Merge branch 'master' into line_search

nifty/field.py

@@ -466,7 +466,7 @@ class Field(Loggable, Versionable, object):
         return result_obj
 
     def power_synthesize(self, spaces=None, real_power=True, real_signal=True,
-                         mean=None, std=None):
+                         mean=None, std=None, distribution_strategy=None):
         """ Yields a sampled field with `self`**2 as its power spectrum.
 
         This method draws a Gaussian random field in the harmonic partner
@@ -541,13 +541,16 @@ class Field(Loggable, Versionable, object):
         else:
             result_list = [None, None]
 
+        if distribution_strategy is None:
+            distribution_strategy = gc['default_distribution_strategy']
+
         result_list = [self.__class__.from_random(
                              'normal',
                              mean=mean,
                              std=std,
                              domain=result_domain,
                              dtype=np.complex,
-                             distribution_strategy=self.distribution_strategy)
+                             distribution_strategy=distribution_strategy)
                        for x in result_list]
 
         # from now on extract the values from the random fields for further

nifty/operators/fft_operator/transformations/rg_transforms.py

@@ -373,6 +373,10 @@ class MPIFFT(Transform):
                 original_shape = inp.shape
                 inp = inp.reshape(inp.shape[0], 1)
                 axes = (0, )
+                if original_shape[0]%2!=0:
+                    raise AttributeError("MPI-FFTs of onedimensional arrays "
+                        "with odd length are currently not supported due to a "
+                        "bug in FFTW. Please use a grid with even length.")
 
             if current_info is None:
                 transform_shape = list(inp.shape)

nifty/operators/invertible_operator_mixin/invertible_operator_mixin.py

@@ -71,7 +71,8 @@ class InvertibleOperatorMixin(object):
 
     def _times(self, x, spaces, x0=None):
         if x0 is None:
-            x0 = Field(self.target, val=0., dtype=x.dtype)
+            x0 = Field(self.target, val=0., dtype=x.dtype,
+                       distribution_strategy=x.distribution_strategy)
 
         (result, convergence) = self.__inverter(A=self.inverse_times,
                                                 b=x,
@@ -80,7 +81,8 @@ class InvertibleOperatorMixin(object):
 
     def _adjoint_times(self, x, spaces, x0=None):
         if x0 is None:
-            x0 = Field(self.domain, val=0., dtype=x.dtype)
+            x0 = Field(self.domain, val=0., dtype=x.dtype,
+                       distribution_strategy=x.distribution_strategy)
 
         (result, convergence) = self.__inverter(A=self.adjoint_inverse_times,
                                                 b=x,
@@ -89,7 +91,8 @@ class InvertibleOperatorMixin(object):
 
     def _inverse_times(self, x, spaces, x0=None):
         if x0 is None:
-            x0 = Field(self.domain, val=0., dtype=x.dtype)
+            x0 = Field(self.domain, val=0., dtype=x.dtype,
+                       distribution_strategy=x.distribution_strategy)
 
         (result, convergence) = self.__inverter(A=self.times,
                                                 b=x,
@@ -98,7 +101,8 @@ class InvertibleOperatorMixin(object):
 
     def _adjoint_inverse_times(self, x, spaces, x0=None):
         if x0 is None:
-            x0 = Field(self.target, val=0., dtype=x.dtype)
+            x0 = Field(self.target, val=0., dtype=x.dtype,
+                       distribution_strategy=x.distribution_strategy)
 
         (result, convergence) = self.__inverter(A=self.adjoint_times,
                                                 b=x,

nifty/probing/prober/prober.py

@@ -37,7 +37,8 @@ class Prober(object):
     """
 
     def __init__(self, domain=None, distribution_strategy=None, probe_count=8,
-                 random_type='pm1', compute_variance=False):
+                 random_type='pm1', probe_dtype=np.float,
+                 compute_variance=False):
 
         self._domain = utilities.parse_domain(domain)
         self._distribution_strategy = \
@@ -45,6 +46,7 @@ class Prober(object):
         self._probe_count = self._parse_probe_count(probe_count)
         self._random_type = self._parse_random_type(random_type)
         self.compute_variance = bool(compute_variance)
+        self.probe_dtype = np.dtype(probe_dtype)
 
     # ---Properties---
 
@@ -104,6 +106,7 @@ class Prober(object):
         """ a random-probe generator """
         f = Field.from_random(random_type=self.random_type,
                               domain=self.domain,
+                              dtype=self.probe_dtype,
                               distribution_strategy=self.distribution_strategy)
         uid = np.random.randint(1e18)
         return (uid, f)

test/test_operators/test_fft_operator.py

@@ -63,7 +63,7 @@ class FFTOperatorTests(unittest.TestCase):
         assert_equal(res[zc1 * (dim1 // 2), zc2 * (dim2 // 2)], 0.)
 
     @expand(product(["numpy", "fftw", "fftw_mpi"],
-                    [10, 11], [False, True], [False, True],
+                    [12, ], [False, True], [False, True],
                     [0.1, 1, 3.7],
                     [np.float64, np.complex128, np.float32, np.complex64]))
     def test_fft1D(self, module, dim1, zc1, zc2, d, itp):
@@ -86,7 +86,7 @@ class FFTOperatorTests(unittest.TestCase):
                         rtol=tol, atol=tol)
 
     @expand(product(["numpy", "fftw", "fftw_mpi"],
-                    [10, 11], [9, 12], [False, True],
+                    [12, 15], [9, 12], [False, True],
                     [False, True], [False, True], [False, True], [0.1, 1, 3.7],
                     [0.4, 1, 2.7],
                     [np.float64, np.complex128, np.float32, np.complex64]))

test/test_serialization.py

@@ -39,4 +39,7 @@ class SpaceSerializationTests(unittest.TestCase):
         repo.commit()
         assert_equal(space, repo.get('space'))
         assert_equal(field, repo.get('field'))
-        os.remove('test.h5')
+        try:
+            os.remove('test.h5')
+        except OSError:
+            pass