Commit b978003d authored by Ultima's avatar Ultima
Browse files

Modified .gitignore to not exclude everything except for optins.

parent ed578dc2
...@@ -12,37 +12,3 @@ ...@@ -12,37 +12,3 @@
.spyderproject .spyderproject
.document .document
build build
operators/*
!operators/__init__.py
!operators/nifty_explicit.py
!operators/nifty_operators.py
!operators/nifty_probing.py
!operators/nifty_probing_old.py
dummys/*
!dummys/__init__.py
!dummys/gfft_dummy.py
!dummys/MPI_dummy.py
rg/*
!rg/__init__.py
!rg/nifty_fft.py
!rg/nifty_rg.py
!rg/nifty_power_conversion_rg.py
lm/*
!lm/__init__.py
!lm/nifty_lm.py
!lm/nifty_power_conversion_lm.py
demos/*
!demos/__init__.py
!demos/demos_core.py
!demos/demo_faraday.py
!demos/demo_faraday_map.npy
!demos/demo_excaliwir.py
!demos/demo_wf1.py
!demos/demo_wf2.py
!demos/demo_wf3.py
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# -*- coding: utf-8 -*-
from numpy.testing import assert_equal,\
assert_almost_equal,\
assert_raises
from nose_parameterized import parameterized
import unittest
import itertools
import numpy as np
from nifty import space,\
point_space,\
rg_space,\
lm_space,\
hp_space,\
gl_space,\
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
###############################################################################
def custom_name_func(testcase_func, param_num, param):
return "%s_%s" % (
testcase_func.__name__,
parameterized.to_safe_name("_".join(str(x) for x in param.args)),
)
###############################################################################
###############################################################################
all_point_datatypes = [np.dtype('bool'),
np.dtype('int16'),
np.dtype('int32'),
np.dtype('int64'),
np.dtype('float32'),
np.dtype('float64'),
np.dtype('complex64'),
np.dtype('complex128')]
all_lm_datatypes = [np.dtype('complex64'),
np.dtype('complex128')]
all_gl_datatypes = [np.dtype('float64'),
np.dtype('float128')]
all_hp_datatypes = [np.dtype('float64')]
###############################################################################
DATAMODELS = {}
DATAMODELS['point_space'] = ['np'] + POINT_DISTRIBUTION_STRATEGIES
DATAMODELS['rg_space'] = ['np'] + RG_DISTRIBUTION_STRATEGIES
DATAMODELS['lm_space'] = ['np'] + LM_DISTRIBUTION_STRATEGIES
DATAMODELS['gl_space'] = ['np'] + GL_DISTRIBUTION_STRATEGIES
DATAMODELS['hp_space'] = ['np'] + HP_DISTRIBUTION_STRATEGIES
###############################################################################
fft_modules = []
for name in ['gfft', 'gfft_dummy', 'pyfftw']:
if RG_GC.validQ('fft_module', name):
fft_modules += [name]
###############################################################################
point_like_spaces = ['point_space', 'rg_space', 'lm_space', 'hp_space',
'gl_space']
###############################################################################
space_list = []
# Add point_spaces
for param in itertools.product([1, 10],
all_point_datatypes,
DATAMODELS['point_space']):
space_list += [[point_space(num=param[0],
dtype=param[1],
datamodel=param[2])]]
# Add rg_spaces
for param in itertools.product([(1,), (4, 6), (5, 8)],
[False, True],
[0, 1, 2],
[None, 0.3],
[False, True],
DATAMODELS['rg_space'],
fft_modules):
space_list += [[rg_space(shape=param[0],
zerocenter=param[1],
complexity=param[2],
distances=param[3],
harmonic=param[4],
datamodel=param[5],
fft_module=param[6])]]
###############################################################################
###############################################################################
class Test_field_init(unittest.TestCase):
@parameterized.expand(space_list)
def test_successfull_init_and_attributes(self, s):
s = s[0]
f = field(s)
assert(f.domain is s)
assert(s.check_codomain(f.codomain))
# -*- coding: utf-8 -*-
import numpy as np
from numpy.testing import assert_equal,\
assert_almost_equal,\
assert_raises
from nose_parameterized import parameterized
import unittest
from nifty.nifty_utilities import hermitianize,\
_hermitianize_inverter
from nifty.nifty_mpi_data import distributed_data_object,\
STRATEGIES
###############################################################################
def custom_name_func(testcase_func, param_num, param):
return "%s_%s" % (
testcase_func.__name__,
parameterized.to_safe_name("_".join(str(x) for x in param.args)),
)
###############################################################################
test_data = np.array([[-10, 9, 10, 2, -7, -8],
[ -5, 5, 5, -1, 9, 3],
[ -2, -2, 8, 9, 9, -10],
[ -8, -5, -2, -10, -7, 7],
[ 10, 6, -2, 6, -3, -1],
[ 8, 1, 10, -7, 6, -6]])
flipped_data = np.array([[-10, -8, -7, 2, 10, 9],
[ 8, -6, 6, -7, 10, 1],
[ 10, -1, -3, 6, -2, 6],
[ -8, 7, -7, -10, -2, -5],
[ -2, -10, 9, 9, 8, -2],
[ -5, 3, 9, -1, 5, 5]])
###############################################################################
###############################################################################
class Test_hermitianize_inverter(unittest.TestCase):
def test_with_ndarray(self):
assert_equal(_hermitianize_inverter(test_data), flipped_data)
@parameterized.expand(STRATEGIES['global'],
testcase_func_name=custom_name_func)
def test_with_d2o(self, distribution_strategy):
d = distributed_data_object(
test_data,
distribution_strategy=distribution_strategy)
assert_equal(_hermitianize_inverter(d).get_full_data(), flipped_data)
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