#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
RGB Colourspace Derivation
==========================
Defines objects related to *RGB* colourspace derivation, essentially
calculating the normalised primary matrix for given *RGB* colourspace primaries
and whitepoint.
See Also
--------
`RGB Colourspaces IPython Notebook
<http://nbviewer.ipython.org/github/colour-science/colour-ipython/blob/master/notebooks/models/rgb.ipynb>`_ # noqa
References
----------
.. [1] SMPTE. (1993). Derivation of Basic Television Color Equations. In
RP 177:1993 (Vol. RP 177:199). doi:10.5594/S9781614821915
"""
from __future__ import division, unicode_literals
import numpy as np
from colour.models import XYZ_to_xy, xy_to_XYZ
from colour.utilities import tsplit
__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013 - 2015 - Colour Developers'
__license__ = 'New BSD License - http://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = 'colour-science@googlegroups.com'
__status__ = 'Production'
__all__ = ['xy_to_z',
'normalised_primary_matrix',
'primaries_whitepoint',
'RGB_luminance_equation',
'RGB_luminance']
[docs]def xy_to_z(xy):
"""
Returns the *z* coordinate using given *xy* chromaticity coordinates.
Parameters
----------
xy : array_like
*xy* chromaticity coordinates.
Returns
-------
numeric
*z* coordinate.
Examples
--------
>>> xy_to_z(np.array([0.25, 0.25]))
0.5
"""
x, y = tsplit(xy)
z = 1 - x - y
return z
[docs]def normalised_primary_matrix(primaries, whitepoint):
"""
Returns the *normalised primary matrix* using given *primaries* and
*whitepoint*.
Parameters
----------
primaries : array_like, (3, 2)
Primaries chromaticity coordinates.
whitepoint : array_like
Illuminant / whitepoint chromaticity coordinates.
Returns
-------
ndarray, (3, 3)
*Normalised primary matrix*.
Examples
--------
>>> pms = np.array([0.73470, 0.26530, 0.00000, 1.00000, 0.00010, -0.07700])
>>> whitepoint = np.array([0.32168, 0.33767])
>>> normalised_primary_matrix(pms, whitepoint) # doctest: +ELLIPSIS
array([[ 9.5255239...e-01, 0.0000000...e+00, 9.3678631...e-05],
[ 3.4396645...e-01, 7.2816609...e-01, -7.2132546...e-02],
[ 0.0000000...e+00, 0.0000000...e+00, 1.0088251...e+00]])
"""
primaries = np.reshape(primaries, (3, 2))
z = xy_to_z(primaries)[..., np.newaxis]
primaries = np.transpose(np.hstack((primaries, z)))
whitepoint = xy_to_XYZ(whitepoint)
coefficients = np.dot(np.linalg.inv(primaries), whitepoint)
coefficients = np.diagflat(coefficients)
npm = np.dot(primaries, coefficients)
return npm
[docs]def primaries_whitepoint(npm):
"""
Returns *primaries* and *whitepoint* using given *normalised primary
matrix*.
Parameters
----------
npm : array_like, (3, 3)
*Normalised primary matrix*.
Returns
-------
tuple
*Primaries* and *whitepoint*.
References
----------
.. [2] Trieu, T. (2015). Private Discussion with Mansencal, T.
Examples
--------
>>> npm = np.array([[9.52552396e-01, 0.00000000e+00, 9.36786317e-05],
... [3.43966450e-01, 7.28166097e-01, -7.21325464e-02],
... [0.00000000e+00, 0.00000000e+00, 1.00882518e+00]])
>>> p, w = primaries_whitepoint(npm)
>>> p # doctest: +ELLIPSIS
array([[ 7.3470000...e-01, 2.6530000...e-01],
[ 0.0000000...e+00, 1.0000000...e+00],
[ 1.0000000...e-04, -7.7000000...e-02]])
>>> w # doctest: +ELLIPSIS
array([ 0.32168, 0.33767])
"""
npm = npm.reshape((3, 3))
primaries = XYZ_to_xy(
np.transpose(np.dot(npm, np.identity(3))))
whitepoint = np.squeeze(XYZ_to_xy(
np.transpose(np.dot(npm, np.ones((3, 1))))))
# TODO: Investigate if we return an ndarray here with primaries and
# whitepoint stacked together.
return primaries, whitepoint
[docs]def RGB_luminance_equation(primaries, whitepoint):
"""
Returns the *luminance equation* from given *primaries* and *whitepoint*.
Parameters
----------
primaries : array_like, (3, 2)
Primaries chromaticity coordinates.
whitepoint : array_like
Illuminant / whitepoint chromaticity coordinates.
Returns
-------
unicode
*Luminance* equation.
Examples
--------
>>> pms = np.array([0.73470, 0.26530, 0.00000, 1.00000, 0.00010, -0.07700])
>>> whitepoint = np.array([0.32168, 0.33767])
>>> # Doctests skip for Python 2.x compatibility.
>>> RGB_luminance_equation(pms, whitepoint) # doctest: +SKIP
'Y = 0.3439664...(R) + 0.7281660...(G) + -0.0721325...(B)'
"""
return 'Y = {0}(R) + {1}(G) + {2}(B)'.format(
*np.ravel(normalised_primary_matrix(primaries, whitepoint))[3:6])
[docs]def RGB_luminance(RGB, primaries, whitepoint):
"""
Returns the *luminance* :math:`Y` of given *RGB* components from given
*primaries* and *whitepoint*.
Parameters
----------
RGB : array_like
*RGB* chromaticity coordinate matrix.
primaries : array_like, (3, 2)
Primaries chromaticity coordinate matrix.
whitepoint : array_like
Illuminant / whitepoint chromaticity coordinates.
Returns
-------
numeric or ndarray
*Luminance* :math:`Y`.
Examples
--------
>>> RGB = np.array([40.6, 4.2, 67.4])
>>> pms = np.array([0.73470, 0.26530, 0.00000, 1.00000, 0.00010, -0.07700])
>>> whitepoint = np.array([0.32168, 0.33767])
>>> RGB_luminance(RGB, pms, whitepoint) # doctest: +ELLIPSIS
12.1616018...
"""
R, G, B = tsplit(RGB)
X, Y, Z = np.ravel(normalised_primary_matrix(primaries, whitepoint))[3:6]
L = X * R + Y * G + Z * B
return L
Colour 0.3