Coverage for python/lsst/meas/extensions/trailedSources/VeresPlugin.py: 31%
71 statements
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1#
2# This file is part of meas_extensions_trailedSources.
3#
4# Developed for the LSST Data Management System.
5# This product includes software developed by the LSST Project
6# (http://www.lsst.org).
7# See the COPYRIGHT file at the top-level directory of this distribution
8# for details of code ownership.
9#
10# This program is free software: you can redistribute it and/or modify
11# it under the terms of the GNU General Public License as published by
12# the Free Software Foundation, either version 3 of the License, or
13# (at your option) any later version.
14#
15# This program is distributed in the hope that it will be useful,
16# but WITHOUT ANY WARRANTY; without even the implied warranty of
17# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
18# GNU General Public License for more details.
19#
20# You should have received a copy of the GNU General Public License
21# along with this program. If not, see <http://www.gnu.org/licenses/>.
22#
24import numpy as np
25import scipy.optimize as sciOpt
27from lsst.pex.config import Field
29from lsst.meas.base.pluginRegistry import register
30from lsst.meas.base import SingleFramePlugin, SingleFramePluginConfig
31from lsst.meas.base import FlagHandler, FlagDefinitionList, SafeCentroidExtractor
32from lsst.meas.base import MeasurementError
34from ._trailedSources import VeresModel
35from .NaivePlugin import SingleFrameNaiveTrailPlugin
36from .utils import getMeasurementCutout
38__all__ = ("SingleFrameVeresTrailConfig", "SingleFrameVeresTrailPlugin")
41class SingleFrameVeresTrailConfig(SingleFramePluginConfig):
42 """Config class for SingleFrameVeresTrailPlugin
43 """
45 optimizerMethod = Field(
46 doc="Optimizer method for scipy.optimize.minimize",
47 dtype=str,
48 default="L-BFGS-B"
49 )
52@register("ext_trailedSources_Veres")
53class SingleFrameVeresTrailPlugin(SingleFramePlugin):
54 """Veres trailed source characterization plugin.
56 Measures the length, angle, flux, centroid, and end points of a trailed
57 source using the Veres et al. 2012 model [1]_.
59 Parameters
60 ----------
61 config: `SingleFrameNaiveTrailConfig`
62 Plugin configuration.
63 name: `str`
64 Plugin name.
65 schema: `lsst.afw.table.Schema`
66 Schema for the output catalog.
67 metadata: `lsst.daf.base.PropertySet`
68 Metadata to be attached to output catalog.
70 Notes
71 -----
72 This plugin is designed to refine the measurements of trail length,
73 angle, and end points from `NaivePlugin`, and of flux and centroid from
74 previous measurement algorithms. Vereš et al. 2012 [1]_ derive a model for
75 the flux in a given image pixel by convolving an axisymmetric Gaussian with
76 a line. The model is parameterized by the total flux, trail length, angle
77 from the x-axis, and the centroid. The best estimates are computed using a
78 chi-squared minimization.
80 References
81 ----------
82 .. [1] Vereš, P., et al. "Improved Asteroid Astrometry and Photometry with
83 Trail Fitting" PASP, vol. 124, 2012.
85 See also
86 --------
87 lsst.meas.base.SingleFramePlugin
88 """
90 ConfigClass = SingleFrameVeresTrailConfig
92 @classmethod
93 def getExecutionOrder(cls):
94 # Needs centroids, shape, flux, and NaivePlugin measurements.
95 # Make sure this always runs after NaivePlugin.
96 return SingleFrameNaiveTrailPlugin.getExecutionOrder() + 0.1
98 def __init__(self, config, name, schema, metadata):
99 super().__init__(config, name, schema, metadata)
101 self.keyXC = schema.addField(
102 name + "_centroid_x", type="D", doc="Trail centroid X coordinate.", units="pixel")
103 self.keyYC = schema.addField(
104 name + "_centroid_y", type="D", doc="Trail centroid Y coordinate.", units="pixel")
105 self.keyX0 = schema.addField(name + "_x0", type="D", doc="Trail head X coordinate.", units="pixel")
106 self.keyY0 = schema.addField(name + "_y0", type="D", doc="Trail head Y coordinate.", units="pixel")
107 self.keyX1 = schema.addField(name + "_x1", type="D", doc="Trail tail X coordinate.", units="pixel")
108 self.keyY1 = schema.addField(name + "_y1", type="D", doc="Trail tail Y coordinate.", units="pixel")
109 self.keyLength = schema.addField(name + "_length", type="D", doc="Length of trail.", units="pixel")
110 self.keyTheta = schema.addField(name + "_angle", type="D", doc="Angle of trail from +x-axis.")
111 self.keyFlux = schema.addField(name + "_flux", type="D", doc="Trailed source flux.", units="count")
112 self.keyRChiSq = schema.addField(name + "_rChiSq", type="D", doc="Reduced chi-squared of fit")
114 flagDefs = FlagDefinitionList()
115 flagDefs.addFailureFlag("No trailed-sources measured")
116 self.NON_CONVERGE = flagDefs.add("flag_nonConvergence", "Optimizer did not converge")
117 self.NO_NAIVE = flagDefs.add("flag_noNaive", "Naive measurement contains NaNs")
118 self.flagHandler = FlagHandler.addFields(schema, name, flagDefs)
120 self.centroidExtractor = SafeCentroidExtractor(schema, name)
122 def measure(self, measRecord, exposure):
123 """Run the Veres trailed source measurement plugin.
125 Parameters
126 ----------
127 measRecord : `lsst.afw.table.SourceRecord`
128 Record describing the object being measured.
129 exposure : `lsst.afw.image.Exposure`
130 Pixel data to be measured.
132 See also
133 --------
134 lsst.meas.base.SingleFramePlugin.measure
135 """
136 xc, yc = self.centroidExtractor(measRecord, self.flagHandler)
138 # Look at measRecord for Naive measurements
139 # ASSUMES NAIVE ALREADY RAN
140 flux = measRecord.get("ext_trailedSources_Naive_flux")
141 length = measRecord.get("ext_trailedSources_Naive_length")
142 theta = measRecord.get("ext_trailedSources_Naive_angle")
143 if not np.isfinite(flux) or not np.isfinite(length) or not np.isfinite(theta):
144 raise MeasurementError(self.NO_NAIVE.doc, self.NO_NAIVE.number)
146 # Get exposure cutout
147 # sigma = exposure.getPsf().getSigma()
148 # cutout = getMeasurementCutout(exposure, xc, yc, length, sigma)
149 cutout = getMeasurementCutout(measRecord, exposure)
151 # Make VeresModel
152 model = VeresModel(cutout)
154 # Do optimization with scipy
155 params = np.array([xc, yc, flux, length, theta])
156 results = sciOpt.minimize(
157 model, params, method=self.config.optimizerMethod, jac=model.gradient)
159 # Check if optimizer converged
160 if not results.success:
161 raise MeasurementError(self.NON_CONVERGE.doc, self.NON_CONVERGE.number)
163 # Calculate end points and reduced chi-squared
164 xc_fit, yc_fit, flux_fit, length_fit, theta_fit = results.x
165 a = length_fit/2
166 x0_fit = xc_fit - a * np.cos(theta_fit)
167 y0_fit = yc_fit - a * np.sin(theta_fit)
168 x1_fit = xc_fit + a * np.cos(theta_fit)
169 y1_fit = yc_fit + a * np.sin(theta_fit)
170 rChiSq = results.fun / (cutout.image.array.size - 6)
172 # Set keys
173 measRecord.set(self.keyXC, xc_fit)
174 measRecord.set(self.keyYC, yc_fit)
175 measRecord.set(self.keyX0, x0_fit)
176 measRecord.set(self.keyY0, y0_fit)
177 measRecord.set(self.keyX1, x1_fit)
178 measRecord.set(self.keyY1, y1_fit)
179 measRecord.set(self.keyFlux, flux_fit)
180 measRecord.set(self.keyLength, length_fit)
181 measRecord.set(self.keyTheta, theta_fit)
182 measRecord.set(self.keyRChiSq, rChiSq)
184 def fail(self, measRecord, error=None):
185 """Record failure
187 See also
188 --------
189 lsst.meas.base.SingleFramePlugin.fail
190 """
191 if error is None:
192 self.flagHandler.handleFailure(measRecord)
193 else:
194 self.flagHandler.handleFailure(measRecord, error.cpp)