matplotlib-users Mailing List for matplotlib

hi all,

i have a set of about 100-500 points that i'd like to color in different
colors. i tried the following, using the c= argument to the scatter command:

x = rand(200)
scatter(x, x, c=xrange(1,201))

however, only a handful of colors seem to be used and the points look very
similar. what i am looking for is a different color for every point -- it
can even be different shades, as in this example:

http://matplotlib.sourceforge.net/examples/pylab_examples/ellipse_collection.html

does anyone know how to create this?

also, more complex, is there a way to do this where every point gets not
only a different color but a different symbol? e.g. '^', 's', 'x', etc. ? i
know there aren't 200 different symbols but it'd be nice if it cycled
through the different symbols as much as possible (e.g. one point might be
blue '^' and another might be red '^') to distinguish the points

thanks.

Timothée Lecomte wrote:
> Jeff Whitaker wrote:
>> Jeff Whitaker wrote:
>>> Timothée Lecomte wrote:
>>>> Dear all,
>>>>
>>>> I am using matplotlib with a great pleasure, and I enjoy its 
>>>> capabilities.
>>>> I have recently attended a conference where the invited speaker 
>>>> showed great visualizations of arrays from both experiments and 
>>>> simulations. His plots were basically looking like those produced 
>>>> by imshow, that is a luminance array rendered as a colormap image, 
>>>> but with the additionnal use of a shading, which gives a really 
>>>> great feeling to the image. You can feel the height of each part of 
>>>> the image.
>>>>
>>>> I have tried to find what software could have produced such a plot, 
>>>> and found the ReliefPlot function of Mathematica, which has 
>>>> precisely this purpose : rendering a colormap image from an array 
>>>> with a shading to give the perception of relief.
>>>>
>>>> The documentation and its examples are self-explanatory :
>>>> http://reference.wolfram.com/mathematica/ref/ReliefPlot.html
>>>> (look in particular at the first "neat example" at the bottom of 
>>>> that page)
>>>>
>>>> The two "live" demonstrations illustrate this plot style quite well 
>>>> too :
>>>> http://demonstrations.wolfram.com/ReliefShadedElevationMap/
>>>> http://demonstrations.wolfram.com/VoronoiImage/
>>>>
>>>> So here are my questions :
>>>> Is there a trick to generate an image with such a shading in 
>>>> matplotlib ?
>>>> If not, do you know of a python tool that could help ?
>>>> Where could I start if I want to code it myself in matplotlib ?
>>>>
>>>> Thanks for your help.
>>>>
>>>> Best regards,
>>>>
>>>> Timothée Lecomte
>>>>
>>>>   
>>>
>>> Timothée:  There is nothing built-in, but it would be a nice thing 
>>> to have.  Here's a proof-of-concept hack that follows the approach 
>>> used in the Generic Mapping Tools (explained here 
>>> http://www.seismo.ethz.ch/gmt/doc/html/tutorial/node70.html), with 
>>> some code borrowed from http://www.langarson.com.au/blog/?p=14.  
>>> It's very rough, but if it looks promising to you I can try to 
>>> polish it.
>>>
>>> -Jeff
>>
>> Found a bug, here's a fixed version.
>>
>> -Jeff
>>
> Hi Jeff,
>
> Sure it looks promising ! The example you provided is very nice. I 
> will try on my own data on Monday, and I'll let you know if it gives a 
> good result too. Thank you very much for that very fast hack !
>
> Best regards,
>
> Timothée
>
>
Timothée:  I've added this capability in svn, along with an example 
(shading_example.py) to show how to use it.  Thanks for suggesting it.

-Jeff

Thomas Robitaille wrote:
>>> It looks like rotation/translation should be easy to do with 
>>> Affine2D, so I tried using it, but I can't seem to get it to work as 
>>> expected - here is an example of how I am using it:
>>
>> Based on a quick look at image.py and _image.cpp, it appears that 
>> there is a low-level capability to rotate an image in the latter, but 
>> no support at higher levels.  It also looks to me like adding that 
>> support would not be trivial--doing it right would take more than just 
>> calling the low-level apply_rotation method.  Mike D. would be the 
>> expert on this, though.
> 
> Does this mean that the transform= keyword has no effect on imshow in 
> general?

It does look like it is ignored.  It is a kwarg for Artists that is not 
supported by all.  The fact that one can specify it and get no feedback 
is a bug.


> 
> I attempted to use the pcolormesh() method, which worked, but is 
> impractical, as a 1000x1000 image produces a 300Mb EPS file when plotted 
> in this way.

There is some infrastructure for handling this via selective 
rasterization of artists, but I can never remember exactly what its 
status is; I don't see anything in the examples.  The topic comes up on 
the list at perhaps 6-month intervals.  Personally, I would very much 
like to see the selective rasterization capability fully developed and 
exposed, complete with documentation and examples; it is important for 
exactly the reason you note above.  It is not something I will be able 
to work on myself, unfortunately.

Eric

On Fri, Mar 13, 2009 at 5:18 PM, per freem <per...@gm...> wrote:

> hi all,
>
> what's the most efficient / preferred python way of parsing tab separated
> data into arrays? for example if i have a file containing two columns one
> corresponding to names the other numbers:
>
> col1    \t     col 2
> joe    \t  12.3
> jane   \t 155.0
>
> i'd like to parse into an array() such that i can do: mydata[:, 0] and
> mydata[:, 1] to easily access all the columns.
>
> right now i can iterate through the file, parse it manually using the
> split('\t') command and construct a list out of it, then convert it to
> arrays. but there must be a better way?
>
> also, my first column is just a name, and so it is variable in length -- is
> there still a way to store it as an array so i can access: mydata[:, 0] to
> get all the names (as a list)?
>
>
Try matplotlib.mlab.csv2rec or numpy.loadtxt

Ryan

-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma
Sent from: Norman Oklahoma United States.

>> It looks like rotation/translation should be easy to do with  
>> Affine2D, so I tried using it, but I can't seem to get it to work  
>> as expected - here is an example of how I am using it:
>
> Based on a quick look at image.py and _image.cpp, it appears that  
> there is a low-level capability to rotate an image in the latter,  
> but no support at higher levels.  It also looks to me like adding  
> that support would not be trivial--doing it right would take more  
> than just calling the low-level apply_rotation method.  Mike D.  
> would be the expert on this, though.

Does this mean that the transform= keyword has no effect on imshow in  
general?

I tried doing a simple image translation, and this didn't work either:

import numpy as np
from matplotlib.pyplot import *
from matplotlib.transforms import Affine2D
im = np.random.random((10,10))
tr = Affine2D().translate(10.,10.)
fig = figure()
ax = fig.add_subplot(111)
ax.imshow(im,transform=tr)
fig.canvas.draw()

I attempted to use the pcolormesh() method, which worked, but is  
impractical, as a 1000x1000 image produces a 300Mb EPS file when  
plotted in this way.

Thanks,

Thomas

>
> Eric
>
>> import numpy as np
>> from matplotlib.pyplot import *
>> from matplotlib.transforms import Affine2D
>> im = np.random.random((10,10))
>> tr = Affine2D().rotate_deg(45.)
>> fig = figure()
>> ax = fig.add_subplot(111)
>> ax.imshow(im,transform=tr)
>> fig.canvas.draw()
>> Am I doing something wrong?
>> Thanks!
>> Thomas
>> On Mar 13, 2009, at 5:20 PM, Andrew Straw wrote:
>>> Eric Firing wrote:
>>>> Thomas Robitaille wrote:
>>>>> Hello,
>>>>>
>>>>> I was wondering whether there is a way to rotate a grayscale/
>>>>> colorscale when using imshow.
>>>>>
>>>>> I have been using PGPLOT (a fortran/c plotting library) for  
>>>>> many years
>>>>> now, and the equivalent to imshow is called PGGRAY (or PGIMAG).  
>>>>> One of
>>>>> the arguments this function takes is a 6-element array TR which  
>>>>> is a
>>>>> transformation matrix. From the PGPLOT documentation:
>>>>>
>>>>> "The transformation matrix TR is used to calculate the world
>>>>> coordinates of the center of the "cell" that represents each array
>>>>> element. The world coordinates of the center of the cell  
>>>>> corresponding
>>>>> to array element A(I,J) are given by:
>>>>> X = TR(1) + TR(2)*I + TR(3)*J
>>>>> Y = TR(4) + TR(5)*I + TR(6)*J"
>>>>
>>>> You could do this with the Axes.pcolormesh method.  You could  
>>>> start with
>>>> an unrotated grid (generated by meshgrid, for example), apply your
>>>> rotation, and use that transformed grid in pcolormesh.  Note that
>>>> pcolormesh requires the grid for the cell boundaries, not centers.
>>>>
>>>
>>> It should work with imshow() as well if you can set the affine  
>>> component
>>> of the transform to the desired values. Which it looks like you  
>>> can in
>>> Affine2D(). (The affine matrix is the elements of TR listed  
>>> above, it
>>> appears.)
>>>
>>> I have not tried to do this, however -- just saying that I think  
>>> it's
>>> possible.
>>>
>>> -Andrew
>

Thomas Robitaille wrote:
> It looks like rotation/translation should be easy to do with Affine2D, 
> so I tried using it, but I can't seem to get it to work as expected - 
> here is an example of how I am using it:

Based on a quick look at image.py and _image.cpp, it appears that there 
is a low-level capability to rotate an image in the latter, but no 
support at higher levels.  It also looks to me like adding that support 
would not be trivial--doing it right would take more than just calling 
the low-level apply_rotation method.  Mike D. would be the expert on 
this, though.

Eric

> 
> import numpy as np
> from matplotlib.pyplot import *
> from matplotlib.transforms import Affine2D
> 
> im = np.random.random((10,10))
> tr = Affine2D().rotate_deg(45.)
> 
> fig = figure()
> ax = fig.add_subplot(111)
> ax.imshow(im,transform=tr)
> fig.canvas.draw()
> 
> Am I doing something wrong?
> 
> Thanks!
> 
> Thomas
> 
> On Mar 13, 2009, at 5:20 PM, Andrew Straw wrote:
> 
>> Eric Firing wrote:
>>> Thomas Robitaille wrote:
>>>> Hello,
>>>>
>>>> I was wondering whether there is a way to rotate a grayscale/
>>>> colorscale when using imshow.
>>>>
>>>> I have been using PGPLOT (a fortran/c plotting library) for many years
>>>> now, and the equivalent to imshow is called PGGRAY (or PGIMAG). One of
>>>> the arguments this function takes is a 6-element array TR which is a
>>>> transformation matrix. From the PGPLOT documentation:
>>>>
>>>> "The transformation matrix TR is used to calculate the world
>>>> coordinates of the center of the "cell" that represents each array
>>>> element. The world coordinates of the center of the cell corresponding
>>>> to array element A(I,J) are given by:
>>>> X = TR(1) + TR(2)*I + TR(3)*J
>>>> Y = TR(4) + TR(5)*I + TR(6)*J"
>>>
>>> You could do this with the Axes.pcolormesh method.  You could start with
>>> an unrotated grid (generated by meshgrid, for example), apply your
>>> rotation, and use that transformed grid in pcolormesh.  Note that
>>> pcolormesh requires the grid for the cell boundaries, not centers.
>>>
>>
>> It should work with imshow() as well if you can set the affine component
>> of the transform to the desired values. Which it looks like you can in
>> Affine2D(). (The affine matrix is the elements of TR listed above, it
>> appears.)
>>
>> I have not tried to do this, however -- just saying that I think it's
>> possible.
>>
>> -Andrew
>