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Merge pull request #1617 from larrybradley/grouper-1src
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Fix SourceGrouper with one source
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@larrybradley
larrybradley authored Sep 5, 2023
2 parents 6541831 + a3fd98f commit 55b2db0
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6 changes: 6 additions & 0 deletions CHANGES.rst
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Expand Up @@ -10,6 +10,12 @@ New Features
Bug Fixes
^^^^^^^^^

- ``photutils.psf``

- Fixed a bug where ``SourceGrouper`` would fail if only one source
was input. [#1617]


API Changes
^^^^^^^^^^^

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9 changes: 9 additions & 0 deletions photutils/psf/groupers.py
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Expand Up @@ -67,6 +67,15 @@ def _group_sources(self, x, y):
"""
from scipy.cluster.hierarchy import fclusterdata

x = np.atleast_1d(x)
y = np.atleast_1d(y)
if x.shape != y.shape:
raise ValueError('x and y must have the same shape')
if x.shape == (0,): # no sources
raise ValueError('x and y must not be empty')
if x.shape == (1,): # single source -> single group
return np.array([1])

xypos = np.transpose((x, y))
group_id = fclusterdata(xypos, t=self.min_separation,
criterion='distance')
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293 changes: 293 additions & 0 deletions photutils/psf/tests/test_groupers.py
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@@ -0,0 +1,293 @@
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
Tests for the grouper module.
"""

import numpy as np
import pytest
from numpy.testing import assert_equal

from photutils.psf.groupers import SourceGrouper
from photutils.utils._optional_deps import HAS_SCIPY


@pytest.mark.skipif(not HAS_SCIPY, reason='scipy is required')
def test_grouper_empty():
"""
Test case when there are no sources.
"""
xx = np.array([])
yy = np.array([])
grouper = SourceGrouper(min_separation=10)
match = 'x and y must not be empty'
with pytest.raises(ValueError, match=match):
grouper(xx, yy)


@pytest.mark.skipif(not HAS_SCIPY, reason='scipy is required')
def test_grouper_one_source():
"""
Test case when there is only one source.
"""
xx = np.array([0])
yy = np.array([0])
gg = np.array([1])
grouper = SourceGrouper(min_separation=10)
groups = grouper(xx, yy)
assert_equal(groups, gg)


@pytest.mark.skipif(not HAS_SCIPY, reason='scipy is required')
def test_grouper_inputs():
xx = np.array([1, 2, 3, 4])
yy = np.array([1, 2])
grouper = SourceGrouper(min_separation=10)
match = 'x and y must have the same shape'
with pytest.raises(ValueError, match=match):
grouper(xx, yy)


@pytest.mark.skipif(not HAS_SCIPY, reason='scipy is required')
def test_isolated_sources():
"""
Test case when all sources are isolated.
"""
xx = np.array([0, np.sqrt(2) / 4, np.sqrt(2) / 4, -np.sqrt(2) / 4,
-np.sqrt(2) / 4])
yy = np.array([0, np.sqrt(2) / 4, -np.sqrt(2) / 4, np.sqrt(2) / 4,
-np.sqrt(2) / 4])
gg = np.arange(len(xx), dtype=int) + 1
grouper = SourceGrouper(min_separation=0.01)
groups = grouper(xx, yy)
assert_equal(groups, gg)


@pytest.mark.skipif(not HAS_SCIPY, reason='scipy is required')
def test_grouper_one():
"""
+---------+--------+---------+---------+--------+---------+
| * * * * |
| |
0.2 + +
| |
| |
| |
0 + * * +
| |
| |
| |
-0.2 + +
| |
| * * * * |
+---------+--------+---------+---------+--------+---------+
0 0.5 1 1.5 2
x and y axis are in pixel coordinates. Each asterisk represents
the centroid of a star.
"""
x1 = np.array([0, np.sqrt(2) / 4, np.sqrt(2) / 4, -np.sqrt(2) / 4,
-np.sqrt(2) / 4])
y1 = np.array([0, np.sqrt(2) / 4, -np.sqrt(2) / 4, np.sqrt(2) / 4,
-np.sqrt(2) / 4])
g1 = np.ones(len(x1), dtype=int)
x2 = x1 + 2.0
y2 = y1
g2 = np.ones(len(x1), dtype=int) + 1

xx = np.hstack([x1, x2])
yy = np.hstack([y1, y2])
gg = np.hstack([g1, g2])
grouper = SourceGrouper(min_separation=0.6)
groups = grouper(xx, yy)
assert_equal(groups, gg)


@pytest.mark.skipif(not HAS_SCIPY, reason='scipy is required')
def test_grouper_two():
"""
+--------------+--------------+-------------+--------------+
3 + * +
| * |
2.5 + * +
| * |
2 + * +
| |
1.5 + +
| |
1 + * +
| * |
0.5 + * +
| * |
0 + * +
+--------------+--------------+-------------+--------------+
-1 -0.5 0 0.5 1
"""
x1 = np.zeros(5)
y1 = np.linspace(0, 1, 5)
g1 = np.ones(5, dtype=int)
x2 = np.zeros(5)
y2 = np.linspace(2, 3, 5)
g2 = np.ones(5, dtype=int) + 1

xx = np.hstack([x1, x2])
yy = np.hstack([y1, y2])
gg = np.hstack([g1, g2])
grouper = SourceGrouper(min_separation=0.3)
groups = grouper(xx, yy)
assert_equal(groups, gg)


@pytest.mark.skipif(not HAS_SCIPY, reason='scipy is required')
def test_grouper_three():
"""
1 +--+-------+--------+--------+--------+-------+--------+--+
| |
| |
| |
0.5 + +
| |
| |
0 + * * * * * * * * * * +
| |
| |
-0.5 + +
| |
| |
| |
-1 +--+-------+--------+--------+--------+-------+--------+--+
0 0.5 1 1.5 2 2.5 3
"""
x1 = np.linspace(0, 1, 5)
y1 = np.zeros(5)
g1 = np.ones(5, dtype=int)
x2 = np.linspace(2, 3, 5)
y2 = np.zeros(5)
g2 = np.ones(5, dtype=int) + 1

xx = np.hstack([x1, x2])
yy = np.hstack([y1, y2])
gg = np.hstack([g1, g2])
grouper = SourceGrouper(min_separation=0.3)
groups = grouper(xx, yy)
assert_equal(groups, gg)


@pytest.mark.skipif(not HAS_SCIPY, reason='scipy is required')
def test_grouper_four():
"""
+-+---------+---------+---------+---------+-+
1 + * +
| * * |
| |
| |
0.5 + +
| |
| |
| |
0 + * * +
| |
| |
-0.5 + +
| |
| |
| * * |
-1 + * +
+-+---------+---------+---------+---------+-+
-1 -0.5 0 0.5 1
"""
x = np.linspace(-1.0, 1.0, 5)
y = np.sqrt(1.0 - x**2)
xx = np.hstack((x, x))
yy = np.hstack((y, -y))
gg = np.ones(len(xx), dtype=int)

grouper = SourceGrouper(min_separation=2.5)
groups = grouper(xx, yy)
assert_equal(groups, gg)


@pytest.mark.skipif(not HAS_SCIPY, reason='scipy is required')
def test_grouper_five():
"""
+--+--------+--------+-------+--------+--------+--------+--+
3 + * +
| * |
2.5 + * +
| * |
2 + * +
| |
1.5 + * * * * * * * * * * +
| |
1 + * +
| * |
0.5 + * +
| * |
0 + * +
+--+--------+--------+-------+--------+--------+--------+--+
0 0.5 1 1.5 2 2.5 3
"""
x1 = 1.5 * np.ones(5)
y1 = np.linspace(0, 1, 5)
g1 = np.ones(5, dtype=int)

x2 = 1.5 * np.ones(5)
y2 = np.linspace(2, 3, 5)
g2 = np.ones(5, dtype=int) + 1

x3 = np.linspace(0, 1, 5)
y3 = 1.5 * np.ones(5)
g3 = np.ones(5, dtype=int) + 2

x4 = np.linspace(2, 3, 5)
y4 = 1.5 * np.ones(5)
g4 = np.ones(5, dtype=int) + 3

xx = np.hstack([x1, x2, x3, x4])
yy = np.hstack([y1, y2, y3, y4])
gg = np.hstack([g1, g2, g3, g4])

grouper = SourceGrouper(min_separation=0.3)
groups = grouper(xx, yy)
assert_equal(groups, gg)


@pytest.mark.skipif(not HAS_SCIPY, reason='scipy is required')
def test_grouper_six():
"""
+------+----------+----------+----------+----------+------+
| * * * * * * |
| |
0.2 + +
| |
| |
| |
0 + * * * +
| |
| |
| |
-0.2 + +
| |
| * * * * * * |
+------+----------+----------+----------+----------+------+
0 1 2 3 4
"""
x1 = np.array([0, np.sqrt(2) / 4, np.sqrt(2) / 4, -np.sqrt(2) / 4,
-np.sqrt(2) / 4])
y1 = np.array([0, np.sqrt(2) / 4, -np.sqrt(2) / 4, np.sqrt(2) / 4,
-np.sqrt(2) / 4])
g1 = np.ones(len(x1), dtype=int)

x2 = x1 + 2.0
y2 = y1
g2 = np.ones(len(x1), dtype=int) + 1

x3 = x1 + 4.0
y3 = y1
g3 = np.ones(len(x1), dtype=int) + 2

xx = np.hstack([x1, x2, x3])
yy = np.hstack([y1, y2, y3])
gg = np.hstack([g1, g2, g3])
grouper = SourceGrouper(min_separation=0.6)
groups = grouper(xx, yy)
assert_equal(groups, gg)

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