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Commit3e4b469

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Fix for mouseover image data with a MultiNorm
If an image is shown, and the user hovers over the image, the value at that coordinate should be displayed. The number formating is handled by colorizer.Colorizer._format_cursor_data_override(). This is now updated to also handle the case where a MultiNorm is used (i.e. a bivariat or multivariate colormap), in which case multiple values are displayed.
1 parent9c26a1e commit3e4b469

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3 files changed

+100
-22
lines changed

3 files changed

+100
-22
lines changed

‎lib/matplotlib/colorizer.py

Lines changed: 43 additions & 19 deletions
Original file line numberDiff line numberDiff line change
@@ -451,39 +451,63 @@ def colorbar(self):
451451
defcolorbar(self,colorbar):
452452
self._colorizer.colorbar=colorbar
453453

454-
def_format_cursor_data_override(self,data):
455-
# This function overwrites Artist.format_cursor_data(). We cannot
456-
# implement cm.ScalarMappable.format_cursor_data() directly, because
457-
# most cm.ScalarMappable subclasses inherit from Artist first and from
458-
# cm.ScalarMappable second, so Artist.format_cursor_data would always
459-
# have precedence over cm.ScalarMappable.format_cursor_data.
460-
461-
# Note if cm.ScalarMappable is depreciated, this functionality should be
462-
# implemented as format_cursor_data() on ColorizingArtist.
463-
n=self.cmap.N
464-
ifnp.ma.getmask(data):
465-
return"[]"
466-
normed=self.norm(data)
454+
@staticmethod
455+
def_sig_digits_from_norm(norm,data,n):
456+
# Determines the number of significant digits
457+
# to use for a number given a norm, and n, where n is the
458+
# number of colors in the colormap.
459+
normed=norm(data)
467460
ifnp.isfinite(normed):
468-
ifisinstance(self.norm,colors.BoundaryNorm):
461+
ifisinstance(norm,colors.BoundaryNorm):
469462
# not an invertible normalization mapping
470-
cur_idx=np.argmin(np.abs(self.norm.boundaries-data))
463+
cur_idx=np.argmin(np.abs(norm.boundaries-data))
471464
neigh_idx=max(0,cur_idx-1)
472465
# use max diff to prevent delta == 0
473466
delta=np.diff(
474-
self.norm.boundaries[neigh_idx:cur_idx+2]
467+
norm.boundaries[neigh_idx:cur_idx+2]
475468
).max()
476-
elifself.norm.vmin==self.norm.vmax:
469+
elifnorm.vmin==norm.vmax:
477470
# singular norms, use delta of 10% of only value
478-
delta=np.abs(self.norm.vmin*.1)
471+
delta=np.abs(norm.vmin*.1)
479472
else:
480473
# Midpoints of neighboring color intervals.
481-
neighbors=self.norm.inverse(
474+
neighbors=norm.inverse(
482475
(int(normed*n)+np.array([0,1]))/n)
483476
delta=abs(neighbors-data).max()
484477
g_sig_digits=cbook._g_sig_digits(data,delta)
485478
else:
486479
g_sig_digits=3# Consistent with default below.
480+
returng_sig_digits
481+
482+
def_format_cursor_data_override(self,data):
483+
# This function overwrites Artist.format_cursor_data(). We cannot
484+
# implement cm.ScalarMappable.format_cursor_data() directly, because
485+
# most cm.ScalarMappable subclasses inherit from Artist first and from
486+
# cm.ScalarMappable second, so Artist.format_cursor_data would always
487+
# have precedence over cm.ScalarMappable.format_cursor_data.
488+
489+
# Note if cm.ScalarMappable is depreciated, this functionality should be
490+
# implemented as format_cursor_data() on ColorizingArtist.
491+
ifnp.ma.getmask(data)ordataisNone:
492+
return"[]"
493+
iflen(data.dtype.descr)>1:
494+
# We have multivariate data encoded as a data type with multiple fields
495+
# NOTE: If any of the fields are masked, "[]" would be returned via
496+
# the if statement above.
497+
s_sig_digits_list= []
498+
ifisinstance(self.cmap,colors.BivarColormap):
499+
n_s= (self.cmap.N,self.cmap.M)
500+
else:
501+
n_s= [part.Nforpartinself.cmap]
502+
os= [f"{d:-#.{self._sig_digits_from_norm(no,d,n)}g}"
503+
forno,d,ninzip(self.norm.norms,data,n_s)]
504+
returnf"[{', '.join(os)}]"
505+
506+
# scalar data
507+
n=self.cmap.N
508+
g_sig_digits=self._sig_digits_from_norm(self.norm,
509+
data,
510+
n)
487511
returnf"[{data:-#.{g_sig_digits}g}]"
488512

489513

‎lib/matplotlib/tests/test_image.py

Lines changed: 9 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -14,7 +14,7 @@
1414

1515
importmatplotlibasmpl
1616
frommatplotlibimport (
17-
colors,imageasmimage,patches,pyplotasplt,style,rcParams)
17+
cbook,colors,imageasmimage,patches,pyplotasplt,style,rcParams)
1818
frommatplotlib.imageimport (AxesImage,BboxImage,FigureImage,
1919
NonUniformImage,PcolorImage)
2020
frommatplotlib.testing.decoratorsimportcheck_figures_equal,image_comparison
@@ -1130,8 +1130,14 @@ def test_image_cursor_formatting():
11301130
data=np.ma.masked_array([0],mask=[False])
11311131
assertim.format_cursor_data(data)=='[0]'
11321132

1133-
data=np.nan
1134-
assertim.format_cursor_data(data)=='[nan]'
1133+
# This used to test
1134+
# > data = np.nan
1135+
# > assert im.format_cursor_data(data) == '[nan]'
1136+
# However, a value of nan will be masked by `cbook.safe_masked_invalid(data)`
1137+
# called by `image._ImageBase._normalize_image_array(data)`
1138+
# The test is therefore changed to:
1139+
data=cbook.safe_masked_invalid(np.nan)
1140+
assertim.format_cursor_data(data)=='[]'
11351141

11361142

11371143
@check_figures_equal()

‎lib/matplotlib/tests/test_multivariate_axes.py

Lines changed: 48 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -629,6 +629,54 @@ def test_cmap_error():
629629
mpl.collections.PatchCollection([],cmap='not_a_cmap')
630630

631631

632+
deftest_artist_format_cursor_data_multivar():
633+
634+
X=np.zeros((4,3))
635+
X[0,0]=0.9
636+
X[0,1]=0.99
637+
X[0,2]=0.999
638+
X[1,0]=-1
639+
X[1,1]=0
640+
X[1,2]=1
641+
X[2,0]=0.09
642+
X[2,1]=0.009
643+
X[2,2]=0.0009
644+
X[3,0]=np.nan
645+
646+
Y=np.arange(np.prod(X.shape)).reshape(X.shape)
647+
648+
labels_list= [
649+
"[0.9, 0.00]",
650+
"[1., 1.00]",
651+
"[1., 2.00]",
652+
"[-1.0, 3.00]",
653+
"[0.0, 4.00]",
654+
"[1.0, 5.00]",
655+
"[0.09, 6.00]",
656+
"[0.009, 7.00]",
657+
"[0.0009, 8.00]",
658+
"[]",
659+
]
660+
661+
pos= [[0,0], [1,0], [2,0],
662+
[0,1], [1,1], [2,1],
663+
[0,2], [1,2], [2,2],
664+
[3,0]]
665+
666+
frommatplotlib.backend_basesimportMouseEvent
667+
668+
forcmapin ['BiOrangeBlue','2VarAddA']:
669+
fig,ax=plt.subplots()
670+
norm=mpl.colors.BoundaryNorm(np.linspace(-1,1,20),256)
671+
data= (X,Y)
672+
im=ax.imshow(data,cmap=cmap,norm=(norm,None))
673+
674+
forv,textinzip(pos,labels_list):
675+
xdisp,ydisp=ax.transData.transform(v)
676+
event=MouseEvent('motion_notify_event',fig.canvas,xdisp,ydisp)
677+
assertim.format_cursor_data(im.get_cursor_data(event))==text
678+
679+
632680
deftest_multivariate_safe_masked_invalid():
633681
dt=np.dtype('float32, float32').newbyteorder('>')
634682
x=np.zeros(2,dtype=dt)

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