Feature Constructor: Vectorize when possible

Orange/widgets/data/owfeatureconstructor.py

@@ -108,7 +108,12 @@ class FeatureEditor(QFrame):
 
 """.lstrip()
 
-    FUNCTIONS = dict(chain([(key, val) for key, val in math.__dict__.items()
+    # import functions from math - but if the function with the same name
+    # exists in np, import it from there
+    # TODO: We need to check that functions are equivalent
+    # TODO: Do we really want to import all functions from math?
+    FUNCTIONS = dict(chain([(key, np.__dict__.get(key, val))
+                            for key, val in math.__dict__.items()
                             if not key.startswith("_")],
                            [(key, val) for key, val in builtins.__dict__.items()
                             if key in {"str", "float", "int", "len",
@@ -1095,9 +1100,12 @@ def make_lambda(expression, args, env=None):
 __GLOBALS = {name: getattr(builtins, name) for name in __ALLOWED
              if hasattr(builtins, name)}
 
-__GLOBALS.update({name: getattr(math, name) for name in dir(math)
+# TODO: See the above TODO's about checking that np and math functions are equivalent etc. :)
+__GLOBALS.update({name: getattr(np, name, getattr(math, name))
+                  for name in dir(math)
                   if not name.startswith("_")})
 
+# TODO: These functions are not shown in the widget's combo. Intentionally?
 __GLOBALS.update({
     "normalvariate": random.normalvariate,
     "gauss": random.gauss,
@@ -1164,7 +1172,30 @@ def __init__(self, expression, args, extra_env=None, cast=None, use_values=False
 
     def __call__(self, instance, *_):
         if isinstance(instance, Orange.data.Table):
-            return [self(inst) for inst in instance]
+            y = None
+            try:
+                args = []
+                for _, var in self.args:
+                    col = instance.get_column_view(var)[0]
+                    if var.is_string:
+                        # Strings can't be handled well with numpy.
+                        # For instance, indexing a string column will return
+                        # i-th value instead of i-th character of each value
+                        break
+                    if var.is_discrete and not self.use_values:
+                        col = np.array(var.values)[col]
+                    args.append(col)
+                else:
+                    y = self.func(*args)
+                    # We allow nans, but infs come from division by zero etc
+                    # However, np.sqrt(-1) is nan.
+                    # TODO: catch warnings and fallback?
+                    if np.any(np.isinf(y)):
+                        y = None
+            except Exception as err:  # pylint: disable=bare-except
+                pass
+            if y is None:
+                return [self(inst) for inst in instance]
         else:
             try:
                 args = [str(instance[var]) if var.is_string
@@ -1178,9 +1209,9 @@ def __call__(self, instance, *_):
                 if not self.mask_exceptions:
                     raise
                 return np.nan
-            if self.cast:
-                y = self.cast(y)
-            return y
+        if self.cast:
+            y = self.cast(y)
+        return y
 
     def __reduce__(self):
         return type(self), (self.expression, self.args,

Orange/widgets/data/tests/test_owfeatureconstructor.py

@@ -500,7 +500,7 @@ def test_report(self):
 class TestFeatureEditor(unittest.TestCase):
     def test_has_functions(self):
         self.assertIs(FeatureEditor.FUNCTIONS["abs"], abs)
-        self.assertIs(FeatureEditor.FUNCTIONS["sqrt"], math.sqrt)
+        self.assertIs(FeatureEditor.FUNCTIONS["sqrt"], np.sqrt)
 
 
 class FeatureConstructorHandlerTests(unittest.TestCase):