يعرض 121 - 140 نتائج من 228 نتيجة بحث عن '(( python ((code representing) OR (plot representing)) ) OR ( python code implementation ))', وقت الاستعلام: 0.50s تنقيح النتائج
  1. 121
  2. 122

    High-Throughput Mass Spectral Library Searching of Small Molecules in R with NIST MSPepSearch حسب Andrey Samokhin (20282728)

    منشور في 2025
    "…Despite the availability of numerous library search algorithms, those developed by NIST and implemented in MS Search remain predominant, partly because commercial databases (e.g., NIST, Wiley) are distributed in proprietary formats inaccessible to custom code. …"
  3. 123

    Comparison data 7 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  4. 124

    Sample data for <i>Neolamprologus multifasciatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  5. 125

    Sample data for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  6. 126

    Comparison data 3 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  7. 127

    Sample data for <i>Telmatochromis temporalis</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  8. 128

    Comparison data 4 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  9. 129

    Comparison data 1 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  10. 130

    Comparison data 2 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  11. 131

    Comparison data 5 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  12. 132

    Comparison data 6 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  13. 133
  14. 134

    Plotting histograms depicting phylogenetic branch lengths (in amino acid substitutions per site) between homeologous gene pairs for 13 tetraploid genomes. حسب Amjad Khalaf (22470183)

    منشور في 2025
    "…<p>Python script used to extract pairwise branch lengths between homeologous gene pairs for 13 tetraploid genomes, and plot them as histograms. …"
  15. 135
  16. 136

    Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx حسب Piyachat Udomwong (22563212)

    منشور في 2025
    "…Its efficiency and scalability make it well-suited for early-stage antibody discovery, repertoire profiling, and therapeutic design, particularly in the absence of structural data. The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…"
  17. 137

    Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 حسب Robert Zomer (12796235)

    منشور في 2025
    "…</p><p dir="ltr">The Python programming source code used to run the calculation of ET0 and AI is provided and available online on Figshare at:</p><p dir="ltr">https://figshare.com/articles/software/Global_Aridity_Index_and_Potential_Evapotranspiration_Climate_Database_v3_-_Algorithm_Code_Python_/20005589</p><p dir="ltr">Peer-Review Reference and Proper Citation:</p><p dir="ltr">Zomer, R.J.; Xu, J.; Trabuco, A. 2022. …"
  18. 138

    Overview of generalized weighted averages. حسب Nobuhito Manome (8882084)

    منشور في 2025
    "…GWA-UCB1 outperformed G-UCB1, UCB1-Tuned, and Thompson sampling in most problem settings and can be useful in many situations. The code is available at <a href="https://github.com/manome/python-mab" target="_blank">https://github.com/manome/python-mab</a>.…"
  19. 139

    MCCN Case Study 3 - Select optimal survey locality حسب Donald Hobern (21435904)

    منشور في 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>…"
  20. 140

    Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games" حسب Krishnendu Chatterjee (15367413)

    منشور في 2024
    "…<br></pre></pre><h2>Structure and How to run</h2><p dir="ltr">There are four Python files in the repository.</p><pre><pre>(i) `StrategyIteration.py` is the backend code, containing the implementation of the RPPI algorithm described in the paper.…"