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* [rpms/python-photutils] epel10: new version
@ 2026-06-26 3:41 Christian Dersch
0 siblings, 0 replies; 2+ messages in thread
From: Christian Dersch @ 2026-06-26 3:41 UTC (permalink / raw)
To: git-commits
A new commit has been pushed.
Repo : rpms/python-photutils
Branch : epel10
Commit : 6f5412fc218da532465fea1961443e5ee397e7b4
Author : Christian Dersch <lupinix@fedoraproject.org>
Date : 2018-10-03T19:09:28+02:00
Stats : +15/-14 in 3 file(s)
URL : https://src.fedoraproject.org/rpms/python-photutils/c/6f5412fc218da532465fea1961443e5ee397e7b4?branch=epel10
Log:
new version
drop old patches
re-enable tests
---
diff --git a/.gitignore b/.gitignore
index c05ce07..de32315 100644
--- a/.gitignore
+++ b/.gitignore
@@ -4,3 +4,4 @@
/photutils-0.3.tar.gz
/photutils-0.3.2.tar.gz
/photutils-0.4.tar.gz
+/photutils-0.5.tar.gz
diff --git a/python-photutils.spec b/python-photutils.spec
index 333d56b..deb1403 100644
--- a/python-photutils.spec
+++ b/python-photutils.spec
@@ -1,8 +1,8 @@
%global srcname photutils
Name: python-%{srcname}
-Version: 0.4
-Release: 8%{?dist}
+Version: 0.5
+Release: 1%{?dist}
Summary: Astropy affiliated package for image photometry tasks
License: BSD
@@ -10,12 +10,6 @@ URL: http://photutils.readthedocs.org/en/latest/index.html
# Use the un-Cythonized github tar, as we need the newer Fedora Cython to build with Python 3.7
Source0: https://github.com/astropy/photutils/archive/v%{version}.tar.gz#/%{srcname}-%{version}.tar.gz
-# Use system copy of astropy-helpers
-Patch0: python-photutils-Use-astropy_helpers-provided-by-the-system.patch
-
-# Fixes for numpy 1.14, rebased version of https://github.com/astropy/photutils/pull/639
-Patch1: python-photutils-fixes-for-numpy-1.14.patch
-
BuildRequires: gcc
BuildRequires: python3-devel
@@ -42,6 +36,7 @@ BuildRequires: python3-scikit-image
BuildRequires: python3-matplotlib
# For tests
BuildRequires: python3-pytest
+BuildRequires: python3-pytest-astropy
%{?python_provide:%python_provide python3-%{srcname}}
@@ -78,11 +73,11 @@ export XDG_CONFIG_HOME=`pwd`
# Avoid writing bad pyc files
export PYTHONDONTWRITEBYTECODE=1
-# Disable tests and wait for new release fixing them
-# https://github.com/astropy/photutils/issues/677
-#pushd %%{buildroot}/%%{python3_sitearch}
-#py.test-%%{python3_version} %%{srcname}
-#popd
+pushd %{buildroot}/%{python3_sitearch}
+# Test test_outline_segments and TestDeblendSources fail as we don't have dask in Fedora
+py.test-%{python3_version} -k "not (test_outline_segments or TestDeblendSources)" %{srcname}
+rm -rf .pytest_cache
+popd
%files -n python3-%{srcname}
@@ -92,6 +87,11 @@ export PYTHONDONTWRITEBYTECODE=1
%{python3_sitearch}/%{srcname}
%changelog
+* Wed Oct 03 2018 Christian Dersch <lupinix@fedoraproject.org> - 0.5-1
+- new version
+- drop old patches
+- re-enable tests
+
* Mon Oct 01 2018 Miro Hrončok <mhroncok@redhat.com> - 0.4-8
- Remove python2 subpackage (#1632572)
diff --git a/sources b/sources
index 5497ec1..a5ea80f 100644
--- a/sources
+++ b/sources
@@ -1 +1 @@
-SHA512 (photutils-0.4.tar.gz) = 90f6e0737f20e6a0221bd397f87684c72c42c8a8d37bd111153f39708f60f993b6640c57f986ddcb664032f0982b162ce29f4f15e691a2432c82c4a1d843d309
+SHA512 (photutils-0.5.tar.gz) = 2e9f233c623725abd7a8e3d991c2c065f7be09fda544c44c69149c6eb04df4ac1eef4cf0c837b1c159445f172da2fd29eafa127abe7bb229d6b0851a4dcf5b64
^ permalink raw reply related [flat|nested] 2+ messages in thread
* [rpms/python-photutils] epel10: new version
@ 2026-06-26 3:41 Christian Dersch
0 siblings, 0 replies; 2+ messages in thread
From: Christian Dersch @ 2026-06-26 3:41 UTC (permalink / raw)
To: git-commits
A new commit has been pushed.
Repo : rpms/python-photutils
Branch : epel10
Commit : 95133437e29a27ed0a1145a1178bfa62b9ba664e
Author : Christian Dersch <lupinix@mailbox.org>
Date : 2019-04-28T16:35:16+02:00
Stats : +8/-1727 in 5 file(s)
URL : https://src.fedoraproject.org/rpms/python-photutils/c/95133437e29a27ed0a1145a1178bfa62b9ba664e?branch=epel10
Log:
new version
---
diff --git a/.gitignore b/.gitignore
index de32315..f754205 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,3 +5,4 @@
/photutils-0.3.2.tar.gz
/photutils-0.4.tar.gz
/photutils-0.5.tar.gz
+/photutils-0.6.tar.gz
diff --git a/python-photutils-Use-astropy_helpers-provided-by-the-system.patch b/python-photutils-Use-astropy_helpers-provided-by-the-system.patch
deleted file mode 100644
index 005adb6..0000000
--- a/python-photutils-Use-astropy_helpers-provided-by-the-system.patch
+++ /dev/null
@@ -1,21 +0,0 @@
-From: Ole Streicher <olebole@debian.org>
-Date: Thu, 7 Jul 2016 10:26:43 +0200
-Subject: Use astropy_helpers provided by the system
-
----
- setup.cfg | 2 +-
- 1 file changed, 1 insertion(+), 1 deletion(-)
-
-diff --git a/setup.cfg b/setup.cfg
-index e7881d0..2d23bfd 100644
---- a/setup.cfg
-+++ b/setup.cfg
-@@ -14,7 +14,7 @@
- addopts = --pyargs -p no:warnings
-
- [ah_bootstrap]
--auto_use = True
-+auto_use = False
-
- [metadata]
- package_name = photutils
diff --git a/python-photutils-fixes-for-numpy-1.14.patch b/python-photutils-fixes-for-numpy-1.14.patch
deleted file mode 100644
index afe2abd..0000000
--- a/python-photutils-fixes-for-numpy-1.14.patch
+++ /dev/null
@@ -1,1701 +0,0 @@
-diff -Naur photutils-0.4/docs/aperture.rst photutils-0.4.fixed/docs/aperture.rst
---- photutils-0.4/docs/aperture.rst 2017-10-30 15:38:18.000000000 +0100
-+++ photutils-0.4.fixed/docs/aperture.rst 2018-02-14 03:56:07.064522634 +0100
-@@ -122,12 +122,13 @@
- >>> from photutils import aperture_photometry
- >>> data = np.ones((100, 100))
- >>> phot_table = aperture_photometry(data, apertures)
-- >>> print(phot_table) # doctest: +SKIP
-- id xcenter ycenter aperture_sum
-+ >>> phot_table['aperture_sum'].info.format = '%.8g' # for consistent table output
-+ >>> print(phot_table)
-+ id xcenter ycenter aperture_sum
- pix pix
-- --- ------- ------- -------------
-- 1 30.0 30.0 28.2743338823
-- 2 40.0 40.0 28.2743338823
-+ --- ------- ------- ------------
-+ 1 30.0 30.0 28.274334
-+ 2 40.0 40.0 28.274334
-
- This function returns the results of the photometry in an Astropy
- `~astropy.table.QTable`. In this example, the table has four columns,
-@@ -159,7 +160,7 @@
-
- >>> phot_table = aperture_photometry(data, apertures, method='subpixel',
- ... subpixels=5)
-- >>> print(phot_table) # doctest: +SKIP
-+ >>> print(phot_table)
- id xcenter ycenter aperture_sum
- pix pix
- --- ------- ------- ------------
-@@ -192,12 +193,14 @@
- >>> radii = [3., 4., 5.]
- >>> apertures = [CircularAperture(positions, r=r) for r in radii]
- >>> phot_table = aperture_photometry(data, apertures)
-- >>> print(phot_table) # doctest: +SKIP
-+ >>> for col in phot_table.colnames:
-+ ... phot_table[col].info.format = '%.8g' # for consistent table output
-+ >>> print(phot_table)
- id xcenter ycenter aperture_sum_0 aperture_sum_1 aperture_sum_2
- pix pix
- --- ------- ------- -------------- -------------- --------------
-- 1 30.0 30.0 28.2743338823 50.2654824574 78.5398163397
-- 2 40.0 40.0 28.2743338823 50.2654824574 78.5398163397
-+ 1 30 30 28.274334 50.265482 78.539816
-+ 2 40 40 28.274334 50.265482 78.539816
-
- For multiple apertures, the output table column names are appended
- with the ``positions`` index.
-@@ -212,12 +215,14 @@
- >>> theta = np.pi / 4.
- >>> apertures = EllipticalAperture(positions, a, b, theta)
- >>> phot_table = aperture_photometry(data, apertures)
-- >>> print(phot_table) # doctest: +SKIP
-- id xcenter ycenter aperture_sum
-+ >>> for col in phot_table.colnames:
-+ ... phot_table[col].info.format = '%.8g' # for consistent table output
-+ >>> print(phot_table)
-+ id xcenter ycenter aperture_sum
- pix pix
-- --- ------- ------- -------------
-- 1 30.0 30.0 47.1238898038
-- 2 40.0 40.0 47.1238898038
-+ --- ------- ------- ------------
-+ 1 30 30 47.12389
-+ 2 40 40 47.12389
-
- Again, for multiple apertures one should input a list of aperture
- objects, each with identical positions::
-@@ -228,12 +233,14 @@
- >>> apertures = [EllipticalAperture(positions, a=ai, b=bi, theta=theta)
- ... for (ai, bi) in zip(a, b)]
- >>> phot_table = aperture_photometry(data, apertures)
-- >>> print(phot_table) # doctest: +SKIP
-+ >>> for col in phot_table.colnames:
-+ ... phot_table[col].info.format = '%.8g' # for consistent table output
-+ >>> print(phot_table)
- id xcenter ycenter aperture_sum_0 aperture_sum_1 aperture_sum_2
- pix pix
- --- ------- ------- -------------- -------------- --------------
-- 1 30.0 30.0 47.1238898038 75.3982236862 109.955742876
-- 2 40.0 40.0 47.1238898038 75.3982236862 109.955742876
-+ 1 30 30 47.12389 75.398224 109.95574
-+ 2 40 40 47.12389 75.398224 109.95574
-
-
- Background Subtraction
-@@ -267,12 +274,14 @@
-
- >>> apers = [apertures, annulus_apertures]
- >>> phot_table = aperture_photometry(data, apers)
-- >>> print(phot_table) # doctest: +SKIP
-+ >>> for col in phot_table.colnames:
-+ ... phot_table[col].info.format = '%.8g' # for consistent table output
-+ >>> print(phot_table)
- id xcenter ycenter aperture_sum_0 aperture_sum_1
- pix pix
- --- ------- ------- -------------- --------------
-- 1 30.0 30.0 28.2743338823 87.9645943005
-- 2 40.0 40.0 28.2743338823 87.9645943005
-+ 1 30 30 28.274334 87.964594
-+ 2 40 40 28.274334 87.964594
-
- Note that we cannot simply subtract the aperture sums because the
- apertures have different areas.
-@@ -289,11 +298,12 @@
- >>> bkg_sum = bkg_mean * apertures.area()
- >>> final_sum = phot_table['aperture_sum_0'] - bkg_sum
- >>> phot_table['residual_aperture_sum'] = final_sum
-- >>> print(phot_table['residual_aperture_sum']) # doctest: +FLOAT_CMP
-+ >>> phot_table['residual_aperture_sum'].info.format = '%.8g' # for consistent table output
-+ >>> print(phot_table['residual_aperture_sum'])
- residual_aperture_sum
- ---------------------
-- -7.1054273576e-15
-- -7.1054273576e-15
-+ -7.1054274e-15
-+ -7.1054274e-15
-
- The result here should be zero because all of the data values are 1.0
- (the tiny difference from 0.0 is due to numerical precision).
-@@ -316,12 +326,14 @@
-
- >>> error = 0.1 * data
- >>> phot_table = aperture_photometry(data, apertures, error=error)
-- >>> print(phot_table) # doctest: +SKIP
-- id xcenter ycenter aperture_sum aperture_sum_err
-+ >>> for col in phot_table.colnames:
-+ ... phot_table[col].info.format = '%.8g' # for consistent table output
-+ >>> print(phot_table)
-+ id xcenter ycenter aperture_sum aperture_sum_err
- pix pix
-- --- ------- ------- ------------- ----------------
-- 1 30.0 30.0 28.2743338823 0.531736155272
-- 2 40.0 40.0 28.2743338823 0.531736155272
-+ --- ------- ------- ------------ ----------------
-+ 1 30 30 28.274334 0.53173616
-+ 2 40 40 28.274334 0.53173616
-
- ``'aperture_sum_err'`` values are given by:
-
-@@ -363,18 +375,20 @@
- >>> data[2, 2] = 100. # bad pixel
- >>> mask[2, 2] = True
- >>> t1 = aperture_photometry(data, aperture, mask=mask)
-- >>> print(t1['aperture_sum']) # doctest: +FLOAT_CMP
-- aperture_sum
-- -------------
-- 11.5663706144
-+ >>> t1['aperture_sum'].info.format = '%.8g' # for consistent table output
-+ >>> print(t1['aperture_sum'])
-+ aperture_sum
-+ ------------
-+ 11.566371
-
- The result is very different if a ``mask`` image is not provided::
-
- >>> t2 = aperture_photometry(data, aperture)
-- >>> print(t2['aperture_sum']) # doctest: +FLOAT_CMP
-+ >>> t2['aperture_sum'].info.format = '%.8g' # for consistent table output
-+ >>> print(t2['aperture_sum'])
- aperture_sum
-- -------------
-- 111.566370614
-+ ------------
-+ 111.56637
-
-
- Aperture Photometry Using Sky Coordinates
-diff -Naur photutils-0.4/docs/background.rst photutils-0.4.fixed/docs/background.rst
---- photutils-0.4/docs/background.rst 2017-10-30 15:38:18.000000000 +0100
-+++ photutils-0.4.fixed/docs/background.rst 2018-02-14 03:56:07.064522634 +0100
-@@ -76,18 +76,18 @@
-
- >>> import numpy as np
- >>> from astropy.stats import biweight_location
-- >>> print(np.median(data))
-- 5.2255295184
-- >>> print(biweight_location(data))
-- 5.1867597555
-+ >>> print(np.median(data)) # doctest: +FLOAT_CMP
-+ 5.225529518399048
-+ >>> print(biweight_location(data)) # doctest: +FLOAT_CMP
-+ 5.186759755495727
-
- Similarly, using the median absolute deviation to estimate the
- background noise level gives a value that is larger than the true
- value of 2::
-
- >>> from astropy.stats import mad_std
-- >>> print(mad_std(data)) # doctest: +FLOAT_CMP
-- 2.1443728009
-+ >>> print(mad_std(data)) # doctest: +FLOAT_CMP
-+ 2.1443760096598914
-
-
- Sigma Clipping Sources
-@@ -103,8 +103,8 @@
-
- >>> from astropy.stats import sigma_clipped_stats
- >>> mean, median, std = sigma_clipped_stats(data, sigma=3.0, iters=5)
-- >>> print((mean, median, std)) # doctest: +FLOAT_CMP
-- (5.1991386516217908, 5.1555874333582912, 2.0942752121329691)
-+ >>> print((mean, median, std)) # doctest: +FLOAT_CMP
-+ (5.199138651621793, 5.155587433358291, 2.094275212132969)
-
-
- Masking Sources
-@@ -132,8 +132,8 @@
- >>> from photutils import make_source_mask
- >>> mask = make_source_mask(data, snr=2, npixels=5, dilate_size=11)
- >>> mean, median, std = sigma_clipped_stats(data, sigma=3.0, mask=mask)
-- >>> print((mean, median, std)) # doctest: +FLOAT_CMP
-- (5.0010134754755695, 5.0005849056043763, 1.970887100626572)
-+ >>> print((mean, median, std)) # doctest: +FLOAT_CMP
-+ (5.001013475475569, 5.000584905604376, 1.970887100626572)
-
- Of course, the source detection and masking procedure can be iterated
- further. Even with one iteration we are within 0.02% of the true
-@@ -229,7 +229,7 @@
- >>> y, x = np.mgrid[:ny, :nx]
- >>> gradient = x * y / 5000.
- >>> data2 = data + gradient
-- >>> plt.imshow(data2, norm=norm, origin='lower', cmap='Greys_r') # doctest: +SKIP
-+ >>> plt.imshow(data2, norm=norm, origin='lower', cmap='Greys_r') # doctest: +SKIP
-
- .. plot::
-
-@@ -271,10 +271,10 @@
-
- .. doctest-requires:: scipy
-
-- >>> print(bkg.background_median)
-- 10.8219978626
-- >>> print(bkg.background_rms_median)
-- 2.29882053968
-+ >>> print(bkg.background_median) # doctest: +FLOAT_CMP
-+ 10.821997862561792
-+ >>> print(bkg.background_rms_median) # doctest: +FLOAT_CMP
-+ 2.298820539683762
-
- Let's plot the background image:
-
-@@ -348,8 +348,8 @@
-
- >>> from scipy.ndimage import rotate
- >>> data3 = rotate(data2, -45.)
-- >>> norm = ImageNormalize(stretch=SqrtStretch()) # doctest: +SKIP
-- >>> plt.imshow(data3, origin='lower', cmap='Greys_r', norm=norm) # doctest: +SKIP
-+ >>> norm = ImageNormalize(stretch=SqrtStretch()) # doctest: +SKIP
-+ >>> plt.imshow(data3, origin='lower', cmap='Greys_r', norm=norm) # doctest: +SKIP
-
- .. plot::
-
-@@ -386,8 +386,8 @@
- .. doctest-requires:: scipy
-
- >>> back3 = bkg3.background * ~mask
-- >>> norm = ImageNormalize(stretch=SqrtStretch()) # doctest: +SKIP
-- >>> plt.imshow(back3, origin='lower', cmap='Greys_r', norm=norm) # doctest: +SKIP
-+ >>> norm = ImageNormalize(stretch=SqrtStretch()) # doctest: +SKIP
-+ >>> plt.imshow(back3, origin='lower', cmap='Greys_r', norm=norm) # doctest: +SKIP
-
- .. plot::
-
-diff -Naur photutils-0.4/docs/detection.rst photutils-0.4.fixed/docs/detection.rst
---- photutils-0.4/docs/detection.rst 2017-10-30 15:38:18.000000000 +0100
-+++ photutils-0.4.fixed/docs/detection.rst 2018-02-14 03:56:07.065522650 +0100
-@@ -62,20 +62,23 @@
- >>> from photutils import DAOStarFinder
- >>> daofind = DAOStarFinder(fwhm=3.0, threshold=5.*std) # doctest: +REMOTE_DATA
- >>> sources = daofind(data - median) # doctest: +REMOTE_DATA
-+ >>> for col in sources.colnames: # doctest: +REMOTE_DATA
-+ ... sources[col].info.format = '%.8g' # for consistent table output
- >>> print(sources) # doctest: +REMOTE_DATA
-- id xcentroid ycentroid ... peak flux mag
-- --- ------------- ------------- ... ------ ------------- ---------------
-- 1 144.247567164 6.37979042704 ... 6903.0 5.70143033038 -1.88995955438
-- 2 208.669068628 6.82058053777 ... 7896.0 6.72306730455 -2.06891864748
-- 3 216.926136655 6.5775933198 ... 2195.0 1.66737467591 -0.555083002864
-- 4 351.625190383 8.5459013233 ... 6977.0 5.90092548147 -1.92730032571
-- 5 377.519909958 12.0655009987 ... 1260.0 1.11856203781 -0.121650189969
-- ... ... ... ... ... ... ...
-- 281 268.049236979 397.925371446 ... 9299.0 6.22022587541 -1.98451538884
-- 282 268.475068392 398.020998272 ... 8754.0 6.05079160593 -1.95453048936
-- 283 299.80943822 398.027911813 ... 8890.0 6.11853416663 -1.96661847383
-- 284 315.689448343 398.70251891 ... 6485.0 5.55471107793 -1.86165368631
-- 285 360.437243037 398.698539555 ... 8079.0 5.26549321379 -1.80359764345
-+ id xcentroid ycentroid sharpness ... sky peak flux mag
-+ --- --------- --------- ---------- ... --- ---- --------- ------------
-+ 1 144.24757 6.3797904 0.58156257 ... 0 6903 5.7014303 -1.8899596
-+ 2 208.66907 6.8205805 0.48348966 ... 0 7896 6.7230673 -2.0689186
-+ 3 216.92614 6.5775933 0.69359525 ... 0 2195 1.6673747 -0.555083
-+ 4 351.62519 8.5459013 0.48577834 ... 0 6977 5.9009255 -1.9273003
-+ 5 377.51991 12.065501 0.52038488 ... 0 1260 1.118562 -0.12165019
-+ ... ... ... ... ... ... ... ... ...
-+ 280 345.59306 395.38222 0.384078 ... 0 9350 5.0559084 -1.759498
-+ 281 268.04924 397.92537 0.29650715 ... 0 9299 6.2202259 -1.9845154
-+ 282 268.47507 398.021 0.28325741 ... 0 8754 6.0507916 -1.9545305
-+ 283 299.80944 398.02791 0.32011339 ... 0 8890 6.1185342 -1.9666185
-+ 284 315.68945 398.70252 0.29502138 ... 0 6485 5.5547111 -1.8616537
-+ 285 360.43724 398.69854 0.81147144 ... 0 8079 5.2654932 -1.8035976
- Length = 285 rows
-
- Let's plot the image and mark the location of detected sources:
-@@ -143,19 +146,20 @@
- >>> mean, median, std = sigma_clipped_stats(data, sigma=3.0)
- >>> threshold = median + (10.0 * std)
- >>> tbl = find_peaks(data, threshold, box_size=5)
-+ >>> tbl['peak_value'].info.format = '%.8g' # for consistent table output
- >>> print(tbl[:10]) # print only the first 10 peaks
-- x_peak y_peak peak_value
-- ------ ------ -------------
-- 233 0 27.4778521972
-- 236 1 27.339519624
-- 289 22 35.8532759965
-- 442 31 30.2399941373
-- 1 40 35.5482863002
-- 89 59 41.2190469279
-- 7 70 33.2880647048
-- 258 75 26.5624808518
-- 463 80 28.7588206692
-- 182 93 38.0885687202
-+ x_peak y_peak peak_value
-+ ------ ------ ----------
-+ 233 0 27.477852
-+ 236 1 27.33952
-+ 289 22 35.853276
-+ 442 31 30.239994
-+ 1 40 35.548286
-+ 89 59 41.219047
-+ 7 70 33.288065
-+ 258 75 26.562481
-+ 463 80 28.758821
-+ 182 93 38.088569
-
- And let's plot the location of the detected peaks in the image:
-
-diff -Naur photutils-0.4/docs/getting_started.rst photutils-0.4.fixed/docs/getting_started.rst
---- photutils-0.4/docs/getting_started.rst 2017-10-30 15:38:18.000000000 +0100
-+++ photutils-0.4.fixed/docs/getting_started.rst 2018-02-14 03:56:07.065522650 +0100
-@@ -31,20 +31,23 @@
- >>> bkg_sigma = mad_std(image) # doctest: +REMOTE_DATA
- >>> daofind = DAOStarFinder(fwhm=4., threshold=3.*bkg_sigma) # doctest: +REMOTE_DATA
- >>> sources = daofind(image) # doctest: +REMOTE_DATA
-+ >>> for col in sources.colnames: # doctest: +REMOTE_DATA
-+ ... sources[col].info.format = '%.8g' # for consistent table output
- >>> print(sources) # doctest: +REMOTE_DATA
-- id xcentroid ycentroid ... peak flux mag
-- --- ------------- -------------- ... ------ ------------- ---------------
-- 1 182.838658938 0.167670190537 ... 3824.0 2.80283459469 -1.11899367311
-- 2 189.204308134 0.260813525338 ... 4913.0 3.87291850311 -1.47009589582
-- 3 5.79464911433 2.61254240807 ... 7752.0 4.1029107294 -1.53273016937
-- 4 36.8470627804 1.32202279582 ... 8739.0 7.43158178793 -2.17770315441
-- 5 3.2565602452 5.41895201748 ... 6935.0 3.81262984074 -1.45306160673
-- ... ... ... ... ... ... ...
-- 148 124.313272579 188.305229159 ... 6702.0 6.63585429303 -2.05474210356
-- 149 24.2572074962 194.714942814 ... 8342.0 3.2671036996 -1.28540729858
-- 150 116.449998422 195.059233325 ... 3299.0 2.87752205766 -1.1475466535
-- 151 18.9580860645 196.342065132 ... 3854.0 2.38352961224 -0.943051379595
-- 152 111.525751196 195.731917995 ... 8109.0 7.9278607401 -2.24789003194
-+ id xcentroid ycentroid sharpness ... sky peak flux mag
-+ --- --------- ---------- ---------- ... --- ---- --------- -----------
-+ 1 182.83866 0.16767019 0.85099873 ... 0 3824 2.8028346 -1.1189937
-+ 2 189.20431 0.26081353 0.7400477 ... 0 4913 3.8729185 -1.4700959
-+ 3 5.7946491 2.6125424 0.39589731 ... 0 7752 4.1029107 -1.5327302
-+ 4 36.847063 1.3220228 0.29594528 ... 0 8739 7.4315818 -2.1777032
-+ 5 3.2565602 5.418952 0.35985495 ... 0 6935 3.8126298 -1.4530616
-+ ... ... ... ... ... ... ... ... ...
-+ 147 197.24864 186.16647 0.31211532 ... 0 8302 7.5814629 -2.1993825
-+ 148 124.31327 188.30523 0.5362742 ... 0 6702 6.6358543 -2.0547421
-+ 149 24.257207 194.71494 0.44169546 ... 0 8342 3.2671037 -1.2854073
-+ 150 116.45 195.05923 0.67080547 ... 0 3299 2.8775221 -1.1475467
-+ 151 18.958086 196.34207 0.56502139 ... 0 3854 2.3835296 -0.94305138
-+ 152 111.52575 195.73192 0.45827852 ... 0 8109 7.9278607 -2.24789
- Length = 152 rows
-
- Using the list of source locations (``xcentroid`` and ``ycentroid``),
-@@ -59,21 +62,23 @@
- >>> positions = (sources['xcentroid'], sources['ycentroid']) # doctest: +REMOTE_DATA
- >>> apertures = CircularAperture(positions, r=4.) # doctest: +REMOTE_DATA
- >>> phot_table = aperture_photometry(image, apertures) # doctest: +REMOTE_DATA
-- >>> print(phot_table) # doctest: +SKIP
-- id xcenter ycenter aperture_sum
-- pix pix
-- --- ------------------ ------------------- -------------
-- 1 182.8386589381308 0.16767019053693752 18121.7594837
-- 2 189.20430813403388 0.26081352533766516 29836.5152158
-- 3 5.794649114329246 2.612542408073547 331979.819037
-- 4 36.84706278043582 1.3220227958153257 183705.093284
-- 5 3.2565602452007325 5.418952017476508 349468.978627
-- ... ... ... ...
-- 148 124.3132725793939 188.30522915858668 45084.8737867
-- 149 24.257207496209027 194.71494281419265 355778.007298
-- 150 116.44999842177826 195.05923332483115 31232.9117818
-- 151 18.958086064485013 196.3420651316401 162076.262752
-- 152 111.52575119605933 195.73191799469373 82795.7145661
-+ >>> for col in phot_table.colnames: # doctest: +REMOTE_DATA
-+ ... phot_table[col].info.format = '%.8g' # for consistent table output
-+ >>> print(phot_table) # doctest: +REMOTE_DATA
-+ id xcenter ycenter aperture_sum
-+ pix pix
-+ --- --------- ---------- ------------
-+ 1 182.83866 0.16767019 18121.759
-+ 2 189.20431 0.26081353 29836.515
-+ 3 5.7946491 2.6125424 331979.82
-+ 4 36.847063 1.3220228 183705.09
-+ 5 3.2565602 5.418952 349468.98
-+ ... ... ... ...
-+ 148 124.31327 188.30523 45084.874
-+ 149 24.257207 194.71494 355778.01
-+ 150 116.45 195.05923 31232.912
-+ 151 18.958086 196.34207 162076.26
-+ 152 111.52575 195.73192 82795.715
- Length = 152 rows
-
- The sum of the pixel values within the apertures are given in the
-diff -Naur photutils-0.4/photutils/aperture/tests/test_aperture_photometry.py photutils-0.4.fixed/photutils/aperture/tests/test_aperture_photometry.py
---- photutils-0.4/photutils/aperture/tests/test_aperture_photometry.py 2017-10-30 15:38:18.000000000 +0100
-+++ photutils-0.4.fixed/photutils/aperture/tests/test_aperture_photometry.py 2018-02-14 03:56:07.063522619 +0100
-@@ -19,8 +19,10 @@
- from astropy.table import Table
- from astropy.tests.helper import remote_data
- import astropy.units as u
-+from astropy.utils.compat import NUMPY_LT_1_14
- from astropy.wcs.utils import pixel_to_skycoord
-
-+
- from ..core import aperture_photometry
- from ..circle import (CircularAperture, CircularAnnulus, SkyCircularAperture,
- SkyCircularAnnulus)
-@@ -664,64 +666,119 @@
- s = SkyCoord([1, 2], [3, 4], unit='deg')
-
- aper = SkyCircularAperture(s, r=3*u.pix)
-- a_repr = ('<SkyCircularAperture(<SkyCoord (ICRS): (ra, dec) in deg\n'
-- ' [( 1., 3.), ( 2., 4.)]>, r=3.0 pix)>')
-- a_str = ('Aperture: SkyCircularAperture\npositions: <SkyCoord '
-- '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-- 'r: 3.0 pix')
-+ if NUMPY_LT_1_14:
-+ a_repr = ('<SkyCircularAperture(<SkyCoord (ICRS): (ra, dec) in deg\n'
-+ ' [( 1., 3.), ( 2., 4.)]>, r=3.0 pix)>')
-+ a_str = ('Aperture: SkyCircularAperture\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'r: 3.0 pix')
-+ else:
-+ a_repr = ('<SkyCircularAperture(<SkyCoord (ICRS): (ra, dec) in deg\n'
-+ ' [(1., 3.), (2., 4.)]>, r=3.0 pix)>')
-+ a_str = ('Aperture: SkyCircularAperture\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [(1., 3.), (2., 4.)]>\n'
-+ 'r: 3.0 pix')
-+
- assert repr(aper) == a_repr
- assert str(aper) == a_str
-
- aper = SkyCircularAnnulus(s, r_in=3.*u.pix, r_out=5*u.pix)
-- a_repr = ('<SkyCircularAnnulus(<SkyCoord (ICRS): (ra, dec) in deg\n'
-- ' [( 1., 3.), ( 2., 4.)]>, r_in=3.0 pix, r_out=5.0 pix)>')
-- a_str = ('Aperture: SkyCircularAnnulus\npositions: <SkyCoord '
-- '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-- 'r_in: 3.0 pix\nr_out: 5.0 pix')
-+ if NUMPY_LT_1_14:
-+ a_repr = ('<SkyCircularAnnulus(<SkyCoord (ICRS): (ra, dec) in deg\n'
-+ ' [( 1., 3.), ( 2., 4.)]>, r_in=3.0 pix, '
-+ 'r_out=5.0 pix)>')
-+ a_str = ('Aperture: SkyCircularAnnulus\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'r_in: 3.0 pix\nr_out: 5.0 pix')
-+ else:
-+ a_repr = ('<SkyCircularAnnulus(<SkyCoord (ICRS): (ra, dec) in deg\n'
-+ ' [(1., 3.), (2., 4.)]>, r_in=3.0 pix, r_out=5.0 pix)>')
-+ a_str = ('Aperture: SkyCircularAnnulus\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [(1., 3.), (2., 4.)]>\n'
-+ 'r_in: 3.0 pix\nr_out: 5.0 pix')
-+
- assert repr(aper) == a_repr
- assert str(aper) == a_str
-
- aper = SkyEllipticalAperture(s, a=3*u.pix, b=5*u.pix, theta=15*u.deg)
-- a_repr = ('<SkyEllipticalAperture(<SkyCoord (ICRS): (ra, dec) in '
-- 'deg\n [( 1., 3.), ( 2., 4.)]>, a=3.0 pix, b=5.0 pix,'
-- ' theta=15.0 deg)>')
-- a_str = ('Aperture: SkyEllipticalAperture\npositions: <SkyCoord '
-- '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-- 'a: 3.0 pix\nb: 5.0 pix\ntheta: 15.0 deg')
-+ if NUMPY_LT_1_14:
-+ a_repr = ('<SkyEllipticalAperture(<SkyCoord (ICRS): (ra, dec) in '
-+ 'deg\n [( 1., 3.), ( 2., 4.)]>, a=3.0 pix, b=5.0 pix,'
-+ ' theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyEllipticalAperture\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'a: 3.0 pix\nb: 5.0 pix\ntheta: 15.0 deg')
-+ else:
-+ a_repr = ('<SkyEllipticalAperture(<SkyCoord (ICRS): (ra, dec) in '
-+ 'deg\n [(1., 3.), (2., 4.)]>, a=3.0 pix, b=5.0 pix,'
-+ ' theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyEllipticalAperture\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [(1., 3.), (2., 4.)]>\n'
-+ 'a: 3.0 pix\nb: 5.0 pix\ntheta: 15.0 deg')
-+
- assert repr(aper) == a_repr
- assert str(aper) == a_str
-
- aper = SkyEllipticalAnnulus(s, a_in=3*u.pix, a_out=5*u.pix, b_out=3*u.pix,
- theta=15*u.deg)
-- a_repr = ('<SkyEllipticalAnnulus(<SkyCoord (ICRS): (ra, dec) in '
-- 'deg\n [( 1., 3.), ( 2., 4.)]>, a_in=3.0 pix, '
-- 'a_out=5.0 pix, b_out=3.0 pix, theta=15.0 deg)>')
-- a_str = ('Aperture: SkyEllipticalAnnulus\npositions: <SkyCoord '
-- '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-- 'a_in: 3.0 pix\na_out: 5.0 pix\nb_out: 3.0 pix\n'
-- 'theta: 15.0 deg')
-+ if NUMPY_LT_1_14:
-+ a_repr = ('<SkyEllipticalAnnulus(<SkyCoord (ICRS): (ra, dec) in '
-+ 'deg\n [( 1., 3.), ( 2., 4.)]>, a_in=3.0 pix, '
-+ 'a_out=5.0 pix, b_out=3.0 pix, theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyEllipticalAnnulus\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'a_in: 3.0 pix\na_out: 5.0 pix\nb_out: 3.0 pix\n'
-+ 'theta: 15.0 deg')
-+ else:
-+ a_repr = ('<SkyEllipticalAnnulus(<SkyCoord (ICRS): (ra, dec) in '
-+ 'deg\n [(1., 3.), (2., 4.)]>, a_in=3.0 pix, '
-+ 'a_out=5.0 pix, b_out=3.0 pix, theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyEllipticalAnnulus\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [(1., 3.), (2., 4.)]>\n'
-+ 'a_in: 3.0 pix\na_out: 5.0 pix\nb_out: 3.0 pix\n'
-+ 'theta: 15.0 deg')
-+
- assert repr(aper) == a_repr
- assert str(aper) == a_str
-
- aper = SkyRectangularAperture(s, w=3*u.pix, h=5*u.pix, theta=15*u.deg)
-- a_repr = ('<SkyRectangularAperture(<SkyCoord (ICRS): (ra, dec) in '
-- 'deg\n [( 1., 3.), ( 2., 4.)]>, w=3.0 pix, h=5.0 pix'
-- ', theta=15.0 deg)>')
-- a_str = ('Aperture: SkyRectangularAperture\npositions: <SkyCoord '
-- '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-- 'w: 3.0 pix\nh: 5.0 pix\ntheta: 15.0 deg')
-+ if NUMPY_LT_1_14:
-+ a_repr = ('<SkyRectangularAperture(<SkyCoord (ICRS): (ra, dec) in '
-+ 'deg\n [( 1., 3.), ( 2., 4.)]>, w=3.0 pix, h=5.0 pix'
-+ ', theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyRectangularAperture\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'w: 3.0 pix\nh: 5.0 pix\ntheta: 15.0 deg')
-+ else:
-+ a_repr = ('<SkyRectangularAperture(<SkyCoord (ICRS): (ra, dec) in '
-+ 'deg\n [(1., 3.), (2., 4.)]>, w=3.0 pix, h=5.0 pix'
-+ ', theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyRectangularAperture\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [(1., 3.), (2., 4.)]>\n'
-+ 'w: 3.0 pix\nh: 5.0 pix\ntheta: 15.0 deg')
-+
- assert repr(aper) == a_repr
- assert str(aper) == a_str
-
- aper = SkyRectangularAnnulus(s, w_in=3*u.pix, w_out=3.4*u.pix,
- h_out=5*u.pix, theta=15*u.deg)
-- a_repr = ('<SkyRectangularAnnulus(<SkyCoord (ICRS): (ra, dec) in deg'
-- '\n [( 1., 3.), ( 2., 4.)]>, w_in=3.0 pix, '
-- 'w_out=3.4 pix, h_out=5.0 pix, theta=15.0 deg)>')
-- a_str = ('Aperture: SkyRectangularAnnulus\npositions: <SkyCoord '
-- '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-- 'w_in: 3.0 pix\nw_out: 3.4 pix\nh_out: 5.0 pix\n'
-- 'theta: 15.0 deg')
-+ if NUMPY_LT_1_14:
-+ a_repr = ('<SkyRectangularAnnulus(<SkyCoord (ICRS): (ra, dec) in deg'
-+ '\n [( 1., 3.), ( 2., 4.)]>, w_in=3.0 pix, '
-+ 'w_out=3.4 pix, h_out=5.0 pix, theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyRectangularAnnulus\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'w_in: 3.0 pix\nw_out: 3.4 pix\nh_out: 5.0 pix\n'
-+ 'theta: 15.0 deg')
-+ else:
-+ a_repr = ('<SkyRectangularAnnulus(<SkyCoord (ICRS): (ra, dec) in deg'
-+ '\n [(1., 3.), (2., 4.)]>, w_in=3.0 pix, '
-+ 'w_out=3.4 pix, h_out=5.0 pix, theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyRectangularAnnulus\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [(1., 3.), (2., 4.)]>\n'
-+ 'w_in: 3.0 pix\nw_out: 3.4 pix\nh_out: 5.0 pix\n'
-+ 'theta: 15.0 deg')
-+
- assert repr(aper) == a_repr
- assert str(aper) == a_str
-
-diff -Naur photutils-0.4/photutils/aperture/tests/test_aperture_photometry.py.orig photutils-0.4.fixed/photutils/aperture/tests/test_aperture_photometry.py.orig
---- photutils-0.4/photutils/aperture/tests/test_aperture_photometry.py.orig 1970-01-01 01:00:00.000000000 +0100
-+++ photutils-0.4.fixed/photutils/aperture/tests/test_aperture_photometry.py.orig 2017-10-30 15:38:18.000000000 +0100
-@@ -0,0 +1,830 @@
-+# Licensed under a 3-clause BSD style license - see LICENSE.rst
-+"""
-+The tests in this file test the accuracy of the photometric results.
-+Here we test directly with aperture objects since we are checking the
-+algorithms in aperture_photometry, not in the wrappers.
-+"""
-+
-+from __future__ import (absolute_import, division, print_function,
-+ unicode_literals)
-+
-+import pytest
-+import numpy as np
-+from numpy.testing import (assert_allclose, assert_array_equal,
-+ assert_array_less)
-+
-+from astropy.coordinates import SkyCoord
-+from astropy.io import fits
-+from astropy.nddata import NDData
-+from astropy.table import Table
-+from astropy.tests.helper import remote_data
-+import astropy.units as u
-+from astropy.wcs.utils import pixel_to_skycoord
-+
-+from ..core import aperture_photometry
-+from ..circle import (CircularAperture, CircularAnnulus, SkyCircularAperture,
-+ SkyCircularAnnulus)
-+from ..ellipse import (EllipticalAperture, EllipticalAnnulus,
-+ SkyEllipticalAperture, SkyEllipticalAnnulus)
-+from ..rectangle import (RectangularAperture, RectangularAnnulus,
-+ SkyRectangularAperture, SkyRectangularAnnulus)
-+from ...datasets import (get_path, make_4gaussians_image, make_wcs,
-+ make_imagehdu)
-+
-+try:
-+ import matplotlib # noqa
-+ HAS_MATPLOTLIB = True
-+except ImportError:
-+ HAS_MATPLOTLIB = False
-+
-+
-+APERTURE_CL = [CircularAperture,
-+ CircularAnnulus,
-+ EllipticalAperture,
-+ EllipticalAnnulus,
-+ RectangularAperture,
-+ RectangularAnnulus]
-+
-+
-+TEST_APERTURES = list(zip(APERTURE_CL, ((3.,), (3., 5.),
-+ (3., 5., 1.), (3., 5., 4., 1.),
-+ (5, 8, np.pi / 4),
-+ (8, 12, 8, np.pi / 8))))
-+
-+
-+@pytest.mark.parametrize(('aperture_class', 'params'), TEST_APERTURES)
-+def test_outside_array(aperture_class, params):
-+ data = np.ones((10, 10), dtype=np.float)
-+ aperture = aperture_class((-60, 60), *params)
-+ fluxtable = aperture_photometry(data, aperture)
-+ # aperture is fully outside array:
-+ assert np.isnan(fluxtable['aperture_sum'])
-+
-+
-+@pytest.mark.parametrize(('aperture_class', 'params'), TEST_APERTURES)
-+def test_inside_array_simple(aperture_class, params):
-+ data = np.ones((40, 40), dtype=np.float)
-+ aperture = aperture_class((20., 20.), *params)
-+ table1 = aperture_photometry(data, aperture, method='center', subpixels=10)
-+ table2 = aperture_photometry(data, aperture, method='subpixel',
-+ subpixels=10)
-+ table3 = aperture_photometry(data, aperture, method='exact', subpixels=10)
-+ true_flux = aperture.area()
-+
-+ if not isinstance(aperture, (RectangularAperture, RectangularAnnulus)):
-+ assert_allclose(table3['aperture_sum'], true_flux)
-+ assert_allclose(table2['aperture_sum'], table3['aperture_sum'],
-+ atol=0.1)
-+ assert table1['aperture_sum'] < table3['aperture_sum']
-+
-+
-+@pytest.mark.skipif('not HAS_MATPLOTLIB')
-+@pytest.mark.parametrize(('aperture_class', 'params'), TEST_APERTURES)
-+def test_aperture_plots(aperture_class, params):
-+ # This test should run without any errors, and there is no return
-+ # value.
-+ # TODO: check the content of the plot
-+ aperture = aperture_class((20., 20.), *params)
-+ aperture.plot()
-+
-+
-+def test_aperture_pixel_positions():
-+ pos1 = (10, 20)
-+ pos2 = u.Quantity((10, 20), unit=u.pixel)
-+ pos3 = ((10, 20, 30), (10, 20, 30))
-+ pos3_pairs = ((10, 10), (20, 20), (30, 30))
-+
-+ r = 3
-+ ap1 = CircularAperture(pos1, r)
-+ ap2 = CircularAperture(pos2, r)
-+ ap3 = CircularAperture(pos3, r)
-+
-+ assert_allclose(np.atleast_2d(pos1), ap1.positions)
-+ assert_allclose(np.atleast_2d(pos2.value), ap2.positions)
-+ assert_allclose(pos3_pairs, ap3.positions)
-+
-+
-+class BaseTestAperturePhotometry(object):
-+
-+ def test_scalar_error(self):
-+ # Scalar error
-+ error = 1.
-+ if not hasattr(self, 'mask'):
-+ mask = None
-+ true_error = np.sqrt(self.area)
-+ else:
-+ mask = self.mask
-+ # 1 masked pixel
-+ true_error = np.sqrt(self.area - 1)
-+
-+ table1 = aperture_photometry(self.data,
-+ self.aperture, method='center',
-+ mask=mask, error=error)
-+ table2 = aperture_photometry(self.data,
-+ self.aperture,
-+ method='subpixel', subpixels=12,
-+ mask=mask, error=error)
-+ table3 = aperture_photometry(self.data,
-+ self.aperture, method='exact',
-+ mask=mask, error=error)
-+
-+ if not isinstance(self.aperture, (RectangularAperture,
-+ RectangularAnnulus)):
-+ assert_allclose(table3['aperture_sum'], self.true_flux)
-+ assert_allclose(table2['aperture_sum'], table3['aperture_sum'],
-+ atol=0.1)
-+ assert np.all(table1['aperture_sum'] < table3['aperture_sum'])
-+
-+ if not isinstance(self.aperture, (RectangularAperture,
-+ RectangularAnnulus)):
-+ assert_allclose(table3['aperture_sum_err'], true_error)
-+ assert_allclose(table2['aperture_sum'], table3['aperture_sum'],
-+ atol=0.1)
-+ assert np.all(table1['aperture_sum_err'] < table3['aperture_sum_err'])
-+
-+ def test_array_error(self):
-+ # Array error
-+ error = np.ones(self.data.shape, dtype=np.float)
-+ if not hasattr(self, 'mask'):
-+ mask = None
-+ true_error = np.sqrt(self.area)
-+ else:
-+ mask = self.mask
-+ # 1 masked pixel
-+ true_error = np.sqrt(self.area - 1)
-+
-+ table1 = aperture_photometry(self.data,
-+ self.aperture, method='center',
-+ mask=mask, error=error)
-+ table2 = aperture_photometry(self.data,
-+ self.aperture,
-+ method='subpixel', subpixels=12,
-+ mask=mask, error=error)
-+ table3 = aperture_photometry(self.data,
-+ self.aperture, method='exact',
-+ mask=mask, error=error)
-+
-+ if not isinstance(self.aperture, (RectangularAperture,
-+ RectangularAnnulus)):
-+ assert_allclose(table3['aperture_sum'], self.true_flux)
-+ assert_allclose(table2['aperture_sum'], table3['aperture_sum'],
-+ atol=0.1)
-+ assert np.all(table1['aperture_sum'] < table3['aperture_sum'])
-+
-+ if not isinstance(self.aperture, (RectangularAperture,
-+ RectangularAnnulus)):
-+ assert_allclose(table3['aperture_sum_err'], true_error)
-+ assert_allclose(table2['aperture_sum_err'],
-+ table3['aperture_sum_err'], atol=0.1)
-+ assert np.all(table1['aperture_sum_err'] < table3['aperture_sum_err'])
-+
-+
-+class TestCircular(BaseTestAperturePhotometry):
-+
-+ def setup_class(self):
-+ self.data = np.ones((40, 40), dtype=np.float)
-+ position = (20., 20.)
-+ r = 10.
-+ self.aperture = CircularAperture(position, r)
-+ self.area = np.pi * r * r
-+ self.true_flux = self.area
-+
-+
-+class TestCircularArray(BaseTestAperturePhotometry):
-+
-+ def setup_class(self):
-+ self.data = np.ones((40, 40), dtype=np.float)
-+ position = ((20., 20.), (25., 25.))
-+ r = 10.
-+ self.aperture = CircularAperture(position, r)
-+ self.area = np.pi * r * r
-+ self.area = np.array((self.area, ) * 2)
-+ self.true_flux = self.area
-+
-+
-+class TestCircularAnnulus(BaseTestAperturePhotometry):
-+
-+ def setup_class(self):
-+ self.data = np.ones((40, 40), dtype=np.float)
-+ position = (20., 20.)
-+ r_in = 8.
-+ r_out = 10.
-+ self.aperture = CircularAnnulus(position, r_in, r_out)
-+ self.area = np.pi * (r_out * r_out - r_in * r_in)
-+ self.true_flux = self.area
-+
-+
-+class TestCircularAnnulusArray(BaseTestAperturePhotometry):
-+
-+ def setup_class(self):
-+ self.data = np.ones((40, 40), dtype=np.float)
-+ position = ((20., 20.), (25., 25.))
-+ r_in = 8.
-+ r_out = 10.
-+ self.aperture = CircularAnnulus(position, r_in, r_out)
-+ self.area = np.pi * (r_out * r_out - r_in * r_in)
-+ self.area = np.array((self.area, ) * 2)
-+ self.true_flux = self.area
-+
-+
-+class TestElliptical(BaseTestAperturePhotometry):
-+
-+ def setup_class(self):
-+ self.data = np.ones((40, 40), dtype=np.float)
-+ position = (20., 20.)
-+ a = 10.
-+ b = 5.
-+ theta = -np.pi / 4.
-+ self.aperture = EllipticalAperture(position, a, b, theta)
-+ self.area = np.pi * a * b
-+ self.true_flux = self.area
-+
-+
-+class TestEllipticalAnnulus(BaseTestAperturePhotometry):
-+
-+ def setup_class(self):
-+ self.data = np.ones((40, 40), dtype=np.float)
-+ position = (20., 20.)
-+ a_in = 5.
-+ a_out = 8.
-+ b_out = 5.
-+ theta = -np.pi / 4.
-+ self.aperture = EllipticalAnnulus(position, a_in, a_out, b_out, theta)
-+ self.area = (np.pi * (a_out * b_out) -
-+ np.pi * (a_in * b_out * a_in / a_out))
-+ self.true_flux = self.area
-+
-+
-+class TestRectangularAperture(BaseTestAperturePhotometry):
-+
-+ def setup_class(self):
-+ self.data = np.ones((40, 40), dtype=np.float)
-+ position = (20., 20.)
-+ h = 5.
-+ w = 8.
-+ theta = np.pi / 4.
-+ self.aperture = RectangularAperture(position, w, h, theta)
-+ self.area = h * w
-+ self.true_flux = self.area
-+
-+
-+class TestRectangularAnnulus(BaseTestAperturePhotometry):
-+
-+ def setup_class(self):
-+ self.data = np.ones((40, 40), dtype=np.float)
-+ position = (20., 20.)
-+ h_out = 8.
-+ w_in = 8.
-+ w_out = 12.
-+ h_in = w_in * h_out / w_out
-+ theta = np.pi / 8.
-+ self.aperture = RectangularAnnulus(position, w_in, w_out, h_out, theta)
-+ self.area = h_out * w_out - h_in * w_in
-+ self.true_flux = self.area
-+
-+
-+class TestMaskedSkipCircular(BaseTestAperturePhotometry):
-+
-+ def setup_class(self):
-+ self.data = np.ones((40, 40), dtype=np.float)
-+ self.mask = np.zeros((40, 40), dtype=bool)
-+ self.mask[20, 20] = True
-+ position = (20., 20.)
-+ r = 10.
-+ self.aperture = CircularAperture(position, r)
-+ self.area = np.pi * r * r
-+ self.true_flux = self.area - 1
-+
-+
-+class BaseTestDifferentData(object):
-+
-+ def test_basic_circular_aperture_photometry(self):
-+ aperture = CircularAperture(self.position, self.radius)
-+ table = aperture_photometry(self.data, aperture,
-+ method='exact', unit='adu')
-+
-+ assert_allclose(table['aperture_sum'].value, self.true_flux)
-+ assert table['aperture_sum'].unit, self.fluxunit
-+
-+ assert np.all(table['xcenter'].value ==
-+ np.transpose(self.position)[0])
-+ assert np.all(table['ycenter'].value ==
-+ np.transpose(self.position)[1])
-+
-+
-+class TestInputPrimaryHDU(BaseTestDifferentData):
-+
-+ def setup_class(self):
-+ data = np.ones((40, 40), dtype=np.float)
-+ self.data = fits.ImageHDU(data=data)
-+ self.data.header['BUNIT'] = 'adu'
-+ self.radius = 3
-+ self.position = (20, 20)
-+ self.true_flux = np.pi * self.radius * self.radius
-+ self.fluxunit = u.adu
-+
-+
-+class TestInputHDUList(BaseTestDifferentData):
-+
-+ def setup_class(self):
-+ data0 = np.ones((40, 40), dtype=np.float)
-+ data1 = np.empty((40, 40), dtype=np.float)
-+ data1.fill(2)
-+ self.data = fits.HDUList([fits.ImageHDU(data=data0),
-+ fits.ImageHDU(data=data1)])
-+ self.radius = 3
-+ self.position = (20, 20)
-+ # It should stop at the first extension
-+ self.true_flux = np.pi * self.radius * self.radius
-+
-+
-+class TestInputHDUDifferentBUNIT(BaseTestDifferentData):
-+
-+ def setup_class(self):
-+ data = np.ones((40, 40), dtype=np.float)
-+ self.data = fits.ImageHDU(data=data)
-+ self.data.header['BUNIT'] = 'Jy'
-+ self.radius = 3
-+ self.position = (20, 20)
-+ self.true_flux = np.pi * self.radius * self.radius
-+ self.fluxunit = u.adu
-+
-+
-+class TestInputNDData(BaseTestDifferentData):
-+
-+ def setup_class(self):
-+ data = np.ones((40, 40), dtype=np.float)
-+ self.data = NDData(data, unit=u.adu)
-+ self.radius = 3
-+ self.position = [(20, 20), (30, 30)]
-+ self.true_flux = np.pi * self.radius * self.radius
-+ self.fluxunit = u.adu
-+
-+
-+@remote_data
-+def test_wcs_based_photometry_to_catalogue():
-+ pathcat = get_path('spitzer_example_catalog.xml', location='remote')
-+ pathhdu = get_path('spitzer_example_image.fits', location='remote')
-+ hdu = fits.open(pathhdu)
-+ scale = hdu[0].header['PIXSCAL1']
-+
-+ catalog = Table.read(pathcat)
-+
-+ pos_skycoord = SkyCoord(catalog['l'], catalog['b'], frame='galactic')
-+
-+ photometry_skycoord = aperture_photometry(
-+ hdu, SkyCircularAperture(pos_skycoord, 4 * u.arcsec))
-+
-+ photometry_skycoord_pix = aperture_photometry(
-+ hdu, SkyCircularAperture(pos_skycoord, 4. / scale * u.pixel))
-+
-+ assert_allclose(photometry_skycoord['aperture_sum'],
-+ photometry_skycoord_pix['aperture_sum'])
-+
-+ # Photometric unit conversion is needed to match the catalogue
-+ factor = (1.2 * u.arcsec) ** 2 / u.pixel
-+ converted_aperture_sum = (photometry_skycoord['aperture_sum'] *
-+ factor).to(u.mJy / u.pixel)
-+
-+ fluxes_catalog = catalog['f4_5'].filled()
-+
-+ # There shouldn't be large outliers, but some differences is OK, as
-+ # fluxes_catalog is based on PSF photometry, etc.
-+ assert_allclose(fluxes_catalog, converted_aperture_sum.value, rtol=1e0)
-+
-+ assert(np.mean(np.fabs(((fluxes_catalog - converted_aperture_sum.value) /
-+ fluxes_catalog))) < 0.1)
-+
-+
-+def test_wcs_based_photometry():
-+ data = make_4gaussians_image()
-+ wcs = make_wcs(data.shape)
-+ hdu = make_imagehdu(data, wcs=wcs)
-+
-+ # hard wired positions in make_4gaussian_image
-+ pos_orig_pixel = u.Quantity(([160., 25., 150., 90.],
-+ [70., 40., 25., 60.]), unit=u.pixel)
-+
-+ pos_skycoord = pixel_to_skycoord(pos_orig_pixel[0], pos_orig_pixel[1], wcs)
-+
-+ pos_skycoord_s = pos_skycoord[2]
-+
-+ photometry_skycoord_circ = aperture_photometry(
-+ hdu, SkyCircularAperture(pos_skycoord, 3 * u.arcsec))
-+ photometry_skycoord_circ_2 = aperture_photometry(
-+ hdu, SkyCircularAperture(pos_skycoord, 2 * u.arcsec))
-+ photometry_skycoord_circ_s = aperture_photometry(
-+ hdu, SkyCircularAperture(pos_skycoord_s, 3 * u.arcsec))
-+
-+ assert_allclose(photometry_skycoord_circ['aperture_sum'][2],
-+ photometry_skycoord_circ_s['aperture_sum'])
-+
-+ photometry_skycoord_circ_ann = aperture_photometry(
-+ hdu, SkyCircularAnnulus(pos_skycoord, 2 * u.arcsec, 3 * u.arcsec))
-+ photometry_skycoord_circ_ann_s = aperture_photometry(
-+ hdu, SkyCircularAnnulus(pos_skycoord_s, 2 * u.arcsec, 3 * u.arcsec))
-+
-+ assert_allclose(photometry_skycoord_circ_ann['aperture_sum'][2],
-+ photometry_skycoord_circ_ann_s['aperture_sum'])
-+
-+ assert_allclose(photometry_skycoord_circ_ann['aperture_sum'],
-+ photometry_skycoord_circ['aperture_sum'] -
-+ photometry_skycoord_circ_2['aperture_sum'])
-+
-+ photometry_skycoord_ell = aperture_photometry(
-+ hdu, SkyEllipticalAperture(pos_skycoord, 3 * u.arcsec,
-+ 3.0001 * u.arcsec, 45 * u.arcsec))
-+ photometry_skycoord_ell_2 = aperture_photometry(
-+ hdu, SkyEllipticalAperture(pos_skycoord, 2 * u.arcsec,
-+ 2.0001 * u.arcsec, 45 * u.arcsec))
-+ photometry_skycoord_ell_s = aperture_photometry(
-+ hdu, SkyEllipticalAperture(pos_skycoord_s, 3 * u.arcsec,
-+ 3.0001 * u.arcsec, 45 * u.arcsec))
-+ photometry_skycoord_ell_ann = aperture_photometry(
-+ hdu, SkyEllipticalAnnulus(pos_skycoord, 2 * u.arcsec, 3 * u.arcsec,
-+ 3.0001 * u.arcsec, 45 * u.arcsec))
-+ photometry_skycoord_ell_ann_s = aperture_photometry(
-+ hdu, SkyEllipticalAnnulus(pos_skycoord_s, 2 * u.arcsec, 3 * u.arcsec,
-+ 3.0001 * u.arcsec, 45 * u.arcsec))
-+
-+ assert_allclose(photometry_skycoord_ell['aperture_sum'][2],
-+ photometry_skycoord_ell_s['aperture_sum'])
-+
-+ assert_allclose(photometry_skycoord_ell_ann['aperture_sum'][2],
-+ photometry_skycoord_ell_ann_s['aperture_sum'])
-+
-+ assert_allclose(photometry_skycoord_ell['aperture_sum'],
-+ photometry_skycoord_circ['aperture_sum'], rtol=5e-3)
-+
-+ assert_allclose(photometry_skycoord_ell_ann['aperture_sum'],
-+ photometry_skycoord_ell['aperture_sum'] -
-+ photometry_skycoord_ell_2['aperture_sum'], rtol=1e-4)
-+
-+ photometry_skycoord_rec = aperture_photometry(
-+ hdu, SkyRectangularAperture(pos_skycoord,
-+ 6 * u.arcsec, 6 * u.arcsec,
-+ 0 * u.arcsec),
-+ method='subpixel', subpixels=20)
-+ photometry_skycoord_rec_4 = aperture_photometry(
-+ hdu, SkyRectangularAperture(pos_skycoord,
-+ 4 * u.arcsec, 4 * u.arcsec,
-+ 0 * u.arcsec),
-+ method='subpixel', subpixels=20)
-+ photometry_skycoord_rec_s = aperture_photometry(
-+ hdu, SkyRectangularAperture(pos_skycoord_s,
-+ 6 * u.arcsec, 6 * u.arcsec,
-+ 0 * u.arcsec),
-+ method='subpixel', subpixels=20)
-+ photometry_skycoord_rec_ann = aperture_photometry(
-+ hdu, SkyRectangularAnnulus(pos_skycoord, 4 * u.arcsec, 6 * u.arcsec,
-+ 6 * u.arcsec, 0 * u.arcsec),
-+ method='subpixel', subpixels=20)
-+ photometry_skycoord_rec_ann_s = aperture_photometry(
-+ hdu, SkyRectangularAnnulus(pos_skycoord_s, 4 * u.arcsec, 6 * u.arcsec,
-+ 6 * u.arcsec, 0 * u.arcsec),
-+ method='subpixel', subpixels=20)
-+
-+ assert_allclose(photometry_skycoord_rec['aperture_sum'][2],
-+ photometry_skycoord_rec_s['aperture_sum'])
-+
-+ assert np.all(photometry_skycoord_rec['aperture_sum'] >
-+ photometry_skycoord_circ['aperture_sum'])
-+
-+ assert_allclose(photometry_skycoord_rec_ann['aperture_sum'][2],
-+ photometry_skycoord_rec_ann_s['aperture_sum'])
-+
-+ assert_allclose(photometry_skycoord_rec_ann['aperture_sum'],
-+ photometry_skycoord_rec['aperture_sum'] -
-+ photometry_skycoord_rec_4['aperture_sum'], rtol=1e-4)
-+
-+
-+def test_basic_circular_aperture_photometry_unit():
-+ data1 = np.ones((40, 40), dtype=np.float)
-+ data2 = u.Quantity(data1, unit=u.adu)
-+
-+ radius = 3
-+ position = (20, 20)
-+ true_flux = np.pi * radius * radius
-+ unit = u.adu
-+
-+ table1 = aperture_photometry(data1, CircularAperture(position, radius),
-+ unit=unit)
-+ table2 = aperture_photometry(data2, CircularAperture(position, radius),
-+ unit=unit)
-+
-+ assert_allclose(table1['aperture_sum'].value, true_flux)
-+ assert_allclose(table2['aperture_sum'].value, true_flux)
-+ assert table1['aperture_sum'].unit == unit
-+ assert table2['aperture_sum'].unit == data2.unit == unit
-+
-+
-+def test_aperture_photometry_with_error_units():
-+ """Test aperture_photometry when error has units (see #176)."""
-+
-+ data1 = np.ones((40, 40), dtype=np.float)
-+ data2 = u.Quantity(data1, unit=u.adu)
-+ error = u.Quantity(data1, unit=u.adu)
-+ radius = 3
-+ true_flux = np.pi * radius * radius
-+ unit = u.adu
-+ position = (20, 20)
-+ table1 = aperture_photometry(data2, CircularAperture(position, radius),
-+ error=error)
-+ assert_allclose(table1['aperture_sum'].value, true_flux)
-+ assert_allclose(table1['aperture_sum_err'].value, np.sqrt(true_flux))
-+ assert table1['aperture_sum'].unit == unit
-+ assert table1['aperture_sum_err'].unit == unit
-+
-+
-+def test_aperture_photometry_inputs_with_mask():
-+ """
-+ Test that aperture_photometry does not modify the input
-+ data or error array when a mask is input.
-+ """
-+
-+ data = np.ones((5, 5))
-+ aperture = CircularAperture((2, 2), 2.)
-+ mask = np.zeros_like(data, dtype=bool)
-+ data[2, 2] = 100. # bad pixel
-+ mask[2, 2] = True
-+ error = np.sqrt(data)
-+ data_in = data.copy()
-+ error_in = error.copy()
-+ t1 = aperture_photometry(data, aperture, error=error, mask=mask)
-+ assert_array_equal(data, data_in)
-+ assert_array_equal(error, error_in)
-+ assert_allclose(t1['aperture_sum'][0], 11.5663706144)
-+ t2 = aperture_photometry(data, aperture)
-+ assert_allclose(t2['aperture_sum'][0], 111.566370614)
-+
-+
-+TEST_ELLIPSE_EXACT_APERTURES = [(3.469906, 3.923861394, 3.),
-+ (0.3834415188257778, 0.3834415188257778, 0.3)]
-+
-+
-+@pytest.mark.parametrize('x,y,r', TEST_ELLIPSE_EXACT_APERTURES)
-+def test_ellipse_exact_grid(x, y, r):
-+ """
-+ Test elliptical exact aperture photometry on a grid of pixel positions.
-+
-+ This is a regression test for the bug discovered in this issue:
-+ https://github.com/astropy/photutils/issues/198
-+ """
-+
-+ data = np.ones((10, 10))
-+
-+ aperture = EllipticalAperture((x, y), r, r, 0.)
-+ t = aperture_photometry(data, aperture, method='exact')
-+ actual = t['aperture_sum'][0] / (np.pi * r ** 2)
-+ assert_allclose(actual, 1)
-+
-+
-+@pytest.mark.parametrize('value', [np.nan, np.inf])
-+def test_nan_inf_mask(value):
-+ """Test that nans and infs are properly masked [267]."""
-+
-+ data = np.ones((9, 9))
-+ mask = np.zeros_like(data, dtype=bool)
-+ data[4, 4] = value
-+ mask[4, 4] = True
-+ radius = 2.
-+ aper = CircularAperture((4, 4), radius)
-+ tbl = aperture_photometry(data, aper, mask=mask)
-+ desired = (np.pi * radius**2) - 1
-+ assert_allclose(tbl['aperture_sum'], desired)
-+
-+
-+def test_aperture_partial_overlap():
-+ data = np.ones((20, 20))
-+ error = np.ones((20, 20))
-+ xypos = [(10, 10), (0, 0), (0, 19), (19, 0), (19, 19)]
-+ r = 5.
-+ aper = CircularAperture(xypos, r=r)
-+ tbl = aperture_photometry(data, aper, error=error)
-+ assert_allclose(tbl['aperture_sum'][0], np.pi * r ** 2)
-+ assert_array_less(tbl['aperture_sum'][1:], np.pi * r ** 2)
-+
-+ unit = u.MJy / u.sr
-+ tbl = aperture_photometry(data * unit, aper, error=error * unit)
-+ assert_allclose(tbl['aperture_sum'][0].value, np.pi * r ** 2)
-+ assert_array_less(tbl['aperture_sum'][1:].value, np.pi * r ** 2)
-+ assert_array_less(tbl['aperture_sum_err'][1:].value, np.pi * r ** 2)
-+ assert tbl['aperture_sum'].unit == unit
-+ assert tbl['aperture_sum_err'].unit == unit
-+
-+
-+def test_pixel_aperture_repr():
-+ aper = CircularAperture((10, 20), r=3.0)
-+ a_repr = '<CircularAperture([[10, 20]], r=3.0)>'
-+ a_str = 'Aperture: CircularAperture\npositions: [[10, 20]]\nr: 3.0'
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+ aper = CircularAnnulus((10, 20), r_in=3.0, r_out=5.0)
-+ a_repr = '<CircularAnnulus([[10, 20]], r_in=3.0, r_out=5.0)>'
-+ a_str = ('Aperture: CircularAnnulus\npositions: [[10, 20]]\nr_in: 3.0\n'
-+ 'r_out: 5.0')
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+ aper = EllipticalAperture((10, 20), a=5.0, b=3.0, theta=15.0)
-+ a_repr = '<EllipticalAperture([[10, 20]], a=5.0, b=3.0, theta=15.0)>'
-+ a_str = ('Aperture: EllipticalAperture\npositions: [[10, 20]]\n'
-+ 'a: 5.0\nb: 3.0\ntheta: 15.0')
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+ aper = EllipticalAnnulus((10, 20), a_in=4.0, a_out=8.0, b_out=4.0,
-+ theta=15.0)
-+ a_repr = ('<EllipticalAnnulus([[10, 20]], a_in=4.0, a_out=8.0, b_out='
-+ '4.0, theta=15.0)>')
-+ a_str = ('Aperture: EllipticalAnnulus\npositions: [[10, 20]]\na_in: '
-+ '4.0\na_out: 8.0\nb_out: 4.0\ntheta: 15.0')
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+ aper = RectangularAperture((10, 20), w=5.0, h=3.0, theta=15.0)
-+ a_repr = '<RectangularAperture([[10, 20]], w=5.0, h=3.0, theta=15.0)>'
-+ a_str = ('Aperture: RectangularAperture\npositions: [[10, 20]]\n'
-+ 'w: 5.0\nh: 3.0\ntheta: 15.0')
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+ aper = RectangularAnnulus((10, 20), w_in=4.0, w_out=8.0, h_out=4.0,
-+ theta=15.0)
-+ a_repr = ('<RectangularAnnulus([[10, 20]], w_in=4.0, w_out=8.0, '
-+ 'h_out=4.0, theta=15.0)>')
-+ a_str = ('Aperture: RectangularAnnulus\npositions: [[10, 20]]\n'
-+ 'w_in: 4.0\nw_out: 8.0\nh_out: 4.0\ntheta: 15.0')
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+
-+def test_sky_aperture_repr():
-+ s = SkyCoord([1, 2], [3, 4], unit='deg')
-+
-+ aper = SkyCircularAperture(s, r=3*u.pix)
-+ a_repr = ('<SkyCircularAperture(<SkyCoord (ICRS): (ra, dec) in deg\n'
-+ ' [( 1., 3.), ( 2., 4.)]>, r=3.0 pix)>')
-+ a_str = ('Aperture: SkyCircularAperture\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'r: 3.0 pix')
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+ aper = SkyCircularAnnulus(s, r_in=3.*u.pix, r_out=5*u.pix)
-+ a_repr = ('<SkyCircularAnnulus(<SkyCoord (ICRS): (ra, dec) in deg\n'
-+ ' [( 1., 3.), ( 2., 4.)]>, r_in=3.0 pix, r_out=5.0 pix)>')
-+ a_str = ('Aperture: SkyCircularAnnulus\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'r_in: 3.0 pix\nr_out: 5.0 pix')
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+ aper = SkyEllipticalAperture(s, a=3*u.pix, b=5*u.pix, theta=15*u.deg)
-+ a_repr = ('<SkyEllipticalAperture(<SkyCoord (ICRS): (ra, dec) in '
-+ 'deg\n [( 1., 3.), ( 2., 4.)]>, a=3.0 pix, b=5.0 pix,'
-+ ' theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyEllipticalAperture\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'a: 3.0 pix\nb: 5.0 pix\ntheta: 15.0 deg')
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+ aper = SkyEllipticalAnnulus(s, a_in=3*u.pix, a_out=5*u.pix, b_out=3*u.pix,
-+ theta=15*u.deg)
-+ a_repr = ('<SkyEllipticalAnnulus(<SkyCoord (ICRS): (ra, dec) in '
-+ 'deg\n [( 1., 3.), ( 2., 4.)]>, a_in=3.0 pix, '
-+ 'a_out=5.0 pix, b_out=3.0 pix, theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyEllipticalAnnulus\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'a_in: 3.0 pix\na_out: 5.0 pix\nb_out: 3.0 pix\n'
-+ 'theta: 15.0 deg')
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+ aper = SkyRectangularAperture(s, w=3*u.pix, h=5*u.pix, theta=15*u.deg)
-+ a_repr = ('<SkyRectangularAperture(<SkyCoord (ICRS): (ra, dec) in '
-+ 'deg\n [( 1., 3.), ( 2., 4.)]>, w=3.0 pix, h=5.0 pix'
-+ ', theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyRectangularAperture\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'w: 3.0 pix\nh: 5.0 pix\ntheta: 15.0 deg')
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+ aper = SkyRectangularAnnulus(s, w_in=3*u.pix, w_out=3.4*u.pix,
-+ h_out=5*u.pix, theta=15*u.deg)
-+ a_repr = ('<SkyRectangularAnnulus(<SkyCoord (ICRS): (ra, dec) in deg'
-+ '\n [( 1., 3.), ( 2., 4.)]>, w_in=3.0 pix, '
-+ 'w_out=3.4 pix, h_out=5.0 pix, theta=15.0 deg)>')
-+ a_str = ('Aperture: SkyRectangularAnnulus\npositions: <SkyCoord '
-+ '(ICRS): (ra, dec) in deg\n [( 1., 3.), ( 2., 4.)]>\n'
-+ 'w_in: 3.0 pix\nw_out: 3.4 pix\nh_out: 5.0 pix\n'
-+ 'theta: 15.0 deg')
-+ assert repr(aper) == a_repr
-+ assert str(aper) == a_str
-+
-+
-+def test_rectangular_bbox():
-+ # odd sizes
-+ width = 7
-+ height = 3
-+ a = RectangularAperture((50, 50), w=width, h=height, theta=0)
-+ assert a.bounding_boxes[0].shape == (height, width)
-+
-+ a = RectangularAperture((50.5, 50.5), w=width, h=height, theta=0)
-+ assert a.bounding_boxes[0].shape == (height + 1, width + 1)
-+
-+ a = RectangularAperture((50, 50), w=width, h=height, theta=90.*np.pi/180.)
-+ assert a.bounding_boxes[0].shape == (width, height)
-+
-+ # even sizes
-+ width = 8
-+ height = 4
-+ a = RectangularAperture((50, 50), w=width, h=height, theta=0)
-+ assert a.bounding_boxes[0].shape == (height + 1, width + 1)
-+
-+ a = RectangularAperture((50.5, 50.5), w=width, h=height, theta=0)
-+ assert a.bounding_boxes[0].shape == (height, width)
-+
-+ a = RectangularAperture((50.5, 50.5), w=width, h=height,
-+ theta=90.*np.pi/180.)
-+ assert a.bounding_boxes[0].shape == (width, height)
-+
-+
-+def test_elliptical_bbox():
-+ # integer axes
-+ a = 7
-+ b = 3
-+ ap = EllipticalAperture((50, 50), a=a, b=b, theta=0)
-+ assert ap.bounding_boxes[0].shape == (2*b + 1, 2*a + 1)
-+
-+ ap = EllipticalAperture((50.5, 50.5), a=a, b=b, theta=0)
-+ assert ap.bounding_boxes[0].shape == (2*b, 2*a)
-+
-+ ap = EllipticalAperture((50, 50), a=a, b=b, theta=90.*np.pi/180.)
-+ assert ap.bounding_boxes[0].shape == (2*a + 1, 2*b + 1)
-+
-+ # fractional axes
-+ a = 7.5
-+ b = 4.5
-+ ap = EllipticalAperture((50, 50), a=a, b=b, theta=0)
-+ assert ap.bounding_boxes[0].shape == (2*b, 2*a)
-+
-+ ap = EllipticalAperture((50.5, 50.5), a=a, b=b, theta=0)
-+ assert ap.bounding_boxes[0].shape == (2*b + 1, 2*a + 1)
-+
-+ ap = EllipticalAperture((50, 50), a=a, b=b, theta=90.*np.pi/180.)
-+ assert ap.bounding_boxes[0].shape == (2*a, 2*b)
-+
-+
-+def test_to_sky_pixel():
-+ data = make_4gaussians_image()
-+ wcs = make_wcs(data.shape)
-+
-+ ap = CircularAperture(((12.3, 15.7), (48.19, 98.14)), r=3.14)
-+ ap2 = ap.to_sky(wcs).to_pixel(wcs)
-+ assert_allclose(ap.positions, ap2.positions)
-+ assert_allclose(ap.r, ap2.r)
-+
-+ ap = CircularAnnulus(((12.3, 15.7), (48.19, 98.14)), r_in=3.14,
-+ r_out=5.32)
-+ ap2 = ap.to_sky(wcs).to_pixel(wcs)
-+ assert_allclose(ap.positions, ap2.positions)
-+ assert_allclose(ap.r_in, ap2.r_in)
-+ assert_allclose(ap.r_out, ap2.r_out)
-+
-+ ap = EllipticalAperture(((12.3, 15.7), (48.19, 98.14)), a=3.14, b=5.32,
-+ theta=103.*np.pi/180.)
-+ ap2 = ap.to_sky(wcs).to_pixel(wcs)
-+ assert_allclose(ap.positions, ap2.positions)
-+ assert_allclose(ap.a, ap2.a)
-+ assert_allclose(ap.b, ap2.b)
-+ assert_allclose(ap.theta, ap2.theta)
-+
-+ ap = EllipticalAnnulus(((12.3, 15.7), (48.19, 98.14)), a_in=3.14,
-+ a_out=15.32, b_out=4.89, theta=103.*np.pi/180.)
-+ ap2 = ap.to_sky(wcs).to_pixel(wcs)
-+ assert_allclose(ap.positions, ap2.positions)
-+ assert_allclose(ap.a_in, ap2.a_in)
-+ assert_allclose(ap.a_out, ap2.a_out)
-+ assert_allclose(ap.b_out, ap2.b_out)
-+ assert_allclose(ap.theta, ap2.theta)
-+
-+ ap = RectangularAperture(((12.3, 15.7), (48.19, 98.14)), w=3.14, h=5.32,
-+ theta=103.*np.pi/180.)
-+ ap2 = ap.to_sky(wcs).to_pixel(wcs)
-+ assert_allclose(ap.positions, ap2.positions)
-+ assert_allclose(ap.w, ap2.w)
-+ assert_allclose(ap.h, ap2.h)
-+ assert_allclose(ap.theta, ap2.theta)
-+
-+ ap = RectangularAnnulus(((12.3, 15.7), (48.19, 98.14)), w_in=3.14,
-+ w_out=15.32, h_out=4.89, theta=103.*np.pi/180.)
-+ ap2 = ap.to_sky(wcs).to_pixel(wcs)
-+ assert_allclose(ap.positions, ap2.positions)
-+ assert_allclose(ap.w_in, ap2.w_in)
-+ assert_allclose(ap.w_out, ap2.w_out)
-+ assert_allclose(ap.h_out, ap2.h_out)
-+ assert_allclose(ap.theta, ap2.theta)
-diff -Naur photutils-0.4/photutils/background/core.py photutils-0.4.fixed/photutils/background/core.py
---- photutils-0.4/photutils/background/core.py 2017-10-30 15:38:18.000000000 +0100
-+++ photutils-0.4.fixed/photutils/background/core.py 2018-02-14 03:56:07.063522619 +0100
-@@ -477,14 +477,14 @@
-
- >>> bkgrms_value = bkgrms.calc_background_rms(data)
- >>> print(bkgrms_value) # doctest: +FLOAT_CMP
-- 28.866070047722118
-+ 28.86607004772212
-
- Alternatively, the background RMS value can be calculated by calling
- the class instance as a function, e.g.:
-
- >>> bkgrms_value = bkgrms(data)
- >>> print(bkgrms_value) # doctest: +FLOAT_CMP
-- 28.866070047722118
-+ 28.86607004772212
- """
-
- def calc_background_rms(self, data, axis=None):
-@@ -531,14 +531,14 @@
-
- >>> bkgrms_value = bkgrms.calc_background_rms(data)
- >>> print(bkgrms_value) # doctest: +FLOAT_CMP
-- 37.065055462640053
-+ 37.06505546264005
-
- Alternatively, the background RMS value can be calculated by calling
- the class instance as a function, e.g.:
-
- >>> bkgrms_value = bkgrms(data)
- >>> print(bkgrms_value) # doctest: +FLOAT_CMP
-- 37.065055462640053
-+ 37.06505546264005
- """
-
- def calc_background_rms(self, data, axis=None):
-@@ -580,14 +580,14 @@
-
- >>> bkgrms_value = bkgrms.calc_background_rms(data)
- >>> print(bkgrms_value) # doctest: +FLOAT_CMP
-- 30.094338485893392
-+ 30.09433848589339
-
- Alternatively, the background RMS value can be calculated by calling
- the class instance as a function, e.g.:
-
- >>> bkgrms_value = bkgrms(data)
- >>> print(bkgrms_value) # doctest: +FLOAT_CMP
-- 30.094338485893392
-+ 30.09433848589339
- """
-
- def __init__(self, c=9.0, M=None, **kwargs):
-diff -Naur photutils-0.4/photutils/datasets/make.py photutils-0.4.fixed/photutils/datasets/make.py
---- photutils-0.4/photutils/datasets/make.py 2017-10-30 15:38:18.000000000 +0100
-+++ photutils-0.4.fixed/photutils/datasets/make.py 2018-02-14 03:56:07.063522619 +0100
-@@ -214,14 +214,16 @@
- >>> param_ranges = OrderedDict(param_ranges)
- >>> sources = make_random_models_table(n_sources, param_ranges,
- ... random_state=12345)
-+ >>> for col in sources.colnames:
-+ ... sources[col].info.format = '%.8g' # for consistent table output
- >>> print(sources)
-- amplitude x_mean y_mean ... y_stddev theta
-- ------------- ------------- ------------- ... ------------- --------------
-- 964.808046409 297.77235149 224.314442781 ... 3.56990131158 2.29238586176
-- 658.187777291 482.257259868 288.392020822 ... 3.86981448325 3.12278892062
-- 591.959405839 326.588548436 2.51648938247 ... 2.87039602888 2.12646148032
-- 602.280139277 374.453318767 31.9333130093 ... 2.30233871016 2.48444221236
-- 783.862514541 326.784935426 89.6111141308 ... 2.75857842354 0.536942976674
-+ amplitude x_mean y_mean x_stddev y_stddev theta
-+ --------- --------- --------- --------- --------- ----------
-+ 964.80805 297.77235 224.31444 3.6256447 3.5699013 2.2923859
-+ 658.18778 482.25726 288.39202 4.2392502 3.8698145 3.1227889
-+ 591.95941 326.58855 2.5164894 4.4887037 2.870396 2.1264615
-+ 602.28014 374.45332 31.933313 4.8585904 2.3023387 2.4844422
-+ 783.86251 326.78494 89.611114 3.8947414 2.7585784 0.53694298
- """
-
- prng = check_random_state(random_state)
-@@ -302,14 +304,16 @@
- >>> param_ranges = OrderedDict(param_ranges)
- >>> sources = make_random_gaussians_table(n_sources, param_ranges,
- ... random_state=12345)
-+ >>> for col in sources.colnames:
-+ ... sources[col].info.format = '%.8g' # for consistent table output
- >>> print(sources)
-- amplitude x_mean y_mean ... y_stddev theta
-- ------------- ------------- ------------- ... ------------- --------------
-- 964.808046409 297.77235149 224.314442781 ... 3.56990131158 2.29238586176
-- 658.187777291 482.257259868 288.392020822 ... 3.86981448325 3.12278892062
-- 591.959405839 326.588548436 2.51648938247 ... 2.87039602888 2.12646148032
-- 602.280139277 374.453318767 31.9333130093 ... 2.30233871016 2.48444221236
-- 783.862514541 326.784935426 89.6111141308 ... 2.75857842354 0.536942976674
-+ amplitude x_mean y_mean x_stddev y_stddev theta
-+ --------- --------- --------- --------- --------- ----------
-+ 964.80805 297.77235 224.31444 3.6256447 3.5699013 2.2923859
-+ 658.18778 482.25726 288.39202 4.2392502 3.8698145 3.1227889
-+ 591.95941 326.58855 2.5164894 4.4887037 2.870396 2.1264615
-+ 602.28014 374.45332 31.933313 4.8585904 2.3023387 2.4844422
-+ 783.86251 326.78494 89.611114 3.8947414 2.7585784 0.53694298
-
- To specifying the flux range instead of the amplitude range:
-
-@@ -322,14 +326,16 @@
- >>> param_ranges = OrderedDict(param_ranges)
- >>> sources = make_random_gaussians_table(n_sources, param_ranges,
- ... random_state=12345)
-+ >>> for col in sources.colnames:
-+ ... sources[col].info.format = '%.8g' # for consistent table output
- >>> print(sources)
-- flux x_mean y_mean ... theta amplitude
-- ------------- ------------- ------------- ... -------------- -------------
-- 964.808046409 297.77235149 224.314442781 ... 2.29238586176 11.8636845806
-- 658.187777291 482.257259868 288.392020822 ... 3.12278892062 6.38543882684
-- 591.959405839 326.588548436 2.51648938247 ... 2.12646148032 7.31222089567
-- 602.280139277 374.453318767 31.9333130093 ... 2.48444221236 8.56917814506
-- 783.862514541 326.784935426 89.6111141308 ... 0.536942976674 11.6117069638
-+ flux x_mean y_mean x_stddev y_stddev theta amplitude
-+ --------- --------- --------- --------- --------- ---------- ---------
-+ 964.80805 297.77235 224.31444 3.6256447 3.5699013 2.2923859 11.863685
-+ 658.18778 482.25726 288.39202 4.2392502 3.8698145 3.1227889 6.3854388
-+ 591.95941 326.58855 2.5164894 4.4887037 2.870396 2.1264615 7.3122209
-+ 602.28014 374.45332 31.933313 4.8585904 2.3023387 2.4844422 8.5691781
-+ 783.86251 326.78494 89.611114 3.8947414 2.7585784 0.53694298 11.611707
-
- Note that in this case the output table contains both a flux and
- amplitude column. The flux column will be ignored when generating
-@@ -694,10 +700,10 @@
- >>> from photutils.datasets import make_wcs
- >>> shape = (100, 100)
- >>> wcs = make_wcs(shape)
-- >>> print(wcs.wcs.crpix)
-- [ 50. 50.]
-- >>> print(wcs.wcs.crval)
-- [ 197.8925 -1.36555556]
-+ >>> print(wcs.wcs.crpix) # doctest: +FLOAT_CMP
-+ [50. 50.]
-+ >>> print(wcs.wcs.crval) # doctest: +FLOAT_CMP
-+ [197.8925 -1.36555556]
- """
-
- wcs = WCS(naxis=2)
-diff -Naur photutils-0.4/photutils/detection/tests/test_findstars.py photutils-0.4.fixed/photutils/detection/tests/test_findstars.py
---- photutils-0.4/photutils/detection/tests/test_findstars.py 2017-10-30 15:38:18.000000000 +0100
-+++ photutils-0.4.fixed/photutils/detection/tests/test_findstars.py 2018-02-14 03:56:07.061522588 +0100
-@@ -46,8 +46,10 @@
- '.txt'.format(threshold, fwhm))
- datafn = op.join(op.dirname(op.abspath(__file__)), 'data', datafn)
- t_ref = Table.read(datafn, format='ascii')
-- assert_allclose(np.array(t).astype(np.float),
-- np.array(t_ref).astype(np.float))
-+
-+ assert t.colnames == t_ref.colnames
-+ for col in t.colnames:
-+ assert_allclose(t[col], t_ref[col])
-
- def test_daofind_include_border(self):
- starfinder = DAOStarFinder(threshold=10, fwhm=2, sigma_radius=1.5,
-@@ -100,8 +102,10 @@
- '.txt'.format(threshold, fwhm))
- datafn = op.join(op.dirname(op.abspath(__file__)), 'data', datafn)
- t_ref = Table.read(datafn, format='ascii')
-- assert_allclose(np.array(t).astype(np.float),
-- np.array(t_ref).astype(np.float))
-+
-+ assert t.colnames == t_ref.colnames
-+ for col in t.colnames:
-+ assert_allclose(t[col], t_ref[col])
-
- def test_irafstarfind_nosources(self):
- data = np.ones((3, 3))
-diff -Naur photutils-0.4/photutils/segmentation/properties.py photutils-0.4.fixed/photutils/segmentation/properties.py
---- photutils-0.4/photutils/segmentation/properties.py 2017-10-30 15:38:18.000000000 +0100
-+++ photutils-0.4.fixed/photutils/segmentation/properties.py 2018-02-14 03:56:07.062522603 +0100
-@@ -1162,11 +1162,11 @@
- >>> import numpy as np
- >>> from photutils import SegmentationImage, source_properties
- >>> image = np.arange(16.).reshape(4, 4)
-- >>> print(image)
-- [[ 0. 1. 2. 3.]
-- [ 4. 5. 6. 7.]
-- [ 8. 9. 10. 11.]
-- [ 12. 13. 14. 15.]]
-+ >>> print(image) # doctest: +SKIP
-+ [[ 0. 1. 2. 3.]
-+ [ 4. 5. 6. 7.]
-+ [ 8. 9. 10. 11.]
-+ [12. 13. 14. 15.]]
- >>> segm = SegmentationImage([[1, 1, 0, 0],
- ... [1, 0, 0, 2],
- ... [0, 0, 2, 2],
-@@ -1179,11 +1179,11 @@
- >>> props[0].id # id corresponds to segment label number
- 1
- >>> props[0].centroid # doctest: +FLOAT_CMP
-- <Quantity [ 0.8, 0.2] pix>
-+ <Quantity [0.8, 0.2] pix>
- >>> props[0].source_sum # doctest: +FLOAT_CMP
- 5.0
- >>> props[0].area # doctest: +FLOAT_CMP
-- <Quantity 3.0 pix2>
-+ <Quantity 3. pix2>
- >>> props[0].max_value # doctest: +FLOAT_CMP
- 4.0
-
-@@ -1193,11 +1193,11 @@
- >>> props[1].id # id corresponds to segment label number
- 2
- >>> props[1].centroid # doctest: +FLOAT_CMP
-- <Quantity [ 2.36363636, 2.09090909] pix>
-+ <Quantity [2.36363636, 2.09090909] pix>
- >>> props[1].perimeter # doctest: +FLOAT_CMP
-- <Quantity 5.414213562373095 pix>
-+ <Quantity 5.41421356 pix>
- >>> props[1].orientation # doctest: +FLOAT_CMP
-- <Quantity -0.7417593069227176 rad>
-+ <Quantity -0.74175931 rad>
- """
-
- if not isinstance(segment_img, SegmentationImage):
-@@ -1412,11 +1412,11 @@
- >>> import numpy as np
- >>> from photutils import source_properties
- >>> image = np.arange(16.).reshape(4, 4)
-- >>> print(image)
-- [[ 0. 1. 2. 3.]
-- [ 4. 5. 6. 7.]
-- [ 8. 9. 10. 11.]
-- [ 12. 13. 14. 15.]]
-+ >>> print(image) # doctest: +SKIP
-+ [[ 0. 1. 2. 3.]
-+ [ 4. 5. 6. 7.]
-+ [ 8. 9. 10. 11.]
-+ [12. 13. 14. 15.]]
- >>> segm = SegmentationImage([[1, 1, 0, 0],
- ... [1, 0, 0, 2],
- ... [0, 0, 2, 2],
-diff -Naur photutils-0.4/photutils/utils/interpolation.py photutils-0.4.fixed/photutils/utils/interpolation.py
---- photutils-0.4/photutils/utils/interpolation.py 2017-10-30 17:14:28.000000000 +0100
-+++ photutils-0.4.fixed/photutils/utils/interpolation.py 2018-02-14 03:56:07.062522603 +0100
-@@ -95,15 +95,15 @@
- >>> f(0.4) # doctest: +FLOAT_CMP
- 0.38862424043228855
- >>> np.sin(0.4) # doctest: +FLOAT_CMP
-- 0.38941834230865052
-+ 0.3894183423086505
-
- >>> xi = np.random.random(4)
-- >>> xi
-- array([ 0.51312815, 0.66662455, 0.10590849, 0.13089495])
-- >>> f(xi) # doctest: +FLOAT_CMP
-- array([ 0.49086423, 0.62647862, 0.1056854 , 0.13048335])
-- >>> np.sin(xi)
-- array([ 0.49090493, 0.6183367 , 0.10571061, 0.13052149])
-+ >>> xi # doctest: +FLOAT_CMP
-+ array([0.51312815, 0.66662455, 0.10590849, 0.13089495])
-+ >>> f(xi) # doctest: +FLOAT_CMP
-+ array([0.49086423, 0.62647862, 0.1056854 , 0.13048335])
-+ >>> np.sin(xi) # doctest: +FLOAT_CMP
-+ array([0.49090493, 0.6183367 , 0.10571061, 0.13052149])
-
- NOTE: In the last example, ``xi`` may be a ``Nx1`` array instead of
- a 1D vector.
-@@ -113,10 +113,10 @@
- >>> pos = np.random.rand(1000, 2)
- >>> val = np.sin(pos[:, 0] + pos[:, 1])
- >>> f = idw(pos, val)
-- >>> f([0.5, 0.6]) # doctest: +FLOAT_CMP
-- 0.89312649587405657
-- >>> np.sin(0.5 + 0.6)
-- 0.89120736006143542
-+ >>> f([0.5, 0.6]) # doctest: +FLOAT_CMP
-+ 0.8931264958740567
-+ >>> np.sin(0.5 + 0.6) # doctest: +FLOAT_CMP
-+ 0.8912073600614354
- """
-
- def __init__(self, coordinates, values, weights=None, leafsize=10):
diff --git a/python-photutils.spec b/python-photutils.spec
index 2526a87..9e1e65c 100644
--- a/python-photutils.spec
+++ b/python-photutils.spec
@@ -1,8 +1,8 @@
%global srcname photutils
Name: python-%{srcname}
-Version: 0.5
-Release: 2%{?dist}
+Version: 0.6
+Release: 1%{?dist}
Summary: Astropy affiliated package for image photometry tasks
License: BSD
@@ -74,8 +74,7 @@ export XDG_CONFIG_HOME=`pwd`
export PYTHONDONTWRITEBYTECODE=1
pushd %{buildroot}/%{python3_sitearch}
-# Test test_outline_segments and TestDeblendSources fail as we don't have dask in Fedora
-py.test-%{python3_version} -k "not (test_outline_segments or TestDeblendSources)" %{srcname}
+py.test-%{python3_version} photutils
rm -rf .pytest_cache
popd
@@ -87,6 +86,9 @@ popd
%{python3_sitearch}/%{srcname}
%changelog
+* Sun Apr 28 2019 Christian Dersch <lupinix@mailbox.org> - 0.6-1
+- new version
+
* Sat Feb 02 2019 Fedora Release Engineering <releng@fedoraproject.org> - 0.5-2
- Rebuilt for https://fedoraproject.org/wiki/Fedora_30_Mass_Rebuild
diff --git a/sources b/sources
index a5ea80f..1fa952c 100644
--- a/sources
+++ b/sources
@@ -1 +1 @@
-SHA512 (photutils-0.5.tar.gz) = 2e9f233c623725abd7a8e3d991c2c065f7be09fda544c44c69149c6eb04df4ac1eef4cf0c837b1c159445f172da2fd29eafa127abe7bb229d6b0851a4dcf5b64
+SHA512 (photutils-0.6.tar.gz) = fb258814cd6ed1337e6f3f4054828b98fc450e1f82d045fcdc7bb2c53d14deb31aecf229bdf56560f9dc5d98042a87c14bbedd6ec1a5cb22c1d18f20b88082ec
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2026-06-26 3:41 [rpms/python-photutils] epel10: new version Christian Dersch
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