Coverage for python/lsst/ip/diffim/makeKernelBasisList.py : 5%

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1#
2# LSST Data Management System
3# Copyright 2008-2016 LSST Corporation.
4#
5# This product includes software developed by the
6# LSST Project (http://www.lsst.org/).
7#
8# This program is free software: you can redistribute it and/or modify
9# it under the terms of the GNU General Public License as published by
10# the Free Software Foundation, either version 3 of the License, or
11# (at your option) any later version.
12#
13# This program is distributed in the hope that it will be useful,
14# but WITHOUT ANY WARRANTY; without even the implied warranty of
15# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
16# GNU General Public License for more details.
17#
18# You should have received a copy of the LSST License Statement and
19# the GNU General Public License along with this program. If not,
20# see <http://www.lsstcorp.org/LegalNotices/>.
21#
23__all__ = ["makeKernelBasisList", "generateAlardLuptonBasisList"]
25from . import diffimLib
26from lsst.log import Log
27import numpy as np
29sigma2fwhm = 2. * np.sqrt(2. * np.log(2.))
32def makeKernelBasisList(config, targetFwhmPix=None, referenceFwhmPix=None,
33 basisDegGauss=None, metadata=None):
34 """Generate the delta function or Alard-Lupton kernel bases depending on the Config.
35 Wrapper to call either `lsst.ip.diffim.makeDeltaFunctionBasisList` or
36 `lsst.ip.diffim.generateAlardLuptonBasisList`.
38 Parameters
39 ----------
40 config : `lsst.ip.diffim.PsfMatchConfigAL`
41 Configuration object.
42 targetFwhmPix : `float`, optional
43 Passed on to `lsst.ip.diffim.generateAlardLuptonBasisList`.
44 Not used for delta function basis sets.
45 referenceFwhmPix : `float`, optional
46 Passed on to `lsst.ip.diffim.generateAlardLuptonBasisList`.
47 Not used for delta function basis sets.
48 basisDegGauss : `list` of `int`, optional
49 Passed on to `lsst.ip.diffim.generateAlardLuptonBasisList`.
50 Not used for delta function basis sets.
51 metadata : `lsst.daf.base.PropertySet`, optional
52 Passed on to `lsst.ip.diffim.generateAlardLuptonBasisList`.
53 Not used for delta function basis sets.
55 Returns
56 -------
57 basisList: `list` of `lsst.afw.math.kernel.FixedKernel`
58 List of basis kernels.
60 Notes
61 -----
62 See `lsst.ip.diffim.generateAlardLuptonBasisList` and
63 `lsst.ip.diffim.makeDeltaFunctionBasisList` for more information.
65 Raises
66 ------
67 ValueError
68 If ``config.kernelBasisSet`` has an invalid value (not "alard-lupton" or "delta-function").
69 """
70 if config.kernelBasisSet == "alard-lupton":
71 return generateAlardLuptonBasisList(config, targetFwhmPix=targetFwhmPix,
72 referenceFwhmPix=referenceFwhmPix,
73 basisDegGauss=basisDegGauss,
74 metadata=metadata)
75 elif config.kernelBasisSet == "delta-function":
76 kernelSize = config.kernelSize
77 return diffimLib.makeDeltaFunctionBasisList(kernelSize, kernelSize)
78 else:
79 raise ValueError("Cannot generate %s basis set" % (config.kernelBasisSet))
82def generateAlardLuptonBasisList(config, targetFwhmPix=None, referenceFwhmPix=None,
83 basisDegGauss=None, metadata=None):
84 """Generate an Alard-Lupton kernel basis list based upon the Config and
85 the input FWHM of the science and template images.
87 Parameters
88 ----------
89 config : `lsst.ip.diffim.PsfMatchConfigAL`
90 Configuration object for the Alard-Lupton algorithm.
91 targetFwhmPix : `float`, optional
92 Fwhm width (pixel) of the template exposure characteristic psf.
93 This is the _target_ that will be matched to the science exposure.
94 referenceFwhmPix : `float`, optional
95 Fwhm width (pixel) of the science exposure characteristic psf.
96 basisDegGauss : `list` of `int`, optional
97 Polynomial degree of each Gaussian (sigma) basis. If None, defaults to `config.alardDegGauss`.
98 metadata : `lsst.daf.base.PropertySet`, optional
99 If specified, object to collect metadata fields about the kernel basis list.
101 Returns
102 -------
103 basisList : `list` of `lsst.afw.math.kernel.FixedKernel`
104 List of basis kernels. For each degree value ``n`` in ``config.basisDegGauss`` (n+2)(n+1)/2 kernels
105 are generated and appended to the list in the order of the polynomial parameter number.
106 See `lsst.afw.math.polynomialFunction2D` documentation for more details.
108 Notes
109 -----
110 The polynomial functions (``f``) are always evaluated in the -1.0, +1.0 range in both x, y directions,
111 edge to edge, with ``f(0,0)`` evaluated at the kernel center pixel, ``f(-1.0,-1.0)`` at the kernel
112 ``(0,0)`` pixel. They are not scaled by the sigmas of the Gaussians.
114 Base Gaussian widths (sigmas in pixels) of the kernels are determined as:
115 - If not all fwhm parameters are provided or ``config.scaleByFwhm==False``
116 then ``config.alardNGauss`` and ``config.alardSigGauss`` are used.
117 - If ``targetFwhmPix<referenceFwhmPix`` (normal convolution):
118 First sigma ``Sig_K`` is determined to satisfy: ``Sig_reference**2 = Sig_target**2 + Sig_K**2``.
119 If it's larger than ``config.alardMinSig * config.alardGaussBeta``, make it the
120 second kernel. Else make it the smallest kernel, unless only 1 kernel is asked for.
121 - If ``referenceFwhmPix < targetFwhmPix`` (deconvolution):
122 Define the progression of Gaussians using a
123 method to derive a deconvolution sum-of-Gaussians from it's
124 convolution counterpart. [1]_ Only use 3 since the algorithm
125 assumes 3 components.
127 Metadata fields
128 ---------------
129 ALBasisNGauss : `int`
130 The number of base Gaussians in the AL basis functions.
131 ALBasisDegGauss : `list` of `int`
132 Polynomial order of spatial modification of the base Gaussian functions.
133 ALBasisSigGauss : `list` of `float`
134 Sigmas in pixels of the base Gaussians.
135 ALKernelSize : `int`
136 Kernel stamp size is (ALKernelSize pix, ALKernelSize pix).
137 ALBasisMode : `str`, either of ``config``, ``convolution``, ``deconvolution``
138 Indicates whether the config file values, the convolution or deconvolution algorithm
139 was used to determine the base Gaussian sigmas and the kernel stamp size.
141 References
142 ----------
144 .. [1] Ulmer, W.: Inverse problem of linear combinations of Gaussian convolution kernels
145 (deconvolution) and some applications to proton/photon dosimetry and image
146 processing. http://iopscience.iop.org/0266-5611/26/8/085002 Equation 40
148 Raises
149 ------
150 RuntimeError
151 - if ``config.kernelBasisSet`` is not equal to "alard-lupton"
152 ValueError
153 - if ``config.kernelSize`` is even
154 - if the number of Gaussians and the number of given
155 sigma values are not equal or
156 - if the number of Gaussians and the number of given
157 polynomial degree values are not equal
158 """
160 if config.kernelBasisSet != "alard-lupton":
161 raise RuntimeError("Cannot generate %s basis within generateAlardLuptonBasisList" %
162 config.kernelBasisSet)
164 kernelSize = config.kernelSize
165 fwhmScaling = config.kernelSizeFwhmScaling
166 basisNGauss = config.alardNGauss
167 basisSigmaGauss = config.alardSigGauss
168 basisGaussBeta = config.alardGaussBeta
169 basisMinSigma = config.alardMinSig
170 if basisDegGauss is None:
171 basisDegGauss = config.alardDegGauss
173 if len(basisDegGauss) != basisNGauss:
174 raise ValueError("len(basisDegGauss) != basisNGauss : %d vs %d" % (len(basisDegGauss), basisNGauss))
175 if len(basisSigmaGauss) != basisNGauss:
176 raise ValueError("len(basisSigmaGauss) != basisNGauss : %d vs %d" %
177 (len(basisSigmaGauss), basisNGauss))
178 if (kernelSize % 2) != 1:
179 raise ValueError("Only odd-sized Alard-Lupton bases allowed")
181 logger = Log.getLogger("ip.diffim.generateAlardLuptonBasisList")
182 if (targetFwhmPix is None) or (referenceFwhmPix is None) or (not config.scaleByFwhm):
183 logger.info("PSF sigmas are not available or scaling by fwhm disabled, "
184 "falling back to config values")
185 if metadata is not None:
186 metadata.add("ALBasisNGauss", basisNGauss)
187 metadata.add("ALBasisDegGauss", basisDegGauss)
188 metadata.add("ALBasisSigGauss", basisSigmaGauss)
189 metadata.add("ALKernelSize", kernelSize)
190 metadata.add("ALBasisMode", "config")
192 return diffimLib.makeAlardLuptonBasisList(kernelSize//2, basisNGauss, basisSigmaGauss, basisDegGauss)
194 targetSigma = targetFwhmPix / sigma2fwhm
195 referenceSigma = referenceFwhmPix / sigma2fwhm
196 logger.debug("Generating matching bases for sigma %.2f pix -> %.2f pix", targetSigma, referenceSigma)
198 # Modify the size of Alard Lupton kernels based upon the images FWHM
199 #
200 # Note the operation is : template.x.kernel = science
201 #
202 # Assuming the template and science image Psfs are Gaussians with
203 # the Fwhm above, Fwhm_T **2 + Fwhm_K **2 = Fwhm_S **2
204 #
205 if targetSigma == referenceSigma:
206 # Leave defaults as-is
207 logger.info("Target and reference psf fwhms are equal, falling back to config values")
208 basisMode = "config"
209 elif referenceSigma > targetSigma:
210 # Normal convolution
212 # First Gaussian has the sigma that comes from the convolution
213 # of two Gaussians : Sig_S**2 = Sig_T**2 + Sig_K**2
214 #
215 # If it's larger than basisMinSigma * basisGaussBeta, make it the
216 # second kernel. Else make it the smallest kernel. Unless
217 # only 1 kernel is asked for.
218 logger.info("Reference psf fwhm is the greater, normal convolution mode")
219 basisMode = "convolution"
220 kernelSigma = np.sqrt(referenceSigma**2 - targetSigma**2)
221 if kernelSigma < basisMinSigma:
222 kernelSigma = basisMinSigma
224 basisSigmaGauss = []
225 if basisNGauss == 1:
226 basisSigmaGauss.append(kernelSigma)
227 nAppended = 1
228 else:
229 if (kernelSigma/basisGaussBeta) > basisMinSigma:
230 basisSigmaGauss.append(kernelSigma/basisGaussBeta)
231 basisSigmaGauss.append(kernelSigma)
232 nAppended = 2
233 else:
234 basisSigmaGauss.append(kernelSigma)
235 nAppended = 1
237 # Any other Gaussians above basisNGauss=1 come from a scaling
238 # relationship: Sig_i+1 / Sig_i = basisGaussBeta
239 for i in range(nAppended, basisNGauss):
240 basisSigmaGauss.append(basisSigmaGauss[-1]*basisGaussBeta)
242 kernelSize = int(fwhmScaling * basisSigmaGauss[-1])
243 kernelSize += 0 if kernelSize%2 else 1 # Make sure it's odd
244 kernelSize = min(config.kernelSizeMax, max(kernelSize, config.kernelSizeMin))
246 else:
247 # Deconvolution; Define the progression of Gaussians using a
248 # method to derive a deconvolution sum-of-Gaussians from it's
249 # convolution counterpart. Only use 3 since the algorithm
250 # assumes 3 components.
251 #
252 # http://iopscience.iop.org/0266-5611/26/8/085002 Equation 40
254 # Use specializations for deconvolution
255 logger.info("Target psf fwhm is the greater, deconvolution mode")
256 basisMode = "deconvolution"
257 basisNGauss = config.alardNGaussDeconv
258 basisMinSigma = config.alardMinSigDeconv
260 kernelSigma = np.sqrt(targetSigma**2 - referenceSigma**2)
261 if kernelSigma < basisMinSigma:
262 kernelSigma = basisMinSigma
264 basisSigmaGauss = []
265 if (kernelSigma/basisGaussBeta) > basisMinSigma:
266 basisSigmaGauss.append(kernelSigma/basisGaussBeta)
267 basisSigmaGauss.append(kernelSigma)
268 nAppended = 2
269 else:
270 basisSigmaGauss.append(kernelSigma)
271 nAppended = 1
273 for i in range(nAppended, basisNGauss):
274 basisSigmaGauss.append(basisSigmaGauss[-1]*basisGaussBeta)
276 kernelSize = int(fwhmScaling * basisSigmaGauss[-1])
277 kernelSize += 0 if kernelSize%2 else 1 # Make sure it's odd
278 kernelSize = min(config.kernelSizeMax, max(kernelSize, config.kernelSizeMin))
280 # Now build a deconvolution set from these sigmas
281 sig0 = basisSigmaGauss[0]
282 sig1 = basisSigmaGauss[1]
283 sig2 = basisSigmaGauss[2]
284 basisSigmaGauss = []
285 for n in range(1, 3):
286 for j in range(n):
287 sigma2jn = (n - j)*sig1**2
288 sigma2jn += j * sig2**2
289 sigma2jn -= (n + 1)*sig0**2
290 sigmajn = np.sqrt(sigma2jn)
291 basisSigmaGauss.append(sigmajn)
293 basisSigmaGauss.sort()
294 basisNGauss = len(basisSigmaGauss)
295 basisDegGauss = [config.alardDegGaussDeconv for x in basisSigmaGauss]
297 if metadata is not None:
298 metadata.add("ALBasisNGauss", basisNGauss)
299 metadata.add("ALBasisDegGauss", basisDegGauss)
300 metadata.add("ALBasisSigGauss", basisSigmaGauss)
301 metadata.add("ALKernelSize", kernelSize)
302 metadata.add("ALBasisMode", basisMode)
304 logger.debug("basisSigmaGauss: %s basisDegGauss: %s",
305 ','.join(['{:.1f}'.format(v) for v in basisSigmaGauss]),
306 ','.join(['{:d}'.format(v) for v in basisDegGauss]))
308 return diffimLib.makeAlardLuptonBasisList(kernelSize//2, basisNGauss, basisSigmaGauss, basisDegGauss)