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Commit8e93d20

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Bivariate works with imshow, pcolor, pcolormesh, pcolorfast
1 parent90eae1f commit8e93d20

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2 files changed

+115
-12
lines changed

2 files changed

+115
-12
lines changed

‎lib/matplotlib/axes/_axes.py

Lines changed: 86 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -5081,12 +5081,30 @@ def imshow(self, X, cmap=None, norm=None, aspect=None,
50815081
ifnotself._hold:
50825082
self.cla()
50835083

5084-
ifnormisnotNoneandnotisinstance(norm,mcolors.Normalize):
5085-
msg="'norm' must be an instance of 'mcolors.Normalize'"
5084+
isNorm=isinstance(norm, (mcolors.Normalize,mcolors.BivariateNorm))
5085+
ifnormisnotNoneandnotisNorm:
5086+
msg="'norm' must be an instance of 'mcolors.Normalize' " \
5087+
"or 'mcolors.BivariateNorm'"
50865088
raiseValueError(msg)
5089+
50875090
ifaspectisNone:
50885091
aspect=rcParams['image.aspect']
50895092
self.set_aspect(aspect)
5093+
5094+
temp=np.asarray(X)
5095+
if (temp.ndim==3andisinstance(norm,mcolors.BivariateNorm)or
5096+
isinstance(cmap,mcolors.BivariateColormap)):
5097+
ifcmapisNone:
5098+
cmap=mcolors.BivariateColormap()
5099+
ifnormisNone:
5100+
norm=mcolors.BivariateNorm()
5101+
temp=norm(temp)
5102+
temp[0]=temp[0]* (cmap.N-1)
5103+
temp[1]=temp[1]* (cmap.N-1)
5104+
temp=temp.astype(int)
5105+
X=temp[0]+cmap.N*temp[1]
5106+
norm=mcolors.NoNorm()
5107+
50905108
im=mimage.AxesImage(self,cmap,norm,interpolation,origin,extent,
50915109
filternorm=filternorm,filterrad=filterrad,
50925110
resample=resample,**kwargs)
@@ -5113,7 +5131,6 @@ def imshow(self, X, cmap=None, norm=None, aspect=None,
51135131

51145132
@staticmethod
51155133
def_pcolorargs(funcname,*args,**kw):
5116-
# This takes one kwarg, allmatch.
51175134
# If allmatch is True, then the incoming X, Y, C must
51185135
# have matching dimensions, taking into account that
51195136
# X and Y can be 1-D rather than 2-D. This perfect
@@ -5126,9 +5143,25 @@ def _pcolorargs(funcname, *args, **kw):
51265143
# is False.
51275144

51285145
allmatch=kw.pop("allmatch",False)
5146+
norm=kw.pop("norm",None)
5147+
cmap=kw.pop("cmap",None)
51295148

51305149
iflen(args)==1:
51315150
C=np.asanyarray(args[0])
5151+
5152+
if (C.ndim==3andisinstance(norm,mcolors.BivariateNorm)or
5153+
isinstance(cmap,mcolors.BivariateColormap)):
5154+
ifcmapisNone:
5155+
cmap=mcolors.BivariateColormap()
5156+
ifnormisNone:
5157+
norm=mcolors.BivariateNorm()
5158+
C=norm(C)
5159+
C[0]=C[0]* (cmap.N-1)
5160+
C[1]=C[1]* (cmap.N-1)
5161+
C=C.astype(int)
5162+
C=C[0]+cmap.N*C[1]
5163+
C=np.array(C)
5164+
51325165
numRows,numCols=C.shape
51335166
ifallmatch:
51345167
X,Y=np.meshgrid(np.arange(numCols),np.arange(numRows))
@@ -5140,6 +5173,18 @@ def _pcolorargs(funcname, *args, **kw):
51405173

51415174
iflen(args)==3:
51425175
X,Y,C= [np.asanyarray(a)forainargs]
5176+
if (C.ndim==3andisinstance(norm,mcolors.BivariateNorm)or
5177+
isinstance(cmap,mcolors.BivariateColormap)):
5178+
ifcmapisNone:
5179+
cmap=mcolors.BivariateColormap()
5180+
ifnormisNone:
5181+
norm=mcolors.BivariateNorm()
5182+
C=norm(C)
5183+
C[0]=C[0]* (cmap.N-1)
5184+
C[1]=C[1]* (cmap.N-1)
5185+
C=C.astype(int)
5186+
C=C[0]+cmap.N*C[1]
5187+
C=np.array(C)
51435188
numRows,numCols=C.shape
51445189
else:
51455190
raiseTypeError(
@@ -5325,9 +5370,14 @@ def pcolor(self, *args, **kwargs):
53255370
vmin=kwargs.pop('vmin',None)
53265371
vmax=kwargs.pop('vmax',None)
53275372

5328-
X,Y,C=self._pcolorargs('pcolor',*args,allmatch=False)
5373+
kw= {'norm':norm,'cmap':cmap,'allmatch':False}
5374+
X,Y,C=self._pcolorargs('pcolor',*args,**kw)
53295375
Ny,Nx=X.shape
53305376

5377+
if (isinstance(norm,mcolors.BivariateNorm)or
5378+
isinstance(cmap,mcolors.BivariateColormap)):
5379+
norm=mcolors.NoNorm()
5380+
53315381
# unit conversion allows e.g. datetime objects as axis values
53325382
self._process_unit_info(xdata=X,ydata=Y,kwargs=kwargs)
53335383
X=self.convert_xunits(X)
@@ -5393,9 +5443,13 @@ def pcolor(self, *args, **kwargs):
53935443

53945444
collection.set_alpha(alpha)
53955445
collection.set_array(C)
5396-
ifnormisnotNoneandnotisinstance(norm,mcolors.Normalize):
5397-
msg="'norm' must be an instance of 'mcolors.Normalize'"
5446+
5447+
isNorm=isinstance(norm, (mcolors.Normalize,mcolors.BivariateNorm))
5448+
ifnormisnotNoneandnotisNorm:
5449+
msg="'norm' must be an instance of 'mcolors.Normalize' " \
5450+
"or 'mcolors.BivariateNorm'"
53985451
raiseValueError(msg)
5452+
53995453
collection.set_cmap(cmap)
54005454
collection.set_norm(norm)
54015455
collection.set_clim(vmin,vmax)
@@ -5525,9 +5579,14 @@ def pcolormesh(self, *args, **kwargs):
55255579

55265580
allmatch= (shading=='gouraud')
55275581

5528-
X,Y,C=self._pcolorargs('pcolormesh',*args,allmatch=allmatch)
5582+
kw= {'norm':norm,'cmap':cmap,'allmatch':allmatch}
5583+
X,Y,C=self._pcolorargs('pcolormesh',*args,**kw)
55295584
Ny,Nx=X.shape
55305585

5586+
if (isinstance(norm,mcolors.BivariateNorm)or
5587+
isinstance(cmap,mcolors.BivariateColormap)):
5588+
norm=mcolors.NoNorm()
5589+
55315590
# unit conversion allows e.g. datetime objects as axis values
55325591
self._process_unit_info(xdata=X,ydata=Y,kwargs=kwargs)
55335592
X=self.convert_xunits(X)
@@ -5666,11 +5725,28 @@ def pcolorfast(self, *args, **kwargs):
56665725
cmap=kwargs.pop('cmap',None)
56675726
vmin=kwargs.pop('vmin',None)
56685727
vmax=kwargs.pop('vmax',None)
5669-
ifnormisnotNoneandnotisinstance(norm,mcolors.Normalize):
5670-
msg="'norm' must be an instance of 'mcolors.Normalize'"
5728+
isNorm=isinstance(norm, (mcolors.Normalize,mcolors.BivariateNorm))
5729+
ifnormisnotNoneandnotisNorm:
5730+
msg="'norm' must be an instance of 'mcolors.Normalize' " \
5731+
"or 'mcolors.BivariateNorm'"
56715732
raiseValueError(msg)
56725733

5673-
C=args[-1]
5734+
C=np.asarray(args[-1])
5735+
5736+
if (C.ndim==3andisinstance(norm,mcolors.BivariateNorm)or
5737+
isinstance(cmap,mcolors.BivariateColormap)):
5738+
ifcmapisNone:
5739+
cmap=mcolors.BivariateColormap()
5740+
ifnormisNone:
5741+
norm=mcolors.BivariateNorm()
5742+
C=norm(C)
5743+
C[0]=C[0]* (cmap.N-1)
5744+
C[1]=C[1]* (cmap.N-1)
5745+
C=C.astype(int)
5746+
C=C[0]+cmap.N*C[1]
5747+
C=np.array(C)
5748+
norm=mcolors.NoNorm()
5749+
56745750
nr,nc=C.shape
56755751
iflen(args)==1:
56765752
style="image"

‎lib/matplotlib/colors.py

Lines changed: 29 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -855,6 +855,32 @@ def reversed(self, name=None):
855855
returnListedColormap(colors_r,name=name,N=self.N)
856856

857857

858+
classBivariateColormap(Colormap):
859+
def__init__(self,name,N=256):
860+
Colormap.__init__(self,name,N)
861+
862+
def_init(self):
863+
red=np.linspace(0,1,self.N)
864+
green=np.linspace(0,1,self.N)
865+
red_mesh,green_mesh=np.meshgrid(red,green)
866+
blue_mesh=np.zeros_like(red_mesh)
867+
alpha_mesh=np.ones_like(red_mesh)
868+
bivariate_cmap=np.dstack((red_mesh,green_mesh,blue_mesh,alpha_mesh))
869+
self._lut=np.vstack(bivariate_cmap)
870+
self._isinit=True
871+
self.N=self.N*self.N
872+
self._set_extremes()
873+
874+
def_resample(self,lutsize):
875+
"""
876+
Return a new color map with *lutsize x lutsize* entries.
877+
"""
878+
returnBivariateColormap(self.name,lutsize)
879+
880+
defreversed(self,name=None):
881+
raiseNotImplementedError()
882+
883+
858884
classNormalize(object):
859885
"""
860886
A class which, when called, can normalize data into
@@ -1387,8 +1413,8 @@ def __call__(self, values, clip=None):
13871413
ifclipisNone:
13881414
clip= [self.norm1.clip,self.norm2.clip]
13891415

1390-
return [self.norm1(values[0],clip=clip[0]),
1391-
self.norm2(values[1],clip=clip[1])]
1416+
returnnp.array([self.norm1(values[0],clip=clip[0]),
1417+
self.norm2(values[1],clip=clip[1])])
13921418

13931419
definverse(self,values):
13941420
"""
@@ -1403,6 +1429,7 @@ def inverse(self, values):
14031429
"""
14041430
return [self.norm1.inverse(values[0]),self.norm.inverse(values[1])]
14051431

1432+
14061433
defrgb_to_hsv(arr):
14071434
"""
14081435
convert float rgb values (in the range [0, 1]), in a numpy array to hsv

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