# Linear Segmentation
[](https://travis-ci.org/kylessmith/linear_segmentation) [](https://badge.fury.io/py/linear_segmentation)
[](https://www.buymeacoffee.com/kylessmith)
linear_segmentation using Bayesian Change Point Segmentation or Circular Binary segmentation.
## Install
If you dont already have numpy and scipy installed, it is best to download
`Anaconda`, a python distribution that has them included.
```
https://continuum.io/downloads
```
Dependencies can be installed by:
```
pip install -r requirements.txt
```
PyPI install, presuming you have all its requirements installed:
```
pip install linear_segment
```
## Usage
```python
from linear_segment import segment
import numpy as np
# Create data
np.random.seed(10)
T = 50
x = np.zeros(T)
x[10:20] = 1.0
x[30:40] = 1.0
labels = np.repeat("a", T) # "a" is a dummy label
# Calculate segments
segments = segment(x, labels, method="online_both", cutoff=0.3, offset=5)
print(segments)
LabeledIntervalArray
(0-10, a)
(10-20, a)
(20-30, a)
(30-40, a)
(40-50, a)
segments = segment(x, labels, method="cbs", shuffles=200, p=0.05)
print(segments)
LabeledIntervalArray
(0-10, a)
(10-20, a)
(20-30, a)
(30-40, a)
(40-50, a)
```
Raw data
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"description": "# Linear Segmentation\n\n[](https://travis-ci.org/kylessmith/linear_segmentation) [](https://badge.fury.io/py/linear_segmentation)\n[](https://www.buymeacoffee.com/kylessmith)\n\nlinear_segmentation using Bayesian Change Point Segmentation or Circular Binary segmentation.\n\n\n## Install\n\nIf you dont already have numpy and scipy installed, it is best to download\n`Anaconda`, a python distribution that has them included. \n```\n https://continuum.io/downloads\n```\n\nDependencies can be installed by:\n\n```\n pip install -r requirements.txt\n```\n\nPyPI install, presuming you have all its requirements installed:\n```\n\tpip install linear_segment\n```\n\n## Usage\n\n```python\nfrom linear_segment import segment\nimport numpy as np\n\n# Create data\nnp.random.seed(10)\nT = 50\nx = np.zeros(T)\nx[10:20] = 1.0\nx[30:40] = 1.0\n\nlabels = np.repeat(\"a\", T) # \"a\" is a dummy label\n\n# Calculate segments\nsegments = segment(x, labels, method=\"online_both\", cutoff=0.3, offset=5)\nprint(segments)\n\nLabeledIntervalArray\n (0-10, a)\n (10-20, a)\n (20-30, a)\n (30-40, a)\n (40-50, a)\nsegments = segment(x, labels, method=\"cbs\", shuffles=200, p=0.05)\nprint(segments)\n\nLabeledIntervalArray\n (0-10, a)\n (10-20, a)\n (20-30, a)\n (30-40, a)\n (40-50, a)\n\n```\n\n",
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