This file is indexed.

/usr/lib/python3/dist-packages/photutils/isophote/tests/test_isophote.py is in python3-photutils 0.4-1.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  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
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
# 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
import pytest

from astropy.io import fits
from astropy.tests.helper import remote_data

from .make_test_data import make_test_image
from ..fitter import EllipseFitter
from ..isophote import Isophote, IsophoteList
from ..sample import EllipseSample
from ...datasets import get_path

try:
    import scipy    # noqa
    HAS_SCIPY = True
except ImportError:
    HAS_SCIPY = False


@remote_data
@pytest.mark.skipif('not HAS_SCIPY')
class TestIsophote(object):

    def setup_class(self):
        path = get_path('isophote/M51.fits', location='photutils-datasets',
                        cache=True)
        hdu = fits.open(path)
        self.data = hdu[0].data
        hdu.close()

    def test_fit(self):
        # low noise image, fitted perfectly by sample
        data = make_test_image(noise=1.e-10, random_state=123)
        sample = EllipseSample(data, 40)
        fitter = EllipseFitter(sample)
        iso = fitter.fit(maxit=400)

        assert iso.valid
        assert iso.stop_code == 0 or iso.stop_code == 2

        # fitted values
        assert iso.intens <= 201.
        assert iso.intens >= 199.
        assert iso.int_err <= 0.0010
        assert iso.int_err >= 0.0009
        assert iso.pix_stddev <= 0.03
        assert iso.pix_stddev >= 0.02
        assert abs(iso.grad) <= 4.25
        assert abs(iso.grad) >= 4.20

        # integrals
        assert iso.tflux_e <= 1.85E6
        assert iso.tflux_e >= 1.82E6
        assert iso.tflux_c <= 2.025E6
        assert iso.tflux_c >= 2.022E6

        # deviations from perfect ellipticity
        assert abs(iso.a3) <= 0.01
        assert abs(iso.b3) <= 0.01
        assert abs(iso.a4) <= 0.01
        assert abs(iso.b4) <= 0.01

    def test_m51(self):
        sample = EllipseSample(self.data, 21.44)
        fitter = EllipseFitter(sample)
        iso = fitter.fit()

        assert iso.valid
        assert iso.stop_code == 0 or iso.stop_code == 2

        # geometry
        g = iso.sample.geometry
        assert g.x0 >= (257 - 1.5)   # position within 1.5 pixel
        assert g.x0 <= (257 + 1.5)
        assert g.y0 >= (259 - 1.5)
        assert g.y0 <= (259 + 2.0)
        assert g.eps >= (0.19 - 0.05)  # eps within 0.05
        assert g.eps <= (0.19 + 0.05)
        assert g.pa >= (0.62 - 0.05)  # pa within 5 deg
        assert g.pa <= (0.62 + 0.05)

        # fitted values
        assert iso.intens == pytest.approx(682.9, abs=0.1)
        assert iso.rms == pytest.approx(83.27, abs=0.01)
        assert iso.int_err == pytest.approx(7.63, abs=0.01)
        assert iso.pix_stddev == pytest.approx(117.8, abs=0.1)
        assert iso.grad == pytest.approx(-36.08, abs=0.1)

        # integrals
        assert iso.tflux_e <= 1.20e6
        assert iso.tflux_e >= 1.19e6
        assert iso.tflux_c <= 1.38e6
        assert iso.tflux_c >= 1.36e6

        # deviations from perfect ellipticity
        assert abs(iso.a3) <= 0.05
        assert abs(iso.b3) <= 0.05
        assert abs(iso.a4) <= 0.05
        assert abs(iso.b4) <= 0.05

    def test_m51_niter(self):
        # compares with old STSDAS task. In this task, the
        # default for the starting value of SMA is 10; it
        # fits with 20 iterations.
        sample = EllipseSample(self.data, 10)
        fitter = EllipseFitter(sample)
        iso = fitter.fit()

        assert iso.valid
        assert iso.niter == 50


class TestIsophoteList(object):

    def setup_class(self):
        data = make_test_image(random_state=123)
        self.slen = 5
        self.isolist_sma10 = self.build_list(data, sma0=10., slen=self.slen)
        self.isolist_sma100 = self.build_list(data, sma0=100., slen=self.slen)
        self.isolist_sma200 = self.build_list(data, sma0=200., slen=self.slen)

    @staticmethod
    def build_list(data, sma0, slen=5):
        iso_list = []
        for k in range(slen):
            sample = EllipseSample(data, float(k + sma0))
            sample.update()
            iso_list.append(Isophote(sample, k, True, 0))
        result = IsophoteList(iso_list)
        return result

    def test_basic_list(self):
        # make sure it can be indexed as a list.
        result = self.isolist_sma10[:]
        assert isinstance(result[0], Isophote)

        # make sure the important arrays contain floats.
        # especially the sma array, which is derived
        # from a property in the Isophote class.
        assert isinstance(result.sma, np.ndarray)
        assert isinstance(result.sma[0], float)
        assert isinstance(result.intens, np.ndarray)
        assert isinstance(result.intens[0], float)
        assert isinstance(result.rms, np.ndarray)
        assert isinstance(result.int_err, np.ndarray)
        assert isinstance(result.pix_stddev, np.ndarray)
        assert isinstance(result.grad, np.ndarray)
        assert isinstance(result.grad_error, np.ndarray)
        assert isinstance(result.grad_r_error, np.ndarray)
        assert isinstance(result.sarea, np.ndarray)
        assert isinstance(result.niter, np.ndarray)
        assert isinstance(result.ndata, np.ndarray)
        assert isinstance(result.nflag, np.ndarray)
        assert isinstance(result.valid, np.ndarray)
        assert isinstance(result.stop_code, np.ndarray)
        assert isinstance(result.tflux_c, np.ndarray)
        assert isinstance(result.tflux_e, np.ndarray)
        assert isinstance(result.npix_c, np.ndarray)
        assert isinstance(result.npix_e, np.ndarray)
        assert isinstance(result.a3, np.ndarray)
        assert isinstance(result.a4, np.ndarray)
        assert isinstance(result.b3, np.ndarray)
        assert isinstance(result.b4, np.ndarray)

        samples = result.sample
        assert isinstance(samples, list)
        assert isinstance(samples[0], EllipseSample)

        iso = result.get_closest(13.6)
        assert isinstance(iso, Isophote)
        assert iso.sma == pytest.approx(14., abs=0.000001)

    def test_extend(self):
        # the extend method shouldn't return anything,
        # and should modify the first list in place.
        inner_list = self.isolist_sma10[:]
        outer_list = self.isolist_sma100[:]
        assert len(inner_list) == self.slen
        assert len(outer_list) == self.slen
        dummy = inner_list.extend(outer_list)
        assert not dummy
        assert len(inner_list) == 2 * self.slen

        # the __iadd__ operator should behave like the
        # extend method.
        inner_list = self.isolist_sma10[:]
        outer_list = self.isolist_sma100[:]
        inner_list += outer_list
        assert len(inner_list) == 2 * self.slen

        # the __add__ operator should create a new IsophoteList
        # instance with the result, and should not modify
        # the operands.
        inner_list = self.isolist_sma10[:]
        outer_list = self.isolist_sma100[:]
        result = inner_list + outer_list
        assert isinstance(result, IsophoteList)
        assert len(inner_list) == self.slen
        assert len(outer_list) == self.slen
        assert len(result) == 2 * self.slen

    def test_slicing(self):
        iso_list = self.isolist_sma10[:]
        assert len(iso_list) == self.slen
        assert len(iso_list[1:-1]) == self.slen - 2
        assert len(iso_list[2:-2]) == self.slen - 4

    def test_combined(self):
        # combine extend with slicing.
        inner_list = self.isolist_sma10[:]
        outer_list = self.isolist_sma100[:]
        sublist = inner_list[2:-2]
        dummy = sublist.extend(outer_list)
        assert not dummy
        assert len(sublist) == 2*self.slen - 4

        # try one more slice.
        even_outer_list = self.isolist_sma200
        sublist.extend(even_outer_list[1:-1])
        assert len(sublist) == 2*self.slen - 4 + 3

        # combine __add__ with slicing.
        sublist = inner_list[2:-2]
        result = sublist + outer_list
        assert isinstance(result, IsophoteList)
        assert len(sublist) == self.slen - 4
        assert len(result) == 2*self.slen - 4

        result = inner_list[2:-2] + outer_list
        assert isinstance(result, IsophoteList)
        assert len(result) == 2*self.slen - 4

    def test_sort(self):
        inner_list = self.isolist_sma10[:]
        outer_list = self.isolist_sma100[:]
        result = outer_list[2:-2] + inner_list

        assert result[-1].sma < result[0].sma
        result.sort()
        assert result[-1].sma > result[0].sma