Spectral Dataset Authoring
What follows are recommendations from CIE 167:2005:
Colour implements the necessary algorithms for that. Taking the Sigma SD1 data Colour ships as an example, performing the necessary shape alignement is done as follows (Sprague (1880) interpolation + constant extrapolation here):
import numpy as np
from pprint import pprint
import colour
np.set_printoptions(formatter={'float': '{:0.13f}'.format})
s = colour.CAMERAS_RGB_SPECTRAL_SENSITIVITIES['Sigma SDMerill (NPL)'].clone()
s.align(colour.SpectralShape(380, 780, 5))
pprint(list(s.__iter__()))Which yields the following output:
[(380.0, array([0.0056210744061, 0.0063280975126, 0.1621594241331])),
(385.0, array([0.0056210744061, 0.0063280975126, 0.1621594241331])),
(390.0, array([0.0056210744061, 0.0063280975126, 0.1621594241331])),
(395.0, array([0.0056210744061, 0.0063280975126, 0.1621594241331])),
(400.0, array([0.0056210744061, 0.0063280975126, 0.1621594241331])),
(405.0, array([-0.0032700368303, 0.0078442533301, 0.2250353173349])),
(410.0, array([0.0065033562451, 0.0097618045959, 0.2854983780463])),
(415.0, array([0.0442283819610, 0.0131806655017, 0.3420658516161])),
(420.0, array([0.0740791128914, 0.0252717700826, 0.3969043106090])),
(425.0, array([0.0648965887945, 0.0511196177435, 0.4523066568906])),
(430.0, array([0.0430229594629, 0.0837511858531, 0.5083102431718])),
(435.0, array([0.0365119103882, 0.1177841176125, 0.5660109443506])),
(440.0, array([0.0345095256225, 0.1437038197436, 0.6221184724695])),
(445.0, array([0.0277755773805, 0.1499994509449, 0.6705963584656])),
(450.0, array([0.0188915672343, 0.1836116893088, 0.7374213624577])),
(455.0, array([0.0087091842944, 0.2908959273186, 0.8487572445276])),
(460.0, array([0.0073110769968, 0.4090947800995, 0.9453803667014])),
(465.0, array([0.0255319264136, 0.4749186195486, 0.9681955435635])),
(470.0, array([0.0454991512310, 0.5159556408618, 0.9644149477028])),
(475.0, array([0.0482549214709, 0.5601470746419, 0.9825808584722])),
(480.0, array([0.0567675292111, 0.6012066466271, 1.0000000000000])),
(485.0, array([0.0939903669557, 0.6358346290067, 0.9958859733900])),
(490.0, array([0.1341959206592, 0.6703167998014, 0.9859802118845])),
(495.0, array([0.1525425415604, 0.7092286996166, 0.9839327960640])),
(500.0, array([0.1647526899784, 0.7525874715348, 0.9834026635753])),
(505.0, array([0.1854871971303, 0.7997156914408, 0.9782595610813])),
(510.0, array([0.2171264197864, 0.8438138436894, 0.9696921956707])),
(515.0, array([0.2633216096660, 0.8785396570588, 0.9589265516683])),
(520.0, array([0.3064834383582, 0.9015172455881, 0.9428081740208])),
(525.0, array([0.3271741563823, 0.9102517532524, 0.9184303066263])),
(530.0, array([0.3498457961489, 0.9197503066877, 0.8966427991807])),
(535.0, array([0.3997744611751, 0.9456251404787, 0.8879120041536])),
(540.0, array([0.4437425813326, 0.9679942905216, 0.8844459022004])),
(545.0, array([0.4493050712078, 0.9672868230961, 0.8785909874648])),
(550.0, array([0.4448886052813, 0.9572523106404, 0.8679189907160])),
(555.0, array([0.4592810217596, 0.9510358717196, 0.8493389158543])),
(560.0, array([0.4789757567470, 0.9520479186005, 0.8337567958491])),
(565.0, array([0.4909632258899, 0.9644813612734, 0.8326564021678])),
(570.0, array([0.5095029148107, 0.9762801445840, 0.8320414024057])),
(575.0, array([0.5467826345353, 0.9738631672683, 0.8175566893965])),
(580.0, array([0.5926290937853, 0.9725862438896, 0.8005495638478])),
(585.0, array([0.6382726163130, 0.9881375121443, 0.7919209358203])),
(590.0, array([0.6738332756070, 1.0000000000000, 0.7828951247465])),
(595.0, array([0.6878419872290, 0.9881898311277, 0.7656981723603])),
(600.0, array([0.7140377148811, 0.9694845275778, 0.7394695300719])),
(605.0, array([0.7874464018679, 0.9607253897964, 0.7037118594951])),
(610.0, array([0.8600076131150, 0.9544131912485, 0.6671864017499])),
(615.0, array([0.8823124202958, 0.9431240656721, 0.6382091164523])),
(620.0, array([0.8981030284957, 0.9333543589092, 0.6204362780682])),
(625.0, array([0.9501811624820, 0.9299677091611, 0.6167230389669])),
(630.0, array([1.0000000000000, 0.9257140683364, 0.6111608787696])),
(635.0, array([1.0034835332372, 0.9081891683204, 0.5840987018028])),
(640.0, array([0.9949421331125, 0.8848643954150, 0.5517355619571])),
(645.0, array([1.0177594613772, 0.8716170685359, 0.5357897232403])),
(650.0, array([0.9208512773614, 0.7616518474162, 0.4653883174452])),
(655.0, array([0.5598719814695, 0.4526713639944, 0.2726189404614])),
(660.0, array([0.1814331163143, 0.1405243705715, 0.0796190783672])),
(665.0, array([0.0238842174801, 0.0145743920235, 0.0039086825328])),
(670.0, array([0.0063097879537, 0.0041436721582, 0.0005924444611])),
(675.0, array([0.0048726008643, 0.0034135547051, 0.0030414341659])),
(680.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(685.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(690.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(695.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(700.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(705.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(710.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(715.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(720.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(725.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(730.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(735.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(740.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(745.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(750.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(755.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(760.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(765.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(770.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(775.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048])),
(780.0, array([0.0052887438317, 0.0018319895817, 0.0046856368048]))]Retrieving the values should be even simpler, by calling colour.TriSpectralPowerDistribution.items method on latest develop branch.
- CIE TC 1-38. (2005). CIE 167:2005 Recommended Practice for Tabulating Spectral Data for Use in Colour Computations. ISBN:978-3-901-90641-1