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corals-0.1.5
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CorALS is an open-source software package for the construction and analysis of large-scale correlation networks for high-dimensional data.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | corals-0.1.5 |
| نام | corals |
| نسخه کتابخانه | 0.1.5 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Martin Becker |
| ایمیل نویسنده | mgbckr@stanford.edu |
| آدرس صفحه اصلی | https://github.com/mgbckr/corals-python |
| آدرس اینترنتی | https://pypi.org/project/corals/ |
| مجوز | MIT |
# CorALS
*CorALS* is an open-source software package for the construction and analysis of large-scale correlation networks for high-dimensional data.
If you use *CorALS* for a scientific publication, please cite:
```plain
TO BE PUBLISHED
```
## Install
```bash
pip install corals
```
## Quick start
The following quick start examples can also be found in [an executable notebook](https://github.com/mgbckr/corals-lib-python/tree/main/docs/notebooks/quickstart.ipynb).
**Note:** If any of the following examples do not work, check the [previously mentioned executable notebook](https://github.com/mgbckr/corals-lib-python/tree/main/docs/notebooks/quickstart.ipynb) as well. It is tested automatically, and this `README` may not have been updated.
### Prepare parallelization
Before running anything, we make sure that `numpy` will not oversubscribe CPUs and slow things down.
Note that this has to be executed **before importing `numpy`**.
* For full correlation matrix calculation, setting `n_threads > 1` can be used to parallelize the calculation.
* For the top-k approaches, setting `n_threads=1` makes the most sense, since parallelization is specified separately.
```python
from corals.threads import set_threads_for_external_libraries
set_threads_for_external_libraries(n_threads=1)
```
### Load data
Create some data (alternatively load your own):
```python
import numpy as np
# create random data
n_features = 20000
n_samples = 50
X = np.random.random((n_samples, n_features))
```
### Full correlation matrix computation
```python
# runtime: ~2 sec
from corals.correlation.full.base import cor_full
cor_values = cor_full(X)
```
### Top-k correlation matrix computation using Spearman correlation
```python
# runtime: ~5 sec with `n_jobs=8`
from corals.correlation.topk.base import cor_topk
cor_topk_result = cor_topk(X, k=0.001, correlation_type="spearman", n_jobs=8)
```
### Top-k differential correlation matrix computation using Spearman correlation
```python
# generate some more data
X1 = X
X2 = np.random.random((n_samples, n_features))
```
```python
# runtime: ~5 sec with `n_jobs=8`
from corals.correlation.topkdiff.base import cor_topkdiff
cor_topkdiff_result = cor_topkdiff(X1, X2, k=0.001, correlation_type="spearman", n_jobs=8)
```
### Calculating p-values
```python
# reusing correlation from the top-k example
# runtime: ~20 sec with `n_jobs=8`
from corals.correlation.topk.base import cor_topk
cor_topk_values, cor_topk_coo = cor_topk(X, correlation_type="spearman", k=0.001, n_jobs=8)
from corals.correlation.utils import derive_pvalues, multiple_test_correction
n_samples = X.shape[0]
n_features = X.shape[1]
# calculate p-values
pvalues = derive_pvalues(cor_topk_values, n_samples)
# multiple hypothesis correction
pvalues_corrected = multiple_test_correction(pvalues, n_features, method="fdr_bh")
```
## Detailed examples
For detailed examples and recommendations, see the corresponding [notebook](https://github.com/mgbckr/corals-lib-python/tree/main/docs/notebooks/full.ipynb).
The `docs/notebooks` folder may contain additional examples and tutorials in the form of Jupyter Notebooks.
Quick setup for Jupyter notebooks.
```bash
export ENV_NAME=corals
conda create -n ${ENV_NAME} python=3.10
conda activate ${ENV_NAME}
pip install corals
conda install -c conda-forge jupyterlab # optional if Jupyter Lab is already installed
conda install -c conda-forge ipykernel
python -m ipykernel install --user --name ${ENV_NAME}
```
## Development
**TODO**: add documentation for contributing new code / methods
### Setup
```bash
git clone git@github.com:mgbckr/corals-lib-python.git
pip install -e .
```
### Release
```bash
git tag -a x.x.x -m "Release x.x.x"
```
نیازمندی
| مقدار | نام |
|---|---|
| >=0.52.0 | numba |
| <2.0.0,>=1.20.3 | numpy |
| <2.0.0,>=1.0.0 | joblib |
| <2.0.0,>=1.6.3 | scipy |
| <2.0.0,>=0.24.2 | scikit-learn |
| - | importlib-metadata |
| - | setuptools |
| - | pytest |
| - | pytest-cov |
| - | nbmake |
| - | statsmodels |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| <3.11,>=3.9 | Python |
نحوه نصب
نصب پکیج whl corals-0.1.5:
pip install corals-0.1.5.whl
نصب پکیج tar.gz corals-0.1.5:
pip install corals-0.1.5.tar.gz