diff --git a/nifty_field.py b/nifty_field.py
index 190eba6f8dc407e71619c311033e384984395c90..490a9a4dedb09d0ec4edaa96a1bdfdb3e9e5e839 100644
--- a/nifty_field.py
+++ b/nifty_field.py
@@ -9,6 +9,8 @@ from nifty.config import about,\
nifty_configuration as gc,\
dependency_injector as gdi
+from nifty.nifty_core import space
+
import nifty.nifty_utilities as utilities
POINT_DISTRIBUTION_STRATEGIES = DISTRIBUTION_STRATEGIES['global']
@@ -202,11 +204,10 @@ class field(object):
if val is None:
if kwargs == {}:
- val = self._map(lambda: self.cast((0,)))
+ val = map(lambda z: self.cast(z), (0,))
else:
- val = self._map(lambda: self.domain.get_random_values(
- codomain=self.codomain,
- **kwargs))
+ val = map(lambda z: self.domain.get_random_values(
+ codomain=z, **kwargs), self.codomain)
self.set_val(new_val=val, copy=copy)
def _parse_comm(self, comm):
@@ -229,7 +230,7 @@ class field(object):
return result_comm
def check_valid_domain(self, domain):
- if not isinstance(domain, np.ndarray):
+ if not isinstance(domain, tuple):
raise TypeError(about._errors.cstring(
"ERROR: The given domain is not a list."))
for d in domain:
@@ -245,15 +246,15 @@ class field(object):
def check_codomain(self, domain, codomain):
if codomain is None:
return False
- if domain.shape == codomain.shape:
+ if len(domain) == len(codomain):
return np.all(map((lambda d, c: d._check_codomain(c)), domain,
codomain))
else:
return False
def get_codomain(self, domain):
- if domain.shape == (1,):
- return np.array(domain[0].get_codomain())
+ if len(domain) == 1:
+ return (domain[0].get_codomain(),)
else:
# TODO implement for multiple domain get_codomain need
# calc_transform
@@ -268,7 +269,7 @@ class field(object):
else:
working_field = self.copy_empty()
- data_object = self._map(
+ data_object = map(
lambda z: self.domain.apply_scalar_function(z, function, inplace),
self.get_val())
@@ -276,7 +277,7 @@ class field(object):
return working_field
def copy(self, domain=None, codomain=None):
- copied_val = self._map(
+ copied_val = map(
lambda z: self.domain.unary_operation(z, op='copy'),
self.get_val())
new_field = self.copy_empty(domain=domain, codomain=codomain)
@@ -334,10 +335,10 @@ class field(object):
"""
if new_val is not None:
if copy:
- new_val = self._map(
- lambda z: self.domain.unary_operation(z, 'copy'),
+ new_val = map(
+ lambda z: self.unary_operation(z, 'copy'),
new_val)
- self.val = self._map(lambda z: self.domain.cast(z), new_val)
+ self.val = map(lambda z: self.cast(z), new_val)
return self.val
def get_val(self):
@@ -359,7 +360,7 @@ class field(object):
if len(key) > len(self.ishape):
if is_data_container:
- gotten = self._map(
+ gotten = map(
lambda z: self.domain.getitem(
z, key[len(self.ishape):]),
gotten)
@@ -382,7 +383,7 @@ class field(object):
is_data_container = False
if is_data_container:
- gotten = self._map(
+ gotten = map(
lambda z1, z2: self.domain.setitem(
z1, z2, key[len(self.ishape):]),
gotten, value)
@@ -607,7 +608,7 @@ class field(object):
else:
new_field = self.copy_empty()
- new_val = self._map(lambda y: self.domain.calc_weight(y, power=power),
+ new_val = map(lambda y: self.domain.calc_weight(y, power=power),
self.get_val())
new_field.set_val(new_val=new_val)
@@ -675,12 +676,12 @@ class field(object):
casted_x = self._cast_to_ishape(x)
# Compute the dot respecting the fact of discrete/continous spaces
if self.domain.discrete or bare:
- result = self._map(
+ result = map(
lambda z1, z2: self.domain.calc_dot(z1, z2),
self.get_val(),
casted_x)
else:
- result = self._map(
+ result = map(
lambda z1, z2: self.domain.calc_dot(
self.domain.calc_weight(z1, power=1),
z2),
@@ -744,7 +745,7 @@ class field(object):
else:
work_field = self.copy_empty()
- new_val = self._map(
+ new_val = map(
lambda z: self.domain.unary_operation(z, 'conjugate'),
self.get_val())
work_field.set_val(new_val=new_val)
@@ -789,7 +790,7 @@ class field(object):
else:
assert(new_domain.check_codomain(new_codomain))
- new_val = self._map(
+ new_val = map(
lambda z: self.domain.calc_transform(
z, codomain=new_domain, **kwargs),
self.get_val())
@@ -835,7 +836,7 @@ class field(object):
else:
new_field = self.copy_empty()
- new_val = self._map(
+ new_val = map(
lambda z: self.domain.calc_smooth(z, sigma=sigma, **kwargs),
self.get_val())
@@ -885,7 +886,7 @@ class field(object):
kwargs.__delitem__("codomain")
about.warnings.cprint("WARNING: codomain was removed from kwargs.")
- power_spectrum = self._map(
+ power_spectrum = map(
lambda z: self.domain.calc_power(z, codomain=self.codomain,
**kwargs),
self.get_val())
@@ -918,7 +919,7 @@ class field(object):
The new diagonal operator instance.
"""
- any_zero_Q = self._map(lambda z: (z == 0).any(), self.get_val())
+ any_zero_Q = map(lambda z: (z == 0).any(), self.get_val())
any_zero_Q = np.any(any_zero_Q)
if any_zero_Q:
raise AttributeError(
@@ -1020,7 +1021,7 @@ class field(object):
"\n- ishape = " + str(self.ishape)
def _unary_helper(self, x, op, **kwargs):
- result = self._map(
+ result = map(
lambda z: self.domain.unary_operation(z, op=op, **kwargs),
self.get_val())
return result
@@ -1237,7 +1238,7 @@ class field(object):
else:
other_val = self._cast_to_tensor_helper(other_val)
- new_val = self._map(
+ new_val = map(
lambda z1, z2: self.domain.binary_operation(z1, z2, op=op, cast=0),
self.get_val(),
other_val)
diff --git a/nifty_power_indices.py b/nifty_power_indices.py
index ae10d6cc36c9c8f5dd132fcf6c3c5549eecf806b..5b10c65b73963dd1fc33420ae40599055963a4d5 100644
--- a/nifty_power_indices.py
+++ b/nifty_power_indices.py
@@ -427,9 +427,8 @@ class power_indices(object):
class rg_power_indices(power_indices):
- def __init__(self, shape, dgrid, datamodel,
- allowed_distribution_strategies,
- zerocentered=False, log=False, nbin=None,
+ def __init__(self, shape, dgrid, allowed_distribution_strategies,
+ datamodel='not', zerocentered=False, log=False, nbin=None,
binbounds=None, comm=None):
"""
Returns an instance of the power_indices class. Given the shape and
diff --git a/test/test_nifty_field.py b/test/test_nifty_field.py
index 61f8fbb385037c1dadb30ea17ccbf4e2228204cd..0093fa4ebbce04b352562a8d89465af958e354e4 100644
--- a/test/test_nifty_field.py
+++ b/test/test_nifty_field.py
@@ -1,7 +1,7 @@
# -*- coding: utf-8 -*-
-from numpy.testing import assert_equal,\
- assert_almost_equal,\
+from numpy.testing import assert_equal, \
+ assert_almost_equal, \
assert_raises
from nose_parameterized import parameterized
@@ -9,21 +9,21 @@ import unittest
import itertools
import numpy as np
-from nifty import space,\
- point_space,\
- rg_space,\
- lm_space,\
- hp_space,\
+from nifty import space, \
+ point_space, \
+ rg_space, \
+ lm_space, \
+ hp_space, \
gl_space
from nifty.nifty_field import field
from nifty.nifty_core import POINT_DISTRIBUTION_STRATEGIES
-from nifty.rg.nifty_rg import RG_DISTRIBUTION_STRATEGIES,\
- gc as RG_GC
-from nifty.lm.nifty_lm import LM_DISTRIBUTION_STRATEGIES,\
- GL_DISTRIBUTION_STRATEGIES,\
- HP_DISTRIBUTION_STRATEGIES
+from nifty.rg.nifty_rg import RG_DISTRIBUTION_STRATEGIES, \
+ gc as RG_GC
+from nifty.lm.nifty_lm import LM_DISTRIBUTION_STRATEGIES, \
+ GL_DISTRIBUTION_STRATEGIES, \
+ HP_DISTRIBUTION_STRATEGIES
###############################################################################
@@ -34,6 +34,7 @@ def custom_name_func(testcase_func, param_num, param):
parameterized.to_safe_name("_".join(str(x) for x in param.args)),
)
+
###############################################################################
###############################################################################
@@ -92,62 +93,33 @@ for param in itertools.product([(1,), (4, 6), (5, 8)],
[False],
DATAMODELS['rg_space'],
fft_modules):
- space_list += [[(rg_space(shape=param[0],
- zerocenter=param[1],
- complexity=param[2],
- distances=param[3],
- harmonic=param[4],
- fft_module=param[6]),param[6])]]
+ space_list += [[rg_space(shape=param[0],
+ zerocenter=param[1],
+ complexity=param[2],
+ distances=param[3],
+ harmonic=param[4],
+ fft_module=param[6]), param[5]]]
###############################################################################
###############################################################################
class Test_field_init(unittest.TestCase):
-
- @parameterized.expand(space_list)
- def test_successfull_init_and_attributes(self, s, datamodel):
- f = field(domain=np.array([s]), dtype=s.dtype, datamodel=datamodel)
- assert(f.domain[0] is s)
- assert(s.check_codomain(f.codomain[0]))
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+ @parameterized.expand(
+ itertools.product([(1,), (4, 6), (5, 8)],
+ [False, True],
+ [0, 1, 2],
+ [None, 0.3],
+ [False],
+ fft_modules,
+ DATAMODELS['rg_space']),
+ testcase_func_name=custom_name_func)
+ def test_successfull_init_and_attributes(self, shape, zerocenter,
+ complexity, distances, harmonic,
+ fft_module, datamodel):
+ s = rg_space(shape=shape, zerocenter=zerocenter,
+ complexity=complexity, distances=distances,
+ harmonic=harmonic, fft_module=fft_module)
+ f = field(domain=(s,), dtype=s.dtype, datamodel=datamodel)
+ assert (f.domain[0] is s)
+ assert (s.check_codomain(f.codomain[0]))