https://github.com/oboulant/tamis
Implementation in C, wrapped in Python of the exact solution by Block Coordinate Descent for fast detection of multiple change-points
https://github.com/oboulant/tamis
change-point-detection changepoint python science scientific-computing signal-processing
Last synced: 3 months ago
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Implementation in C, wrapped in Python of the exact solution by Block Coordinate Descent for fast detection of multiple change-points
- Host: GitHub
- URL: https://github.com/oboulant/tamis
- Owner: oboulant
- License: bsd-2-clause
- Created: 2021-06-25T13:15:11.000Z (about 5 years ago)
- Default Branch: main
- Last Pushed: 2021-12-03T09:59:46.000Z (over 4 years ago)
- Last Synced: 2025-03-25T09:21:35.379Z (over 1 year ago)
- Topics: change-point-detection, changepoint, python, science, scientific-computing, signal-processing
- Language: C
- Homepage:
- Size: 179 KB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# tamis
Python wrapping of an implementation in C of the exact solution by Block Coordinate Descent for fast detection of multiple change-points.
It follows the following paper :
* J.-P. Vert and K. Bleakley, "Fast detection of multiple change-points shared by many signals using group LARS", In J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel and A. Culotta (Eds), Advances in Neural Information Processing Systems 23 (NIPS), p.2343-2351, 2010. [[paper]](https://members.cbio.mines-paristech.fr/~jvert/svn/ngs/Lasso/article/groupLARS/nips2010/nips2010.pdf) [[supplementary informations]](https://members.cbio.mines-paristech.fr/~jvert/svn/ngs/Lasso/article/groupLARS/nips2010/supplementary.pdf) [[poster]](https://members.cbio.mines-paristech.fr/~jvert/publi/nips2010poster/poster.pdf)
The Matlab implementation by the authors can be found [here](https://members.cbio.mines-paristech.fr/~jvert/svn/GFLseg/html/).
Details about the pseudo code by the same authors can be found [here](https://hal.archives-ouvertes.fr/hal-00602121).
## Local Build
A local build requires to have a working C compilation suite.
### From the source
In case you have cloned the repo on your machine and wish to build from the source :
If you are using `bash` :
```bash
> python -m pip install .[dev,display]
```
If you are using `zsh` :
```zsh
> python -m pip install .\[dev,display\]
```
### From the github repository
You can also build using `pip` by providing the link to the remote repo :
If you are using `zsh` :
```zsh
> pip install git+https://github.com/oboulant/tamis.git
```
This still need to have configured on the machine a working C compilation chain.
## Contributing
If you wish to contribute, please install the pre-commit hooks. If you performed a previous local install with `python -m pip install .\[dev,display\]`, then the `pre-commit` package should already be installed. Then, you just have to tell `pre-commit` to install the hooks.
```zsh
> pre-commit install
```
## Examples
### Run built-in example
```zsh
> python -m examples.example
```
### Code example
```python
import tamis as tam
import numpy as np
import ruptures as rpt
import matplotlib.pylab as plt
def get_default_weights(n):
i = np.arange(1, n)
return np.sqrt(n * 1.0 / (i * 1.0 * (n - i)))
#######################################
# Generate signal
#######################################
n, dim = 500, 3 # number of samples, dimension
n_bkps, sigma = 3, 0.2 # number of change points, noise standard deviation
signal, bkps = rpt.pw_constant(n, dim, n_bkps, noise_std=sigma, seed=1234)
#######################################
# Compute change points
#######################################
weights = get_default_weights(n)
regularization_lambda = 30.0
n_A, A, U = tam.ebcd(signal, weights, regularization_lambda)
#######################################
# Communicate on results
#######################################
print(f"{n_A} break points found :")
print(list(A))
print(f"True break points are :")
print(bkps)
rpt.display(signal, bkps, A)
plt.show()
```
## Run tests
### All tests
In order to start both tests in C and Python, from the top directory :
```zsh
> make test && make clean
```
### Python test
The package has to be installed with the `.[dev,test]` options (so that `pytest` is installed)
```zsh
> python -m pip install .[dev,test]
> python -m pytest
```
It is to be noted that this repository being just a wrapper on the C implementation, tests in python only perform a high level test (we check that with a multidimensional signal without any noise, it outputs the true break points).
Unit tests are performed in C.
### C tests
From the top directory:
```zsh
> (cd tests/c && make test && ./test && make clean)
```