test_correlated_fields.py 3.77 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
# 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/>.
#
# Copyright(C) 2013-2019 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.

import pytest
from numpy.random import seed
Philipp Arras's avatar
Philipp Arras committed
20
from numpy.testing import assert_allclose
21

Martin Reinecke's avatar
5->6    
Martin Reinecke committed
22
import nifty6 as ift
23
24


Philipp Arras's avatar
Philipp Arras committed
25
26
27
28
@pytest.mark.parametrize('sspace', [ift.RGSpace(4),
                                    ift.RGSpace((4, 4), (0.123, 0.4)),
                                    ift.HPSpace(8),
                                    ift.GLSpace(4)])
29
@pytest.mark.parametrize('rseed', [13, 2])
Philipp Arras's avatar
Philipp Arras committed
30
@pytest.mark.parametrize('Astds', [[1., 3.], [0.2, 1.4]])
Lukas Platz's avatar
Lukas Platz committed
31
@pytest.mark.parametrize('offset_std_mean', [1., 10.])
Philipp Arras's avatar
Philipp Arras committed
32
@pytest.mark.parametrize('N', [0, 2])
33
34
@pytest.mark.parametrize('zm_mean', [0, 1.])
def testAmplitudesConsistency(rseed, sspace, Astds, offset_std_mean, N, zm_mean):
Philipp Arras's avatar
Philipp Arras committed
35
    def stats(op, samples):
Philipp Frank's avatar
fixes    
Philipp Frank committed
36
37
38
        sc = ift.StatCalculator()
        for s in samples:
            sc.add(op(s.extract(op.domain)))
Martin Reinecke's avatar
stage 3    
Martin Reinecke committed
39
        return sc.mean.val, sc.var.sqrt().val
Philipp Arras's avatar
Philipp Arras committed
40

41
42
43
44
    seed(rseed)
    nsam = 100

    fsspace = ift.RGSpace((12,), (0.4,))
Philipp Arras's avatar
Philipp Arras committed
45
46
47
48
    if N == 2:
        dofdex1 = [0, 0]
        dofdex2 = [1, 0]
        dofdex3 = [1, 1]
Philipp Haim's avatar
Philipp Haim committed
49
50
    else:
        dofdex1, dofdex2, dofdex3 = None, None, None
51

52
    fa = ift.CorrelatedFieldMaker.make(zm_mean, offset_std_mean, 1E-8, '', N, dofdex1)
Philipp Arras's avatar
Philipp Arras committed
53
54
    fa.add_fluctuations(sspace, Astds[0], 1E-8, 1.1, 2., 2.1, .5, -2, 1., 'spatial', dofdex=dofdex2)
    fa.add_fluctuations(fsspace, Astds[1], 1E-8, 3.1, 1., .5, .1, -4, 1., 'freq', dofdex=dofdex3)
55
    op = fa.finalize()
56

Philipp Arras's avatar
Philipp Arras committed
57
58
    samples = [ift.from_random('normal', op.domain) for _ in range(nsam)]
    tot_flm, _ = stats(fa.total_fluctuation, samples)
Philipp Haim's avatar
Philipp Haim committed
59
    offset_amp_std, _ = stats(fa.amplitude_total_offset, samples)
Philipp Arras's avatar
Philipp Arras committed
60
61
    intergated_fluct_std0, _ = stats(fa.average_fluctuation(0), samples)
    intergated_fluct_std1, _ = stats(fa.average_fluctuation(1), samples)
Martin Reinecke's avatar
stage 3    
Martin Reinecke committed
62

Philipp Arras's avatar
Philipp Arras committed
63
64
    slice_fluct_std0, _ = stats(fa.slice_fluctuation(0), samples)
    slice_fluct_std1, _ = stats(fa.slice_fluctuation(1), samples)
65
66
67

    sams = [op(s) for s in samples]
    fluct_total = fa.total_fluctuation_realized(sams)
Philipp Arras's avatar
Philipp Arras committed
68
69
    fluct_space = fa.average_fluctuation_realized(sams, 0)
    fluct_freq = fa.average_fluctuation_realized(sams, 1)
70
    zm_std_mean = fa.offset_amplitude_realized(sams)
Philipp Arras's avatar
Philipp Arras committed
71
72
    sl_fluct_space = fa.slice_fluctuation_realized(sams, 0)
    sl_fluct_freq = fa.slice_fluctuation_realized(sams, 1)
73

Philipp Haim's avatar
Philipp Haim committed
74
    assert_allclose(offset_amp_std, zm_std_mean, rtol=0.5)
75
76
77
78
79
80
    assert_allclose(intergated_fluct_std0, fluct_space, rtol=0.5)
    assert_allclose(intergated_fluct_std1, fluct_freq, rtol=0.5)
    assert_allclose(tot_flm, fluct_total, rtol=0.5)
    assert_allclose(slice_fluct_std0, sl_fluct_space, rtol=0.5)
    assert_allclose(slice_fluct_std1, sl_fluct_freq, rtol=0.5)

Lukas Platz's avatar
Lukas Platz committed
81
    fa = ift.CorrelatedFieldMaker.make(0., offset_std_mean, .1, '', N, dofdex1)
Philipp Arras's avatar
Philipp Arras committed
82
    fa.add_fluctuations(fsspace, Astds[1], 1., 3.1, 1., .5, .1, -4, 1., 'freq', dofdex=dofdex3)
83
84
    m = 3.
    x = fa.moment_slice_to_average(m)
Philipp Arras's avatar
Philipp Arras committed
85
    fa.add_fluctuations(sspace, x, 1.5, 1.1, 2., 2.1, .5, -2, 1., 'spatial', 0, dofdex=dofdex2)
86
    op = fa.finalize()
Philipp Arras's avatar
Philipp Arras committed
87
    em, estd = stats(fa.slice_fluctuation(0), samples)
88
89

    assert_allclose(m, em, rtol=0.5)
Philipp Haim's avatar
Philipp Haim committed
90
91
    assert op.target[-2] == sspace
    assert op.target[-1] == fsspace