ref: change behavior for empty pipeline.get_features and update screenshots

Author: paulmueller

CHANGELOG

@@ -3,6 +3,9 @@
    learning features)
  - fix: modify the GUI to enable box filtering for ml_score_???
    features
+ - ref: pipeline.get_features now only returns features that are
+   available (previously all features were returned when no
+   datasets were in the pipeline)
 2.1.6
  - fix: export file names were allowed to have invalid characters
  - fix: Quick View showed filtered events that were not plotted

docs/scrots/make_scrots.sh

@@ -0,0 +1,10 @@
+#!/bin/bash
+
+# Run all scrots
+FILES=make_scrots_*.py
+for f in $FILES
+do
+  echo "Running $f..."
+  # take action on each file. $f store current file name
+  python $f
+done

docs/scrots/ui_ana_plot.png

@@ -100,15 +100,7 @@ def _populate_box_filters(self):
         times, additional features that were not there before
         (e.g. `ml_score_???`) are added.
         """
-        if self.pipeline is not None:
-            # Do not sort here, because we will have to sort anyway
-            # if there is no pipeline.
-            feats, labs = self.pipeline.get_features(scalar=True,
-                                                     ret_labels=True)
-        else:
-            # This does not include the `ml_score_???` features.
-            feats = dclab.dfn.scalar_feature_names
-            labs = [dclab.dfn.feature_name2label[f] for f in feats]
+        feats, labs = self.get_features_labels()
 
         self.verticalLayout_box.setAlignment(QtCore.Qt.AlignTop)
 
@@ -172,6 +164,22 @@ def filter_names(self):
     def pipeline(self):
         return self._pipeline
 
+    def get_features_labels(self):
+        """Wrapper around pipeline with default features if empty"""
+        if self.pipeline is not None and self.pipeline.num_slots != 0:
+            feats, labs = self.pipeline.get_features(scalar=True,
+                                                     label_sort=True,
+                                                     ret_labels=True,
+                                                     union=True)
+        else:
+            # fallback (nothing in the pipeline or no pipeline)
+            features = dclab.dfn.scalar_feature_names
+            labs = [dclab.dfn.get_feature_label(f) for f in features]
+            lf = sorted(zip(labs, features))
+            feats = [it[1] for it in lf]
+            labs = [it[0] for it in lf]
+        return feats, labs
+
     def on_duplicate_filter(self):
         # determine the new filter state
         filt_state = self.__getstate__()
@@ -196,9 +204,7 @@ def on_moreless(self):
         """User wants to choose box filters"""
         if not self._box_edit_view:
             # get available features to show
-            features = self.pipeline.get_features(scalar=True,
-                                                  label_sort=True,
-                                                  union=True)
+            features, _ = self.get_features_labels()
             # create missing range controls if applicable (e.g. ml_score_???)
             self._populate_box_filters()
             # Show all filters shared by all datasets to the user

docs/scrots/ui_qv_event.png

@@ -57,8 +57,7 @@ def __init__(self, *args, **kwargs):
         self.widget_range_y.range_changed.connect(self.on_range_changed)
 
     def __getstate__(self):
-        feats_srt = self.pipeline.get_features(
-            scalar=True, label_sort=True, plot_id=self.current_plot.identifier)
+        feats_srt = self.get_features()
 
         rx = self.widget_range_x.__getstate__()
         ry = self.widget_range_y.__getstate__()
@@ -130,8 +129,7 @@ def __getstate__(self):
     def __setstate__(self, state):
         if self.current_plot.identifier != state["identifier"]:
             raise ValueError("Plot identifier mismatch!")
-        feats_srt = self.pipeline.get_features(
-            scalar=True, label_sort=True, plot_id=self.current_plot.identifier)
+        feats_srt = self.get_features()
         toblock = [
             self.comboBox_axis_x,
             self.comboBox_axis_y,
@@ -397,6 +395,18 @@ def plot_names(self):
             ids = []
         return ids
 
+    def get_features(self):
+        """Wrapper around pipeline with default features if empty"""
+        feats_srt = self.pipeline.get_features(
+            scalar=True, label_sort=True, plot_id=self.current_plot.identifier)
+        if len(feats_srt) == 0:
+            # fallback (nothing in the pipeline)
+            features = dclab.dfn.scalar_feature_names
+            labs = [dclab.dfn.get_feature_label(f) for f in features]
+            lf = sorted(zip(labs, features))
+            feats_srt = [it[1] for it in lf]
+        return feats_srt
+
     def on_axis_changed(self):
         gen = self.__getstate__()["general"]
         if self.sender() == self.comboBox_axis_x:
@@ -518,10 +528,7 @@ def update_content(self, event=None, plot_index=None):
                     curfeat = None
                 # repopulate
                 cb.clear()
-                feats_srt = self.pipeline.get_features(
-                    scalar=True,
-                    label_sort=True,
-                    plot_id=self.current_plot.identifier)
+                feats_srt = self.get_features()
                 for feat in feats_srt:
                     cb.addItem(dclab.dfn.get_feature_label(feat), feat)
                 if curfeat is not None:

docs/scrots/ui_qv_poly.png

@@ -185,11 +185,15 @@ def update_feature_list(self, use_pipeline=True):
                                                        union=True,
                                                        label_sort=True)
         else:
-            # This is just a cheap way of getting a label-sorted list
-            # of all scalar features.
-            empty_pipeline = Pipeline()
-            self.features = empty_pipeline.get_features(scalar=True,
-                                                        label_sort=True)
+            # We want to compute statistics from a folder
+            # TODO:
+            # - Add ml_score_??? features
+
+            # label-sorted features
+            features = dclab.dfn.scalar_feature_names
+            labs = [dclab.dfn.get_feature_label(f) for f in features]
+            lf = sorted(zip(labs, features))
+            self.features = [it[1] for it in lf]
 
         self.listWidget_features.clear()
         for feat in self.features:

docs/scrots/ui_qv_settings.png

@@ -303,6 +303,11 @@ def get_features(self, scalar=False, label_sort=False, union=False,
             are used.
         ret_labels: bool
             If True, return the labels as well
+
+        Notes
+        -----
+        This function returns an empty list if there are no features
+        available.
         """
         if union:
             features = set()
@@ -325,8 +330,9 @@ def get_features(self, scalar=False, label_sort=False, union=False,
                         features = ds_features
                     else:
                         features &= ds_features
-            else:
-                features = dclab.dfn.scalar_feature_names
+        if features is None:
+            # This means that the pipeline is empty
+            features = []
         labs = [dclab.dfn.get_feature_label(f) for f in features]
         if label_sort:
             lf = sorted(zip(labs, features))