test_field.py 5.22 KB
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# 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/>.
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#
# Copyright(C) 2013-2017 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.
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import unittest
import numpy as np
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from numpy.testing import assert_equal, assert_allclose
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from itertools import product
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import nifty4 as ift
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from test.common import expand
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SPACES = [ift.RGSpace((4,)), ift.RGSpace((5))]
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SPACE_COMBINATIONS = [(), SPACES[0], SPACES[1], SPACES]
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class Test_Interface(unittest.TestCase):
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    @expand(product(SPACE_COMBINATIONS,
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                    [['domain', ift.DomainTuple],
                     ['val', ift.dobj.data_object],
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                     ['shape', tuple],
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                     ['size', (np.int, np.int64)]]))
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    def test_return_types(self, domain, attribute_desired_type):
        attribute = attribute_desired_type[0]
        desired_type = attribute_desired_type[1]
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        f = ift.Field(domain=domain, val=1.)
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        assert_equal(isinstance(getattr(f, attribute), desired_type), True)
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def _spec1(k):
    return 42/(1.+k)**2


def _spec2(k):
    return 42/(1.+k)**3


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class Test_Functionality(unittest.TestCase):
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    @expand(product([ift.RGSpace((8,), harmonic=True),
                     ift.RGSpace((8, 8), harmonic=True, distances=0.123)],
                    [ift.RGSpace((8,), harmonic=True),
                     ift.LMSpace(12)]))
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    def test_power_synthesize_analyze(self, space1, space2):
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        np.random.seed(11)
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        p1 = ift.PowerSpace(space1)
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        p1val = _spec1(p1.k_lengths)
        fp1 = ift.Field(p1, val=ift.dobj.from_global_data(p1val))
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        p2 = ift.PowerSpace(space2)
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        p2val = _spec2(p2.k_lengths)
        fp2 = ift.Field(p2, val=ift.dobj.from_global_data(p2val))
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        outer = ift.dobj.from_global_data(np.outer(p1val, p2val))
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        fp = ift.Field((p1, p2), val=outer)
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        samples = 500
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        ps1 = 0.
        ps2 = 0.
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        for ii in range(samples):
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            sk = ift.power_synthesize(fp, spaces=(0, 1), real_signal=True)
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            sp = ift.power_analyze(sk, spaces=(0, 1),
                                   keep_phase_information=False)
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            ps1 += sp.sum(spaces=1)/fp2.sum()
            ps2 += sp.sum(spaces=0)/fp1.sum()
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        assert_allclose(ift.dobj.to_global_data(ps1.val/samples),
                        ift.dobj.to_global_data(fp1.val), rtol=0.2)
        assert_allclose(ift.dobj.to_global_data(ps2.val/samples),
                        ift.dobj.to_global_data(fp2.val), rtol=0.2)
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    @expand(product([ift.RGSpace((8,), harmonic=True),
                     ift.RGSpace((8, 8), harmonic=True, distances=0.123)],
                    [ift.RGSpace((8,), harmonic=True),
                     ift.LMSpace(12)]))
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    def test_DiagonalOperator_power_analyze(self, space1, space2):
        np.random.seed(11)

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        fulldomain = ift.DomainTuple.make((space1, space2))
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        p1 = ift.PowerSpace(space1)
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        p1val = _spec1(p1.k_lengths)
        fp1 = ift.Field(p1, val=ift.dobj.from_global_data(p1val))
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        p2 = ift.PowerSpace(space2)
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        p2val = _spec2(p2.k_lengths)
        fp2 = ift.Field(p2, val=ift.dobj.from_global_data(p2val))
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        S_1 = ift.create_power_field(space1, lambda x: np.sqrt(_spec1(x)))
        S_1 = ift.DiagonalOperator(S_1, domain=fulldomain, spaces=0)
        S_2 = ift.create_power_field(space2, lambda x: np.sqrt(_spec2(x)))
        S_2 = ift.DiagonalOperator(S_2, domain=fulldomain, spaces=1)
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        samples = 500
        ps1 = 0.
        ps2 = 0.

        for ii in range(samples):
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            rand_k = ift.Field.from_random('normal', domain=fulldomain)
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            sk = S_1.times(S_2.times(rand_k))
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            sp = ift.power_analyze(sk, spaces=(0, 1),
                                   keep_phase_information=False)
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            ps1 += sp.sum(spaces=1)/fp2.sum()
            ps2 += sp.sum(spaces=0)/fp1.sum()
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        assert_allclose(ift.dobj.to_global_data(ps1.val/samples),
                        ift.dobj.to_global_data(fp1.val), rtol=0.2)
        assert_allclose(ift.dobj.to_global_data(ps2.val/samples),
                        ift.dobj.to_global_data(fp2.val), rtol=0.2)
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    def test_vdot(self):
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        s = ift.RGSpace((10,))
        f1 = ift.Field.from_random("normal", domain=s, dtype=np.complex128)
        f2 = ift.Field.from_random("normal", domain=s, dtype=np.complex128)
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        assert_allclose(f1.vdot(f2), f1.vdot(f2, spaces=0))
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        assert_allclose(f1.vdot(f2), np.conj(f2.vdot(f1)))
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    def test_vdot2(self):
        x1 = ift.RGSpace((200,))
        x2 = ift.RGSpace((150,))
        m = ift.Field((x1, x2), val=.5)
        res = m.vdot(m, spaces=1)
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        assert_allclose(ift.dobj.to_global_data(res.val), 37.5)