Coverage for python/lsst/analysis/tools/actions/vector/calcMomentSize.py: 45%
25 statements
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1# This file is part of analysis_tools.
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/>.
21from __future__ import annotations
23__all__ = ("CalcMomentSize",)
25import numpy as np
26from lsst.pex.config import Field, FieldValidationError
27from lsst.pex.config.choiceField import ChoiceField
29from ...interfaces import KeyedData, KeyedDataSchema, Vector, VectorAction
32class CalcMomentSize(VectorAction):
33 r"""Calculate a size based on 2D moments.
35 Given a 2x2 matrix of moments (i.e. moment of inertia), two sizes can be
36 defined as follows:
38 Determinant radius: :math:`(I_{xx}I_{yy}-I_{xy}^2)^{\frac{1}{4}}`
39 Trace radius: :math:`\sqrt{(I_{xx}+I_{yy})/2}`
41 The square of size measure is typically expressed either as the arithmetic
42 mean of the eigenvalues of the moment matrix (trace radius) or as the
43 geometric mean of the eigenvalues (determinant radius), which can be
44 specified using the `sizeType` parameter. Both of these measures
45 correspond to the :math:`\sigma^2` parameter for a 2D Gaussian.
47 Notes
48 -----
49 Since lensing preserves surface brightness, the determinant radius relates
50 the magnification cleanly as it is derived from the area of isophotes, but
51 have a slightly higher chance of being NaNs for noisy moment estimates.
52 """
54 colXx = Field[str](
55 doc="The column name to get the xx shape component from.",
56 default="{band}_ixx",
57 )
59 colYy = Field[str](
60 doc="The column name to get the yy shape component from.",
61 default="{band}_iyy",
62 )
64 colXy = Field[str](
65 doc="The column name to get the xy shape component from.",
66 default="{band}_ixy",
67 optional=True,
68 )
70 sizeType = ChoiceField[str](
71 doc="The type of size to calculate",
72 default="determinant",
73 optional=False,
74 allowed={
75 "trace": r"Trace radius :math:`\sqrt{(I_{xx}+I_{yy})/2}`",
76 "determinant": r"Determinant radius :math:`(I_{xx}I_{yy}-I_{xy}^2)^{\frac{1}{4}}`",
77 },
78 )
80 def getInputSchema(self) -> KeyedDataSchema:
81 if self.sizeType == "trace":
82 return (
83 (self.colXx, Vector),
84 (self.colYy, Vector),
85 )
86 else:
87 return (
88 (self.colXx, Vector),
89 (self.colYy, Vector),
90 (self.colXy, Vector),
91 ) # type: ignore
93 def __call__(self, data: KeyedData, **kwargs) -> Vector:
94 if self.sizeType == "trace":
95 size = np.sqrt(
96 0.5 * (data[self.colXx.format(**kwargs)] + data[self.colYy.format(**kwargs)]) # type: ignore
97 )
98 else:
99 size = np.power(
100 data[self.colXx.format(**kwargs)] * data[self.colYy.format(**kwargs)] # type: ignore
101 - data[self.colXy.format(**kwargs)] ** 2, # type: ignore
102 0.25,
103 )
105 return size
107 def validate(self):
108 super().validate()
109 if self.sizeType == "determinant" and self.colXy is None:
110 msg = "colXy is required for determinant-type size"
111 raise FieldValidationError(self.__class__.colXy, self, msg)