Merge pull request #3 from ZanMervic/develop

Fixes to widget documentation, Install TensorFlow button

.gitignore

@@ -48,7 +48,7 @@ coverage.xml
 
 
 # Sphinx documentation
-docs/_build/
+doc/_build/
 
 # Jupyter Notebook
 .ipynb_checkpoints

orangecontrib/fairness/modeling/adversarial.py

@@ -28,7 +28,6 @@ class AdversarialDebiasingModel(Model):
     def __init__(self, model):
         super().__init__()
         self._model = model
-        self.params = vars()
 
     def predict(self, data):
         """Function used to predict on new data"""

orangecontrib/fairness/widgets/__init__.py

@@ -9,21 +9,21 @@
 BACKGROUND = "#FFE559"
 
 # Location of widget help files.
-# WIDGET_HELP_PATH = (
-#     # Development documentation
-#     # You need to build help pages manually using
-#     # make htmlhelp
-#     # inside doc folder
-#     ("{DEVELOP_ROOT}/doc/_build/html/index.html", None),
+WIDGET_HELP_PATH = (
+    # Development documentation
+    # You need to build help pages manually using
+    # make htmlhelp
+    # inside doc folder
+    ("{DEVELOP_ROOT}/doc/_build/html/index.html", None),
 
-#     # Documentation included in wheel
-#     # Correct DATA_FILES entry is needed in setup.py and documentation has to be built
-#     # before the wheel is created.
-#     ("{}/help/orange3-fairness/index.html".format(sysconfig.get_path("data")), None),
+    # Documentation included in wheel
+    # Correct DATA_FILES entry is needed in setup.py and documentation has to be built
+    # before the wheel is created.
+    ("{}/help/orange3-fairness/index.html".format(sysconfig.get_path("data")), None),
 
-#     # Online documentation url, used when the local documentation is not available.
-#     # Url should point to a page with a section Widgets. This section should
-#     # includes links to documentation pages of each widget. Matching is
-#     # performed by comparing link caption to widget name.
-#     ("http://orange3-fairness.readthedocs.io/en/latest/", "")
-# )
+    # Online documentation url, used when the local documentation is not available.
+    # Url should point to a page with a section Widgets. This section should
+    # includes links to documentation pages of each widget. Matching is
+    # performed by comparing link caption to widget name.
+    ("http://orange3-fairness.readthedocs.io/en/latest/", "")
+)

orangecontrib/fairness/widgets/owadversarialdebiasing.py

@@ -7,8 +7,9 @@
 from Orange.widgets.utils.concurrent import TaskState, ConcurrentWidgetMixin
 from Orange.base import Model
 from Orange.widgets.widget import Msg
+from orangecanvas.application.addons import AddonManagerDialog
 
-from AnyQt.QtWidgets import QFormLayout, QLabel, QVBoxLayout
+from AnyQt.QtWidgets import QFormLayout, QLabel, QVBoxLayout, QPushButton
 from AnyQt.QtCore import Qt
 
 from orangecontrib.fairness.modeling.adversarial import AdversarialDebiasingLearner
@@ -208,16 +209,27 @@ def no_tensorflow_layout(self):
         layout = QVBoxLayout()
         label = QLabel(
             'The Adversarial Debiasing widget requires TensorFlow, which is not installed.\n' 
-            'Install it via Options->Add-ons by clicking "Add more...", typing "tensorflow", and hitting "Add".\n'
-            'Note: TensorFlow installation may render Orange3 unusable, requiring a reinstallation.'
+            'You can install it by clicking the "Install TensorFlow" button below, selecting \n'
+            'the checkbox next to the "tensorflow" text and clicking the "Ok" button.\n'
+            'After that, you will need to restart Orange.'
         )
         label.setWordWrap(True)
         layout.addWidget(label)
+        button = QPushButton("Install TensorFlow")
+        button.clicked.connect(self.instaall_tensorflow)
+        layout.addWidget(button)
 
         box = gui.widgetBox(self.controlArea, True, orientation=layout)
 
         self.Error.add_message("no_tensorflow", TENSORFLOW_NOT_INSTALLED)
         self.Error.no_tensorflow()
+
+    def instaall_tensorflow(self):
+        """
+        Installs tensorflow using the AddonManagerDialog
+        """
+        manager = AddonManagerDialog(self)
+        manager.runQueryAndAddResults(["tensorflow"])
 
     def add_main_layout(self):
         if is_tensorflow_installed():

orangecontrib/fairness/widgets/tests/test_owadversarialdebiasing.py

@@ -124,122 +124,5 @@ def test_callback_with_learner(self):
         self.assertTrue(0 <= self.last_received_progress <= 100)
 
 
-
-
 if __name__ == "__main__":
-    unittest.main()
-
-
-
-
-
-
-
-
-
-
-
-# def test_cross_validation(self):
-#     """Check if the widget works with cross validation"""
-#     self.widget.number_of_epochs = 10
-#     self.widget.debias = False
-
-#     test_data = Table(self.data_path_adult)
-
-#     learner = self.widget.create_learner()
-
-#     cv = CrossValidation(k=5, random_state=42, store_data=True)
-#     results = cv(test_data, [learner])
-
-#     self.assertIsNotNone(results)
-#     print("Cross validation results:")
-#     print_metrics(results)
-
-# def test_train_test_split(self):
-#     """Check if the widget works with a normal train-test split"""
-#     self.widget.number_of_epochs = 10
-#     self.widget.debias = False
-
-#     test_data = Table(self.data_path_adult)
-
-#     learner = self.widget.create_learner()
-
-#     test_on_training = TestOnTrainingData(store_data=True)
-#     results = test_on_training(test_data, [learner])
-
-#     self.assertIsNotNone(results)
-#     print("Train test split results:")
-#     print_metrics(results)
-
-
-# def test_compatibility_with_test_and_score(self):
-#     """Check that the widget works with the predictions widget"""
-#     self.test_and_score = self.create_widget(OWTestAndScore)
-
-#     self.widget.number_of_epochs = 10
-#     self.widget.debias = False
-
-#     data_sample = Table("orangedemo/tests/datasets/adult_sample.pkl")
-#     data_remaining = Table("orangedemo/tests/datasets/adult_remaining.pkl")
-#     self.send_signal(self.widget.Inputs.data, data_sample)
-
-#     self.wait_until_finished(self.widget, timeout=2000000)
-
-#     learner = self.get_output(self.widget.Outputs.learner)
-
-#     self.send_signal(
-#         self.test_and_score.Inputs.train_data, data_remaining, widget=self.test_and_score
-#     )
-#     self.send_signal(
-#         self.test_and_score.Inputs.learner, learner, widget=self.test_and_score
-#     )
-#     results = self.get_output(
-#         self.test_and_score.Outputs.evaluations_results, widget=self.test_and_score
-#     )
-
-#     print_metrics(results)
-
-# def test_compatibility_with_predictions(self):
-#     """Check that the widget works with the predictions widget"""
-#     self.predictions = self.create_widget(OWPredictions)
-
-#     self.widget.number_of_epochs = 10
-#     self.widget.debias = False
-
-#     data_sample = Table("orangedemo/tests/datasets/adult_sample.pkl")
-#     data_remaining = Table("orangedemo/tests/datasets/adult_remaining.pkl")
-#     self.send_signal(self.widget.Inputs.data, data_sample)
-
-#     self.wait_until_finished(self.widget, timeout=2000000)
-
-#     model = self.get_output(self.widget.Outputs.model)
-
-#     self.send_signal(
-#         self.predictions.Inputs.data, data_remaining, widget=self.predictions
-#     )
-#     self.send_signal(
-#         self.predictions.Inputs.predictors, model, widget=self.predictions
-#     )
-#     results = self.get_output(
-#         self.predictions.Outputs.evaluation_results, widget=self.predictions
-#     )
-
-#     print_metrics(results)
-
-# def test_model_with_predictions_and_average_impute(self):
-#     from Orange.widgets.evaluate.owpredictions import OWPredictions
-
-#     self.predictions = self.create_widget(OWPredictions)
-
-#     self.widget.number_of_epochs = 10
-#     self.widget.debias = True
-#     test_data = Table("C:/Users/zanme/Downloads/my_adult.pkl")
-
-#     self.send_signal(self.widget.Inputs.data, test_data)
-#     self.wait_until_finished(self.widget, timeout=200000)
-#     model = self.get_output(self.widget.Outputs.model)
-
-#     self.send_signal(self.predictions.Inputs.data, test_data)
-#     self.send_signal(self.predictions.Inputs.predictors, model)
-#     results = self.get_output(self.predictions.Outputs.evaluation_results)
-#     print(CA(results))
+    unittest.main()

orangecontrib/fairness/widgets/utils.py

@@ -69,7 +69,6 @@ def wrapper(widget, input, *args, **kwargs):
 
 
 
-#TODO: Make the fairness widgets compatible with eachother.
 def check_for_reweighing_preprocessor(f):
     """A function which checks if the input to a widget is a reweighing preprocessor."""
     from orangecontrib.fairness.widgets.owreweighing import ReweighingTransform

setup.py

@@ -1,5 +1,5 @@
 from setuptools import setup, find_packages
-from os import path
+from os import path, walk
 
 VERSION = "0.1.6"
 
@@ -10,6 +10,19 @@
 except FileNotFoundError:
     LONG_DESCRIPTION = ""
 
+
+DATA_FILES = []
+
+def include_documentation(local_dir, install_dir):
+    global DATA_FILES
+    doc_files = []
+    for dirpath, dirs, files in walk(local_dir):
+        doc_files.append((dirpath.replace(local_dir, install_dir),
+                          [path.join(dirpath, f) for f in files]))
+    DATA_FILES.extend(doc_files)
+
+include_documentation('doc/_build/html', 'help/orange3-fairness')
+
 setup(
     name="Orange3-Fairness",
     version=VERSION,
@@ -41,6 +54,9 @@
     entry_points={
         "orange3.addon": ("Orange3-Fairness = orangecontrib.fairness",),
         "orange.widgets": ("Fairness = orangecontrib.fairness.widgets",),
+        "orange.canvas.help": (
+        'html-index = orangecontrib.fairness.widgets:WIDGET_HELP_PATH',
+        ),
         },
     install_requires=[
         "Orange3",
@@ -54,4 +70,5 @@
             "recommonmark",
         ]
     },
+    data_files=DATA_FILES,
 )