track std of scores along with their averages

experiments/matrix-completion-accuracy.py

@@ -151,37 +151,55 @@ class ScoreSet(object):
         if self.verbose:
             print("--> %s:%s %0.4f" % (group, score_type, value))
 
-    def averages(self):
+    def score_types(self):
+        result = set([])
+        for (g, d) in sorted(self.groups.items()):
+            for score_type in sorted(d.keys()):
+                result.add(score_type)
+        return list(sorted(result))
+
+    def _reduce_scores(self, reduce_fn):
+        score_types = self.score_types()
         return {
             group:
                 OrderedDict([
-                    (score_type, np.mean(scores))
-                    for (score_type, scores)
-                    in sorted(score_dict.items())
+                    (score_type, reduce_fn(score_dict[score_type]))
+                    for score_type
+                    in score_types
                 ])
             for (group, score_dict)
             in self.groups.items()
         }
 
-    def score_types(self):
-        result = set([])
-        for (g, d) in sorted(self.groups.items()):
-            for score_type in sorted(d.keys()):
-                result.add(score_type)
-        return list(result)
+    def averages(self):
+        return self._reduce_scores(np.mean)
+
+    def stds(self):
+        return self._reduce_scores(np.std)
 
     def to_csv(self, filename):
         with open(filename, "w") as f:
-            score_types = scores.score_types()
-            header_list = ["name"] + list(score_types)
+            header_list = ["name"]
+            score_types = self.score_types()
+            for score_type in score_types:
+                header_list.append(score_type)
+                header_list.append(score_type + "_std")
+
             header_line = ",".join(header_list) + "\n"
             if self.verbose:
                 print(header_line)
             f.write(header_line)
-            for name, score_type_dict in sorted(scores.averages().items()):
+
+            score_averages = self.averages()
+            score_stds = self.stds()
+
+            for name in sorted(score_averages.keys()):
                 line_elements = [name]
-                for _, value in sorted(score_type_dict.items()):
-                    line_elements.append("%0.4f" % value)
+                for score_type in score_types:
+                    line_elements.append(
+                        "%0.4f" % score_averages[name][score_type])
+                    line_elements.append(
+                        "%0.4f" % score_stds[name][score_type])
                 line = ",".join(line_elements) + "\n"
                 if self.verbose:
                     print(line)
@@ -204,7 +222,7 @@ if __name__ == "__main__":
         "zeroFill": SimpleFill("zero"),
         "MICE": MICE(
             n_burn_in=5,
-            n_imputations=20,
+            n_imputations=25,
             min_value=None if args.normalize_rows or args.normalize_columns else 0,
             max_value=None if args.normalize_rows or args.normalize_columns else 1,
             verbose=VERBOSE),