serial FFT module), NumPy array manipulations and with MPI communications handled by MPI for Python (mpi4py). We show how we are able to execute a 3D parallel FFT in Python for a slab mesh decomposition using 4 lines of compact Python code, for which the parallel performance on Shaheen is found to be slightly better than similar routines provided through the FFTW library. For a pencil mesh decomposition 7 lines of code is required to execute a transform.

  1. Jet flavor tagging with Deep Learning using Python

    CERN Document Server

    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.

  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. Multi-thread-ready EPICS-Python interface

    International Nuclear Information System (INIS)

    EPICS (Experimental Physics and Industrial Controls) is a software toolkit for an accelerator control system and now widely used in the various laboratories and accelerators over the world. RARF/RIBF in Riken, KEKB/PF-AR in KEK and J-PARC in JAEA/KEK joint project are instalments of EPICS in Japan. Python, an object oriented script language, is also widely used in these systems for testing a system and for GUI building. Making EPICS-Python Interface multi-thread-ready improves performance of these application and also ease a development of applications. (author)

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

    International Nuclear Information System (INIS)

    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.)

  5. Frequentism and Bayesianism: A Python-driven Primer

    CERN Document Server

    VanderPlas, Jake

    2014-01-01

    This paper presents a brief, semi-technical comparison of the essential features of the frequentist and Bayesian approaches to statistical inference, with several illustrative examples implemented in Python. The differences between frequentism and Bayesianism fundamentally stem from differing definitions of probability, a philosophical divide which leads to distinct approaches to the solution of statistical problems as well as contrasting ways of asking and answering questions about unknown parameters. After an example-driven discussion of these differences, we briefly compare several leading Python statistical packages which implement frequentist inference using classical methods and Bayesian inference using Markov Chain Monte Carlo.

  6. Exomerge user's manual : a lightweight Python interface for manipulating Exodus files.

    Energy Technology Data Exchange (ETDEWEB)

    Kostka, Timothy D.

    2013-01-01

    Exomerge is a lightweight Python module for reading, manipulating and writing data within ExodusII files. It is built upon a Python wrapper around the ExodusII API functions. This module, the Python wrapper, and the ExodusII libraries are available as part of the standard SIERRA installation.

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

    CERN Document Server

    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.

  8. 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. PMID:27610080

  9. 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.

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

    OpenAIRE

    Vladimiras Dolgopolovas; Valentina Dagienė; Saulius Minkevičius; Leonidas Sakalauskas

    2014-01-01

    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.

  11. 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.

  12. 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.

  13. 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 va

  14. 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. PMID:26001643

  15. 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 for...

  16. Setting Up an Integrated Development Environment for Python (Windows)

    OpenAIRE

    William J. Turkel; Adam Crymble

    2012-01-01

    An Integrated Development Environment lets you write and run your Python code all in one place. For users who do not like the idea of the command line, this offers a solution that is more similar to the types of interfaces you are probably used to using.

  17. Setting up an Integrated Development Environment for Python (Linux)

    OpenAIRE

    William J. Turkel; Adam Crymble

    2012-01-01

    An Integrated Development Environment lets you write and run your Python code all in one place. For users who do not like the idea of the command line, this offers a solution that is more similar to the types of interfaces you are probably used to using.

  18. Setting Up an Integrated Development Environment for Python (Windows

    Directory of Open Access Journals (Sweden)

    William J. Turkel

    2012-07-01

    Full Text Available An Integrated Development Environment lets you write and run your Python code all in one place. For users who do not like the idea of the command line, this offers a solution that is more similar to the types of interfaces you are probably used to using.

  19. Setting Up an Integrated Development Environment for Python (Mac)

    OpenAIRE

    William J. Turkel; Adam Crymble

    2012-01-01

    An Integrated Development Environment lets you write and run your Python code all in one place. For users who do not like the idea of the command line, this offers a solution that is more similar to the types of interfaces you are probably used to using.

  20. Los primeros minutos de Monty Python y el santo Grial

    Directory of Open Access Journals (Sweden)

    Alberto Chimal

    2007-07-01

    Full Text Available Cet article problématise quelques fragments de "Monty Python et le Saint Graal" ("Monty Python and the Holy Grail", film réalisé en 1975 par Terry Gilliam et Terry Jones. En parodiant des textes et des films arthuriens - notamment La mort d’Arthur de Thomas Malory, souvent considéré comme le résumé “canonique” de la tradition arthurienne-, le film met ouvertement en question les réductions faites par le cinéma de la matière de Bretagne, en les ridiculisant et les opposant à d’autres éléments arthuriens pris dans les textes originels.El artículo problematiza momentos importantes de Monty Python y el Santo Grial (Monty Python and the Holy Grail, filme dirigido en 1975 por Terry Gilliam y Terry Jones. Parodia de textos y filmes artúricos -en especial La muerte de Arturo de Thomas Malory, considerada a veces resumen “canónico” de la tradición artúrica-, la película cuestiona abiertamente las reducciones hechas por el cine de la Materia de la Gran Bretaña, ridiculizándolas y contrastándolas con otros elementos artúricos tomados de los textos originales.

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

    NARCIS (Netherlands)

    Gouw, C.P.T. de; Boer, F.S. de

    2015-01-01

    Tim 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 algorithm in Ja

  2. Rabacus: A Python package for analytic cosmological radiative transfer calculations

    Science.gov (United States)

    Altay, G.; Wise, J. H.

    2015-04-01

    We describe RABACUS, a Python package for calculating the transfer of hydrogen ionizing radiation in simplified geometries relevant to astronomy and cosmology. We present example solutions for three specific cases: (1) a semi-infinite slab gas distribution in a homogeneous isotropic background, (2) a spherically symmetric gas distribution with a point source at the center, and (3) a spherically symmetric gas distribution in a homogeneous isotropic background. All problems can accommodate arbitrary spectra and density profiles as input. The solutions include a treatment of both hydrogen and helium, a self-consistent calculation of equilibrium temperatures, and the transfer of recombination radiation. The core routines are written in Fortran 90 and then wrapped in Python leading to execution speeds thousands of times faster than equivalent routines written in pure Python. In addition, all variables have associated units for ease of analysis. The software is part of the Python Package Index and the source code is available on Bitbucket at

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

    OpenAIRE

    Helmus, Jonathan J.; Scott M Collis

    2016-01-01

    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 Cy...

  4. Python programming language and the effectiveness of its inclusion in the teaching

    OpenAIRE

    Vitásek, Tomáš

    2009-01-01

    The goal of the first part of this work is to summarize the basics of the Python programming language. Show how to create programs in Python, what are the modules, the basic data types, syntax and the possibility of approach to language. The second part will address the description of the initial programming courses, their objectives and what benefits it brings to teaching Python. Finally, then look at the (in)dependence on the Python platform for running and how to get from Python to another...

  5. 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

  6. Flexible Environmental Modeling with Python and Open - GIS

    Science.gov (United States)

    Pryet, Alexandre; Atteia, Olivier; Delottier, Hugo; Cousquer, Yohann

    2015-04-01

    Numerical modeling now represents a prominent task of environmental studies. During the last decades, numerous commercial programs have been made available to environmental modelers. These software applications offer user-friendly graphical user interfaces that allow an efficient management of many case studies. However, they suffer from a lack of flexibility and closed-source policies impede source code reviewing and enhancement for original studies. Advanced modeling studies require flexible tools capable of managing thousands of model runs for parameter optimization, uncertainty and sensitivity analysis. In addition, there is a growing need for the coupling of various numerical models associating, for instance, groundwater flow modeling to multi-species geochemical reactions. Researchers have produced hundreds of open-source powerful command line programs. However, there is a need for a flexible graphical user interface allowing an efficient processing of geospatial data that comes along any environmental study. Here, we present the advantages of using the free and open-source Qgis platform and the Python scripting language for conducting environmental modeling studies. The interactive graphical user interface is first used for the visualization and pre-processing of input geospatial datasets. Python scripting language is then employed for further input data processing, call to one or several models, and post-processing of model outputs. Model results are eventually sent back to the GIS program, processed and visualized. This approach combines the advantages of interactive graphical interfaces and the flexibility of Python scripting language for data processing and model calls. The numerous python modules available facilitate geospatial data processing and numerical analysis of model outputs. Once input data has been prepared with the graphical user interface, models may be run thousands of times from the command line with sequential or parallel calls. We

  7. Pyvolve: A Flexible Python Module for Simulating Sequences along Phylogenies.

    Directory of Open Access Journals (Sweden)

    Stephanie J Spielman

    Full Text Available We introduce Pyvolve, a flexible Python module for simulating genetic data along a phylogeny using continuous-time Markov models of sequence evolution. Easily incorporated into Python bioinformatics pipelines, Pyvolve can simulate sequences according to most standard models of nucleotide, amino-acid, and codon sequence evolution. All model parameters are fully customizable. Users can additionally specify custom evolutionary models, with custom rate matrices and/or states to evolve. This flexibility makes Pyvolve a convenient framework not only for simulating sequences under a wide variety of conditions, but also for developing and testing new evolutionary models. Pyvolve is an open-source project under a FreeBSD license, and it is available for download, along with a detailed user-manual and example scripts, from http://github.com/sjspielman/pyvolve.

  8. Pyvolve: A Flexible Python Module for Simulating Sequences along Phylogenies.

    Science.gov (United States)

    Spielman, Stephanie J; Wilke, Claus O

    2015-01-01

    We introduce Pyvolve, a flexible Python module for simulating genetic data along a phylogeny using continuous-time Markov models of sequence evolution. Easily incorporated into Python bioinformatics pipelines, Pyvolve can simulate sequences according to most standard models of nucleotide, amino-acid, and codon sequence evolution. All model parameters are fully customizable. Users can additionally specify custom evolutionary models, with custom rate matrices and/or states to evolve. This flexibility makes Pyvolve a convenient framework not only for simulating sequences under a wide variety of conditions, but also for developing and testing new evolutionary models. Pyvolve is an open-source project under a FreeBSD license, and it is available for download, along with a detailed user-manual and example scripts, from http://github.com/sjspielman/pyvolve. PMID:26397960

  9. Developing PYTHON Codes for the Undergraduate ALFALFA Team

    Science.gov (United States)

    Troischt, Parker; Ryan, Nicholas; Alfalfa Team

    2016-03-01

    We describe here progress toward developing a number of new PYTHON routines to be used by members of the Undergraduate ALFALFA Team. The codes are designed to analyze HI spectra and assist in identifying and categorizing some of the intriguing sources found in the initial blind ALFALFA survey. Numerical integration is performed on extragalactic sources using 21cm line spectra produced with the L-Band Wide receiver at the National Astronomy and Ionosphere Center. Prior to the integration, polynomial fits are employed to obtain an appropriate baseline for each source. The codes developed here are part of a larger team effort to use new PYTHON routines in order to replace, upgrade, or supplement a wealth of existing IDL codes within the collaboration. This work has been supported by NSF Grant AST-1211005.

  10. A pythonic integrated solution for virtual prototyping of cyclotrons

    International Nuclear Information System (INIS)

    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

  11. Basic Data Analysis and More - A Guided Tour Using Python

    CERN Document Server

    Melchert, O

    2012-01-01

    In these lecture notes, a selection of frequently required statistical tools will be introduced and illustrated. They allow to post-process data that stem from, e.g., large-scale numerical simulations (aka sequence of random experiments). From a point of view of data analysis, the concepts and techniques introduced here are of general interest and are, at best, employed by computational aid. Consequently, an exemplary implementation of the presented techniques using the Python programming language is provided. The contents of these lecture notes is rather selective and represents a computational experimentalist's view on the subject of basic data analysis, ranging from the simple computation of moments for distributions of random variables to more involved topics such as hierarchical cluster analysis and the parallelization of Python code.

  12. Python Implementation for Local Correlation Tracking Analysis of Solar Data

    Science.gov (United States)

    Campos Rozo, J. I.; Vargas Domínguez, S.

    2015-12-01

    The Local Correlation Tracking (LCT) technique is a robust method that has been extensively applied to infer proper motions of structures in time series of images. In solar physics research, LCT is a useful tool to analyse the dynamics of plasma and the evolution of magnetic fields in the solar atmosphere at different spatial and temporal scales, among others (e.g granular and supergranular convective cells, meridional flows, etc) SunPy is a joint effort of, using the advantages of Python, developing tools to be applied for processing and analysis of solar data. In this work, a widget implemented in Python and Sunpy is developed, to generate a user-friendly graphical user interface (GUI) to control various parameters for the process of calculating flow maps of proper motions for a series of filtergrams.

  13. Interoperability between .Net framework and Python in Component way

    Directory of Open Access Journals (Sweden)

    M. K. Pawar

    2013-01-01

    Full Text Available The objective of this work is to make interoperability of the distributed object based on CORBA middleware technology and standards. The distributed objects for the client-server technology are implemented in C#.Net framework and the Python language. The interoperability result shows the possibilities of application in which objects can communicate in different environment and different languages. It is also analyzing that how to achieve client-server communication in heterogeneous environment using the OmniORBpy IDL compiler and IIOP.NET IDLtoCLS mapping. The results were obtained that demonstrate the interoperability between .Net Framework and Python language. This paper also summarizes a set of fairly simple examples using some reasonably complex software tools.

  14. 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. PMID:24142834

  15. PyCraters: A Python framework for crater function analysis

    CERN Document Server

    Norris, Scott A

    2014-01-01

    We introduce a Python framework designed to automate the most common tasks associated with the extraction and upscaling of the statistics of single-impact crater functions to inform coefficients of continuum equations describing surface morphology evolution. Designed with ease-of-use in mind, the framework allows users to extract meaningful statistical estimates with very short Python programs. Wrappers to interface with specific simulation packages, routines for statistical extraction of output, and fitting and differentiation libraries are all hidden behind simple, high-level user-facing functions. In addition, the framework is extensible, allowing advanced users to specify the collection of specialized statistics or the creation of customized plots. The framework is hosted on the BitBucket service under an open-source license, with the aim of helping non-specialists easily extract preliminary estimates of relevant crater function results associated with a particular experimental system.

  16. Parallel Astronomical Data Processing with Python: Recipes for multicore machines

    CERN Document Server

    Singh, Navtej; Butler, Ray

    2013-01-01

    High performance computing has been used in various fields of astrophysical research. But most of it is implemented on massively parallel systems (supercomputers) or graphical processing unit clusters. With the advent of multicore processors in the last decade, many serial software codes have been re-implemented in parallel mode to utilize the full potential of these processors. In this paper, we propose parallel processing recipes for multicore machines for astronomical data processing. The target audience are astronomers who are using Python as their preferred scripting language and who may be using PyRAF/IRAF for data processing. Three problems of varied complexity were benchmarked on three different types of multicore processors to demonstrate the benefits, in terms of execution time, of parallelizing data processing tasks. The native multiprocessing module available in Python makes it a relatively trivial task to implement the parallel code. We have also compared the three multiprocessing approaches - Po...

  17. 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.

  18. PRECESSION. Dynamics of spinning black-hole binaries with python

    OpenAIRE

    Gerosa, Davide; Kesden, Michael

    2016-01-01

    We present the numerical code PRECESSION: a new open-source python module to study the dynamics of precessing black-hole binaries in the post-Newtonian regime. The code provides a comprehensive toolbox to (i) study the evolution of the black-hole spins along their precession cycles, (ii) perform gravitational-wave driven binary inspirals using both orbit-averaged and precession-averaged integrations, and (iii) predict the properties of the merger remnant through fitting formulae obtained from...

  19. Python as a federation tool for GENESIS 3.0.

    Directory of Open Access Journals (Sweden)

    Hugo Cornelis

    Full Text Available 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

  20. ObsPy: A Python Toolbox for Seismology

    Science.gov (United States)

    Wassermann, J. M.; Krischer, L.; Megies, T.; Barsch, R.; Beyreuther, M.

    2013-12-01

    Python combines the power of a full-blown programming language with the flexibility and accessibility of an interactive scripting language. Its extensive standard library and large variety of freely available high quality scientific modules cover most needs in developing scientific processing workflows. ObsPy is a community-driven, open-source project extending Python's capabilities to fit the specific needs that arise when working with seismological data. It a) comes with a continuously growing signal processing toolbox that covers most tasks common in seismological analysis, b) provides read and write support for many common waveform, station and event metadata formats and c) enables access to various data centers, webservices and databases to retrieve waveform data and station/event metadata. In combination with mature and free Python packages like NumPy, SciPy, Matplotlib, IPython, Pandas, lxml, and PyQt, ObsPy makes it possible to develop complete workflows in Python, ranging from reading locally stored data or requesting data from one or more different data centers via signal analysis and data processing to visualization in GUI and web applications, output of modified/derived data and the creation of publication-quality figures. All functionality is extensively documented and the ObsPy Tutorial and Gallery give a good impression of the wide range of possible use cases. ObsPy is tested and running on Linux, OS X and Windows and comes with installation routines for these systems. ObsPy is developed in a test-driven approach and is available under the LGPLv3 open source licence. Users are welcome to request help, report bugs, propose enhancements or contribute code via either the user mailing list or the project page on GitHub.

  1. Wyrm, A Pythonic Toolbox for Brain-Computer Interfacing

    OpenAIRE

    Venthur, Bastian; Blankertz, Benjamin

    2014-01-01

    A Brain-Computer Interface (BCI) is a system that measures central nervous system activity and translates the recorded data into an output suitable for a computer to use as an input signal. Such a BCI system consists of three parts, the signal acquisition, the signal processing and the feedback/stimulus presentation. In this paper we present Wyrm, a signal processing toolbox for BCI in Python. Wyrm is applicable to a broad range of neuroscientific problems and capable for running online exper...

  2. Psyplot: Visualizing rectangular and triangular Climate Model Data with Python

    Science.gov (United States)

    Sommer, Philipp

    2016-04-01

    The development and use of climate models often requires the visualization of geo-referenced data. Creating visualizations should be fast, attractive, flexible, easily applicable and easily reproducible. There is a wide range of software tools available for visualizing raster data, but they often are inaccessible to many users (e.g. because they are difficult to use in a script or have low flexibility). In order to facilitate easy visualization of geo-referenced data, we developed a new framework called "psyplot," which can aid earth system scientists with their daily work. It is purely written in the programming language Python and primarily built upon the python packages matplotlib, cartopy and xray. The package can visualize data stored on the hard disk (e.g. NetCDF, GeoTIFF, any other file format supported by the xray package), or directly from the memory or Climate Data Operators (CDOs). Furthermore, data can be visualized on a rectangular grid (following or not following the CF Conventions) and on a triangular grid (following the CF or UGRID Conventions). Psyplot visualizes 2D scalar and vector fields, enabling the user to easily manage and format multiple plots at the same time, and to export the plots into all common picture formats and movies covered by the matplotlib package. The package can currently be used in an interactive python session or in python scripts, and will soon be developed for use with a graphical user interface (GUI). Finally, the psyplot framework enables flexible configuration, allows easy integration into other scripts that uses matplotlib, and provides a flexible foundation for further development.

  3. Parallelization of Dataset Transformation with Processing Order Constraints in Python

    OpenAIRE

    Gramfors, Dexter

    2016-01-01

    Financial data is often represented with rows of values, contained in a dataset. This data needs to be transformed into a common format in order for comparison and matching to be made, which can take a long time for larger datasets. The main goal of this master’s thesis is speeding up these transformations through parallelization using Python multiprocessing. The datasets in question consist of several rows representing trades, and are transformed into a common format using rules known as fil...

  4. Theano: A Python framework for fast computation of mathematical expressions

    OpenAIRE

    The Theano Development Team; Al-Rfou, Rami; Alain, Guillaume; Almahairi, Amjad; Angermueller, Christof; Bahdanau, Dzmitry; Ballas, Nicolas; Bastien, Frédéric; Bayer, Justin; Belikov, Anatoly; Belopolsky, Alexander; Bengio, Yoshua; Bergeron, Arnaud; Bergstra, James; Bisson, Valentin

    2016-01-01

    Theano is a Python library that allows to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Since its introduction, it has been one of the most used CPU and GPU mathematical compilers - especially in the machine learning community - and has shown steady performance improvements. Theano is being actively and continuously developed since 2008, multiple frameworks have been built on top of it and it has been used to produce many state-of-the-...

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

    OpenAIRE

    Tobias Houska; Philipp Kraft; Alejandro Chamorro-Chavez; Lutz Breuer

    2015-01-01

    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...

  6. Interoperability between .Net framework and Python in Component way

    OpenAIRE

    M. K. Pawar; Ravindra Patel; Dr. N. S. Chaudhari

    2013-01-01

    The objective of this work is to make interoperability of the distributed object based on CORBA middleware technology and standards. The distributed objects for the client-server technology are implemented in C#.Net framework and the Python language. The interoperability result shows the possibilities of application in which objects can communicate in different environment and different languages. It is also analyzing that how to achieve client-server communication in heterogeneous environmen...

  7. MEG and EEG data analysis with MNE-Python

    OpenAIRE

    Gramfort, Alexandre; Luessi, Martin; Larson, Eric; Denis A Engemann; 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 Pyt...

  8. 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 for...... implementing the system. Finally, we present an analysis of the results of the competition as well as propose areas of improvement....

  9. 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...

  10. Frequentism and Bayesianism: A Python-driven Primer

    OpenAIRE

    Vanderplas, Jake

    2014-01-01

    This paper presents a brief, semi-technical comparison of the essential features of the frequentist and Bayesian approaches to statistical inference, with several illustrative examples implemented in Python. The differences between frequentism and Bayesianism fundamentally stem from differing definitions of probability, a philosophical divide which leads to distinct approaches to the solution of statistical problems as well as contrasting ways of asking and answering questions about unknown p...

  11. NIMFA: A Python Library for Nonnegative Matrix Factorization

    OpenAIRE

    Zitnik, Marinka; Zupan, Blaz

    2012-01-01

    NIMFA is an open-source Python library that provides a unified interface to nonnegative matrix factorization algorithms. It includes implementations of state-of-the-art factorization methods, initialization approaches, and quality scoring. It supports both dense and sparse matrix representation. NIMFA's component-based implementation and hierarchical design should help the users to employ already implemented techniques or design and code new strategies for matrix factorization tasks.

  12. Building and Documenting Workflows with Python-Based Snakemake

    OpenAIRE

    Köster, Johannes; Rahmann, Sven

    2012-01-01

    Snakemake 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 write human-readable workflows that document themselves. We have found Snakemake especially useful for building high-throughput sequencing data analysis pipelines and present examples from this area. Snakemake e...

  13. E-resource for learning programming in Python

    OpenAIRE

    Strnad, Mojca

    2011-01-01

    For a better understanding of all computer programs, with which nowadays we are surrounded, the demand for knowing programming languages has nowadays been growing. As more and more people have been interested in learning programming languages, even the basic knowledge of only one programming language is very helpful. As there are nowadays already many programming languages, we decided for the programming language Python. It is anticipated as a programming language which is easy to read an...

  14. Output Data as an HTML File with Python

    OpenAIRE

    William J. Turkel; Adam Crymble

    2012-01-01

    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.

  15. Rapid Development of Interferometric Software Using MIRIAD and Python

    OpenAIRE

    Williams, Peter K. G.; Law, Casey J.; Bower, Geoffrey C.

    2012-01-01

    New and upgraded radio interferometers produce data at massive rates and will require significant improvements in analysis techniques to reach their promised levels of performance in a routine manner. Until these techniques are fully developed, productivity and accessibility in scientific programming environments will be key bottlenecks in the pipeline leading from data-taking to research results. We present an open-source software package, miriad-python, that allows access to the MIRIAD inte...

  16. A Python interface to Diffpack-based classes and solvers

    OpenAIRE

    Munthe-Kaas, Heidi Vikki

    2013-01-01

    Python is a programming language that has gained a lot of popularity during the last 15 years, and as a very easy-to-learn and flexible scripting language it is very well suited for computa- tional science, both in mathematics and in physics. Diffpack is a PDE library written in C++, made for easier implementation of both smaller PDE solvers and for larger libraries of simu- lators. It contains large class hierarchies for different solvers, grids, arrays, parallel computing and almost everyth...

  17. Python for teaching introductory programming: A quantitative evaluation

    OpenAIRE

    Jayal, A; S. Lauria; 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...

  18. Evaluating Scripting Languages : How Python Can Help Political Methodologists

    OpenAIRE

    Döring, Holger

    2008-01-01

    Why Python?Political methodologists tend to make passionate statements about their software tools. The PolMeth mailing list frequently gives strong advocacy for the use of Linux, LATEX, Emacs and other specific programmes. For statistical analysis R has become the mainstream programming language. However, frequent encouragements to use PHP for web purposes or Perl for various scripting tasks highlight the need for a major scripting language beside R. Once political scientists need systematic ...

  19. PYESSENCE - Generalised Coupled Quintessence Linear Perturbation Python Code - User Guide

    OpenAIRE

    Leithes, Alexander

    2016-01-01

    This paper is a guide to the installation and use of the Python package PYESSENCE. PYESSENCE is designed to evolve linear perturbations to Coupled Quintessence models with a arbitrary number of cold dark matter (CDM) fluids and dark energy (DE) scalar fields as dictated by a given model. The equations are sufficiently general to allow for more exotic dark matter with a non-zero equation of state. Several example uses are included in order to demonstrate typical functionality to the potential ...

  20. 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.

  1. ELLIPT2D: A Flexible Finite Element Code Written Python

    International Nuclear Information System (INIS)

    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

  2. GAiN: Distributed Array Computation with Python

    Energy Technology Data Exchange (ETDEWEB)

    Daily, Jeffrey A.

    2009-04-24

    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.

  3. User-friendly parallelization of GAUDI applications with Python

    International Nuclear Information System (INIS)

    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.

  4. 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/ PMID:24961236

  5. What parts of the US mainland are climatically suitable for invasive alien pythons spreading from Everglades National Park?

    Science.gov (United States)

    Rodda, G.H.; Jarnevich, C.S.; Reed, R.N.

    2009-01-01

    The Burmese Python (Python molurus bivittatus) is now well established in southern Florida and spreading northward. The factors likely to limit this spread are unknown, but presumably include climate or are correlated with climate. We compiled monthly rainfall and temperature statistics from 149 stations located near the edge of the python's native range in Asia (Pakistan east to China and south to Indonesia). The southern and eastern native range limits extend to saltwater, leaving unresolved the species' climatic tolerances in those areas. The northern and western limits are associated with cold and aridity respectively. We plotted mean monthly rainfall against mean monthly temperature for the 149 native range weather stations to identify the climate conditions inhabited by pythons in their native range, and mapped areas of the coterminous United States with the same climate today and projected for the year 2100. We accounted for both dry-season aestivation and winter hibernation (under two scenarios of hibernation duration). The potential distribution was relatively insensitive to choice of scenario for hibernation duration. US areas climatically matched at present ranged up the coasts and across the south from Delaware to Oregon, and included most of California, Texas, Oklahoma, Arkansas, Louisiana, Mississippi, Alabama, Florida, Georgia, and South and North Carolina. By the year 2100, projected areas of potential suitable climate extend northward beyond the current limit to include parts of the states of Washington, Colorado, Illinois, Indiana, Ohio, West Virginia, Pennsylvania, New Jersey, and New York. Thus a substantial portion of the mainland US is potentially vulnerable to this ostensibly tropical invader. ?? 2008 Springer Science+Business Media B.V.

  6. 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.

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

    OpenAIRE

    Xing Cai; Hans Petter Langtangen; Halvard Moe

    2005-01-01

    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-r...

  8. Performance and productivity of parallel python programming: a study with a CFD test case

    OpenAIRE

    Basermann, Achim; Röhrig-Zöllner, Melven; Illmer, Joachim

    2015-01-01

    The programming language Python is widely used to create rapidly compact software. However, compared to low-level programming languages like C or Fortran low performance is preventing its use for HPC applications. Efficient parallel programming of multi-core systems and graphic cards is generally a complex task. Python with add-ons might provide a simple approach to program those systems. This paper evaluates the performance of Python implementations with different libraries and compares it t...

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

    OpenAIRE

    Forrest Sheng Bao; Xin Liu; Christina Zhang

    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 ...

  10. An OpenModelica Python Interface and its use in PySimulator

    OpenAIRE

    Ganeson, Anand Kalaiarasi; Fritzson, Peter; Rogovchenko, Olena; Asghar, Adeel; Sjölund, Martin; Pfeiffer, Andreas

    2012-01-01

    How can Python users be empowered with the robust simulation, compilation and scripting abilities of a non-proprietary object-oriented, equation based modeling language such as Modelica? The immediate objective of this work is to develop an application programming interface for the OpenModelica modeling and simulation environment that would bridge the gap between the two agile programming languages Python and Modelica. The Python interface to OpenModelica – OMPython, is both a tool and a f...

  11. Design and Implementation of a User Friendly OpenModelica - Python interface

    OpenAIRE

    Ganeson, Anand

    2012-01-01

    How can Python users be empowered with the robust simulation, compilation and scripting abilities of a non-proprietary object-oriented, equation based modeling language such as Modelica? The immediate objective of this thesis work is to develop an application programming interface for the OpenModelica modeling and simulation environment that would bridge the gap between the two agile programming languages Python and Modelica. The Python interface to OpenModelica OMPython, is both a tool and a...

  12. Leveraging Python Interoperability Tools to Improve Sapphire's Usability

    Energy Technology Data Exchange (ETDEWEB)

    Gezahegne, A; Love, N S

    2007-12-10

    The Sapphire project at the Center for Applied Scientific Computing (CASC) develops and applies an extensive set of data mining algorithms for the analysis of large data sets. Sapphire's algorithms are currently available as a set of C++ libraries. However many users prefer higher level scripting languages such as Python for their ease of use and flexibility. In this report, we evaluate four interoperability tools for the purpose of wrapping Sapphire's core functionality with Python. Exposing Sapphire's functionality through a Python interface would increase its usability and connect its algorithms to existing Python tools.

  13. PYESSENCE - Generalised Coupled Quintessence Linear Perturbation Python Code - User Guide

    CERN Document Server

    Leithes, Alexander

    2016-01-01

    This paper is a guide to the installation and use of the Python package PYESSENCE. PYESSENCE is designed to evolve linear perturbations to Coupled Quintessence models with a arbitrary number of cold dark matter (CDM) fluids and dark energy (DE) scalar fields as dictated by a given model. The equations are sufficiently general to allow for more exotic dark matter with a non-zero equation of state. Several example uses are included in order to demonstrate typical functionality to the potential user. PYESSENCE is released under an open source modified BSD license and is available on Bitbucket.

  14. Ontopy : programmation orientée ontologie en Python

    OpenAIRE

    Lamy, Jean-Baptiste; Berthelot, Hélène

    2015-01-01

    Les ontologies et les modèles objets partagent un vocabulaire commun mais diffèrent dans leurs utilisations : l'ontologie permet d'effectuer des inférences et les modèles objets sont utilisés pour la programmation. Il est souvent nécessaire d'interfacer ontologie et programme objet. Plusieurs approches ont été proposées, de OWL API à la programmation orientée ontologie. Dans cet article, nous présentons Ontopy, un module de programmation orientée ontologie dynamique en Python, et nous prendro...

  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. Use of Python and Phoenix-M Interface in Robotics

    CERN Document Server

    Chakraborty, Shubham

    2011-01-01

    In this paper I will show how to use Python programming with a computer interface such as Phoenix-M 1 to drive simple robots. In my quest towards Artificial Intelligence(AI) I am experimenting with a lot of different possibilities in Robotics. This one will try to mimic the working of a simple insect's nervous system using hard wiring and some minimal software usage. This is the precursor to my advanced robotics and AI integration where I plan to use a new paradigm of AI based on Machine Learning and Self Consciousness via Knowledge Feedback and Update Process.

  17. Python GST Implementation v. 0.9 beta

    Energy Technology Data Exchange (ETDEWEB)

    2015-12-18

    PyGSTi is an implementation of Gate Set Tomography in the python programming language. Gate Set Tomography (GST) is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the "goodness" of qubits but also a means of debugging (i.e. improving) them.

  18. 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.

  19. Python text processing with NLTK 2.0 cookbook LITE

    CERN Document Server

    Perkins, Jacob

    2011-01-01

    The learn-by-doing approach of this book will enable you to dive right into the heart of text processing from the very first page. Each recipe is carefully designed to fulfill your appetite for Natural Language Processing. Packed with numerous illustrative examples and code samples, it will make the task of using the NLTK for Natural Language Processing easy and straightforward. This book is for Python programmers who want to quickly get to grips with using the NLTK for Natural Language Processing. Familiarity with basic text processing concepts is required. Programmers experienced in the NLTK

  20. Enrico : a Python package to simplify Fermi-LAT analysis

    OpenAIRE

    Sanchez, D. A.; Deil, C.

    2013-01-01

    With the advent of the Large Array Telescope (LAT) on board the Fermi satellite, a new window on the Universe has been opened. Publicly available, the Fermi-LAT data come together with an analysis software named ScienceTools (ST, http://fermi.gsfc.nasa.gov/ssc/data/analysis/software/) which can be run through a Python interface. Nevertheless, for the user, the ST can be hard to run and imply several steps. Users already contributed with scripts for a specific task but no tool allowing a compl...

  1. High performance Python for direct numerical simulations of turbulent flows

    OpenAIRE

    2016-01-01

    Direct Numerical Simulations (DNS) of the Navier Stokes equations is an invaluable research tool in fluid dynamics. Still, there are few publicly available research codes and, due to the heavy number crunching implied, available codes are usually written in low-level languages such as C/C++ or Fortran. In this paper we describe a pure scientific Python pseudo-spectral DNS code that nearly matches the performance of C++ for thousands of processors and billions of unknowns. We also describe a v...

  2. 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

  3. Use programming language Python for construction of knowledge bases and expert systems

    OpenAIRE

    Копей, Володимир Богданович; Семанишин, Леся Михайлівна

    2012-01-01

    On the basis of frames for knowledge representation have been proposed principles for the development of knowledge bases and expert systems on general-purpose programming language Python. Object-oriented and introspection capabilities of Python have been analyzed. The demo of knowledge base and the examples of querying to it have been developed

  4. 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....

  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. 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. .

  7. Conservative constraints on early cosmology with MONTE PYTHON

    International Nuclear Information System (INIS)

    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

  8. New Python-based methods for data processing

    International Nuclear Information System (INIS)

    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

  9. New Python-based methods for data processing

    Energy Technology Data Exchange (ETDEWEB)

    Sauter, Nicholas K., E-mail: nksauter@lbl.gov; Hattne, Johan; Grosse-Kunstleve, Ralf W.; Echols, Nathaniel [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 (United States)

    2013-07-01

    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{sup −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.

  10. precession: Dynamics of spinning black-hole binaries with python

    Science.gov (United States)

    Gerosa, Davide; Kesden, Michael

    2016-06-01

    We present the numerical code precession, a new open-source python module to study the dynamics of precessing black-hole binaries in the post-Newtonian regime. The code provides a comprehensive toolbox to (i) study the evolution of the black-hole spins along their precession cycles, (ii) perform gravitational-wave-driven binary inspirals using both orbit-averaged and precession-averaged integrations, and (iii) predict the properties of the merger remnant through fitting formulas obtained from numerical-relativity simulations. precession is a ready-to-use tool to add the black-hole spin dynamics to larger-scale numerical studies such as gravitational-wave parameter estimation codes, population synthesis models to predict gravitational-wave event rates, galaxy merger trees and cosmological simulations of structure formation. precession provides fast and reliable integration methods to propagate statistical samples of black-hole binaries from/to large separations where they form to/from small separations where they become detectable, thus linking gravitational-wave observations of spinning black-hole binaries to their astrophysical formation history. The code is also a useful tool to compute initial parameters for numerical-relativity simulations targeting specific precessing systems. precession can be installed from the python Package Index, and it is freely distributed under version control on github, where further documentation is provided.

  11. SClib, a hack for straightforward embedded C functions in Python

    CERN Document Server

    Fuentes, Esteban

    2014-01-01

    We present SClib, a simple hack that allows easy and straightforward evaluation of C functions within Python code, boosting flexibility for better trade-off between computation power and feature availability, such as visualization and existing computation routines in SciPy. We also present two cases were SClib has been used. In the first set of applications we use SClib to write a port to Python of a Schr\\"odinger equation solver that has been extensively used the literature, the resulting script presents a speed-up of about 150x with respect to the original one. A review of the situations where the speeded-up script has been used is presented. We also describe the solution to the related problem of solving a set of coupled Schr\\"odinger-like equations where SClib is used to implement the speed-critical parts of the code. We argue that when using SClib within IPython we can use NumPy and Matplotlib for the manipulation and visualization of the solutions in an interactive environment with no performance compro...

  12. Enrico : a Python package to simplify Fermi-LAT analysis

    CERN Document Server

    Sanchez, D A

    2013-01-01

    With the advent of the Large Array Telescope (LAT) on board the Fermi satellite, a new window on the Universe has been opened. Publicly available, the Fermi-LAT data come together with an analysis software named ScienceTools (ST, http://fermi.gsfc.nasa.gov/ssc/data/analysis/software/) which can be run through a Python interface. Nevertheless, for the user, the ST can be hard to run and imply several steps. Users already contributed with scripts for a specific task but no tool allowing a complete analysis is currently available. We present a Python package called {\\tt Enrico}, designed to facilitate the data analysis. Using only configuration files and front end tools from the command line, the user can easily perform/reproduce an entire Fermi analysis and make plots for publications. It also include new features like debug plots, pipeline execution on one or several CPUs, downloading of the Fermi data or the generation of a sky model from the Fermi catalogue. {\\tt Enrico} is an open-source project currently a...

  13. A Flexible Python Design for Analytic Modeling of Groundwater Flow

    Science.gov (United States)

    Bakker, M.

    2008-12-01

    We present a simple and flexible, object-oriented design for the modeling of groundwater flow using analytic elements in Python. The primary feature is that new analytic elements may be added to the code without the need to make any changes in the existing part of the code. The code consists of a Model class and an Element base class. Each new element is derived from the Element base class (or a derived class) and added to the model. Boundary conditions are implemented by each element itself, because they generate their own equations. Significant speed-up may be obtained through the use of FORTRAN extensions of the computationally intensive functions. Another way to increase performance is by grouping elements with same-type boundary conditions, although that requires changes to the existing code when elements with new boundary conditions are implemented. The described design has been applied successfully to three types of flow: steady multi-aquifer flow, transient periodic flow, and steady unsaturated flow. All systems include wells (point-sinks), line-sinks and circular inhomogeneities. Heads and velocities can be computed analytically at any point; path lines may be computed through numerical integration of the velocity field. The multi-aquifer code is the most extensive and includes many other features such as polygonal inhomogeneities and impermeable walls. Additional Python features make it very easy to create models; input scripts can be generated from GIS coverages of elements; high-quality and interactive graphical output is generated with the matplotlib package.

  14. 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.

  15. New Python-based methods for data processing.

    Science.gov (United States)

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

    2013-07-01

    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. PMID:23793153

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

    International Nuclear Information System (INIS)

    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.

  17. PyMidas--A Python Interface to ESO-MIDAS

    Science.gov (United States)

    Hook, R. N.; Maisala, S.; Oittinen, T.; Ullgren, M.; Vasko, K.; Savolainen, V.; Lindroos, J.; Anttila, M.; Solin, O.; Møller, P. M.; Banse, K.; Peron, M.

    2006-07-01

    Finland joined the European Southern Observatory in 2004, providing a contribution in kind of software expertise as part of its joining fee. This significant resource, called the Sampo project, will be devoted to exploring the options for the future of data reduction and analysis in an ESO context, to understanding user requirements and to performing a series of major pilot projects to investigate different technologies, approaches and architectures. The Sampo project {http://www.eso.org/sampo} will run for three years and aims to prepare the ESO community for the data analysis and reduction challenges of the next decades. The first major Sampo project is PyMidas, an interface from Python to the ESO-MIDAS data analysis and reduction system. This paper describes the motivation for this project, how it has been implemented and gives some examples of PyMidas in action.

  18. 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.

  19. 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).

  20. PyORBIT: A Python Shell For ORBIT

    International Nuclear Information System (INIS)

    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

  1. PyGSM: Python interface to the Global Sky Model

    Science.gov (United States)

    Price, Danny C.

    2016-03-01

    PyGSM is a Python interface for the Global Sky Model (GSM, ascl:1011.010). The GSM is a model of diffuse galactic radio emission, constructed from a variety of all-sky surveys spanning the radio band (e.g. Haslam and WMAP). PyGSM uses the GSM to generate all-sky maps in Healpix format of diffuse Galactic radio emission from 10 MHz to 94 GHz. The PyGSM module provides visualization utilities, file output in FITS format, and the ability to generate observed skies for a given location and date. PyGSM requires Healpy, PyEphem (ascl:1112.014), and AstroPy (ascl:1304.002).

  2. Překladač podmnožiny jazyka Python

    OpenAIRE

    Falhar, Radek

    2014-01-01

    Python  je  dynamicky  typovaný,  interpretovaný  programovací  jazyk.  Díky  dynamickému  typovému systému je tedy obtížné jej zkompilovat do statického zdrojového kódu. Tedy kódu, kde je přesně dáno,jaké typy existují a jaká je jejich struktůra. Existuje několik způsobů jak tohoto dosáhnout a jedním z primárních  je  typová  inference.  Tento  přístup  se  snaží  určit  struktura  typů &...

  3. PYTRANSIT: fast and easy exoplanet transit modelling in PYTHON

    Science.gov (United States)

    Parviainen, Hannu

    2015-07-01

    We present a fast and user friendly exoplanet transit light-curve modelling package PYTRANSIT, implementing optimized versions of the Giménez and Mandel & Agol transit models. The package offers an object-oriented PYTHON interface to access the two models implemented natively in FORTRAN with OpenMP parallelization. A partial OpenCL version of the quadratic Mandel-Agol model is also included for GPU-accelerated computations. The aim of PYTRANSIT is to facilitate the analysis of photometric time series of exoplanet transits consisting of hundreds of thousands of data points, and of multipassband transit light curves from spectrophotometric observations, as a part of a researcher's programming toolkit for building complex, problem-specific analyses.

  4. PyRAT (python radiography analysis tool): overview

    Energy Technology Data Exchange (ETDEWEB)

    Armstrong, Jerawan C [Los Alamos National Laboratory; Temple, Brian A [Los Alamos National Laboratory; Buescher, Kevin L [Los Alamos National Laboratory

    2011-01-14

    PyRAT was developed as a quantitative tool for robustly characterizing objects from radiographs to solve problems such as the hybrid nonlinear inverse problem. The optimization software library that was used is the nonsmooth optimization by MADS algorithm (NOMAD). Some of PyRAT's features are: (1) hybrid nonlinear inverse problem with calculated x-ray spectrum and detector response; (2) optimization based inversion approach with goal of identifying unknown object configurations - MVO problem; (3) using functionalities of Python libraries for radiographic image processing and analysis; (4) using the Tikhonov regularization method of linear inverse problem to recover partial information of object configurations; (5) using a priori knowledge of problem solutions to define feasible region and discrete neighbor for the MVO problem - initial data analysis + material library {yields} a priori knowledge; and (6) using the NOMAD (C++ version) software in the object.

  5. DNest4: Diffusive Nested Sampling in C++ and Python

    CERN Document Server

    Brewer, Brendon J

    2016-01-01

    In probabilistic (Bayesian) inferences, we typically want to compute properties of the posterior distribution, describing knowledge of unknown quantities in the context of a particular dataset and the assumed prior information. The marginal likelihood, also known as the "evidence", is a key quantity in Bayesian model selection. The Diffusive Nested Sampling algorithm, a variant of Nested Sampling, is a powerful tool for generating posterior samples and estimating marginal likelihoods. It is effective at solving complex problems including many where the posterior distribution is multimodal or has strong dependencies between variables. DNest4 is an open source (MIT licensed), multi-threaded implementation of this algorithm in C++11, along with associated utilities including: i) RJObject, a class template for finite mixture models, (ii) A Python package allowing basic use without C++ coding, and iii) Experimental support for models implemented in Julia. In this paper we demonstrate DNest4 usage through examples ...

  6. 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.

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

    International Nuclear Information System (INIS)

    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)

  8. Python 解析XML文件的软件实现

    Institute of Scientific and Technical Information of China (English)

    宋汉宏

    2015-01-01

    在民用航空电子产品的测试过程中,需要用 Python 对 XML 文件的数据进行解析。本文首先介绍了 Python 语言特点,然后给出Python解析XML文件的软件实现,最后总结了 XML 文件以及 Python语言在测试领域中的应用越来越多,使得用 Python 解析 XML 文件显得越来越重要。

  9. Performance of Python runtimes on a non-numeric scientific code

    OpenAIRE

    Murri, Riccardo

    2014-01-01

    The Python library FatGHol FatGHoL used in Murri2012 to reckon the rational homology of the moduli space of Riemann surfaces is an example of a non-numeric scientific code: most of the processing it does is generating graphs (represented by complex Python objects) and computing their isomorphisms (a triple of Python lists; again a nested data structure). These operations are repeated many times over: for example, the spaces and are triangulated by 4'583'322 and 747'664 graphs, respectively. T...

  10. SunPy: Python for Solar Physics. An implementation for local correlation tracking

    OpenAIRE

    Campos Rozo, J. I.; Vargas Dominguez, Santiago

    2014-01-01

    Python programming language has experienced a great progress and growing use in the scientific community in the last years as well as a direct impact on solar physics. Python is a very mature language and almost any fundamental feature you might want to do is already implemented in a library or module. SunPy is a common effort of, using the advantages of Python, developing tools to be applied for processing and analysis of solar data. In this work we present a particular developm...

  11. 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...

  12. 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...

  13. Multi Scale Investigation of Surface Topography of Ball Python (Python Regius) Shed Skin in Comparison to Human skin

    CERN Document Server

    Abdel-Aal, H A; Mezghani, S; 10.1007/s11249-009-9547-y

    2010-01-01

    Constructing a surface that is an integral part of the function of tribosystems (deterministic surface) is an intriguing goal. Inspirations for such surfaces come from studying natural systems and deducing design rules. The major attraction is that natural systems, while functionally complex, are, in general, of optimized shape and performance. It is further believed that functional complexity of natural systems is what affords natural species to morph continuously to adapt with the operating environment. One bio-species that is of interest is the Ball Python. This is because such a species continuously slides against various surfaces, many of which are deemed tribologically hostile, without sustaining much damage. Much of the success of that species in adapting to its environment is attributed to surface design features. In that respect, studying these features and how do they contribute to the control of friction and wear is very attractive. This paper is a step in this direction. In this work we apply a mu...

  14. Modernizing the ESRF beamline application software architecture with generic Python modules

    OpenAIRE

    Klora, Jorg

    2002-01-01

    We report on the modernization of the ESRF beamline application software with Python modules. The current building blocks used around the SPEC data acquisition software together with the new elements are presented.

  15. 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. 

  16. 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.

  17. 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.

  18. 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.

  19. Sharma′s python sign: A New tubal sign in female genital tuberculosis

    Directory of Open Access Journals (Sweden)

    Jai Bhagwan Sharma

    2016-01-01

    Full Text Available Female genital tuberculosis (FGTB is an important cause of infertility in developing countries. Various type of TB salpingitis can be endosalpingitis, exosalpingitis, interstitial TB salpingitis, and salpingitis isthmica nodosa. The fallopian tubes are thickened enlarged and tortuous. Unilateral or bilateral hydrosalpinx or pyosalpinx may be formed. A new sign python sign is presented in which fallopian tube looks like a blue python on dye testing in FGTB.

  20. Sharma's Python Sign: A New Tubal Sign in Female Genital Tuberculosis.

    Science.gov (United States)

    Sharma, Jai Bhagwan

    2016-01-01

    Female genital tuberculosis (FGTB) is an important cause of infertility in developing countries. Various type of TB salpingitis can be endosalpingitis, exosalpingitis, interstitial TB salpingitis, and salpingitis isthmica nodosa. The fallopian tubes are thickened enlarged and tortuous. Unilateral or bilateral hydrosalpinx or pyosalpinx may be formed. A new sign python sign is presented in which fallopian tube looks like a blue python on dye testing in FGTB. PMID:27365923

  1. Simplifying Parallelization of Scientific Codes by a Function-Centric Approach in Python

    OpenAIRE

    Nilsen, Jon K.; Cai, Xing; Hoyland, Bjorn; Langtangen, Hans Petter

    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 parallel communication is implemented. We provide specific examples on such layers of code, and these examples may 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 ...

  2. Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit

    OpenAIRE

    Morley Chris; O'Boyle Noel M; Hutchison Geoffrey R

    2008-01-01

    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...

  3. Benchmarking Python Interpreters : Measuring Performance of CPython, Cython, Jython and PyPy

    OpenAIRE

    Roghult, Alexander

    2016-01-01

    For the Python programming language there are several different interpreters and implementations. In this thesis project the performance regarding execution time is evaluated for four of these; CPython, Cython, Jython and PyPy. The performance was measured in a test suite, created during the project, comprised of tests for Python dictionaries, lists, tuples, generators and objects. Each test was run with both integers and objects as test data with varying problem size. Each test was implement...

  4. Sharma's Python Sign: A New Tubal Sign in Female Genital Tuberculosis

    Science.gov (United States)

    Sharma, Jai Bhagwan

    2016-01-01

    Female genital tuberculosis (FGTB) is an important cause of infertility in developing countries. Various type of TB salpingitis can be endosalpingitis, exosalpingitis, interstitial TB salpingitis, and salpingitis isthmica nodosa. The fallopian tubes are thickened enlarged and tortuous. Unilateral or bilateral hydrosalpinx or pyosalpinx may be formed. A new sign python sign is presented in which fallopian tube looks like a blue python on dye testing in FGTB. PMID:27365923

  5. 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.

  6. Python 3.0抢“鲜”体验——兼谈Python 3.0的历史、现状和未来

    Institute of Scientific and Technical Information of China (English)

    赖勇浩

    2007-01-01

    2007年8月31日,Python 3.0版本终于发布了第一个alpha版本。这是一个充满历史意义的日子,意味着之前经常彼人称为Python 3000的Python 3.0走进了现实。Python的设计者Guido van Rossum在加盟Google后宣称有一半的工作时间用以完成Python 3.0的开发,宽裕的自由时间让Guido实现众多新特性成为可能。回味一下Python 3.0的过去,了解它所经历的风风雨雨,在Python 3.0这第一个alpha版本发布之际具有独特意义。

  7. batman: BAsic Transit Model cAlculatioN in Python

    CERN Document Server

    Kreidberg, Laura

    2015-01-01

    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.

  8. 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 and eclipse 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 s 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.

  9. 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.

  10. MCPB.py: A Python Based Metal Center Parameter Builder.

    Science.gov (United States)

    Li, Pengfei; Merz, Kenneth M

    2016-04-25

    MCPB.py, a python based metal center parameter builder, has been developed to build force fields for the simulation of metal complexes employing the bonded model approach. It has an optimized code structure, with far fewer required steps than the previous developed MCPB program. It supports various AMBER force fields and more than 80 metal ions. A series of parametrization schemes to derive force constants and charge parameters are available within the program. We give two examples (one metalloprotein example and one organometallic compound example), indicating the program's ability to build reliable force fields for different metal ion containing complexes. The original version was released with AmberTools15. It is provided via the GNU General Public License v3.0 (GNU_GPL_v3) agreement and is free to download and distribute. MCPB.py provides a bridge between quantum mechanical calculations and molecular dynamics simulation software packages thereby enabling the modeling of metal ion centers. It offers an entry into simulating metal ions in a number of situations by providing an efficient way for researchers to handle the vagaries and difficulties associated with metal ion modeling. PMID:26913476

  11. PRECESSION. Dynamics of spinning black-hole binaries with python

    CERN Document Server

    Gerosa, Davide

    2016-01-01

    We present the numerical code PRECESSION: a new open-source python module to study the dynamics of precessing black-hole binaries in the post-Newtonian regime. The code provides a comprehensive toolbox to (i) study the evolution of the black-hole spins along their precession cycles, (ii) perform gravitational-wave driven binary inspirals using both orbit-averaged and precession-averaged integrations, and (iii) predict the properties of the merger remnant through fitting formulae obtained from numerical-relativity simulations. PRECESSION is a ready-to-use tool to add the black-hole spin dynamics to larger-scale numerical studies such as gravitational-wave parameter estimation codes, population synthesis models to predict gravitational-wave event rates, galaxy merger trees and cosmological simulations of structure formation. PRECESSION provides fast and reliable integration methods to propagate statistical samples of black-hole binaries from/to large separations where they form to/from small separations where t...

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

    Science.gov (United States)

    Houska, Tobias; Kraft, Philipp; Chamorro-Chavez, Alejandro; Breuer, Lutz

    2015-01-01

    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. PMID:26680783

  13. 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.

  14. Gammapy - A Python package for {\\gamma}-ray astronomy

    CERN Document Server

    Donath, Axel; Arribas, Manuel P; King, Johannes; Owen, Ellis; Terrier, Régis; Reichardt, Ignasi; Harris, Jon; Bühler, Rolf; Klepser, Stefan

    2015-01-01

    In the past decade imaging atmospheric Cherenkov telescope arrays such as H.E.S.S., MAGIC, VERITAS, as well as the Fermi-LAT space telescope have provided us with detailed images and spectra of the {\\gamma}-ray universe for the first time. Currently the {\\gamma}-ray community is preparing to build the next-generation Cherenkov Telecope Array (CTA), which will be operated as an open observatory. Gammapy (available at https://github.com/gammapy/gammapy under the open-source BSD li- cense) is a new in-development Astropy affiliated package for high-level analysis and simulation of astronomical {\\gamma}-ray data. It is built on the scientific Python stack (Numpy, Scipy, matplotlib and scikit-image) and makes use of other open-source astronomy packages such as Astropy, Sherpa and Naima to provide a flexible set of tools for {\\gamma}-ray astronomers. We present an overview of the current Gammapy features and example analyses on real as well as simulated {\\gamma}-ray datasets. We would like Gammapy to become a commu...

  15. Cluster-lensing: A Python Package for Galaxy Clusters & Miscentering

    CERN Document Server

    Ford, Jes

    2016-01-01

    We describe a new open source package for calculating properties of galaxy clusters, including NFW halo profiles with and without the effects of cluster miscentering. This pure-Python package, cluster-lensing, provides well-documented and easy-to-use classes and functions for calculating cluster scaling relations, including mass-richness and mass-concentration relations from the literature, as well as the surface mass density $\\Sigma(R)$ and differential surface mass density $\\Delta\\Sigma(R)$ profiles, probed by weak lensing magnification and shear. Galaxy cluster miscentering is especially a concern for stacked weak lensing shear studies of galaxy clusters, where offsets between the assumed and the true underlying matter distribution can lead to a significant bias in the mass estimates if not accounted for. This software has been developed and released in a public GitHub repository, and is licensed under the permissive MIT license. The cluster-lensing package is archived on Zenodo (Ford 2016). Full documenta...

  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. PMID:25381290

  17. Py4CAtS - Python Tools for Line-by-Line Modelling of Infrared Atmospheric Radiative Transfer

    OpenAIRE

    Schreier, Franz; Gimeno Garcia, Sebastian

    2013-01-01

    Py4CAtS — Python scripts for Computational ATmospheric Spectroscopy is a Python re-implementation of the Fortran infrared radiative transfer code GARLIC, where compute-intensive code sections utilize the Numeric/Scientific Python modules for highly optimized array-processing. The individual steps of an infrared or microwave radiative transfer computation are implemented in separate scripts to extract lines of relevant molecules in the spectral range of interest, to compute line-by-line cross ...

  18. Python Regius (Ball Python) shed skin: Biomimetic analogue for function-targeted design of tribo-surfaces

    CERN Document Server

    Abdel-Aal, H A; Gebeshuber, I C

    2010-01-01

    A major concern in designing tribo-systems is to minimize friction, save energy, and to reduce wear. Satisfying these requirements depends on the integrity of the rubbing surface and its suitability to sliding conditions. As such, designers currently focus on constructing surfaces that are an integral part of the function of the tribo-system. Inspirations for such constructs come from studying natural systems and from implementing natural design rules. One species that may serve as an analogue for design is the Ball python. This is because such a creature while depending on legless locomotion when sliding against various surfaces, many of which are deemed tribologically hostile, doesn't sustain much damage. Resistance to damage in this case originates from surface design features. As such, studying these features and how do they contribute to the control of friction and wear is very attractive for design purposes. In this work we apply a multi scale surface characterization approach to study surface design fe...

  19. seismic-py: Reading seismic data with Python

    Directory of Open Access Journals (Sweden)

    2008-08-01

    Full Text Available The field of seismic exploration of the Earth has changed
    dramatically over the last half a century. The Society of Exploration
    Geophysicists (SEG has worked to create standards to store the vast
    amounts of seismic data in a way that will be portable across computer
    architectures. However, it has been impossible to predict the needs of the
    immense range of seismic data acquisition systems. As a result, vendors have
    had to bend the rules to accommodate the needs of new instruments and
    experiment types. For low level access to seismic data, there is need for a
    standard open source library to allow access to a wide range of vendor data
    files that can handle all of the variations. A new seismic software package,
    seismic-py, provides an infrastructure for creating and managing drivers for
    each particular format. Drivers can be derived from one of the known formats
    and altered to handle any slight variations. Alternatively drivers can be
    developed from scratch for formats that are very different from any previously
    defined format. Python has been the key to making driver development easy
    and efficient to implement. The goal of seismic-py is to be the base system
    that will power a wide range of experimentation with seismic data and at the
    same time provide clear documentation for the historical record of seismic
    data formats.

  20. 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.

  1. 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.

  2. A Python-based Post-processing Toolset For Seismic Analyses

    CERN Document Server

    Brasier, Steve

    2014-01-01

    This paper discusses the design and implementation of a Python-based toolset to aid in assessing the response of the UK's Advanced Gas Reactor nuclear power stations to earthquakes. The seismic analyses themselves are carried out with a commercial Finite Element solver, but understanding the raw model output this produces requires customised post-processing and visualisation tools. Extending the existing tools had become increasingly difficult and a decision was made to develop a new, Python-based toolset. This comprises of a post-processing framework (aftershock) which includes an embedded Python interpreter, and a plotting package (afterplot) based on numpy and matplotlib. The new toolset had to be significantly more flexible and easier to maintain than the existing code-base, while allowing the majority of development to be carried out by engineers with little training in software development. The resulting architecture will be described with a focus on exploring how the design drivers were met and the suc...

  3. 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

  4. 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/. PMID:25974373

  5. Object-oriented implementations of the MPDATA advection equation solver in C++, Python and Fortran

    CERN Document Server

    Arabas, Sylwester; Jaruga, Anna; Fijałkowski, Maciej

    2013-01-01

    Three object-oriented implementations of a prototype solver of the advection equation are introduced. Presented programs are based on Blitz++ (C++), NumPy (Python), and Fortran's built-in array containers. The solvers include an implementation of the Multidimensional Positive-Definite Advective Transport Algorithm (MPDATA). The introduced codes exemplify how the application of object-oriented programming (OOP) techniques allows to reproduce the mathematical notation used in the literature within the program code. The introduced codes serve as a basis for discussion on the tradeoffs of the programming language choice. The main angles of comparison are code brevity and syntax clarity (and hence maintainability and auditability) as well as performance. In case of Python, a significant performance gain is observed when switching from the standard interpreter (CPython) to the PyPy implementation of Python. Entire source code of all three implementations is embedded in the text and is licensed under the terms of th...

  6. 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.

  7. Parallel selective pressures drive convergent diversification of phenotypes in pythons and boas.

    Science.gov (United States)

    Esquerré, Damien; Scott Keogh, J

    2016-07-01

    Pythons and boas are globally distributed and distantly related radiations with remarkable phenotypic and ecological diversity. We tested whether pythons, boas and their relatives have evolved convergent phenotypes when they display similar ecology. We collected geometric morphometric data on head shape for 1073 specimens representing over 80% of species. We show that these two groups display strong and widespread convergence when they occupy equivalent ecological niches and that the history of phenotypic evolution strongly matches the history of ecological diversification, suggesting that both processes are strongly coupled. These results are consistent with replicated adaptive radiation in both groups. We argue that strong selective pressures related to habitat-use have driven this convergence. Pythons and boas provide a new model system for the study of macro-evolutionary patterns of morphological and ecological evolution and they do so at a deeper level of divergence and global scale than any well-established adaptive radiation model systems. PMID:27264195

  8. PyTransport: A Python package for the calculation of inflationary correlation functions

    CERN Document Server

    Mulryne, David J

    2016-01-01

    PyTransport constitutes a straightforward code written in C++ together with Python scripts which automatically edit, compile and run the C++ code as a Python module. It has been written for Unix-like systems (OS X and Linux). Primarily the module employs the transport approach to inflationary cosmology to calculate the tree-level power-spectrum and bispectrum of user specified models of multi-field inflation, accounting for all sub and super-horizon effects. The transport method we utilise means only coupled differential equations need to be solved, and the implementation presented here combines the speed of C++ with the functionality and convenience of Python. At present the code is restricted to canonical models. This document details the code and illustrates how to use it with a worked example.

  9. 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.

  10. 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

  11. An intuitive Python interface for Bioconductor libraries demonstrates the utility of language translators

    DEFF Research Database (Denmark)

    Gautier, Laurent

    2010-01-01

    given task to be implemented. The Bioconductor project, based on the R language, has become a reference for the numerical processing and statistical analysis of data coming from high-throughput biological assays, providing a rich selection of methods and algorithms to the research community. At the same...... time, Python has matured as a rich and reliable language for the agile development of prototypes or final implementations, as well as for handling large data sets. Results The data structures and functions from Bioconductor can be exposed to Python as a regular library. This allows a fully transparent...

  12. Python y OpenCV aplicados a un caso de estudio real

    OpenAIRE

    García del Arco, José Antonio

    2015-01-01

    Este trabajo se centra en el uso del lenguaje Python y la librería OpenCV de visión por computador para el seguimiento de crustáceos marinos en condiciones experimentales y determinar su comportamiento en un entorno social. Aquest treball es centra en l'ús del llenguatge Python i la llibreria OpenCV de visió per computador per al seguiment de crustacis marins en condicions experimentals i determinar el seu comportament en un entorn social.

  13. ModFossa: A library for modeling ion channels using Python.

    Science.gov (United States)

    Ferneyhough, Gareth B; Thibealut, Corey M; Dascalu, Sergiu M; Harris, Frederick C

    2016-06-01

    The creation and simulation of ion channel models using continuous-time Markov processes is a powerful and well-used tool in the field of electrophysiology and ion channel research. While several software packages exist for the purpose of ion channel modeling, most are GUI based, and none are available as a Python library. In an attempt to provide an easy-to-use, yet powerful Markov model-based ion channel simulator, we have developed ModFossa, a Python library supporting easy model creation and stimulus definition, complete with a fast numerical solver, and attractive vector graphics plotting. PMID:26932271

  14. Enhancements to Ginga: a Python Package for Building Astronomical Data Viewers

    Science.gov (United States)

    Jeschke, E.; Inagaki, T.; Kackley, R.

    2015-09-01

    Ginga is a toolkit for building astronomical image viewers. The package is available under a BSD license at github.com and has undergone continuous development since its introduction at ADASS 2012. The package may may be of interest to software developers who are looking for a solution for integrating FITS or numpy-based data visualization into their python programs and end users interested in FITS viewers (via the example reference viewer). We present the updates and enhanced capabilities of the package, including: support for additional GUI toolkits, WCS-based image mosaicing, image overlays, customizable user interface bindings, support for python3 and more.

  15. 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

  16. 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

  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. PMID:27111016

  18. Developing Communication Monitor System of Cluster Network with Python and GTK%用Python+GTK开发机群网络通信监控系统

    Institute of Scientific and Technical Information of China (English)

    赵毅; 马捷

    2003-01-01

    文中介绍了Python语言、GTK图形包、Glade图形界面生成器以及用Python+GTK开发GUI程序的方法.同时描述了机群网络通信监控系统的功能和结构,并对开发过程中的几个关键技术进行了详细阐述.

  19. 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 pr...... convenient platform for researchers in compressed sensing aiming at obtaining a high degree of reproducibility of their research....

  20. 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.

  1. A Python Class for Higher-Dimensional Schr\\"odinger Equations

    CERN Document Server

    Noreen, Amna

    2015-01-01

    We announce a Python class for numerical solution of Schr{\\"o}dinger equations in one or more space dimensions, employing some recently developed general classes for numerical solution of partial differential equations, and routines from \\texttt{numpy} and \\texttt{scipy.sparse.linalg} (or \\texttt{scipy.linalg} for smaller problems).

  2. Automating Geographic Information Systems (GIS) through Python for the Hydrological Sciences

    Science.gov (United States)

    Madsen, K.

    2013-12-01

    Geographic Information Systems (GIS) have many applications in the hydrological sciences. However, GIS software is often expensive and difficult to automate. This paper will demonstrate how to automate GRASS GIS software using the Python programming language. Both GRASS GIS and Python are open source projects that are free for anyone to use. Automation of GIS processes is important when dealing with large-scale geographic studies, as large GIS maps are usually divided into discrete tiles. When conducting GIS transformations on such maps, the user must repeat the action for each tile, a process that is greatly expedited through automation. The paper will work through several examples of automated GIS processes and provide complete Python codes that demonstrate correct syntax for working with GRASS GIS applications. The provided examples will demonstrate automation of the following processes 1.) using raster math to calculate foliage thickness from LIDAR and DEM data; 2.) conducting raster interpolation from a set of vector points to develop a continuous hydraulic conductivity coverage; 3.) automating raster coloration to sync the coloration of a large number of raster tiles for website display, and 4.) constructing contoured vector lines from topography rasters. These examples programs will serve as the building blocks for readers, giving them the tools to automate any GIS process using Python and GRASS GIS.

  3. PyMercury: Interactive Python for the Mercury Monte Carlo Particle Transport Code

    Energy Technology Data Exchange (ETDEWEB)

    Iandola, F N; O' Brien, M J; Procassini, R J

    2010-11-29

    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.

  4. PCSIM: a parallel simulation environment for neural circuits fully integrated with Python

    Directory of Open Access Journals (Sweden)

    Dejan Pecevski

    2009-05-01

    Full Text Available The Parallel Circuit SIMulator (PCSIM is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations.

  5. Data Flow of a Multiple Instrument On-Demand Processing Engine with Python and DPLKIT

    Science.gov (United States)

    Garcia, Joseph P.; Eloranta, Edwin; Garcia, Raymond K.

    2016-06-01

    The University of Wisconsin LIDAR Group's High Spectral Resolution LIDAR on-demand data website and processing codebase uses Python to explore coding techniques which facilitate a flexible codebase that is reusable for various outputs, cooperative multi-instrument products, and retains stability and maintainability without hindering dynamic experimentation.

  6. Python-based framework for coupled MC-TH reactor calculations

    International Nuclear Information System (INIS)

    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

  7. History Revenged: Monty Python Translates Chretien de Troyes's "Perceval, or the Story of the Grail" (Again).

    Science.gov (United States)

    Murrell, Elizabeth

    1998-01-01

    Finds "Monty Python and the Holy Grail" functions as a "surprisingly accurate cultural translation" of de Troyes's "Perceval" text. Suggests that using such films helps students open a door upon film studies and discursive studies that will serve them well as they adapt to their own historical moment. (PA)

  8. Výuka programování v jazyce Python

    OpenAIRE

    FORTELKA, Tomáš

    2010-01-01

    The target of this Bachelor thesis is to create a training-lesson's collection, which will be usable for teaching object oriented programing in high schools and also in universities. The Python language is dynamic object oriented language, which has, beside using in practice, very good response also as the language used in the preliminary courses object oriented programing.

  9. 77 FR 3329 - Injurious Wildlife Species; Listing Three Python Species and One Anaconda Species as Injurious...

    Science.gov (United States)

    2012-01-23

    ..., 2010, we published a proposed rule in the Federal Register (75 FR 11808) to list Python molurus (which... inquiry in the Federal Register (73 FR 5784; January 31, 2008) soliciting available biological, economic... (75 FR 38069; July 1, 2010). For the injurious wildlife evaluation in this final rule, in addition...

  10. PyMercury: Interactive Python for the Mercury Monte Carlo Particle Transport Code

    International Nuclear Information System (INIS)

    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.

  11. 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…

  12. HOPE: A Python Just-In-Time compiler for astrophysical computations

    CERN Document Server

    Akeret, Joel; Amara, Adam; Refregier, Alexandre

    2014-01-01

    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 n...

  13. 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.

  14. Integrating three lake models into a Phytoplankton Prediction System for Lake Taihu (Taihu PPS) with Python

    NARCIS (Netherlands)

    Huang, J.C.; Gao, J.F.; Hormann, 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. ‘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.

  16. Py-oopsi: the python implementation of the fast-oopsi algorithm

    OpenAIRE

    Liu, Benyuan

    2014-01-01

    Fast-oopsi was developed by Joshua Vogelstein in 2009, which is now widely used to extract neuron spike activities from calcium fluorescence signals. Here, we propose detailed implementation of the fast-oopsi algorithm in python programming language. Some corrections are also made to the original fast-oopsi paper.

  17. Identification and comparison of marbofloxacin metabolites from the plasma of ball pythons (Python regius) and blue and gold macaws (Ara ararauna).

    Science.gov (United States)

    Hunter, R P; Koch, D E; Coke, R L; Carpenter, J W; Isaza, R

    2007-06-01

    Marbofloxacin is a veterinary only, synthetic, broad spectrum fluoroquinolone antimicrobial agent. In mammals, approximately 40% of the oral dose of marbofloxacin is excreted unchanged in the urine; the remaining is excreted via the bile as unchanged drug in the feces. The Vd ranges from 1.1 (cattle) to 1.3 (dog, goat, swine) L/kg. Because of extra-label use of marbofloxacin in birds and reptiles, this study was designed to determine the profile of metabolites in plasma and compare the circulating metabolite profile between a reptile and an avian species. Six adult ball pythons (Python regius) and 10 blue and gold macaws (Ara ararauna) were used in this study. The macaws were dosed both i.v. and p.o. with a single 2.5 mg/kg administration where as the pythons received a single 10 mg/kg dose both i.v. and p.o. The metabolite profiles of marbofloxacin in the plasma of these species were determined using a high performance liquid chromatography system with a mass spectrometer for detection (LC/MS/MS). Mass spectra data generated from the snake and bird plasma samples were compared with previously reported LC/MS/MS mass spectral data. Evidence does not suggest differences due to route of administration (i.v. vs. p.o.) in either species. Four chromatographic peaks with resulting daughter spectrum were identified and represent 12 possible metabolite structures. All of the proposed metabolites, except for the N-oxide, appear to be unique to macaws. The potential metabolites identified in macaws appear to be very different than those reported for chickens. PMID:17472658

  18. 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

  19. 基于 Python 语言的 Add -In 开发应用%The Development and Application of Add-In Based on Python Language

    Institute of Scientific and Technical Information of China (English)

    张玉群; 朱道壮

    2014-01-01

    By introducing the process method of Python language menu developmentusing Add-In plugins in ArcGIS, proposed in ArcGIS for data processing, to guide developers to use a simple way of development.%通过简要介绍Python语言在ArcGIS中采用Add-In插件进行菜单开发的流程,提出了在ArcGIS进行数据处理时,开发人员应使用的一种简便易行的开发方式。

  20. Programovací jazyk Python a účelnosť jeho zaradenia do výučby

    OpenAIRE

    Arendáč, Tomáš

    2011-01-01

    This thesis is concerned by programming language Python and its suitability of his assignment to the tuition. The work is divided into three dominant parts. The first part describes programming language Python, its elementary characteristics and features. The purpose is to introduce its properties to the reader so that he could estimate if there is point in the deeper concern. There are elements of object-oriented programming in description, too. The second part analyses programming language ...

  1. 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.

  2. Optimizing Python-based ROOT I/O with PyPy's Tracing JIT

    CERN Document Server

    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.

  3. 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.

  4. InfraPy: Python-Based Signal Analysis Tools for Infrasound

    Energy Technology Data Exchange (ETDEWEB)

    Blom, Philip Stephen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Marcillo, Omar Eduardo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Euler, Garrett Gene [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-31

    InfraPy is a Python-based analysis toolkit being development at LANL. The algorithms are intended for ground-based nuclear detonation detection applications to detect, locate, and characterize explosive sources using infrasonic observations. The implementation is usable as a stand-alone Python library or as a command line driven tool operating directly on a database. With multiple scientists working on the project, we've begun using a LANL git repository for collaborative development and version control. Current and planned work on InfraPy focuses on the development of new algorithms and propagation models. Collaboration with Southern Methodist University (SMU) has helped identify bugs and limitations of the algorithms. The current focus of usage development is focused on library imports and CLI.

  5. pyFRET: A Python Library for Single Molecule Fluorescence Data Analysis

    CERN Document Server

    Murphy, Rebecca R; Klenerman, David

    2014-01-01

    Single molecule F\\"orster resonance energy transfer (smFRET) is a powerful experimental technique for studying the properties of individual biological molecules in solution. However, as adoption of smFRET techniques becomes more widespread, the lack of available software, whether open source or commercial, for data analysis, is becoming a significant issue. Here, we present pyFRET, an open source Python package for the analysis of data from single-molecule fluorescence experiments from freely diffusing biomolecules. The package provides methods for the complete analysis of a smFRET dataset, from burst selection and denoising, through data visualisation and model fitting. We provide support for both continuous excitation and alternating laser excitation (ALEX) data analysis. pyFRET is available as a package downloadable from the Python Package Index (PyPI) under the open source three-clause BSD licence, together with links to extensive documentation and tutorials, including example usage and test data. Additio...

  6. ExoData: A python package to handle large exoplanet catalogue data

    CERN Document Server

    Varley, Ryan

    2015-01-01

    Exoplanet science often involves using the system parameters of real exoplanets for tasks such as simulations, fitting routines, and target selection for proposals. Software that bridges the barrier between the catalogues and code enables users to improve the specific repeatability of results by facilitating the retrieval of exact system parameters used in an articles results along with unifying the equations and software used. As exoplanet science moves towards large data, gone are the days where researchers can recall the current population from memory. An interface able to query the population now becomes invaluable for target selection and population analysis. ExoData is a python interface and exploratory analysis tool for the Open Exoplanet Catalogue. It allows the loading of exoplanet systems into python as objects (Planet, Star, Binary etc) from which common orbital and system equations can be calculated and measured parameters retrieved. This allows researchers to use tested code of the common equatio...

  7. Modular Python-based Code for Thomson Scattering System on NSTX-U

    Science.gov (United States)

    Horowitz, Benjamin; Diallo, Ahmed; Feibush, Eliot; Leblanc, Benoit

    2013-10-01

    Fast accurate and reliable measurements of electron temperature and density profiles within magnetically confined plasmas are essential for full operation of fusion devices. We detail the design and implementation of a modular Pythonbased code for the Thomson Scattering diagnostic system of NSTX-U which offers improvements in speed by making full use of the Python's architecture, open-source module packages, and ability to be parallelized across many processors. SciPy's weave package allows the implementation of C/C++ code within our program to clear up bottlenecks in data fitting while not loosing the flexibility and clarity of Python, while Numpy and MatplotLib allow calculations and plotting of the processed data. Using the standard MDSplus input, we create a flexible and expandable algorithm structure which can be implemented on any fusion device utilizing polychromator-based Thomson scattering diagnostic system. Supported by DOE SULI Fellowship at Princeton Plasma Physics Lab.

  8. 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.

  9. 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....

  10. 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....

  11. Pyrcca: regularized kernel canonical correlation analysis in Python and its applications to neuroimaging

    OpenAIRE

    Bilenko, Natalia Y.; Gallant, Jack L.

    2015-01-01

    Canonical correlation analysis (CCA) is a valuable method for interpreting cross-covariance across related datasets of different dimensionality. There are many potential applications of CCA to neuroimaging data analysis. For instance, CCA can be used for finding functional similarities across fMRI datasets collected from multiple subjects without resampling individual datasets to a template anatomy. In this paper, we introduce Pyrcca, an open-source Python module for executing CCA between two...

  12. 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; Casilari, E.

    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...

  13. PCSIM: a parallel simulation environment for neural circuits fully integrated with Python

    OpenAIRE

    Dejan Pecevski; Thomas Natschläger; Klaus Schuch

    2009-01-01

    The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage...

  14. STEPS: modeling and simulating complex reaction-diffusion systems with Python

    OpenAIRE

    Stefan Wils; Erik De Schutter

    2009-01-01

    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 b...

  15. 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...... present an analysis of the results of the competition as well as propose areas of improvement....

  16. PyXel: A Python Package for Astronomical X-ray Data Modeling

    Science.gov (United States)

    Ogrean, Georgiana

    2016-06-01

    PyXel is an new Python package for modeling astronomical X-ray imaging data. It is built on NumPy, SciPy, matplotlib, and Astropy, and distributed under an open-source license. The package aims to provide a common set of image analysis tools for astronomers working with extended X-ray sources. I will present an overview of its existing and planned features, and analysis examples based on public Chandra data.

  17. The adaptive significance of ontogenetic colour change in a tropical python

    OpenAIRE

    Wilson, David; Heinsohn, Robert; Endler, John A

    2006-01-01

    Ontogenetic colour change is typically associated with changes in size, vulnerability or habitat, but assessment of its functional significance requires quantification of the colour signals from the receivers' perspective. The tropical python, Morelia viridis, is an ideal species to establish the functional significance of ontogenetic colour change. Neonates hatch either yellow or red and both the morphs change to green with age. Here, we show that colour change from red or yellow to green pr...

  18. An Object-Oriented Python Implementation of an Intermediate-Level Atmospheric Model

    Science.gov (United States)

    Lin, J. W.

    2008-12-01

    The Neelin-Zeng Quasi-equilibrium Tropical Circulation Model (QTCM1) is a Fortran-based intermediate-level atmospheric model that includes simplified treatments of several physical processes, including a GCM-like convective scheme and a land-surface scheme with representations of different surface types, evaporation, and soil moisture. This model has been used in studies of the Madden-Julian oscillation, ENSO, and vegetation-atmosphere interaction effects on climate. Through the assumption of convective quasi-equilibrium in the troposphere, the QTCM1 is able to include full nonlinearity, resolve baroclinic disturbances, and generate a reasonable climatology, all at low computational cost. One year of simulation on a PC at 5.625 × 3.75 degree longitude-latitude resolution takes under three minutes of wall-clock time. The Python package qtcm implements the QTCM1 in a mixed-language environment that retains the speed of compiled Fortran while providing the benefits of Python's object-oriented framework and robust suite of utilities and datatypes. We describe key programming constructs used to create this modeling environment: the decomposition of model runs into Python objects, providing methods so visualization tools are attached to model runs, and the use of Python's mutable datatypes (lists and dictionaries) to implement the "run list" entity, which enables total runtime control of subroutine execution order and content. The result is an interactive modeling environment where the traditional sequence of "hypothesis → modeling → visualization and analysis" is opened up and made nonlinear and flexible. In this environment, science tasks such as parameter-space exploration and testing alternative parameterizations can be easily automated, without the need for multiple versions of the model code interacting with a bevy of makefiles and shell scripts. The environment also simplifies interfacing of the atmospheric model to other models (e.g., hydrologic models

  19. ObsPy: A Python Toolbox for Seismology and Seismological Observatories

    Science.gov (United States)

    Krischer, Lion; Megies, Tobias; Barsch, Robert; Beyreuther, Moritz; Wassermann, Joachim

    2013-04-01

    Python combines the power of a full-blown programming language with the flexibility and accessibility of an interactive scripting language. Its extensive standard library and large variety of freely available high quality scientific modules cover most needs in developing scientific processing workflows. ObsPy extends Python's capabilities to fit the specific needs that arise when working with seismological data. It a) comes with a continuously growing signal processing toolbox that covers most tasks common in seismological analysis, b) provides read and write support for many common waveform, station and event metadata formats and c) enables access to various data centers, webservices and databases to retrieve waveform data and station/event metadata. In combination with mature and free Python packages like NumPy, SciPy, Matplotlib, IPython and PyQt, ObsPy makes it possible to develop complete workflows in Python, ranging from reading locally stored data or requesting data from one or more different data centers via signal analysis and data processing to visualization in GUI and web applications, output of modified/derived data and the creation of publication-quality figures. All functionality is extensively documented and the ObsPy Tutorial and Gallery give a good impression of the wide range of possible use cases. ObsPy is tested and running on Linux, OS X and Windows and comes with installation routines for these systems. ObsPy is developed in a test-driven approach and is available under the GPL/LGPLv3 open source licences. Users are welcome to request help, report bugs, propose enhancements or contribute code via either the user mailing list or the project page on GitHub.

  20. NIFTY - Numerical Information Field Theory - a versatile Python library for signal inference

    OpenAIRE

    Selig, Marco; Bell, Michael R.; Junklewitz, Henrik; Oppermann, Niels; Reinecke, Martin; Greiner, Maksim; Pachajoa, Carlos; Enßlin, Torsten A.

    2013-01-01

    NIFTY, "Numerical Information Field Theory", is a software package designed to enable the development of signal inference algorithms that operate regardless of the underlying spatial grid and its resolution. Its object-oriented framework is written in Python, although it accesses libraries written in Cython, C++, and C for efficiency. NIFTY offers a toolkit that abstracts discretized representations of continuous spaces, fields in these spaces, and operators acting on fields into classes. The...

  1. pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis

    OpenAIRE

    Theodoros Giannakopoulos

    2015-01-01

    Audio information plays a rather important role in the increasing digital content that is available today, resulting in a need for methodologies that automatically analyze such content: audio event recognition for home automations and surveillance systems, speech recognition, music information retrieval, multimodal analysis (e.g. audio-visual analysis of online videos for content-based recommendation), etc. This paper presents pyAudioAnalysis, an open-source Python library that provides a wid...

  2. Mobile Programming with QT : Python programming for Maemo/MeeGo platform

    OpenAIRE

    Zhou, Quan

    2011-01-01

    Kemi-Tornio University of Applied Sciences, Technology Degree Programme Information Technology Name Zhou Quan Title Python Programming for Maemo/MeeGo Platform Type of Study Bachelor’s Thesis Date 21 September 2011 Pages 30 + 5 appendices Instructor Teppo Aalto Mobile devices already became one of the most necessary things nowadays. There are several mobile platforms in the market like Symbian S40, Symbian S60, Symbian Anna, Symbian Bella, IOS, Android, Mae...

  3. PCSIM: A Parallel Simulation Environment for Neural Circuits Fully Integrated with Python

    OpenAIRE

    Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus

    2009-01-01

    The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the f...

  4. NEVESIM: Event-Driven Neural Simulation Framework with a Python Interface

    OpenAIRE

    Dejan ePecevski; David eKappel; Zeno eJonke

    2014-01-01

    NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language. It supports simulation of heterogeneous networks with different types of neurons and synapses, and can be easily extended by the user with new neuron and synapse types. To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events (spikes...

  5. Modular Toolkit for Data Processing (MDP): A Python Data Processing Framework

    OpenAIRE

    Zito, Tiziano; Wilbert, Niko; Wiskott, Laurenz; Berkes, Pietro

    2009-01-01

    Modular toolkit for Data Processing (MDP) is a data processing framework written in Python. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. Computations are performed efficiently in terms of speed and memory requirements. From the scientific developer's perspective, MDP is a modular framework, which can eas...

  6. NEVESIM: event-driven neural simulation framework with a Python interface

    OpenAIRE

    Pecevski, Dejan; Kappel, David; Jonke, Zeno

    2014-01-01

    NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language. It supports simulation of heterogeneous networks with different types of neurons and synapses, and can be easily extended by the user with new neuron and synapse types. To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events (spikes...

  7. Massively parallel implementation in Python of a pseudo-spectral DNS code for turbulent flows

    OpenAIRE

    Mortensen, Mikael

    2016-01-01

    Direct Numerical Simulations (DNS) of the Navier Stokes equations is a valuable research tool in fluid dynamics, but there are very few publicly available codes and, due to heavy number crunching, codes are usually written in low-level languages. In this work a \\textasciitilde{}100 line standard scientific Python DNS code is described that nearly matches the performance of pure C for thousands of processors and billions of unknowns. With optimization of a few routines in Cython, it is found t...

  8. HOPE: A Python Just-In-Time compiler for astrophysical computations

    OpenAIRE

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

    2014-01-01

    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 langua...

  9. Design of a blocks-based environment for introductory programming in Python

    OpenAIRE

    Poole, Matthew James

    2015-01-01

    This paper details the design of a visual blocks-based tool for editing Python programs. Its purpose is to close the gap between programming using a simplified blocks-based language and textual programming in a mainstream language. As well as helping to guarantee the syntactic validity of programs, the tool aims to reduce the occurrence of run-time errors, a source of learner frustration with dynamic languages, by ensuring that constructed programs will remain well-typed during execution. The...

  10. Powerlaw: a Python package for analysis of heavy-tailed distributions

    OpenAIRE

    Alstott, Jeff; Bullmore, Ed; Plenz, Dietmar

    2013-01-01

    Power laws are theoretically interesting probability distributions that are also frequently used to describe empirical data. In recent years, effective statistical methods for fitting power laws have been developed, but appropriate use of these techniques requires significant programming and statistical insight. In order to greatly decrease the barriers to using good statistical methods for fitting power law distributions, we developed the powerlaw Python package. This software package provid...

  11. Integrating the Media Computation API with Pythy, an Online IDE for Novice Python Programmers

    OpenAIRE

    Athri, Ashima

    2015-01-01

    Improvements in both software and curricula have helped introductory computer science courses attract and retain more students. Pythy is one such online learning environment that aims to reduce software setup related barriers to learning Python while providing facilities like course management and grading to instructors. To further enable its goals of being beginner-centric, we want to integrate full support for media-computation-style programming activities. The media computation curriculum ...

  12. ObsPy: A Python Toolbox for Seismologists, Seismological Observatories and Data Centers

    Science.gov (United States)

    Megies, T.; Barsch, R.; Beyreuther, M.; Krischer, L.; Wassermann, J.

    2012-04-01

    Python combines the possibilities of a full-blown programming language with the flexibility of an interactive scripting language. Its extensive standard library and many freely available high quality scientific modules cover most needs in developing scientific processing workflows. ObsPy extends Python's capabilities to fit the specific needs that arise when working with seismological data. It a) comes with a continuously growing signal processing toolbox that covers the most common tasks in seismological analysis, b) provides read and write support for many common waveform and metadata file formats and c) enables access to various data centers, webservices and databases to retrieve waveform data and station/event metadata. In combination with widely used, free Python packages like NumPy, SciPy, Matplotlib, IPython and PyQt, ObsPy makes it possible to develop complete workflows in Python, ranging from reading locally stored data or requesting data from one or more different data centers via signal analysis and data processing to visualization in GUI applications, output of modified/derived data and creating publication-quality figures. All functionality is extensively documented and the ObsPy Gallery/Tutorial give a good impression of the wide range of use cases. ObsPy is tested and running on Linux, MacOSX and Windows XP/Vista/7 and comes with installation routines for these systems. ObsPy is developed in a test-driven approach and is available under the GPL/LGPLv3 licences. Users are welcome to request help, report bugs or propose enhancements via the user mailing list or the Trac ticket system.

  13. Processing: A Python Framework for the Seamless Integration of Geoprocessing Tools in QGIS

    OpenAIRE

    Anita Graser; Victor Olaya

    2015-01-01

    Processing is an object-oriented Python framework for the popular open source Geographic Information System QGIS, which provides a seamless integration of geoprocessing tools from a variety of different software libraries. In this paper, we present the development history, software architecture and features of the Processing framework, which make it a versatile tool for the development of geoprocessing algorithms and workflows, as well as an efficient integration platform for algorithms from ...

  14. Implementation of Tainted Mode approach to finding security vulnerabilities for Python technology

    OpenAIRE

    Kozlov, D.; Petukhov, A.

    2007-01-01

    Most web applications contain security vulnerabilities that result in high rate of SQL injection and crosssite scripting attacks present-day. The most of vulnerabilities is the result of improper or none input validation by web application. The Tainted Mode approach is widely used for detection of such vulnerabilities. This paper presents the implementation of Tainted Mode approach to finding security vulnerabilities for Python technology.

  15. Naval Observatory Vector Astrometry Software (NOVAS) Version 3.1:Fortran, C, and Python Editions

    Science.gov (United States)

    Kaplan, G. H.; Bangert, J. A.; Barron, E. G.; Bartlett, J. L.; Puatua, W.; Harris, W.; Barrett, P.

    2012-08-01

    The Naval Observatory Vector Astrometry Software (NOVAS) is a source - code library that provides common astrometric quantities and transformations to high precision. The library can supply, in one or two subroutine or function calls, the instantaneous celestial position of any star or planet in a variety of coordinate systems. NOVAS also provides access to all of the building blocks that go into such computations. NOVAS is used for a wide variety of applications, including the U.S. portions of The Astronomical Almanac and a number of telescope control systems. NOVAS uses IAU recommended models for Earth orientation, including the IAU 2006 precession theory, the IAU 2000A and 2000B nutation series, and diurnal rotation based on the celestial and terrestrial intermediate origins. Equinox - based quantities, such as sidereal time, are also supported. NOVAS Earth orientation calculations match those from SOFA at the sub - microarcsecond level for comparable transformations. NOVAS algorithms for aberration an d gravitational light deflection are equivalent, at the microarcsecond level, to those inherent in the current consensus VLBI delay algorithm. NOVAS can be easily connected to the JPL planetary/lunar ephemerides (e.g., DE405), and connections to IMCCE and IAA planetary ephemerides are planned. NOVAS Version 3.1 introduces a Python edition alongside the Fortran and C editions. The Python edition uses the computational code from the C edition and currently mimics the function calls of the C edition. Future versions will expand the functionality of the Python edition to exploit the object - oriented features of Python. In the Version 3.1 C edition, the ephemeris - access functions have been revised for use on 64 - bit systems and for improved performance in general. NOVAS source code, auxiliary files, and documentation are available from the USNO website (http://aa.usno.navy.mil/software/novas/novas_info.php).

  16. 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 & PMID:19788032

  17. pypk - A Python extension module to handle chemical kinetics in plasma physics modeling

    Directory of Open Access Journals (Sweden)

    2008-06-01

    Full Text Available PLASMAKIN is a package to handle physical and chemical data used in plasma physics modeling and to compute gas-phase and gas-surface kinetics data: particle production and loss rates, photon emission spectra and energy exchange rates. A large number of species properties and reaction types are supported, namely: gas or electron temperature dependent collision rate coefficients, vibrational and cascade levels, evaluation of branching ratios, superelastic and other reverse processes, three-body collisions, radiation imprisonment and photoelectric emission. Support of non-standard rate coefficient functions can be handled by a user-supplied shared library.

    The main block of the PLASMAKIN package is a Fortran module that can be included in an user's program or compiled as a shared library, libpk. pypk is a new addition to the package and provides access to libpk from Python programs. It is build on top of the ctypes foreign function library module and is prepared to work with several Fortran compilers. However pypk is more than a wrapper and provides its own classes and functions taking advantage of Python language characteristics. Integration with Python tools allows substantial productivity gains on program development and insight on plasma physics problems.

  18. Elementary mechanics using Python a modern course combining analytical and numerical techniques

    CERN Document Server

    Malthe-Sørenssen, Anders

    2015-01-01

    This book – specifically developed as a novel textbook on elementary classical mechanics – shows how analytical and numerical methods can be seamlessly integrated to solve physics problems. This approach allows students to solve more advanced and applied problems at an earlier stage and equips them to deal with real-world examples well beyond the typical special cases treated in standard textbooks. Another advantage of this approach is that students are brought closer to the way physics is actually discovered and applied, as they are introduced right from the start to a more exploratory way of understanding phenomena and of developing their physical concepts. While not a requirement, it is advantageous for the reader to have some prior knowledge of scientific programming with a scripting-type language. This edition of the book uses Python, and a chapter devoted to the basics of scientific programming with Python is included. A parallel edition using Matlab instead of Python is also available. Last but not...

  19. A Python analytical pipeline to identify prohormone precursors and predict prohormone cleavage sites

    Directory of Open Access Journals (Sweden)

    Bruce Southey

    2008-12-01

    Full Text Available Neuropeptides and hormones are signaling molecules that support cell-cell communication in the central nervous system. Experimentally characterizing neuropeptides requires significant efforts because of the complex and variable processing of prohormone precursor proteins into neuropeptides and hormones. We demonstrate the power and flexibility of the Python language to develop components of an bioinformatic analytical pipeline to identify precursors from genomic data and to predict cleavage as these precursors are en route to the final bioactive peptides. We identified 75 precursors in the rhesus genome, predicted cleavage sites using support vector machines and compared the rhesus predictions to putative assignments based on homology to human sequences. The correct classification rate of cleavage using the support vector machines was over 97% for both human and rhesus data sets. The functionality of Python has been important to develop and maintain NeuroPred (http://neuroproteomics.scs.uiuc.edu/neuropred.html, a user-centered web application for the neuroscience community that provides cleavage site prediction from a wide range of models, precision and accuracy statistics, post-translational modifications, and the molecular mass of potential peptides. The combined results illustrate the suitability of the Python language to implement an all-inclusive bioinformatics approach to predict neuropeptides that encompasses a large number of interdependent steps, from scanning genomes for precursor genes to identification of potential bioactive neuropeptides.

  20. A new open-source Python-based Space Weather data access, visualization, and analysis toolkit

    Science.gov (United States)

    de Larquier, S.; Ribeiro, A.; Frissell, N. A.; Spaleta, J.; Kunduri, B.; Thomas, E. G.; Ruohoniemi, J.; Baker, J. B.

    2013-12-01

    Space weather research relies heavily on combining and comparing data from multiple observational platforms. Current frameworks exist to aggregate some of the data sources, most based on file downloads via web or ftp interfaces. Empirical models are mostly fortran based and lack interfaces with more useful scripting languages. In an effort to improve data and model access, the SuperDARN community has been developing a Python-based Space Science Data Visualization Toolkit (DaViTpy). At the center of this development was a redesign of how our data (from 30 years of SuperDARN radars) was made available. Several access solutions are now wrapped into one convenient Python interface which probes local directories, a new remote NoSQL database, and an FTP server to retrieve the requested data based on availability. Motivated by the efficiency of this interface and the inherent need for data from multiple instruments, we implemented similar modules for other space science datasets (POES, OMNI, Kp, AE...), and also included fundamental empirical models with Python interfaces to enhance data analysis (IRI, HWM, MSIS...). All these modules and more are gathered in a single convenient toolkit, which is collaboratively developed and distributed using Github and continues to grow. While still in its early stages, we expect this toolkit will facilitate multi-instrument space weather research and improve scientific productivity.