@@ -1351,10 +1351,10 @@ def __call__(self, X, alpha=None, bytes=False, clip=True):
13511351 if alpha is not None :
13521352 if clip :
13531353 alpha = np .clip (alpha , 0 , 1 )
1354- if alpha .shape not in np .array (X [0 ]). shape ]:
1354+ if np .shape ( alpha ) not in np .shape (X [0 ])]:
13551355 raise ValueError (
1356- f"alpha is array-like but its shape { alpha .shape }
1357- f"not match that of X[0] { np .array (X [0 ]). shape } )
1356+ f"alpha is array-like but its shape { np .shape ( alpha ) }
1357+ f"not match that of X[0] { np .shape (X [0 ])} )
13581358 rgba [..., - 1 ] *= alpha
13591359
13601360 if bytes :
@@ -1385,14 +1385,14 @@ def __copy__(self):
13851385 def __eq__ (self , other ):
13861386 if not isinstance (other , MultivarColormap ):
13871387 return False
1388- if not len (self ) = =len (other ):
1388+ if len (self ) ! =len (other ):
13891389 return False
13901390 for c0 , c1 in zip (self , other ):
1391- if not c0 = =c1 :
1391+ if c0 ! =c1 :
13921392 return False
13931393 if not all (self ._rgba_bad == other ._rgba_bad ):
13941394 return False
1395- if not self .combination_mode = =other .combination_mode :
1395+ if self .combination_mode ! =other .combination_mode :
13961396 return False
13971397 return True
13981398
@@ -1430,7 +1430,7 @@ def resampled(self, lutshape):
14301430 MultivarColormap
14311431 """
14321432
1433- if not np .iterable (lutshape ) or not len (lutshape ) = =len (self ):
1433+ if not np .iterable (lutshape ) or len (lutshape ) ! =len (self ):
14341434 raise ValueError (f"lutshape must be of length { len (self )} )
14351435 new_cmap = self .copy ()
14361436 for i , s in enumerate (lutshape ):
@@ -1447,7 +1447,7 @@ def with_extremes(self, *, bad=None, under=None, over=None):
14471447
14481448 Parameters
14491449 ----------
1450- bad : None or Matplotlib color
1450+ bad : None or :mpltype:` color`
14511451 If Matplotlib color, the bad value is set accordingly in the copy
14521452
14531453 under : None or tuple of length matching the length of the MultivarColormap
@@ -1468,17 +1468,19 @@ def with_extremes(self, *, bad=None, under=None, over=None):
14681468 if bad is not None :
14691469 new_cm ._rgba_bad = to_rgba (bad )
14701470 if under is not None :
1471- if not np .iterable (under ) or not len (under ) = =len (new_cm ):
1471+ if not np .iterable (under ) or len (under ) ! =len (new_cm ):
14721472 raise ValueError ("*under* must contain a color for each scalar colormap"
14731473 f" i.e. be of length { len (new_cm )} )
14741474 else :
1475- [c .set_under (b ) for c , b in zip (new_cm , under )]
1475+ for c , b in zip (new_cm , under ):
1476+ c .set_under (b )
14761477 if over is not None :
1477- if not np .iterable (over ) or not len (over ) = =len (new_cm ):
1478+ if not np .iterable (over ) or len (over ) ! =len (new_cm ):
14781479 raise ValueError ("*over* must contain a color for each scalar colormap"
14791480 f" i.e. be of length { len (new_cm )} )
14801481 else :
1481- [c .set_over (b ) for c , b in zip (new_cm , over )]
1482+ for c , b in zip (new_cm , over ):
1483+ c .set_over (b )
14821484 return new_cm
14831485
14841486 @property
@@ -1511,9 +1513,9 @@ def _repr_html_(self):
15111513
15121514class BivarColormap :
15131515 """
1514- Baseclass for all bivarate to RGBA mappings.
1516+ Base class for all bivariate to RGBA mappings.
15151517
1516- Designed as a drop-in replcement for Colormap when using a 2D
1518+ Designed as a drop-in replacement for Colormap when using a 2D
15171519 lookup table. To be used with `~matplotlib.cm.VectorMappable`.
15181520 """
15191521
@@ -1527,7 +1529,7 @@ def __init__(self, N=256, M=256, shape='square', origin=(0, 0),
15271529 M : int
15281530 The number of RGB quantization levels along the second axis.
15291531 If None, M = N
1530- shape: str 'square' or 'circle' or 'ignore' or 'circleignore'
1532+ shape: { 'square', 'circle', 'ignore', 'circleignore'}
15311533
15321534 - 'square' each variate is clipped to [0,1] independently
15331535 - 'circle' the variates are clipped radially to the center
@@ -1594,7 +1596,7 @@ def __call__(self, X, alpha=None, bytes=False):
15941596 if len (X ) != 2 :
15951597 raise ValueError (
15961598 f'For a `BivarColormap` the data must have a first dimension '
1597- f'{ 2 } { len (X )} )
1599+ f'2 , not { len (X )} )
15981600
15991601 if not self ._isinit :
16001602 self ._init ()
@@ -1621,8 +1623,7 @@ def __call__(self, X, alpha=None, bytes=False):
16211623 X1 [X1 == self .M ] = self .M - 1
16221624
16231625 # Pre-compute the masks before casting to int (which can truncate)
1624- mask_outside = (X0 < 0 ) | (X1 < 0 ) \
1625- | (X0 >= self .N ) | (X1 >= self .M )
1626+ mask_outside = (X0 < 0 ) | (X1 < 0 ) | (X0 >= self .N ) | (X1 >= self .M )
16261627 # If input was masked, get the bad mask from it; else mask out nans.
16271628 mask_bad_0 = X0 .mask if np .ma .is_masked (X0 ) else np .isnan (X0 )
16281629 mask_bad_1 = X1 .mask if np .ma .is_masked (X1 ) else np .isnan (X1 )
@@ -1650,10 +1651,10 @@ def __call__(self, X, alpha=None, bytes=False):
16501651 alpha = np .clip (alpha , 0 , 1 )
16511652 if bytes :
16521653 alpha *= 255 # Will be cast to uint8 upon assignment.
1653- if alpha .shape not in np .array (X0 ). shape ]:
1654+ if np .shape ( alpha ) not in np .shape (X0 )]:
16541655 raise ValueError (
1655- f"alpha is array-like but its shape { alpha .shape }
1656- f"not match that of X[0] { np .array (X0 ). shape } )
1656+ f"alpha is array-like but its shape { np .shape ( alpha ) }
1657+ f"not match that of X[0] { np .shape (X0 )} )
16571658 rgba [..., - 1 ] = alpha
16581659 # If the "bad" color is all zeros, then ignore alpha input.
16591660 if (np .array (self ._rgba_bad ) == 0 ).all ():
@@ -1713,7 +1714,7 @@ def __eq__(self, other):
17131714 return False
17141715 if not np .array_equal (self ._rgba_outside , other ._rgba_outside ):
17151716 return False
1716- if not self .shape = =other .shape :
1717+ if self .shape ! =other .shape :
17171718 return False
17181719 return True
17191720
@@ -1728,6 +1729,7 @@ def get_outside(self):
17281729 def resampled (self , lutshape , transposed = False ):
17291730 """
17301731 Return a new colormap with *lutshape* entries.
1732+
17311733 Note that this function does not move the origin.
17321734
17331735 Parameters
@@ -1748,7 +1750,7 @@ def resampled(self, lutshape, transposed=False):
17481750 BivarColormap
17491751 """
17501752
1751- if not np .iterable (lutshape ) or not len (lutshape ) = =2 :
1753+ if not np .iterable (lutshape ) or len (lutshape ) ! =2 :
17521754 raise ValueError ("lutshape must be of length 2" )
17531755 lutshape = [lutshape [0 ], lutshape [1 ]]
17541756 if lutshape [0 ] is None or lutshape [0 ] == 1 :
@@ -1776,7 +1778,7 @@ def resampled(self, lutshape, transposed=False):
17761778 else :
17771779 x_1 = np .linspace (1 , 0 , lutshape [1 ])[np .newaxis , :] * np .ones (lutshape )
17781780
1779- # we need to use shape = 'sqare ' while resampling the colormap.
1781+ # we need to use shape = 'square ' while resampling the colormap.
17801782 # if the colormap has shape = 'circle' we would otherwise get *outside* in the
17811783 # resampled colormap
17821784 shape_memory = self ._shape
@@ -1785,7 +1787,7 @@ def resampled(self, lutshape, transposed=False):
17851787 new_lut = self ((x_1 , x_0 ))
17861788 new_cmap = BivarColormapFromImage (new_lut , name = self .name ,
17871789 shape = shape_memory ,
1788- origin = ( self .origin [1 ], self . origin [ 0 ]) )
1790+ origin = self .origin [:: - 1 ] )
17891791 else :
17901792 new_lut = self ((x_0 , x_1 ))
17911793 new_cmap = BivarColormapFromImage (new_lut , name = self .name ,
@@ -1801,12 +1803,8 @@ def reversed(self, axis_0=True, axis_1=True):
18011803 """
18021804 Reverses both or one of the axis.
18031805 """
1804- r_0 = 1
1805- if axis_0 :
1806- r_0 = - 1
1807- r_1 = 1
1808- if axis_1 :
1809- r_1 = - 1
1806+ r_0 = - 1 if axis_0 else 1
1807+ r_1 = - 1 if axis_1 else 1
18101808 return self .resampled ((r_0 , r_1 ))
18111809
18121810 def transposed (self ):
@@ -1823,22 +1821,22 @@ def with_extremes(self, *, bad=None, outside=None, shape=None, origin=None):
18231821
18241822 Parameters
18251823 ----------
1826- bad : None or Matplotlib color
1824+ bad : None or :mpltype:` color`
18271825 If Matplotlib color, the *bad* value is set accordingly in the copy
18281826
1829- outside : None or Matplotlib color
1827+ outside : None or :mpltype:` color`
18301828 If Matplotlib color and shape is 'ignore' or 'circleignore', values
18311829 *outside* the colormap are colored accordingly in the copy
18321830
1833- shape: str 'square' or 'circle' or 'ignore' or 'circleignore'
1831+ shape : { 'square', 'circle', 'ignore', 'circleignore'}
18341832
18351833 - If 'square' each variate is clipped to [0,1] independently
18361834 - If 'circle' the variates are clipped radially to the center
18371835 of the colormap, and a circular mask is applied when the colormap
18381836 is displayed
18391837 - If 'ignore' the variates are not clipped, but instead assigned the
18401838 *outside* color
1841- - If 'circleignore' a circular mask is applied, but the data is not
1839+ - If 'circleignore' a circular mask is applied, but the data is not
18421840 clipped and instead assigned the *outside* color
18431841
18441842 origin: (float, float)
@@ -1890,7 +1888,7 @@ def _clip(self, X):
18901888 ----------
18911889 X: np.array
18921890 array of floats or ints to be clipped
1893- shape: str 'square' or 'circle' or 'ignore' or 'circleignore'
1891+ shape : { 'square', 'circle', 'ignore', 'circleignore'}
18941892
18951893 - If 'square' each variate is clipped to [0,1] independently
18961894 - If 'circle' the variates are clipped radially to the center
@@ -1921,7 +1919,7 @@ def _clip(self, X):
19211919
19221920 elif self .shape == 'circle' or self .shape == 'circleignore' :
19231921 for X_part in X :
1924- if not X_part .dtype .kind = ="f" :
1922+ if X_part .dtype .kind ! ="f" :
19251923 raise NotImplementedError (
19261924 "Circular bivariate colormaps are only"
19271925 " implemented for use with with floats" )
@@ -1944,14 +1942,14 @@ def __getitem__(self, item):
19441942 if origin_1_as_int > self .M - 1 :
19451943 origin_1_as_int = self .M - 1
19461944 one_d_lut = self ._lut [:, origin_1_as_int ]
1947- new_cmap = ListedColormap (one_d_lut , name = self .name + ' _0'N = self .N )
1945+ new_cmap = ListedColormap (one_d_lut , name = f' { self .name } N = self .N )
19481946
19491947 elif item == 1 :
19501948 origin_0_as_int = int (self ._origin [0 ]* self .N )
19511949 if origin_0_as_int > self .N - 1 :
19521950 origin_0_as_int = self .N - 1
19531951 one_d_lut = self ._lut [origin_0_as_int , :]
1954- new_cmap = ListedColormap (one_d_lut , name = self .name + ' _1'N = self .M )
1952+ new_cmap = ListedColormap (one_d_lut , name = f' { self .name } N = self .M )
19551953 else :
19561954 raise KeyError (f"only 0 or 1 are"
19571955 f" valid keys for BivarColormap, not { item !r} )
@@ -2025,15 +2023,15 @@ def copy(self):
20252023
20262024class SegmentedBivarColormap (BivarColormap ):
20272025 """
2028- BivarColormap object generated by supersampling a regular grid
2026+ BivarColormap object generated by supersampling a regular grid.
20292027
20302028 Parameters
20312029 ----------
2032- patch : nparray of shape (k, k, 3)
2033- This patch gets supersamples to a lut of shape (N, M, 4)
2030+ patch : np.array of shape (k, k, 3)
2031+ This patch gets supersampled to a lut of shape (N, M, 4).
20342032 N : int
20352033 The number of RGB quantization levels along each axis.
2036- shape: str 'square' or 'circle' or 'ignore' or 'circleignore'
2034+ shape: { 'square', 'circle', 'ignore', 'circleignore'}
20372035
20382036 - If 'square' each variate is clipped to [0,1] independently
20392037 - If 'circle' the variates are clipped radially to the center
@@ -2073,13 +2071,13 @@ def _init(self):
20732071
20742072class BivarColormapFromImage (BivarColormap ):
20752073 """
2076- BivarColormap object generated by supersampling a regular grid
2074+ BivarColormap object generated by supersampling a regular grid.
20772075
20782076 Parameters
20792077 ----------
20802078 lut : nparray of shape (N, M, 3) or (N, M, 4)
20812079 The look-up-table
2082- shape: str 'square' or 'circle' or 'ignore' or 'circleignore'
2080+ shape: { 'square', 'circle', 'ignore', 'circleignore'}
20832081
20842082 - If 'square' each variate is clipped to [0,1] independently
20852083 - If 'circle' the variates are clipped radially to the center
@@ -2099,7 +2097,7 @@ class BivarColormapFromImage(BivarColormap):
20992097 """
21002098
21012099 def __init__ (self , lut , shape = 'square' , origin = (0 , 0 ), name = 'from image' ):
2102- # We can allow for a PIL.Image as unput in the following way, but importing
2100+ # We can allow for a PIL.Image as input in the following way, but importing
21032101 # matplotlib.image.pil_to_array() results in a circular import
21042102 # For now, this function only accepts numpy arrays.
21052103 # i.e.:
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