matplotlib-users Mailing List for matplotlib

Thanks! I did use geopandas and it seems it is the easiest method of
creating a choropleth in Python. Support for displaying a colorbar for
noncategorical data is missing so I implemented it but my PR hasn't
been merged yet.

On Fri, Nov 14, 2014 at 6:07 PM, Benjamin Root <ben...@ou...> wrote:
> Sorry for the delay. Here is an example I came across today using geopandas
> and pysal:
> http://nbviewer.ipython.org/github/geopandas/geopandas/blob/master/examples/choropleths.ipynb
>
> Cheers!
> Ben Root
>
> On Fri, Oct 24, 2014 at 3:59 PM, Christian Alis <ia...@gm...> wrote:
>>
>> Hi Ben,
>>
>> Yes, indeed. I'm referring to a choropleth. :)
>>
>> Thanks,
>>
>> Christian
>>
>> On Oct 24, 2014 8:23 PM, "Benjamin Root" <ben...@ou...> wrote:
>>>
>>> Do you mean choropleth? http://en.wikipedia.org/wiki/Choropleth_map
>>>
>>> On Fri, Oct 24, 2014 at 1:18 PM, ianalis <ia...@gm...> wrote:
>>>>
>>>> I have been creating chloropleth maps in Python by adding patches and/or
>>>> polygons in a matplotlib Axes but I'm looking for something easier to
>>>> use.
>>>>
>>>> Ideally, the interface should be similar to how contour maps or
>>>> pseudocolor
>>>> plots are created where, at the minimum, only one call to a function is
>>>> needed to create these plots from data. Colors are automatically
>>>> assigned
>>>> and normalized based on values. A colorbar can then be added by calling
>>>> another function.
>>>>
>>>> So far, the closest package seems to be geopandas. Is there an another
>>>> package that is nearer to what I want? That is, is there a package that
>>>> can
>>>> make a (basic) chloropleth of values stored as a dictionary, numpy array
>>>> or
>>>> pandas dataframe in one call?
>>>>
>>>> I'm willing to contribute code and help develop the chloropleth
>>>> capability
>>>> of a package since I currently end up creating my own function and
>>>> manipulating Axes internals just to create a chloropleth.
>>>>
>>>>
>>>>
>>>> --
>>>> View this message in context:
>>>> http://matplotlib.1069221.n5.nabble.com/Easiest-way-to-create-a-chloropleth-in-Python-tp44195.html
>>>> Sent from the matplotlib - users mailing list archive at Nabble.com.
>>>>
>>>>
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>>>
>>>
>

On 2014/11/16, 10:21 AM, j1 wrote:
> I have posted this in the user sub forum as well because i'm not sure that it
> is a user issue or development issue.
> Information about my problem and my code are here
>
> http://matplotlib.1069221.n5.nabble.com/Assign-labels-to-colorbar-extensions-user-or-development-issue-td44392.html
> <http://matplotlib.1069221.n5.nabble.com/Assign-labels-to-colorbar-extensions-user-or-development-issue-td44392.html>
>
> Is it possible to assign tick labels/values to extensions?

You would have to do it manually; you can put marks and text anywhere 
you want in a matplotlib figure, but there is no mechanism for adding 
ticks to the extensions.  That's simply not what they are for.  They are 
intended only to indicate a single color to which values outside the 
vmin-to-vmax range of the norm are assigned.

>
> If so, how can I do it

It looks like you might be able to achieve what you want *without* using 
extensions, by using a custom colormap and/or norm.  You would extend 
the actual contour levels to include the full range you want "ticked and 
labeled", but you would use the colormap and/or norm to ensure those 
beyond a given range are mapped to the appropriate end color(s).

Eric

I am not sure if this is a user issue or a development issue.
Using version 1.4.2
My code allows the user to hone in on a specific contour range, by changing
the minimum and maximum of the contour and the number of levels.
I am using colorbar "extend" to prevent any white patches, as the data may
have values outside the contour range.

I want the extensions to have tick values but I can't seem to figure out,
how to do it?

This is my code

import numpy as np
import matplotlib.pyplot as plt
xi = np.array([0., 0.5, 1.0])#xi data
yi = np.array([0., 0.5, 1.0])#yi data
zi = np.array([[0., 1.0, 2.0],[0., 1.0, 2.0],[-0.1, 1.0, 2.0]])#zi data
n=5#number of levels of user specified range
umin=0.5#user defined minimum of contour
umax=1#user defined maximum of contout
u = np.linspace(umin, umax, n)#user specified contour levels
cbtics = np.hstack([zi.min(),u,zi.max()])#contour ticks including maximum
and minimum of zi
plt.contourf(xi, yi, zi, u, cmap=plt.cm.jet,extend='both')#plot contour
cbar=plt.colorbar(extendrect='True',extendfrac='auto',spacing='proportional')#plot
colorbar
print cbar.ax.get_ylim()#show y limits
print cbar.ax.get_yticks()#show yticks
plt.show()


Using the user entered values:
ylim are (-0.25, 1.25)
but the yticks are:
[ 0.   0.2  0.4  0.6  0.8  1. ] range from 0 to 1

I'm guessing that the difference between ylim (-0.25 to 1.25) and yticks (0
to 1) is that I am using extensions, so is there no way to update y ticks to
include the extensions so that I can  assign labels to the extensions?



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