test_field.py 4.14 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
11
12
# 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/>.
Theo Steininger's avatar
Theo Steininger committed
13
14
15
16
17
#
# 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.
18
19
20
21
22

import unittest

import numpy as np
from numpy.testing import assert_,\
23
24
                          assert_almost_equal,\
                          assert_allclose
Theo Steininger's avatar
Theo Steininger committed
25
from nose.plugins.skip import SkipTest
26

27
from itertools import product
28

Martin Reinecke's avatar
Martin Reinecke committed
29
from nifty2go import Field,\
30
                  RGSpace,\
31
                  LMSpace,\
Martin Reinecke's avatar
cleanup  
Martin Reinecke committed
32
                  PowerSpace
33

Jait Dixit's avatar
Jait Dixit committed
34
from test.common import expand
35
36


Martin Reinecke's avatar
Martin Reinecke committed
37
SPACES = [RGSpace((4,)), RGSpace((5))]
Theo Steininger's avatar
Theo Steininger committed
38
SPACE_COMBINATIONS = [(), SPACES[0], SPACES[1], SPACES]
39
40
41


class Test_Interface(unittest.TestCase):
42
    @expand(product(SPACE_COMBINATIONS,
Martin Reinecke's avatar
stage1  
Martin Reinecke committed
43
                    [['domain', tuple],
44
                     ['domain_axes', tuple],
Martin Reinecke's avatar
stage1  
Martin Reinecke committed
45
                     ['val', np.ndarray],
46
47
48
49
50
51
52
                     ['shape', tuple],
                     ['dim', np.int],
                     ['dof', np.int],
                     ['total_volume', np.float]]))
    def test_return_types(self, domain, attribute_desired_type):
        attribute = attribute_desired_type[0]
        desired_type = attribute_desired_type[1]
53
        f = Field(domain=domain)
54
55
        assert_(isinstance(getattr(f, attribute), desired_type))

Martin Reinecke's avatar
Martin Reinecke committed
56

57
58
59
class Test_Functionality(unittest.TestCase):
    @expand(product([True, False], [True, False],
                    [(1,), (4,), (5,)], [(1,), (6,), (7,)]))
60
    def test_hermitian_decomposition(self, preserve, complexdata, s1, s2):
61
        np.random.seed(123)
62
63
64
        r1 = RGSpace(s1, harmonic=True)
        r2 = RGSpace(s2, harmonic=True)
        ra = RGSpace(s1+s2, harmonic=True)
Martin Reinecke's avatar
Martin Reinecke committed
65

Martin Reinecke's avatar
Martin Reinecke committed
66
67
        if preserve:
            complexdata=True
68
69
70
71
72
        v = np.random.random(s1+s2)
        if complexdata:
            v = v + 1j*np.random.random(s1+s2)
        f1 = Field(ra, val=v, copy=True)
        f2 = Field((r1, r2), val=v, copy=True)
Martin Reinecke's avatar
cleanup  
Martin Reinecke committed
73
74
        h1, a1 = Field._hermitian_decomposition(f1.val, preserve)
        h2, a2 = Field._hermitian_decomposition(f2.val, preserve)
75

Martin Reinecke's avatar
stage1  
Martin Reinecke committed
76
77
        assert_almost_equal(h1, h2)
        assert_almost_equal(a1, a2)
78

79
80
81
    @expand(product([RGSpace((8,), harmonic=True),
                     RGSpace((8, 8), harmonic=True, distances=0.123)],
                    [RGSpace((8,), harmonic=True),
Martin Reinecke's avatar
more  
Martin Reinecke committed
82
83
                     LMSpace(12)]))
    def test_power_synthesize_analyze(self, space1, space2):
Martin Reinecke's avatar
stage1  
Martin Reinecke committed
84
        np.random.seed(11)
85

86
87
        p1 = PowerSpace(space1)
        spec1 = lambda k: 42/(1+k)**2
Martin Reinecke's avatar
Martin Reinecke committed
88
        fp1 = Field(p1, val=spec1(p1.kindex))
89
90
91

        p2 = PowerSpace(space2)
        spec2 = lambda k: 42/(1+k)**3
Martin Reinecke's avatar
Martin Reinecke committed
92
        fp2 = Field(p2, val=spec2(p2.kindex))
93

Martin Reinecke's avatar
stage1  
Martin Reinecke committed
94
        outer = np.outer(fp1.val, fp2.val)
95
96
        fp = Field((p1, p2), val=outer)

97
        samples = 2000
98
99
        ps1 = 0.
        ps2 = 0.
Martin Reinecke's avatar
Martin Reinecke committed
100
        for ii in range(samples):
101
102
103
104
105
106
            sk = fp.power_synthesize(spaces=(0, 1), real_signal=True)

            sp = sk.power_analyze(spaces=(0, 1), keep_phase_information=False)
            ps1 += sp.sum(spaces=1)/fp2.sum()
            ps2 += sp.sum(spaces=0)/fp1.sum()

Martin Reinecke's avatar
stage1  
Martin Reinecke committed
107
108
        assert_allclose(ps1.val/samples,
                        fp1.val,
109
                        rtol=0.2)
Martin Reinecke's avatar
stage1  
Martin Reinecke committed
110
111
        assert_allclose(ps2.val/samples,
                        fp2.val,
112
                        rtol=0.2)
Martin Reinecke's avatar
Martin Reinecke committed
113
114
115
116
117
118
119
120
121

    def test_vdot(self):
        s=RGSpace((10,))
        f1=Field.from_random("normal",domain=s,dtype=np.complex128)
        f2=Field.from_random("normal",domain=s,dtype=np.complex128)
        assert_allclose(f1.vdot(f2),f1.vdot(f2,spaces=0))
        assert_allclose(f1.vdot(f2),np.conj(f2.vdot(f1)))