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Open Source Science

https://github.com/cimagroup/d6.3_experiments_t6.3.3

Code for the experiments in Section 7.2 of the Deliverable D6.3 for the European project REXASI-PRO

https://github.com/cimagroup/d6.3_experiments_t6.3.3

Science Score: 13.0%

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    CITATION.cff file
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    Low similarity (3.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Code for the experiments in Section 7.2 of the Deliverable D6.3 for the European project REXASI-PRO

Basic Info
  • Host: GitHub
  • Owner: Cimagroup
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Size: 0 Bytes
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

How to install everything:

  1. Create the virtual environment
  2. Install jupyterlab, jupyer notebook or something similar
  3. Make sure that you have the navground-blofun-main folder in here
  4. pip install -r requirements.txt
  5. Go to tdqual
  6. pip install . (this installs tdqual)
  7. Go to navground-blofun-main
  8. pip install . (this installs perdiver)

How to run the experiments:

In the 'Example3agents' and 'Example5agents' folders:

  1. run creating_poses.py
  2. run creating_signals.py

In the 'Corridor', 'Cross' and 'CrossTorus' folders:

  1. run creating_dataset.py
  2. run creating_signals.py
  3. run cluster_analysis.py

Owner

  • Name: Combinatorial Image Analysis research group
  • Login: Cimagroup
  • Kind: organization

GitHub Events

Total
  • Release event: 1
  • Push event: 38
  • Create event: 3
Last Year
  • Release event: 1
  • Push event: 38
  • Create event: 3

Dependencies

requirements.txt pypi
  • NetworkX ==3.4.1
  • POT *
  • cairosvg ==2.7.1
  • gudhi ==3.10.1
  • h5py ==3.12.1
  • matplotlib ==3.9.2
  • moviepy ==1.0.3
  • navground ==0.3.3
  • scipy ==1.14.1
  • seaborn ==0.13.2
  • shapely ==2.0.6
  • sktime *
  • tslearn ==0.6.3
  • umap-learn *
  • websockets ==13.0