Source code for colour.colorimetry.lefs

# -*- coding: utf-8 -*-
"""
Luminous Efficiency Functions Spectral Distributions
====================================================

Defines luminous efficiency functions computation related objects.

References
----------
-   :cite:`Wikipedia2005d` : Wikipedia. (2005). Mesopic weighting function.
    Retrieved June 20, 2014, from
    http://en.wikipedia.org/wiki/Mesopic_vision#Mesopic_weighting_function
"""

from __future__ import division, unicode_literals

from colour.colorimetry import (PHOTOPIC_LEFS, SCOTOPIC_LEFS,
                                SpectralDistribution, SpectralShape)
from colour.colorimetry.datasets.lefs import MESOPIC_X_DATA
from colour.utilities import closest

__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013-2020 - Colour Developers'
__license__ = 'New BSD License - https://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = 'colour-developers@colour-science.org'
__status__ = 'Production'

__all__ = [
    'mesopic_weighting_function', 'sd_mesopic_luminous_efficiency_function'
]


def mesopic_weighting_function(
        wavelength,
        Lp,
        source='Blue Heavy',
        method='MOVE',
        photopic_lef=PHOTOPIC_LEFS['CIE 1924 Photopic Standard Observer'],
        scotopic_lef=SCOTOPIC_LEFS['CIE 1951 Scotopic Standard Observer']):
    """
    Calculates the mesopic weighting function factor at given wavelength
    :math:`\\lambda` using the photopic luminance :math:`L_p`.

    Parameters
    ----------
    wavelength : numeric or array_like
        Wavelength :math:`\\lambda` to calculate the mesopic weighting function
        factor.
    Lp : numeric
        Photopic luminance :math:`L_p`.
    source : unicode, optional
        **{'Blue Heavy', 'Red Heavy'}**,
        Light source colour temperature.
    method : unicode, optional
        **{'MOVE', 'LRC'}**,
        Method to calculate the weighting factor.
    photopic_lef : SpectralDistribution, optional
        :math:`V(\\lambda)` photopic luminous efficiency function.
    scotopic_lef : SpectralDistribution, optional
        :math:`V^\\prime(\\lambda)` scotopic luminous efficiency function.

    Returns
    -------
    numeric or ndarray
        Mesopic weighting function factor.

    References
    ----------
    :cite:`Wikipedia2005d`

    Examples
    --------
    >>> mesopic_weighting_function(500, 0.2)  # doctest: +ELLIPSIS
    0.7052200...
    """

    mesopic_x_luminance_values = sorted(MESOPIC_X_DATA.keys())
    index = mesopic_x_luminance_values.index(
        closest(mesopic_x_luminance_values, Lp))
    x = MESOPIC_X_DATA[mesopic_x_luminance_values[index]][source][method]

    Vm = (1 - x) * scotopic_lef[wavelength] + x * photopic_lef[wavelength]

    return Vm


[docs]def sd_mesopic_luminous_efficiency_function( Lp, source='Blue Heavy', method='MOVE', photopic_lef=PHOTOPIC_LEFS['CIE 1924 Photopic Standard Observer'], scotopic_lef=SCOTOPIC_LEFS['CIE 1951 Scotopic Standard Observer']): """ Returns the mesopic luminous efficiency function :math:`V_m(\\lambda)` for given photopic luminance :math:`L_p`. Parameters ---------- Lp : numeric Photopic luminance :math:`L_p`. source : unicode, optional **{'Blue Heavy', 'Red Heavy'}**, Light source colour temperature. method : unicode, optional **{'MOVE', 'LRC'}**, Method to calculate the weighting factor. photopic_lef : SpectralDistribution, optional :math:`V(\\lambda)` photopic luminous efficiency function. scotopic_lef : SpectralDistribution, optional :math:`V^\\prime(\\lambda)` scotopic luminous efficiency function. Returns ------- SpectralDistribution Mesopic luminous efficiency function :math:`V_m(\\lambda)`. References ---------- :cite:`Wikipedia2005d` Examples -------- >>> from colour.utilities import numpy_print_options >>> with numpy_print_options(suppress=True): ... sd_mesopic_luminous_efficiency_function(0.2) # doctest: +ELLIPSIS SpectralDistribution([[ 380. , 0.000424 ...], [ 381. , 0.0004781...], [ 382. , 0.0005399...], [ 383. , 0.0006122...], [ 384. , 0.0006961...], [ 385. , 0.0007929...], [ 386. , 0.000907 ...], [ 387. , 0.0010389...], [ 388. , 0.0011923...], [ 389. , 0.0013703...], [ 390. , 0.0015771...], [ 391. , 0.0018167...], [ 392. , 0.0020942...], [ 393. , 0.0024160...], [ 394. , 0.0027888...], [ 395. , 0.0032196...], [ 396. , 0.0037222...], [ 397. , 0.0042957...], [ 398. , 0.0049531...], [ 399. , 0.0057143...], [ 400. , 0.0065784...], [ 401. , 0.0075658...], [ 402. , 0.0086912...], [ 403. , 0.0099638...], [ 404. , 0.0114058...], [ 405. , 0.0130401...], [ 406. , 0.0148750...], [ 407. , 0.0169310...], [ 408. , 0.0192211...], [ 409. , 0.0217511...], [ 410. , 0.0245342...], [ 411. , 0.0275773...], [ 412. , 0.0309172...], [ 413. , 0.0345149...], [ 414. , 0.0383998...], [ 415. , 0.0425744...], [ 416. , 0.0471074...], [ 417. , 0.0519322...], [ 418. , 0.0570541...], [ 419. , 0.0625466...], [ 420. , 0.0683463...], [ 421. , 0.0745255...], [ 422. , 0.0809440...], [ 423. , 0.0877344...], [ 424. , 0.0948915...], [ 425. , 0.1022731...], [ 426. , 0.109877 ...], [ 427. , 0.1178421...], [ 428. , 0.1260316...], [ 429. , 0.1343772...], [ 430. , 0.143017 ...], [ 431. , 0.1518128...], [ 432. , 0.1608328...], [ 433. , 0.1700088...], [ 434. , 0.1792726...], [ 435. , 0.1886934...], [ 436. , 0.1982041...], [ 437. , 0.2078032...], [ 438. , 0.2174184...], [ 439. , 0.2271147...], [ 440. , 0.2368196...], [ 441. , 0.2464623...], [ 442. , 0.2561153...], [ 443. , 0.2657160...], [ 444. , 0.2753387...], [ 445. , 0.2848520...], [ 446. , 0.2944648...], [ 447. , 0.3034902...], [ 448. , 0.3132347...], [ 449. , 0.3223257...], [ 450. , 0.3314513...], [ 451. , 0.3406129...], [ 452. , 0.3498117...], [ 453. , 0.3583617...], [ 454. , 0.3676377...], [ 455. , 0.3762670...], [ 456. , 0.3849392...], [ 457. , 0.3936540...], [ 458. , 0.4024077...], [ 459. , 0.4111965...], [ 460. , 0.4193298...], [ 461. , 0.4281803...], [ 462. , 0.4363804...], [ 463. , 0.4453117...], [ 464. , 0.4542949...], [ 465. , 0.4626509...], [ 466. , 0.4717570...], [ 467. , 0.4809300...], [ 468. , 0.4901776...], [ 469. , 0.4995075...], [ 470. , 0.5096145...], [ 471. , 0.5191293...], [ 472. , 0.5294259...], [ 473. , 0.5391316...], [ 474. , 0.5496217...], [ 475. , 0.5602103...], [ 476. , 0.5702197...], [ 477. , 0.5810207...], [ 478. , 0.5919093...], [ 479. , 0.6028683...], [ 480. , 0.6138806...], [ 481. , 0.6249373...], [ 482. , 0.6360619...], [ 483. , 0.6465989...], [ 484. , 0.6579538...], [ 485. , 0.6687841...], [ 486. , 0.6797939...], [ 487. , 0.6909887...], [ 488. , 0.7023827...], [ 489. , 0.7133032...], [ 490. , 0.7244513...], [ 491. , 0.7358470...], [ 492. , 0.7468118...], [ 493. , 0.7580294...], [ 494. , 0.7694964...], [ 495. , 0.7805225...], [ 496. , 0.7917805...], [ 497. , 0.8026123...], [ 498. , 0.8130793...], [ 499. , 0.8239297...], [ 500. , 0.8352251...], [ 501. , 0.8456342...], [ 502. , 0.8564818...], [ 503. , 0.8676921...], [ 504. , 0.8785021...], [ 505. , 0.8881489...], [ 506. , 0.8986405...], [ 507. , 0.9079322...], [ 508. , 0.9174255...], [ 509. , 0.9257739...], [ 510. , 0.9350656...], [ 511. , 0.9432365...], [ 512. , 0.9509063...], [ 513. , 0.9586931...], [ 514. , 0.9658413...], [ 515. , 0.9722825...], [ 516. , 0.9779924...], [ 517. , 0.9836106...], [ 518. , 0.9883465...], [ 519. , 0.9920964...], [ 520. , 0.9954436...], [ 521. , 0.9976202...], [ 522. , 0.9993457...], [ 523. , 1. ...], [ 524. , 0.9996498...], [ 525. , 0.9990487...], [ 526. , 0.9975356...], [ 527. , 0.9957615...], [ 528. , 0.9930143...], [ 529. , 0.9899559...], [ 530. , 0.9858741...], [ 531. , 0.9814453...], [ 532. , 0.9766885...], [ 533. , 0.9709363...], [ 534. , 0.9648947...], [ 535. , 0.9585832...], [ 536. , 0.952012 ...], [ 537. , 0.9444916...], [ 538. , 0.9367089...], [ 539. , 0.9293506...], [ 540. , 0.9210429...], [ 541. , 0.9124772...], [ 542. , 0.9036604...], [ 543. , 0.8945958...], [ 544. , 0.8845999...], [ 545. , 0.8750500...], [ 546. , 0.8659457...], [ 547. , 0.8559224...], [ 548. , 0.8456846...], [ 549. , 0.8352499...], [ 550. , 0.8253229...], [ 551. , 0.8152079...], [ 552. , 0.8042205...], [ 553. , 0.7944209...], [ 554. , 0.7837466...], [ 555. , 0.7735680...], [ 556. , 0.7627808...], [ 557. , 0.7522710...], [ 558. , 0.7417549...], [ 559. , 0.7312909...], [ 560. , 0.7207983...], [ 561. , 0.7101939...], [ 562. , 0.6996362...], [ 563. , 0.6890656...], [ 564. , 0.6785599...], [ 565. , 0.6680593...], [ 566. , 0.6575697...], [ 567. , 0.6471578...], [ 568. , 0.6368208...], [ 569. , 0.6264871...], [ 570. , 0.6161541...], [ 571. , 0.6058896...], [ 572. , 0.5957000...], [ 573. , 0.5855937...], [ 574. , 0.5754412...], [ 575. , 0.5653883...], [ 576. , 0.5553742...], [ 577. , 0.5454680...], [ 578. , 0.5355972...], [ 579. , 0.5258267...], [ 580. , 0.5160152...], [ 581. , 0.5062322...], [ 582. , 0.4965595...], [ 583. , 0.4868746...], [ 584. , 0.4773299...], [ 585. , 0.4678028...], [ 586. , 0.4583704...], [ 587. , 0.4489722...], [ 588. , 0.4397606...], [ 589. , 0.4306131...], [ 590. , 0.4215446...], [ 591. , 0.4125681...], [ 592. , 0.4037550...], [ 593. , 0.3950359...], [ 594. , 0.3864104...], [ 595. , 0.3778777...], [ 596. , 0.3694405...], [ 597. , 0.3611074...], [ 598. , 0.3528596...], [ 599. , 0.3447056...], [ 600. , 0.3366470...], [ 601. , 0.3286917...], [ 602. , 0.3208410...], [ 603. , 0.3130808...], [ 604. , 0.3054105...], [ 605. , 0.2978225...], [ 606. , 0.2903027...], [ 607. , 0.2828727...], [ 608. , 0.2755311...], [ 609. , 0.2682900...], [ 610. , 0.2611478...], [ 611. , 0.2541176...], [ 612. , 0.2471885...], [ 613. , 0.2403570...], [ 614. , 0.2336057...], [ 615. , 0.2269379...], [ 616. , 0.2203527...], [ 617. , 0.2138465...], [ 618. , 0.2073946...], [ 619. , 0.2009789...], [ 620. , 0.1945818...], [ 621. , 0.1881943...], [ 622. , 0.1818226...], [ 623. , 0.1754987...], [ 624. , 0.1692476...], [ 625. , 0.1630876...], [ 626. , 0.1570257...], [ 627. , 0.151071 ...], [ 628. , 0.1452469...], [ 629. , 0.1395845...], [ 630. , 0.1341087...], [ 631. , 0.1288408...], [ 632. , 0.1237666...], [ 633. , 0.1188631...], [ 634. , 0.1141075...], [ 635. , 0.1094766...], [ 636. , 0.1049613...], [ 637. , 0.1005679...], [ 638. , 0.0962924...], [ 639. , 0.0921296...], [ 640. , 0.0880778...], [ 641. , 0.0841306...], [ 642. , 0.0802887...], [ 643. , 0.0765559...], [ 644. , 0.0729367...], [ 645. , 0.0694345...], [ 646. , 0.0660491...], [ 647. , 0.0627792...], [ 648. , 0.0596278...], [ 649. , 0.0565970...], [ 650. , 0.0536896...], [ 651. , 0.0509068...], [ 652. , 0.0482444...], [ 653. , 0.0456951...], [ 654. , 0.0432510...], [ 655. , 0.0409052...], [ 656. , 0.0386537...], [ 657. , 0.0364955...], [ 658. , 0.0344285...], [ 659. , 0.0324501...], [ 660. , 0.0305579...], [ 661. , 0.0287496...], [ 662. , 0.0270233...], [ 663. , 0.0253776...], [ 664. , 0.0238113...], [ 665. , 0.0223226...], [ 666. , 0.0209086...], [ 667. , 0.0195688...], [ 668. , 0.0183056...], [ 669. , 0.0171216...], [ 670. , 0.0160192...], [ 671. , 0.0149986...], [ 672. , 0.0140537...], [ 673. , 0.0131784...], [ 674. , 0.0123662...], [ 675. , 0.0116107...], [ 676. , 0.0109098...], [ 677. , 0.0102587...], [ 678. , 0.0096476...], [ 679. , 0.0090665...], [ 680. , 0.0085053...], [ 681. , 0.0079567...], [ 682. , 0.0074229...], [ 683. , 0.0069094...], [ 684. , 0.0064213...], [ 685. , 0.0059637...], [ 686. , 0.0055377...], [ 687. , 0.0051402...], [ 688. , 0.00477 ...], [ 689. , 0.0044263...], [ 690. , 0.0041081...], [ 691. , 0.0038149...], [ 692. , 0.0035456...], [ 693. , 0.0032984...], [ 694. , 0.0030718...], [ 695. , 0.0028639...], [ 696. , 0.0026738...], [ 697. , 0.0025000...], [ 698. , 0.0023401...], [ 699. , 0.0021918...], [ 700. , 0.0020526...], [ 701. , 0.0019207...], [ 702. , 0.001796 ...], [ 703. , 0.0016784...], [ 704. , 0.0015683...], [ 705. , 0.0014657...], [ 706. , 0.0013702...], [ 707. , 0.001281 ...], [ 708. , 0.0011976...], [ 709. , 0.0011195...], [ 710. , 0.0010464...], [ 711. , 0.0009776...], [ 712. , 0.0009131...], [ 713. , 0.0008525...], [ 714. , 0.0007958...], [ 715. , 0.0007427...], [ 716. , 0.0006929...], [ 717. , 0.0006462...], [ 718. , 0.0006026...], [ 719. , 0.0005619...], [ 720. , 0.0005240...], [ 721. , 0.0004888...], [ 722. , 0.0004561...], [ 723. , 0.0004255...], [ 724. , 0.0003971...], [ 725. , 0.0003704...], [ 726. , 0.0003455...], [ 727. , 0.0003221...], [ 728. , 0.0003001...], [ 729. , 0.0002796...], [ 730. , 0.0002604...], [ 731. , 0.0002423...], [ 732. , 0.0002254...], [ 733. , 0.0002095...], [ 734. , 0.0001947...], [ 735. , 0.0001809...], [ 736. , 0.0001680...], [ 737. , 0.0001560...], [ 738. , 0.0001449...], [ 739. , 0.0001345...], [ 740. , 0.0001249...], [ 741. , 0.0001159...], [ 742. , 0.0001076...], [ 743. , 0.0000999...], [ 744. , 0.0000927...], [ 745. , 0.0000862...], [ 746. , 0.0000801...], [ 747. , 0.0000745...], [ 748. , 0.0000693...], [ 749. , 0.0000646...], [ 750. , 0.0000602...], [ 751. , 0.0000561...], [ 752. , 0.0000523...], [ 753. , 0.0000488...], [ 754. , 0.0000456...], [ 755. , 0.0000425...], [ 756. , 0.0000397...], [ 757. , 0.0000370...], [ 758. , 0.0000346...], [ 759. , 0.0000322...], [ 760. , 0.0000301...], [ 761. , 0.0000281...], [ 762. , 0.0000262...], [ 763. , 0.0000244...], [ 764. , 0.0000228...], [ 765. , 0.0000213...], [ 766. , 0.0000198...], [ 767. , 0.0000185...], [ 768. , 0.0000173...], [ 769. , 0.0000161...], [ 770. , 0.0000150...], [ 771. , 0.0000140...], [ 772. , 0.0000131...], [ 773. , 0.0000122...], [ 774. , 0.0000114...], [ 775. , 0.0000106...], [ 776. , 0.0000099...], [ 777. , 0.0000092...], [ 778. , 0.0000086...], [ 779. , 0.0000080...], [ 780. , 0.0000075...]], interpolator=SpragueInterpolator, interpolator_kwargs={}, extrapolator=Extrapolator, extrapolator_kwargs={...}) """ photopic_lef_shape = photopic_lef.shape scotopic_lef_shape = scotopic_lef.shape shape = SpectralShape( max(photopic_lef_shape.start, scotopic_lef_shape.start), min(photopic_lef_shape.end, scotopic_lef_shape.end), max(photopic_lef_shape.interval, scotopic_lef_shape.interval)) wavelengths = shape.range() sd_data = dict( zip( wavelengths, mesopic_weighting_function(wavelengths, Lp, source, method, photopic_lef, scotopic_lef))) sd = SpectralDistribution( sd_data, name='{0} Lp Mesopic Luminous Efficiency Function'.format(Lp)) return sd.normalise()