Merge pull request biolab#1897 from ales-erjavec/fixes/pca-all-const-col

[FIX] owpca: Handle the case of 0 total variance in the PCA solution
(cherry picked from commit ce7912e)

Orange/widgets/unsupervised/owpca.py

@@ -1,3 +1,5 @@
+import numbers
+
 from AnyQt.QtWidgets import QFormLayout, QLineEdit
 from AnyQt.QtGui import QColor
 from AnyQt.QtCore import Qt, QTimer
@@ -41,6 +43,11 @@ class OWPCA(widget.OWWidget):
 
     graph_name = "plot.plotItem"
 
+    class Warning(widget.OWWidget.Warning):
+        trivial_components = widget.Msg(
+            "All components of the PCA are trivial (explain 0 variance). "
+            "Input data is constant (or near constant).")
+
     def __init__(self):
         super().__init__()
         self.data = None
@@ -186,12 +193,15 @@ def fit(self):
             pca = self._pca_projector(data)
             variance_ratio = pca.explained_variance_ratio_
             cumulative = numpy.cumsum(variance_ratio)
-            self.components_spin.setRange(0, len(cumulative))
 
-            self._pca = pca
-            self._variance_ratio = variance_ratio
-            self._cumulative = cumulative
-            self._setup_plot()
+            if numpy.isfinite(cumulative[-1]):
+                self.components_spin.setRange(0, len(cumulative))
+                self._pca = pca
+                self._variance_ratio = variance_ratio
+                self._cumulative = cumulative
+                self._setup_plot()
+            else:
+                self.Warning.trivial_components()
 
             self.unconditional_commit()
 
@@ -204,6 +214,7 @@ def clear(self):
         self.plot_horlabels = []
         self.plot_horlines = []
         self.plot.clear()
+        self.Warning.trivial_components.clear()
 
     def get_model(self):
         if self.rpca is None:
@@ -222,6 +233,9 @@ def get_model(self):
 
     def _setup_plot(self):
         self.plot.clear()
+        if self._pca is None:
+            return
+
         explained_ratio = self._variance_ratio
         explained = self._cumulative
         p = min(len(self._variance_ratio), self.maxp)
@@ -279,7 +293,9 @@ def _on_cut_changed(self, line):
         self._set_horline_pos()
 
         if self._pca is not None:
-            self.variance_covered = self._cumulative[components - 1] * 100
+            var = self._cumulative[components - 1]
+            if numpy.isfinite(var):
+                self.variance_covered = int(var * 100)
 
         if current != self._nselected_components():
             self._invalidate_selection()
@@ -295,7 +311,10 @@ def _update_selection_component_spin(self):
             cut = len(self._variance_ratio)
         else:
             cut = self.ncomponents
-        self.variance_covered = self._cumulative[cut - 1] * 100
+
+        var = self._cumulative[cut - 1]
+        if numpy.isfinite(var):
+            self.variance_covered = int(var) * 100
 
         if numpy.floor(self._line.value()) + 1 != cut:
             self._line.setValue(cut - 1)
@@ -339,7 +358,8 @@ def _nselected_components(self):
         var_max = self._cumulative[max_comp - 1]
         if var_max != numpy.floor(self.variance_covered / 100.0):
             cut = max_comp
-            self.variance_covered = var_max * 100
+            assert numpy.isfinite(var_max)
+            self.variance_covered = int(var_max * 100)
         else:
             self.ncomponents = cut = numpy.searchsorted(
                 self._cumulative, self.variance_covered / 100.0) + 1
@@ -391,6 +411,20 @@ def send_report(self):
         ))
         self.report_plot()
 
+    @classmethod
+    def migrate_settings(cls, settings, version):
+        if "variance_covered" in settings:
+            # Due to the error in gh-1896 the variance_covered was persisted
+            # as a NaN value, causing a TypeError in the widgets `__init__`.
+            vc = settings["variance_covered"]
+            if isinstance(vc, numbers.Real):
+                if numpy.isfinite(vc):
+                    vc = int(vc)
+                else:
+                    vc = 100
+                settings["variance_covered"] = vc
+
+
 def main():
     import gc
     from AnyQt.QtWidgets import QApplication

Orange/widgets/unsupervised/tests/test_owpca.py

@@ -6,10 +6,18 @@
 class TestOWDistanceMatrix(WidgetTest):
 
     def setUp(self):
-        self.widget = self.create_widget(OWPCA)
+        self.widget = self.create_widget(OWPCA)  # type: OWPCA
 
     def test_set_variance100(self):
         iris = Table("iris")[:5]
         self.widget.set_data(iris)
         self.widget.variance_covered = 100
         self.widget._update_selection_variance_spin()
+
+    def test_constant_data(self):
+        data = Table("iris")[::5]
+        data.X[:, :] = 1.0
+        self.send_signal("Data", data)
+        self.assertTrue(self.widget.Warning.trivial_components.is_shown())
+        self.assertIsNone(self.get_output("Transformed Data"))
+        self.assertIsNone(self.get_output("Components"))