Data

Tools

Indexes

Applications

Experiments

Open Source Science

https://github.com/datasig-ac-uk/signature_applications

Example applications of path signatures

https://github.com/datasig-ac-uk/signature_applications

Science Score: 31.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 4 committers (25.0%) from academic institutions
  • ✓
    Institutional organization owner
    Organization datasig-ac-uk has institutional domain (datasig.web.ox.ac.uk)
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (4.1%) to scientific vocabulary

Keywords

hut23 hut23-1132 hut23-1376 hut23-171 hut23-457 hut23-953
Last synced: 6 months ago · JSON representation

Repository

Example applications of path signatures

Basic Info
  • Host: GitHub
  • Owner: datasig-ac-uk
  • Language: Jupyter Notebook
  • Default Branch: master
  • Homepage:
  • Size: 39.4 MB
Statistics
  • Stars: 38
  • Watchers: 3
  • Forks: 10
  • Open Issues: 7
  • Releases: 0
Topics
hut23 hut23-1132 hut23-1376 hut23-171 hut23-457 hut23-953
Created over 5 years ago · Last pushed about 1 year ago
Metadata Files
Readme

README.md

signature_applications

Development

This repo uses pre-commit, which will automatically format your code and run some basic checks before you commit:

pip install pre-commit # or brew install pre-commit on macOS pre-commit install # will install a pre-commit hook into the git repo

After doing this, each time you commit, some linters will be applied to format the codebase. You can also/alternatively run pre-commit run --all-files to run the checks.

Owner

  • Name: DataSig
  • Login: datasig-ac-uk
  • Kind: organization

A rough path between mathematics and data science

GitHub Events

Total
  • Issues event: 1
  • Watch event: 4
  • Push event: 19
  • Pull request event: 7
  • Create event: 6
Last Year
  • Issues event: 1
  • Watch event: 4
  • Push event: 19
  • Pull request event: 7
  • Create event: 6

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 48
  • Total Committers: 4
  • Avg Commits per committer: 12.0
  • Development Distribution Score (DDS): 0.458
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Peter Foster p****r@t****k 26
Peter Foster p****r 12
Sam Morley s****m@i****m 8
Kevin Schlegel k****2@g****m 2
Committer Domains (Top 20 + Academic)
inakleinbottle.com: 1 turing.ac.uk: 1

Issues and Pull Requests

Last synced: about 2 years ago

All Time
  • Total issues: 1
  • Total pull requests: 5
  • Average time to close issues: N/A
  • Average time to close pull requests: about 4 hours
  • Total issue authors: 1
  • Total pull request authors: 3
  • Average comments per issue: 2.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • rchan26 (6)
  • inakleinbottle (1)
Pull Request Authors
  • philipparubin (5)
  • rchan26 (4)
  • pafoster (3)
  • inakleinbottle (1)
Top Labels
Issue Labels
Pull Request Labels

Dependencies

controlled_neural_differential_equations/requirements.txt pypi
  • matplotlib *
  • signatory ==1.2.4.1.7.1
  • torch >=1.7.1
  • wheel *
drone_identification/requirements.txt pypi
  • esig *
  • joblib *
  • matplotlib *
  • numpy *
  • scikit-learn *
  • scipy *
  • tqdm *
human_action_recognition/requirements.txt pypi
  • ipywidgets ==7.5.1
  • matplotlib ==3.2.1
  • moviepy ==1.0.3
  • notebook ==6.1.1
  • opencv-python ==4.2.0.34
  • requests ==2.22.0
  • scikit-learn ==0.23.1
  • tqdm ==4.46.1
human_action_recognition/requirements_torch.txt pypi
  • torch ==1.5.0
mnist_classification/requirements.txt pypi
  • esig ==0.9.7
  • joblib ==1.0.1
  • matplotlib *
  • numpy *
  • scikit-learn ==0.24.2
natural_language_processing/requirements.txt pypi
  • iisignature ==0.24
  • jupyter *
  • matplotlib ==3.5.1
  • matplotlib-inline ==0.1.3
  • numpy ==1.21.2
  • pandas ==1.4.1
  • scikit-learn ==1.0.2
  • scipy ==1.8.0
  • tqdm ==4.62.3
  • transformers ==4.16.2
  • umap-learn ==0.5.2
  • zarr ==2.11.0
natural_language_processing/requirements_torch.txt pypi
  • torch ==1.11.0