Context settings, radiobutton sparse_support check

Orange/projection/{base.py, pca.py}: supports_sparse attribute Orange/widgets/unsupervised/owpca.py: - normalize and radio buttons are now context settings. - enable/disable radio buttons selectively depending on sparse support - method is automatically re-selected to the first method that supports sparse decomposition (avoid hard-coding index). test_owpca.py: Remove error message test (not needed anymore).
biolab · May 17, 2017 · 26bef48 · 26bef48
1 parent ffd8ec8
commit 26bef48
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Showing 4 changed files with 41 additions and 18 deletions.
diff --git a/Orange/projection/base.py b/Orange/projection/base.py
@@ -82,6 +82,8 @@ class SklProjector(Projector, metaclass=WrapperMeta):
     __wraps__ = None
     _params = {}
     name = 'skl projection'
+    supports_sparse = True
+
     preprocessors = [Orange.preprocess.Continuize(),
                      Orange.preprocess.SklImpute()]
 

diff --git a/Orange/projection/pca.py b/Orange/projection/pca.py
@@ -34,6 +34,7 @@ def score(self, data):
 class PCA(SklProjector, _FeatureScorerMixin):
     __wraps__ = skl_decomposition.PCA
     name = 'pca'
+    supports_sparse = False
 
     def __init__(self, n_components=None, copy=True, whiten=False,
                  svd_solver='auto', tol=0.0, iterated_power='auto',
@@ -61,6 +62,7 @@ def fit(self, X, Y=None):
 class SparsePCA(SklProjector):
     __wraps__ = skl_decomposition.SparsePCA
     name = 'sparse pca'
+    supports_sparse = False
 
     def __init__(self, n_components=None, alpha=1, ridge_alpha=0.01,
                  max_iter=1000, tol=1e-8, method='lars', n_jobs=1, U_init=None,
@@ -125,6 +127,7 @@ def pca_variable(i):
 class IncrementalPCA(SklProjector):
     __wraps__ = skl_decomposition.IncrementalPCA
     name = 'incremental pca'
+    supports_sparse = False
 
     def __init__(self, n_components=None, whiten=False, copy=True,
                  batch_size=None, preprocessors=None):

diff --git a/Orange/widgets/unsupervised/owpca.py b/Orange/widgets/unsupervised/owpca.py
@@ -39,13 +39,15 @@ class OWPCA(widget.OWWidget):
                ("Components", Table),
                ("PCA", PCA)]
 
+    settingsHandler = settings.DomainContextHandler()
+
     ncomponents = settings.Setting(2)
     variance_covered = settings.Setting(100)
     batch_size = settings.Setting(100)
     address = settings.Setting('')
     auto_update = settings.Setting(True)
     auto_commit = settings.Setting(True)
-    normalize = settings.Setting(True)
+    normalize = settings.ContextSetting(True)
     decomposition_idx = settings.ContextSetting(0)
     maxp = settings.Setting(20)
     axis_labels = settings.Setting(10)
@@ -72,7 +74,7 @@ def __init__(self):
         self._cumulative = None
         self._line = False
         self._init_projector()
-        
+
         # Components Selection
         box = gui.vBox(self.controlArea, "Components Selection")
         form = QFormLayout()
@@ -124,15 +126,18 @@ def __init__(self):
         self.sampling_box.setVisible(remotely)
 
         # Decomposition
-        self.decomposition_box = gui.radioButtons(self.controlArea, self, 
-                        "decomposition_idx", [d.name for d in DECOMPOSITIONS], 
-                        box="Decomposition", callback=self._update_decomposition
+        self.decomposition_box = gui.radioButtons(
+            self.controlArea, self,
+            "decomposition_idx", [d.__name__ for d in DECOMPOSITIONS],
+            box="Decomposition", callback=self._update_decomposition
         )
 
         # Options
         self.options_box = gui.vBox(self.controlArea, "Options")
-        self.normalize_box = gui.checkBox(self.options_box, self, "normalize", 
-                    "Normalize data", callback=self._update_normalize)
+        self.normalize_box = gui.checkBox(
+            self.options_box, self, "normalize",
+            "Normalize data", callback=self._update_normalize
+        )
 
         self.maxp_spin = gui.spin(
             self.options_box, self, "maxp", 1, MAX_COMPONENTS,
@@ -169,6 +174,23 @@ def update_model(self):
         else:
             self.__timer.stop()
 
+    def update_buttons_sparse(self):
+        update_selection = False
+        if DECOMPOSITIONS[self.decomposition_idx].supports_sparse == False:
+            update_selection = True
+
+        for i, cls in enumerate(DECOMPOSITIONS):
+            if cls.supports_sparse == False:
+                self.decomposition_box.group.box.buttons[i].setEnabled(False)
+            elif update_selection == True:
+                # Fallback to first method that supports sparse
+                self.decomposition_idx = i
+                update_selection = False
+
+    def update_buttons_dense(self):
+        for i in range(len(DECOMPOSITIONS)):
+            self.decomposition_box.group.box.buttons[i].setEnabled(True)
+
     def start(self):
         if 'Abort' in self.start_button.text():
             self.rpca.abort()
@@ -184,6 +206,7 @@ def start(self):
             self.start_button.setText("Abort remote computation")
 
     def set_data(self, data):
+        self.closeContext()
         self.clear_messages()
         self.clear()
         self.start_button.setEnabled(False)
@@ -203,18 +226,19 @@ def set_data(self, data):
                 self.start_button.setEnabled(True)
         if not isinstance(data, SqlTable):
             self.sampling_box.setVisible(False)
+
+        self.openContext(data)
         if isinstance(data, Table):
             if data.is_sparse():
                 # PCA does not support sparse data
                 # Falling back to TruncatedSVD aka LSA
-                self.decomposition_idx = 1
                 self.normalize = False
                 self.normalize_box.setEnabled(False)
-                self.decomposition_box.setEnabled(False)
+                self.update_buttons_sparse()
             else:
                 self.normalize_box.setEnabled(True)
-                self.decomposition_box.setEnabled(True)
-            
+                self.update_buttons_dense()
+
             self._update_decomposition()
 
             if len(data.domain.attributes) == 0:
@@ -398,7 +422,7 @@ def _init_projector(self):
         self._pca_projector = cls(max_components=MAX_COMPONENTS)
         self._pca_projector.component = self.ncomponents
         self._pca_preprocessors = cls.preprocessors
-    
+
     def _update_decomposition(self):
         self.clear_messages()
         self._init_projector()

diff --git a/Orange/widgets/unsupervised/tests/test_owpca.py b/Orange/widgets/unsupervised/tests/test_owpca.py
@@ -70,9 +70,3 @@ def test_variance_shown(self):
         self.widget._update_selection_component_spin()
         var3 = self.widget.variance_covered
         self.assertGreater(var3, var2)
-
-    def test_error_on_sparse_data(self):
-        data = Table('iris')
-        data.X = sp.csr_matrix(data.X)
-        self.widget.set_data(data)
-        self.assertTrue(self.widget.Error.sparse_data.is_shown())