Commit d6a40b95 authored by Martin Reinecke's avatar Martin Reinecke
Browse files

put tests in their correct location

parent 2da0de8b
Pipeline #12380 passed with stage
in 6 minutes and 2 seconds
......@@ -17,24 +17,18 @@
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import unittest
import numpy as np
from numpy.testing import assert_equal,\
assert_allclose
from nifty.config import dependency_injector as di
from nifty import Field,\
RGSpace,\
LMSpace,\
HPSpace,\
GLSpace,\
PowerSpace,\
FFTOperator,\
SmoothingOperator
FFTOperator
from itertools import product
from test.common import expand
from nose.plugins.skip import SkipTest
......@@ -54,7 +48,7 @@ def _get_rtol(tp):
return 1e-5
class Misc_Tests(unittest.TestCase):
class FFTOperatorTests(unittest.TestCase):
@expand(product([10, 11], [False, True], [0.1, 1, 3.7]))
def test_RG_distance_1D(self, dim1, zc1, d):
foo = RGSpace([dim1], zerocenter=zc1, distances=d)
......@@ -160,53 +154,3 @@ class Misc_Tests(unittest.TestCase):
v1 = np.sqrt(out.dot(out))
v2 = np.sqrt(inp.dot(fft.adjoint_times(out)))
assert_allclose(v1, v2, rtol=tol, atol=tol)
@expand(product([100, 200], [1, 0.4], [0., 1., 3.7],
[np.float64, np.complex128]))
def test_smooth_regular1(self, sz, d, sigma, tp):
tol = _get_rtol(tp)
sp = RGSpace(sz, harmonic=True, distances=d)
smo = SmoothingOperator(sp, sigma=sigma)
inp = Field.from_random(domain=sp, random_type='normal', std=1, mean=4,
dtype=tp)
out = smo(inp)
inp = inp.val.get_full_data()
assert_allclose(inp.sum(), out.sum(), rtol=tol, atol=tol)
@expand(product([10, 15], [7, 10], [1, 0.4], [2, 0.3], [0., 1., 3.7],
[np.float64, np.complex128]))
def test_smooth_regular2(self, sz1, sz2, d1, d2, sigma, tp):
tol = _get_rtol(tp)
sp = RGSpace([sz1, sz2], distances=[d1, d2], harmonic=True)
smo = SmoothingOperator(sp, sigma=sigma)
inp = Field.from_random(domain=sp, random_type='normal', std=1, mean=4,
dtype=tp)
out = smo(inp)
inp = inp.val.get_full_data()
assert_allclose(inp.sum(), out.sum(), rtol=tol, atol=tol)
@expand(product([100, 200], [False, True], [0., 1., 3.7],
[np.float64, np.complex128]))
def test_smooth_irregular1(self, sz, log, sigma, tp):
tol = _get_rtol(tp)
sp = RGSpace(sz, harmonic=True)
ps = PowerSpace(sp, nbin=sz, logarithmic=log)
smo = SmoothingOperator(ps, sigma=sigma)
inp = Field.from_random(domain=ps, random_type='normal', std=1, mean=4,
dtype=tp)
out = smo(inp)
inp = inp.val.get_full_data()
assert_allclose(inp.sum(), out.sum(), rtol=tol, atol=tol)
@expand(product([10, 15], [7, 10], [False, True], [0., 1., 3.7],
[np.float64, np.complex128]))
def test_smooth_irregular2(self, sz1, sz2, log, sigma, tp):
tol = _get_rtol(tp)
sp = RGSpace([sz1, sz2], harmonic=True)
ps = PowerSpace(sp, logarithmic=log)
smo = SmoothingOperator(ps, sigma=sigma)
inp = Field.from_random(domain=ps, random_type='normal', std=1, mean=4,
dtype=tp)
out = smo(inp)
inp = inp.val.get_full_data()
assert_allclose(inp.sum(), out.sum(), rtol=tol, atol=tol)
# NIFTy
# Copyright (C) 2017 Theo Steininger
#
# Author: Theo Steininger
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import unittest
import numpy as np
from numpy.testing import assert_equal,\
assert_allclose
from nifty.config import dependency_injector as di
from nifty import Field,\
RGSpace,\
PowerSpace,\
SmoothingOperator
from itertools import product
from test.common import expand
def _get_rtol(tp):
if (tp == np.float64) or (tp == np.complex128):
return 1e-10
else:
return 1e-5
class Misc_Tests(unittest.TestCase):
@expand(product([100, 200], [1, 0.4], [0., 1., 3.7],
[np.float64, np.complex128]))
def test_smooth_regular1(self, sz, d, sigma, tp):
tol = _get_rtol(tp)
sp = RGSpace(sz, harmonic=True, distances=d)
smo = SmoothingOperator(sp, sigma=sigma)
inp = Field.from_random(domain=sp, random_type='normal', std=1, mean=4,
dtype=tp)
out = smo(inp)
inp = inp.val.get_full_data()
assert_allclose(inp.sum(), out.sum(), rtol=tol, atol=tol)
@expand(product([10, 15], [7, 10], [1, 0.4], [2, 0.3], [0., 1., 3.7],
[np.float64, np.complex128]))
def test_smooth_regular2(self, sz1, sz2, d1, d2, sigma, tp):
tol = _get_rtol(tp)
sp = RGSpace([sz1, sz2], distances=[d1, d2], harmonic=True)
smo = SmoothingOperator(sp, sigma=sigma)
inp = Field.from_random(domain=sp, random_type='normal', std=1, mean=4,
dtype=tp)
out = smo(inp)
inp = inp.val.get_full_data()
assert_allclose(inp.sum(), out.sum(), rtol=tol, atol=tol)
@expand(product([100, 200], [False, True], [0., 1., 3.7],
[np.float64, np.complex128]))
def test_smooth_irregular1(self, sz, log, sigma, tp):
tol = _get_rtol(tp)
sp = RGSpace(sz, harmonic=True)
ps = PowerSpace(sp, nbin=sz, logarithmic=log)
smo = SmoothingOperator(ps, sigma=sigma)
inp = Field.from_random(domain=ps, random_type='normal', std=1, mean=4,
dtype=tp)
out = smo(inp)
inp = inp.val.get_full_data()
assert_allclose(inp.sum(), out.sum(), rtol=tol, atol=tol)
@expand(product([10, 15], [7, 10], [False, True], [0., 1., 3.7],
[np.float64, np.complex128]))
def test_smooth_irregular2(self, sz1, sz2, log, sigma, tp):
tol = _get_rtol(tp)
sp = RGSpace([sz1, sz2], harmonic=True)
ps = PowerSpace(sp, logarithmic=log)
smo = SmoothingOperator(ps, sigma=sigma)
inp = Field.from_random(domain=ps, random_type='normal', std=1, mean=4,
dtype=tp)
out = smo(inp)
inp = inp.val.get_full_data()
assert_allclose(inp.sum(), out.sum(), rtol=tol, atol=tol)
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