Merge branch 'nifty2go' into fun_with_operators

nifty/data_objects/random.py

@@ -32,6 +32,16 @@ class Random(object):
 
     @staticmethod
     def normal(dtype, shape, mean=0., std=1.):
+        if not (np.issubdtype(dtype, np.floating) or
+                np.issubdtype(dtype, np.complexfloating)):
+            raise TypeError("dtype must be float or complex")
+        if not np.isscalar(mean) or not np.isscalar(std):
+            raise TypeError("mean and std must be scalars")
+        if np.issubdtype(type(std), np.complexfloating):
+            raise TypeError("std must not be complex")
+        if ((not np.issubdtype(dtype, np.complexfloating)) and
+                np.issubdtype(type(mean), np.complexfloating)):
+            raise TypeError("mean must not be complex for a real result field")
         if np.issubdtype(dtype, np.complexfloating):
             x = np.empty(shape, dtype=dtype)
             x.real = np.random.normal(mean.real, std*np.sqrt(0.5), shape)
@@ -42,12 +52,20 @@ class Random(object):
 
     @staticmethod
     def uniform(dtype, shape, low=0., high=1.):
+        if not np.isscalar(low) or not np.isscalar(high):
+            raise TypeError("low and high must be scalars")
+        if (np.issubdtype(type(low), np.complexfloating) or
+                np.issubdtype(type(high), np.complexfloating)):
+            raise TypeError("low and high must not be complex")
         if np.issubdtype(dtype, np.complexfloating):
             x = np.empty(shape, dtype=dtype)
             x.real = np.random.uniform(low, high, shape)
             x.imag = np.random.uniform(low, high, shape)
         elif np.issubdtype(dtype, np.integer):
-            x = np.random.random.randint(low, high+1, shape)
+            if not (np.issubdtype(type(low), np.integer) and
+                    np.issubdtype(type(high), np.integer)):
+                raise TypeError("low and high must be integer")
+            x = np.random.randint(low, high+1, shape)
         else:
             x = np.random.uniform(low, high, shape)
         return x.astype(dtype, copy=False)

nifty/field.py

@@ -427,13 +427,19 @@ class Field(object):
         return self._contraction_helper('max', spaces)
 
     def mean(self, spaces=None):
+        if self.scalar_weight(spaces) is not None:
             return self._contraction_helper('mean', spaces)
+        raise NotImplementedError
 
     def var(self, spaces=None):
+        if self.scalar_weight(spaces) is not None:
             return self._contraction_helper('var', spaces)
+        raise NotImplementedError
 
     def std(self, spaces=None):
+        if self.scalar_weight(spaces) is not None:
             return self._contraction_helper('std', spaces)
+        return sqrt(self.var(spaces))
 
     def copy_content_from(self, other):
         if not isinstance(other, Field):