Coverage for colour/io/uprtek_sekonic.py: 100%
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1"""
2UPRTek and Sekonic Spectral Data
3================================
5Define input and output objects for parsing and handling *UPRTek* and
6*Sekonic* spectral measurement data stored in *Pseudo-XLS* and *CSV* file
7formats.
9- :class:`colour.SpectralDistribution_UPRTek`
10- :class:`colour.SpectralDistribution_Sekonic`
11"""
13from __future__ import annotations
15import csv
16import json
17import os
18import re
19import typing
20from collections import defaultdict
22if typing.TYPE_CHECKING:
23 from colour.hints import Any, PathLike
25from colour.hints import cast
26from colour.io import SpectralDistribution_IESTM2714
27from colour.utilities import as_float_array, as_float_scalar
29__author__ = "Colour Developers"
30__copyright__ = "Copyright 2013 Colour Developers"
31__license__ = "BSD-3-Clause - https://opensource.org/licenses/BSD-3-Clause"
32__maintainer__ = "Colour Developers"
33__email__ = "colour-developers@colour-science.org"
34__status__ = "Production"
36__all__ = [
37 "SpectralDistribution_UPRTek",
38 "SpectralDistribution_Sekonic",
39]
42class SpectralDistribution_UPRTek(SpectralDistribution_IESTM2714):
43 """
44 Implement support to read and write *IES TM-27-14* spectral data XML
45 files from *UPRTek* *Pseudo-XLS* files.
47 This class extends :class:`SpectralDistribution_IESTM2714` to handle
48 the specific *Pseudo-XLS* format used by *UPRTek* spectral measurement
49 devices. The implementation parses metadata embedded in the file and
50 converts it to the standard *IES TM-27-14* XML format.
52 Parameters
53 ----------
54 path
55 Absolute or relative path to the *UPRTek* *Pseudo-XLS* file.
57 Attributes
58 ----------
59 - :attr:`~colour.SpectralDistribution_UPRTek.metadata`
61 Methods
62 -------
63 - :meth:`~colour.SpectralDistribution_UPRTek.__init__`
64 - :meth:`~colour.SpectralDistribution_UPRTek.__str__`
65 - :meth:`~colour.SpectralDistribution_UPRTek.read`
67 Examples
68 --------
69 >>> from os.path import dirname, join
70 >>> from colour import SpectralShape
71 >>> directory = join(dirname(__file__), "tests", "resources")
72 >>> sd = SpectralDistribution_UPRTek(
73 ... join(directory, "ESPD2021_0104_231446.xls")
74 ... )
75 >>> print(sd.align(SpectralShape(380, 780, 10)))
76 ... # doctest: +ELLIPSIS
77 UPRTek
78 ======
79 <BLANKLINE>
80 Path : ...
81 Spectral Quantity : irradiance
82 Reflection Geometry : None
83 Transmission Geometry : None
84 Bandwidth (FWHM) : None
85 Bandwidth Corrected : None
86 <BLANKLINE>
87 Header
88 ------
89 <BLANKLINE>
90 Manufacturer : UPRTek
91 Catalog Number : None
92 Description : None
93 Document Creator : None
94 Unique Identifier : None
95 Measurement Equipment : CV600
96 Laboratory : None
97 Report Number : None
98 Report Date : 2021/01/04_23:14:46
99 Document Creation Date : None
100 Comments : {...}
101 <BLANKLINE>
102 Spectral Data
103 -------------
104 <BLANKLINE>
105 [[ 3.80000000e+02 3.02670000e-02]
106 [ 3.90000000e+02 3.52230000e-02]
107 [ 4.00000000e+02 1.93250000e-02]
108 [ 4.10000000e+02 2.94260000e-02]
109 [ 4.20000000e+02 8.76780000e-02]
110 [ 4.30000000e+02 6.32578000e-01]
111 [ 4.40000000e+02 3.62565900e+00]
112 [ 4.50000000e+02 1.42069180e+01]
113 [ 4.60000000e+02 1.70112970e+01]
114 [ 4.70000000e+02 1.19673130e+01]
115 [ 4.80000000e+02 8.42736200e+00]
116 [ 4.90000000e+02 7.97729800e+00]
117 [ 5.00000000e+02 8.71903600e+00]
118 [ 5.10000000e+02 9.55321500e+00]
119 [ 5.20000000e+02 9.90610500e+00]
120 [ 5.30000000e+02 9.91394400e+00]
121 [ 5.40000000e+02 9.74738000e+00]
122 [ 5.50000000e+02 9.53404900e+00]
123 [ 5.60000000e+02 9.27392200e+00]
124 [ 5.70000000e+02 9.02323400e+00]
125 [ 5.80000000e+02 8.91788800e+00]
126 [ 5.90000000e+02 9.11454600e+00]
127 [ 6.00000000e+02 9.55787100e+00]
128 [ 6.10000000e+02 1.00600760e+01]
129 [ 6.20000000e+02 1.04846200e+01]
130 [ 6.30000000e+02 1.05679540e+01]
131 [ 6.40000000e+02 1.04359870e+01]
132 [ 6.50000000e+02 9.82122300e+00]
133 [ 6.60000000e+02 8.77578300e+00]
134 [ 6.70000000e+02 7.56471800e+00]
135 [ 6.80000000e+02 6.29808600e+00]
136 [ 6.90000000e+02 5.15623400e+00]
137 [ 7.00000000e+02 4.05390600e+00]
138 [ 7.10000000e+02 3.06638600e+00]
139 [ 7.20000000e+02 2.19250000e+00]
140 [ 7.30000000e+02 1.53922800e+00]
141 [ 7.40000000e+02 1.14938200e+00]
142 [ 7.50000000e+02 9.05095000e-01]
143 [ 7.60000000e+02 6.90947000e-01]
144 [ 7.70000000e+02 5.08426000e-01]
145 [ 7.80000000e+02 4.11766000e-01]]
147 >>> sd.header.comments
148 '{"Model Name": "CV600", "Serial Number": "19J00789", \
149"Time": "2021/01/04_23:14:46", "Memo": [], "LUX": 695.154907, \
150"fc": 64.605476, "CCT": 5198.0, "Duv": -0.00062, "I-Time": 12000.0, \
151"X": 682.470886, "Y": 695.154907, "Z": 631.635071, "x": 0.339663, \
152"y": 0.345975, "u\\'": 0.209915, "v\\'": 0.481087, "LambdaP": 456.0, \
153"LambdaPValue": 18.404581, "CRI": 92.956993, "R1": 91.651062, \
154"R2": 93.014732, "R3": 97.032013, "R4": 93.513229, "R5": 92.48259, \
155"R6": 91.48687, "R7": 93.016129, "R8": 91.459312, "R9": 77.613075, \
156"R10": 86.981613, "R11": 94.841324, "R12": 74.139542, "R13": 91.073837, \
157"R14": 97.064323, "R15": 88.615669, "TLCI": 97.495056, "TLMF-A": 1.270032, \
158"SSI-A": 44.881924, "Rf": 87.234917, "Rg": 98.510712, "IRR": 2.607891}'
159 >>> sd.metadata.keys()
160 dict_keys(['Model Name', 'Serial Number', 'Time', 'Memo', 'LUX', 'fc', \
161'CCT', 'Duv', 'I-Time', 'X', 'Y', 'Z', 'x', 'y', "u'", "v'", 'LambdaP', \
162'LambdaPValue', 'CRI', 'R1', 'R2', 'R3', 'R4', 'R5', 'R6', 'R7', 'R8', 'R9', \
163'R10', 'R11', 'R12', 'R13', 'R14', 'R15', 'TLCI', 'TLMF-A', 'SSI-A', 'Rf', \
164'Rg', 'IRR'])
165 >>> sd.write(join(directory, "ESPD2021_0104_231446.spdx"))
166 ... # doctest: +SKIP
167 """
169 _DELIMITER: str = "\t"
170 _SPECTRAL_SECTION: str = "380"
171 _SPECTRAL_DATA_PATTERN: str = "(\\d{3})nm"
173 def __init__(self, path: str | PathLike, **kwargs: Any) -> None:
174 self._metadata: dict = {}
176 super().__init__(path, **kwargs)
178 @property
179 def metadata(self) -> dict:
180 """
181 Getter for the dataset metadata.
183 Returns
184 -------
185 :class:`dict`
186 Dataset metadata containing information about the data source,
187 structure, and properties.
188 """
190 return self._metadata
192 def __str__(self) -> str:
193 """
194 Return a formatted string representation of the *UPRTek* spectral
195 distribution.
197 Returns
198 -------
199 :class:`str`
200 Formatted string representation.
202 Examples
203 --------
204 >>> from os.path import dirname, join
205 >>> from colour import SpectralShape
206 >>> directory = join(dirname(__file__), "tests", "resources")
207 >>> sd = SpectralDistribution_UPRTek(
208 ... join(directory, "ESPD2021_0104_231446.xls")
209 ... )
210 >>> print(sd.read().align(SpectralShape(380, 780, 10)))
211 ... # doctest: +ELLIPSIS
212 UPRTek
213 ======
214 <BLANKLINE>
215 Path : ...
216 Spectral Quantity : irradiance
217 Reflection Geometry : None
218 Transmission Geometry : None
219 Bandwidth (FWHM) : None
220 Bandwidth Corrected : None
221 <BLANKLINE>
222 Header
223 ------
224 <BLANKLINE>
225 Manufacturer : UPRTek
226 Catalog Number : None
227 Description : None
228 Document Creator : None
229 Unique Identifier : None
230 Measurement Equipment : CV600
231 Laboratory : None
232 Report Number : None
233 Report Date : 2021/01/04_23:14:46
234 Document Creation Date : None
235 Comments : {...}
236 <BLANKLINE>
237 Spectral Data
238 -------------
239 <BLANKLINE>
240 [[ 3.80000000e+02 3.02670000e-02]
241 [ 3.90000000e+02 3.52230000e-02]
242 [ 4.00000000e+02 1.93250000e-02]
243 [ 4.10000000e+02 2.94260000e-02]
244 [ 4.20000000e+02 8.76780000e-02]
245 [ 4.30000000e+02 6.32578000e-01]
246 [ 4.40000000e+02 3.62565900e+00]
247 [ 4.50000000e+02 1.42069180e+01]
248 [ 4.60000000e+02 1.70112970e+01]
249 [ 4.70000000e+02 1.19673130e+01]
250 [ 4.80000000e+02 8.42736200e+00]
251 [ 4.90000000e+02 7.97729800e+00]
252 [ 5.00000000e+02 8.71903600e+00]
253 [ 5.10000000e+02 9.55321500e+00]
254 [ 5.20000000e+02 9.90610500e+00]
255 [ 5.30000000e+02 9.91394400e+00]
256 [ 5.40000000e+02 9.74738000e+00]
257 [ 5.50000000e+02 9.53404900e+00]
258 [ 5.60000000e+02 9.27392200e+00]
259 [ 5.70000000e+02 9.02323400e+00]
260 [ 5.80000000e+02 8.91788800e+00]
261 [ 5.90000000e+02 9.11454600e+00]
262 [ 6.00000000e+02 9.55787100e+00]
263 [ 6.10000000e+02 1.00600760e+01]
264 [ 6.20000000e+02 1.04846200e+01]
265 [ 6.30000000e+02 1.05679540e+01]
266 [ 6.40000000e+02 1.04359870e+01]
267 [ 6.50000000e+02 9.82122300e+00]
268 [ 6.60000000e+02 8.77578300e+00]
269 [ 6.70000000e+02 7.56471800e+00]
270 [ 6.80000000e+02 6.29808600e+00]
271 [ 6.90000000e+02 5.15623400e+00]
272 [ 7.00000000e+02 4.05390600e+00]
273 [ 7.10000000e+02 3.06638600e+00]
274 [ 7.20000000e+02 2.19250000e+00]
275 [ 7.30000000e+02 1.53922800e+00]
276 [ 7.40000000e+02 1.14938200e+00]
277 [ 7.50000000e+02 9.05095000e-01]
278 [ 7.60000000e+02 6.90947000e-01]
279 [ 7.70000000e+02 5.08426000e-01]
280 [ 7.80000000e+02 4.11766000e-01]]
281 """
283 representation = super().__str__()
285 return representation.replace(
286 ("IES TM-27-14 Spectral Distribution\n=================================="),
287 "UPRTek\n======",
288 )
290 def read(self) -> SpectralDistribution_UPRTek:
291 """
292 Read and parse the spectral data from the specified *UPRTek* *CSV*
293 file.
295 Returns
296 -------
297 :class:`colour.SpectralDistribution_UPRTek`
298 *UPRTek* spectral distribution.
300 Raises
301 ------
302 IOError
303 If the file cannot be read.
305 Examples
306 --------
307 >>> from os.path import dirname, join
308 >>> from colour import SpectralShape
309 >>> directory = join(dirname(__file__), "tests", "resources")
310 >>> sd = SpectralDistribution_UPRTek(
311 ... join(directory, "ESPD2021_0104_231446.xls")
312 ... )
313 >>> print(sd.read().align(SpectralShape(380, 780, 10)))
314 ... # doctest: +ELLIPSIS
315 UPRTek
316 ======
317 <BLANKLINE>
318 Path : ...
319 Spectral Quantity : irradiance
320 Reflection Geometry : None
321 Transmission Geometry : None
322 Bandwidth (FWHM) : None
323 Bandwidth Corrected : None
324 <BLANKLINE>
325 Header
326 ------
327 <BLANKLINE>
328 Manufacturer : UPRTek
329 Catalog Number : None
330 Description : None
331 Document Creator : None
332 Unique Identifier : None
333 Measurement Equipment : CV600
334 Laboratory : None
335 Report Number : None
336 Report Date : 2021/01/04_23:14:46
337 Document Creation Date : None
338 Comments : {...}
339 <BLANKLINE>
340 Spectral Data
341 -------------
342 <BLANKLINE>
343 [[ 3.80000000e+02 3.02670000e-02]
344 [ 3.90000000e+02 3.52230000e-02]
345 [ 4.00000000e+02 1.93250000e-02]
346 [ 4.10000000e+02 2.94260000e-02]
347 [ 4.20000000e+02 8.76780000e-02]
348 [ 4.30000000e+02 6.32578000e-01]
349 [ 4.40000000e+02 3.62565900e+00]
350 [ 4.50000000e+02 1.42069180e+01]
351 [ 4.60000000e+02 1.70112970e+01]
352 [ 4.70000000e+02 1.19673130e+01]
353 [ 4.80000000e+02 8.42736200e+00]
354 [ 4.90000000e+02 7.97729800e+00]
355 [ 5.00000000e+02 8.71903600e+00]
356 [ 5.10000000e+02 9.55321500e+00]
357 [ 5.20000000e+02 9.90610500e+00]
358 [ 5.30000000e+02 9.91394400e+00]
359 [ 5.40000000e+02 9.74738000e+00]
360 [ 5.50000000e+02 9.53404900e+00]
361 [ 5.60000000e+02 9.27392200e+00]
362 [ 5.70000000e+02 9.02323400e+00]
363 [ 5.80000000e+02 8.91788800e+00]
364 [ 5.90000000e+02 9.11454600e+00]
365 [ 6.00000000e+02 9.55787100e+00]
366 [ 6.10000000e+02 1.00600760e+01]
367 [ 6.20000000e+02 1.04846200e+01]
368 [ 6.30000000e+02 1.05679540e+01]
369 [ 6.40000000e+02 1.04359870e+01]
370 [ 6.50000000e+02 9.82122300e+00]
371 [ 6.60000000e+02 8.77578300e+00]
372 [ 6.70000000e+02 7.56471800e+00]
373 [ 6.80000000e+02 6.29808600e+00]
374 [ 6.90000000e+02 5.15623400e+00]
375 [ 7.00000000e+02 4.05390600e+00]
376 [ 7.10000000e+02 3.06638600e+00]
377 [ 7.20000000e+02 2.19250000e+00]
378 [ 7.30000000e+02 1.53922800e+00]
379 [ 7.40000000e+02 1.14938200e+00]
380 [ 7.50000000e+02 9.05095000e-01]
381 [ 7.60000000e+02 6.90947000e-01]
382 [ 7.70000000e+02 5.08426000e-01]
383 [ 7.80000000e+02 4.11766000e-01]]
384 """
386 path = cast("str", self.path)
388 def as_array(a: Any) -> list:
389 """
390 Input list of numbers and converts each element to
391 float data type.
392 """
394 return [as_float_scalar(e) for e in a]
396 spectral_sections = defaultdict(list)
397 with open(path, encoding="utf-8") as csv_file:
398 content = csv.reader(csv_file, delimiter=self._DELIMITER)
400 spectral_section = 0
401 for row in content:
402 if not "".join(row).strip():
403 continue
405 attribute, tokens = row[0], row[1:]
406 value = tokens[0] if len(tokens) == 1 else tokens
408 if (
409 match := re.match(self._SPECTRAL_DATA_PATTERN, attribute)
410 ) is not None:
411 wavelength = match.group(1)
413 if wavelength == self._SPECTRAL_SECTION:
414 spectral_section += 1
416 spectral_sections[spectral_section].append([wavelength, value])
417 else:
418 for method in (int, float, as_array):
419 try:
420 self._metadata[attribute] = method(
421 value # pyright: ignore
422 )
423 except (TypeError, ValueError): # noqa: PERF203
424 self._metadata[attribute] = value
425 else:
426 break
428 self.name = os.path.splitext(os.path.basename(path))[0]
429 spectral_data = as_float_array(
430 spectral_sections[sorted(spectral_sections.keys())[-1]]
431 )
433 self.wavelengths = spectral_data[..., 0]
434 self.values = spectral_data[..., 1]
436 self.header.comments = json.dumps(self._metadata)
438 self.header.report_date = self._metadata.get("Time")
439 self.header.measurement_equipment = self._metadata.get("Model Name")
440 self.header.manufacturer = "UPRTek"
441 self.spectral_quantity = "irradiance"
443 return self
446class SpectralDistribution_Sekonic(SpectralDistribution_UPRTek):
447 """
448 Provide support for reading and writing *IES TM-27-14* spectral data XML
449 files from *Sekonic* *CSV* files.
451 This class extends the *UPRTek* spectral distribution functionality to
452 handle *Sekonic* spectrometer data files. It enables conversion between
453 *Sekonic* *CSV* format and the standardized *IES TM-27-14* XML format.
455 Parameters
456 ----------
457 path
458 Path for *Sekonic* *CSV* file.
460 Attributes
461 ----------
462 - :attr:`~colour.SpectralDistribution_UPRTek.metadata`
464 Methods
465 -------
466 - :meth:`~colour.SpectralDistribution_Sekonic.__init__`
467 - :meth:`~colour.SpectralDistribution_Sekonic.__str__`
468 - :meth:`~colour.SpectralDistribution_Sekonic.read`
470 Examples
471 --------
472 >>> from os.path import dirname, join
473 >>> from colour import SpectralShape
474 >>> directory = join(dirname(__file__), "tests", "resources")
475 >>> sd = SpectralDistribution_Sekonic(join(directory, "RANDOM_001_02._3262K.csv"))
476 >>> print(sd.read().align(SpectralShape(380, 780, 10)))
477 ... # doctest: +ELLIPSIS
478 Sekonic
479 =======
480 <BLANKLINE>
481 Path : ...
482 Spectral Quantity : irradiance
483 Reflection Geometry : None
484 Transmission Geometry : None
485 Bandwidth (FWHM) : None
486 Bandwidth Corrected : None
487 <BLANKLINE>
488 Header
489 ------
490 <BLANKLINE>
491 Manufacturer : Sekonic
492 Catalog Number : None
493 Description : None
494 Document Creator : None
495 Unique Identifier : None
496 Measurement Equipment : None
497 Laboratory : None
498 Report Number : None
499 Report Date : 15/03/2021 3:44:14 p.m.
500 Document Creation Date : None
501 Comments : {...}
502 <BLANKLINE>
503 Spectral Data
504 -------------
505 <BLANKLINE>
506 [[ 3.80000000e+02 1.69406589e-21]
507 [ 3.90000000e+02 2.11758237e-22]
508 [ 4.00000000e+02 1.19813650e-05]
509 [ 4.10000000e+02 1.97110530e-05]
510 [ 4.20000000e+02 2.99661440e-05]
511 [ 4.30000000e+02 6.38192720e-05]
512 [ 4.40000000e+02 1.68909683e-04]
513 [ 4.50000000e+02 3.31902935e-04]
514 [ 4.60000000e+02 3.33143020e-04]
515 [ 4.70000000e+02 2.30227481e-04]
516 [ 4.80000000e+02 1.66981976e-04]
517 [ 4.90000000e+02 1.64439844e-04]
518 [ 5.00000000e+02 2.01534538e-04]
519 [ 5.10000000e+02 2.57840526e-04]
520 [ 5.20000000e+02 3.04612651e-04]
521 [ 5.30000000e+02 3.41368344e-04]
522 [ 5.40000000e+02 3.63639323e-04]
523 [ 5.50000000e+02 3.87050648e-04]
524 [ 5.60000000e+02 4.21619130e-04]
525 [ 5.70000000e+02 4.58150520e-04]
526 [ 5.80000000e+02 5.01176575e-04]
527 [ 5.90000000e+02 5.40883630e-04]
528 [ 6.00000000e+02 5.71256795e-04]
529 [ 6.10000000e+02 5.83703280e-04]
530 [ 6.20000000e+02 5.57688472e-04]
531 [ 6.30000000e+02 5.17328095e-04]
532 [ 6.40000000e+02 4.39994939e-04]
533 [ 6.50000000e+02 3.62766819e-04]
534 [ 6.60000000e+02 2.96465587e-04]
535 [ 6.70000000e+02 2.43966802e-04]
536 [ 6.80000000e+02 2.04134776e-04]
537 [ 6.90000000e+02 1.75304012e-04]
538 [ 7.00000000e+02 1.52887544e-04]
539 [ 7.10000000e+02 1.29795619e-04]
540 [ 7.20000000e+02 1.03122693e-04]
541 [ 7.30000000e+02 8.77607820e-05]
542 [ 7.40000000e+02 7.61524130e-05]
543 [ 7.50000000e+02 7.06516880e-05]
544 [ 7.60000000e+02 3.72199210e-05]
545 [ 7.70000000e+02 3.63058860e-05]
546 [ 7.80000000e+02 3.55755470e-05]]
547 >>> sd.header.comments # doctest: +SKIP
548 >>> sd.metadata.keys() # doctest: +SKIP
549 >>> sd.write(join(directory, "RANDOM_001_02._3262K.spdx"))
550 ... # doctest: +SKIP
551 """
553 _DELIMITER: str = ","
554 _SPECTRAL_SECTION: str = "380"
555 _SPECTRAL_DATA_PATTERN: str = "Spectral Data (\\d{3})\\[nm\\]"
557 def __init__(self, path: str | PathLike, **kwargs: Any) -> None:
558 super().__init__(path, **kwargs)
560 def __str__(self) -> str:
561 """
562 Return a formatted string representation of the *Sekonic* spectral
563 distribution.
565 Returns
566 -------
567 :class:`str`
568 Formatted string representation.
570 Examples
571 --------
572 >>> from os.path import dirname, join
573 >>> from colour import SpectralShape
574 >>> directory = join(dirname(__file__), "tests", "resources")
575 >>> sd = SpectralDistribution_UPRTek(
576 ... join(directory, "ESPD2021_0104_231446.xls")
577 ... )
578 >>> print(sd.read().align(SpectralShape(380, 780, 10)))
579 ... # doctest: +ELLIPSIS
580 UPRTek
581 ======
582 <BLANKLINE>
583 Path : ...
584 Spectral Quantity : irradiance
585 Reflection Geometry : None
586 Transmission Geometry : None
587 Bandwidth (FWHM) : None
588 Bandwidth Corrected : None
589 <BLANKLINE>
590 Header
591 ------
592 <BLANKLINE>
593 Manufacturer : UPRTek
594 Catalog Number : None
595 Description : None
596 Document Creator : None
597 Unique Identifier : None
598 Measurement Equipment : CV600
599 Laboratory : None
600 Report Number : None
601 Report Date : 2021/01/04_23:14:46
602 Document Creation Date : None
603 Comments : {...}
604 <BLANKLINE>
605 Spectral Data
606 -------------
607 <BLANKLINE>
608 [[ 3.80000000e+02 3.02670000e-02]
609 [ 3.90000000e+02 3.52230000e-02]
610 [ 4.00000000e+02 1.93250000e-02]
611 [ 4.10000000e+02 2.94260000e-02]
612 [ 4.20000000e+02 8.76780000e-02]
613 [ 4.30000000e+02 6.32578000e-01]
614 [ 4.40000000e+02 3.62565900e+00]
615 [ 4.50000000e+02 1.42069180e+01]
616 [ 4.60000000e+02 1.70112970e+01]
617 [ 4.70000000e+02 1.19673130e+01]
618 [ 4.80000000e+02 8.42736200e+00]
619 [ 4.90000000e+02 7.97729800e+00]
620 [ 5.00000000e+02 8.71903600e+00]
621 [ 5.10000000e+02 9.55321500e+00]
622 [ 5.20000000e+02 9.90610500e+00]
623 [ 5.30000000e+02 9.91394400e+00]
624 [ 5.40000000e+02 9.74738000e+00]
625 [ 5.50000000e+02 9.53404900e+00]
626 [ 5.60000000e+02 9.27392200e+00]
627 [ 5.70000000e+02 9.02323400e+00]
628 [ 5.80000000e+02 8.91788800e+00]
629 [ 5.90000000e+02 9.11454600e+00]
630 [ 6.00000000e+02 9.55787100e+00]
631 [ 6.10000000e+02 1.00600760e+01]
632 [ 6.20000000e+02 1.04846200e+01]
633 [ 6.30000000e+02 1.05679540e+01]
634 [ 6.40000000e+02 1.04359870e+01]
635 [ 6.50000000e+02 9.82122300e+00]
636 [ 6.60000000e+02 8.77578300e+00]
637 [ 6.70000000e+02 7.56471800e+00]
638 [ 6.80000000e+02 6.29808600e+00]
639 [ 6.90000000e+02 5.15623400e+00]
640 [ 7.00000000e+02 4.05390600e+00]
641 [ 7.10000000e+02 3.06638600e+00]
642 [ 7.20000000e+02 2.19250000e+00]
643 [ 7.30000000e+02 1.53922800e+00]
644 [ 7.40000000e+02 1.14938200e+00]
645 [ 7.50000000e+02 9.05095000e-01]
646 [ 7.60000000e+02 6.90947000e-01]
647 [ 7.70000000e+02 5.08426000e-01]
648 [ 7.80000000e+02 4.11766000e-01]]
649 """
651 representation = super().__str__()
653 return representation.replace(
654 "UPRTek\n======",
655 "Sekonic\n=======",
656 )
658 def read(self) -> SpectralDistribution_Sekonic:
659 """
660 Read and parse the spectral data from the specified *Sekonic*
661 *Pseudo-XLS* file.
663 Returns
664 -------
665 :class:`colour.SpectralDistribution_Sekonic`
666 *Sekonic* spectral distribution.
668 Raises
669 ------
670 IOError
671 If the file cannot be read.
673 Examples
674 --------
675 >>> from os.path import dirname, join
676 >>> from colour import SpectralShape
677 >>> directory = join(dirname(__file__), "tests", "resources")
678 >>> sd = SpectralDistribution_Sekonic(
679 ... join(directory, "RANDOM_001_02._3262K.csv")
680 ... )
681 >>> print(sd.read().align(SpectralShape(380, 780, 10)))
682 ... # doctest: +ELLIPSIS
683 Sekonic
684 =======
685 <BLANKLINE>
686 Path : ...
687 Spectral Quantity : irradiance
688 Reflection Geometry : None
689 Transmission Geometry : None
690 Bandwidth (FWHM) : None
691 Bandwidth Corrected : None
692 <BLANKLINE>
693 Header
694 ------
695 <BLANKLINE>
696 Manufacturer : Sekonic
697 Catalog Number : None
698 Description : None
699 Document Creator : None
700 Unique Identifier : None
701 Measurement Equipment : None
702 Laboratory : None
703 Report Number : None
704 Report Date : 15/03/2021 3:44:14 p.m.
705 Document Creation Date : None
706 Comments : {...}
707 <BLANKLINE>
708 Spectral Data
709 -------------
710 <BLANKLINE>
711 [[ 3.80000000e+02 1.69406589e-21]
712 [ 3.90000000e+02 2.11758237e-22]
713 [ 4.00000000e+02 1.19813650e-05]
714 [ 4.10000000e+02 1.97110530e-05]
715 [ 4.20000000e+02 2.99661440e-05]
716 [ 4.30000000e+02 6.38192720e-05]
717 [ 4.40000000e+02 1.68909683e-04]
718 [ 4.50000000e+02 3.31902935e-04]
719 [ 4.60000000e+02 3.33143020e-04]
720 [ 4.70000000e+02 2.30227481e-04]
721 [ 4.80000000e+02 1.66981976e-04]
722 [ 4.90000000e+02 1.64439844e-04]
723 [ 5.00000000e+02 2.01534538e-04]
724 [ 5.10000000e+02 2.57840526e-04]
725 [ 5.20000000e+02 3.04612651e-04]
726 [ 5.30000000e+02 3.41368344e-04]
727 [ 5.40000000e+02 3.63639323e-04]
728 [ 5.50000000e+02 3.87050648e-04]
729 [ 5.60000000e+02 4.21619130e-04]
730 [ 5.70000000e+02 4.58150520e-04]
731 [ 5.80000000e+02 5.01176575e-04]
732 [ 5.90000000e+02 5.40883630e-04]
733 [ 6.00000000e+02 5.71256795e-04]
734 [ 6.10000000e+02 5.83703280e-04]
735 [ 6.20000000e+02 5.57688472e-04]
736 [ 6.30000000e+02 5.17328095e-04]
737 [ 6.40000000e+02 4.39994939e-04]
738 [ 6.50000000e+02 3.62766819e-04]
739 [ 6.60000000e+02 2.96465587e-04]
740 [ 6.70000000e+02 2.43966802e-04]
741 [ 6.80000000e+02 2.04134776e-04]
742 [ 6.90000000e+02 1.75304012e-04]
743 [ 7.00000000e+02 1.52887544e-04]
744 [ 7.10000000e+02 1.29795619e-04]
745 [ 7.20000000e+02 1.03122693e-04]
746 [ 7.30000000e+02 8.77607820e-05]
747 [ 7.40000000e+02 7.61524130e-05]
748 [ 7.50000000e+02 7.06516880e-05]
749 [ 7.60000000e+02 3.72199210e-05]
750 [ 7.70000000e+02 3.63058860e-05]
751 [ 7.80000000e+02 3.55755470e-05]]
752 """
754 super().read()
756 self.header.report_date = self._metadata.get("Date Saved")
757 self.header.manufacturer = "Sekonic"
759 return self