Coverage for python / lsst / ip / isr / shutterMotion.py: 9%
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1# This file is part of ip_isr.
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/>.
21"""
22Shutter motion profile storage class
23"""
25__all__ = ["ShutterMotionProfile", "ShutterMotionProfileFull"]
27from astropy.table import Table
28from scipy.optimize import newton
29import numpy as np
31from lsst.ip.isr import IsrCalib
34class ShutterMotionProfile(IsrCalib):
35 """Shutter motion profile measurements.
37 Parameters
38 ----------
39 log : `logging.Logger`, optional
40 Log to write messages to. If `None` a default logger will be used.
41 **kwargs :
42 Additional parameters.
43 """
45 _OBSTYPE = "shutterMotionProfile"
46 _SCHEMA = "ShutterMotionProfile"
47 _VERSION = 1.0
49 def __init__(self, **kwargs):
50 super().__init__(**kwargs)
52 # Quantities that come from `encodeSamples`
53 self.time_tai = []
54 self.time_mjd = []
55 self.position = []
56 self.hall_time_tai = []
57 self.hall_time_mjd = []
58 self.hall_position = []
59 self.hall_sensorId = []
60 self.hall_isOn = []
61 self.fit_name = []
62 self.fit_start_time = []
63 self.fit_pivot1 = []
64 self.fit_pivot2 = []
65 self.fit_jerk0 = []
66 self.fit_jerk1 = []
67 self.fit_jerk2 = []
69 self.requiredAttributes.update(["time_tai", "time_mjd", "position",
70 "hall_time_tai", "hall_time_mjd", "hall_position",
71 "hall_sensorId", "hall_isOn",
72 "fit_name", "fit_start_time", "fit_pivot1",
73 "fit_pivot2", "fit_jerk0", "fit_jerk1", "fit_jerk2",
74 ])
76 def calculateMidpoint(self, modelName="hallSensorFit", skipPosition=False):
77 """Calculate time of midpoint of travel for this profile.
79 Derived from Shuang Liang's CTN-002 (https://ctn-002.lsst.io).
80 Equation numbers listed are from this document. As the fits
81 have already been done, we can ignore the raw position/Hall
82 sensor data.
84 Parameters
85 ----------
86 modelName : `str`
87 Fit model to use to calculate the midpoint.
88 skipPosition : `bool`
89 If true, only the acceleration based calculation will be
90 done. If false, both the acceleration and position based
91 calculations are done.
93 Returns
94 -------
95 tm_accel : `float`
96 The time of the midpoint from the start of motion in
97 seconds, as derived from the point where the acceleration
98 on the shutter is zero.
99 tm_position : `float`
100 The time of the midpoint from the start of motion in
101 seconds, as derived from the point where the shutter
102 position is midway between its starting and ending
103 locations. This will be NaN if ``skipPosition`` is true.
105 Raises
106 ------
107 RuntimeError
108 Raised if the requested ``modelName`` is not found in the
109 calibration.
110 """
111 modelIndex = -1
112 for idx, name in enumerate(self.fit_name):
113 if name == modelName:
114 modelIndex = idx
115 if modelIndex == -1:
116 raise RuntimeError(f"Unknown model {modelName} requested.")
118 # Alias to follow technote
119 t0 = self.fit_start_time[modelIndex]
120 t1 = self.fit_pivot1[modelIndex]
121 t2 = self.fit_pivot2[modelIndex]
123 # Equation (3.1)
124 j0 = self.fit_jerk0[modelIndex]
125 j1 = self.fit_jerk1[modelIndex]
127 # Equation (3.2)
128 a1 = j0*t1
130 # Equation (3.4)
131 A1 = a1 - j1*t1
133 # First estimate of midpoint, where acceleration is zero.
134 # a = 0 = A1 + j1*t (Equation 5.1)
135 def acc(t):
136 return A1 + j1 * t
138 try:
139 tm_accel = newton(acc, 0.5*(t2 + t1))
140 except Exception as e:
141 self.log.warn(f"Midpoint calculation (from acceleration) failed to converge: {e}")
142 tm_accel = np.nan
144 if skipPosition:
145 tm_position = np.nan
146 else:
147 # Second estimate of midpoint, when s is halfway betweeen
148 # start and final position. Equation (5.2).
149 V1 = t1**2 * (j0 - j1)/2. - t1*A1
150 S1 = t1**3 * (j0 - j1)/6. - t1**2 * A1/2. - t1*V1
151 Smid = 0.5*(self.metadata["startPosition"] + self.metadata["endPosition"])
153 def pos(t):
154 return j1*(t**3)/6. + A1*(t**2)/2. + V1*t + S1 - Smid
156 try:
157 tm_position = newton(pos, tm_accel)
158 except Exception as e:
159 self.log.warn(f"Midpoint calculation (from position) failed to converge: {e}")
160 tm_position = np.nan
162 # Restore t0 so these can be compared to raw timestamps.
163 return tm_accel + t0, tm_position + t0
165 @classmethod
166 def fromExposure(cls, exposure, direction="open"):
167 """Construct a ShutterMotionProfile from an exposure.
169 Parameters
170 ----------
171 exposure : `lsst.afw.image.Exposuref`
172 Exposure to read header information from.
173 direction : `str`, optional
174 Direction of shutter to construcxt. Should be one of
175 "open" or "close".
177 Returns
178 -------
179 calib : `lsst.ip.isr.ShutterMotionProfile`
180 Constructed profile.
182 """
183 if direction not in ('open', 'close'):
184 raise ValueError(f"Unknown shutter direction {direction} suppled.")
186 keywords = [f'SHUTTER {direction.upper()} STARTTIME TAI ISOT',
187 f'SHUTTER {direction.upper()} STARTTIME TAI MJD',
188 f'SHUTTER {direction.upper()} SIDE',
189 f'SHUTTER {direction.upper()} MODEL',
190 f'SHUTTER {direction.upper()} HALLSENSORFIT MODELSTARTTIME',
191 f'SHUTTER {direction.upper()} HALLSENSORFIT PIVOTPOINT1',
192 f'SHUTTER {direction.upper()} HALLSENSORFIT PIVOTPOINT2',
193 f'SHUTTER {direction.upper()} HALLSENSORFIT JERK0',
194 f'SHUTTER {direction.upper()} HALLSENSORFIT JERK1',
195 f'SHUTTER {direction.upper()} HALLSENSORFIT JERK2']
197 for kw in keywords:
198 if kw not in exposure.metadata:
199 raise RuntimeError(f"Expected header keyword not found: {kw}.")
201 calib = cls()
202 calib.time_tai.append(exposure.metadata[f'SHUTTER {direction.upper()} STARTTIME TAI ISOT'])
203 calib.time_mjd.append(exposure.metadata[f'SHUTTER {direction.upper()} STARTTIME TAI MJD'])
204 calib.metadata['SIDE'] = exposure.metadata[f'SHUTTER {direction.upper()} SIDE']
206 calib.fit_name.append("hallSensorFit")
208 calib.fit_start_time.append(
209 exposure.metadata[f'SHUTTER {direction.upper()} HALLSENSORFIT MODELSTARTTIME']
210 )
211 calib.fit_pivot1.append(exposure.metadata[f'SHUTTER {direction.upper()} HALLSENSORFIT PIVOTPOINT1'])
212 calib.fit_pivot2.append(exposure.metadata[f'SHUTTER {direction.upper()} HALLSENSORFIT PIVOTPOINT2'])
213 calib.fit_jerk0.append(exposure.metadata[f'SHUTTER {direction.upper()} HALLSENSORFIT JERK0'])
214 calib.fit_jerk1.append(exposure.metadata[f'SHUTTER {direction.upper()} HALLSENSORFIT JERK1'])
215 calib.fit_jerk2.append(exposure.metadata[f'SHUTTER {direction.upper()} HALLSENSORFIT JERK2'])
217 return calib
219 @classmethod
220 def fromDict(cls, dictionary):
221 """Construct a ShutterMotionProfile from a dictionary of properties.
223 Parameters
224 ----------
225 dictionary : `dict`
226 Dictionary of properties.
228 Returns
229 -------
230 calib : `lsst.ip.isr.ShutterMotionProfile
231 Constructed calibration.
233 Raises
234 ------
235 RuntimeError
236 Raised if the supplied dictionary is for a different
237 calibration type.
238 """
239 calib = cls()
241 if calib._OBSTYPE != dictionary["fileType"]:
242 raise RuntimeError(f"Incorrect calibration supplied. Expected {calib._OBSTYPE}, "
243 f"found {dictionary['OBSTYPE']}")
244 motionProfile = dictionary.pop("motionProfile")
246 encodeSamples = motionProfile.pop("encodeSamples")
247 hallTransitions = motionProfile.pop("hallTransitions")
248 fitResults = motionProfile.pop("fitResults")
250 if "metadata" in dictionary:
251 metadata = dictionary.pop("metadata")
252 for key, value in metadata.items():
253 dictionary[key] = value
254 calib.setMetadata(dictionary)
256 formatVersion = calib.metadata["version"]
258 startTime = motionProfile.pop("startTime")
259 if formatVersion == 1.0:
260 # Original format.
261 motionProfile["startTime_tai"] = startTime["tai"]
262 motionProfile["startTime_mjd"] = startTime["mjd"]
263 else:
264 # Update to clarify all times are in the TAI system.
265 motionProfile["startTime_tai"] = startTime["tai"]["isot"]
266 motionProfile["startTime_mjd"] = startTime["tai"]["mjd"]
268 calib.readEncodeSamples(encodeSamples, formatVersion)
269 calib.readHallTransitions(hallTransitions, formatVersion)
270 calib.readFitResults(fitResults)
272 calib.updateMetadata(**motionProfile)
273 return calib
275 def toDict(self):
276 """Return a dictionary containing the calibration properties.
278 The dictionary should be able to be round-tripped through
279 `fromDict`.
281 Returns
282 -------
283 dictionary : `dict`
284 Dictionary of properties.
285 """
286 self.updateMetadata()
287 formatVersion = self.metadata["version"]
289 if formatVersion == 1.0:
290 outDict = {
291 "fileName": self.metadata["fileName"],
292 "fileType": self.metadata["fileType"],
293 "metadata": {
294 "CALIBCLS": "lsst.ip.isr.ShutterMotionProfile",
295 "OBSTYPE": self._OBSTYPE,
296 },
297 "obsId": self.metadata["obsId"],
298 "version": self.metadata.get("version", -1),
299 "motionProfile": {
300 "startTime": {
301 "tai": self.metadata["startTime_tai"],
302 "mjd": self.metadata["startTime_mjd"],
303 },
304 "startPosition": self.metadata["startPosition"],
305 "targetPosition": self.metadata["targetPosition"],
306 "endPosition": self.metadata["endPosition"],
307 "targetDuration": self.metadata["targetDuration"],
308 "actionDuration": self.metadata["actionDuration"],
309 "side": self.metadata["side"],
310 "isOpen": self.metadata["isOpen"],
311 "encodeSamples": self.writeEncodeSamples(),
312 "hallTransitions": self.writeHallTransitions(),
313 "fitResults": self.writeFitResults(),
314 },
315 }
316 elif formatVersion == 2.0:
317 outDict = {
318 "fileName": self.metadata["fileName"],
319 "fileType": self.metadata["fileType"],
320 "metadata": {
321 "CALIBCLS": "lsst.ip.isr.ShutterMotionProfile",
322 "OBSTYPE": self._OBSTYPE,
323 },
324 "obsId": self.metadata["obsId"],
325 "version": self.metadata.get("version", -1),
326 "motionProfile": {
327 "startTime": {
328 "tai": {
329 "isot": self.metadata["startTime_tai"],
330 "mjd": self.metadata["startTime_mjd"],
331 },
332 },
333 "startPosition": self.metadata["startPosition"],
334 "targetPosition": self.metadata["targetPosition"],
335 "endPosition": self.metadata["endPosition"],
336 "targetDuration": self.metadata["targetDuration"],
337 "actionDuration": self.metadata["actionDuration"],
338 "side": self.metadata["side"],
339 "isOpen": self.metadata["isOpen"],
340 "encodeSamples": self.writeEncodeSamples(),
341 "hallTransitions": self.writeHallTransitions(),
342 "fitResults": self.writeFitResults(),
343 },
344 }
345 else:
346 raise RuntimeError(f"Unknown file version: {formatVersion}")
347 return outDict
349 @classmethod
350 def fromTable(cls, tableList):
351 """Construct calibration from a list of tables.
353 This method uses the `fromDict` method to create the
354 calibration, after constructing an appropriate dictionary from
355 the input tables.
357 Parameters
358 ----------
359 tableList : `list` [`lsst.afw.table.Table`]
360 List of tables to use to construct the crosstalk
361 calibration. For shutter motion profiles, the first table
362 contains the samples, the second the Hall transition data,
363 and the third the model fits.
365 Returns
366 -------
367 calib : `lsst.ip.isr.ShutterMotionProfile`
368 The calibration defined in the tables.
369 """
370 samples = tableList[0]
371 transitions = tableList[1]
372 modelFits = tableList[2]
374 metadata = samples.meta
376 calib = cls()
377 calib.time_tai = np.squeeze(samples["TIME_TAI"].data).tolist()
378 if hasattr(calib.time_tai[0], "decode"):
379 calib.time_tai = [time.decode("utf-8") for time in calib.time_tai]
380 calib.time_mjd = np.squeeze(samples["TIME_MJD"].data).tolist()
381 calib.position = np.squeeze(samples["POSITION"].data).tolist()
383 calib.hall_time_tai = np.squeeze(transitions["HALL_TIME_TAI"].data).tolist()
384 if hasattr(calib.hall_time_tai[0], "decode"):
385 calib.hall_time_tai = [time.decode("utf-8") for time in calib.hall_time_tai]
386 calib.hall_time_mjd = np.squeeze(transitions["HALL_TIME_MJD"].data).tolist()
387 calib.hall_position = np.squeeze(transitions["HALL_POSITION"].data).tolist()
388 calib.hall_sensorId = np.squeeze(transitions["HALL_SENSORID"].data).tolist()
389 calib.hall_isOn = np.squeeze(transitions["HALL_ISON"].data).tolist()
391 calib.fit_model = modelFits.meta["FIT_MODEL"]
393 calib.fit_name = np.squeeze(modelFits["FIT_NAME"].data).tolist()
394 if hasattr(calib.fit_name[0], "decode"):
395 calib.fit_name = [fit.decode("utf-8") for fit in calib.fit_name]
396 calib.fit_start_time = np.squeeze(modelFits["FIT_START_TIME"].data).tolist()
397 calib.fit_pivot1 = np.squeeze(modelFits["FIT_PIVOT1"].data).tolist()
398 calib.fit_pivot2 = np.squeeze(modelFits["FIT_PIVOT2"].data).tolist()
399 calib.fit_jerk0 = np.squeeze(modelFits["FIT_JERK0"].data).tolist()
400 calib.fit_jerk1 = np.squeeze(modelFits["FIT_JERK1"].data).tolist()
401 calib.fit_jerk2 = np.squeeze(modelFits["FIT_JERK2"].data).tolist()
403 if "OBSTYPE" not in metadata:
404 metadata["OBSTYPE"] = cls._OBSTYPE
406 # This translation is needed to support correct
407 # round-tripping. It's not an elegant solution.
408 for key in ("fileName", "fileType", "obsId", "version", "side", "isOpen"):
409 if key.upper() in metadata:
410 value = metadata.pop(key.upper())
411 metadata[key] = value
412 for key in ("CALIB_ID", "DETECTOR", "DET_NAME", "DET_SER", "FILTER", "INSTRUME",
413 "RAFTNAME", "SEQCKSUM", "SEQFILE", "SEQNAME", "SLOTNAME"):
414 if key in metadata:
415 if metadata[key] == "":
416 metadata[key] = None
418 calib.updateMetadata(**metadata)
419 return calib
421 def toTable(self):
422 """Construct a list of tables containing the information in this
423 calibration.
425 The list of tables should create an identical calibration
426 after being passed to this class's fromTable method.
428 Returns
429 -------
430 tableList : `list` [`lsst.afw.table.Table`]
431 List of tables containing the shutter motion profile
432 information.
433 """
434 self.updateMetadata()
436 samples = Table(
437 {"TIME_TAI": np.array(self.time_tai).tolist(),
438 "TIME_MJD": np.array(self.time_mjd).tolist(),
439 "POSITION": np.array(self.position).tolist()},
440 names=("TIME_TAI", "TIME_MJD", "POSITION"),
441 dtype=("U32", "f8", "f8")
442 )
443 transitions = Table(
444 {"HALL_TIME_TAI": np.array(self.hall_time_tai).tolist(),
445 "HALL_TIME_MJD": np.array(self.hall_time_mjd).tolist(),
446 "HALL_POSITION": np.array(self.hall_position).tolist(),
447 "HALL_SENSORID": np.array(self.hall_sensorId).tolist(),
448 "HALL_ISON": np.array(self.hall_isOn).tolist()},
449 names=("HALL_TIME_TAI", "HALL_TIME_MJD", "HALL_POSITION",
450 "HALL_SENSORID", "HALL_ISON"),
451 dtype=("U32", "f8", "f8", "i4", "?")
452 )
453 modelFits = Table(
454 {"FIT_NAME": np.array(self.fit_name).tolist(),
455 "FIT_START_TIME": np.array(self.fit_start_time).tolist(),
456 "FIT_PIVOT1": np.array(self.fit_pivot1).tolist(),
457 "FIT_PIVOT2": np.array(self.fit_pivot2).tolist(),
458 "FIT_JERK0": np.array(self.fit_jerk0).tolist(),
459 "FIT_JERK1": np.array(self.fit_jerk1).tolist(),
460 "FIT_JERK2": np.array(self.fit_jerk2).tolist()},
461 names=("FIT_NAME", "FIT_START_TIME", "FIT_PIVOT1", "FIT_PIVOT2",
462 "FIT_JERK0", "FIT_JERK1", "FIT_JERK2"),
463 dtype=("U32", "f8", "f8", "f8", "f8", "f8", "f8")
464 )
465 modelFits.meta["FIT_MODEL"] = self.fit_model
467 inMeta = self.getMetadata().toDict()
468 outMeta = {k: v for k, v in inMeta.items() if v is not None}
469 outMeta.update({k: "" for k, v in inMeta.items() if v is None})
470 samples.meta = outMeta
472 return [samples, transitions, modelFits]
474 def readEncodeSamples(self, inputSamples, formatVersion):
475 """Read a list of input samples into the calibration.
477 Parameters
478 ----------
479 inputSamples : `list` [`dict` [`str` `str`]]
480 List of dictionaries of samples.
481 formatVersion : `float`
482 Version of the file format to read.
484 Raises
485 ------
486 RuntimeError
487 Raised if the calibration has already read samples, or if
488 the format is not known.
489 """
490 if len(self.time_tai) != 0:
491 raise RuntimeError("Cannot re-read already-read calibration.")
493 if formatVersion == 1.0:
494 for sample in inputSamples:
495 self.time_tai.append(sample["time"]["tai"])
496 self.time_mjd.append(sample["time"]["mjd"])
497 self.position.append(sample["position"])
498 elif formatVersion == 2.0:
499 for sample in inputSamples:
500 self.time_tai.append(sample["tai"]["isot"])
501 self.time_mjd.append(sample["tai"]["mjd"])
502 self.position.append(sample["position"])
503 else:
504 raise RuntimeError(f"Unknown file version: {formatVersion}")
506 def writeEncodeSamples(self):
507 """Return list of samples as dictionaries.
509 Returns
510 -------
511 inputSamples : `list` [`dict` [`str` `str`]]
512 List of dictionaries of samples.
514 Raises
515 ------
516 RuntimeError
517 Raised if the calibration has not read samples.
518 """
519 if len(self.time_tai) == 0:
520 raise RuntimeError("Cannot export empty calibration.")
522 formatVersion = self.metadata["version"]
524 samples = []
525 if formatVersion == 1.0:
526 for tai, mjd, position in zip(self.time_tai, self.time_mjd, self.position):
527 sample = {"time": {"tai": tai, "mjd": mjd},
528 "position": position}
529 samples.append(sample)
530 elif formatVersion == 2.0:
531 for tai, mjd, position in zip(self.time_tai, self.time_mjd, self.position):
532 sample = {"tai": {"isot": tai, "mjd": mjd},
533 "position": position}
534 samples.append(sample)
535 else:
536 raise RuntimeError(f"Unknown file version: {formatVersion}")
538 return samples
540 def readHallTransitions(self, inputTransitions, formatVersion):
541 """Read a list of input samples into the calibration.
543 Parameters
544 ----------
545 inputTransitions : `list` [`dict` [`str` `str`]]
546 List of dictionaries of transitions.
547 formatVersion : `float`
548 Version of the file format to read.
550 Raises
551 ------
552 RuntimeError
553 Raised if the calibration has already read samples, or if
554 the format is not known.
555 """
556 if len(self.hall_time_tai) != 0:
557 raise RuntimeError("Cannot re-read alreday-read calibration.")
559 if formatVersion == 1.0:
560 for transition in inputTransitions:
561 self.hall_time_tai.append(transition["time"]["tai"])
562 self.hall_time_mjd.append(transition["time"]["mjd"])
563 self.hall_position.append(transition["position"])
564 self.hall_sensorId.append(transition["sensorId"])
565 self.hall_isOn.append(bool(transition["isOn"]))
566 elif formatVersion == 2.0:
567 for transition in inputTransitions:
568 self.hall_time_tai.append(transition["tai"]["isot"])
569 self.hall_time_mjd.append(transition["tai"]["mjd"])
570 self.hall_position.append(transition["position"])
571 self.hall_sensorId.append(transition["sensorId"])
572 self.hall_isOn.append(bool(transition["isOn"]))
573 else:
574 raise RuntimeError(f"Unknown file version: {formatVersion}")
576 def writeHallTransitions(self):
577 """Return list of samples as dictionaries.
579 Returns
580 -------
581 inputTransitions : `list` [`dict` [`str` `str`]]
582 List of dictionaries of Hall transitions
584 Raises
585 ------
586 RuntimeError
587 Raised if the calibration has not read Hall
588 transitions.
589 """
590 if len(self.hall_time_tai) == 0:
591 raise RuntimeError("Cannot export empty calibration.")
593 formatVersion = self.metadata["version"]
594 if formatVersion not in (1.0, 2.0):
595 raise RuntimeError(f"Unknown file version: {formatVersion}")
596 transitions = []
598 for tai, mjd, position, sensorId, isOn in zip(
599 self.hall_time_tai,
600 self.hall_time_mjd,
601 self.hall_position,
602 self.hall_sensorId,
603 self.hall_isOn):
604 if formatVersion == 1.0:
605 transition = {"time": {"tai": tai, "mjd": mjd},
606 "position": position,
607 "sensorId": sensorId,
608 "isOn": isOn}
609 elif formatVersion == 2.0:
610 transition = {"tai": {"isot": tai, "mjd": mjd},
611 "position": position,
612 "sensorId": sensorId,
613 "isOn": isOn}
614 transitions.append(transition)
615 return transitions
617 def readFitResults(self, fitResults):
618 """Read a list of fit results into the calibration.
620 Parameters
621 ----------
622 inputTransitions : `list` [`dict` [`str` `str`]]
623 List of dictionaries of fit results.
625 Raises
626 ------
627 RuntimeError
628 Raised if the calibration has already read fit results.
629 """
630 if len(self.fit_name) != 0:
631 raise RuntimeError("Cannot re-read already-read fit results.")
632 self.fit_model = fitResults.pop("Model")
634 for fitName, fitModel in fitResults.items():
635 if hasattr(fitName, "decode"):
636 fitName = fitName.decode("utf-8")
637 self.fit_name.append(fitName)
638 self.fit_start_time.append(fitModel["ModelStartTime"])
639 self.fit_pivot1.append(fitModel["PivotPoint1"])
640 self.fit_pivot2.append(fitModel["PivotPoint2"])
641 self.fit_jerk0.append(fitModel["Jerk0"])
642 self.fit_jerk1.append(fitModel["Jerk1"])
643 self.fit_jerk2.append(fitModel["Jerk2"])
645 def writeFitResults(self):
646 """Return list of samples as dictionaries.
648 Returns
649 -------
650 inputTransitions : `list` [`dict` [`str` `str`]]
651 List of dictionaries of Hall transitions
653 Raises
654 ------
655 RuntimeError
656 Raised if the calibration has not read Hall
657 transitions.
658 """
659 if len(self.fit_name) == 0:
660 raise RuntimeError("Cannot export empty calibration.")
662 fitResults = {"Model": self.fit_model}
663 for fitName, startTime, pivot1, pivot2, jerk0, jerk1, jerk2 in zip(
664 self.fit_name, self.fit_start_time,
665 self.fit_pivot1, self.fit_pivot2,
666 self.fit_jerk0, self.fit_jerk1, self.fit_jerk2):
667 fitResults[fitName] = {"ModelStartTime": startTime,
668 "PivotPoint1": pivot1,
669 "PivotPoint2": pivot2,
670 "Jerk0": jerk0,
671 "Jerk1": jerk1,
672 "Jerk2": jerk2}
673 return fitResults
676class ShutterMotionProfileFull(IsrCalib):
677 """Class to hold both open and close profiles, as stored in the
678 exposure headers.
680 Parameters
681 ----------
682 log : `logging.Logger`, optional
683 Log to write messages to. If `None` a default logger will be used.
684 **kwargs :
685 Additional parameters.
686 """
687 _OBSTYPE = "shutterMotionProfileFull"
688 _SCHEMA = "ShutterMotionProfileFull"
689 _VERSION = 1.0
691 def __init__(self, **kwargs):
692 super().__init__(**kwargs)
694 self.profile_open = None
695 self.profile_close = None
697 self.requiredAttributes.update(["profile_open", "profile_close"])
699 @classmethod
700 def fromExposure(cls, exposure):
701 """Construct a ShutterMotionProfileFull from an exposure.
703 Parameters
704 ----------
705 exposure : `lsst.afw.image.Exposuref`
706 Exposure to read header information from.
707 direction : `str`, optional
708 Direction of shutter to construcxt. Should be one of
709 "open" or "close".
711 Returns
712 -------
713 calib : `lsst.ip.isr.ShutterMotionProfile`
714 Constructed profile.
715 """
716 calib = cls()
717 calib.profile_open = ShutterMotionProfile.fromExposure(exposure, direction="open")
718 calib.profile_close = ShutterMotionProfile.fromExposure(exposure, direction="close")
720 return calib
722 def calculateMidpoints(self):
723 # This is at least a start for downstream calculations.
724 midpoint_open, _ = self.profile_open.calculateMidpoint(skipPosition=True)
725 midpoint_close, _ = self.profile_close.calculateMidpoint(skipPosition=True)
727 return midpoint_open, midpoint_close