wassname/scikit-image
1
0
Fork 0
mirror of https://github.com/wassname/scikit-image.git synced 2026-08-07 11:28:14 +08:00
Code Issues Packages Projects Releases Wiki Activity

docstring changes to correctly format input/output, clarifying XYZ and reference white

Browse Source
This commit is contained in:
Matthew Trentacoste
2013-10-23 22:21:15 -07:00
parent 44580817fc
commit c05d18a010
1 changed files with 30 additions and 30 deletions
Download Patch File Download Diff File Expand all files Collapse all files
skimage/color/colorconv.py
+30 -30
View File
@@ -854,25 +854,24 @@ def xyz2luv(xyz):
Parameters
----------
xyz : array_like
The image in XYZ format, in a 3- or 4-D array of shape
(.., ..,[ ..,] 3).
xyz : (M, N, [P,] 3) array_like
The 3 or 4 dimensional image in XYZ format. Final dimension denotes
channels.
Returns
-------
out : ndarray
The image in CIE-Luv format, in a 3- or 4-D array of shape
(.., ..,[ ..,] 3).
out : (M, N, [P,] 3) ndarray
The image in CIE-Luv format. Same dimensions as input.
Raises
------
ValueError
If `xyz` is not a 3-D array of shape (.., ..,[ ..,] 3).
If `xyz` is not a 3-D or 4-D array of shape `(M, N, [P,] 3)`.
Notes
-----
Observer= 2A, Illuminant= D65
CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883
XYZ conversion weights use Observer = 2A. Reference whitepoint for D65
Illuminant, with XYZ tristimulus values of `(95.047, 100., 108.883)`.
References
----------
@@ -918,27 +917,28 @@ def xyz2luv(xyz):
def luv2xyz(luv):
"""CIE-Luv to XYZcolor space conversion.
"""CIE-Luv to XYZ color space conversion.
Parameters
----------
lab : array_like
The image in lab format, in a 3-D array of shape (.., .., 3).
luv : (M, N, [P,] 3) array_like
The 3 or 4 dimensional image in CIE-Luv format. Final dimension denotes
channels.
Returns
-------
out : ndarray
The image in XYZ format, in a 3-D array of shape (.., .., 3).
out : (M, N, [P,] 3) ndarray
The image in XYZ format. Same dimensions as input.
Raises
------
ValueError
If `lab` is not a 3-D array of shape (.., .., 3).
If `luv` is not a 3-D or 4-D array of shape `(M, N, [P,] 3)`.
Notes
-----
Observer= 2A, Illuminant= D65
CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883
XYZ conversion weights use Observer = 2A. Reference whitepoint for D65
Illuminant, with XYZ tristimulus values of `(95.047, 100., 108.883)`.
References
----------
@@ -978,24 +978,23 @@ def luv2xyz(luv):
def rgb2luv(rgb):
"""RGB to luv color space conversion.
"""RGB to CIE-Luv color space conversion.
Parameters
----------
rgb : array_like
The image in RGB format, in a 3- or 4-D array of shape
(.., ..,[ ..,] 3).
rgb : (M, N, [P,] 3) array_like
The 3 or 4 dimensional image in RGB format. Final dimension denotes
channels.
Returns
-------
out : ndarray
The image in Luv format, in a 3- or 4-D array of shape
(.., ..,[ ..,] 3).
out : (M, N, [P,] 3) ndarray
The image in CIE Luv format. Same dimensions as input.
Raises
------
ValueError
If `rgb` is not a 3- or 4-D array of shape (.., ..,[ ..,] 3).
If `rgb` is not a 3-D or 4-D array of shape `(M, N, [P,] 3)`.
Notes
-----
@@ -1009,18 +1008,19 @@ def luv2rgb(luv):
Parameters
----------
rgb : array_like
The image in Luv format, in a 3-D array of shape (.., .., 3).
luv : (M, N, [P,] 3) array_like
The 3 or 4 dimensional image in CIE Luv format. Final dimension denotes
channels.
Returns
-------
out : ndarray
The image in RGB format, in a 3-D array of shape (.., .., 3).
out : (M, N, [P,] 3) ndarray
The image in RGB format. Same dimensions as input.
Raises
------
ValueError
If `luv` is not a 3-D array of shape (.., .., 3).
If `luv` is not a 3-D or 4-D array of shape `(M, N, [P,] 3)`.
Notes
-----