From 80939997311a0a5837b017c7c194d1367f4d2d4d Mon Sep 17 00:00:00 2001
From: Matthew Trentacoste <trentaco@adobe.com>
Date: Tue, 22 Oct 2013 23:26:49 -0700
Subject: [PATCH 1/9] Luv colorspace conversions

Adding XYZ <--> Luv, RGB <-->
Adding test functions to mirror Lab tests
---
 skimage/color/__init__.py             |   4 +
 skimage/color/colorconv.py            | 191 ++++++++++++++++++++++++++
 skimage/color/tests/test_colorconv.py |  42 ++++++
 3 files changed, 237 insertions(+)

diff --git a/skimage/color/__init__.py b/skimage/color/__init__.py
index 1c61020d..a471fd82 100644
--- a/skimage/color/__init__.py
+++ b/skimage/color/__init__.py
@@ -13,6 +13,10 @@ from .colorconv import (convert_colorspace,
                         lab2xyz,
                         lab2rgb,
                         rgb2lab,
+                        xyz2luv,
+                        luv2xyz,
+                        luv2rgb,
+                        rgb2luv,
                         rgb2hed,
                         hed2rgb,
                         lab2lch,
diff --git a/skimage/color/colorconv.py b/skimage/color/colorconv.py
index 7562b650..cad4565e 100644
--- a/skimage/color/colorconv.py
+++ b/skimage/color/colorconv.py
@@ -849,6 +849,197 @@ def lab2rgb(lab):
     return xyz2rgb(lab2xyz(lab))
 
 
+def xyz2luv(xyz):
+    """XYZ to CIE-Luv color space conversion.
+
+    Parameters
+    ----------
+    xyz : array_like
+        The image in XYZ format, in a 3- or 4-D array of shape
+        (.., ..,[ ..,] 3).
+
+    Returns
+    -------
+    out : ndarray
+        The image in CIE-Luv format, in a 3- or 4-D array of shape
+        (.., ..,[ ..,] 3).
+
+    Raises
+    ------
+    ValueError
+        If `xyz` is not a 3-D array of shape (.., ..,[ ..,] 3).
+
+    Notes
+    -----
+    Observer= 2A, Illuminant= D65
+    CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883
+
+    References
+    ----------
+    .. [1] http://www.easyrgb.com/index.php?X=MATH&H=16#text16
+    .. [2] http://en.wikipedia.org/wiki/CIELUV
+
+    Examples
+    --------
+    >>> from skimage import data
+    >>> from skimage.color import rgb2xyz, xyz2luv
+    >>> lena = data.lena()
+    >>> lena_xyz = rgb2xyz(lena)
+    >>> lena_luv = xyz2luv(lena_xyz)
+    """
+    arr = _prepare_colorarray(xyz)  
+
+    # extract channels
+    x, y, z = arr[..., 0], arr[..., 1], arr[..., 2]
+
+    machineEps = np.finfo(np.float).eps
+
+    # compute y_r and L
+    L           = y / lab_ref_white[1]
+    mask        = L > 0.008856
+    L[mask]     = 116. * np.power( L[mask], 1. / 3. ) - 16.
+    L[~mask]    = 903.3 * L[~mask]
+
+    u0  = 4*lab_ref_white[0] / np.dot( [1, 15, 3], lab_ref_white )
+    v0  = 9*lab_ref_white[1] / np.dot( [1, 15, 3], lab_ref_white )
+
+    def div_nan_check( n, d ):
+        out = n / d
+        mask = np.isnan( out )
+        out[mask] = 0.
+        return out 
+
+    # u' and v' helper functions
+    def fu( X, Y, Z ):
+        return ( 4.*X ) / ( X + 15.*Y + 3.*Z + machineEps )
+    def fv( X, Y, Z ):
+        return ( 9.*Y ) / ( X + 15.*Y + 3.*Z + machineEps )
+
+    # compute u and v using helper functions
+    u = 13.*L * ( fu(x,y,z) - u0 )
+    v = 13.*L * ( fv(x,y,z) - v0 )
+
+    return np.concatenate([x[..., np.newaxis] for x in [L, u, v]], axis=-1)
+
+
+def luv2xyz(luv):
+    """CIE-LAB to XYZcolor space conversion.
+
+    Parameters
+    ----------
+    lab : array_like
+        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).
+
+    Raises
+    ------
+    ValueError
+        If `lab` is not a 3-D array of shape (.., .., 3).
+
+    Notes
+    -----
+    Observer= 2A, Illuminant= D65
+    CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883
+
+    References
+    ----------
+    .. [1] http://www.easyrgb.com/index.php?X=MATH&H=16#text16
+    .. [2] http://en.wikipedia.org/wiki/CIELUV
+
+    """
+
+    arr = _prepare_colorarray(luv).copy()
+
+    L, u, v = arr[:, :, 0], arr[:, :, 1], arr[:, :, 2]
+
+    machineEps = np.finfo(np.float).eps
+
+    # compute y
+    y = L.copy()
+    mask = y > 7.999625
+    y[mask] = np.power( (y[mask]+16.) / 116., 3.)
+    y[~mask] = y[~mask] / 903.3
+    y *= lab_ref_white[1]
+
+    # reference white x,z
+    uv_weights = [1, 15, 3]
+    u0  = 4*lab_ref_white[0] / np.dot( uv_weights, lab_ref_white )
+    v0  = 9*lab_ref_white[1] / np.dot( uv_weights, lab_ref_white )
+
+    def div_nan_check( n, d ):
+        out = n / d
+        mask = np.isnan( out )
+        out[mask] = 0.
+        return out 
+
+    # compute intermediate values
+    a = u0 + u / ( 13.*L + machineEps )
+    b = v0 + v / ( 13.*L + machineEps )
+    c = 3*y * (5*b-3)
+
+    # compute x and z
+    z = ( (a-4)*c - 15*a*b*y ) / ( 12*b )
+    x = -( c/b + 3.*z )
+
+    return np.concatenate([x[..., np.newaxis] for x in [x, y, z]], axis=-1)
+
+
+def rgb2luv(rgb):
+    """RGB to luv color space conversion.
+
+    Parameters
+    ----------
+    rgb : array_like
+        The image in RGB format, in a 3- or 4-D array of shape
+        (.., ..,[ ..,] 3).
+
+    Returns
+    -------
+    out : ndarray
+        The image in Luv format, in a 3- or 4-D array of shape
+        (.., ..,[ ..,] 3).
+
+    Raises
+    ------
+    ValueError
+        If `rgb` is not a 3- or 4-D array of shape (.., ..,[ ..,] 3).
+
+    Notes
+    -----
+    This function uses rgb2xyz and xyz2luv.
+    """
+    return xyz2luv(rgb2xyz(rgb))
+
+
+def luv2rgb(luv):
+    """Luv to RGB color space conversion.
+
+    Parameters
+    ----------
+    rgb : array_like
+        The image in Luv 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).
+
+    Raises
+    ------
+    ValueError
+        If `luv` is not a 3-D array of shape (.., .., 3).
+
+    Notes
+    -----
+    This function uses luv2xyz and xyz2rgb.
+    """
+    return xyz2rgb(luv2xyz(luv))
+
+
 def rgb2hed(rgb):
     """RGB to Haematoxylin-Eosin-DAB (HED) color space conversion.
 
diff --git a/skimage/color/tests/test_colorconv.py b/skimage/color/tests/test_colorconv.py
index fbec9ba6..26b55e35 100644
--- a/skimage/color/tests/test_colorconv.py
+++ b/skimage/color/tests/test_colorconv.py
@@ -33,6 +33,8 @@ from skimage.color import (rgb2hsv, hsv2rgb,
                            rgb2grey, gray2rgb,
                            xyz2lab, lab2xyz,
                            lab2rgb, rgb2lab,
+                           xyz2luv, luv2xyz,
+                           luv2rgb, rgb2luv,
                            is_rgb, is_gray,
                            lab2lch, lch2lab,
                            guess_spatial_dimensions
@@ -81,6 +83,13 @@ class TestColorconv(TestCase):
                     [[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
+        ])
+
     # RGB to HSV
     def test_rgb2hsv_conversion(self):
         rgb = img_as_float(self.img_rgb)[::16, ::16]
@@ -250,6 +259,39 @@ 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
+    # Note: easyrgb website displays xyz*100
+    def test_xyz2luv(self):
+        assert_array_almost_equal(xyz2luv(self.xyz_array),
+                                  self.luv_array, decimal=3)
+
+    def test_luv2xyz(self):
+        assert_array_almost_equal(luv2xyz(self.luv_array),
+                                  self.xyz_array, decimal=3)
+
+    def test_rgb2luv_brucelindbloom(self):
+        """
+        Test the RGB->Lab conversion by comparing to the calculator on the
+        authoritative Bruce Lindbloom
+        [website](http://brucelindbloom.com/index.html?ColorCalculator.html).
+        """
+        # Obtained with D65 white point, sRGB model and gamma
+        gt_for_colbars = np.array([
+            [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
+        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)
+
+    def test_luv_rgb_roundtrip(self):
+        img_rgb = img_as_float(self.img_rgb)
+        assert_array_almost_equal(luv2rgb(rgb2luv(img_rgb)), img_rgb)
+
     def test_lab_lch_roundtrip(self):
         rgb = img_as_float(self.img_rgb)
         lab = rgb2lab(rgb)

From 57eb69465c5d44bc2a51a1288429d5b76bfc09a9 Mon Sep 17 00:00:00 2001
From: Matthew Trentacoste <trentaco@adobe.com>
Date: Tue, 22 Oct 2013 23:29:51 -0700
Subject: [PATCH 2/9] Adding references regarding Lab and Luv spaces to
 docstring

---
 skimage/color/colorconv.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/skimage/color/colorconv.py b/skimage/color/colorconv.py
index cad4565e..97811bda 100644
--- a/skimage/color/colorconv.py
+++ b/skimage/color/colorconv.py
@@ -871,6 +871,12 @@ def xyz2luv(xyz):
 
     Notes
     -----
+    According to "Principles of Color Technology" by Roy S. Berns, it is a myth
+    that "CIELAB was recommended for large color differences and that CIELUV was 
+    recommended for small color differences."  It is also a myth that "CIELAB is 
+    recommended for reflecting samples while CIELUV is recommended for sources 
+    and displays."
+
     Observer= 2A, Illuminant= D65
     CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883
 

From 36e56e26394a5598718a1e4b2f894c33894653d7 Mon Sep 17 00:00:00 2001
From: Matthew Trentacoste <trentaco@adobe.com>
Date: Tue, 22 Oct 2013 23:33:38 -0700
Subject: [PATCH 3/9] Removing unneeded division checking code

---
 skimage/color/colorconv.py | 12 ------------
 1 file changed, 12 deletions(-)

diff --git a/skimage/color/colorconv.py b/skimage/color/colorconv.py
index 97811bda..bae63ac9 100644
--- a/skimage/color/colorconv.py
+++ b/skimage/color/colorconv.py
@@ -909,12 +909,6 @@ def xyz2luv(xyz):
     u0  = 4*lab_ref_white[0] / np.dot( [1, 15, 3], lab_ref_white )
     v0  = 9*lab_ref_white[1] / np.dot( [1, 15, 3], lab_ref_white )
 
-    def div_nan_check( n, d ):
-        out = n / d
-        mask = np.isnan( out )
-        out[mask] = 0.
-        return out 
-
     # u' and v' helper functions
     def fu( X, Y, Z ):
         return ( 4.*X ) / ( X + 15.*Y + 3.*Z + machineEps )
@@ -976,12 +970,6 @@ def luv2xyz(luv):
     u0  = 4*lab_ref_white[0] / np.dot( uv_weights, lab_ref_white )
     v0  = 9*lab_ref_white[1] / np.dot( uv_weights, lab_ref_white )
 
-    def div_nan_check( n, d ):
-        out = n / d
-        mask = np.isnan( out )
-        out[mask] = 0.
-        return out 
-
     # compute intermediate values
     a = u0 + u / ( 13.*L + machineEps )
     b = v0 + v / ( 13.*L + machineEps )

From 9d9d16d2a49b22114857548f2d1478fc833647be Mon Sep 17 00:00:00 2001
From: Matthew Trentacoste <trentaco@adobe.com>
Date: Tue, 22 Oct 2013 23:52:12 -0700
Subject: [PATCH 4/9] renaming machineEps to eps to match convention

---
 skimage/color/colorconv.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/skimage/color/colorconv.py b/skimage/color/colorconv.py
index bae63ac9..17ebd2bc 100644
--- a/skimage/color/colorconv.py
+++ b/skimage/color/colorconv.py
@@ -898,7 +898,7 @@ def xyz2luv(xyz):
     # extract channels
     x, y, z = arr[..., 0], arr[..., 1], arr[..., 2]
 
-    machineEps = np.finfo(np.float).eps
+    eps = np.finfo(np.float).eps
 
     # compute y_r and L
     L           = y / lab_ref_white[1]
@@ -911,9 +911,9 @@ def xyz2luv(xyz):
 
     # u' and v' helper functions
     def fu( X, Y, Z ):
-        return ( 4.*X ) / ( X + 15.*Y + 3.*Z + machineEps )
+        return ( 4.*X ) / ( X + 15.*Y + 3.*Z + eps )
     def fv( X, Y, Z ):
-        return ( 9.*Y ) / ( X + 15.*Y + 3.*Z + machineEps )
+        return ( 9.*Y ) / ( X + 15.*Y + 3.*Z + eps )
 
     # compute u and v using helper functions
     u = 13.*L * ( fu(x,y,z) - u0 )
@@ -956,7 +956,7 @@ def luv2xyz(luv):
 
     L, u, v = arr[:, :, 0], arr[:, :, 1], arr[:, :, 2]
 
-    machineEps = np.finfo(np.float).eps
+    eps = np.finfo(np.float).eps
 
     # compute y
     y = L.copy()
@@ -971,8 +971,8 @@ def luv2xyz(luv):
     v0  = 9*lab_ref_white[1] / np.dot( uv_weights, lab_ref_white )
 
     # compute intermediate values
-    a = u0 + u / ( 13.*L + machineEps )
-    b = v0 + v / ( 13.*L + machineEps )
+    a = u0 + u / ( 13.*L + eps )
+    b = v0 + v / ( 13.*L + eps )
     c = 3*y * (5*b-3)
 
     # compute x and z

From df6a112bc51256a16c1d50b1dd6579faefdeebe8 Mon Sep 17 00:00:00 2001
From: Matthew Trentacoste <trentaco@adobe.com>
Date: Wed, 23 Oct 2013 00:07:00 -0700
Subject: [PATCH 5/9] flake8-compliant formatting

---
 skimage/color/colorconv.py | 45 +++++++++++++++++++-------------------
 1 file changed, 23 insertions(+), 22 deletions(-)

diff --git a/skimage/color/colorconv.py b/skimage/color/colorconv.py
index 17ebd2bc..c15ccf02 100644
--- a/skimage/color/colorconv.py
+++ b/skimage/color/colorconv.py
@@ -893,7 +893,7 @@ def xyz2luv(xyz):
     >>> lena_xyz = rgb2xyz(lena)
     >>> lena_luv = xyz2luv(lena_xyz)
     """
-    arr = _prepare_colorarray(xyz)  
+    arr = _prepare_colorarray(xyz)
 
     # extract channels
     x, y, z = arr[..., 0], arr[..., 1], arr[..., 2]
@@ -901,25 +901,26 @@ def xyz2luv(xyz):
     eps = np.finfo(np.float).eps
 
     # compute y_r and L
-    L           = y / lab_ref_white[1]
-    mask        = L > 0.008856
-    L[mask]     = 116. * np.power( L[mask], 1. / 3. ) - 16.
-    L[~mask]    = 903.3 * L[~mask]
+    L = y / lab_ref_white[1]
+    mask = L > 0.008856
+    L[mask] = 116. * np.power(L[mask], 1. / 3.) - 16.
+    L[~mask] = 903.3 * L[~mask]
 
-    u0  = 4*lab_ref_white[0] / np.dot( [1, 15, 3], lab_ref_white )
-    v0  = 9*lab_ref_white[1] / np.dot( [1, 15, 3], lab_ref_white )
+    u0 = 4*lab_ref_white[0] / np.dot([1, 15, 3], lab_ref_white)
+    v0 = 9*lab_ref_white[1] / np.dot([1, 15, 3], lab_ref_white)
 
     # u' and v' helper functions
-    def fu( X, Y, Z ):
-        return ( 4.*X ) / ( X + 15.*Y + 3.*Z + eps )
-    def fv( X, Y, Z ):
-        return ( 9.*Y ) / ( X + 15.*Y + 3.*Z + eps )
+    def fu(X, Y, Z):
+        return (4.*X) / (X + 15.*Y + 3.*Z + eps)
+
+    def fv(X, Y, Z):
+        return (9.*Y) / (X + 15.*Y + 3.*Z + eps)
 
     # compute u and v using helper functions
-    u = 13.*L * ( fu(x,y,z) - u0 )
-    v = 13.*L * ( fv(x,y,z) - v0 )
+    u = 13.*L * (fu(x, y, z) - u0)
+    v = 13.*L * (fv(x, y, z) - v0)
 
-    return np.concatenate([x[..., np.newaxis] for x in [L, u, v]], axis=-1)
+    return np.concatenate([q[..., np.newaxis] for q in [L, u, v]], axis=-1)
 
 
 def luv2xyz(luv):
@@ -961,25 +962,25 @@ def luv2xyz(luv):
     # compute y
     y = L.copy()
     mask = y > 7.999625
-    y[mask] = np.power( (y[mask]+16.) / 116., 3.)
+    y[mask] = np.power((y[mask]+16.) / 116., 3.)
     y[~mask] = y[~mask] / 903.3
     y *= lab_ref_white[1]
 
     # reference white x,z
     uv_weights = [1, 15, 3]
-    u0  = 4*lab_ref_white[0] / np.dot( uv_weights, lab_ref_white )
-    v0  = 9*lab_ref_white[1] / np.dot( uv_weights, lab_ref_white )
+    u0 = 4*lab_ref_white[0] / np.dot(uv_weights, lab_ref_white)
+    v0 = 9*lab_ref_white[1] / np.dot(uv_weights, lab_ref_white)
 
     # compute intermediate values
-    a = u0 + u / ( 13.*L + eps )
-    b = v0 + v / ( 13.*L + eps )
+    a = u0 + u / (13.*L + eps)
+    b = v0 + v / (13.*L + eps)
     c = 3*y * (5*b-3)
 
     # compute x and z
-    z = ( (a-4)*c - 15*a*b*y ) / ( 12*b )
-    x = -( c/b + 3.*z )
+    z = ((a-4)*c - 15*a*b*y) / (12*b)
+    x = -(c/b + 3.*z)
 
-    return np.concatenate([x[..., np.newaxis] for x in [x, y, z]], axis=-1)
+    return np.concatenate([q[..., np.newaxis] for q in [x, y, z]], axis=-1)
 
 
 def rgb2luv(rgb):

From 44580817fcfdf1b59499fece18a390e0712692df Mon Sep 17 00:00:00 2001
From: Matthew Trentacoste <trentaco@adobe.com>
Date: Wed, 23 Oct 2013 12:42:40 -0700
Subject: [PATCH 6/9] Cleaning up docstrings

---
 skimage/color/colorconv.py | 8 +-------
 1 file changed, 1 insertion(+), 7 deletions(-)

diff --git a/skimage/color/colorconv.py b/skimage/color/colorconv.py
index c15ccf02..e40e9c55 100644
--- a/skimage/color/colorconv.py
+++ b/skimage/color/colorconv.py
@@ -871,12 +871,6 @@ def xyz2luv(xyz):
 
     Notes
     -----
-    According to "Principles of Color Technology" by Roy S. Berns, it is a myth
-    that "CIELAB was recommended for large color differences and that CIELUV was 
-    recommended for small color differences."  It is also a myth that "CIELAB is 
-    recommended for reflecting samples while CIELUV is recommended for sources 
-    and displays."
-
     Observer= 2A, Illuminant= D65
     CIE XYZ tristimulus values x_ref = 95.047, y_ref = 100., z_ref = 108.883
 
@@ -924,7 +918,7 @@ def xyz2luv(xyz):
 
 
 def luv2xyz(luv):
-    """CIE-LAB to XYZcolor space conversion.
+    """CIE-Luv to XYZcolor space conversion.
 
     Parameters
     ----------

From c05d18a0107757815680d87ff699cf51a6620a77 Mon Sep 17 00:00:00 2001
From: Matthew Trentacoste <trentaco@adobe.com>
Date: Wed, 23 Oct 2013 22:21:15 -0700
Subject: [PATCH 7/9] docstring changes to correctly format input/output,
 clarifying XYZ and reference white

---
 skimage/color/colorconv.py | 60 +++++++++++++++++++-------------------
 1 file changed, 30 insertions(+), 30 deletions(-)

diff --git a/skimage/color/colorconv.py b/skimage/color/colorconv.py
index e40e9c55..e7774003 100644
--- a/skimage/color/colorconv.py
+++ b/skimage/color/colorconv.py
@@ -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
     -----

From 888ef05b63a89627a474e11afca894aa350a1536 Mon Sep 17 00:00:00 2001
From: Matthew Trentacoste <trentaco@adobe.com>
Date: Wed, 23 Oct 2013 22:23:26 -0700
Subject: [PATCH 8/9] Adding note for Luv colorspace to top docstring

---
 skimage/color/colorconv.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/skimage/color/colorconv.py b/skimage/color/colorconv.py
index e7774003..39d35f56 100644
--- a/skimage/color/colorconv.py
+++ b/skimage/color/colorconv.py
@@ -29,6 +29,9 @@ Supported color spaces
 * LAB CIE : Lightness, a, b
         Colorspace derived from XYZ CIE that is intended to be more
         perceptually uniform
+* LUV CIE : Lightness, u, v
+        Colorspace derived from XYZ CIE that is intended to be more
+        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)

From 3dd1bc17949c507a61413c2d69c415de862fe5a3 Mon Sep 17 00:00:00 2001
From: Stefan van der Walt <stefan@sun.ac.za>
Date: Sun, 27 Oct 2013 22:06:13 +0200
Subject: [PATCH 9/9] Format color conversion docstrings.

---
 skimage/color/colorconv.py            | 146 +++++++++++++-------------
 skimage/color/tests/test_colorconv.py |  40 +++----
 2 files changed, 94 insertions(+), 92 deletions(-)

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)