Relevant bibliographies by topics / Python tool

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Python tool'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Python tool"

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Conway, Matthew J. "Python: a GUI development tool." Interactions 2, no. 2 (1995): 23–28. http://dx.doi.org/10.1145/205350.205354.

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J, LAKSHMI. "A Python - Powered Keylogger Detection Tool." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31982.

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Keyloggers are a prevalent threat that record users' keystrokes to steal credentials and sensitive data. This paper presents a Python-based keylogger detection tool that scans running processes and checks them against indicators of compromise (IOCs). The detector integrates process inspection, signature matching, and automated remediation functions. A graphical user interface allows easy operation and threat response. The tool was tested against known keyloggers and demonstrated effective discovery with minimal false positives. This demonstrates Python's capabilities for building specialized s
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Preeti, Tupsakhare. "Python for Automation and Scripting: Streamlining Operations and Increasing Efficiency." Journal of Scientific and Engineering Research 6, no. 9 (2019): 222–27. https://doi.org/10.5281/zenodo.13918609.

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In today's rapidly evolving technological landscape, Python has emerged as a pivotal tool for automation and scripting, streamlining operations and significantly increasing efficiency across various industries. This white paper delves into the numerous advantages of Python, highlighting its accessibility, simplicity, and the powerful ecosystem of libraries that support a wide range of automation tasks. From automating mundane data entry tasks to orchestrating complex network operations, Python's versatility makes it an indispensable tool for developers and non-developers alike. We will explore
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Murthy, P. V. S. N. "Automated Penetration Testing Tool Using Python." International Journal for Research in Applied Science and Engineering Technology 13, no. 3 (2025): 1100–1105. https://doi.org/10.22214/ijraset.2025.67480.

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This title accurately reflects the core objectives of the project creating a tool that automates the penetration testing process and generates detailed reports [4]. It encapsulates the primary focus of the project, which is to enhance the efficiency of penetration testing through automation, while ensuring that the resulting reports provide valuable insights into system vulnerabilities and security weaknesses. The tool will streamline the testing procedure, making it accessible to both experienced security professionals and those new to penetration testing.
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Dronov, V. Y., and G. A. Dronova. "Python as an automation tool in IS. Protecting Database Access in Python." Journal of Physics: Conference Series 2182, no. 1 (2022): 012093. http://dx.doi.org/10.1088/1742-6596/2182/1/012093.

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Abstract The activity of modern organizations, regardless of the form of ownership, is highly risky. There are up to 600 risk factors in total. It is possible to reduce risk levels only after assessing them. The basis of risk assessment is analytical processing of information relating to the sphere of organization’s activity. The information to be analyzed is usually accumulated in databases. This information is usually accessed with SQL queries and analyzed with application software. The most rational variant is when the business unit employees are able to select the data from the database an
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Karunamurthy, Dr A., Vithanala Manoj Kumar, and Prasanth C. "AIRMATH GESTURE-DRIVEN VIRTUAL CALCULATOR." International Scientific Journal of Engineering and Management 03, no. 12 (2024): 1–9. https://doi.org/10.55041/isjem02161.

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The Virtual Calculator project is a Python-based application that allows users to perform mathematical calculations through an intuitive graphical user interface (GUI). Designed to support basic operations such as addition, subtraction, multiplication, and division, the calculator offers a simple yet powerful tool for solving everyday mathematical problems. The application leverages Python's Tkinter library to create an easy-to-use interface, ensuring that users can interact with the tool effortlessly, regardless of their technical background. This project demonstrates the versatility of Pytho
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Dronov, V. Y., and G. A. Dronova. "PYTHON AS AN AUTOMATION TOOL IN INFORMATION SECURITY. PROTECTING DATABASE ACCESS IN PYTHON." Dynamics of Systems, Mechanisms and Machines 9, no. 4 (2021): 054–59. http://dx.doi.org/10.25206/2310-9793-9-4-54-59.

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Деятельность современных организаций, не зависимо от форм собственности, является высокорискованной. Всего насчитывается до 600 риск факторов. Снижение уровней риском, можно только оценив их. Основой оценки рисков является аналитическая обработка информации, относящейся к сфере деятельности организации. Информация, подлежащая анализу, обычно аккумулируется в базах данных. Доступ к этой информации обычно осуществляется с помощью SQL-запросов, а анализ проводится с помощью прикладного программного обеспечения. Наиболее рациональный вариант - когда сотрудники бизнес-подразделения самостоятельно с
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Li, Yang, Yanchen Zou, and Yanda Qian. "Practice of Python in Programming and Optimization of Quantitative Analysis Model of Fixed Income." Mathematical Modeling and Algorithm Application 3, no. 1 (2024): 23–26. http://dx.doi.org/10.54097/z441c084.

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Python has become an indispensable tool in fixed income trading. This paper introduces the principles and general process of data analysis visualisation by analysing the basic operation and performance of personal investment and finance, combined with data analysis in the era of big data. The library of data analysis tools using Python has become an indispensable tool in fixed income trading. In fixed income trading, it supports fixed income traders to handle tasks such as bond pricing, interest rate modelling, and credit risk analysis Using Python's powerful data processing capabilities, trad
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Gely, Mario F., and Gary A. Steele. "QuCAT: quantum circuit analyzer tool in Python." New Journal of Physics 22, no. 1 (2020): 013025. http://dx.doi.org/10.1088/1367-2630/ab60f6.

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Yadav, Vinay, Subhankar Karmakar, Pradip P. Kalbar, and A. K. Dikshit. "PyTOPS: A Python based tool for TOPSIS." SoftwareX 9 (January 2019): 217–22. http://dx.doi.org/10.1016/j.softx.2019.02.004.

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Dissertations / Theses on the topic "Python tool"

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Feng, Michelle. "Automatically Fixing Syntax Errors with PEST, a Python Tool for Beginners." Scholarship @ Claremont, 2018. http://scholarship.claremont.edu/scripps_theses/1148.

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Psycholinguistic research shows that it is unreasonable to expect programmers to easily find minor typos in their otherwise correct code. The Python Error Support Tool PEST was designed and developed to address this. PEST offers an explanation for why the error happened and presents a list of possible fixes that will allow the user’s code to compile. This tool was evaluated by several students with a beginner’s level of expertise in Python, and feedback was generally positive with tangible steps for improvement.
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Haupt, Cornelis Dirk. "Mesoscale Brain Explorer, a flexible Python-based image analysis and visualization tool." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/62667.

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Imaging of mesoscale brain activity is used to map interactions between brain regions. This work has benefited from the pioneering studies of Grinvald et al., who employed optical methods to image brain function by exploiting the properties of intrinsic optical signals and small molecule voltage-sensitive dyes. Mesoscale interareal brain imaging techniques have been advanced by cell targeted and selective recombinant indicators of neuronal activity. Spontaneous resting state activity is often collected during mesoscale imaging to provide the basis for mapping of connectivity relationships usin
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Barlow, Jane E., and Jane E. Barlow. "Python Tools to Aid and Improve Rapid Hydrologic and Hydraulic Modeling with the Automated Geospatial Watershed Assessment Tool (AGWA)." Thesis, The University of Arizona, 2017. http://hdl.handle.net/10150/622849.

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Hydrologic and hydraulic modeling are used to assess watershed function at different spatial and temporal scales. Many tools have been developed to make these types of models more accessible to use and model results easier to interpret. One tool that makes hydrologic models more accessible in a geographic information system (GIS) is the Automated Geospatial Watershed Assessment tool (AGWA); the GIS enables the development of spatially variable model inputs and model results for a variety of applications. Two major applications of AGWA are for rangeland watershed assessments and post-wildfire r
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Rathore, Akash. "Tool for querying the National Household Travel Survey data." Kansas State University, 2018. http://hdl.handle.net/2097/38795.

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Master of Science<br>Department of Computer Science<br>Doina Caragea<br>The goal of the project is to create a database for storing the National Household Travel Survey (NHTS) data, and a user interface to query the database. Currently, the survey data is stored in excel files in the CSV format, which makes it hard to perform complex analyses over the data. Analyses of interest to transportation community include comparisons of the trips made by urban household to those made by rural household, finding the average trip time spent based on ethnicity, the total travel time of a particular house
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Witulski, John [Verfasser], Michael [Gutachter] Leuschel, and Michael [Gutachter] Schöttner. "A Python B Implementation - PyB A Second Tool-Chain / John Witulski ; Gutachter: Michael Leuschel, Michael Schöttner." Düsseldorf : Universitäts- und Landesbibliothek der Heinrich-Heine-Universität Düsseldorf, 2018. http://d-nb.info/1171519125/34.

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Tilden, Daniel Steven. "Design and Evaluation of a Web-Based Programming Tool to Improve the Introductory Computer Science Experience." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23149.

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Introductory computer science courses can be notoriously difficult for students, especially those outside of the major. There are many reasons for this, but the programming software itself may play a significant role.  To address this issue, we have developed Pythy, a web-based programming environment that allows students to write, execute, and test programming assignments from within the familiar interface of a web browser.  In this work, we discuss various aspects of Pythy in detail, including the rationale behind its design, the system architecture on which it is built, and the various func
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Paternesi, Claudio. "Virtual Reality Labelling Tool for 3D Semantic Segmentation." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

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Durante gli ultimi anni nel campo della Computer Vision si sono susseguiti studi sempre più approfonditi sulla segmentazione semantica 3D, questi lavori richiedono spesso una enorme quantità di modelli 3D su cui fare le elaborazioni. Non sempre però, i dataset disponibili forniscono delle informazioni complete riguardanti anche la segmentazione dei modelli 3D. In questa tesi si propone uno strumento software con cui si possa creare, a partire da un modello 3D, la sua versione segmentata semanticamente, così da poter creare dei dataset completi da usare nelle fasi di training e test di modelli
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Šmalec, Ondřej. "Aplikace pro monitorování sítí." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-400875.

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Diplomová práce popisuje vytvoření aplikace pro monitorování síťových zařízení. Výsledky jsou zobrazené jako grafické uživatelské rozhraní společně s vykreslenou topologií. Aplikace je z velké části napsána v jazyce Python. Pro získávání informací z topologie jsou využity protokoly SNMP a SSH. Hlavní cíl je vytvořit aplikaci, která monitoruje síťová zařízení a vykresluje tuhle topologii do grafického uživatelského rozhraní. Tato aplikace reaguje dynamicky na změny v monitorovací topologii.
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Lundgren, Marcus, and Johan Persson. "Constructing and Evaluating a Raspberry Pi Penetration Testing/Digital Forensics Reconnaissance Tool." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-42805.

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Tools that automate processes are always sough after across the entire IT field. This project's aim was to build and evaluate a semi-automated reconnaissance tool based on a Raspberry Pi 4, for use in penetration testing and/or digital forensics. The software is written in Python 3 and utilizes Scapy, PyQt5 and the Aircrack-ng suite along with other pre-existing tools. The device is targeted against wireless networks and its main purpose is to capture what is known as the WPA handshake and thereby crack Wi-Fi passwords. Upon achieving this, the program shall then connect to the cracked network
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Simondon, Camille. "Optimization of thermal response test equipment and evaluation tools." Thesis, KTH, Tillämpad termodynamik och kylteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-147764.

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Nowadays Ground Source Heat Pumps (GSHP) are widely used to provide heating and/or cooling as well as domestic hot water in commercial and residential buildings. The Swedish GSHPs market is the first one in the European Union with more than 378,000 units installed until 2010 according to the Swedish Heat Pump Association (SVEP). This thesis focuses on the improvement of a Thermal Response Test (TRT) apparatus available at KTH Royal Institute of Technology – Energy Technology Department. This equipment aims at improving Borehole Heat Exchanger (BHE) design in terms of size. Its key purpose is t
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Books on the topic "Python tool"

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Krivolapov, Sergey. Introduction to data analysis. Searching for a data structure using Python. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/2082643.

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The tutorial discusses Python language tools for identifying and subsequent use of the internal structure of data using Markov process methods, statistical, cluster and regression analysis of data.&#x0D; Meets the requirements of the federal state educational standards of higher education of the latest generation.&#x0D; For students, postgraduates, researchers and teachers.
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Krivolapov, Sergey. Data analysis. Methods of probability theory and mathematical statistics in Python. INFRA-M Academic Publishing LLC., 2025. https://doi.org/10.12737/2034420.

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The textbook contains a description of probabilistic and statistical methods that form the theoretical basis of data analysis. It is characterized by intensive use of Python language tools. Detailed solutions are provided for all examples and tasks. Meets the requirements of the latest generation of federal state educational standards for higher education. For students, postgraduates, researchers and teachers.
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Inc, ebrary, ed. Python geospatial development: Build a complete and sophisticated mapping application from scratch using Python tools for GIS development. Packt Open Source, 2010.

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Nazarov, Dmitriy, and Anton Kopnin. Information technologies in professional activity: data mining and business analytics. INFRA-M Academic Publishing LLC., 2024. http://dx.doi.org/10.12737/2110964.

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The textbook offers a comprehensive look covering a wide range of topics related to the role of information technology in the modern world. Starting with an overview of the history of information technology and its evolution, the book introduces the reader to professions in the field of information and digital technologies, emphasizing them in various professional fields. The content of the textbook includes a detailed analysis of key concepts such as Data Science, Data Mining and Machine Learning, and their role in healthcare, law, education, science and business. The textbook provides a deta
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Publishing, K. M. L. Python Programmer Notebook: Lined Notebook / Journal Gift, 120 Pages, 6x9, ... Python for Dummies, Key Fob Programming Tool. Independently Published, 2021.

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Publishing, K. M. L. Python Programmer Notebook: Lined Notebook / Journal Gift, 120 Pages, 8. 5x11 ... Python for Dummies, Key Fob Programming Tool. Independently Published, 2021.

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Essick, John. The Python-Based Laboratory. Oxford University PressOxford, 2024. https://doi.org/10.1093/9780191998478.001.0001.

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Abstract The Python-Based Laboratory: A Hands-On Guide for Scientists and Engineers provides a learn-by-doing approach to acquiring the Python programming skills needed to implement computer-controlled experimental work. The Python-Based Laboratory leads its readers to mastery of the popular, open-source Python computer language in its role as a powerful laboratory tool by carrying out interesting and relevant projects that explore the acquisition, production, analysis, and presentation of digitized waveforms. Readers, who are assumed to have no prior computer programming or Python background,
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Scratch, Michael, and Erik Scratch. Coding Python: The Ultimate Tool to Progress Your Python Programming from Good to Great While Making Coding in Scratch Look Easy. Independently Published, 2020.

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Overy, Enedina. Tool for Raspberry Pi 3 Configuration : Interacting with Raspberry Pi: Python Raspberry Pi Tutorial. Independently Published, 2021.

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Lawhead, Joel. QGIS Python Programming Cookbook: Over 140 Recipes to Help You Turn QGIS from a Desktop GIS Tool into a Powerful Automated Geospatial Framework. Packt Publishing, Limited, 2015.

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Book chapters on the topic "Python tool"

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Jalaja, T., and T. Adilakshmi. "CIA Tool Using Python and mypy for Python Applications." In Proceedings of the 2nd International Conference on Cognitive and Intelligent Computing. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2746-3_61.

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Oladokun, O., B. Nyakuma, W. S. Luing, et al. "Gasific: A Python Tool for Biomass Gasification Process." In Green Energy and Technology. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95820-6_28.

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Godbole, Adwait, Brian Huffman, Fangfei Liu, Carlos V. Rozas, and Sanjit A. Seshia. "$$\mathbf{{\textsc {PyCaliper}}}$$: Python-Embedded Infrastructure for RTL Verification and Specification Synthesis." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-98682-6_21.

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Abstract We present PyCaliper: a Python-embedded framework to formulate, verify, and auto-synthesize specifications for hardware designs at the register transfer level (RTL). By being Python-embedded, PyCaliper is easy to use and benefits from object-oriented principles and Python’s rich ecosystem. Further, PyCaliper is a common platform that integrates novel research techniques such as specification synthesis and mature, industry-scale tooling, thus allowing them to benefit from each other. We discuss the system and implementation of PyCaliper and demonstrate its use in two case studies: in t
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Arya, Swasti, Mihika Chitranshi, and Yograj Singh. "Analysing Distance Measures in Topsis: A Python-Based Tool." In Algorithms for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1528-3_24.

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Untwal, Nitin Jaglal, and Utku Kose. "The Random Forest Technique Is a Tool for Stock Trading Decisions." In Data Analytics for Finance Using Python. CRC Press, 2024. http://dx.doi.org/10.1201/9781032618241-5.

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Bhavsar, Nisarg, Abhinav Thakur, Amrit Lal Singh, and Ashish Patwa. "RTaC: A Generalized Framework for Tooling." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65794-8_5.

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AbstractIn the rapidly evolving domain of Large Language Models (LLMs), integrating tool usage remains a formidable challenge, particularly when it comes to the dynamic selection and sequencing of tools in response to complex queries. Addressing this, we introduce Reimagining Tooling as Coding (RTaC), a groundbreaking framework that transforms tool usage into a coding paradigm. Inspired by recent advancements [18], RTaC conceptualizes tools as Python functions within a dual-agent system [2], significantly enhancing LLMs’ tool usage efficiency. Our comprehensive experiments reveal that RTaC ena
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Battistini, Tommaso, Nicolò Isaia, Andrea Sterbini, and Marco Temperini. "DrPython–WEB: A Tool to Help Teaching Well-Written Python Programs." In Lecture Notes in Computer Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12429-7_20.

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de Oliveira Junior, Clevio Orlando, Jonathan Carvalho, Fábio Fagundes Silveira, Tiago Silva da Silva, and Eduardo Martins Guerra. "CALint: A Tool for Enforcing the Clean Architecture’s Dependency Rule in Python." In Computational Science and Its Applications – ICCSA 2022 Workshops. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10548-7_39.

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Cadilhac, Michaël, and Guillermo A. Pérez. "Acacia-Bonsai: A Modern Implementation of Downset-Based LTL Realizability." In Tools and Algorithms for the Construction and Analysis of Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30820-8_14.

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AbstractWe describe our implementation of downset-manipulating algorithms used to solve the realizability problem for linear temporal logic (LTL). These algorithms were introduced by Filiot et al. in the 2010s and implemented in the tools Acacia and Acacia+ in C and Python. We identify degrees of freedom in the original algorithms and provide a complete rewriting of Acacia in C++20 articulated around genericity and leveraging modern techniques for better performance. These techniques include compile-time specialization of the algorithms, the use of SIMD registers to store vectors, and several
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Alsabbagh, Wael, and Peter Langendoerfer. "A Remote Attack Tool Against Siemens S7-300 Controllers: A Practical Report." In Technologien für die intelligente Automation. Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/978-3-662-64283-2_1.

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AbstractThis paper presents a series of attacks against Siemens S7-300 programmable logic controllers (PLCs), using our remote IHP-Attack tool. Due to the lack of integrity checks in S7-300 PLCs, such controllers execute commands whether or not they are delivered from a legitimate user. Thus, they were exposed to various kind of cyber-attacks over the last years such as reply, bypass authentication and access control attacks. In this work, we build up our tool to carry out a series of attacks based on the existing reported vulnerabilities of S7-300 PLCs in the research community. For real worl
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Conference papers on the topic "Python tool"

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Montanares, Mauricio, Minda Wen, V. H. Arzate Palma, Kevin G. McCarthy, and Gerardo Molina Salgado. "IceMOS: Cryo-CMOS Python-Based Calibration Tool." In 2024 IEEE 67th International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2024. http://dx.doi.org/10.1109/mwscas60917.2024.10658695.

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Boloori, Aryan, and Tushar Sharma. "DPy: Code Smells Detection Tool for Python." In 2025 IEEE/ACM 22nd International Conference on Mining Software Repositories (MSR). IEEE, 2025. https://doi.org/10.1109/msr66628.2025.00119.

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Shivashankar, Karthik, and Antonio Martini. "PyExamine: A Comprehensive, Un-Opinionated Smell Detection Tool for Python." In 2025 IEEE/ACM 22nd International Conference on Mining Software Repositories (MSR). IEEE, 2025. https://doi.org/10.1109/msr66628.2025.00114.

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Perry, Travis, and Andrew Gallaher. "Automated Layout with a Python Integrated NDARC Environment." In Vertical Flight Society 74th Annual Forum & Technology Display. The Vertical Flight Society, 2018. http://dx.doi.org/10.4050/f-0074-2018-12723.

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Geometric layout of an aircraft concept is a fundamental aspect of the design process and can often be a primary driver for design choices, and trade space decisions. Most commonly, geometry is either estimated analytically by performance and sizing tools, from in-production aircraft data, or modeled using Computer Aided Design (CAD). Analytic geometry estimates are often not precise, requiring CAD to refine these estimates. Modeling an aircraft design to the fidelity needed to refine these geometric estimates can be a time consuming process. Furthermore, the initial layout design iterations a
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Reznichenko, Igor, Primož Podržaj, Tomaž Požrl, and Gašper Škulj. "Python as a Tool in Feedback Control System Analysis and Design." In 2025 IEEE 22nd International Multi-Conference on Systems, Signals & Devices (SSD). IEEE, 2025. https://doi.org/10.1109/ssd64182.2025.10989835.

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Pattedar, Nischal V., Punav Anirudh Potluri, Jayarama Krishna A., and Aiswariya Milan K. "Search Engine Optimization (SEO) Auditing Tool with Geospatial Analysis using Python." In 2025 7th International Conference on Intelligent Sustainable Systems (ICISS). IEEE, 2025. https://doi.org/10.1109/iciss63372.2025.11076433.

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Armitage, Jack, Miguel Crozzoli, and Daniel Jones. "Artificial Life in Integrated Interactive Sonification and Visualisation: Initial Experiments with a Python-Based Workflow." In ICAD 2024: The 29th International Conference on Auditory Display. International Community for Auditory Display, 2024. http://dx.doi.org/10.21785/icad2024.003.

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Multimodal displays that combine interaction, sonification, visu- alisation and perhaps other modalities, are seeing increased interest from researchers seeking to take advantage of cross-modal perception, by increasing display bandwidth and expanding affordances. To support researchers and designers, many new tools are being proposed that aim to consolidate these broad feature sets into Python libraries, due to Python’s extensive ecosystem that in particular encompasses the domain of artificial intelligence (AI). Artificial life (ALife) is a domain of AI that is seeing renewed interest, and i
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Khan, Abdul Mateen, Wesam Salah Alaloul, Muhammad Ali Musarat, and Muhammad Hassaan Farooq Khan. "Python: An Automation Tool for Unlocking Innovation and Efficiency in the AEC Sector." In 2023 4th International Conference on Data Analytics for Business and Industry (ICDABI). IEEE, 2023. http://dx.doi.org/10.1109/icdabi60145.2023.10629478.

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Baskaran, Kumaran, Jonathan Wedell, Eldon Ulrich, Jeffery Hoch, and John Markley. "PyBMRB: Data visualization tool for BioMagResBank." In Python in Science Conference. SciPy, 2021. http://dx.doi.org/10.25080/majora-1b6fd038-00a.

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Shah, Viral B., and Brad McRae. "Circuitscape: A Tool for Landscape Ecology." In Python in Science Conference. SciPy, 2008. http://dx.doi.org/10.25080/ewdj4033.

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The modeling of ecological connectivity across networks and landscapes is an active research area that spans the disciplines of ecology, conservation, and population genetics. Recently, concepts and algorithms from electrical circuit theory have been adapted to address these problems. The approach is based on linkages between circuit and random walk theories, and has several advantages over previous analytic approaches, including incorporation of multiple dispersal pathways into analyses. Here we describe Circuitscape, a computational tool developed for modeling landscape connectivity using ci
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Reports on the topic "Python tool"

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Armstrong, Jerawan C., Brian A. Temple, and Kevin L. Buescher. PyRAT (python radiography analysis tool): overview. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1047140.

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Horn, Mike. Shadowcopy: A Python-Based Shadow Volume Enumeration and Digest Tool. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada548850.

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Temple, Brian Allen, and Jerawan Chudoung Armstrong. LANL12-RS-107J PYTHON radiography analysis tool final report for FY15. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1215800.

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Temple, Brian A., and Jerawan C. Armstrong. LANL13-RS-107J PYTHON Radiography Analysis Tool Final Report for FY13. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1095194.

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McKnight, C., Drew Loney, and Kevin Winters. Watershed and catchment meshing Python tool utilizing the XmsMesh meshing software. Engineer Research and Development Center (U.S.), 2019. http://dx.doi.org/10.21079/11681/34323.

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Temple, Brian Allen, and Jerawan Chudoung Armstrong. LANL12-RS-107J PYTHON Radiography Analysis Tool (PyRAT). Mid-Year Deliverable Report for FY15. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1177993.

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Letcher, Theodore, Sandra LeGrand, and Christopher Polashenski. The Blowing Snow Hazard Assessment and Risk Prediction model : a Python based downscaling and risk prediction for snow surface erodibility and probability of blowing snow. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/43582.

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Blowing snow is an extreme terrain hazard causing intermittent severe reductions in ground visibility and snow drifting. These hazards pose significant risk to operations in snow-covered regions. While many ingredients-based forecasting methods can be employed to predict where blowing snow is likely to occur, there are currently no physically based tools to predict blowing snow from a weather forecast. However, there are several different process models that simulate the transport of snow over short distances that can be adapted into a terrain forecasting tool. This report documents a downscal
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Temple, Brian A., and Jerawan C. Armstrong. LANL12-RS-107J Interfacing the X-Ray Toolkit and the PYTHON Radiography Analysis Tool Final Report for FY12. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1052777.

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Ugarcina Perovic, Svetlana, Vedanth Ramji, Hui Chong, Yiqian Duan, and Luis Pedro Coelho. argNorm: Normalization of antibiotic resistance gene annotations to the Antibiotic Resistance Ontology (ARO). Queensland University of Technology, 2024. http://dx.doi.org/10.5204/rep.eprints.252448.

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Motivation: Currently available and frequently used tools for annotating antimicrobial resistance genes (ARGs) in genomes and metagenomes provide results using inconsistent nomenclature. This makes the comparison of different ARG annotation outputs challenging. The comparability of ARG annotation outputs can be improved by mapping gene names and their categories to a common controlled vocabulary such as the Antibiotic Resistance Ontology (ARO). Results: We developed argNorm, a command line tool and Python library, to normalize all detected genes across 6 ARG annotation tools (8 databases) to t
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Walizer, Laura, Robert Haehnel, Luke Allen, and Yonghu Wenren. Application of multi-fidelity methods to rotorcraft performance assessment. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48474.

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We present a Python-based multi-fidelity tool to estimate rotorcraft performance metrics. We use Gaussian-Process regression (GPR) methods to adaptively build a surrogate model using a small number of high-fidelity CFD points to improve estimates of performance metrics from a medium-fidelity comprehensive analysis model. To include GPR methods in our framework, we used the EmuKit Python package. Our framework adaptively chooses new high-fidelity points to run in regions where the model variance is high. These high-fidelity points are used to update the GPR model; convergence is reached when mo
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