Suchergebnisse - (( (stated OR stat) python code analysis ) OR ( statement python code analysis ))

Percolation theory using Python von Malthe-Sørenssen, Anders

“… Readers will learn how to generate, analyze, and comprehend data and models, with detailed theoretical discussions complemented by accessible computer codes …”
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Decoding the JAK-STAT Axis in Colorectal Cancer with AI-HOPE-JAK-STAT: A Conversational Artificial Intelligence Approach to Clinical–Genomic Integration von Yang, Ei-Wen, Waldrup, Brigette, Velazquez-Villarreal, Enrique

“… : AI-HOPE-JAK-STAT combines large language models (LLMs), a natural language-to-code engine, and harmonized public CRC datasets from cBioPortal …”
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Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial von Smith, Matthew J., Mansournia, Mohammad A., Maringe, Camille, Zivich, Paul N., Cole, Stephen R., Leyrat, Clémence, Belot, Aurélien, Rachet, Bernard, Luque‐Fernandez, Miguel A.

“… The main purpose of many medical studies is to estimate the effects of a treatment or exposure on an outcome. However, it is not always possible to randomize …”
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Python Data Analyst's Toolkit - Learn Python and Python-Based Libraries with Applications in Data Analysis and Statistics von Rajagopalan, Gayathri

“… The code is presented in Jupyter notebooks that can further be adapted and extended. This book is divided into three parts - programming with Python, data analysis and visualization, and statistics …”
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LiPydomics: A Python Package for Comprehensive Prediction of Lipid Collision Cross Sections and Retention Times and Analysis of Ion Mobility-Mass Spectrometry-Based Lipidomics Data von Ross, Dylan H, Cho, Jang Ho, Zhang, Rutan, Hines, Kelly M, Xu, Libin

“… Existing solutions for these data analysis challenges (i.e., multivariate statistics and lipid identification …”
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Statistics Using Python von Campesato, Oswald

“… This book is designed to offer a fast-paced yet thorough introduction to essential statistical concepts using Python code samples, and aims to assist data scientists in their daily endeavors …”
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Assessing code readability in Python programming courses using eye‐tracking von Segedinac, Milan, Savić, Goran, Zeljković, Ivana, Slivka, Jelena, Konjović, Zora

“… This paper assesses the readability of Python code statements commonly used in undergraduate programming courses …”
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Mitigating the Uncertainty and Imprecision of Log-Based Code Coverage Without Requiring Additional Logging Statements von Xu, Xiaoyan, Cogo, Filipe R., McIntosh, Shane

“… Understanding code coverage is an important precursor to software maintenance activities (e.g., better testing …”
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Pastas: Open Source Software for the Analysis of Groundwater Time Series von Collenteur, Raoul A., Bakker, Mark, Caljé, Ruben, Klop, Stijn A., Schaars, Frans

“… ), and the detection of trends and outliers. Pastas is a new and open source Python package for the analysis of hydrogeological time series …”
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Detecting Memory Errors in Python Native Code by Tracking Object Lifecycle with Reference Count von Ma, Xutong, Yan, Jiwei, Zhang, Hao, Yan, Jun, Zhang, Jian

“… Third-party Python modules are usually implemented as binary extensions by using native code (C/C++ …”
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GraphPyRec: A novel graph-based approach for fine-grained Python code recommendation von Zong, Xing, Zheng, Shang, Zou, Haitao, Yu, Hualong, Gao, Shang

“… Significant progress has been made in code recommendation for static languages in recent years, but it remains challenging for dynamic languages like Python as accurately determining data flows …”
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Evaluating Large Language Models in Class-Level Code Generation von Du, Xueying, Liu, Mingwei, Wang, Kaixin, Wang, Hanlin, Liu, Junwei, Chen, Yixuan, Feng, Jiayi, Sha, Chaofeng, Peng, Xin, Lou, Yiling

“… , function-level or statement-level code generation), which mainly asks LLMs to generate one single code unit (e.g …”
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Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data von Pakkir Shah, Abzer K., Walter, Axel, Ottosson, Filip, Russo, Francesco, Navarro-Diaz, Marcelo, Boldt, Judith, Kalinski, Jarmo-Charles J., Kontou, Eftychia Eva, Elofson, James, Polyzois, Alexandros, González-Marín, Carolina, Farrell, Shane, Aggerbeck, Marie R., Pruksatrakul, Thapanee, Chan, Nathan, Wang, Yunshu, Pöchhacker, Magdalena, Brungs, Corinna, Cámara, Beatriz, Caraballo-Rodríguez, Andrés Mauricio, Cumsille, Andres, de Oliveira, Fernanda, Dührkop, Kai, El Abiead, Yasin, Geibel, Christian, Graves, Lana G., Hansen, Martin, Heuckeroth, Steffen, Knoblauch, Simon, Kostenko, Anastasiia, Kuijpers, Mirte C. M., Mildau, Kevin, Papadopoulos Lambidis, Stilianos, Portal Gomes, Paulo Wender, Schramm, Tilman, Steuer-Lodd, Karoline, Stincone, Paolo, Tayyab, Sibgha, Vitale, Giovanni Andrea, Wagner, Berenike C., Xing, Shipei, Yazzie, Marquis T., Zuffa, Simone, de Kruijff, Martinus, Beemelmanns, Christine, Link, Hannes, Mayer, Christoph, van der Hooft, Justin J. J., Damiani, Tito, Pluskal, Tomáš, Dorrestein, Pieter, Stanstrup, Jan, Schmid, Robin, Wang, Mingxun, Aron, Allegra, Ernst, Madeleine, Petras, Daniel

“… We provide explanations and code in two scripting languages (R and Python) as well …”
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From code to reliability: Python-powered Paraconsistent Logic for alarm detection in the power gris/ Do codigo a confiabilidade: Logica Paraconsistente impulsionada por Python para a deteccao de alarmes na rede de energia von de Oliveira, Joseffe Barroso, Gino, Joao Vitor Santa Rosa, de Lima, Carlos Jose, Filho, Joao Inacio da Silva

“… This application enables the comparison of triggered alarms with the resultant logical states obtained during the analysis …”
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Stress-Constrained Topology Optimization for Commercial Software: A Python Implementation for ABAQUS von Fernandes, Pedro, Ferrer, Àlex, Gonçalves, Paulo, Parente, Marco, Pinto, Ricardo, Correia, Nuno

“… , using validated FEM commercial software. The methodology was validated by comparing the sensitivity analysis with the results obtained through finite differences and solving two benchmark problems with the following optimizers …”
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Quantifying the interpretation overhead of Python von Zhang, Qiang, Xu, Lei, Zhang, Xiangyu, Xu, Baowen

“… •Quantitative overhead analysis for the Python interpreter based on sampling.•Overhead decomposition from both opcode and project composition perspectives …”
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Python for Everyone: Learn and polish your coding skills in Python (English Edition) von Saurabh Chandrakar, Dr. Nilesh Bhaskarrao Bahadure

“… A hands-on guide that will help you to write clean and efficient code in Python Key Features …”
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Data Science Fundamentals with R, Python, and Open Data von Cremonini, Marco

“… Introduction to essential concepts and techniques of the fundamentals of R and Python needed to start data science projectsOrganized with a strong focus on open data, This book discusses concepts …”
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Robustness Analysis of Watermarking Techniques for LLM-Generated Code von Cao, Di, Liu, Shigang, Zhang, Jun, Xiang, Yang

“… The widespread adoption of large language models (LLMs) for code generation raises critical concerns regarding authorship attribution and accountability, motivating the development of watermarking techniques to trace model outputs …”
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Visualization of Aqueous Geochemical Data Using Python and WQChartPy von Yang, Jing, Liu, Honghua, Tang, Zhonghua, Peeters, Luk, Ye, Ming

“… This method note presents WQChartPy, an open‐source Python package developed to plot a total of 12 diagrams for analysis of aqueous geochemical data …”
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