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Commit6a2d157

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Merge pull requestmatplotlib#21039 from dstansby/hexbin-marginal
Fix `hexbin` marginals and log scaling
2 parents5a4fe4a +c8f8002 commit6a2d157

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4 files changed

+51
-47
lines changed

4 files changed

+51
-47
lines changed
Lines changed: 4 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,4 @@
1+
hexbin with a log norm
2+
----------------------
3+
`~.axes.Axes.hexbin` no longer (incorrectly) adds 1 to every bin value if a
4+
log norm is being used.

‎lib/matplotlib/axes/_axes.py‎

Lines changed: 45 additions & 46 deletions
Original file line numberDiff line numberDiff line change
@@ -4589,6 +4589,11 @@ def reduce_C_function(C: array) -> float
45894589
# Count the number of data in each hexagon
45904590
x=np.array(x,float)
45914591
y=np.array(y,float)
4592+
4593+
ifmarginals:
4594+
xorig=x.copy()
4595+
yorig=y.copy()
4596+
45924597
ifxscale=='log':
45934598
ifnp.any(x<=0.0):
45944599
raiseValueError("x contains non-positive values, so can not"
@@ -4617,10 +4622,6 @@ def reduce_C_function(C: array) -> float
46174622
sx= (xmax-xmin)/nx
46184623
sy= (ymax-ymin)/ny
46194624

4620-
ifmarginals:
4621-
xorig=x.copy()
4622-
yorig=y.copy()
4623-
46244625
x= (x-xmin)/sx
46254626
y= (y-ymin)/sy
46264627
ix1=np.round(x).astype(int)
@@ -4746,11 +4747,6 @@ def reduce_C_function(C: array) -> float
47464747
vmin=vmax=None
47474748
bins=None
47484749

4749-
ifisinstance(norm,mcolors.LogNorm):
4750-
if (accum==0).any():
4751-
# make sure we have no zeros
4752-
accum+=1
4753-
47544750
# autoscale the norm with current accum values if it hasn't
47554751
# been set
47564752
ifnormisnotNone:
@@ -4781,40 +4777,42 @@ def reduce_C_function(C: array) -> float
47814777
ifnotmarginals:
47824778
returncollection
47834779

4780+
# Process marginals
47844781
ifCisNone:
47854782
C=np.ones(len(x))
47864783

4787-
defcoarse_bin(x,y,coarse):
4788-
ind=coarse.searchsorted(x).clip(0,len(coarse)-1)
4789-
mus=np.zeros(len(coarse))
4790-
foriinrange(len(coarse)):
4791-
yi=y[ind==i]
4784+
defcoarse_bin(x,y,bin_edges):
4785+
"""
4786+
Sort x-values into bins defined by *bin_edges*, then for all the
4787+
corresponding y-values in each bin use *reduce_c_function* to
4788+
compute the bin value.
4789+
"""
4790+
nbins=len(bin_edges)-1
4791+
# Sort x-values into bins
4792+
bin_idxs=np.searchsorted(bin_edges,x)-1
4793+
mus=np.zeros(nbins)*np.nan
4794+
foriinrange(nbins):
4795+
# Get y-values for each bin
4796+
yi=y[bin_idxs==i]
47924797
iflen(yi)>0:
4793-
mu=reduce_C_function(yi)
4794-
else:
4795-
mu=np.nan
4796-
mus[i]=mu
4798+
mus[i]=reduce_C_function(yi)
47974799
returnmus
47984800

4799-
coarse=np.linspace(xmin,xmax,gridsize)
4801+
ifxscale=='log':
4802+
bin_edges=np.geomspace(xmin,xmax,nx+1)
4803+
else:
4804+
bin_edges=np.linspace(xmin,xmax,nx+1)
4805+
xcoarse=coarse_bin(xorig,C,bin_edges)
48004806

4801-
xcoarse=coarse_bin(xorig,C,coarse)
4802-
valid=~np.isnan(xcoarse)
48034807
verts,values= [], []
4804-
fori,valinenumerate(xcoarse):
4805-
thismin=coarse[i]
4806-
ifi<len(coarse)-1:
4807-
thismax=coarse[i+1]
4808-
else:
4809-
thismax=thismin+np.diff(coarse)[-1]
4810-
4811-
ifnotvalid[i]:
4808+
forbin_left,bin_right,valinzip(
4809+
bin_edges[:-1],bin_edges[1:],xcoarse):
4810+
ifnp.isnan(val):
48124811
continue
4813-
4814-
verts.append([(thismin,0),
4815-
(thismin,0.05),
4816-
(thismax,0.05),
4817-
(thismax,0)])
4812+
verts.append([(bin_left,0),
4813+
(bin_left,0.05),
4814+
(bin_right,0.05),
4815+
(bin_right,0)])
48184816
values.append(val)
48194817

48204818
values=np.array(values)
@@ -4829,20 +4827,21 @@ def coarse_bin(x, y, coarse):
48294827
hbar.update(kwargs)
48304828
self.add_collection(hbar,autolim=False)
48314829

4832-
coarse=np.linspace(ymin,ymax,gridsize)
4833-
ycoarse=coarse_bin(yorig,C,coarse)
4834-
valid=~np.isnan(ycoarse)
4830+
ifyscale=='log':
4831+
bin_edges=np.geomspace(ymin,ymax,2*ny+1)
4832+
else:
4833+
bin_edges=np.linspace(ymin,ymax,2*ny+1)
4834+
ycoarse=coarse_bin(yorig,C,bin_edges)
4835+
48354836
verts,values= [], []
4836-
fori,valinenumerate(ycoarse):
4837-
thismin=coarse[i]
4838-
ifi<len(coarse)-1:
4839-
thismax=coarse[i+1]
4840-
else:
4841-
thismax=thismin+np.diff(coarse)[-1]
4842-
ifnotvalid[i]:
4837+
forbin_bottom,bin_top,valinzip(
4838+
bin_edges[:-1],bin_edges[1:],ycoarse):
4839+
ifnp.isnan(val):
48434840
continue
4844-
verts.append([(0,thismin), (0.0,thismax),
4845-
(0.05,thismax), (0.05,thismin)])
4841+
verts.append([(0,bin_bottom),
4842+
(0,bin_top),
4843+
(0.05,bin_top),
4844+
(0.05,bin_bottom)])
48464845
values.append(val)
48474846

48484847
values=np.array(values)
14.5 KB
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‎lib/matplotlib/tests/test_axes.py‎

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -781,7 +781,8 @@ def test_hexbin_log():
781781
y=np.power(2,y*0.5)
782782

783783
fig,ax=plt.subplots()
784-
h=ax.hexbin(x,y,yscale='log',bins='log')
784+
h=ax.hexbin(x,y,yscale='log',bins='log',
785+
marginals=True,reduce_C_function=np.sum)
785786
plt.colorbar(h)
786787

787788

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