Science Score: 23.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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○Academic publication links
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✓Committers with academic emails
1 of 13 committers (7.7%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (8.5%) to scientific vocabulary
Keywords
Repository
DTW (Dynamic Time Warping) python module
Basic Info
- Host: GitHub
- Owner: pollen-robotics
- License: gpl-3.0
- Language: Python
- Default Branch: master
- Size: 191 KB
Statistics
- Stars: 1,206
- Watchers: 32
- Forks: 236
- Open Issues: 16
- Releases: 1
Topics
Metadata Files
README.md
Dynamic Time Warping Python Module
Dynamic time warping is used as a similarity measured between temporal sequences. This package provides two implementations:
- the basic version (see here) for the algorithm
- an accelerated version which relies on scipy cdist (see https://github.com/pierre-rouanet/dtw/pull/8 for detail)
```python
import numpy as np
We define two sequences x, y as numpy array
where y is actually a sub-sequence from x
x = np.array([2, 0, 1, 1, 2, 4, 2, 1, 2, 0]).reshape(-1, 1) y = np.array([1, 1, 2, 4, 2, 1, 2, 0]).reshape(-1, 1)
from dtw import dtw
manhattan_distance = lambda x, y: np.abs(x - y)
d, costmatrix, acccostmatrix, path = dtw(x, y, dist=manhattandistance)
print(d)
2.0 # Only the cost for the insertions is kept
You can also visualise the accumulated cost and the shortest path
import matplotlib.pyplot as plt
plt.imshow(acccostmatrix.T, origin='lower', cmap='gray', interpolation='nearest') plt.plot(path[0], path[1], 'w') plt.show()
```
Result of the accumulated cost matrix and the shortest path (in white) found:
Other examples are available as notebook
Installation
python -m pip install dtw
It is tested on Python 2.7, 3.4, 3.5 and 3.6. It requires numpy and scipy.
Owner
- Name: Pollen Robotics
- Login: pollen-robotics
- Kind: organization
- Email: contact@pollen-robotics.com
- Location: Bordeaux, France
- Website: https://www.pollen-robotics.com
- Repositories: 93
- Profile: https://github.com/pollen-robotics
GitHub Events
Total
- Watch event: 54
- Fork event: 3
Last Year
- Watch event: 54
- Fork event: 3
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Pierre Rouanet | p****t@g****m | 32 |
| mynameisvinn | v****g@g****m | 7 |
| Alexander Kain | k****a@o****u | 3 |
| Sebastian Rodriguez | v****w@g****m | 2 |
| cperales | c****s@u****s | 2 |
| Roberto | r****r@h****t | 1 |
| Petr Viktorin | e****u@g****m | 1 |
| Mutex86 | g****h@g****m | 1 |
| Michael Schubert | m****v@g****m | 1 |
| Martin Mauch | m****h@g****m | 1 |
| James Christie | j****e@l****m | 1 |
| David Schaefer | d****r@u****e | 1 |
| cperales | s****s@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 41
- Total pull requests: 22
- Average time to close issues: about 1 month
- Average time to close pull requests: 6 days
- Total issue authors: 40
- Total pull request authors: 14
- Average comments per issue: 1.83
- Average comments per pull request: 0.95
- Merged pull requests: 17
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 3
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 3
- Pull request authors: 0
- Average comments per issue: 0.33
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- schaefed (2)
- rabihiawaludin (1)
- TrayyTur (1)
- Karim-53 (1)
- rekadanielweiner (1)
- ruiann (1)
- FranGoitia (1)
- wxtyixiao (1)
- alexvks22 (1)
- cmuell89 (1)
- TaosifShaad (1)
- MatthieuBizien (1)
- Erickrus (1)
- iWangLin (1)
- zhangboyang (1)
Pull Request Authors
- pierre-rouanet (5)
- mynameisvinn (3)
- schaefed (2)
- nightscape (2)
- lxkain (2)
- renataghisloti (1)
- encukou (1)
- capkuro (1)
- 0mod4 (1)
- mschubert (1)
- jlc-christie (1)
- rob-med (1)
- cperales (1)
- mutex86 (1)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- numpy *
- scipy *