Does this code work for anyone else?
import numpy as np
import matplotlib.cm as cm
import matplotlib.pyplot as plt
n = 100000
x = np.random.standard_normal(n)
y = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)
xmin = x.min()
xmax = x.max()
ymin = y.min()
ymax = y.max()
plt.hexbin(x,y, cmap=cm.jet, gridsize=(50,50), extent=[-2,2,-10,10])
plt.axis([xmin, xmax, ymin, ymax])
plt.title("Hexagon binning")
cb = plt.colorbar()
cb.set_label('counts')
plt.show()
Without the extent option, I get the expected plot of all the data. But,
what I'd like is to trim out some of the empty regions. If I just reset
xmin, xmax, etc. the binning of the data still occurs over the entire range
of the data in x and y, although the plot is correct, but the plot doesn't
have the desired 50x50 bins. With the "extent" option I get these errors:
Traceback (most recent call last):
File "HexBin.py", line 23, in <module>
plt.hexbin(x,y, cmap=cm.jet, extent=[-2,2,-10,10])
File "/usr/lib64/python2.5/site-packages/matplotlib/pyplot.py", line 1920,
in hexbin
ret = gca().hexbin(*args, **kwargs)
File "/usr/lib64/python2.5/site-packages/matplotlib/axes.py", line 5447,
in hexbin
collection.update(kwargs)
File "/usr/lib64/python2.5/site-packages/matplotlib/artist.py", line 548,
in update
raise AttributeError('Unknown property %s'%k)
AttributeError: Unknown property extent
Best,
Alex
On Thu, Jun 18, 2009 at 11:27 AM, Alexandar Hansen <viochem...@gmail.com>wrote:
> Ok, fair enough. Let's use that:
>
> ------------------
> import numpy as np
> import matplotlib.cm as cm
> import matplotlib.pyplot as plt
>
> n = 100000
> x = np.random.standard_normal(n)
> y = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)
> xmin = x.min()
> xmax = x.max()
> ymin = y.min()
> ymax = y.max()
>
> plt.hexbin(x,y, cmap=cm.jet, gridsize=(50,50), extent=[-2,2,-10,10])
> plt.axis([xmin, xmax, ymin, ymax])
> plt.title("Hexagon binning")
> cb = plt.colorbar()
> cb.set_label('counts')
>
>
> plt.show()
> ----------------------
>
>
> I trimmed this from the example, which works fine. Without the extent
> option, I get the expected plot of all the data. But, what I'd like is to
> trim out some of the empty regions. If I just reset xmin, xmax, etc. the
> binning of the data still occurs over the entire range of the data in x and
> y, although the plot is correct, but the plot doesn't have the desired 50x50
> bins. With the "extent" option I get these errors:
>
>
> Traceback (most recent call last):
> File "HexBin.py", line 23, in <module>
> plt.hexbin(x,y, cmap=cm.jet, extent=[-2,2,-10,10])
> File "/usr/lib64/python2.5/site-packages/matplotlib/pyplot.py", line
> 1920, in hexbin
> ret = gca().hexbin(*args, **kwargs)
> File "/usr/lib64/python2.5/site-packages/matplotlib/axes.py", line 5447,
> in hexbin
> collection.update(kwargs)
> File "/usr/lib64/python2.5/site-packages/matplotlib/artist.py", line 548,
> in update
> raise AttributeError('Unknown property %s'%k)
> AttributeError: Unknown property extent
>
>
> The same thing as before. It doesn't know what 'extent' is for some reason.
> Or, perhaps more accurately, hexbin knows what it is but artist.py doesn't?
> The only "solution" i've come up with is to trim the original data that I
> input, but that is far from ideal.
>
>
> Best,
>
> Alex
>
>
>
>
>
>
>
> On Wed, Jun 17, 2009 at 7:50 PM, John Hunter <jdh2...@gmail.com> wrote:
>
>> On Wed, Jun 17, 2009 at 5:31 PM, Alexandar Hansen<viochem...@gmail.com>
>> wrote:
>> > Hello,
>> >
>> > I've been having fun using hexbin, but I'd like to have consistent bin
>> sizes
>> > and plot ranges for different sets of data. What I'm finding is that the
>> bin
>> > sizes are primarily determined by the input data mins and maxes. For
>> > instance, I'm plotting data with something like:
>>
>> Instead of a "something like" could you please post a complete example
>> that we can run so we can replicate the error. This saves us a lot of
>> time. Also, please report any version info, as described at
>>
>>
>> http://matplotlib.sourceforge.net/faq/troubleshooting_faq.html#report-a-problem
>>
>> For example, the following runs for me using mpl svn:
>>
>> import numpy as np
>> import matplotlib.cm as cm
>> import matplotlib.pyplot as plt
>>
>> n = 100000
>> x = np.random.standard_normal(n)
>> y = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)
>> xmin = x.min()
>> xmax = x.max()
>> ymin = y.min()
>> ymax = y.max()
>>
>> plt.subplots_adjust(hspace=0.5)
>> plt.subplot(121)
>> plt.hexbin(x,y, cmap=cm.jet, extent=[xmin, xmax, ymin, ymax])
>> plt.axis([xmin, xmax, ymin, ymax])
>> plt.title("Hexagon binning")
>> cb = plt.colorbar()
>> cb.set_label('counts')
>>
>> plt.subplot(122)
>> plt.hexbin(x,y,bins='log', cmap=cm.jet)
>> plt.axis([xmin, xmax, ymin, ymax])
>> plt.title("With a log color scale")
>> cb = plt.colorbar()
>> cb.set_label('log10(N)')
>>
>> plt.show()
>>
>
>
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