[MAINT] Make package pip-installable (#61)

* [MAINT] Make package pip-installable

* cleanup + pep

* bump version to 0.1.3

* Update README.md

* Update conf.py

.github/workflows/pythonpackage.yml

@@ -26,7 +26,7 @@ jobs:
       run: |
         python -m pip install --upgrade pip
         pip install -r requirements.txt
-        pip install -e ".[extra]"
+        pip install -e ".[tests]"
     - name: Lint with flake8
       run: |
         make pep

.travis.yml

@@ -12,7 +12,7 @@ python:
 install:
   - sudo apt-get update
   - pip install -r requirements.txt
-  - pip install -e ".[extra]"
+  - pip install -e ".[docs]"
 script:
   - mkdir docs
   - cd doc

MANIFEST.in

@@ -0,0 +1 @@
+include README.md

README.md

@@ -6,11 +6,11 @@
 [![twitter](https://img.shields.io/twitter/follow/lebababa?label=Twitter&style=flat&logo=Twitter)](https://twitter.com/intent/follow?screen_name=lebababa)
 
 # MEEGkit
+
 Denoising tools for M/EEG processing in Python 3.7+.
 
 ![meegkit-ERP](https://user-images.githubusercontent.com/10333715/176754293-eaa35071-94f8-40dd-a487-9f8103c92571.png)
 
-
 > **Disclaimer:** The project mostly consists of development code, although some modules and functions are already working. Bugs and performance problems are to be expected, so use at your own risk. More tests and improvements will be added in the future. Comments and suggestions are welcome.
 
 ## Documentation
@@ -21,10 +21,10 @@ This code can also be tested directly from your browser using [Binder](https://m
 
 ## Installation
 
-This package can be installed easily using `pip+git`:
+This package can be installed easily using `pip`:
 
 ```bash
-pip install git+https://github.com/nbara/python-meegkit.git
+pip install meegkit
 ```
 
 Or you can clone this repository and run the following commands inside the `python-meegkit` directory:
@@ -47,9 +47,11 @@ pip install -e '.[extra]'
 or:
 
 ```bash
-pip install git+https://github.com/nbara/python-meegkit.git#egg=meegkit[extra]
+pip install meegkit[extra]
 ```
 
+Other available options are `[docs]` (which installs dependencies required to build the documentation), or `[tests]` (which install dependencies to run unit tests).
+
 ## References
 
 ### 1. CCA, STAR, SNS, DSS, ZapLine, and robust detrending

doc/conf.py

@@ -23,8 +23,8 @@
 
 # -- Project information -----------------------------------------------------
 
-project = f'MEEGkit v{meegkit.__version__}'
-copyright = '2021, Nicolas Barascud'
+project = 'MEEGkit'
+copyright = '2022, Nicolas Barascud'
 author = 'Nicolas Barascud'
 release = meegkit.__version__
 version = meegkit.__version__

meegkit/__init__.py

@@ -1,5 +1,5 @@
 """M/EEG denoising utilities in python."""
-__version__ = '0.1.2'
+__version__ = '0.1.3'
 
 from . import asr, cca, detrend, dss, sns, star, ress, trca, tspca, utils
 

meegkit/sns.py

@@ -7,7 +7,7 @@
 
 
 def sns(X, n_neighbors=0, skip=0, weights=np.array([])):
-    """Sensor Noise Suppresion.
+    """Sensor Noise Suppression.
 
     This algorithm will replace the data from each channel by its regression on
     the subspace formed by the other channels. The underlying assumptions are
@@ -62,7 +62,7 @@ def sns(X, n_neighbors=0, skip=0, weights=np.array([])):
 
 
 def sns0(c, n_neighbors=0, skip=0, wc=np.array([])):
-    """Sensor Noise Suppresion from data covariance.
+    """Sensor Noise Suppression from data covariance.
 
     Parameters
     ----------
@@ -130,7 +130,7 @@ def sns0(c, n_neighbors=0, skip=0, wc=np.array([])):
 
 
 def sns1(X, n_neighbors=None, skip=0):
-    """Sensor Noise Suppresion 1.
+    """Sensor Noise Suppression 1.
 
     This version of SNS first regresses out major shared components.
     """

meegkit/utils/asr.py

@@ -412,7 +412,7 @@ def polystab(a):
     b = a[ind[0][0]] * np.poly(v)
 
     # Return only real coefficients if input was real:
-    if not(np.sum(np.imag(a))):
+    if not np.sum(np.imag(a)):
         b = np.real(b)
 
     return b

requirements.txt

@@ -4,12 +4,6 @@ matplotlib
 scikit-learn
 pandas
 joblib
-flake8
-pytest
-pytest-cov
-codecov
-codespell
-pydocstyle
 tqdm
 statsmodels
 pyriemann>=0.2.7

setup.cfg

@@ -20,4 +20,6 @@ upload-dir = doc/_build/html
 
 [options.extras_require]
 extra = pymanopt
+docs = sphinx;sphinx-gallery;sphinx-bootstrap_theme;sphinx-copybutton;sphinxemoji;numpydoc;pydata-sphinx-theme;pillow;jupyter-sphinx;meegkit[extra]
+tests = pytest;pytest-cov;codecov;codespell;flake8;pydocstyle;meegkit[extra]
 

setup.py

@@ -2,13 +2,27 @@
 #
 from setuptools import setup, find_packages
 
+with open("README.md", "r", encoding="utf8") as fid:
+    long_description = fid.read()
+
 setup(
     name='meegkit',
     description='M/EEG denoising in Python',
+    long_description=long_description,
+    long_description_content_type="text/markdown",
     url='http://github.com/nbara/python-meegkit/',
-    author='N Barascud',
+    author='Nicolas Barascud',
     author_email='[email protected]',
-    license='UNLICENSED',
-    version='0.1.2',
+    license='BSD (3-clause)',
+    version='0.1.3',
     packages=find_packages(exclude=['doc', 'tests']),
+    project_urls={
+        "Documentation": "https://nbara.github.io/python-meegkit/",
+        "Source": "https://github.com/nbara/python-meegkit/",
+        "Tracker": "https://github.com/nbara/python-meegkit/issues/",
+    },
+    platforms="any",
+    python_requires=">=3.7",
+    install_requires=["numpy", "scipy", "scikit-learn", "joblib", "pandas",
+                      "matplotlib", "tqdm", "pyriemann", "statsmodels"],
     zip_safe=False)