colour.volume Package

Module Contents

colour.volume.is_within_macadam_limits(xyY, illuminant, tolerance=None)[source]

Returns if given CIE xyY colourspace array is within MacAdam limits of given illuminant.

Parameters:
  • xyY (array_like) – CIE xyY colourspace array.
  • illuminant (unicode) – Illuminant.
  • tolerance (numeric, optional) – Tolerance allowed in the inside-triangle check.
Returns:

Is within MacAdam limits.

Return type:

bool

Notes

  • Input CIE xyY colourspace array is in domain [0, 1].

Examples

>>> is_within_macadam_limits(np.array([0.3205, 0.4131, 0.51]), 'A')
array(True, dtype=bool)
>>> a = np.array([[0.3205, 0.4131, 0.51],
...               [0.0005, 0.0031, 0.001]])
>>> is_within_macadam_limits(a, 'A')
array([ True, False], dtype=bool)
colour.volume.is_within_mesh_volume(points, mesh, tolerance=None)[source]

Returns if given points are within given mesh volume using Delaunay triangulation.

Parameters:
  • points (array_like) – Points to check if they are within mesh volume.
  • mesh (array_like) – Points of the volume used to generate the Delaunay triangulation.
  • tolerance (numeric, optional) – Tolerance allowed in the inside-triangle check.
Returns:

Is within mesh volume.

Return type:

bool

Examples

>>> mesh = np.array([[-1.0, -1.0, 1.0],
...                  [1.0, -1.0, 1.0],
...                  [1.0, -1.0, -1.0],
...                  [-1.0, -1.0, -1.0],
...                  [0.0, 1.0, 0.0]])
>>> is_within_mesh_volume(np.array([0.0005, 0.0031, 0.0010]), mesh)
array(True, dtype=bool)
>>> a = np.array([[0.0005, 0.0031, 0.0010],
...               [0.3205, 0.4131, 0.5100]])
>>> is_within_mesh_volume(a, mesh)
array([ True, False], dtype=bool)
colour.volume.is_within_pointer_gamut(XYZ, tolerance=None)[source]

Returns if given CIE XYZ tristimulus values are within Pointer’s Gamut volume.

Parameters:
  • XYZ (array_like) – CIE XYZ tristimulus values.
  • tolerance (numeric, optional) – Tolerance allowed in the inside-triangle check.
Returns:

Is within Pointer’s Gamut.

Return type:

bool

Notes

  • Input CIE XYZ tristimulus values are in domain [0, 1].

Examples

>>> import numpy as np
>>> is_within_pointer_gamut(np.array([0.3205, 0.4131, 0.5100]))
array(True, dtype=bool)
>>> a = np.array([[0.3205, 0.4131, 0.5100],
...               [0.0005, 0.0031, 0.0010]])
>>> is_within_pointer_gamut(a)
array([ True, False], dtype=bool)
colour.volume.is_within_visible_spectrum(XYZ, cmfs=XYZ_ColourMatchingFunctions( 'CIE 1931 2 Degree Standard Observer', {u'x_bar': {360.0: 0.0001299, 361.0: 0.000145847, 362.0: 0.0001638021, 363.0: 0.0001840037, 364.0: 0.0002066902, 365.0: 0.0002321, 366.0: 0.000260728, 367.0: 0.000293075, 368.0: 0.000329388, 369.0: 0.000369914, 370.0: 0.0004149, 371.0: 0.0004641587, 372.0: 0.000518986, 373.0: 0.000581854, 374.0: 0.0006552347, 375.0: 0.0007416, 376.0: 0.0008450296, 377.0: 0.0009645268, 378.0: 0.001094949, 379.0: 0.001231154, 380.0: 0.001368, 381.0: 0.00150205, 382.0: 0.001642328, 383.0: 0.001802382, 384.0: 0.001995757, 385.0: 0.002236, 386.0: 0.002535385, 387.0: 0.002892603, 388.0: 0.003300829, 389.0: 0.003753236, 390.0: 0.004243, 391.0: 0.004762389, 392.0: 0.005330048, 393.0: 0.005978712, 394.0: 0.006741117, 395.0: 0.00765, 396.0: 0.008751373, 397.0: 0.01002888, 398.0: 0.0114217, 399.0: 0.01286901, 400.0: 0.01431, 401.0: 0.01570443, 402.0: 0.01714744, 403.0: 0.01878122, 404.0: 0.02074801, 405.0: 0.02319, 406.0: 0.02620736, 407.0: 0.02978248, 408.0: 0.03388092, 409.0: 0.03846824, 410.0: 0.04351, 411.0: 0.0489956, 412.0: 0.0550226, 413.0: 0.0617188, 414.0: 0.069212, 415.0: 0.07763, 416.0: 0.08695811, 417.0: 0.09717672, 418.0: 0.1084063, 419.0: 0.1207672, 420.0: 0.13438, 421.0: 0.1493582, 422.0: 0.1653957, 423.0: 0.1819831, 424.0: 0.198611, 425.0: 0.21477, 426.0: 0.2301868, 427.0: 0.2448797, 428.0: 0.2587773, 429.0: 0.2718079, 430.0: 0.2839, 431.0: 0.2949438, 432.0: 0.3048965, 433.0: 0.3137873, 434.0: 0.3216454, 435.0: 0.3285, 436.0: 0.3343513, 437.0: 0.3392101, 438.0: 0.3431213, 439.0: 0.3461296, 440.0: 0.34828, 441.0: 0.3495999, 442.0: 0.3501474, 443.0: 0.350013, 444.0: 0.349287, 445.0: 0.34806, 446.0: 0.3463733, 447.0: 0.3442624, 448.0: 0.3418088, 449.0: 0.3390941, 450.0: 0.3362, 451.0: 0.3331977, 452.0: 0.3300411, 453.0: 0.3266357, 454.0: 0.3228868, 455.0: 0.3187, 456.0: 0.3140251, 457.0: 0.308884, 458.0: 0.3032904, 459.0: 0.2972579, 460.0: 0.2908, 461.0: 0.2839701, 462.0: 0.2767214, 463.0: 0.2689178, 464.0: 0.2604227, 465.0: 0.2511, 466.0: 0.2408475, 467.0: 0.2298512, 468.0: 0.2184072, 469.0: 0.2068115, 470.0: 0.19536, 471.0: 0.1842136, 472.0: 0.1733273, 473.0: 0.1626881, 474.0: 0.1522833, 475.0: 0.1421, 476.0: 0.1321786, 477.0: 0.1225696, 478.0: 0.1132752, 479.0: 0.1042979, 480.0: 0.09564, 481.0: 0.08729955, 482.0: 0.07930804, 483.0: 0.07171776, 484.0: 0.06458099, 485.0: 0.05795001, 486.0: 0.05186211, 487.0: 0.04628152, 488.0: 0.04115088, 489.0: 0.03641283, 490.0: 0.03201, 491.0: 0.0279172, 492.0: 0.0241444, 493.0: 0.020687, 494.0: 0.0175404, 495.0: 0.0147, 496.0: 0.01216179, 497.0: 0.00991996, 498.0: 0.00796724, 499.0: 0.006296346, 500.0: 0.0049, 501.0: 0.003777173, 502.0: 0.00294532, 503.0: 0.00242488, 504.0: 0.002236293, 505.0: 0.0024, 506.0: 0.00292552, 507.0: 0.00383656, 508.0: 0.00517484, 509.0: 0.00698208, 510.0: 0.0093, 511.0: 0.01214949, 512.0: 0.01553588, 513.0: 0.01947752, 514.0: 0.02399277, 515.0: 0.0291, 516.0: 0.03481485, 517.0: 0.04112016, 518.0: 0.04798504, 519.0: 0.05537861, 520.0: 0.06327, 521.0: 0.07163501, 522.0: 0.08046224, 523.0: 0.08973996, 524.0: 0.09945645, 525.0: 0.1096, 526.0: 0.1201674, 527.0: 0.1311145, 528.0: 0.1423679, 529.0: 0.1538542, 530.0: 0.1655, 531.0: 0.1772571, 532.0: 0.18914, 533.0: 0.2011694, 534.0: 0.2133658, 535.0: 0.2257499, 536.0: 0.2383209, 537.0: 0.2510668, 538.0: 0.2639922, 539.0: 0.2771017, 540.0: 0.2904, 541.0: 0.3038912, 542.0: 0.3175726, 543.0: 0.3314384, 544.0: 0.3454828, 545.0: 0.3597, 546.0: 0.3740839, 547.0: 0.3886396, 548.0: 0.4033784, 549.0: 0.4183115, 550.0: 0.4334499, 551.0: 0.4487953, 552.0: 0.464336, 553.0: 0.480064, 554.0: 0.4959713, 555.0: 0.5120501, 556.0: 0.5282959, 557.0: 0.5446916, 558.0: 0.5612094, 559.0: 0.5778215, 560.0: 0.5945, 561.0: 0.6112209, 562.0: 0.6279758, 563.0: 0.6447602, 564.0: 0.6615697, 565.0: 0.6784, 566.0: 0.6952392, 567.0: 0.7120586, 568.0: 0.7288284, 569.0: 0.7455188, 570.0: 0.7621, 571.0: 0.7785432, 572.0: 0.7948256, 573.0: 0.8109264, 574.0: 0.8268248, 575.0: 0.8425, 576.0: 0.8579325, 577.0: 0.8730816, 578.0: 0.8878944, 579.0: 0.9023181, 580.0: 0.9163, 581.0: 0.9297995, 582.0: 0.9427984, 583.0: 0.9552776, 584.0: 0.9672179, 585.0: 0.9786, 586.0: 0.9893856, 587.0: 0.9995488, 588.0: 1.0090892, 589.0: 1.0180064, 590.0: 1.0263, 591.0: 1.0339827, 592.0: 1.040986, 593.0: 1.047188, 594.0: 1.0524667, 595.0: 1.0567, 596.0: 1.0597944, 597.0: 1.0617992, 598.0: 1.0628068, 599.0: 1.0629096, 600.0: 1.0622, 601.0: 1.0607352, 602.0: 1.0584436, 603.0: 1.0552244, 604.0: 1.0509768, 605.0: 1.0456, 606.0: 1.0390369, 607.0: 1.0313608, 608.0: 1.0226662, 609.0: 1.0130477, 610.0: 1.0026, 611.0: 0.9913675, 612.0: 0.9793314, 613.0: 0.9664916, 614.0: 0.9528479, 615.0: 0.9384, 616.0: 0.923194, 617.0: 0.907244, 618.0: 0.890502, 619.0: 0.87292, 620.0: 0.8544499, 621.0: 0.835084, 622.0: 0.814946, 623.0: 0.794186, 624.0: 0.772954, 625.0: 0.7514, 626.0: 0.7295836, 627.0: 0.7075888, 628.0: 0.6856022, 629.0: 0.6638104, 630.0: 0.6424, 631.0: 0.6215149, 632.0: 0.6011138, 633.0: 0.5811052, 634.0: 0.5613977, 635.0: 0.5419, 636.0: 0.5225995, 637.0: 0.5035464, 638.0: 0.4847436, 639.0: 0.4661939, 640.0: 0.4479, 641.0: 0.4298613, 642.0: 0.412098, 643.0: 0.394644, 644.0: 0.3775333, 645.0: 0.3608, 646.0: 0.3444563, 647.0: 0.3285168, 648.0: 0.3130192, 649.0: 0.2980011, 650.0: 0.2835, 651.0: 0.2695448, 652.0: 0.2561184, 653.0: 0.2431896, 654.0: 0.2307272, 655.0: 0.2187, 656.0: 0.2070971, 657.0: 0.1959232, 658.0: 0.1851708, 659.0: 0.1748323, 660.0: 0.1649, 661.0: 0.1553667, 662.0: 0.14623, 663.0: 0.13749, 664.0: 0.1291467, 665.0: 0.1212, 666.0: 0.1136397, 667.0: 0.106465, 668.0: 0.09969044, 669.0: 0.09333061, 670.0: 0.0874, 671.0: 0.08190096, 672.0: 0.07680428, 673.0: 0.07207712, 674.0: 0.06768664, 675.0: 0.0636, 676.0: 0.05980685, 677.0: 0.05628216, 678.0: 0.05297104, 679.0: 0.04981861, 680.0: 0.04677, 681.0: 0.04378405, 682.0: 0.04087536, 683.0: 0.03807264, 684.0: 0.03540461, 685.0: 0.0329, 686.0: 0.03056419, 687.0: 0.02838056, 688.0: 0.02634484, 689.0: 0.02445275, 690.0: 0.0227, 691.0: 0.02108429, 692.0: 0.01959988, 693.0: 0.01823732, 694.0: 0.01698717, 695.0: 0.01584, 696.0: 0.01479064, 697.0: 0.01383132, 698.0: 0.01294868, 699.0: 0.0121292, 700.0: 0.01135916, 701.0: 0.01062935, 702.0: 0.009938846, 703.0: 0.009288422, 704.0: 0.008678854, 705.0: 0.008110916, 706.0: 0.007582388, 707.0: 0.007088746, 708.0: 0.006627313, 709.0: 0.006195408, 710.0: 0.005790346, 711.0: 0.005409826, 712.0: 0.005052583, 713.0: 0.004717512, 714.0: 0.004403507, 715.0: 0.004109457, 716.0: 0.003833913, 717.0: 0.003575748, 718.0: 0.003334342, 719.0: 0.003109075, 720.0: 0.002899327, 721.0: 0.002704348, 722.0: 0.00252302, 723.0: 0.002354168, 724.0: 0.002196616, 725.0: 0.00204919, 726.0: 0.00191096, 727.0: 0.001781438, 728.0: 0.00166011, 729.0: 0.001546459, 730.0: 0.001439971, 731.0: 0.001340042, 732.0: 0.001246275, 733.0: 0.001158471, 734.0: 0.00107643, 735.0: 0.0009999493, 736.0: 0.0009287358, 737.0: 0.0008624332, 738.0: 0.0008007503, 739.0: 0.000743396, 740.0: 0.0006900786, 741.0: 0.0006405156, 742.0: 0.0005945021, 743.0: 0.0005518646, 744.0: 0.000512429, 745.0: 0.0004760213, 746.0: 0.0004424536, 747.0: 0.0004115117, 748.0: 0.0003829814, 749.0: 0.0003566491, 750.0: 0.0003323011, 751.0: 0.0003097586, 752.0: 0.0002888871, 753.0: 0.0002695394, 754.0: 0.0002515682, 755.0: 0.0002348261, 756.0: 0.000219171, 757.0: 0.0002045258, 758.0: 0.0001908405, 759.0: 0.0001780654, 760.0: 0.0001661505, 761.0: 0.0001550236, 762.0: 0.0001446219, 763.0: 0.0001349098, 764.0: 0.000125852, 765.0: 0.000117413, 766.0: 0.0001095515, 767.0: 0.0001022245, 768.0: 9.539445e-05, 769.0: 8.90239e-05, 770.0: 8.307527e-05, 771.0: 7.751269e-05, 772.0: 7.231304e-05, 773.0: 6.745778e-05, 774.0: 6.292844e-05, 775.0: 5.870652e-05, 776.0: 5.477028e-05, 777.0: 5.109918e-05, 778.0: 4.767654e-05, 779.0: 4.448567e-05, 780.0: 4.150994e-05, 781.0: 3.873324e-05, 782.0: 3.614203e-05, 783.0: 3.372352e-05, 784.0: 3.146487e-05, 785.0: 2.935326e-05, 786.0: 2.737573e-05, 787.0: 2.552433e-05, 788.0: 2.379376e-05, 789.0: 2.21787e-05, 790.0: 2.067383e-05, 791.0: 1.927226e-05, 792.0: 1.79664e-05, 793.0: 1.674991e-05, 794.0: 1.561648e-05, 795.0: 1.455977e-05, 796.0: 1.357387e-05, 797.0: 1.265436e-05, 798.0: 1.179723e-05, 799.0: 1.099844e-05, 800.0: 1.025398e-05, 801.0: 9.559646e-06, 802.0: 8.912044e-06, 803.0: 8.308358e-06, 804.0: 7.745769e-06, 805.0: 7.221456e-06, 806.0: 6.732475e-06, 807.0: 6.276423e-06, 808.0: 5.851304e-06, 809.0: 5.455118e-06, 810.0: 5.085868e-06, 811.0: 4.741466e-06, 812.0: 4.420236e-06, 813.0: 4.120783e-06, 814.0: 3.841716e-06, 815.0: 3.581652e-06, 816.0: 3.339127e-06, 817.0: 3.112949e-06, 818.0: 2.902121e-06, 819.0: 2.705645e-06, 820.0: 2.522525e-06, 821.0: 2.351726e-06, 822.0: 2.192415e-06, 823.0: 2.043902e-06, 824.0: 1.905497e-06, 825.0: 1.776509e-06, 826.0: 1.656215e-06, 827.0: 1.544022e-06, 828.0: 1.43944e-06, 829.0: 1.341977e-06, 830.0: 1.251141e-06}, u'y_bar': {360.0: 3.917e-06, 361.0: 4.393581e-06, 362.0: 4.929604e-06, 363.0: 5.532136e-06, 364.0: 6.208245e-06, 365.0: 6.965e-06, 366.0: 7.813219e-06, 367.0: 8.767336e-06, 368.0: 9.839844e-06, 369.0: 1.104323e-05, 370.0: 1.239e-05, 371.0: 1.388641e-05, 372.0: 1.555728e-05, 373.0: 1.744296e-05, 374.0: 1.958375e-05, 375.0: 2.202e-05, 376.0: 2.483965e-05, 377.0: 2.804126e-05, 378.0: 3.153104e-05, 379.0: 3.521521e-05, 380.0: 3.9e-05, 381.0: 4.28264e-05, 382.0: 4.69146e-05, 383.0: 5.15896e-05, 384.0: 5.71764e-05, 385.0: 6.4e-05, 386.0: 7.234421e-05, 387.0: 8.221224e-05, 388.0: 9.350816e-05, 389.0: 0.0001061361, 390.0: 0.00012, 391.0: 0.000134984, 392.0: 0.000151492, 393.0: 0.000170208, 394.0: 0.000191816, 395.0: 0.000217, 396.0: 0.0002469067, 397.0: 0.00028124, 398.0: 0.00031852, 399.0: 0.0003572667, 400.0: 0.000396, 401.0: 0.0004337147, 402.0: 0.000473024, 403.0: 0.000517876, 404.0: 0.0005722187, 405.0: 0.00064, 406.0: 0.00072456, 407.0: 0.0008255, 408.0: 0.00094116, 409.0: 0.00106988, 410.0: 0.00121, 411.0: 0.001362091, 412.0: 0.001530752, 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653.0: 0.0, 654.0: 0.0, 655.0: 0.0, 656.0: 0.0, 657.0: 0.0, 658.0: 0.0, 659.0: 0.0, 660.0: 0.0, 661.0: 0.0, 662.0: 0.0, 663.0: 0.0, 664.0: 0.0, 665.0: 0.0, 666.0: 0.0, 667.0: 0.0, 668.0: 0.0, 669.0: 0.0, 670.0: 0.0, 671.0: 0.0, 672.0: 0.0, 673.0: 0.0, 674.0: 0.0, 675.0: 0.0, 676.0: 0.0, 677.0: 0.0, 678.0: 0.0, 679.0: 0.0, 680.0: 0.0, 681.0: 0.0, 682.0: 0.0, 683.0: 0.0, 684.0: 0.0, 685.0: 0.0, 686.0: 0.0, 687.0: 0.0, 688.0: 0.0, 689.0: 0.0, 690.0: 0.0, 691.0: 0.0, 692.0: 0.0, 693.0: 0.0, 694.0: 0.0, 695.0: 0.0, 696.0: 0.0, 697.0: 0.0, 698.0: 0.0, 699.0: 0.0, 700.0: 0.0, 701.0: 0.0, 702.0: 0.0, 703.0: 0.0, 704.0: 0.0, 705.0: 0.0, 706.0: 0.0, 707.0: 0.0, 708.0: 0.0, 709.0: 0.0, 710.0: 0.0, 711.0: 0.0, 712.0: 0.0, 713.0: 0.0, 714.0: 0.0, 715.0: 0.0, 716.0: 0.0, 717.0: 0.0, 718.0: 0.0, 719.0: 0.0, 720.0: 0.0, 721.0: 0.0, 722.0: 0.0, 723.0: 0.0, 724.0: 0.0, 725.0: 0.0, 726.0: 0.0, 727.0: 0.0, 728.0: 0.0, 729.0: 0.0, 730.0: 0.0, 731.0: 0.0, 732.0: 0.0, 733.0: 0.0, 734.0: 0.0, 735.0: 0.0, 736.0: 0.0, 737.0: 0.0, 738.0: 0.0, 739.0: 0.0, 740.0: 0.0, 741.0: 0.0, 742.0: 0.0, 743.0: 0.0, 744.0: 0.0, 745.0: 0.0, 746.0: 0.0, 747.0: 0.0, 748.0: 0.0, 749.0: 0.0, 750.0: 0.0, 751.0: 0.0, 752.0: 0.0, 753.0: 0.0, 754.0: 0.0, 755.0: 0.0, 756.0: 0.0, 757.0: 0.0, 758.0: 0.0, 759.0: 0.0, 760.0: 0.0, 761.0: 0.0, 762.0: 0.0, 763.0: 0.0, 764.0: 0.0, 765.0: 0.0, 766.0: 0.0, 767.0: 0.0, 768.0: 0.0, 769.0: 0.0, 770.0: 0.0, 771.0: 0.0, 772.0: 0.0, 773.0: 0.0, 774.0: 0.0, 775.0: 0.0, 776.0: 0.0, 777.0: 0.0, 778.0: 0.0, 779.0: 0.0, 780.0: 0.0, 781.0: 0.0, 782.0: 0.0, 783.0: 0.0, 784.0: 0.0, 785.0: 0.0, 786.0: 0.0, 787.0: 0.0, 788.0: 0.0, 789.0: 0.0, 790.0: 0.0, 791.0: 0.0, 792.0: 0.0, 793.0: 0.0, 794.0: 0.0, 795.0: 0.0, 796.0: 0.0, 797.0: 0.0, 798.0: 0.0, 799.0: 0.0, 800.0: 0.0, 801.0: 0.0, 802.0: 0.0, 803.0: 0.0, 804.0: 0.0, 805.0: 0.0, 806.0: 0.0, 807.0: 0.0, 808.0: 0.0, 809.0: 0.0, 810.0: 0.0, 811.0: 0.0, 812.0: 0.0, 813.0: 0.0, 814.0: 0.0, 815.0: 0.0, 816.0: 0.0, 817.0: 0.0, 818.0: 0.0, 819.0: 0.0, 820.0: 0.0, 821.0: 0.0, 822.0: 0.0, 823.0: 0.0, 824.0: 0.0, 825.0: 0.0, 826.0: 0.0, 827.0: 0.0, 828.0: 0.0, 829.0: 0.0, 830.0: 0.0}}, 'CIE 1931 2$^\circ$ Standard Observer'), tolerance=None)[source]

Returns if given CIE XYZ tristimulus values are within visible spectrum volume / given colour matching functions volume.

Parameters:
  • XYZ (array_like) – CIE XYZ tristimulus values.
  • cmfs (XYZ_ColourMatchingFunctions) – Standard observer colour matching functions.
  • tolerance (numeric, optional) – Tolerance allowed in the inside-triangle check.
Returns:

Is within visible spectrum.

Return type:

bool

Notes

  • Input CIE XYZ tristimulus values are in domain [0, 1].

Examples

>>> import numpy as np
>>> is_within_visible_spectrum(np.array([0.3205, 0.4131, 0.51]))
array(True, dtype=bool)
>>> a = np.array([[0.3205, 0.4131, 0.51],
...               [-0.0005, 0.0031, 0.001]])
>>> is_within_visible_spectrum(a)
array([ True, False], dtype=bool)
colour.volume.RGB_colourspace_limits(colourspace, illuminant=array([ 0.3457, 0.3585]))[source]

Computes given RGB colourspace volume limits in Lab colourspace.

Parameters:
  • colourspace (RGB_Colourspace) – RGB colourspace to compute the volume of.
  • illuminant (array_like, optional) – Lab colourspace illuminant chromaticity coordinates.
Returns:

RGB colourspace volume limits.

Return type:

ndarray

Examples

>>> from colour import sRGB_COLOURSPACE as sRGB
>>> RGB_colourspace_limits(sRGB)  
array([[   0...        ,  100.0000848...],
       [ -79.2197012...,   94.6760011...],
       [-114.7814393...,   96.7261797...]])
colour.volume.RGB_colourspace_volume_MonteCarlo(colourspace, samples=10000000.0, limits=array([[ 0, 100], [-150, 150], [-150, 150]]), illuminant_Lab=array([ 0.3457, 0.3585]), chromatic_adaptation_method=u'CAT02', random_generator=<function random_triplet_generator>, random_state=None, processes=None)[source]

Performs given RGB colourspace volume computation using Monte Carlo method and multiprocessing.

Parameters:
  • colourspace (RGB_Colourspace) – RGB colourspace to compute the volume of.
  • samples (numeric, optional) – Samples count.
  • limits (array_like, optional) – Lab colourspace volume.
  • illuminant_Lab (array_like, optional) – Lab colourspace illuminant chromaticity coordinates.
  • chromatic_adaptation_method (unicode, optional) – {‘CAT02’, ‘XYZ Scaling’, ‘Von Kries’, ‘Bradford’, ‘Sharp’, ‘Fairchild’, ‘CMCCAT97’, ‘CMCCAT2000’, ‘CAT02_BRILL_CAT’, ‘Bianco’, ‘Bianco PC’}, Chromatic adaptation method.
  • random_generator (generator, optional) – Random triplet generator providing the random samples within the Lab colourspace volume.
  • random_state (RandomState, optional) – Mersenne Twister pseudo-random number generator to use in the random number generator.
  • processes (integer, optional) – Processes count, default to multiprocessing.cpu_count() definition.
Returns:

RGB colourspace volume.

Return type:

float

Notes

Examples

>>> from colour import sRGB_COLOURSPACE as sRGB
>>> prng = np.random.RandomState(2)
>>> processes = 1
>>> RGB_colourspace_volume_MonteCarlo(  
...     sRGB, 10e3, random_state=prng, processes=processes)
858...
colour.volume.RGB_colourspace_volume_coverage_MonteCarlo(colourspace, coverage_sampler, samples=10000000.0, random_generator=<function random_triplet_generator>, random_state=None)[source]

Returns given RGB colourspace percentage coverage of an arbitrary volume.

Parameters:
  • colourspace (RGB_Colourspace) – RGB colourspace to compute the volume coverage percentage.
  • coverage_sampler (object) – Python object responsible for checking the volume coverage.
  • samples (numeric, optional) – Samples count.
  • random_generator (generator, optional) – Random triplet generator providing the random samples.
  • random_state (RandomState, optional) – Mersenne Twister pseudo-random number generator to use in the random number generator.
Returns:

Percentage coverage of volume.

Return type:

float

Examples

>>> from colour import sRGB_COLOURSPACE as sRGB
>>> prng = np.random.RandomState(2)
>>> RGB_colourspace_volume_coverage_MonteCarlo(  
...     sRGB,
...     is_within_pointer_gamut,
...     10e3,
...     random_state=prng)
83...
colour.volume.RGB_colourspace_pointer_gamut_coverage_MonteCarlo(colourspace, samples=10000000.0, random_generator=<function random_triplet_generator>, random_state=None)[source]

Returns given RGB colourspace percentage coverage of Pointer’s Gamut volume using Monte Carlo method.

Parameters:
  • colourspace (RGB_Colourspace) – RGB colourspace to compute the Pointer’s Gamut coverage percentage.
  • samples (numeric, optional) – Samples count.
  • random_generator (generator, optional) – Random triplet generator providing the random samples.
  • random_state (RandomState, optional) – Mersenne Twister pseudo-random number generator to use in the random number generator.
Returns:

Percentage coverage of Pointer’s Gamut volume.

Return type:

float

Examples

>>> from colour import sRGB_COLOURSPACE as sRGB
>>> prng = np.random.RandomState(2)
>>> RGB_colourspace_pointer_gamut_coverage_MonteCarlo(
...     sRGB,
...     10e3,
...     random_state=prng)  
83...
colour.volume.RGB_colourspace_visible_spectrum_coverage_MonteCarlo(colourspace, samples=10000000.0, random_generator=<function random_triplet_generator>, random_state=None)[source]

Returns given RGB colourspace percentage coverage of visible spectrum volume using Monte Carlo method.

Parameters:
  • colourspace (RGB_Colourspace) – RGB colourspace to compute the visible spectrum coverage percentage.
  • samples (numeric, optional) – Samples count.
  • random_generator (generator, optional) – Random triplet generator providing the random samples.
  • random_state (RandomState, optional) – Mersenne Twister pseudo-random number generator to use in the random number generator.
Returns:

Percentage coverage of visible spectrum volume.

Return type:

float

Examples

>>> from colour import sRGB_COLOURSPACE as sRGB
>>> prng = np.random.RandomState(2)
>>> RGB_colourspace_visible_spectrum_coverage_MonteCarlo(
...     sRGB,
...     10e3,
...     random_state=prng)  
36...