1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
|
From: Ole Streicher <olebole@debian.org>
Date: Wed, 4 Jan 2023 10:33:50 +0100
Subject: Update test_kernel_smooth to latest github version
Closes: #1026720, #1027396
---
spectral_cube/tests/test_regrid.py | 47 ++++++++++++++++++++++++++------------
1 file changed, 32 insertions(+), 15 deletions(-)
diff --git a/spectral_cube/tests/test_regrid.py b/spectral_cube/tests/test_regrid.py
index d832cd8..46d369f 100644
--- a/spectral_cube/tests/test_regrid.py
+++ b/spectral_cube/tests/test_regrid.py
@@ -126,18 +126,36 @@ def test_spectral_smooth(data_522_delta, use_dask):
cube, data = cube_and_raw(data_522_delta, use_dask=use_dask)
- result = cube.spectral_smooth(kernel=convolution.Gaussian1DKernel(1.0), use_memmap=False)
+ kernel = convolution.Gaussian1DKernel(1.0)
+
+ result = cube.spectral_smooth(kernel=kernel, use_memmap=False)
+
+ # check that all values come out right from the cube creation
+ np.testing.assert_almost_equal(cube[2,:,:].value, 1.0)
+ np.testing.assert_almost_equal(cube.unitless_filled_data[:2,:,:], 0.0)
+ np.testing.assert_almost_equal(cube.unitless_filled_data[3:,:,:], 0.0)
+
+ # make sure the kernel comes out right; the convolution test will fail if this is wrong
+ assert kernel.array.size == 9
+ # this was the old astropy normalization
+ # We don't actually need the kernel to match these values, but I'm leaving this here
+ # as a note for future us:
+ # https://github.com/astropy/astropy/pull/13299
+ # the error came about because we were using two different kernel sizes, which resulted in
+ # two different normalizations after the correction in 13299
+ # Before 13299, normalization was not guaranteed.
+ #np.testing.assert_almost_equal(kernel.array[2:-2],
+ # np.array([0.05399097, 0.24197072, 0.39894228, 0.24197072, 0.05399097]))
np.testing.assert_almost_equal(result[:,0,0].value,
- convolution.Gaussian1DKernel(1.0,
- x_size=5).array,
+ kernel.array[2:-2],
4)
- result = cube.spectral_smooth(kernel=convolution.Gaussian1DKernel(1.0), use_memmap=True)
+ # second test with memmap=True
+ result = cube.spectral_smooth(kernel=kernel, use_memmap=True)
np.testing.assert_almost_equal(result[:,0,0].value,
- convolution.Gaussian1DKernel(1.0,
- x_size=5).array,
+ kernel.array[2:-2],
4)
def test_catch_kernel_with_units(data_522_delta, use_dask):
@@ -158,19 +176,19 @@ def test_spectral_smooth_4cores(data_522_delta):
cube, data = cube_and_raw(data_522_delta, use_dask=False)
- result = cube.spectral_smooth(kernel=convolution.Gaussian1DKernel(1.0), num_cores=4, use_memmap=True)
+ kernel = convolution.Gaussian1DKernel(1.0)
+ result = cube.spectral_smooth(kernel=kernel, num_cores=4, use_memmap=True)
+ assert kernel.array.size == 9
np.testing.assert_almost_equal(result[:,0,0].value,
- convolution.Gaussian1DKernel(1.0,
- x_size=5).array,
+ kernel.array[2:-2],
4)
# this is one way to test non-parallel mode
- result = cube.spectral_smooth(kernel=convolution.Gaussian1DKernel(1.0), num_cores=4, use_memmap=False)
+ result = cube.spectral_smooth(kernel=kernel, num_cores=4, use_memmap=False)
np.testing.assert_almost_equal(result[:,0,0].value,
- convolution.Gaussian1DKernel(1.0,
- x_size=5).array,
+ kernel.array[2:-2],
4)
# num_cores = 4 is a contradiction with parallel=False, so we want to make
@@ -180,12 +198,11 @@ def test_spectral_smooth_4cores(data_522_delta):
"multiple cores were: these are incompatible "
"options. Either specify num_cores=1 or "
"parallel=True")):
- result = cube.spectral_smooth(kernel=convolution.Gaussian1DKernel(1.0),
+ result = cube.spectral_smooth(kernel=kernel,
num_cores=4, parallel=False)
np.testing.assert_almost_equal(result[:,0,0].value,
- convolution.Gaussian1DKernel(1.0,
- x_size=5).array,
+ kernel.array[2:-2],
4)
|
