Commit c4d65780 authored by Jait Dixit's avatar Jait Dixit
Browse files

Merge branch 'master' into add_axes_to_rg_fft

parents 38c6be56 d9c94eb0
Pipeline #3214 skipped
......@@ -406,32 +406,26 @@ class distributed_data_object(object):
"""
remember_hermitianQ = self.hermitian
if inplace is True:
temp = self
if dtype is not None and self.dtype != np.dtype(dtype):
about.warnings.cprint(
"WARNING: Inplace dtype conversion is not possible!")
local_data = self.get_local_data(copy=False)
try:
result_data = function(local_data)
except:
about.warnings.cprint(
"WARNING: Trying to use np.vectorize!")
result_data = np.vectorize(function)(local_data)
if inplace is True:
result_d2o = self
else:
temp = self.copy_empty(dtype=dtype)
result_d2o = self.copy_empty(dtype=result_data.dtype)
if np.prod(self.local_shape) != 0:
try:
temp.data[:] = function(self.data)
except:
about.warnings.cprint(
"WARNING: Trying to use np.vectorize!")
temp.data[:] = np.vectorize(function)(self.data)
else:
# Noting to do here. The value-empty array
# is also geometrically empty
pass
result_d2o.set_local_data(result_data, copy=False)
if function in (np.exp, np.log):
temp.hermitian = remember_hermitianQ
result_d2o.hermitian = remember_hermitianQ
else:
temp.hermitian = False
return temp
result_d2o.hermitian = False
return result_d2o
def apply_generator(self, generator, copy=False):
""" Evaluates generator(local_shape) and stores the result locally.
......
......@@ -87,6 +87,7 @@ class FFTW(FFT):
if 'pyfftw' not in gdi:
raise ImportError("The module pyfftw is needed but not available.")
self.name = 'pyfftw'
# The plan_dict stores the plan_and_info objects which correspond
# to a certain set of (field_val, domain, codomain) sets.
self.plan_dict = {}
......@@ -402,6 +403,7 @@ class GFFT(FFT):
"""
def __init__(self, fft_module_name):
self.name = fft_module_name
self.fft_machine = gdi.get(fft_module_name)
if self.fft_machine is None:
raise ImportError(
......
......@@ -258,6 +258,7 @@ class rg_space(point_space):
distances=self.distances,
harmonic=self.harmonic,
datamodel=self.datamodel,
fft_module=self.fft_machine.name,
comm=self.comm)
def get_shape(self):
......@@ -482,6 +483,7 @@ class rg_space(point_space):
distances = 1 / (np.array(self.paradict['shape']) *
np.array(self.distances))
datamodel = self.datamodel
fft_module = self.fft_machine.name
comm = self.comm
complexity = {0: 1, 1: 0, 2: 2}[self.paradict['complexity']]
harmonic = bool(not self.harmonic)
......@@ -492,6 +494,7 @@ class rg_space(point_space):
distances=distances,
harmonic=harmonic,
datamodel=datamodel,
fft_module=fft_module,
comm=comm)
return new_space
......
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