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Showing 61 - 80 results of 123 for search '((python tool) OR (python code)) representing', query time: 0.25s Refine Results
  1. 61

    <b>Data and Code from 'The Perfect and Legitimate Bribe': A Transparent Record of Human-AI Collaboration in Legal Scholarship</b> by Joshua Stern (21748181)

    Published 2025
    “…</p><p dir="ltr">For optimal viewing of `collated-anonymized.txt`, a text editor that can handle long lines without word wrapping is recommended to preserve the indentation that represents the conversational branching structure.</p><p><br></p><p dir="ltr">### **Running Code/Software**</p><p dir="ltr">The provided scripts (`collator-ipynb.txt` and `sentence-ancestry-ipynb.txt`) are Jupyter Notebooks and require a Python 3 environment to run. …”
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    Data and code from: Hatchery-reared coho salmon develop less otolith deformities in tanks with alternating water flow directions by Leigh Gaffney (1389855)

    Published 2025
    “…</li><li>Measurements were generated by manually classifying otolith regions in Adobe Photoshop and calculating pixel coverage using a Python script.</li><li>Representative otolith images and details of the classification workflow are provided in the main manuscript figures and Methods section. …”
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    Data and Code repository for the paper: <b>Visual loom caused by self- or object-movement elicits distinct responses in mouse superior colliculus</b> by Stefano Zucca (21686006)

    Published 2025
    “…Binned rates were transformed into z-scores by normalizing to the mean and standard deviation of firing rate across all stimulus conditions.</p><h2>Code Description</h2><p dir="ltr">Shared code contains both MATLAB and Python functions used in the analysis provided in the study. …”
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    Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

    Published 2024
    “…In recent years, manual model tuning has been gradually replaced by automated parameter search using a variety of different tools and methods. However, using most of these software tools and choosing the most appropriate algorithm for a given optimization task require substantial technical expertise, which prevents the majority of researchers from using these methods effectively. …”
  8. 68

    Improving the calibration of an integrated CA-What If? digital planning framework by CA What If? (21381170)

    Published 2025
    “…</p><p dir="ltr">This dataset includes (1) all required data for reproducing the materials within the manuscript, (2) detailed Python codes of the proposed CA-What If? model, and (3) a step-by-step instruction document.…”
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    Machine Learning-Driven Discovery and Database of Cyanobacteria Bioactive Compounds: A Resource for Therapeutics and Bioremediation by Renato Soares (20348202)

    Published 2024
    “…This resource, adhering to the findability, accessibility, interoperability, and reuse of digital assets (FAIR) principles, is an excellent tool for pharmaceutical and bioremediation researchers. …”
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    Tracking when the number of individuals in the video frame changes. by Hirotsugu Azechi (20700528)

    Published 2025
    “…The yellow box in the schematic represents the processes using multi-animal tracking tools, while the green box represents the processes using single-animal tracking tools. …”
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    Missing and Unaccounted-for People in Mexico (1960s–2025) by Montserrat Mora (20430644)

    Published 2025
    “…</li><li><b>Requirements File:</b> A <code>requirements.txt</code> file listing the necessary Python libraries to run the script seamlessly.…”
  14. 74

    CpG Signature Profiling and Heatmap Visualization of SARS-CoV Genomes: Tracing the Genomic Divergence From SARS-CoV (2003) to SARS-CoV-2 (2019) by Tahir Bhatti (20961974)

    Published 2025
    “…Heatmap Generation</p><p dir="ltr">Tools :</p><p dir="ltr">Heatmaps were generated using Python's seaborn library (sns.heatmap) and matplotlib for visualization.…”
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    Dataset for CNN-based Bayesian Calibration of TELEMAC-2D Hydraulic Model by Jose Zevallos (21379988)

    Published 2025
    “…</li><li>Files starting with <code>y_part</code> are flattened output arrays representing corresponding water depth values.…”
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    Moulin distributions during 2016-2021 on the southwest Greenland Ice Sheet by Kang Yang (7323734)

    Published 2025
    “…</p><p><br></p><ul><li>00_Satellite-derived moulins: Moulins directly mapped from Sentinel-2 imagery, representing actual moulin positions;</li><li>01_Snapped moulins: Moulins snapped to DEM-modeled supraglacial drainage networks, primarily used for analyses;</li><li>02_Moulin recurrences: Recurring moulins determined from the snapped moulins;</li><li>03_Internally drained catchments: Internally drained catchment (IDC) associated with each moulin;</li><li>04_Surface meltwater runoff: surface meltwater runoff calculated from MAR for the study area, elevation bins, and IDCs; </li><li>05_DEM-derived: Topographic features modeled from ArcticDEM, including elevation bins, depressions and drainage networks;</li><li>06_GWR: Variables for conducting geographically weighted regression (GWR) analysis;</li></ul><p><br></p><ul><li>Code_01_Mapping moulins on the southwestern GrIS.ipynb: A Jupyter Notebook to analyze moulin distributions, reproducing most of the analyses and figures presented in the manuscript using the provided datasets;</li><li>Code_02_pre1_calculate Strain Rate from XY ice velocity.py: A preprocessing Python script to calculate strain rate for the GWR analysis;</li><li>Code_02_pre2_calculate Driving Stress from ice thickness and surface slope.py: A preprocessing Python script to calculate driving stress for the GWR analysis;</li><li>Code_02_GWR analysis.ipynb: A Jupyter Notebook to conduct the GWR analysis using the provided datasets.…”
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    <b>Dataset for manuscript: </b><b>Phylogenetic and genomic insights into the evolution of terpenoid biosynthesis genes in diverse plant lineages</b> by Puguang Zhao (19023065)

    Published 2025
    “…</p><p dir="ltr"> 'boxplot.py': This script is executed in Visual Studio Code, using Python 3.10.4 as the runtime environment.…”
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    <b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b> by Shubham Pawar (22471285)

    Published 2025
    “…</p><p dir="ltr"><b>Input:</b></p><ul><li><code>svi_module/svi_data/svi_info.csv</code> - Image metadata from Step 1</li><li><code>perception_module/trained_models/</code> - Pre-trained models</li></ul><p dir="ltr"><b>Command:</b></p><pre><pre>python -m perception_module.pred \<br> --model-weights .…”
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    MCCN Case Study 3 - Select optimal survey locality by Donald Hobern (21435904)

    Published 2025
    “…</p><p dir="ltr">This is a simple implementation that uses four environmental attributes imported for all Australia (or a subset like NSW) at a moderate grid scale:</p><ol><li>Digital soil maps for key soil properties over New South Wales, version 2.0 - SEED - see <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html" target="_blank">https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html</a></li><li>ANUCLIM Annual Mean Rainfall raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer</a></li><li>ANUCLIM Annual Mean Temperature raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer</a></li></ol><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Generate STAC metadata for layers from predefined configuratiion</li><li>Load data cube and exclude nodata values</li><li>Scale all variables to a 0.0-1.0 range</li><li>Select four layers for comparison (soil organic carbon 0-30 cm, soil pH 0-30 cm, mean annual rainfall, mean annual temperature)</li><li>Select 10 random points within NSW</li><li>Generate 10 new layers representing standardised environmental distance between one of the selected points and all other points in NSW</li><li>For every point in NSW, find the lowest environmental distance to any of the selected points</li><li>Select the point in NSW that has the highest value for the lowest environmental distance to any selected point - this is the most different point</li><li>Clean up and save results to RO-Crate</li></ol><p><br></p>…”
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