Merge pull request #25 from gmrukwa/develop

Release 2.3.6

.github/actions/build-python-dist/Dockerfile

@@ -1,4 +1,4 @@
-FROM spectreteam/python_msi:v5.0.0
+FROM spectreteam/python_msi:v5.1.0.2019a.py37
 
 RUN pip install --no-cache-dir --upgrade \
     setuptools \

.github/workflows/deploy.yml

@@ -12,7 +12,7 @@ on:
 env:
   MAJOR: ${{ 2 }}
   MINOR: ${{ 3 }}
-  FIXUP: ${{ 5 }}
+  FIXUP: ${{ 6 }}
   PACKAGE_INIT_FILE: ${{ 'divik/__init__.py' }}
   DOCKER_REPO: ${{ 'gmrukwa/divik' }}
   IS_ALPHA: ${{ github.event_name == 'pull_request' }}

README.md

@@ -1,8 +1,8 @@
 [![CodeFactor](https://www.codefactor.io/repository/github/gmrukwa/divik/badge)](https://www.codefactor.io/repository/github/gmrukwa/divik)
 [![BCH compliance](https://bettercodehub.com/edge/badge/gmrukwa/divik?branch=master)](https://bettercodehub.com/)
 [![Maintainability](https://api.codeclimate.com/v1/badges/4cf5d42d0a0076c38445/maintainability)](https://codeclimate.com/github/gmrukwa/divik/maintainability)
-![](https://github.com/gmrukwa/divik/workflows/.github/workflows/push_images.yml/badge.svg)
-![](https://github.com/gmrukwa/divik/workflows/.github/workflows/unittest.yml/badge.svg)
+![](https://github.com/gmrukwa/divik/workflows/Build%20and%20push%20deployment%20images/badge.svg)
+![](https://github.com/gmrukwa/divik/workflows/Run%20unit%20tests%20in%20MCR%20environment/badge.svg)
 [![Documentation Status](https://readthedocs.org/projects/divik/badge/?version=latest)](https://divik.readthedocs.io/en/latest/?badge=latest)
 
 # divik
@@ -40,26 +40,26 @@ docker pull gmrukwa/divik
 To install specific version, you can specify it in the command, e.g.:
 
 ```bash
-docker pull gmrukwa/divik:2.1.8
+docker pull gmrukwa/divik:2.3.6
 ```
 
 ## Python package
 
 Prerequisites for installation of base package:
 
-- Python 3.5
+- Python 3.5 / 3.6 / 3.7
 
 These are required for using `divik` application and GMM-based filtering:
 
 - [MATLAB Compiler Runtime](https://www.mathworks.com/products/compiler/matlab-runtime.html),
 version 2016b or newer, installed to default path
-- [compiled package with legacy code](https://github.com/spectre-team/matlab-legacy/releases/tag/legacy-v4.0.9)
+- [compiled package with legacy code](https://github.com/spectre-team/matlab-legacy/releases/tag/legacy-v5.0.0)
 
 Installation process may be clearer with insight into Docker images used for
 application deployment:
 
 - [`python_mcr` image](https://github.com/spectre-team/python_mcr) - installs
-MCR r2016b onto Python 3.5 image
+MCR r2019a onto Python 3.7 image
 - [`python_msi` image](https://github.com/spectre-team/python_msi) - installs
 compiled legacy code onto MCR image
 - [`divik` image](https://github.com/spectre-team/spectre-divik/blob/master/dockerfile) -
@@ -75,7 +75,7 @@ pip install divik
 or any stable tagged version, e.g.:
 
 ```bash
-pip install divik==2.1.8
+pip install divik==2.3.6
 ```
 
 # References

divik/__init__.py

@@ -1,4 +1,4 @@
-__version__ = '2.3.5'
+__version__ = '2.3.6'
 
 from ._seeding import seeded
 from ._utils import DivikResult

divik/_matlab_legacy.py

@@ -4,15 +4,17 @@
 import logging
 import os
 import platform
+import warnings
 
 import numpy as np
 
+
 # noinspection SpellCheckingInspection
 _MATLAB_SEARCH_PATHS = \
-    "/usr/local/MATLAB/MATLAB_Runtime/v91/runtime/glnxa64:" + \
-    "/usr/local/MATLAB/MATLAB_Runtime/v91/bin/glnxa64:" + \
-    "/usr/local/MATLAB/MATLAB_Runtime/v91/sys/os/glnxa64:" + \
-    "/usr/local/MATLAB/MATLAB_Runtime/v91/sys/opengl/lib/glnxa64:"
+    "/usr/local/MATLAB/MATLAB_Runtime/v96/runtime/glnxa64:" + \
+    "/usr/local/MATLAB/MATLAB_Runtime/v96/bin/glnxa64:" + \
+    "/usr/local/MATLAB/MATLAB_Runtime/v96/sys/os/glnxa64:" + \
+    "/usr/local/MATLAB/MATLAB_Runtime/v96/extern/bin/glnxa64:"
 
 
 _local_system = platform.system()
@@ -82,7 +84,9 @@ def find_thresholds(values: np.ndarray, max_components: int = 10,
         import MatlabAlgorithms.MsiAlgorithms
         # noinspection PyPackageRequirements
         import matlab
-        values = matlab.double([[element] for element in values.ravel()])
+        with warnings.catch_warnings():
+            warnings.simplefilter("ignore")
+            values = matlab.double([[element] for element in values.ravel()])
         try:
             thresholds = engine.fetch_thresholds(values,
                                                  'MaxComponents',

divik/cluster/_kmeans/_auto.py

@@ -215,7 +215,7 @@ def predict(self, X):
         labels : array, shape [n_samples,]
             Index of the cluster each sample belongs to.
         """
-        check_is_fitted(self, 'best_')
+        check_is_fitted(self)
         return self.best_.predict(X)
 
     def transform(self, X):
@@ -238,5 +238,5 @@ def transform(self, X):
             X transformed in the new space.
 
         """
-        check_is_fitted(self, 'best_')
+        check_is_fitted(self)
         return self.best_.transform(X)

divik/cluster/_kmeans/_core.py

@@ -225,7 +225,7 @@ def predict(self, X):
         labels : array, shape [n_samples,]
             Index of the cluster each sample belongs to.
         """
-        check_is_fitted(self, 'cluster_centers_')
+        check_is_fitted(self)
         if self.normalize_rows:
             X = normalize_rows(X)
         labels = dst.cdist(
@@ -252,7 +252,7 @@ def transform(self, X):
             X transformed in the new space.
 
         """
-        check_is_fitted(self, 'cluster_centers_')
+        check_is_fitted(self)
         if self.normalize_rows:
             X = normalize_rows(X)
         return dst.cdist(X, self.cluster_centers_, self.distance)

divik/cluster/_sklearn.py

@@ -6,6 +6,7 @@
 import pandas as pd
 import scipy.spatial.distance as dist
 from sklearn.base import BaseEstimator, ClusterMixin, TransformerMixin
+from sklearn.utils.validation import check_is_fitted
 import tqdm
 
 import divik.feature_selection as fs
@@ -412,6 +413,7 @@ def transform(self, X):
         X_new : array, shape [n_samples, self.n_clusters_]
             X transformed in the new space.
         """
+        check_is_fitted(self)
         if self._needs_normalization():
             X = normalize_rows(X)
         distances = np.hstack([
@@ -440,6 +442,7 @@ def predict(self, X):
         labels : array, shape [n_samples,]
             Index of the cluster each sample belongs to.
         """
+        check_is_fitted(self)
         if self._needs_normalization():
             X = normalize_rows(X)
         n_jobs = get_n_jobs(self.n_jobs)

divik/feature_extraction/_spectral.py

@@ -182,7 +182,7 @@ def save(self, destination: str):
             Directory to save the embedding.
         """
         logging.info('Saving embedding to {0}.'.format(destination))
-        check_is_fitted(self, 'embedding_')
+        check_is_fitted(self)
         from functools import partial
         import os
         import pickle

divik/feature_selection/_specialized.py

@@ -1,6 +1,6 @@
 import numpy as np
 from sklearn.base import BaseEstimator
-from sklearn.feature_selection.base import SelectorMixin
+from ._stat_selector_mixin import SelectorMixin
 from ._gmm_selector import GMMSelector
 from ._outlier import OutlierSelector
 from ._percentage_selector import PercentageSelector

divik/feature_selection/_stat_selector_mixin.py

@@ -2,7 +2,7 @@
 
 import numpy as np
 from sklearn.base import BaseEstimator
-from sklearn.feature_selection.base import SelectorMixin
+from sklearn.feature_selection._base import SelectorMixin
 
 
 class StatSelectorMixin(SelectorMixin, metaclass=ABCMeta):

docker/deploy.dockerfile

@@ -1,4 +1,4 @@
-FROM spectreteam/python_msi:v5.0.0
+FROM spectreteam/python_msi:v5.1.0.2019a.py37
 
 ENV PYTHONUNBUFFERED TRUE
 

docker/development.dockerfile

@@ -1,4 +1,4 @@
-FROM spectreteam/python_msi:v5.0.0
+FROM spectreteam/python_msi:v5.1.0.2019a.py37
 
 ENV PYTHONUNBUFFERED TRUE
 

docker/docs.dockerfile

@@ -1,4 +1,4 @@
-FROM spectreteam/python_msi:v5.0.0
+FROM spectreteam/python_msi:v5.1.0.2019a.py37
 
 COPY requirements.txt /requirements.txt
 

docker/unittest.dockerfile

@@ -1,4 +1,4 @@
-FROM spectreteam/python_msi:v5.0.0
+FROM spectreteam/python_msi:v5.1.0.2019a.py37
 
 ENV PYTHONUNBUFFERED TRUE
 

docs/instructions/installation.rst

@@ -15,7 +15,7 @@ To install latest stable version use::
 
 To install specific version, you can specify it in the command, e.g.::
 
-    docker pull gmrukwa/divik:2.3.5
+    docker pull gmrukwa/divik:2.3.6
 
 Python package
 --------------
@@ -43,4 +43,4 @@ package::
 
 or any stable tagged version, e.g.::
 
-    pip install divik==2.3.5
+    pip install divik==2.3.6

docs/instructions/simple_windows.rst

@@ -20,6 +20,6 @@ This is the simplest instruction to run DiviK on Windows.
 #. Adjust the configuration to your needs
 
 .. note:: Configuration follows the JSON format with fields defined as
-``here <https://github.com/gmrukwa/divik/blob/master/divik/_cli/divik.md>`_.
+`here <https://github.com/gmrukwa/divik/blob/master/divik/_cli/divik.md>`_.
 
 #. Double click the ``run_divik.bat``

requirements-base.txt

@@ -3,15 +3,14 @@ dash-html-components==0.13.4
 dash-core-components==0.42.0
 dash-renderer==0.17.0
 dash-table==3.1.11
-h5py==2.8.0
-matplotlib==2.2.2
-networkx==2.1
-numpy==1.15.2
-pandas==0.20.3
-pyamg==4.0.0
-scikit-image==0.14.1
-scikit-learn==0.19.1
-scipy==1.1.0
-statsmodels==0.10.2
-tqdm==4.11.2
-typing==3.6.2; python_version=='3.4'
+h5py
+matplotlib
+networkx
+numpy
+pandas
+pyamg
+scikit-image
+scikit-learn
+scipy
+statsmodels
+tqdm

requirements.txt

@@ -1,64 +1,47 @@
-appdirs==1.4.3
-atomicwrites==1.3.0
-attrs==18.2.0
-certifi==2018.11.29
-chardet==3.0.4
+attrs==19.3.0
 Click==7.0
-cloudpickle==0.7.0
 cycler==0.10.0
 dash==0.34.0
 dash-core-components==0.42.0
 dash-html-components==0.13.4
 dash-renderer==0.17.0
 dash-table==3.1.11
-dask==1.1.1
-decorator==4.3.2
-Flask==1.0.2
+decorator==4.4.1
+Flask==1.1.1
 Flask-Compress==1.4.0
-future==0.17.1
 h5py==2.8.0
-idna==2.8
-ipython-genutils==0.2.0
+imageio==2.6.1
+importlib-metadata==1.3.0
 itsdangerous==1.1.0
-Jinja2==2.10
-jsonschema==2.6.0
-jupyter-core==4.4.0
-kiwisolver==1.0.1
-MarkupSafe==1.1.0
-matplotlib==2.2.2
-more-itertools==5.0.0
-nbformat==4.4.0
-networkx==2.1
-numpy==1.15.2
-packaging==19.0
-pandas==0.20.3
-pathlib2==2.3.3
+Jinja2==2.10.3
+joblib==0.14.1
+kiwisolver==1.1.0
+MarkupSafe==1.1.1
+matplotlib==3.1.2
+more-itertools==8.0.2
+networkx==2.4
+numpy==1.18.0
+packaging==19.2
+pandas==0.25.3
 patsy==0.5.1
-Pillow==5.4.1
-plotly==3.6.0
-pluggy==0.8.1
-py==1.7.0
+Pillow==6.2.1
+plotly==4.4.1
+pluggy==0.13.1
+py==1.8.0
 pyamg==4.0.0
-pyarrow==0.12.0
-pybind11==2.2.4
-pyparsing==2.3.1
-pytest==4.2.0
-python-dateutil==2.8.0
-pytz==2018.9
-PyWavelets==1.0.1
-PyYAML==3.13
-quilt==2.9.12
-requests==2.21.0
+pybind11==2.4.3
+pyparsing==2.4.5
+pytest==5.3.2
+python-dateutil==2.8.1
+pytz==2019.3
+PyWavelets==1.1.1
 retrying==1.3.3
-scikit-image==0.14.1
-scikit-learn==0.19.1
-scipy==1.1.0
-six==1.12.0
+scikit-image==0.16.2
+scikit-learn==0.22
+scipy==1.4.1
+six==1.13.0
 statsmodels==0.10.2
-toolz==0.9.0
-tqdm==4.11.2
-traitlets==4.3.2
-typing==3.6.6
-urllib3==1.24.1
-Werkzeug==0.14.1
-xlrd==1.2.0
+tqdm==4.41.0
+wcwidth==0.1.7
+Werkzeug==0.16.0
+zipp==0.6.0

setup.py

@@ -17,13 +17,14 @@
     author_email='g.mrukwa@gmail.com',
     classifiers=[
         # based on https://pypi.python.org/pypi?%3Aaction=list_classifiers
-        'Development Status :: 3 - Alpha',
+        'Development Status :: 5 - Production/Stable',
         'Intended Audience :: Developers',
         'Intended Audience :: Science/Research',
         'License :: OSI Approved :: Apache Software License',
         'Programming Language :: Python :: 3',
-        'Programming Language :: Python :: 3.4',
         'Programming Language :: Python :: 3.5',
+        'Programming Language :: Python :: 3.6',
+        'Programming Language :: Python :: 3.7',
         'Topic :: Scientific/Engineering :: Artificial Intelligence',
         'Topic :: Scientific/Engineering :: Bio-Informatics',
         'Topic :: Scientific/Engineering :: Information Analysis',