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_chebyshevBoundedField.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#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <https://www.gnu.org/licenses/>.
21
22import numpy as np
23
24from lsst.utils import continueClass
25from ._math import ChebyshevBoundedField, ChebyshevBoundedFieldControl
26
27__all__ = [] # import this module only for its side effects
28
29
30@continueClass
31class ChebyshevBoundedField: # noqa: F811
32 @classmethod
33 def approximate(cls, boundedField,
34 orderX=3, orderY=3,
35 nStepX=100, nStepY=100):
36 """
37 Approximate a bounded field as a ChebyshevBoundedField.
38
39 Parameters
40 ----------
41 boundedField : `lsst.afw.math.BoundedField`
42 A bounded field to approximate
43 orderX : `int`, optional
44 Order of the Chebyshev polynomial in the x direction.
45 Default is 3.
46 orderY : `int`, optional
47 Order of the Chebyshev polynomial in the y direction.
48 Default is 3.
49 nStepX : `int`, optional
50 Number of x steps to approximate boundedField.
51 Default is 100.
52 nStepY : `int`, optional
53 Number of y steps to approximate boundedField.
54 Default is 100.
55
56 Returns
57 -------
58 chebyshevBoundedField : `lsst.afw.math.ChebyshevBoundedField`
59 """
60
61 ctrl = ChebyshevBoundedFieldControl()
62 ctrl.orderX = orderX
63 ctrl.orderY = orderY
64 ctrl.triangular = False
65
66 bbox = boundedField.getBBox()
67
68 xSteps = np.linspace(bbox.getMinX(), bbox.getMaxX(), nStepX)
69 ySteps = np.linspace(bbox.getMinY(), bbox.getMaxY(), nStepY)
70
71 x = np.tile(xSteps, nStepY)
72 y = np.repeat(ySteps, nStepX)
73
74 return cls.fit(bbox, x, y, boundedField.evaluate(x, y), ctrl)
approximate(cls, boundedField, orderX=3, orderY=3, nStepX=100, nStepY=100)