diff --git a/skimage/color/colorconv.py b/skimage/color/colorconv.py index 39d35f56..e2c7af17 100644 --- a/skimage/color/colorconv.py +++ b/skimage/color/colorconv.py @@ -34,7 +34,7 @@ Supported color spaces perceptually uniform * LCH CIE : Lightness, Chroma, Hue Defined in terms of LAB CIE. C and H are the polar representation of - a and b. The polar angle C is defined to be on (0, 2*pi) + a and b. The polar angle C is defined to be on ``(0, 2*pi)`` :author: Nicolas Pinto (rgb2hsv) :author: Ralf Gommers (hsv2rgb) @@ -71,7 +71,7 @@ def guess_spatial_dimensions(image): ------- spatial_dims : int or None The number of spatial dimensions of `image`. If ambiguous, the value - is `None`. + is ``None``. Raises ------ @@ -125,12 +125,12 @@ def convert_colorspace(arr, fromspace, tospace): The image to convert. fromspace : str The color space to convert from. Valid color space strings are - ['RGB', 'HSV', 'RGB CIE', 'XYZ']. Value may also be specified as lower - case. + ``['RGB', 'HSV', 'RGB CIE', 'XYZ']``. Value may also be specified as + lower case. tospace : str The color space to convert to. Valid color space strings are - ['RGB', 'HSV', 'RGB CIE', 'XYZ']. Value may also be specified as lower - case. + ``['RGB', 'HSV', 'RGB CIE', 'XYZ']``. Value may also be specified as + lower case. Returns ------- @@ -140,7 +140,7 @@ def convert_colorspace(arr, fromspace, tospace): Notes ----- Conversion occurs through the "central" RGB color space, i.e. conversion - from XYZ to HSV is implemented as XYZ -> RGB -> HSV instead of directly. + from XYZ to HSV is implemented as ``XYZ -> RGB -> HSV`` instead of directly. Examples -------- @@ -184,17 +184,17 @@ def rgb2hsv(rgb): Parameters ---------- rgb : array_like - The image in RGB format, in a 3-D array of shape (.., .., 3). + The image in RGB format, in a 3-D array of shape ``(.., .., 3)``. Returns ------- out : ndarray - The image in HSV format, in a 3-D array of shape (.., .., 3). + The image in HSV format, in a 3-D array of shape ``(.., .., 3)``. Raises ------ ValueError - If `rgb` is not a 3-D array of shape (.., .., 3). + If `rgb` is not a 3-D array of shape ``(.., .., 3)``. Notes ----- @@ -262,21 +262,21 @@ def hsv2rgb(hsv): Parameters ---------- hsv : array_like - The image in HSV format, in a 3-D array of shape (.., .., 3). + The image in HSV format, in a 3-D array of shape ``(.., .., 3)``. Returns ------- out : ndarray - The image in RGB format, in a 3-D array of shape (.., .., 3). + The image in RGB format, in a 3-D array of shape ``(.., .., 3)``. Raises ------ ValueError - If `hsv` is not a 3-D array of shape (.., .., 3). + If `hsv` is not a 3-D array of shape ``(.., .., 3)``. Notes ----- - The conversion assumes an input data range of [0, 1] for all + The conversion assumes an input data range of ``[0, 1]`` for all color components. Conversion between RGB and HSV color spaces results in some loss of @@ -471,17 +471,17 @@ def xyz2rgb(xyz): Parameters ---------- xyz : array_like - The image in XYZ format, in a 3-D array of shape (.., .., 3). + The image in XYZ format, in a 3-D array of shape ``(.., .., 3)``. Returns ------- out : ndarray - The image in RGB format, in a 3-D array of shape (.., .., 3). + The image in RGB format, in a 3-D array of shape ``(.., .., 3)``. Raises ------ ValueError - If `xyz` is not a 3-D array of shape (.., .., 3). + If `xyz` is not a 3-D array of shape ``(.., .., 3)``. Notes ----- @@ -516,18 +516,18 @@ def rgb2xyz(rgb): ---------- rgb : array_like The image in RGB format, in a 3- or 4-D array of shape - (.., ..,[ ..,] 3). + ``(.., ..,[ ..,] 3)``. Returns ------- out : ndarray The image in XYZ format, in a 3- or 4-D array of shape - (.., ..,[ ..,] 3). + ``(.., ..,[ ..,] 3)``. Raises ------ ValueError - If `rgb` is not a 3- or 4-D array of shape (.., ..,[ ..,] 3). + If `rgb` is not a 3- or 4-D array of shape ``(.., ..,[ ..,] 3)``. Notes ----- @@ -559,17 +559,17 @@ def rgb2rgbcie(rgb): Parameters ---------- rgb : array_like - The image in RGB format, in a 3-D array of shape (.., .., 3). + The image in RGB format, in a 3-D array of shape ``(.., .., 3)``. Returns ------- out : ndarray - The image in RGB CIE format, in a 3-D array of shape (.., .., 3). + The image in RGB CIE format, in a 3-D array of shape ``(.., .., 3)``. Raises ------ ValueError - If `rgb` is not a 3-D array of shape (.., .., 3). + If `rgb` is not a 3-D array of shape ``(.., .., 3)``. References ---------- @@ -591,17 +591,17 @@ def rgbcie2rgb(rgbcie): Parameters ---------- rgbcie : array_like - The image in RGB CIE format, in a 3-D array of shape (.., .., 3). + The image in RGB CIE format, in a 3-D array of shape ``(.., .., 3)``. Returns ------- out : ndarray - The image in RGB format, in a 3-D array of shape (.., .., 3). + The image in RGB format, in a 3-D array of shape ``(.., .., 3)``. Raises ------ ValueError - If `rgbcie` is not a 3-D array of shape (.., .., 3). + If `rgbcie` is not a 3-D array of shape ``(.., .., 3)``. References ---------- @@ -624,8 +624,8 @@ def rgb2gray(rgb): Parameters ---------- rgb : array_like - The image in RGB format, in a 3-D array of shape (.., .., 3), - or in RGBA format with shape (.., .., 4). + The image in RGB format, in a 3-D array of shape ``(.., .., 3)``, + or in RGBA format with shape ``(.., .., 4)``. Returns ------- @@ -635,8 +635,8 @@ def rgb2gray(rgb): Raises ------ ValueError - If `rgb2gray` is not a 3-D array of shape (.., .., 3) or - (.., .., 4). + If `rgb2gray` is not a 3-D array of shape ``(.., .., 3)`` or + ``(.., .., 4)``. References ---------- @@ -701,18 +701,18 @@ def xyz2lab(xyz): ---------- xyz : array_like The image in XYZ format, in a 3- or 4-D array of shape - (.., ..,[ ..,] 3). + ``(.., ..,[ ..,] 3)``. Returns ------- out : ndarray The image in CIE-LAB format, in a 3- or 4-D array of shape - (.., ..,[ ..,] 3). + ``(.., ..,[ ..,] 3)``. Raises ------ ValueError - If `xyz` is not a 3-D array of shape (.., ..,[ ..,] 3). + If `xyz` is not a 3-D array of shape ``(.., ..,[ ..,] 3)``. Notes ----- @@ -758,21 +758,21 @@ def lab2xyz(lab): Parameters ---------- lab : array_like - The image in lab format, in a 3-D array of shape (.., .., 3). + The image in lab format, in a 3-D array of shape ``(.., .., 3)``. Returns ------- out : ndarray - The image in XYZ format, in a 3-D array of shape (.., .., 3). + The image in XYZ format, in a 3-D array of shape ``(.., .., 3)``. Raises ------ ValueError - If `lab` is not a 3-D array of shape (.., .., 3). + If `lab` is not a 3-D array of shape ``(.., .., 3)``. Notes ----- - Observer= 2A, Illuminant= D65 + Observer = 2A, Illuminant = D65 CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883 References @@ -807,18 +807,18 @@ def rgb2lab(rgb): ---------- rgb : array_like The image in RGB format, in a 3- or 4-D array of shape - (.., ..,[ ..,] 3). + ``(.., ..,[ ..,] 3)``. Returns ------- out : ndarray The image in Lab format, in a 3- or 4-D array of shape - (.., ..,[ ..,] 3). + ``(.., ..,[ ..,] 3)``. Raises ------ ValueError - If `rgb` is not a 3- or 4-D array of shape (.., ..,[ ..,] 3). + If `rgb` is not a 3- or 4-D array of shape ``(.., ..,[ ..,] 3)``. Notes ----- @@ -833,17 +833,17 @@ def lab2rgb(lab): Parameters ---------- rgb : array_like - The image in Lab format, in a 3-D array of shape (.., .., 3). + The image in Lab format, in a 3-D array of shape ``(.., .., 3)``. Returns ------- out : ndarray - The image in RGB format, in a 3-D array of shape (.., .., 3). + The image in RGB format, in a 3-D array of shape ``(.., .., 3)``. Raises ------ ValueError - If `lab` is not a 3-D array of shape (.., .., 3). + If `lab` is not a 3-D array of shape ``(.., .., 3)``. Notes ----- @@ -858,7 +858,7 @@ def xyz2luv(xyz): Parameters ---------- xyz : (M, N, [P,] 3) array_like - The 3 or 4 dimensional image in XYZ format. Final dimension denotes + The 3 or 4 dimensional image in XYZ format. Final dimension denotes channels. Returns @@ -869,12 +869,12 @@ def xyz2luv(xyz): Raises ------ ValueError - If `xyz` is not a 3-D or 4-D array of shape `(M, N, [P,] 3)`. + If `xyz` is not a 3-D or 4-D array of shape ``(M, N, [P,] 3)``. Notes ----- - XYZ conversion weights use Observer = 2A. Reference whitepoint for D65 - Illuminant, with XYZ tristimulus values of `(95.047, 100., 108.883)`. + XYZ conversion weights use Observer = 2A. Reference whitepoint for D65 + Illuminant, with XYZ tristimulus values of ``(95.047, 100., 108.883)``. References ---------- @@ -936,12 +936,12 @@ def luv2xyz(luv): Raises ------ ValueError - If `luv` is not a 3-D or 4-D array of shape `(M, N, [P,] 3)`. + If `luv` is not a 3-D or 4-D array of shape ``(M, N, [P,] 3)``. Notes ----- - XYZ conversion weights use Observer = 2A. Reference whitepoint for D65 - Illuminant, with XYZ tristimulus values of `(95.047, 100., 108.883)`. + XYZ conversion weights use Observer = 2A. Reference whitepoint for D65 + Illuminant, with XYZ tristimulus values of ``(95.047, 100., 108.883)``. References ---------- @@ -986,7 +986,7 @@ def rgb2luv(rgb): Parameters ---------- rgb : (M, N, [P,] 3) array_like - The 3 or 4 dimensional image in RGB format. Final dimension denotes + The 3 or 4 dimensional image in RGB format. Final dimension denotes channels. Returns @@ -997,7 +997,7 @@ def rgb2luv(rgb): Raises ------ ValueError - If `rgb` is not a 3-D or 4-D array of shape `(M, N, [P,] 3)`. + If `rgb` is not a 3-D or 4-D array of shape ``(M, N, [P,] 3)``. Notes ----- @@ -1023,7 +1023,7 @@ def luv2rgb(luv): Raises ------ ValueError - If `luv` is not a 3-D or 4-D array of shape `(M, N, [P,] 3)`. + If `luv` is not a 3-D or 4-D array of shape ``(M, N, [P,] 3)``. Notes ----- @@ -1038,17 +1038,17 @@ def rgb2hed(rgb): Parameters ---------- rgb : array_like - The image in RGB format, in a 3-D array of shape (.., .., 3). + The image in RGB format, in a 3-D array of shape ``(.., .., 3)``. Returns ------- out : ndarray - The image in HED format, in a 3-D array of shape (.., .., 3). + The image in HED format, in a 3-D array of shape ``(.., .., 3)``. Raises ------ ValueError - If `rgb` is not a 3-D array of shape (.., .., 3). + If `rgb` is not a 3-D array of shape ``(.., .., 3)``. References @@ -1074,17 +1074,17 @@ def hed2rgb(hed): Parameters ---------- hed : array_like - The image in the HED color space, in a 3-D array of shape (.., .., 3). + The image in the HED color space, in a 3-D array of shape ``(.., .., 3)``. Returns ------- out : ndarray - The image in RGB, in a 3-D array of shape (.., .., 3). + The image in RGB, in a 3-D array of shape ``(.., .., 3)``. Raises ------ ValueError - If `hed` is not a 3-D array of shape (.., .., 3). + If `hed` is not a 3-D array of shape ``(.., .., 3)``. References ---------- @@ -1110,19 +1110,19 @@ def separate_stains(rgb, conv_matrix): Parameters ---------- rgb : array_like - The image in RGB format, in a 3-D array of shape (.., .., 3). + The image in RGB format, in a 3-D array of shape ``(.., .., 3)``. conv_matrix: ndarray The stain separation matrix as described by G. Landini [1]_. Returns ------- out : ndarray - The image in stain color space, in a 3-D array of shape (.., .., 3). + The image in stain color space, in a 3-D array of shape ``(.., .., 3)``. Raises ------ ValueError - If `rgb` is not a 3-D array of shape (.., .., 3). + If `rgb` is not a 3-D array of shape ``(.., .., 3)``. Notes ----- @@ -1164,19 +1164,19 @@ def combine_stains(stains, conv_matrix): Parameters ---------- stains : array_like - The image in stain color space, in a 3-D array of shape (.., .., 3). + The image in stain color space, in a 3-D array of shape ``(.., .., 3)``. conv_matrix: ndarray The stain separation matrix as described by G. Landini [1]_. Returns ------- out : ndarray - The image in RGB format, in a 3-D array of shape (.., .., 3). + The image in RGB format, in a 3-D array of shape ``(.., .., 3)``. Raises ------ ValueError - If `stains` is not a 3-D array of shape (.., .., 3). + If `stains` is not a 3-D array of shape ``(.., .., 3)``. Notes ----- @@ -1226,9 +1226,9 @@ def lab2lch(lab): Parameters ---------- lab : array_like - The N-D image in CIE-LAB format. The last (`N+1`th) dimension must have - at least 3 elements, corresponding to the ``L``, ``a``, and ``b`` color - channels. Subsequent elements are copied. + The N-D image in CIE-LAB format. The last (``N+1``-th) dimension must + have at least 3 elements, corresponding to the ``L``, ``a``, and ``b`` + color channels. Subsequent elements are copied. Returns ------- @@ -1242,7 +1242,7 @@ def lab2lch(lab): Notes ----- - The Hue is expressed as an angle between (0, 2*pi) + The Hue is expressed as an angle between ``(0, 2*pi)`` Examples -------- @@ -1262,7 +1262,7 @@ def lab2lch(lab): def _cart2polar_2pi(x, y): """convert cartesian coordiantes to polar (uses non-standard theta range!) - NON-STANDARD RANGE! Maps to (0, 2*pi) rather than usual (-pi, +pi) + NON-STANDARD RANGE! Maps to ``(0, 2*pi)`` rather than usual ``(-pi, +pi)`` """ r, t = np.hypot(x, y), np.arctan2(y, x) t += np.where(t < 0., 2 * np.pi, 0) @@ -1277,9 +1277,9 @@ def lch2lab(lch): Parameters ---------- lch : array_like - The N-D image in CIE-LCH format. The last (`N+1`th) dimension must have - at least 3 elements, corresponding to the ``L``, ``a``, and ``b`` color - channels. Subsequent elements are copied. + The N-D image in CIE-LCH format. The last (``N+1``-th) dimension must + have at least 3 elements, corresponding to the ``L``, ``a``, and ``b`` + color channels. Subsequent elements are copied. Returns ------- diff --git a/skimage/color/tests/test_colorconv.py b/skimage/color/tests/test_colorconv.py index 26b55e35..c7393355 100644 --- a/skimage/color/tests/test_colorconv.py +++ b/skimage/color/tests/test_colorconv.py @@ -71,24 +71,24 @@ class TestColorconv(TestCase): colbars_point75_array = np.swapaxes(colbars_point75.reshape(3, 4, 2), 0, 2) xyz_array = np.array([[[0.4124, 0.21260, 0.01930]], # red - [[0, 0, 0]], # black - [[.9505, 1., 1.089]], # white - [[.1805, .0722, .9505]], # blue - [[.07719, .15438, .02573]], # green - ]) + [[0, 0, 0]], # black + [[.9505, 1., 1.089]], # white + [[.1805, .0722, .9505]], # blue + [[.07719, .15438, .02573]], # green + ]) lab_array = np.array([[[53.233, 80.109, 67.220]], # red - [[0., 0., 0.]], # black - [[100.0, 0.005, -0.010]], # white - [[32.303, 79.197, -107.864]], # blue - [[46.229, -51.7, 49.898]], # green - ]) + [[0., 0., 0.]], # black + [[100.0, 0.005, -0.010]], # white + [[32.303, 79.197, -107.864]], # blue + [[46.229, -51.7, 49.898]], # green + ]) luv_array = np.array([[[53.233, 175.053, 37.751]], # red - [[0., 0., 0.]], # black - [[100., 0.001, -0.017]], # white - [[32.303, -9.400, -130.358]], # blue - [[46.228, -43.774, 56.589]], # green - ]) + [[0., 0., 0.]], # black + [[100., 0.001, -0.017]], # white + [[32.303, -9.400, -130.358]], # blue + [[46.228, -43.774, 56.589]], # green + ]) # RGB to HSV def test_rgb2hsv_conversion(self): @@ -259,7 +259,8 @@ class TestColorconv(TestCase): img_rgb = img_as_float(self.img_rgb) assert_array_almost_equal(lab2rgb(rgb2lab(img_rgb)), img_rgb) - # test matrices for xyz2luv and luv2xyz generated using http://www.easyrgb.com/index.php?X=CALC + # test matrices for xyz2luv and luv2xyz generated using + # http://www.easyrgb.com/index.php?X=CALC # Note: easyrgb website displays xyz*100 def test_xyz2luv(self): assert_array_almost_equal(xyz2luv(self.xyz_array), @@ -277,16 +278,17 @@ class TestColorconv(TestCase): """ # Obtained with D65 white point, sRGB model and gamma gt_for_colbars = np.array([ - [100,0,0], + [100, 0, 0], [97.1393, 7.7056, 106.7866], [91.1132, -70.4773, -15.2042], [87.7347, -83.0776, 107.3985], [60.3242, 84.0714, -108.6834], [53.2408, 175.0151, 37.7564], [32.2970, -9.4054, -130.3423], - [0,0,0]]).T + [0, 0, 0]]).T gt_array = np.swapaxes(gt_for_colbars.reshape(3, 4, 2), 0, 2) - assert_array_almost_equal(rgb2luv(self.colbars_array), gt_array, decimal=2) + assert_array_almost_equal(rgb2luv(self.colbars_array), + gt_array, decimal=2) def test_luv_rgb_roundtrip(self): img_rgb = img_as_float(self.img_rgb)