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_spanSetContinued.py
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1# This file is part of afw.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (https://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19import numpy as np
20
21from . import SpanSet
22from lsst.utils import continueClass
23
24__all__ = []
25
26
27@continueClass
28class SpanSet: # noqa: F811
29 def asArray(self, shape=None, xy0=None):
30 """Convert a SpanSet into a numpy boolean array
31
32 Parameters
33 ----------
34 shape : `tuple` of `int`
35 The final shape of the output array.
36 If `shape` is `None` then the extent of the bounding box is used.
37 xy0 : `~lsst.geom.Box2I` or `tuple` of `int`
38 The lower-left corner of the array that will contain the spans.
39 If `xy0` is `None` then the origin of the bounding box is used.
40
41 Returns
42 -------
43 result : `numpy.ndarray`
44 The array with pixels contained in `spans` marked as `True`.
45 """
46 # prevent circular import
47 from lsst.afw.image import Mask
48
49 if shape is None and xy0 is None:
50 # It's slightly faster to set the array with the Mask instead of
51 # shifting the spans.
52 bbox = self.getBBox()
53 mask = Mask(bbox)
54 self.setMask(mask, 1)
55 result = mask.getArray().astype(bool)
56 else:
57 if shape is None:
58 # Use the shape of the full SpanSet
59 extent = self.getBBox().getDimensions()
60 shape = extent[1], extent[0]
61
62 if xy0 is None:
63 xy0 = self.getBBox().getMin()
64 offset = (-xy0[0], -xy0[1])
65
66 result = np.zeros(shape, dtype=bool)
67 yidx, xidx = self.shiftedBy(*offset).indices()
68 result[yidx, xidx] = 1
69 return result