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 Raises
109 ------
110 RuntimeError
111 - if ``config.kernelBasisSet`` is not equal to "alard-lupton"
112 ValueError
113 - if ``config.kernelSize`` is even
114 - if the number of Gaussians and the number of given
115 sigma values are not equal or
116 - if the number of Gaussians and the number of given
117 polynomial degree values are not equal
119 Notes
120 -----
121 The polynomial functions (``f``) are always evaluated in the -1.0, +1.0 range in both x, y directions,
122 edge to edge, with ``f(0,0)`` evaluated at the kernel center pixel, ``f(-1.0,-1.0)`` at the kernel
123 ``(0,0)`` pixel. They are not scaled by the sigmas of the Gaussians.
125 Base Gaussian widths (sigmas in pixels) of the kernels are determined as:
126 - If not all fwhm parameters are provided or ``config.scaleByFwhm==False``
127 then ``config.alardNGauss`` and ``config.alardSigGauss`` are used.
128 - If ``targetFwhmPix<referenceFwhmPix`` (normal convolution):
129 First sigma ``Sig_K`` is determined to satisfy: ``Sig_reference**2 = Sig_target**2 + Sig_K**2``.
130 If it's larger than ``config.alardMinSig * config.alardGaussBeta``, make it the
131 second kernel. Else make it the smallest kernel, unless only 1 kernel is asked for.
132 - If ``referenceFwhmPix < targetFwhmPix`` (deconvolution):
133 Define the progression of Gaussians using a
134 method to derive a deconvolution sum-of-Gaussians from it's
135 convolution counterpart. [1]_ Only use 3 since the algorithm
136 assumes 3 components.
138 **Metadata fields**
140 ALBasisNGauss : `int`
141 The number of base Gaussians in the AL basis functions.
142 ALBasisDegGauss : `list` of `int`
143 Polynomial order of spatial modification of the base Gaussian functions.
144 ALBasisSigGauss : `list` of `float`
145 Sigmas in pixels of the base Gaussians.
146 ALKernelSize : `int`
147 Kernel stamp size is (ALKernelSize pix, ALKernelSize pix).
148 ALBasisMode : `str`, either of ``config``, ``convolution``, ``deconvolution``
149 Indicates whether the config file values, the convolution or deconvolution algorithm
150 was used to determine the base Gaussian sigmas and the kernel stamp size.
152 References
153 ----------
154 .. [1] Ulmer, W.: Inverse problem of linear combinations of Gaussian convolution kernels
155 (deconvolution) and some applications to proton/photon dosimetry and image
156 processing. http://iopscience.iop.org/0266-5611/26/8/085002 Equation 40
157 """
159 if config.kernelBasisSet != "alard-lupton":
160 raise RuntimeError("Cannot generate %s basis within generateAlardLuptonBasisList" %
161 config.kernelBasisSet)
163 kernelSize = config.kernelSize
164 fwhmScaling = config.kernelSizeFwhmScaling
165 basisNGauss = config.alardNGauss
166 basisSigmaGauss = config.alardSigGauss
167 basisGaussBeta = config.alardGaussBeta
168 basisMinSigma = config.alardMinSig
169 if basisDegGauss is None:
170 basisDegGauss = config.alardDegGauss
172 if len(basisDegGauss) != basisNGauss:
173 raise ValueError("len(basisDegGauss) != basisNGauss : %d vs %d" % (len(basisDegGauss), basisNGauss))
174 if len(basisSigmaGauss) != basisNGauss:
175 raise ValueError("len(basisSigmaGauss) != basisNGauss : %d vs %d" %
176 (len(basisSigmaGauss), basisNGauss))
177 if (kernelSize % 2) != 1:
178 raise ValueError("Only odd-sized Alard-Lupton bases allowed")
180 logger = Log.getLogger("ip.diffim.generateAlardLuptonBasisList")
181 if (targetFwhmPix is None) or (referenceFwhmPix is None) or (not config.scaleByFwhm):
182 logger.info("PSF sigmas are not available or scaling by fwhm disabled, "
183 "falling back to config values")
184 if metadata is not None:
185 metadata.add("ALBasisNGauss", basisNGauss)
186 metadata.add("ALBasisDegGauss", basisDegGauss)
187 metadata.add("ALBasisSigGauss", basisSigmaGauss)
188 metadata.add("ALKernelSize", kernelSize)
189 metadata.add("ALBasisMode", "config")
191 return diffimLib.makeAlardLuptonBasisList(kernelSize//2, basisNGauss, basisSigmaGauss, basisDegGauss)
193 targetSigma = targetFwhmPix / sigma2fwhm
194 referenceSigma = referenceFwhmPix / sigma2fwhm
195 logger.debug("Generating matching bases for sigma %.2f pix -> %.2f pix", targetSigma, referenceSigma)
197 # Modify the size of Alard Lupton kernels based upon the images FWHM
198 #
199 # Note the operation is : template.x.kernel = science
200 #
201 # Assuming the template and science image Psfs are Gaussians with
202 # the Fwhm above, Fwhm_T **2 + Fwhm_K **2 = Fwhm_S **2
203 #
204 if targetSigma == referenceSigma:
205 # Leave defaults as-is
206 logger.info("Target and reference psf fwhms are equal, falling back to config values")
207 basisMode = "config"
208 elif referenceSigma > targetSigma:
209 # Normal convolution
211 # First Gaussian has the sigma that comes from the convolution
212 # of two Gaussians : Sig_S**2 = Sig_T**2 + Sig_K**2
213 #
214 # If it's larger than basisMinSigma * basisGaussBeta, make it the
215 # second kernel. Else make it the smallest kernel. Unless
216 # only 1 kernel is asked for.
217 logger.info("Reference psf fwhm is the greater, normal convolution mode")
218 basisMode = "convolution"
219 kernelSigma = np.sqrt(referenceSigma**2 - targetSigma**2)
220 if kernelSigma < basisMinSigma:
221 kernelSigma = basisMinSigma
223 basisSigmaGauss = []
224 if basisNGauss == 1:
225 basisSigmaGauss.append(kernelSigma)
226 nAppended = 1
227 else:
228 if (kernelSigma/basisGaussBeta) > basisMinSigma:
229 basisSigmaGauss.append(kernelSigma/basisGaussBeta)
230 basisSigmaGauss.append(kernelSigma)
231 nAppended = 2
232 else:
233 basisSigmaGauss.append(kernelSigma)
234 nAppended = 1
236 # Any other Gaussians above basisNGauss=1 come from a scaling
237 # relationship: Sig_i+1 / Sig_i = basisGaussBeta
238 for i in range(nAppended, basisNGauss):
239 basisSigmaGauss.append(basisSigmaGauss[-1]*basisGaussBeta)
241 kernelSize = int(fwhmScaling * basisSigmaGauss[-1])
242 kernelSize += 0 if kernelSize%2 else 1 # Make sure it's odd
243 kernelSize = min(config.kernelSizeMax, max(kernelSize, config.kernelSizeMin))
245 else:
246 # Deconvolution; Define the progression of Gaussians using a
247 # method to derive a deconvolution sum-of-Gaussians from it's
248 # convolution counterpart. Only use 3 since the algorithm
249 # assumes 3 components.
250 #
251 # http://iopscience.iop.org/0266-5611/26/8/085002 Equation 40
253 # Use specializations for deconvolution
254 logger.info("Target psf fwhm is the greater, deconvolution mode")
255 basisMode = "deconvolution"
256 basisNGauss = config.alardNGaussDeconv
257 basisMinSigma = config.alardMinSigDeconv
259 kernelSigma = np.sqrt(targetSigma**2 - referenceSigma**2)
260 if kernelSigma < basisMinSigma:
261 kernelSigma = basisMinSigma
263 basisSigmaGauss = []
264 if (kernelSigma/basisGaussBeta) > basisMinSigma:
265 basisSigmaGauss.append(kernelSigma/basisGaussBeta)
266 basisSigmaGauss.append(kernelSigma)
267 nAppended = 2
268 else:
269 basisSigmaGauss.append(kernelSigma)
270 nAppended = 1
272 for i in range(nAppended, basisNGauss):
273 basisSigmaGauss.append(basisSigmaGauss[-1]*basisGaussBeta)
275 kernelSize = int(fwhmScaling * basisSigmaGauss[-1])
276 kernelSize += 0 if kernelSize%2 else 1 # Make sure it's odd
277 kernelSize = min(config.kernelSizeMax, max(kernelSize, config.kernelSizeMin))
279 # Now build a deconvolution set from these sigmas
280 sig0 = basisSigmaGauss[0]
281 sig1 = basisSigmaGauss[1]
282 sig2 = basisSigmaGauss[2]
283 basisSigmaGauss = []
284 for n in range(1, 3):
285 for j in range(n):
286 sigma2jn = (n - j)*sig1**2
287 sigma2jn += j * sig2**2
288 sigma2jn -= (n + 1)*sig0**2
289 sigmajn = np.sqrt(sigma2jn)
290 basisSigmaGauss.append(sigmajn)
292 basisSigmaGauss.sort()
293 basisNGauss = len(basisSigmaGauss)
294 basisDegGauss = [config.alardDegGaussDeconv for x in basisSigmaGauss]
296 if metadata is not None:
297 metadata.add("ALBasisNGauss", basisNGauss)
298 metadata.add("ALBasisDegGauss", basisDegGauss)
299 metadata.add("ALBasisSigGauss", basisSigmaGauss)
300 metadata.add("ALKernelSize", kernelSize)
301 metadata.add("ALBasisMode", basisMode)
303 logger.debug("basisSigmaGauss: %s basisDegGauss: %s",
304 ','.join(['{:.1f}'.format(v) for v in basisSigmaGauss]),
305 ','.join(['{:d}'.format(v) for v in basisDegGauss]))
307 return diffimLib.makeAlardLuptonBasisList(kernelSize//2, basisNGauss, basisSigmaGauss, basisDegGauss)