Coverage for python/lsst/obs/subaru/strayLight/yStrayLight.py: 18%
91 statements
« prev ^ index » next coverage.py v6.5.0, created at 2022-12-06 12:50 +0000
« prev ^ index » next coverage.py v6.5.0, created at 2022-12-06 12:50 +0000
1# Copyright (C) 2017 HSC Software Team
2# Copyright (C) 2017 Sogo Mineo
3#
4# This program is free software: you can redistribute it and/or modify
5# it under the terms of the GNU General Public License as published by
6# the Free Software Foundation, either version 3 of the License, or
7# (at your option) any later version.
8#
9# This program is distributed in the hope that it will be useful,
10# but WITHOUT ANY WARRANTY; without even the implied warranty of
11# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
12# GNU General Public License for more details.
13#
14# You should have received a copy of the GNU General Public License
15# along with this program. If not, see <http://www.gnu.org/licenses/>.
17__all__ = ["SubaruStrayLightTask"]
19import datetime
20from typing import Optional
22import numpy
23from astropy.io import fits
24import scipy.interpolate
26from lsst.geom import Angle, degrees
27from lsst.daf.butler import DeferredDatasetHandle
28from lsst.ip.isr.straylight import StrayLightConfig, StrayLightTask, StrayLightData
30from . import waveletCompression
31from .rotatorAngle import inrStartEnd
34BAD_THRESHOLD = 500 # Threshold for identifying bad pixels in the reconstructed dark image
37class SubaruStrayLightTask(StrayLightTask):
38 """Remove stray light in the y-band
40 LEDs in an encoder in HSC are producing stray light on the detectors,
41 producing the "Eye of Y-band" feature. It can be removed by
42 subtracting open-shutter darks. However, because the pattern of stray
43 light varies with rotator angle, many dark exposures are required.
44 To reduce the data volume for the darks, the images have been
45 compressed using wavelets. The code used to construct these is at:
47 https://hsc-gitlab.mtk.nao.ac.jp/sogo.mineo/ybackground/
49 This Task retrieves the appropriate dark, uncompresses it and
50 uses it to remove the stray light from an exposure.
51 """
53 ConfigClass = StrayLightConfig
55 def check(self, exposure):
56 # Docstring inherited from StrayLightTask.check.
57 detId = exposure.getDetector().getId()
58 if not self.checkFilter(exposure):
59 # No correction to be made
60 return False
61 if detId in range(104, 112):
62 # No correction data: assume it's zero
63 return False
64 if exposure.getInfo().getVisitInfo().getDate().toPython() >= datetime.datetime(2018, 1, 1):
65 # LEDs causing the stray light have been covered up.
66 # We believe there is no remaining stray light.
67 return False
69 return True
71 def run(self, exposure, strayLightData):
72 """Subtract the y-band stray light
74 This relies on knowing the instrument rotator angle during the
75 exposure. The FITS headers provide only the instrument rotator
76 angle at the start of the exposure (INR_STR), but better
77 stray light removal is obtained when we calculate the start and
78 end instrument rotator angles ourselves (config parameter
79 ``doRotatorAngleCorrection=True``).
81 Parameters
82 ----------
83 exposure : `lsst.afw.image.Exposure`
84 Exposure to correct.
85 strayLightData : `SubaruStrayLightData` or
86 `~lsst.daf.butler.DeferredDatasetHandle`
87 An opaque object that contains any calibration data used to
88 correct for stray light.
89 """
90 if not self.check(exposure):
91 return None
93 if strayLightData is None:
94 raise RuntimeError("No strayLightData supplied for correction.")
96 if isinstance(strayLightData, DeferredDatasetHandle):
97 # Get the deferred object.
98 strayLightData = strayLightData.get()
100 exposureMetadata = exposure.getMetadata()
101 detId = exposure.getDetector().getId()
102 if self.config.doRotatorAngleCorrection:
103 angleStart, angleEnd = inrStartEnd(exposure.getInfo().getVisitInfo())
104 self.log.debug(
105 "(INR-STR, INR-END) = (%g, %g) (FITS header says (%g, %g)).",
106 angleStart, angleEnd,
107 exposureMetadata.getDouble('INR-STR'), exposureMetadata.getDouble('INR-END')
108 )
109 else:
110 angleStart = exposureMetadata.getDouble('INR-STR')
111 angleEnd = None
113 self.log.info("Correcting y-band background.")
115 model = strayLightData.evaluate(angleStart*degrees,
116 None if angleStart == angleEnd else angleEnd*degrees)
118 # Some regions don't have useful model values because the amplifier is
119 # dead when the darks were taken
120 #
121 badAmps = {9: [0, 1, 2, 3], 33: [0, 1], 43: [0]} # Known bad amplifiers in the data: {ccdId: [ampId]}
122 if detId in badAmps:
123 isBad = numpy.zeros_like(model, dtype=bool)
124 for ii in badAmps[detId]:
125 amp = exposure.getDetector()[ii]
126 box = amp.getBBox()
127 isBad[box.getBeginY():box.getEndY(), box.getBeginX():box.getEndX()] = True
128 mask = exposure.getMaskedImage().getMask()
129 if numpy.all(isBad):
130 model[:] = 0.0
131 else:
132 model[isBad] = numpy.median(model[~isBad])
133 mask.array[isBad] |= mask.getPlaneBitMask("SUSPECT")
135 model *= exposure.getInfo().getVisitInfo().getExposureTime()
136 exposure.image.array -= model
139class SubaruStrayLightData(StrayLightData):
140 """Object that reads and integrates the wavelet-compressed
141 HSC y-band stray-light model.
143 Parameters
144 ----------
145 filename : `str`
146 Full path to a FITS files containing the stray-light model.
147 """
149 @classmethod
150 def readFits(cls, filename, **kwargs):
151 calib = cls()
153 with fits.open(filename) as hdulist:
154 calib.ampData = [hdu.data for hdu in hdulist]
155 calib.setMetadata(hdulist[0].header)
157 calib.log.info("Finished reading straylightData.")
158 return calib
160 def evaluate(self, angle_start: Angle, angle_end: Optional[Angle] = None):
161 """Get y-band background image array for a range of angles.
163 It is hypothesized that the instrument rotator rotates at a constant
164 angular velocity. This is not strictly true, but should be a
165 sufficient approximation for the relatively short exposure times
166 typical for HSC.
168 Parameters
169 ----------
170 angle_start : `float`
171 Instrument rotation angle in degrees at the start of the exposure.
172 angle_end : `float`, optional
173 Instrument rotation angle in degrees at the end of the exposure.
174 If not provided, the returned array will reflect a snapshot at
175 `angle_start`.
177 Returns
178 -------
179 ccd_img : `numpy.ndarray`
180 Background data for this exposure.
181 """
182 header = self.getMetadata()
184 # full-size ccd height & channel width
185 ccd_h, ch_w = header["F_NAXIS2"], header["F_NAXIS1"]
186 # saved data is compressed to 1/2**scale_level of the original size
187 image_scale_level = header["WTLEVEL2"], header["WTLEVEL1"]
188 angle_scale_level = header["WTLEVEL3"]
190 ccd_w = ch_w * len(self.ampData)
191 ccd_img = numpy.empty(shape=(ccd_h, ccd_w), dtype=numpy.float32)
193 for ch, hdu in enumerate(self.ampData):
194 volume = _upscale_volume(hdu, angle_scale_level)
196 if angle_end is None:
197 img = volume(angle_start.asDegrees())
198 else:
199 img = (volume.integrate(angle_start.asDegrees(), angle_end.asDegrees())
200 * (1.0 / (angle_end.asDegrees() - angle_start.asDegrees())))
202 ccd_img[:, ch_w*ch:ch_w*(ch+1)] = _upscale_image(img, (ccd_h, ch_w), image_scale_level)
204 # Some regions don't have useful values because the amplifier is dead
205 # when the darks were taken
206 # is_bad = ccd_img > BAD_THRESHOLD
207 # ccd_img[is_bad] = numpy.median(ccd_img[~is_bad])
209 return ccd_img
212def _upscale_image(img, target_shape, level):
213 """Upscale the given image to `target_shape` .
215 Parameters
216 ----------
217 img : `numpy.array`, (Nx, Ny)
218 Compressed image. ``img.shape`` must agree
219 with waveletCompression.scaled_size(target_shape, level)
220 target_shape : `tuple` [`int`, `int`]
221 The shape of upscaled image, which is to be returned.
222 level : `int` or `tuple` [`int`]
223 Level of multiresolution analysis (or synthesis)
225 Returns
226 -------
227 resized : `numpy.array`, (Nu, Nv)
228 Upscaled image with the ``target_shape``.
229 """
230 h, w = waveletCompression.scaled_size(target_shape, level)
232 large_img = numpy.zeros(shape=target_shape, dtype=float)
233 large_img[:h, :w] = img
235 return waveletCompression.icdf_9_7(large_img, level)
238def _upscale_volume(volume, level):
239 """Upscale the given volume (= sequence of images) along the 0-th
240 axis, and return an instance of a interpolation object that
241 interpolates the 0-th axis. The 0-th axis is the instrument
242 rotation.
244 Parameters
245 ----------
246 volume : `numpy.array`, (Nx, Ny, Nz)
247 Sequence of images.
248 level : `int`
249 Level of multiresolution analysis along the 0-th axis.
251 interpolator : callable
252 An object that returns a slice of the volume at a specific
253 angle (in degrees), with one positional argument:
255 - ``angle``: The angle in degrees.
256 """
257 angles = 720
258 _, h, w = volume.shape
260 large_volume = numpy.zeros(shape=(angles+1, h, w), dtype=float)
262 layers = waveletCompression.scaled_size(angles, level)
263 large_volume[:layers] = volume
265 large_volume[:-1] = waveletCompression.periodic_icdf_9_7_1d(large_volume[:-1], level, axis=0)
266 large_volume[-1] = large_volume[0]
268 x = numpy.arange(angles+1) / 2.0
269 return scipy.interpolate.CubicSpline(x, large_volume, axis=0, bc_type="periodic")