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use np.rollaxis

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Matt Terry
2013-07-24 08:07:14 -07:00
parent 1cd918e5c0
commit b566ba496b
1 changed files with 8 additions and 14 deletions
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skimage/color/delta_e.py
+8 -14
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@@ -28,12 +28,6 @@ import numpy as np
DEG = np.pi / 180
def _unpack_last(x):
x = np.asarray(x)
shape = x.shape
return [x[..., i] for i in range(shape[-1])]
def _arctan2pi(b, a):
"""np.arctan2 mapped to (0, 2 * pi)"""
ans = np.arctan2(b, a)
@@ -61,8 +55,8 @@ def deltaE_cie76(lab1, lab2):
http://en.wikipedia.org/wiki/Color_difference
A. R. Robertson, "The CIE 1976 color-difference formulae," Color Res. Appl. 2, 7-11 (1977).
"""
l1, a1, b1 = _unpack_last(lab1)
l2, a2, b2 = _unpack_last(lab2)
l1, a1, b1 = np.rollaxis(lab1, -1)[:3]
l2, a2, b2 = np.rollaxis(lab2, -1)[:3]
return np.sqrt((l2 - l1) ** 2 + (a2 - a1) ** 2 + (b2 - b1) ** 2)
@@ -115,8 +109,8 @@ def deltaE_ciede94(lab1, lab2, kH=1, kC=1, kL=1, k1=0.045, k2=0.015):
http://en.wikipedia.org/wiki/Color_difference
http://www.brucelindbloom.com/index.html?Eqn_DeltaE_CIE94.html
"""
l1, a1, b1 = _unpack_last(lab1)
l2, a2, b2 = _unpack_last(lab2)
l1, a1, b1 = np.rollaxis(lab1, -1)[:3]
l2, a2, b2 = np.rollaxis(lab2, -1)[:3]
dl = l1 - l2
c1 = np.sqrt(a1 ** 2 + b1 ** 2)
@@ -170,8 +164,8 @@ def deltaE_ciede2000(lab1, lab2, kL=1, kC=1, kH=1):
http://www.ece.rochester.edu/~gsharma/ciede2000/ciede2000noteCRNA.pdf (doi:10.1364/AO.33.008069)
M. Melgosa, J. Quesada, and E. Hita, "Uniformity of some recent color metrics tested with an accurate color-difference tolerance dataset," Appl. Opt. 33, 8069-8077 (1994).
"""
L1, a1, b1 = _unpack_last(lab1)
L2, a2, b2 = _unpack_last(lab2)
L1, a1, b1 = np.rollaxis(lab1, -1)[:3]
L2, a2, b2 = np.rollaxis(lab2, -1)[:3]
c1 = np.sqrt(a1 ** 2 + b1 ** 2)
c2 = np.sqrt(a2 ** 2 + b2 ** 2)
@@ -280,8 +274,8 @@ def deltaE_cmc(lab1, lab2, kL=1, kC=1):
http://www.brucelindbloom.com/index.html?Eqn_DeltaE_CIE94.html
F. J. J. Clarke, R. McDonald, and B. Rigg, "Modification to the JPC79 colour-difference formula," J. Soc. Dyers Colour. 100, 128-132 (1984).
"""
l1, a1, b1 = _unpack_last(lab1)
l2, a2, b2 = _unpack_last(lab2)
l1, a1, b1 = np.rollaxis(lab1, -1)[:3]
l2, a2, b2 = np.rollaxis(lab2, -1)[:3]
c1 = np.sqrt(a1 ** 2 + b1 ** 2)
c2 = np.sqrt(a2 ** 2 + b2 ** 2)