Mercurial > repos > kls286 > chap_test_20230328
comparison CHAP/models/integration.py @ 0:cbbe42422d56 draft
planemo upload for repository https://github.com/CHESSComputing/ChessAnalysisPipeline/tree/galaxy commit 1401a7e1ae007a6bda260d147f9b879e789b73e0-dirty
author | kls286 |
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date | Tue, 28 Mar 2023 15:07:30 +0000 |
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1 import copy | |
2 from functools import cache, lru_cache | |
3 import json | |
4 import logging | |
5 import os | |
6 from time import time | |
7 from typing import Literal, Optional | |
8 | |
9 # from multiprocessing.pool import ThreadPool | |
10 # from nexusformat.nexus import (NXdata, | |
11 # NXdetector, | |
12 # NXfield, | |
13 # NXprocess, | |
14 # NXroot) | |
15 import numpy as np | |
16 from pydantic import (BaseModel, | |
17 validator, | |
18 constr, | |
19 conlist, | |
20 conint, | |
21 confloat, | |
22 FilePath) | |
23 #import pyFAI, pyFAI.multi_geometry, pyFAI.units | |
24 from pyFAI import load as pyfai_load | |
25 from pyFAI.multi_geometry import MultiGeometry | |
26 from pyFAI.units import AZIMUTHAL_UNITS, RADIAL_UNITS | |
27 #from pyspec.file.tiff import TiffFile | |
28 | |
29 #from .map import MapConfig, SpecScans | |
30 | |
31 | |
32 class Detector(BaseModel): | |
33 """ | |
34 Detector class to represent a single detector used in the experiment. | |
35 | |
36 :param prefix: Prefix of the detector in the SPEC file. | |
37 :type prefix: str | |
38 :param poni_file: Path to the poni file. | |
39 :type poni_file: str | |
40 :param mask_file: Optional path to the mask file. | |
41 :type mask_file: str, optional | |
42 """ | |
43 prefix: constr(strip_whitespace=True, min_length=1) | |
44 poni_file: FilePath | |
45 mask_file: Optional[FilePath] | |
46 @validator('poni_file', allow_reuse=True) | |
47 def validate_poni_file(cls, poni_file): | |
48 """ | |
49 Validate the poni file by checking if it's a valid PONI file. | |
50 | |
51 :param poni_file: Path to the poni file. | |
52 :type poni_file: str | |
53 :raises ValueError: If poni_file is not a valid PONI file. | |
54 :returns: Absolute path to the poni file. | |
55 :rtype: str | |
56 """ | |
57 poni_file = os.path.abspath(poni_file) | |
58 try: | |
59 ai = azimuthal_integrator(poni_file) | |
60 except: | |
61 raise(ValueError(f'{poni_file} is not a valid PONI file')) | |
62 else: | |
63 return(poni_file) | |
64 @validator('mask_file', allow_reuse=True) | |
65 def validate_mask_file(cls, mask_file, values): | |
66 """ | |
67 Validate the mask file. If a mask file is provided, it checks if it's a valid TIFF file. | |
68 | |
69 :param mask_file: Path to the mask file. | |
70 :type mask_file: str or None | |
71 :param values: A dictionary of the Detector fields. | |
72 :type values: dict | |
73 :raises ValueError: If mask_file is provided and it's not a valid TIFF file. | |
74 :raises ValueError: If `'poni_file'` is not provided in `values`. | |
75 :returns: Absolute path to the mask file or None. | |
76 :rtype: str or None | |
77 """ | |
78 if mask_file is None: | |
79 return(mask_file) | |
80 else: | |
81 mask_file = os.path.abspath(mask_file) | |
82 poni_file = values.get('poni_file') | |
83 if poni_file is None: | |
84 raise(ValueError('Cannot validate mask file without a PONI file.')) | |
85 else: | |
86 try: | |
87 mask_array = get_mask_array(mask_file, poni_file) | |
88 except BaseException as e: | |
89 raise(ValueError(f'Unable to open {mask_file} as a TIFF file')) | |
90 else: | |
91 return(mask_file) | |
92 @property | |
93 def azimuthal_integrator(self): | |
94 return(azimuthal_integrator(self.poni_file)) | |
95 @property | |
96 def mask_array(self): | |
97 return(get_mask_array(self.mask_file, self.poni_file)) | |
98 | |
99 @cache | |
100 def azimuthal_integrator(poni_file:str): | |
101 if not isinstance(poni_file, str): | |
102 poni_file = str(poni_file) | |
103 return(pyfai_load(poni_file)) | |
104 @cache | |
105 def get_mask_array(mask_file:str, poni_file:str): | |
106 if mask_file is not None: | |
107 if not isinstance(mask_file, str): | |
108 mask_file = str(mask_file) | |
109 | |
110 from pyspec.file.tiff import TiffFile | |
111 with TiffFile(mask_file) as tiff: | |
112 mask_array = tiff.asarray() | |
113 else: | |
114 mask_array = np.zeros(azimuthal_integrator(poni_file).detector.shape) | |
115 return(mask_array) | |
116 | |
117 class IntegrationConfig(BaseModel): | |
118 """ | |
119 Class representing the configuration for a raw detector data integration. | |
120 | |
121 :ivar tool_type: type of integration tool; always set to "integration" | |
122 :type tool_type: str, optional | |
123 :ivar title: title of the integration | |
124 :type title: str | |
125 :ivar integration_type: type of integration, one of "azimuthal", "radial", or "cake" | |
126 :type integration_type: str | |
127 :ivar detectors: list of detectors used in the integration | |
128 :type detectors: List[Detector] | |
129 :ivar radial_units: radial units for the integration, defaults to `'q_A^-1'` | |
130 :type radial_units: str, optional | |
131 :ivar radial_min: minimum radial value for the integration range | |
132 :type radial_min: float, optional | |
133 :ivar radial_max: maximum radial value for the integration range | |
134 :type radial_max: float, optional | |
135 :ivar radial_npt: number of points in the radial range for the integration | |
136 :type radial_npt: int, optional | |
137 :ivar azimuthal_units: azimuthal units for the integration | |
138 :type azimuthal_units: str, optional | |
139 :ivar azimuthal_min: minimum azimuthal value for the integration range | |
140 :type azimuthal_min: float, optional | |
141 :ivar azimuthal_max: maximum azimuthal value for the integration range | |
142 :type azimuthal_max: float, optional | |
143 :ivar azimuthal_npt: number of points in the azimuthal range for the integration | |
144 :type azimuthal_npt: int, optional | |
145 :ivar error_model: error model for the integration, one of "poisson" or "azimuthal" | |
146 :type error_model: str, optional | |
147 """ | |
148 tool_type: Literal['integration'] = 'integration' | |
149 title: constr(strip_whitespace=True, min_length=1) | |
150 integration_type: Literal['azimuthal', 'radial', 'cake'] | |
151 detectors: conlist(item_type=Detector, min_items=1) | |
152 radial_units: str = 'q_A^-1' | |
153 radial_min: confloat(ge=0) | |
154 radial_max: confloat(gt=0) | |
155 radial_npt: conint(gt=0) = 1800 | |
156 azimuthal_units: str = 'chi_deg' | |
157 azimuthal_min: confloat(ge=-180) = -180 | |
158 azimuthal_max: confloat(le=360) = 180 | |
159 azimuthal_npt: conint(gt=0) = 3600 | |
160 error_model: Optional[Literal['poisson', 'azimuthal']] | |
161 sequence_index: Optional[conint(gt=0)] | |
162 @validator('radial_units', allow_reuse=True) | |
163 def validate_radial_units(cls, radial_units): | |
164 """ | |
165 Validate the radial units for the integration. | |
166 | |
167 :param radial_units: unvalidated radial units for the integration | |
168 :type radial_units: str | |
169 :raises ValueError: if radial units are not one of the recognized radial units | |
170 :return: validated radial units | |
171 :rtype: str | |
172 """ | |
173 if radial_units in RADIAL_UNITS.keys(): | |
174 return(radial_units) | |
175 else: | |
176 raise(ValueError(f'Invalid radial units: {radial_units}. Must be one of {", ".join(RADIAL_UNITS.keys())}')) | |
177 @validator('azimuthal_units', allow_reuse=True) | |
178 def validate_azimuthal_units(cls, azimuthal_units): | |
179 """ | |
180 Validate that `azimuthal_units` is one of the keys in the | |
181 `pyFAI.units.AZIMUTHAL_UNITS` dictionary. | |
182 | |
183 :param azimuthal_units: The string representing the unit to be validated. | |
184 :type azimuthal_units: str | |
185 :raises ValueError: If `azimuthal_units` is not one of the keys in `pyFAI.units.AZIMUTHAL_UNITS` | |
186 :return: The original supplied value, if is one of the keys in `pyFAI.units.AZIMUTHAL_UNITS`. | |
187 :rtype: str | |
188 """ | |
189 if azimuthal_units in AZIMUTHAL_UNITS.keys(): | |
190 return(azimuthal_units) | |
191 else: | |
192 raise(ValueError(f'Invalid azimuthal units: {azimuthal_units}. Must be one of {", ".join(AZIMUTHAL_UNITS.keys())}')) | |
193 def validate_range_max(range_name:str): | |
194 """Validate the maximum value of an integration range. | |
195 | |
196 :param range_name: The name of the integration range (e.g. radial, azimuthal). | |
197 :type range_name: str | |
198 :return: The callable that performs the validation. | |
199 :rtype: callable | |
200 """ | |
201 def _validate_range_max(cls, range_max, values): | |
202 """Check if the maximum value of the integration range is greater than its minimum value. | |
203 | |
204 :param range_max: The maximum value of the integration range. | |
205 :type range_max: float | |
206 :param values: The values of the other fields being validated. | |
207 :type values: dict | |
208 :raises ValueError: If the maximum value of the integration range is not greater than its minimum value. | |
209 :return: The validated maximum range value | |
210 :rtype: float | |
211 """ | |
212 range_min = values.get(f'{range_name}_min') | |
213 if range_min < range_max: | |
214 return(range_max) | |
215 else: | |
216 raise(ValueError(f'Maximum value of integration range must be greater than minimum value of integration range ({range_name}_min={range_min}).')) | |
217 return(_validate_range_max) | |
218 _validate_radial_max = validator('radial_max', allow_reuse=True)(validate_range_max('radial')) | |
219 _validate_azimuthal_max = validator('azimuthal_max', allow_reuse=True)(validate_range_max('azimuthal')) | |
220 def validate_for_map_config(self, map_config:BaseModel): | |
221 """ | |
222 Validate the existence of the detector data file for all scan points in `map_config`. | |
223 | |
224 :param map_config: The `MapConfig` instance to validate against. | |
225 :type map_config: MapConfig | |
226 :raises RuntimeError: If a detector data file could not be found for a scan point occurring in `map_config`. | |
227 :return: None | |
228 :rtype: None | |
229 """ | |
230 for detector in self.detectors: | |
231 for scans in map_config.spec_scans: | |
232 for scan_number in scans.scan_numbers: | |
233 scanparser = scans.get_scanparser(scan_number) | |
234 for scan_step_index in range(scanparser.spec_scan_npts): | |
235 # Make sure the detector data file exists for all scan points | |
236 try: | |
237 detector_data_file = scanparser.get_detector_data_file(detector.prefix, scan_step_index) | |
238 except: | |
239 raise(RuntimeError(f'Could not find data file for detector prefix {detector.prefix} on scan number {scan_number} in spec file {scans.spec_file}')) | |
240 def get_azimuthal_adjustments(self): | |
241 """To enable a continuous range of integration in the azimuthal direction | |
242 for radial and cake integration, obtain adjusted values for this | |
243 `IntegrationConfig`'s `azimuthal_min` and `azimuthal_max` values, the | |
244 angle amount by which those values were adjusted, and the proper location | |
245 of the discontinuity in the azimuthal direction. | |
246 | |
247 :return: Adjusted chi_min, adjusted chi_max, chi_offset, chi_discontinuity | |
248 :rtype: tuple[float,float,float,float] | |
249 """ | |
250 return(get_azimuthal_adjustments(self.azimuthal_min, self.azimuthal_max)) | |
251 def get_azimuthal_integrators(self): | |
252 """Get a list of `AzimuthalIntegrator`s that correspond to the detector | |
253 configurations in this instance of `IntegrationConfig`. | |
254 | |
255 The returned `AzimuthalIntegrator`s are (if need be) artificially rotated | |
256 in the azimuthal direction to achieve a continuous range of integration | |
257 in the azimuthal direction. | |
258 | |
259 :returns: A list of `AzimuthalIntegrator`s appropriate for use by this | |
260 `IntegrationConfig` tool | |
261 :rtype: list[pyFAI.azimuthalIntegrator.AzimuthalIntegrator] | |
262 """ | |
263 chi_min, chi_max, chi_offset, chi_disc = self.get_azimuthal_adjustments() | |
264 return(get_azimuthal_integrators(tuple([detector.poni_file for detector in self.detectors]), chi_offset=chi_offset)) | |
265 def get_multi_geometry_integrator(self): | |
266 """Get a `MultiGeometry` integrator suitable for use by this instance of | |
267 `IntegrationConfig`. | |
268 | |
269 :return: A `MultiGeometry` integrator | |
270 :rtype: pyFAI.multi_geometry.MultiGeometry | |
271 """ | |
272 poni_files = tuple([detector.poni_file for detector in self.detectors]) | |
273 radial_range = (self.radial_min, self.radial_max) | |
274 azimuthal_range = (self.azimuthal_min, self.azimuthal_max) | |
275 return(get_multi_geometry_integrator(poni_files, self.radial_units, radial_range, azimuthal_range)) | |
276 def get_azimuthally_integrated_data(self, spec_scans:BaseModel, scan_number:int, scan_step_index:int): | |
277 """Return azimuthally-integrated data for the scan step specified. | |
278 | |
279 :param spec_scans: An instance of `SpecScans` containing the scan step requested. | |
280 :type spec_scans: SpecScans | |
281 :param scan_number: The number of the scan containing the scan step requested. | |
282 :type scan_number: int | |
283 :param scan_step_index: The index of the scan step requested. | |
284 :type scan_step_index: int | |
285 :return: A 1D array of azimuthally-integrated raw detector intensities. | |
286 :rtype: np.ndarray | |
287 """ | |
288 detector_data = spec_scans.get_detector_data(self.detectors, scan_number, scan_step_index) | |
289 integrator = self.get_multi_geometry_integrator() | |
290 lst_mask = [detector.mask_array for detector in self.detectors] | |
291 result = integrator.integrate1d(detector_data, lst_mask=lst_mask, npt=self.radial_npt, error_model=self.error_model) | |
292 if result.sigma is None: | |
293 return(result.intensity) | |
294 else: | |
295 return(result.intensity, result.sigma) | |
296 def get_radially_integrated_data(self, spec_scans:BaseModel, scan_number:int, scan_step_index:int): | |
297 """Return radially-integrated data for the scan step specified. | |
298 | |
299 :param spec_scans: An instance of `SpecScans` containing the scan step requested. | |
300 :type spec_scans: SpecScans | |
301 :param scan_number: The number of the scan containing the scan step requested. | |
302 :type scan_number: int | |
303 :param scan_step_index: The index of the scan step requested. | |
304 :type scan_step_index: int | |
305 :return: A 1D array of radially-integrated raw detector intensities. | |
306 :rtype: np.ndarray | |
307 """ | |
308 # Handle idiosyncracies of azimuthal ranges in pyFAI | |
309 # Adjust chi ranges to get a continuous range of iintegrated data | |
310 chi_min, chi_max, chi_offset, chi_disc = self.get_azimuthal_adjustments() | |
311 # Perform radial integration on a detector-by-detector basis. | |
312 I_each_detector = [] | |
313 variance_each_detector = [] | |
314 integrators = self.get_azimuthal_integrators() | |
315 for i,(integrator,detector) in enumerate(zip(integrators,self.detectors)): | |
316 detector_data = spec_scans.get_detector_data([detector], scan_number, scan_step_index)[0] | |
317 result = integrator.integrate_radial(detector_data, self.azimuthal_npt, | |
318 unit=self.azimuthal_units, azimuth_range=(chi_min,chi_max), | |
319 radial_unit=self.radial_units, radial_range=(self.radial_min,self.radial_max), | |
320 mask=detector.mask_array) #, error_model=self.error_model) | |
321 I_each_detector.append(result.intensity) | |
322 if result.sigma is not None: | |
323 variance_each_detector.append(result.sigma**2) | |
324 # Add the individual detectors' integrated intensities together | |
325 I = np.nansum(I_each_detector, axis=0) | |
326 # Ignore data at values of chi for which there was no data | |
327 I = np.where(I==0, np.nan, I) | |
328 if len(I_each_detector) != len(variance_each_detector): | |
329 return(I) | |
330 else: | |
331 # Get the standard deviation of the summed detectors' intensities | |
332 sigma = np.sqrt(np.nansum(variance_each_detector, axis=0)) | |
333 return(I, sigma) | |
334 def get_cake_integrated_data(self, spec_scans:BaseModel, scan_number:int, scan_step_index:int): | |
335 """Return cake-integrated data for the scan step specified. | |
336 | |
337 :param spec_scans: An instance of `SpecScans` containing the scan step requested. | |
338 :type spec_scans: SpecScans | |
339 :param scan_number: The number of the scan containing the scan step requested. | |
340 :type scan_number: int | |
341 :param scan_step_index: The index of the scan step requested. | |
342 :type scan_step_index: int | |
343 :return: A 2D array of cake-integrated raw detector intensities. | |
344 :rtype: np.ndarray | |
345 """ | |
346 detector_data = spec_scans.get_detector_data(self.detectors, scan_number, scan_step_index) | |
347 integrator = self.get_multi_geometry_integrator() | |
348 lst_mask = [detector.mask_array for detector in self.detectors] | |
349 result = integrator.integrate2d(detector_data, lst_mask=lst_mask, | |
350 npt_rad=self.radial_npt, npt_azim=self.azimuthal_npt, | |
351 method='bbox', | |
352 error_model=self.error_model) | |
353 if result.sigma is None: | |
354 return(result.intensity) | |
355 else: | |
356 return(result.intensity, result.sigma) | |
357 def get_integrated_data(self, spec_scans:BaseModel, scan_number:int, scan_step_index:int): | |
358 """Return integrated data for the scan step specified. | |
359 | |
360 :param spec_scans: An instance of `SpecScans` containing the scan step requested. | |
361 :type spec_scans: SpecScans | |
362 :param scan_number: The number of the scan containing the scan step requested. | |
363 :type scan_number: int | |
364 :param scan_step_index: The index of the scan step requested. | |
365 :type scan_step_index: int | |
366 :return: An array of integrated raw detector intensities. | |
367 :rtype: np.ndarray | |
368 """ | |
369 if self.integration_type == 'azimuthal': | |
370 return(self.get_azimuthally_integrated_data(spec_scans, scan_number, scan_step_index)) | |
371 elif self.integration_type == 'radial': | |
372 return(self.get_radially_integrated_data(spec_scans, scan_number, scan_step_index)) | |
373 elif self.integration_type == 'cake': | |
374 return(self.get_cake_integrated_data(spec_scans, scan_number, scan_step_index)) | |
375 | |
376 @property | |
377 def integrated_data_coordinates(self): | |
378 """ | |
379 Return a dictionary of coordinate arrays for navigating the dimension(s) | |
380 of the integrated data produced by this instance of `IntegrationConfig`. | |
381 | |
382 :return: A dictionary with either one or two keys: 'azimuthal' and/or | |
383 'radial', each of which points to a 1-D `numpy` array of coordinate | |
384 values. | |
385 :rtype: dict[str,np.ndarray] | |
386 """ | |
387 if self.integration_type == 'azimuthal': | |
388 return(get_integrated_data_coordinates(radial_range=(self.radial_min,self.radial_max), | |
389 radial_npt=self.radial_npt)) | |
390 elif self.integration_type == 'radial': | |
391 return(get_integrated_data_coordinates(azimuthal_range=(self.azimuthal_min,self.azimuthal_max), | |
392 azimuthal_npt=self.azimuthal_npt)) | |
393 elif self.integration_type == 'cake': | |
394 return(get_integrated_data_coordinates(radial_range=(self.radial_min,self.radial_max), | |
395 radial_npt=self.radial_npt, | |
396 azimuthal_range=(self.azimuthal_min,self.azimuthal_max), | |
397 azimuthal_npt=self.azimuthal_npt)) | |
398 @property | |
399 def integrated_data_dims(self): | |
400 """Return a tuple of the coordinate labels for the integrated data | |
401 produced by this instance of `IntegrationConfig`. | |
402 """ | |
403 directions = list(self.integrated_data_coordinates.keys()) | |
404 dim_names = [getattr(self, f'{direction}_units') for direction in directions] | |
405 return(dim_names) | |
406 @property | |
407 def integrated_data_shape(self): | |
408 """Return a tuple representing the shape of the integrated data | |
409 produced by this instance of `IntegrationConfig` for a single scan step. | |
410 """ | |
411 return(tuple([len(coordinate_values) for coordinate_name,coordinate_values in self.integrated_data_coordinates.items()])) | |
412 | |
413 @cache | |
414 def get_azimuthal_adjustments(chi_min:float, chi_max:float): | |
415 """ | |
416 Fix chi discontinuity at 180 degrees and return the adjusted chi range, | |
417 offset, and discontinuty. | |
418 | |
419 If the discontinuity is crossed, obtain the offset to artificially rotate | |
420 detectors to achieve a continuous azimuthal integration range. | |
421 | |
422 :param chi_min: The minimum value of the azimuthal range. | |
423 :type chi_min: float | |
424 :param chi_max: The maximum value of the azimuthal range. | |
425 :type chi_max: float | |
426 :return: The following four values: the adjusted minimum value of the | |
427 azimuthal range, the adjusted maximum value of the azimuthal range, the | |
428 value by which the chi angle was adjusted, the position of the chi | |
429 discontinuity. | |
430 """ | |
431 # Fix chi discontinuity at 180 degrees for now. | |
432 chi_disc = 180 | |
433 # If the discontinuity is crossed, artificially rotate the detectors to | |
434 # achieve a continuous azimuthal integration range | |
435 if chi_min < chi_disc and chi_max > chi_disc: | |
436 chi_offset = chi_max - chi_disc | |
437 else: | |
438 chi_offset = 0 | |
439 return(chi_min-chi_offset, chi_max-chi_offset, chi_offset, chi_disc) | |
440 @cache | |
441 def get_azimuthal_integrators(poni_files:tuple, chi_offset=0): | |
442 """ | |
443 Return a list of `AzimuthalIntegrator` objects generated from PONI files. | |
444 | |
445 :param poni_files: Tuple of strings, each string being a path to a PONI file. : tuple | |
446 :type poni_files: tuple | |
447 :param chi_offset: The angle in degrees by which the `AzimuthalIntegrator` objects will be rotated, defaults to 0. | |
448 :type chi_offset: float, optional | |
449 :return: List of `AzimuthalIntegrator` objects | |
450 :rtype: list[pyFAI.azimuthalIntegrator.AzimuthalIntegrator] | |
451 """ | |
452 ais = [] | |
453 for poni_file in poni_files: | |
454 ai = copy.deepcopy(azimuthal_integrator(poni_file)) | |
455 ai.rot3 += chi_offset * np.pi/180 | |
456 ais.append(ai) | |
457 return(ais) | |
458 @cache | |
459 def get_multi_geometry_integrator(poni_files:tuple, radial_unit:str, radial_range:tuple, azimuthal_range:tuple): | |
460 """Return a `MultiGeometry` instance that can be used for azimuthal or cake | |
461 integration. | |
462 | |
463 :param poni_files: Tuple of PONI files that describe the detectors to be | |
464 integrated. | |
465 :type poni_files: tuple | |
466 :param radial_unit: Unit to use for radial integration range. | |
467 :type radial_unit: str | |
468 :param radial_range: Tuple describing the range for radial integration. | |
469 :type radial_range: tuple[float,float] | |
470 :param azimuthal_range:Tuple describing the range for azimuthal integration. | |
471 :type azimuthal_range: tuple[float,float] | |
472 :return: `MultiGeometry` instance that can be used for azimuthal or cake | |
473 integration. | |
474 :rtype: pyFAI.multi_geometry.MultiGeometry | |
475 """ | |
476 chi_min, chi_max, chi_offset, chi_disc = get_azimuthal_adjustments(*azimuthal_range) | |
477 ais = copy.deepcopy(get_azimuthal_integrators(poni_files, chi_offset=chi_offset)) | |
478 multi_geometry = MultiGeometry(ais, | |
479 unit=radial_unit, | |
480 radial_range=radial_range, | |
481 azimuth_range=(chi_min,chi_max), | |
482 wavelength=sum([ai.wavelength for ai in ais])/len(ais), | |
483 chi_disc=chi_disc) | |
484 return(multi_geometry) | |
485 @cache | |
486 def get_integrated_data_coordinates(azimuthal_range:tuple=None, azimuthal_npt:int=None, radial_range:tuple=None, radial_npt:int=None): | |
487 """ | |
488 Return a dictionary of coordinate arrays for the specified radial and/or | |
489 azimuthal integration ranges. | |
490 | |
491 :param azimuthal_range: Tuple specifying the range of azimuthal angles over | |
492 which to generate coordinates, in the format (min, max), defaults to | |
493 None. | |
494 :type azimuthal_range: tuple[float,float], optional | |
495 :param azimuthal_npt: Number of azimuthal coordinate points to generate, | |
496 defaults to None. | |
497 :type azimuthal_npt: int, optional | |
498 :param radial_range: Tuple specifying the range of radial distances over | |
499 which to generate coordinates, in the format (min, max), defaults to | |
500 None. | |
501 :type radial_range: tuple[float,float], optional | |
502 :param radial_npt: Number of radial coordinate points to generate, defaults | |
503 to None. | |
504 :type radial_npt: int, optional | |
505 :return: A dictionary with either one or two keys: 'azimuthal' and/or | |
506 'radial', each of which points to a 1-D `numpy` array of coordinate | |
507 values. | |
508 :rtype: dict[str,np.ndarray] | |
509 """ | |
510 integrated_data_coordinates = {} | |
511 if azimuthal_range is not None and azimuthal_npt is not None: | |
512 integrated_data_coordinates['azimuthal'] = np.linspace(*azimuthal_range, azimuthal_npt) | |
513 if radial_range is not None and radial_npt is not None: | |
514 integrated_data_coordinates['radial'] = np.linspace(*radial_range, radial_npt) | |
515 return(integrated_data_coordinates) |