/usr/lib/python3/dist-packages/photutils/segmentation/tests/test_detect.py is in python3-photutils 0.4-1.
This file is owned by root:root, with mode 0o644.
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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 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 | # Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
from numpy.testing import assert_array_equal, assert_allclose
import pytest
from astropy.tests.helper import catch_warnings
from astropy.utils.exceptions import AstropyUserWarning
from astropy.convolution import Gaussian2DKernel
from astropy.stats import gaussian_fwhm_to_sigma
from ..detect import detect_sources, make_source_mask
from ...datasets import make_4gaussians_image
try:
import scipy # noqa
HAS_SCIPY = True
except ImportError:
HAS_SCIPY = False
try:
import skimage # noqa
HAS_SKIMAGE = True
except ImportError:
HAS_SKIMAGE = False
@pytest.mark.skipif('not HAS_SCIPY')
class TestDetectSources(object):
def setup_class(self):
self.data = np.array([[0, 1, 0], [0, 2, 0],
[0, 0, 0]]).astype(np.float)
self.ref1 = np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0]])
self.ref2 = np.array([[0, 1, 0], [0, 1, 0], [0, 0, 0]])
fwhm2sigma = 1.0 / (2.0 * np.sqrt(2.0 * np.log(2.0)))
filter_kernel = Gaussian2DKernel(2. * fwhm2sigma, x_size=3, y_size=3)
filter_kernel.normalize()
self.filter_kernel = filter_kernel
def test_detection(self):
"""Test basic detection."""
segm = detect_sources(self.data, threshold=0.9, npixels=2)
assert_array_equal(segm.data, self.ref2)
def test_small_sources(self):
"""Test detection where sources are smaller than npixels size."""
segm = detect_sources(self.data, threshold=0.9, npixels=5)
assert_array_equal(segm.data, self.ref1)
def test_zerothresh(self):
"""Test detection with zero threshold."""
segm = detect_sources(self.data, threshold=0., npixels=2)
assert_array_equal(segm.data, self.ref2)
def test_zerodet(self):
"""Test detection with large snr_threshold giving no detections."""
segm = detect_sources(self.data, threshold=7, npixels=2)
assert_array_equal(segm.data, self.ref1)
def test_8connectivity(self):
"""Test detection with connectivity=8."""
data = np.eye(3)
segm = detect_sources(data, threshold=0.9, npixels=1, connectivity=8)
assert_array_equal(segm.data, data)
def test_4connectivity(self):
"""Test detection with connectivity=4."""
data = np.eye(3)
ref = np.diag([1, 2, 3])
segm = detect_sources(data, threshold=0.9, npixels=1, connectivity=4)
assert_array_equal(segm.data, ref)
def test_basic_filter_kernel(self):
"""Test detection with filter_kernel."""
kernel = np.ones((3, 3)) / 9.
threshold = 0.3
expected = np.ones((3, 3))
expected[2] = 0
segm = detect_sources(self.data, threshold, npixels=1,
filter_kernel=kernel)
assert_array_equal(segm.data, expected)
def test_npixels_nonint(self):
"""Test if error raises if npixel is non-integer."""
with pytest.raises(ValueError):
detect_sources(self.data, threshold=1, npixels=0.1)
def test_npixels_negative(self):
"""Test if error raises if npixel is negative."""
with pytest.raises(ValueError):
detect_sources(self.data, threshold=1, npixels=-1)
def test_connectivity_invalid(self):
"""Test if error raises if connectivity is invalid."""
with pytest.raises(ValueError):
detect_sources(self.data, threshold=1, npixels=1, connectivity=10)
def test_filter_kernel_array(self):
segm = detect_sources(self.data, 0.1, npixels=1,
filter_kernel=self.filter_kernel.array)
assert_array_equal(segm.data, np.ones((3, 3)))
def test_filter_kernel(self):
segm = detect_sources(self.data, 0.1, npixels=1,
filter_kernel=self.filter_kernel)
assert_array_equal(segm.data, np.ones((3, 3)))
def test_unnormalized_filter_kernel(self):
with catch_warnings(AstropyUserWarning) as warning_lines:
detect_sources(self.data, 0.1, npixels=1,
filter_kernel=self.filter_kernel*10.)
assert warning_lines[0].category == AstropyUserWarning
assert ('The kernel is not normalized.'
in str(warning_lines[0].message))
@pytest.mark.skipif('not HAS_SCIPY')
class TestMakeSourceMask(object):
def setup_class(self):
self.data = make_4gaussians_image()
def test_dilate_size(self):
mask1 = make_source_mask(self.data, 5, 10)
mask2 = make_source_mask(self.data, 5, 10, dilate_size=20)
assert np.count_nonzero(mask2) > np.count_nonzero(mask1)
def test_kernel(self):
mask1 = make_source_mask(self.data, 5, 10, filter_fwhm=2,
filter_size=3)
sigma = 2 * gaussian_fwhm_to_sigma
kernel = Gaussian2DKernel(sigma, x_size=3, y_size=3)
mask2 = make_source_mask(self.data, 5, 10, filter_kernel=kernel)
assert_allclose(mask1, mask2)
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