Hello everybody,
First I have to say, how much I appreciate using matplotlib.
But there are some annoyances. One I stumbled over recently is that histograms
don't deal with masked arrays properly.
For example:
from numpy import *
from pylab import *
bins = arange(21)
data_masked = ma.masked_values(bins,10)
hist(data_masked,bins)
show()
This example produces (with maplotlib-0.90.0, numpy-1.0) this message:
/usr/lib/python2.4/site-packages/numpy/core/ma.py:604: UserWarning: Cannot
automatically convert masked array to numeric because data
is masked in one or more locations.
warnings.warn("Cannot automatically convert masked array to "\
But it shows a histogram with one count per bin although data_masked[10] should
not be counted.
When I'm trying "plot(bins,data_masked)", data_masked[10] is left out as expected.
Am I missing something or are histograms not (yet) suited for handling masked
arrays?
Best regards,
Peter Melchior
Peter Melchior wrote:
Hello everybody,
First I have to say, how much I appreciate using matplotlib.
But there are some annoyances. One I stumbled over recently is that histograms
don't deal with masked arrays properly.
Fixed now in svn.
If you don't want to install from svn, use
hist(data_masked.compressed(), bins)
Eric
···
For example:
from numpy import *
from pylab import *
bins = arange(21)
data_masked = ma.masked_values(bins,10)
hist(data_masked,bins)
show()
This example produces (with maplotlib-0.90.0, numpy-1.0) this message:
/usr/lib/python2.4/site-packages/numpy/core/ma.py:604: UserWarning: Cannot
automatically convert masked array to numeric because data
is masked in one or more locations.
warnings.warn("Cannot automatically convert masked array to "\
But it shows a histogram with one count per bin although data_masked[10] should
not be counted.
When I'm trying "plot(bins,data_masked)", data_masked[10] is left out as expected.
Am I missing something or are histograms not (yet) suited for handling masked
arrays?
Best regards,
Peter Melchior
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