ramdomscs in pypi

.github/workflows/python-package.yml

@@ -29,7 +29,6 @@ jobs:
         python -m pip install --upgrade pip setuptools wheel
         python -m pip install flake8 pytest pytest-cov
         if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
-        pip install git+https://github.com/thibgo/randomscm.git@v0.0.0-alpha
 
     - name: install summit
       run: |

.gitlab-ci.yml

@@ -7,7 +7,7 @@ tests:
         - export LC_ALL=C.UTF-8
         - export LANG=C.UTF-8
         - if [ -f requirements.txt ]; then pip3 install -r requirements.txt; fi
-        - pip3 install -e .[install]
+        - pip3 install -e .
         - pip3 install -e .[test]
         - pytest --cov=. --cov-report=html
     coverage: '/^TOTAL.+?(\d+\%)$/'
@@ -50,7 +50,6 @@ pages:
         - export LC_ALL=C.UTF-8
         - export LANG=C.UTF-8
         - if [ -f requirements.txt ]; then pip3 install -r requirements.txt; fi
-        - pip3 install git+https://github.com/thibgo/randomscm.git@v0.0.0-alpha
         - pip3 install -e .[test]
         - pip3 install -e .[doc]
         - pytest --cov=. --cov-report=html

requirements.txt

@@ -14,5 +14,6 @@ tabulate>=0.8.6
 pyscm-ml>=1.0.0
 imbalanced-learn>=0.10.1
 scikit-multimodallearn==0.0.3
+randomscm==0.1.2
 # Dépendances depuis des dépôts Git
-# randomscm @ git+https://github.com/thibgo/randomscm.git@v0.0.0-alpha # pip install -e .[install]
+# randomscm @ git+https://github.com/thibgo/randomscm.git@v0.0.0-alpha
\ No newline at end of file

setup.py

@@ -150,8 +150,7 @@ def setup_package():
     extras_require = {
          'test' : ['pytest', 'pytest-cov'],
          'doc' : ['sphinx >= 3.0.2', 'numpydoc', 'docutils', 'sphinx-autoapi',
-                 'sphinx_rtd_theme'],
-        'install' : ['randomscm @ git+https://github.com/thibgo/randomscm.git@v0.0.0-alpha']}
+                 'sphinx_rtd_theme']}
 
 
     setup(version=version,

summit/multiview_platform/monoview_classifiers/random_scm.py

@@ -119,7 +119,7 @@ class ScmBagging(RandomScmClassifier, BaseMonoviewClassifier):
                  max_samples=max_samples,
                  max_features=max_features,
                  max_rules=max_rules,
-                 p_options=p_options,
+                 p=p_options,
                  model_type=model_type,
                  random_state=random_state)
         self.param_names = ["n_estimators", "max_rules", "max_samples", "max_features", "model_type", "p_options", "random_state"]