Coverage for colorimetry/lefs.py: 48%

1"""

2Luminous Efficiency Functions Spectral Distributions

3====================================================

5Define the luminous efficiency functions and their computation objects for

6photopic, scotopic, and mesopic vision conditions.

8References

9----------

10- :cite:`Wikipedia2005d` : Wikipedia. (2005). Mesopic weighting function.

11 Retrieved June 20, 2014, from

12 http://en.wikipedia.org/wiki/Mesopic_vision#Mesopic_weighting_function

13"""

15from __future__ import annotations

17import typing

19from colour.colorimetry import (

20 SDS_LEFS_PHOTOPIC,

21 SDS_LEFS_SCOTOPIC,

22 SpectralDistribution,

23 SpectralShape,

24)

25from colour.colorimetry.datasets.lefs import DATA_MESOPIC_X

27if typing.TYPE_CHECKING:

28 from colour.hints import ArrayLike, Literal, NDArrayFloat

30from colour.utilities import closest, optional, validate_method

32__author__ = "Colour Developers"

34__license__ = "BSD-3-Clause - https://opensource.org/licenses/BSD-3-Clause"

35__maintainer__ = "Colour Developers"

36__email__ = "colour-developers@colour-science.org"

37__status__ = "Production"

39__all__ = [

40 "mesopic_weighting_function",

41 "sd_mesopic_luminous_efficiency_function",

42]

45def mesopic_weighting_function(

46 wavelength: ArrayLike,

47 L_p: float,

48 source: Literal["Blue Heavy", "Red Heavy"] | str = "Blue Heavy",

49 method: Literal["MOVE", "LRC"] | str = "MOVE",

50 photopic_lef: SpectralDistribution | None = None,

51 scotopic_lef: SpectralDistribution | None = None,

52) -> NDArrayFloat:

53 """

54 Calculate the mesopic weighting function factor :math:`V_m` at the specified

55 wavelength :math:`\\lambda` using the specified photopic luminance

56 :math:`L_p`.

58 The mesopic weighting function provides a transition between photopic and

59 scotopic vision, accounting for the combined response of rods and cones

60 under intermediate lighting conditions.

62 Parameters

63 ----------

64 wavelength

65 Wavelength :math:`\\lambda` to calculate the mesopic weighting function

66 factor.

67 L_p

68 Photopic luminance :math:`L_p`.

69 source

70 Light source colour temperature.

71 method

72 Method to calculate the weighting factor.

73 photopic_lef

74 :math:`V(\\lambda)` photopic luminous efficiency function, defaults to

75 the *CIE 1924 Photopic Standard Observer*.

76 scotopic_lef

77 :math:`V^\\prime(\\lambda)` scotopic luminous efficiency function,

78 defaults to the *CIE 1951 Scotopic Standard Observer*.

80 Returns

81 -------

82 :class:`numpy.ndarray`

83 Mesopic weighting function factor :math:`V_m`.

85 References

86 ----------

87 :cite:`Wikipedia2005d`

89 Examples

90 --------

91 >>> mesopic_weighting_function(500, 0.2) # doctest: +ELLIPSIS

92 0.7052...

93 """

95 photopic_lef = optional(

96 photopic_lef,

97 SDS_LEFS_PHOTOPIC["CIE 1924 Photopic Standard Observer"],

98 )

100 scotopic_lef = optional(

101 scotopic_lef,

102 SDS_LEFS_SCOTOPIC["CIE 1951 Scotopic Standard Observer"],

103 )

104

105 source = validate_method(

106 source,

107 ("Blue Heavy", "Red Heavy"),

108 '"{0}" light source colour temperature is invalid, it must be one of {1}!',

109 )

110 method = validate_method(method, ("MOVE", "LRC"))

111

112 mesopic_x_luminance_values = sorted(DATA_MESOPIC_X.keys())

113 index = mesopic_x_luminance_values.index(closest(mesopic_x_luminance_values, L_p))

114 x = DATA_MESOPIC_X[mesopic_x_luminance_values[index]][source][method]

115

116 return (1 - x) * scotopic_lef[wavelength] + x * photopic_lef[wavelength]

117

118

119def sd_mesopic_luminous_efficiency_function(

120 L_p: float,

121 source: Literal["Blue Heavy", "Red Heavy"] | str = "Blue Heavy",

122 method: Literal["MOVE", "LRC"] | str = "MOVE",

123 photopic_lef: SpectralDistribution | None = None,

124 scotopic_lef: SpectralDistribution | None = None,

125) -> SpectralDistribution:

126 """

127 Return the mesopic luminous efficiency function :math:`V_m(\\lambda)` for

128 the specified photopic luminance :math:`L_p`.

129

130 Parameters

131 ----------

132 L_p

133 Photopic luminance :math:`L_p`.

134 source

135 Light source colour temperature.

136 method

137 Method to calculate the weighting factor.

138 photopic_lef

139 :math:`V(\\lambda)` photopic luminous efficiency function, default to

140 the *CIE 1924 Photopic Standard Observer*.

141 scotopic_lef

142 :math:`V^\\prime(\\lambda)` scotopic luminous efficiency function,

143 default to the *CIE 1951 Scotopic Standard Observer*.

144

145 Returns

146 -------

147 :class:`colour.SpectralDistribution`

148 Mesopic luminous efficiency function :math:`V_m(\\lambda)`.

149

150 References

151 ----------

152 :cite:`Wikipedia2005d`

153

154 Examples

155 --------

156 >>> from colour.utilities import numpy_print_options

157 >>> with numpy_print_options(suppress=True):

158 ... sd_mesopic_luminous_efficiency_function(0.2) # doctest: +ELLIPSIS

159 SpectralDistribution([[ 380. , 0.000424 ...],

160 [ 381. , 0.0004781...],

161 [ 382. , 0.0005399...],

162 [ 383. , 0.0006122...],

163 [ 384. , 0.0006961...],

164 [ 385. , 0.0007929...],

165 [ 386. , 0.000907 ...],

166 [ 387. , 0.0010389...],

167 [ 388. , 0.0011923...],

168 [ 389. , 0.0013703...],

169 [ 390. , 0.0015771...],

170 [ 391. , 0.0018167...],

171 [ 392. , 0.0020942...],

172 [ 393. , 0.0024160...],

173 [ 394. , 0.0027888...],

174 [ 395. , 0.0032196...],

175 [ 396. , 0.0037222...],

176 [ 397. , 0.0042957...],

177 [ 398. , 0.0049531...],

178 [ 399. , 0.0057143...],

179 [ 400. , 0.0065784...],

180 [ 401. , 0.0075658...],

181 [ 402. , 0.0086912...],

182 [ 403. , 0.0099638...],

183 [ 404. , 0.0114058...],

184 [ 405. , 0.0130401...],

185 [ 406. , 0.0148750...],

186 [ 407. , 0.0169310...],

187 [ 408. , 0.0192211...],

188 [ 409. , 0.0217511...],

189 [ 410. , 0.0245342...],

190 [ 411. , 0.0275773...],

191 [ 412. , 0.0309172...],

192 [ 413. , 0.0345149...],

193 [ 414. , 0.0383998...],

194 [ 415. , 0.0425744...],

195 [ 416. , 0.0471074...],

196 [ 417. , 0.0519322...],

197 [ 418. , 0.0570541...],

198 [ 419. , 0.0625466...],

199 [ 420. , 0.0683463...],

200 [ 421. , 0.0745255...],

201 [ 422. , 0.0809440...],

202 [ 423. , 0.0877344...],

203 [ 424. , 0.0948915...],

204 [ 425. , 0.1022731...],

205 [ 426. , 0.109877 ...],

206 [ 427. , 0.1178421...],

207 [ 428. , 0.1260316...],

208 [ 429. , 0.1343772...],

209 [ 430. , 0.143017 ...],

210 [ 431. , 0.1518128...],

211 [ 432. , 0.1608328...],

212 [ 433. , 0.1700088...],

213 [ 434. , 0.1792726...],

214 [ 435. , 0.1886934...],

215 [ 436. , 0.1982041...],

216 [ 437. , 0.2078032...],

217 [ 438. , 0.2174184...],

218 [ 439. , 0.2271147...],

219 [ 440. , 0.2368196...],

220 [ 441. , 0.2464623...],

221 [ 442. , 0.2561153...],

222 [ 443. , 0.2657160...],

223 [ 444. , 0.2753387...],

224 [ 445. , 0.2848520...],

225 [ 446. , 0.2944648...],

226 [ 447. , 0.3034902...],

227 [ 448. , 0.3132347...],

228 [ 449. , 0.3223257...],

229 [ 450. , 0.3314513...],

230 [ 451. , 0.3406129...],

231 [ 452. , 0.3498117...],

232 [ 453. , 0.3583617...],

233 [ 454. , 0.3676377...],

234 [ 455. , 0.3762670...],

235 [ 456. , 0.3849392...],

236 [ 457. , 0.3936540...],

237 [ 458. , 0.4024077...],

238 [ 459. , 0.4111965...],

239 [ 460. , 0.4193298...],

240 [ 461. , 0.4281803...],

241 [ 462. , 0.4363804...],

242 [ 463. , 0.4453117...],

243 [ 464. , 0.4542949...],

244 [ 465. , 0.4626509...],

245 [ 466. , 0.4717570...],

246 [ 467. , 0.4809300...],

247 [ 468. , 0.4901776...],

248 [ 469. , 0.4995075...],

249 [ 470. , 0.5096145...],

250 [ 471. , 0.5191293...],

251 [ 472. , 0.5294259...],

252 [ 473. , 0.5391316...],

253 [ 474. , 0.5496217...],

254 [ 475. , 0.5602103...],

255 [ 476. , 0.5702197...],

256 [ 477. , 0.5810207...],

257 [ 478. , 0.5919093...],

258 [ 479. , 0.6028683...],

259 [ 480. , 0.6138806...],

260 [ 481. , 0.6249373...],

261 [ 482. , 0.6360619...],

262 [ 483. , 0.6465989...],

263 [ 484. , 0.6579538...],

264 [ 485. , 0.6687841...],

265 [ 486. , 0.6797939...],

266 [ 487. , 0.6909887...],

267 [ 488. , 0.7023827...],

268 [ 489. , 0.7133032...],

269 [ 490. , 0.7244513...],

270 [ 491. , 0.7358470...],

271 [ 492. , 0.7468118...],

272 [ 493. , 0.7580294...],

273 [ 494. , 0.7694964...],

274 [ 495. , 0.7805225...],

275 [ 496. , 0.7917805...],

276 [ 497. , 0.8026123...],

277 [ 498. , 0.8130793...],

278 [ 499. , 0.8239297...],

279 [ 500. , 0.8352251...],

280 [ 501. , 0.8456342...],

281 [ 502. , 0.8564818...],

282 [ 503. , 0.8676921...],

283 [ 504. , 0.8785021...],

284 [ 505. , 0.8881489...],

285 [ 506. , 0.8986405...],

286 [ 507. , 0.9079322...],

287 [ 508. , 0.9174255...],

288 [ 509. , 0.9257739...],

289 [ 510. , 0.9350656...],

290 [ 511. , 0.9432365...],

291 [ 512. , 0.9509063...],

292 [ 513. , 0.9586931...],

293 [ 514. , 0.9658413...],

294 [ 515. , 0.9722825...],

295 [ 516. , 0.9779924...],

296 [ 517. , 0.9836106...],

297 [ 518. , 0.9883465...],

298 [ 519. , 0.9920964...],

299 [ 520. , 0.9954436...],

300 [ 521. , 0.9976202...],

301 [ 522. , 0.9993457...],

302 [ 523. , 1. ...],

303 [ 524. , 0.9996498...],

304 [ 525. , 0.9990487...],

305 [ 526. , 0.9975356...],

306 [ 527. , 0.9957615...],

307 [ 528. , 0.9930143...],

308 [ 529. , 0.9899559...],

309 [ 530. , 0.9858741...],

310 [ 531. , 0.9814453...],

311 [ 532. , 0.9766885...],

312 [ 533. , 0.9709363...],

313 [ 534. , 0.9648947...],

314 [ 535. , 0.9585832...],

315 [ 536. , 0.952012 ...],

316 [ 537. , 0.9444916...],

317 [ 538. , 0.9367089...],

318 [ 539. , 0.9293506...],

319 [ 540. , 0.9210429...],

320 [ 541. , 0.9124772...],

321 [ 542. , 0.9036604...],

322 [ 543. , 0.8945958...],

323 [ 544. , 0.8845999...],

324 [ 545. , 0.8750500...],

325 [ 546. , 0.8659457...],

326 [ 547. , 0.8559224...],

327 [ 548. , 0.8456846...],

328 [ 549. , 0.8352499...],

329 [ 550. , 0.8253229...],

330 [ 551. , 0.8152079...],

331 [ 552. , 0.8042205...],

332 [ 553. , 0.7944209...],

333 [ 554. , 0.7837466...],

334 [ 555. , 0.7735680...],

335 [ 556. , 0.7627808...],

336 [ 557. , 0.7522710...],

337 [ 558. , 0.7417549...],

338 [ 559. , 0.7312909...],

339 [ 560. , 0.7207983...],

340 [ 561. , 0.7101939...],

341 [ 562. , 0.6996362...],

342 [ 563. , 0.6890656...],

343 [ 564. , 0.6785599...],

344 [ 565. , 0.6680593...],

345 [ 566. , 0.6575697...],

346 [ 567. , 0.6471578...],

347 [ 568. , 0.6368208...],

348 [ 569. , 0.6264871...],

349 [ 570. , 0.6161541...],

350 [ 571. , 0.6058896...],

351 [ 572. , 0.5957000...],

352 [ 573. , 0.5855937...],

353 [ 574. , 0.5754412...],

354 [ 575. , 0.5653883...],

355 [ 576. , 0.5553742...],

356 [ 577. , 0.5454680...],

357 [ 578. , 0.5355972...],

358 [ 579. , 0.5258267...],

359 [ 580. , 0.5160152...],

360 [ 581. , 0.5062322...],

361 [ 582. , 0.4965595...],

362 [ 583. , 0.4868746...],

363 [ 584. , 0.4773299...],

364 [ 585. , 0.4678028...],

365 [ 586. , 0.4583704...],

366 [ 587. , 0.4489722...],

367 [ 588. , 0.4397606...],

368 [ 589. , 0.4306131...],

369 [ 590. , 0.4215446...],

370 [ 591. , 0.4125681...],

371 [ 592. , 0.4037550...],

372 [ 593. , 0.3950359...],

373 [ 594. , 0.3864104...],

374 [ 595. , 0.3778777...],

375 [ 596. , 0.3694405...],

376 [ 597. , 0.3611074...],

377 [ 598. , 0.3528596...],

378 [ 599. , 0.3447056...],

379 [ 600. , 0.3366470...],

380 [ 601. , 0.3286917...],

381 [ 602. , 0.3208410...],

382 [ 603. , 0.3130808...],

383 [ 604. , 0.3054105...],

384 [ 605. , 0.2978225...],

385 [ 606. , 0.2903027...],

386 [ 607. , 0.2828727...],

387 [ 608. , 0.2755311...],

388 [ 609. , 0.2682900...],

389 [ 610. , 0.2611478...],

390 [ 611. , 0.2541176...],

391 [ 612. , 0.2471885...],

392 [ 613. , 0.2403570...],

393 [ 614. , 0.2336057...],

394 [ 615. , 0.2269379...],

395 [ 616. , 0.2203527...],

396 [ 617. , 0.2138465...],

397 [ 618. , 0.2073946...],

398 [ 619. , 0.2009789...],

399 [ 620. , 0.1945818...],

400 [ 621. , 0.1881943...],

401 [ 622. , 0.1818226...],

402 [ 623. , 0.1754987...],

403 [ 624. , 0.1692476...],

404 [ 625. , 0.1630876...],

405 [ 626. , 0.1570257...],

406 [ 627. , 0.151071 ...],

407 [ 628. , 0.1452469...],

408 [ 629. , 0.1395845...],

409 [ 630. , 0.1341087...],

410 [ 631. , 0.1288408...],

411 [ 632. , 0.1237666...],

412 [ 633. , 0.1188631...],

413 [ 634. , 0.1141075...],

414 [ 635. , 0.1094766...],

415 [ 636. , 0.1049613...],

416 [ 637. , 0.1005679...],

417 [ 638. , 0.0962924...],

418 [ 639. , 0.0921296...],

419 [ 640. , 0.0880778...],

420 [ 641. , 0.0841306...],

421 [ 642. , 0.0802887...],

422 [ 643. , 0.0765559...],

423 [ 644. , 0.0729367...],

424 [ 645. , 0.0694345...],

425 [ 646. , 0.0660491...],

426 [ 647. , 0.0627792...],

427 [ 648. , 0.0596278...],

428 [ 649. , 0.0565970...],

429 [ 650. , 0.0536896...],

430 [ 651. , 0.0509068...],

431 [ 652. , 0.0482444...],

432 [ 653. , 0.0456951...],

433 [ 654. , 0.0432510...],

434 [ 655. , 0.0409052...],

435 [ 656. , 0.0386537...],

436 [ 657. , 0.0364955...],

437 [ 658. , 0.0344285...],

438 [ 659. , 0.0324501...],

439 [ 660. , 0.0305579...],

440 [ 661. , 0.0287496...],

441 [ 662. , 0.0270233...],

442 [ 663. , 0.0253776...],

443 [ 664. , 0.0238113...],

444 [ 665. , 0.0223226...],

445 [ 666. , 0.0209086...],

446 [ 667. , 0.0195688...],

447 [ 668. , 0.0183056...],

448 [ 669. , 0.0171216...],

449 [ 670. , 0.0160192...],

450 [ 671. , 0.0149986...],

451 [ 672. , 0.0140537...],

452 [ 673. , 0.0131784...],

453 [ 674. , 0.0123662...],

454 [ 675. , 0.0116107...],

455 [ 676. , 0.0109098...],

456 [ 677. , 0.0102587...],

457 [ 678. , 0.0096476...],

458 [ 679. , 0.0090665...],

459 [ 680. , 0.0085053...],

460 [ 681. , 0.0079567...],

461 [ 682. , 0.0074229...],

462 [ 683. , 0.0069094...],

463 [ 684. , 0.0064213...],

464 [ 685. , 0.0059637...],

465 [ 686. , 0.0055377...],

466 [ 687. , 0.0051402...],

467 [ 688. , 0.00477 ...],

468 [ 689. , 0.0044263...],

469 [ 690. , 0.0041081...],

470 [ 691. , 0.0038149...],

471 [ 692. , 0.0035456...],

472 [ 693. , 0.0032984...],

473 [ 694. , 0.0030718...],

474 [ 695. , 0.0028639...],

475 [ 696. , 0.0026738...],

476 [ 697. , 0.0025000...],

477 [ 698. , 0.0023401...],

478 [ 699. , 0.0021918...],

479 [ 700. , 0.0020526...],

480 [ 701. , 0.0019207...],

481 [ 702. , 0.001796 ...],

482 [ 703. , 0.0016784...],

483 [ 704. , 0.0015683...],

484 [ 705. , 0.0014657...],

485 [ 706. , 0.0013702...],

486 [ 707. , 0.001281 ...],

487 [ 708. , 0.0011976...],

488 [ 709. , 0.0011195...],

489 [ 710. , 0.0010464...],

490 [ 711. , 0.0009776...],

491 [ 712. , 0.0009131...],

492 [ 713. , 0.0008525...],

493 [ 714. , 0.0007958...],

494 [ 715. , 0.0007427...],

495 [ 716. , 0.0006929...],

496 [ 717. , 0.0006462...],

497 [ 718. , 0.0006026...],

498 [ 719. , 0.0005619...],

499 [ 720. , 0.0005240...],

500 [ 721. , 0.0004888...],

501 [ 722. , 0.0004561...],

502 [ 723. , 0.0004255...],

503 [ 724. , 0.0003971...],

504 [ 725. , 0.0003704...],

505 [ 726. , 0.0003455...],

506 [ 727. , 0.0003221...],

507 [ 728. , 0.0003001...],

508 [ 729. , 0.0002796...],

509 [ 730. , 0.0002604...],

510 [ 731. , 0.0002423...],

511 [ 732. , 0.0002254...],

512 [ 733. , 0.0002095...],

513 [ 734. , 0.0001947...],

514 [ 735. , 0.0001809...],

515 [ 736. , 0.0001680...],

516 [ 737. , 0.0001560...],

517 [ 738. , 0.0001449...],

518 [ 739. , 0.0001345...],

519 [ 740. , 0.0001249...],

520 [ 741. , 0.0001159...],

521 [ 742. , 0.0001076...],

522 [ 743. , 0.0000999...],

523 [ 744. , 0.0000927...],

524 [ 745. , 0.0000862...],

525 [ 746. , 0.0000801...],

526 [ 747. , 0.0000745...],

527 [ 748. , 0.0000693...],

528 [ 749. , 0.0000646...],

529 [ 750. , 0.0000602...],

530 [ 751. , 0.0000561...],

531 [ 752. , 0.0000523...],

532 [ 753. , 0.0000488...],

533 [ 754. , 0.0000456...],

534 [ 755. , 0.0000425...],

535 [ 756. , 0.0000397...],

536 [ 757. , 0.0000370...],

537 [ 758. , 0.0000346...],

538 [ 759. , 0.0000322...],

539 [ 760. , 0.0000301...],

540 [ 761. , 0.0000281...],

541 [ 762. , 0.0000262...],

542 [ 763. , 0.0000244...],

543 [ 764. , 0.0000228...],

544 [ 765. , 0.0000213...],

545 [ 766. , 0.0000198...],

546 [ 767. , 0.0000185...],

547 [ 768. , 0.0000173...],

548 [ 769. , 0.0000161...],

549 [ 770. , 0.0000150...],

550 [ 771. , 0.0000140...],

551 [ 772. , 0.0000131...],

552 [ 773. , 0.0000122...],

553 [ 774. , 0.0000114...],

554 [ 775. , 0.0000106...],

555 [ 776. , 0.0000099...],

556 [ 777. , 0.0000092...],

557 [ 778. , 0.0000086...],

558 [ 779. , 0.0000080...],

559 [ 780. , 0.0000075...]],

560 SpragueInterpolator,

561 {},

562 Extrapolator,

563 {'method': 'Constant', 'left': None, 'right': None})

564 """

565

566 photopic_lef = optional(

567 photopic_lef,

568 SDS_LEFS_PHOTOPIC["CIE 1924 Photopic Standard Observer"],

569 )

570

571 scotopic_lef = optional(

572 scotopic_lef,

573 SDS_LEFS_SCOTOPIC["CIE 1951 Scotopic Standard Observer"],

574 )

575

576 shape = SpectralShape(

577 max([photopic_lef.shape.start, scotopic_lef.shape.start]),

578 min([photopic_lef.shape.end, scotopic_lef.shape.end]),

579 max([photopic_lef.shape.interval, scotopic_lef.shape.interval]),

580 )

581

582 sd = SpectralDistribution(

583 mesopic_weighting_function(

584 shape.wavelengths, L_p, source, method, photopic_lef, scotopic_lef

585 ),

586 shape.wavelengths,

587 name=f"{L_p} Lp Mesopic Luminous Efficiency Function",

588 )

589

590 return sd.normalise()