matplotlib-users Mailing List for matplotlib

Hi,

I just committed a patch to do this in svn, also allowing for contour
lines along other directions.

See the attached image for an example.

Cheers,
Reinier

On Thu, Dec 3, 2009 at 10:01 AM, Matthias Michler
<Mat...@gm...> wrote:
> Thanks a lot!
>
> Regards,
> Matthias
>
> On Wednesday 02 December 2009 17:10:54 Reinier Heeres wrote:
>> Hi Matthias,
>>
>> I have a similar patch lying around somewhere, and I will try to apply
>> it soon. I've been terribly busy lately, but I expect some nice
>> mplot3d enhancements in the very near future.
>>
>> Regards,
>> Reinier
>>
>> On Wed, Dec 2, 2009 at 4:22 PM, Matthias Michler
>>
>> <Mat...@gm...> wrote:
>> > Hi Andrew,
>> >
>> > do you have any idea if the patch (or a part of it) may get a part of
>> > matplotlib-svn some day?
>> >
>> > Kind regards,
>> > Matthias
>> >
>> > On Friday 09 October 2009 23:25:28 Andrew Straw wrote:
>> >> Matthias Michler wrote:
>> >> > Hello list,
>> >> >
>> >> > I'm not an expert in axes3d, but in case the feature which Nicolas
>> >> > requested is not possible in an easy manner up to now, I propose an
>> >> > additional kwarg for axes3d.Axes3D.contour. Something like *offset*.
>> >> > If offset is None the z-values of the contour lines corresponds to
>> >> > given Z and otherwise offset is used for the z-values of the contour
>> >> > lines. I attached a changed axes3d.py and a patch against current svn.
>> >> > The result is illustrated in the contour3d_demo.png.
>> >> >
>> >> > Could any of the experts have a look at it and tell me if this could
>> >> > be useful, please?
>> >> >
>> >> > Thanks in advance for any comments.
>> >> >
>> >> > Kind regards
>> >> > Matthias
>> >> >
>> >> > On Wednesday 30 September 2009 19:22:42 Nicolas Bigaouette wrote:
>> >> >> Hi,
>> >> >> I have a nice plot_surface() using mplot3d (see attachement).
>> >> >>
>> >> >> I'd like to project the surface on the axis xoy, xoz and yoz with a
>> >> >> contour, similar to this figure:
>> >> >> http://homepages.ulb.ac.be/~dgonze/INFO/matlab/fig19.jpg
>> >> >>
>> >> >> Is it possible using matplotlib and mplot3d?
>> >> >>
>> >> >> Thanx!
>> >>
>> >> Hi Matthias,
>> >>
>> >> I committed your patch to a github branch of MPL, but I'll let Reinier
>> >> actually commit something based on this to MPL.
>> >> http://github.com/astraw/matplotlib/tree/dev/michler-3d-contourf-offsets
>> >>
>> >> -Andrew
>
>
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-- 
Reinier Heeres
Tel: +31 6 10852639

I use to save my plots as tiff. The color model of these plots is RGB. Can I change it to CMYK?

mar...@if... wrote:
> 
> Hello,
> 
> let's say I have given an image of distance values, which I display with 
> the jet colormap. Now if there are invalid pixels within the image they 
> have the value -1 or -2. Is there a way to display just the "valid" 
> image with the jet colorbar and the -1 pixels as white pixels and the -2 
> pixels as black pixels?

See 
http://matplotlib.sourceforge.net/examples/pylab_examples/image_masked.html.

You might need to use a masked array and mask the -2 values.

Eric

> 
> Till now I scale the image with vmin, vmax:
> 
>  >>> vmin = img[(img != -1) & (img != -2)].min()
>  >>> vmax = img[(img != -1) & (img != -2)].max()
>  >>> imshow(img, vmin=vmin, vmax=vmax, interpolation = 'nearest')
> 
> But how can I now paint the black and white pixels?
> 
> Regards,
> 
> Markus
> 
> 
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Hello,

According to http://matplotlib.sourceforge.net/api/ 
pyplot_api.html#matplotlib.pyplot.scatter , the keyword argument that  
takes an array to specify the colors of the individual markers is c.  
color is interpreted as a color to give to all markers at once.

The following works on my computer (matplotlib 0.99.0) :

import numpy as N
from matplotlib import pyplot as P

x = N.random.randn(100)
y = N.random.randn(100)
z = N.random.randn(100)**2

fig = P.figure()
ax = fig.add_subplot(1,1,1)

cmap = P.matplotlib.cm.jet
norm = P.matplotlib.colors.Normalize(vmin=0, vmax=1)

sc = ax.scatter(x,y,
                  c=z,
                  cmap=cmap,
                  norm=norm,
                  )



Le 10 déc. 09 à 14:44, Yannick Copin a écrit :

> Hi,
>
> according to the documentation, scatter should accept a 1D float  
> array for
> color kwarg. Therefore, I thought the following code would work  
> (and I think
> it worked at some point in the past; I'm currently using matplotlib  
> 0.99.0):
>
> import numpy as N
> from matplotlib import pyplot as P
>
> x = N.random.randn(100)
> y = N.random.randn(100)
> z = N.random.randn(100)**2
>
> fig = P.figure()
> ax = fig.add_subplot(1,1,1)
>
> cmap = P.matplotlib.cm.jet
> norm = P.matplotlib.colors.Normalize(vmin=0, vmax=1)
>
> sc = ax.scatter(x,y,
>                  color=z,
>                  cmap=cmap,
>                  norm=norm,
>                  )
>
> But this crashes with the following error:
>
> [...]

Thanks, the svn version is working nicely.

Cheers
Mike

On 12/09/2009 01:21 PM, Michael Droettboom wrote:
> I can confirm this bug on matplotlib-0.99.0, and 0.99.1.2, but not on
> SVN head. I think this is related to a recently fixed bug involving the
> renderer outputting single-point lines (which obviously doesn't make
> sense, and Postscript has problems with).
>
> You can either install from SVN (I recommend using the 0.99.x branch
> [1], rather than the trunk), or set the rcParam 'path.simplify' to
> False. Unfortunately, the latter will result in some very large file sizes.
>
> [1] https://matplotlib.svn.sf.net/svnroot/matplotlib/branches/v0_99_maint
>
> Cheers,
> Mike
>
> Michael Cohen wrote:
>> Hi there,
>> Does anyone know what might be the problem with this EPS write?
>> Please see my email of Dec 6th for the attachments.
>>
>> Regards,
>> Michael
>>
>> Michael Cohen wrote:
>>> Hi,
>>>
>>> Sorry for taking a few days to reply.
>>> Basic system information
>>>
>>> $ uname -a
>>> Linux shc-b 2.6.18-128.1.10.el5 #1 SMP Wed Apr 29 13:53:08 EDT 2009
>>> x86_64 x86_64 x86_64 GNU/Linux
>>> $ head -n1 /etc/issue
>>> Red Hat Enterprise Linux Server release 5.3 (Tikanga)
>>> $
>>>
>>> matplotlibrc attached.
>>>
>>> plot_test.py attached also.
>>>
>>> $ python
>>> Python 2.6.2 (r262:71600, Sep 16 2009, 13:37:23)
>>> [GCC 4.1.2 20080704 (Red Hat 4.1.2-44)] on linux2
>>> Type "help", "copyright", "credits" or "license" for more information.
>>> >>> import matplotlib
>>> >>> print matplotlib.__version__
>>> 0.99.0
>>> >>>
>>>
>>> finally, failed output eps also attached.
>>>
>>> The plot generates a set of horizontal and vertical lines to make a
>>> grid, and then applies the Mollweide projection to give latitude and
>>> longitude lines.
>>> For some reason, not running the projection (i.e. lines 43-51 in the
>>> python script) gives a file that outputs as a nice eps. If you do
>>> keep the Mollweide projection in, you still generate a lovely plot,
>>> but the savefig to .eps fails.
>>>
>>> Thanks,
>>> Michael
>>>
>>>
>>> John Hunter wrote:
>>>> On Wed, Dec 2, 2009 at 3:20 PM, Michael Cohen <mc...@ca...>
>>>> wrote:
>>>>> Hi,
>>>>> To add more information. I am trying this on two separate installs of
>>>>> matplotlib 0.99, both using TkAgg as the backend. One produces an
>>>>> unreadable file, the other does produce a readable EPS. However, even
>>>>> in this case, zooming in on the image shows that what is being
>>>>> saved is
>>>>> bitmapped, not a vector graphic.
>>>> Could you please post some sample code and the EPS it generates, as
>>>> well as platform information and any specific rc settings you may
>>>> have?
>>>>
>>>> Thanks,
>>>> JDH
>>
>> ------------------------------------------------------------------------------
>>
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>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hello,

let's say I have given an image of distance values, which I display with 
the jet colormap. Now if there are invalid pixels within the image they 
have the value -1 or -2. Is there a way to display just the "valid" image 
with the jet colorbar and the -1 pixels as white pixels and the -2 pixels 
as black pixels?

Till now I scale the image with vmin, vmax:

>>> vmin = img[(img != -1) & (img != -2)].min()
>>> vmax = img[(img != -1) & (img != -2)].max()
>>> imshow(img, vmin=vmin, vmax=vmax, interpolation = 'nearest')

But how can I now paint the black and white pixels?

Regards,

Markus

Unfortunately i have not found such a function as of yet and the function
that sound close to it (aspect) only controls the windows aspect ratio

Fortunately there is a quick and dirty work around


I have found the following to be useful

Assuming you have X Y Z matrices made using meshgrid or some other means

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np


fig = plt.figure()
ax = Axes3D(fig)

u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)

x = 10 * np.outer(np.cos(u), np.sin(v))
y = 10 * np.outer(np.sin(u), np.sin(v))
z = 50 * np.outer(np.ones(np.size(u)), np.cos(v))
ax.plot_surface(x, y, z,  rstride=4, cstride=4, color='b')



Xstart=(x.min())
Xend  =(x.max())

Ystart=(y.min())
Zstart=(z.min())

Scalex=(Xend-Xstart)


ax.set_xlim3d(Xstart,Xstart+Scale)
ax.set_ylim3d(Ystart,Ystart+Scale)
ax.set_zlim3d(Zstart,Zstart+Scale)

plt.show()

again I have made the assumption that the plot is "squarish" in the x and y
direction, a more robust version would test to see which is the biggest
scalex,scaley,scalez center the other axis value but again i just coded this
in 5 min as an example

-----Original Message-----
From: David Arnold [mailto:dwa...@su...] 
Sent: December-07-09 12:30 PM
To: mat...@li...
Subject: [Matplotlib-users] axis equal

All,

Is there an "axis equal" command for mplot3d?

D.

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Hi Mike,

Sorry for the slow reply, but I put support for this in the
development version in SVN. It can also do a bit of shading to make
the surface look more structured.

Note that the fact that a 40x40 grid turns into 39x39 squares is
expected behavior: the code assumes the 40 points are the *edges* of
the patches. There are only 39 patches between 40 points.

Regards,
Reinier

On Tue, Dec 1, 2009 at 3:06 AM, Mike Alger <ma...@ry...> wrote:
> After a weekend of no replies I managed to figure a way out myself
>
> As this was “left to the reader as an exercise” I will leave the integration
> or improvement of this solution as an exercise to the next reader
>
> What I have done is basically cloned the plot surface function and replaced
> the avgz variable with a reference to the “colors” parameter i have added to
> the function call.
>
> This code doesn’t  center things perfectly with respect to the grid (for
> some reason a 40x40 grid turns into 39x39 grid in the function) again this
> is something else that could be improved, however I am happy with it and a
> one pixel shift won’t be missed in my plots.  I also have no real clue as to
> what the following comments was about
>
>
>
>                 # The construction leaves the array with duplicate points,
> which
>
>                 # are removed here.
>
>
>
>  but it is probably related to my non centered plots.
>
>
>
>
>
>
>
>
>
> What follows is the modified function  :
>
>
>
>
>
>
>
> def plot_surface2(self, X, Y, Z, colors, *args, **kwargs):
>
>         '''
>
>         Create a surface plot.
>
>
>
>         By default it will be colored in shades of a solid color,
>
>         but it also supports color mapping by supplying the *cmap*
>
>         argument.
>
>
>
>         ==========  ================================================
>
>         Argument    Description
>
>         ==========  ================================================
>
>         *X*, *Y*,   Data values as numpy.arrays
>
>         *Z*
>
>         *colors*   an array the same size as z that contains a separate
> color data
>
>         *rstride*   Array row stride (step size)
>
>         *cstride*   Array column stride (step size)
>
>         *color*     Color of the surface patches
>
>         *cmap*      A colormap for the surface patches.
>
>         ==========  ================================================
>
>         '''
>
>
>
>         had_data = self.has_data()
>
>
>
>         rows, cols = Z.shape
>
>         tX, tY, tZ = np.transpose(X), np.transpose(Y), np.transpose(Z)
>
>         rstride = kwargs.pop('rstride', 10)
>
>         cstride = kwargs.pop('cstride', 10)
>
>
>
>         color = kwargs.pop('color', 'b')
>
>         color = np.array(colorConverter.to_rgba(color))
>
>         cmap = kwargs.get('cmap', None)
>
>
>
>         polys = []
>
>         normals = []
>
>         avgz = []
>
>         for rs in np.arange(0, rows-1, rstride):
>
>             for cs in np.arange(0, cols-1, cstride):
>
>                 ps = []
>
>                 corners = []
>
>                 for a, ta in [(X, tX), (Y, tY), (Z, tZ)]:
>
>                     ztop = a[rs][cs:min(cols, cs+cstride+1)]
>
>                     zleft = ta[min(cols-1, cs+cstride)][rs:min(rows,
> rs+rstride+1)]
>
>                     zbase = a[min(rows-1, rs+rstride)][cs:min(cols,
> cs+cstride+1):]
>
>                     zbase = zbase[::-1]
>
>                     zright = ta[cs][rs:min(rows, rs+rstride+1):]
>
>                     zright = zright[::-1]
>
>                     corners.append([ztop[0], ztop[-1], zbase[0], zbase[-1]])
>
>                     z = np.concatenate((ztop, zleft, zbase, zright))
>
>                     ps.append(z)
>
>
>
>                 # The construction leaves the array with duplicate points,
> which
>
>                 # are removed here.
>
>                 ps = zip(*ps)
>
>                 lastp = np.array([])
>
>                 ps2 = []
>
>                 avgzsum = 0.0
>
>                 for p in ps:
>
>                     if p != lastp:
>
>                         ps2.append(p)
>
>                         lastp = p
>
>                         avgzsum += p[2]
>
>                 polys.append(ps2)
>
>                 ##################################
>
>                 Begin of changes
>
> ##################################
>
>                 #avgz.append(avgzsum / len(ps2))
>
> avgz.append(colors[rs][cs])
>
>                 ##################################
>
>                 end of changes
>
> ##################################
>
>
>
>                 v1 = np.array(ps2[0]) - np.array(ps2[1])
>
>                 v2 = np.array(ps2[2]) - np.array(ps2[0])
>
>                 normals.append(np.cross(v1, v2))
>
>
>
>         polyc = art3d.Poly3DCollection(polys, *args, **kwargs)
>
>         if cmap is not None:
>
>          #  polyc.set_array(np.array(colors))
>
>             polyc.set_array(np.array(avgz))
>
>             polyc.set_linewidth(0)
>
>         else:
>
>             colors = self._shade_colors(color, normals)
>
>             polyc.set_facecolors(colors)
>
>
>
>         self.add_collection(polyc)
>
>         self.auto_scale_xyz(X, Y, Z, had_data)
>
>
>
>         return polyc
>
>
>
>
>
> From: Mike Alger [mailto:ma...@ry...]
> Sent: November-25-09 8:42 PM
> To: mat...@li...
> Subject: Re: [Matplotlib-users] Color in 3d plots
>
>
>
> I have been looking at this for the past day and in am pretty sure I could
> replace the instance of polyc by the “cmap if statements” my colour array
> and I should be able to get close to what I want. However I am new to both
> python & mpl, and I am not entirely sure in how I would go about testing my
> hypothesis. Furthermore I am also relatively new to submitting fixes to
> open-source projects so I have lots of questions about how I would go about
> suggesting a modification.
>
>
>
> 1.)    can I just modify the file in the
> C:\python26\Lib\site-packages\mpl-toolkits\mplot3d\axes3d.py file to do my
> tests?
>
> a.       Also, where are these files usually kept in a linux environment ?
>
> b.      What do I do with the. pyc files with the same name? are they
> re-complied automatically when I call the function externally?
>
> 2.)    Is this capability  already built in with the colour argument ? if so
> how do I properly call it?
>
> 3.)    If I do make a modification should it be as a separate function with
> the additional variable or should I try to stuff the new capability into the
> old function
>
> 4.)    is there a clean easy to follow tutorial for submitting changes via
> svn or can I rely on someone else to do the final commit?
>
>
>
> I have attached the function in question for reference to save others from
> digging down into their python directories
>
>
>
>
>
> Again thanks for taking your time to help me figure this out
>
>
>
> Mike Alger
>
>
>
> < Code>
>
>   def plot_surface(self, X, Y, Z, *args, **kwargs):
>
>         '''
>
>         Create a surface plot.
>
>
>
>         By default it will be colored in shades of a solid color,
>
>         but it also supports color mapping by supplying the *cmap*
>
>         argument.
>
>
>
>         ==========  ================================================
>
>         Argument    Description
>
>         ==========  ================================================
>
>         *X*, *Y*,   Data values as numpy.arrays
>
>         *Z*
>
>         *rstride*   Array row stride (step size)
>
>         *cstride*   Array column stride (step size)
>
>         *color*     Color of the surface patches
>
>         *cmap*      A colormap for the surface patches.
>
>         ==========  ================================================
>
>         '''
>
>
>
>         had_data = self.has_data()
>
>
>
>         rows, cols = Z.shape
>
>         tX, tY, tZ = np.transpose(X), np.transpose(Y), np.transpose(Z)
>
>         rstride = kwargs.pop('rstride', 10)
>
>         cstride = kwargs.pop('cstride', 10)
>
>
>
>         color = kwargs.pop('color', 'b')
>
>         color = np.array(colorConverter.to_rgba(color))
>
>         cmap = kwargs.get('cmap', None)
>
>
>
>         polys = []
>
>         normals = []
>
>         avgz = []
>
>         for rs in np.arange(0, rows-1, rstride):
>
>             for cs in np.arange(0, cols-1, cstride):
>
>                 ps = []
>
>                 corners = []
>
>                 for a, ta in [(X, tX), (Y, tY), (Z, tZ)]:
>
>                     ztop = a[rs][cs:min(cols, cs+cstride+1)]
>
>                     zleft = ta[min(cols-1, cs+cstride)][rs:min(rows,
> rs+rstride+1)]
>
>                     zbase = a[min(rows-1, rs+rstride)][cs:min(cols,
> cs+cstride+1):]
>
>                     zbase = zbase[::-1]
>
>                     zright = ta[cs][rs:min(rows, rs+rstride+1):]
>
>                     zright = zright[::-1]
>
>                     corners.append([ztop[0], ztop[-1], zbase[0], zbase[-1]])
>
>                     z = np.concatenate((ztop, zleft, zbase, zright))
>
>                     ps.append(z)
>
>
>
>                 # The construction leaves the array with duplicate points,
> which
>
>                 # are removed here.
>
>                 ps = zip(*ps)
>
>                 lastp = np.array([])
>
>                 ps2 = []
>
>                 avgzsum = 0.0
>
>                 for p in ps:
>
>                     if p != lastp:
>
>                         ps2.append(p)
>
>                         lastp = p
>
>                         avgzsum += p[2]
>
>                 polys.append(ps2)
>
>                 avgz.append(avgzsum / len(ps2))
>
>
>
>                 v1 = np.array(ps2[0]) - np.array(ps2[1])
>
>                 v2 = np.array(ps2[2]) - np.array(ps2[0])
>
>                 normals.append(np.cross(v1, v2))
>
>
>
>         polyc = art3d.Poly3DCollection(polys, *args, **kwargs) ## this is
> where a modification could be made to allow for a separate colour matrix
>
>         if cmap is not None:
>
>             polyc.set_array(np.array(avgz))
>
>             polyc.set_linewidth(0)
>
>         else:
>
>             colors = self._shade_colors(color, normals)
>
>             polyc.set_facecolors(colors)
>
>
>
>         self.add_collection(polyc)
>
>         self.auto_scale_xyz(X, Y, Z, had_data)
>
>
>
>         return polyc
>
> </Code>
>
>
>
> From: Mike Alger [mailto:mik...@ng...]
> Sent: November-23-09 3:42 PM
> To: mat...@li...
> Subject: [Matplotlib-users] Color in 3d plots
>
>
>
> This may be a dumb question, however I have been scratching my head trying
> to figure out how to plot a 3 dimensional plot with with a colour map
> different from the elevation(Z) parameter.
>
>
>
> An example of this done in Matlab would be
>
>
>
> [X,Y,Z] = peaks(30);
>
> C=Z'% could be anything other than Z as long as it has the same dimensions
>
> surf(X,Y,Z,C)
>
>
>
> axis([-3 3 -3 3 -10 5])
>
>
>
>
>
> Is this possible with matplotlib '0.99.1'
>
>
>
> If so how do i go about doing this  is there some sample code?
>
>
>
> Mike Alger, M.A.Sc
>
> ma...@ry...
>
>
>
> ------------------------------------------------------------------------------
> Join us December 9, 2009 for the Red Hat Virtual Experience,
> a free event focused on virtualization and cloud computing.
> Attend in-depth sessions from your desk. Your couch. Anywhere.
> http://p.sf.net/sfu/redhat-sfdev2dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>



-- 
Reinier Heeres
Tel: +31 6 10852639

I had a hunch that was the case but wasn`t entirely sure, and to be honest
3d plot functions have always been a black box for me and  i have never
really thought about what exactly gets plotted in 3d plot until now

Thanks again 
Reinier i will take a look at the SVN A.S.A.P. 

Mike

-----Original Message-----
From: Reinier Heeres [mailto:re...@he...] 
Sent: December-09-09 7:17 PM
To: Mike Alger
Cc: mat...@li...
Subject: Re: [Matplotlib-users] Color in 3d plots

Hi Mike,

Sorry for the slow reply, but I put support for this in the
development version in SVN. It can also do a bit of shading to make
the surface look more structured.

Note that the fact that a 40x40 grid turns into 39x39 squares is
expected behavior: the code assumes the 40 points are the *edges* of
the patches. There are only 39 patches between 40 points.

Regards,
Reinier

On Tue, Dec 1, 2009 at 3:06 AM, Mike Alger <ma...@ry...> wrote:
> After a weekend of no replies I managed to figure a way out myself
>
> As this was “left to the reader as an exercise” I will leave the
integration
> or improvement of this solution as an exercise to the next reader
>
> What I have done is basically cloned the plot surface function and
replaced
> the avgz variable with a reference to the “colors” parameter i have added
to
> the function call.
>
> This code doesn’t  center things perfectly with respect to the grid (for
> some reason a 40x40 grid turns into 39x39 grid in the function) again this
> is something else that could be improved, however I am happy with it and a
> one pixel shift won’t be missed in my plots.  I also have no real clue as
to
> what the following comments was about
>
>
>
>                 # The construction leaves the array with duplicate points,
> which
>
>                 # are removed here.
>
>
>
>  but it is probably related to my non centered plots.
>
>
>
>
>
>
>
>
>
> What follows is the modified function  :
>
>
>
>
>
>
>
> def plot_surface2(self, X, Y, Z, colors, *args, **kwargs):
>
>         '''
>
>         Create a surface plot.
>
>
>
>         By default it will be colored in shades of a solid color,
>
>         but it also supports color mapping by supplying the *cmap*
>
>         argument.
>
>
>
>         ==========  ================================================
>
>         Argument    Description
>
>         ==========  ================================================
>
>         *X*, *Y*,   Data values as numpy.arrays
>
>         *Z*
>
>         *colors*   an array the same size as z that contains a separate
> color data
>
>         *rstride*   Array row stride (step size)
>
>         *cstride*   Array column stride (step size)
>
>         *color*     Color of the surface patches
>
>         *cmap*      A colormap for the surface patches.
>
>         ==========  ================================================
>
>         '''
>
>
>
>         had_data = self.has_data()
>
>
>
>         rows, cols = Z.shape
>
>         tX, tY, tZ = np.transpose(X), np.transpose(Y), np.transpose(Z)
>
>         rstride = kwargs.pop('rstride', 10)
>
>         cstride = kwargs.pop('cstride', 10)
>
>
>
>         color = kwargs.pop('color', 'b')
>
>         color = np.array(colorConverter.to_rgba(color))
>
>         cmap = kwargs.get('cmap', None)
>
>
>
>         polys = []
>
>         normals = []
>
>         avgz = []
>
>         for rs in np.arange(0, rows-1, rstride):
>
>             for cs in np.arange(0, cols-1, cstride):
>
>                 ps = []
>
>                 corners = []
>
>                 for a, ta in [(X, tX), (Y, tY), (Z, tZ)]:
>
>                     ztop = a[rs][cs:min(cols, cs+cstride+1)]
>
>                     zleft = ta[min(cols-1, cs+cstride)][rs:min(rows,
> rs+rstride+1)]
>
>                     zbase = a[min(rows-1, rs+rstride)][cs:min(cols,
> cs+cstride+1):]
>
>                     zbase = zbase[::-1]
>
>                     zright = ta[cs][rs:min(rows, rs+rstride+1):]
>
>                     zright = zright[::-1]
>
>                     corners.append([ztop[0], ztop[-1], zbase[0],
zbase[-1]])
>
>                     z = np.concatenate((ztop, zleft, zbase, zright))
>
>                     ps.append(z)
>
>
>
>                 # The construction leaves the array with duplicate points,
> which
>
>                 # are removed here.
>
>                 ps = zip(*ps)
>
>                 lastp = np.array([])
>
>                 ps2 = []
>
>                 avgzsum = 0.0
>
>                 for p in ps:
>
>                     if p != lastp:
>
>                         ps2.append(p)
>
>                         lastp = p
>
>                         avgzsum += p[2]
>
>                 polys.append(ps2)
>
>                 ##################################
>
>                 Begin of changes
>
> ##################################
>
>                 #avgz.append(avgzsum / len(ps2))
>
> avgz.append(colors[rs][cs])
>
>                 ##################################
>
>                 end of changes
>
> ##################################
>
>
>
>                 v1 = np.array(ps2[0]) - np.array(ps2[1])
>
>                 v2 = np.array(ps2[2]) - np.array(ps2[0])
>
>                 normals.append(np.cross(v1, v2))
>
>
>
>         polyc = art3d.Poly3DCollection(polys, *args, **kwargs)
>
>         if cmap is not None:
>
>          #  polyc.set_array(np.array(colors))
>
>             polyc.set_array(np.array(avgz))
>
>             polyc.set_linewidth(0)
>
>         else:
>
>             colors = self._shade_colors(color, normals)
>
>             polyc.set_facecolors(colors)
>
>
>
>         self.add_collection(polyc)
>
>         self.auto_scale_xyz(X, Y, Z, had_data)
>
>
>
>         return polyc
>
>
>
>
>
> From: Mike Alger [mailto:ma...@ry...]
> Sent: November-25-09 8:42 PM
> To: mat...@li...
> Subject: Re: [Matplotlib-users] Color in 3d plots
>
>
>
> I have been looking at this for the past day and in am pretty sure I could
> replace the instance of polyc by the “cmap if statements” my colour array
> and I should be able to get close to what I want. However I am new to both
> python & mpl, and I am not entirely sure in how I would go about testing
my
> hypothesis. Furthermore I am also relatively new to submitting fixes to
> open-source projects so I have lots of questions about how I would go
about
> suggesting a modification.
>
>
>
> 1.)    can I just modify the file in the
> C:\python26\Lib\site-packages\mpl-toolkits\mplot3d\axes3d.py file to do my
> tests?
>
> a.       Also, where are these files usually kept in a linux environment ?
>
> b.      What do I do with the. pyc files with the same name? are they
> re-complied automatically when I call the function externally?
>
> 2.)    Is this capability  already built in with the colour argument ? if
so
> how do I properly call it?
>
> 3.)    If I do make a modification should it be as a separate function
with
> the additional variable or should I try to stuff the new capability into
the
> old function
>
> 4.)    is there a clean easy to follow tutorial for submitting changes via
> svn or can I rely on someone else to do the final commit?
>
>
>
> I have attached the function in question for reference to save others from
> digging down into their python directories
>
>
>
>
>
> Again thanks for taking your time to help me figure this out
>
>
>
> Mike Alger
>
>
>
> < Code>
>
>   def plot_surface(self, X, Y, Z, *args, **kwargs):
>
>         '''
>
>         Create a surface plot.
>
>
>
>         By default it will be colored in shades of a solid color,
>
>         but it also supports color mapping by supplying the *cmap*
>
>         argument.
>
>
>
>         ==========  ================================================
>
>         Argument    Description
>
>         ==========  ================================================
>
>         *X*, *Y*,   Data values as numpy.arrays
>
>         *Z*
>
>         *rstride*   Array row stride (step size)
>
>         *cstride*   Array column stride (step size)
>
>         *color*     Color of the surface patches
>
>         *cmap*      A colormap for the surface patches.
>
>         ==========  ================================================
>
>         '''
>
>
>
>         had_data = self.has_data()
>
>
>
>         rows, cols = Z.shape
>
>         tX, tY, tZ = np.transpose(X), np.transpose(Y), np.transpose(Z)
>
>         rstride = kwargs.pop('rstride', 10)
>
>         cstride = kwargs.pop('cstride', 10)
>
>
>
>         color = kwargs.pop('color', 'b')
>
>         color = np.array(colorConverter.to_rgba(color))
>
>         cmap = kwargs.get('cmap', None)
>
>
>
>         polys = []
>
>         normals = []
>
>         avgz = []
>
>         for rs in np.arange(0, rows-1, rstride):
>
>             for cs in np.arange(0, cols-1, cstride):
>
>                 ps = []
>
>                 corners = []
>
>                 for a, ta in [(X, tX), (Y, tY), (Z, tZ)]:
>
>                     ztop = a[rs][cs:min(cols, cs+cstride+1)]
>
>                     zleft = ta[min(cols-1, cs+cstride)][rs:min(rows,
> rs+rstride+1)]
>
>                     zbase = a[min(rows-1, rs+rstride)][cs:min(cols,
> cs+cstride+1):]
>
>                     zbase = zbase[::-1]
>
>                     zright = ta[cs][rs:min(rows, rs+rstride+1):]
>
>                     zright = zright[::-1]
>
>                     corners.append([ztop[0], ztop[-1], zbase[0],
zbase[-1]])
>
>                     z = np.concatenate((ztop, zleft, zbase, zright))
>
>                     ps.append(z)
>
>
>
>                 # The construction leaves the array with duplicate points,
> which
>
>                 # are removed here.
>
>                 ps = zip(*ps)
>
>                 lastp = np.array([])
>
>                 ps2 = []
>
>                 avgzsum = 0.0
>
>                 for p in ps:
>
>                     if p != lastp:
>
>                         ps2.append(p)
>
>                         lastp = p
>
>                         avgzsum += p[2]
>
>                 polys.append(ps2)
>
>                 avgz.append(avgzsum / len(ps2))
>
>
>
>                 v1 = np.array(ps2[0]) - np.array(ps2[1])
>
>                 v2 = np.array(ps2[2]) - np.array(ps2[0])
>
>                 normals.append(np.cross(v1, v2))
>
>
>
>         polyc = art3d.Poly3DCollection(polys, *args, **kwargs) ## this is
> where a modification could be made to allow for a separate colour matrix
>
>         if cmap is not None:
>
>             polyc.set_array(np.array(avgz))
>
>             polyc.set_linewidth(0)
>
>         else:
>
>             colors = self._shade_colors(color, normals)
>
>             polyc.set_facecolors(colors)
>
>
>
>         self.add_collection(polyc)
>
>         self.auto_scale_xyz(X, Y, Z, had_data)
>
>
>
>         return polyc
>
> </Code>
>
>
>
> From: Mike Alger [mailto:mik...@ng...]
> Sent: November-23-09 3:42 PM
> To: mat...@li...
> Subject: [Matplotlib-users] Color in 3d plots
>
>
>
> This may be a dumb question, however I have been scratching my head trying
> to figure out how to plot a 3 dimensional plot with with a colour map
> different from the elevation(Z) parameter.
>
>
>
> An example of this done in Matlab would be
>
>
>
> [X,Y,Z] = peaks(30);
>
> C=Z'% could be anything other than Z as long as it has the same dimensions
>
> surf(X,Y,Z,C)
>
>
>
> axis([-3 3 -3 3 -10 5])
>
>
>
>
>
> Is this possible with matplotlib '0.99.1'
>
>
>
> If so how do i go about doing this  is there some sample code?
>
>
>
> Mike Alger, M.A.Sc
>
> ma...@ry...
>
>
>
>
----------------------------------------------------------------------------
--
> Join us December 9, 2009 for the Red Hat Virtual Experience,
> a free event focused on virtualization and cloud computing.
> Attend in-depth sessions from your desk. Your couch. Anywhere.
> http://p.sf.net/sfu/redhat-sfdev2dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>



-- 
Reinier Heeres
Tel: +31 6 10852639