matplotlib-users Mailing List for matplotlib (Page 12)

Hi.  I am trying to output multiple 2D graphs (subplots) in one figure
(using pylab) for each time-step that the python code runs - basically an
interactive graphs.  We use the 'ion()' and 'imshow()' functions for this.
I have many graphs to chose from, but say if I chose 4 graphs to output, all
4 will output for the 1st time step, but for every additional time step only
the last graph will update.  The first 3 will remain the same, as they were
in the 1st time step.  Has anyone has this problem?  Any suggestions?

A portion of the O-O code is below.  This function is called in another
file. I tried to add notes where I thought they were helpful.

    def multi_display(self, n=4):

        ''' displaying multiple graphs '''

        ion()
        m = self.displayed_multi     # four input graph names (provided when
function is called)
        nsub = n      # no. of subgraphs/time step

        for i in range(nsub): # for each subplot

            p = i +1
            exec ("self.subplot" + str(p) + " = subplot(2, 2, p)")   # OR
subplot(2,2,p)

            self.displayed = m[i]
            self.display_stand()   # this calls the function below  with
'self.displayed' in it.

def display_stand(self): # displays individual graphs

        if self.displayed == 'ht': # this is only one of the four graphs (or
subplots)

            vm = 0.0
            vx = 40.0
            t = 'Height (m)'
            imshow(self.old_ht, vmin = vm, vmax = vx,
               interpolation = 'nearest')
            title(t)

Thanks,
Louise

On Mon, Jul 13, 2009 at 4:56 PM, Uri Laserson<las...@mi...> wrote:
> Hi everyone,
>
> I am trying to create some brand new types of plots for a unique data set
> that I have.  My question basically boils down to getting some advice on
> what is the proper way to set up a function that will act like one of the
> matplotlib pyplot functions (e.g., have all the same behavior regarding
> interactive stuff, resizing, etc.).

Most of the pyplot functions are wrapper around the method in the Axes class.
For example, pyplot.plot is basically

 ax = gca()
 ax.plot()
 draw_if_interactive()

And the basic role of the plotting method in the Axes class is to
create appropriate
matplotlib artists and add them to the axes. If your plot can be
created with matplotlib's currently existing artists, you can simply
reuse them. Otherwise, you need to create your own artist, but this
requires some understandings of internals.

For example,

def ax_my_plot(ax, *kl, **ka):
    # create artists and add them to ax

def my_plot(*kl, **ka):
    ax = gca()
    ax_my_plot(ax, *kl, **ka)
    draw_if_interactive()

"my_plot" will behave similar to other pyplot command.

>
> I have been looking through some of the code for the major functions like
> plot, but have been having trouble parsing it.  I think that some of this is
> obfuscated in the complexity of the functions.
>
> At some level, I would also like to be able to draw on the canvas in a very
> explicit way, like in Processing (http://processing.org/); what is the best
> way to approach this?

You can draw something in the canvas coordinate. But what you can do
is limited by the matplotlib's backend api, which is more like a
vector drawing tool. So things like a pixel manipulation is not
suitable.

Regards,

-JJ

>
> Another thing that could be really nice is to have some boilerplate
> framework that someone could start with to quickly write functions that
> integrate well into the rest of matplotlib.
>
> (And sorry if I am sounding critical of the package.  I actually love it,
> and have been quite the MPL evangelist in my little section of Boston.)
>
> Any suggestions are welcome.
>
> Uri
>
> --
> Uri Laserson
> PhD Candidate, Biomedical Engineering
> Harvard Medical School (Genetics)
> Massachusetts Institute of Technology (Mathematics)
> phone +1 917 742 8019
> las...@mi...
>
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>

Check the gallery where a few example shows you how to draw arrows.

My recommendation is to use "annotate" with empty string.

e.g.,

annotate("", (1,2), xytext=(5,2), arrowprops=dict(fc="b"))

http://matplotlib.sourceforge.net/api/pyplot_api.html?highlight=annotate#matplotlib.pyplot.annotate

However, a line with an arrow in the middle is not supported. But
something like below may be close enough?

annotate("", (3,5), xytext=(5,5),
         arrowprops=dict(arrowstyle="->", fc="b", shrinkB=0))
annotate("", (1,5), xytext=(3,5),
         arrowprops=dict(arrowstyle="-", fc="b", shrinkA=0))

-JJ


On Tue, Jul 14, 2009 at 2:13 PM, Afi Welbeck<wel...@ya...> wrote:
> Hi all,
>
> I'm a newbie, I'm trying to plot a line with an arrow
> (arrow in the  middle and another with an arrow at
> the end) with the following points: [1, 2] and [5, 2]
> Could anyone please help me with the code?
> Thanks.
> Harriet A. Welbeck
>
>
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>

http://matplotlib.sourceforge.net/api/pyplot_api.html?highlight=errorbar#matplotlib.pyplot.errorbar

As described in the doc, the errorbar command creates lines and line
collections, where the  errorbars  are created as line collections.
Axes.collections contains the list of collection artist that belong to
the axes hence this is the place.

However, I don't think manipulating Axes.collections (and the return
value of get_lines() ) in this way is a good idea. All the artist
added to an axes has "remove" method. When called, the artist remove
itself from the axes it belongs.

I'm not sure what your intention is, but if you want to temporarily
remove some artists from the axes, it would be easier  to make them
simply invisible. Otherwise, I recommend you to use the remove method.

Regards,

-JJ



On Tue, Jul 14, 2009 at 6:13 PM, Jack Sankey<jac...@gm...> wrote:
> Hello,
> I'm writing a script that removes data from plots by looping over
> axes.get_lines(), removing data, then using axes.set_lines(). It works quite
> well, but when it's a plot with error bars, the vertical part of the error
> bar is not disappearing.
> I'm assuming the vertical part is a vline or something and so should not be
> with the other lines. Where does this data get stuck? :)
> Thanks!
> Jack
> ------------------------------------------------------------------------------
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Hi matplotters,

I am trying to create an image and save it to pdf.
Unfortunately, the result is much different if I save it to pdf, eps  
or png.
I am on Mac OS X 10.4, using qt4 4.5.0 and the qt4agg backend (but  
the problems also occur with -dmacosx).

The plot I am trying to make is an overlay of hists + datapoints with  
errorbars.
The png roughly looks like I would expect (although I can't figure  
out how to plot a straight black horizontal line at y=0. pylab.plot  
doesn't seem to do what I want)
The eps doesn't get filled with the correct colors, and the pdf and  
the svg don't work at all.

The error message for saving as svg is inlined below the message.
The rest of the files should be accessible at https:// 
jstrube.web.cern.ch/jstrube/matplotlib_testcase/
You need the python bindings to CERN's ROOT libraries if you want to  
reproduce the plot.

Any help is greatly appreciated.
Cheers,
     Jan

   File "analyzeLambdaPbarGammaShape.py", line 128, in <module>
     pl.savefig('lambdaPbarGamma_all.svg')
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/pyplot.py", line 354, in savefig
     return fig.savefig(*args, **kwargs)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/figure.py", line 1002, in savefig
     self.canvas.print_figure(*args, **kwargs)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/backends/backend_qt4agg.py", line  
144, in print_figure
     FigureCanvasAgg.print_figure(self, *args, **kwargs)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/backend_bases.py", line 1476, in  
print_figure
     **kwargs)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/backend_bases.py", line 1355, in  
print_svg
     return svg.print_svg(*args, **kwargs)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/backends/backend_svg.py", line  
615, in print_svg
     return self._print_svg(filename, svgwriter, fh_to_close, **kwargs)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/backends/backend_svg.py", line  
650, in _print_svg
     self.figure.draw(renderer)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/artist.py", line 46, in draw_wrapper
     draw(artist, renderer, *kl)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/figure.py", line 774, in draw
     for a in self.axes: a.draw(renderer)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/artist.py", line 46, in draw_wrapper
     draw(artist, renderer, *kl)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/axes.py", line 1826, in draw
     a.draw(renderer)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/artist.py", line 46, in draw_wrapper
     draw(artist, renderer, *kl)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/patches.py", line 326, in draw
     renderer.draw_path(gc, tpath, affine, rgbFace)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/backends/backend_svg.py", line  
233, in draw_path
     self._draw_svg_element('path', 'd="%s"' % path_data, gc, rgbFace)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/backends/backend_svg.py", line 69,  
in _draw_svg_element
     style = self._get_style(gc, rgbFace)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/backends/backend_svg.py", line  
121, in _get_style
     fill = "url(#%s)" % self._get_hatch(gc, rgbFace)
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/backends/backend_svg.py", line  
107, in _get_hatch
     (HATCH_SIZE+1, HATCH_SIZE+1, rgb2hex(rgbFace)))
   File "/Library/Frameworks/Python.framework/Versions/2.6/lib/ 
python2.6/site-packages/matplotlib/colors.py", line 221, in rgb2hex
     return '#%02x%02x%02x' % tuple([round(val*255) for val in rgb])
TypeError: 'NoneType' object is not iterable

I also recently posted an example that may do something similar to what you
are after, you can have a look here:
http://www.nabble.com/contribute-to-gallery--Or%2C-just-advice-on-changing-colors-automagically....-td24419101.html#a24427781



per freem-2 wrote:
> 
> Hi all,
> 
> i would like to set the colors of the lines i plot (using the plot
> function)
> to go from red to blue, in evenly spaced interval. that is, imagine a
> color
> map from red to green, where i plot n-many lines, each receiving a color
> from this color map, starting at the red end and going to green.
> 
> the docs say how to set the color cycle of lines set by plot, using:
> 
> matplotlib.axes.set_default_color_cycle(['r', 'y', 'g', 'b'])
> 
> but this only allows me to use named colors, and here i am looking to use
> shades from red to green.
> my question is: first, how can i generate N evenly spaced colors from the
> red spectrum to the green spectrum? and two, how can i make it so plot
> uses
> these colors for its line plots?
> 
> thanks very much.
> 
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> 
> 

-- 
View this message in context: http://www.nabble.com/question-about-setting-colors-of-lines-using-colormap-tp24479842p24498248.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

On Tue, Jul 14, 2009 at 12:48 PM, Northenlight<Jia...@gm...> wrote:
>
> Hi,
>
> Is there a way to interactive with the plot? For example, draw a vertical
> marker on the plot, let user move the marker and shows x, y values of the
> point where the curve intersect with the marker?


See these examples and tutorial:

http://matplotlib.sourceforge.net/users/event_handling.html
http://matplotlib.sourceforge.net/examples/event_handling/index.html

In particular, the
http://matplotlib.sourceforge.net/examples/event_handling/path_editor.html
example shows how to click and drag points

JDH

per freem wrote:
> hi all,
>
> i'm getting very strange behavior from the matplotlib 'plot' function 
> when attempting to plot multiple lines. i have a series of x, y data 
> points that are being generated in a loop and i want to simply plot 
> each of them on the same plot. my code is:
>
> import matplotlib
> matplotlib.use('PDF')
> import matplotlib.pyplot as plt
> from matplotlib import rc
> rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
> plt.rcParams['ps.useafm'] = True
> rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
>
> my_fig = plt.figure(figsize=(6,5), dpi=100)
> num_lines = 3
>
> for n in range(0, num_lines):
>     print "Printing line %d" %(n+1)
>     x = range(0, 100)
>     y = (ones(100)*(n+1))
>     plt.plot(x, y)
>
> plt.savefig('plot_example.pdf')
>
> when I do this, it only plots the last line (a horizontal line at y = 
> 3). how can i get to actually plot all three lines?
>
> more strangely, it shows *stochastic* behavior: sometimes when i run 
> the code, it generates a green line at y = 3, and other times a blue 
> line. from plot to plot, the upper bound of the y axis changes, 
> sometimes being 3.15, sometimes 3.2.  i'm not sure why it is doing that.
>
> how can i get it to simply add whatever i plot in the body of the 
> 'for' loop to the same graph? i tried adding plt.plot() after my call 
> to plt.plot but that did not fix it.
>
> thank you.

Per:  The plots are there, you just can't see them because the y-axis 
has been auto-scaled so that the first and last lines lie on the top and 
bottom of the plot window.  Just add plt.ylim(0,4) after the loop and 
you will see all three lines.

-Jeff

hi all,

i'm getting very strange behavior from the matplotlib 'plot' function when
attempting to plot multiple lines. i have a series of x, y data points that
are being generated in a loop and i want to simply plot each of them on the
same plot. my code is:

import matplotlib
matplotlib.use('PDF')
import matplotlib.pyplot as plt
from matplotlib import rc
rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
plt.rcParams['ps.useafm'] = True
rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})

my_fig = plt.figure(figsize=(6,5), dpi=100)
num_lines = 3

for n in range(0, num_lines):
    print "Printing line %d" %(n+1)
    x = range(0, 100)
    y = (ones(100)*(n+1))
    plt.plot(x, y)

plt.savefig('plot_example.pdf')

when I do this, it only plots the last line (a horizontal line at y = 3).
how can i get to actually plot all three lines?

more strangely, it shows *stochastic* behavior: sometimes when i run the
code, it generates a green line at y = 3, and other times a blue line. from
plot to plot, the upper bound of the y axis changes, sometimes being 3.15,
sometimes 3.2.  i'm not sure why it is doing that.

how can i get it to simply add whatever i plot in the body of the 'for' loop
to the same graph? i tried adding plt.plot() after my call to plt.plot but
that did not fix it.

thank you.

Hi Jon,

To clarify, I think you need to read Christoph Gohlke original message 
(7/7/2009) to me to put my response into context:
> Hi Steve,
>
> matplotlib-0.98.5.3.win32-py2.6.exe was compiled without support for GTK.
>
> If you don't mind trying, I have a build of the matplotlib trunk 
> available on my homepage that has GTK support enabled:
>
> http://www.lfd.uci.edu/~gohlke/#pythonlibs
>
> It should work with the PyGTK 2.12 Windows binaries from 
> http://www.pygtk.org/downloads.html.
>
> SVG support seems broken: the window.set_icon_from_file() function in 
> backend_gtk.py will raise an exception, not recognizing SVG files. The 
> PNG icon works.
>
> Christoph
>   

 From that web page I downloaded 
http://www.lfd.uci.edu/~gohlke/download/matplotlib-0.98.6svn.win32-py2.6.exe
NOTICE the version number 0.98.6svn

Then in my code I have the following lines:

from matplotlib.backends.backend_gtk import FigureCanvasGTK as FigureCanvas
from matplotlib.backends.backend_gtk import NavigationToolbar2GTK as 
NavigationToolbar

For your benefit I changed to the same backend as yours ( GTKAgg backend 
) and run again

My application ran successfully with both the GTKAgg and GTKCario backends.
Why don't you take the svn version for a spin, you might also have success.

Hope this has been of some help
Steve


Jon Roadley-Battin wrote:
> Question is however, are you using the GTK backend?
> ie
>
> from matplotlib.backends.backend_gtkagg import FigureCanvasGTKAgg as 
> FigureCanvas
> from matplotlib.backends.backend_gtkagg import 
> NavigationToolbar2GTKAgg as NavigationToolbar
>
> backend_gtkagg then imports matplotlib.backends._gtkagg
> For matplotlib-0.98.5.2.win32-py2.5.exe
> C:\Python25\Lib\site-packages\matplotlib\backends\_gtkagg.pyd  exists
>
> For matplotlib-0.98.5.3.win32-py2.6.exe
> C:\Python26\Lib\site-packages\matplotlib\backends\_gtkagg.pyd doesn't
>
> ie gtk backend doesn't seem to be compiled.
> matplotlib is the only thing holding me back in moving to python26 (on 
> windows). Hopefully the svn build is updated soon or a new release is 
> due soon (I can wait )
>  
>
>     >Hi Christoph,
>     >
>     >Sorry for my delay to get back to you.
>     >
>     >The svn version seems to work fine with GTK support, at least my
>     >application had no problems running
>     >
>     >The versions I tested with are as follows:
>     >  python version: 2.6.0 final 0
>     >   numpy version: 1.3.0
>
>     >  matplotlib version: 0.98.6svn
>     >   gtk+ version: 2.16.2
>     >   pyGTK version: 2.12.1
>     >
>     >Thank you
>     >you have been a big help
>
>     >Steve
>
>
> ------------------------------------------------------------------------
>
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>
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>   

Hello,
I'm writing a script that removes data from plots by looping over
axes.get_lines(), removing data, then using axes.set_lines(). It works quite
well, but when it's a plot with error bars, the vertical part of the error
bar is not disappearing.

I'm assuming the vertical part is a vline or something and so should not be
with the other lines. Where does this data get stuck? :)

Thanks!
Jack

On Jul 14, 2009, at 3:12 PM, per freem wrote:

> Hi Tony,
>
> thanks for the pointer.  that code does not run for me, it generates  
> the following error:
>
> ttributeError                            Traceback (most recent call  
> last)
>
....
>
> /Library/Python/2.5/site-packages/matplotlib/rcsetup.pyc in  
> validate_color(s)
>     160 def validate_color(s):
>     161     'return a valid color arg'
> --> 162     if s.lower() == 'none':
>     163         return 'None'
>     164     if is_color_like(s):
>
> AttributeError: 'list' object has no attribute 'lower'
> WARNING: Failure executing file: <color_cycle.py>
>
> any idea what might be wrong?

Hmm, it looks like there was a fix added a couple of months ago (svn  
revision 7164). If you're on trunk, then updating it should fix this  
problem. If you're not on trunk: I don't think any official releases  
have occurred since this fix, so I don't think updating to the last  
official release will help.

In any case, I think this error only affects the ``cycle_cmap``  
function in the code (calls to ``cmap_intervals`` should work fine).  
If you comment out the 4 lines of code after the comment "Change the  
default color cycle", I believe everything should work fine.

-Tony

Hi Tony,

thanks for the pointer.  that code does not run for me, it generates the
following error:

ttributeError                            Traceback (most recent call last)

color_cycle.py in <module>()
     63 if __name__ == '__main__':
     64     n_lines = 10
---> 65     cycle_cmap(length=n_lines)
     66     x = np.linspace(0, 10)
     67     for shift in np.linspace(0, np.pi, n_lines):

color_cycle.py in cycle_cmap(cmap, length)
     59     idx = np.linspace(crange['start'], crange['stop'],
length).astype(np.int)
     60     colors = cm(idx)
---> 61     mpl.axes.set_default_color_cycle(colors.tolist())
     62
     63 if __name__ == '__main__':

/Library/Python/2.5/site-packages/matplotlib/axes.pyc in
set_default_color_cycle(clist)
    113     """
    114     _process_plot_var_args.defaultColors = clist[:]
--> 115     rcParams['lines.color'] = clist[0]
    116
    117 class _process_plot_var_args:

/Library/Python/2.5/site-packages/matplotlib/__init__.pyc in
__setitem__(self, key, val)
    603 instead.'% (key, alt))
    604                 key = alt
--> 605             cval = self.validate[key](val)
    606             dict.__setitem__(self, key, cval)
    607         except KeyError:

/Library/Python/2.5/site-packages/matplotlib/rcsetup.pyc in
validate_color(s)
    160 def validate_color(s):
    161     'return a valid color arg'
--> 162     if s.lower() == 'none':
    163         return 'None'
    164     if is_color_like(s):

AttributeError: 'list' object has no attribute 'lower'
WARNING: Failure executing file: <color_cycle.py>

any idea what might be wrong?


On Tue, Jul 14, 2009 at 10:14 AM, Tony S Yu <to...@mi...> wrote:

> Not too long ago, I posted an example of this to the list<http://www.nabble.com/Where-to-post-examples-%2528specifically%252C-one-that-may-be-useful-for-time-evolution-plots%2529-td23901837.html>.
> The code near the bottom of that thread is a little more general than the
> one at the top and shows, three different ways to cycle through the colors
> of a colormap.
>
> Hope that helps,
> -Tony
>
>
> On Jul 14, 2009, at 9:51 AM, per freem wrote:
>
> Hi all,
>
> i would like to set the colors of the lines i plot (using the plot
> function) to go from red to blue, in evenly spaced interval. that is,
> imagine a color map from red to green, where i plot n-many lines, each
> receiving a color from this color map, starting at the red end and going to
> green.
>
> the docs say how to set the color cycle of lines set by plot, using:
>
> matplotlib.axes.set_default_color_cycle(['r', 'y', 'g', 'b'])
>
> but this only allows me to use named colors, and here i am looking to use
> shades from red to green.
> my question is: first, how can i generate N evenly spaced colors from the
> red spectrum to the green spectrum? and two, how can i make it so plot uses
> these colors for its line plots?
>
> thanks very much.
>
> ------------------------------------------------------------------------------
> Enter the BlackBerry Developer Challenge
> This is your chance to win up to $100,000 in prizes! For a limited time,
> vendors submitting new applications to BlackBerry App World(TM) will have
> the opportunity to enter the BlackBerry Developer Challenge. See full prize
>
> details at:
> http://p.sf.net/sfu/Challenge_______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
>

On 2009-07-14 12:52, Robert Cimrman wrote:
> Robert Kern wrote:
>> On 2009-07-13 13:20, Robert Cimrman wrote:
>>> Hi all,
>>>
>>> I would like to use griddata() to interpolate a function given at
>>> specified points of a bunch of other points. While the method works
>>> well, it slows down considerably as the number of points to interpolate
>>> to increases.
>>>
>>> The dependence of time/(number of points) is nonlinear (see the
>>> attachment) - it seems that while the Delaunay trinagulation itself is
>>> fast, I wonder how to speed-up the interpolation. The docstring says,
>>> that it is based on "natural neighbor interpolation" - how are the
>>> neighbors searched?
>> Using the Delaunay triangulation. The "natural neighbors" of an interpolation
>> point are those points participating in triangles in the Delaunay triangulation
>> whose circumcircles include the interpolation point. The triangle that encloses
>> the interpolation point is found by a standard walking procedure, then the
>> neighboring triangles (natural or otherwise) are explored in a breadth-first
>> search around the starting triangle to find the natural neighbors.
>
> I see, thanks for the explanation. The walking procedure is what is
> described e.g. in [1], right? (summary; starting from a random triangle,
> a line is made connecting that triangle with the interpolation point,
> and triangles along that line are probed.)
>
> [1] http://www.geom.uiuc.edu/software/cglist/GeomDir/ptloc96.ps.gz

Yes.

>>> Does it use the kd-trees like scipy.spatial? I have
>>> a very good experience with scipy.spatial performance.
>>>
>>> Also, is there a way of reusing the triangulation when interpolating
>>> several times using the same grid?
>> One would construct a Triangulation() object with the (x,y) data points, get a
>> new NNInterpolator() object using the .nn_interpolator(z) method for each new z
>> data set, and then interpolate your grid on the NNInterpolator.
>
> So if the above fails, I can bypass griddata() by using the delaunay
> module directly, good.

Yes. griddata is a fairly light wrapper that exists mainly to sanitize inputs 
and allow use of the natgrid implementation easily.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco

Hi all,

I'm a newbie, I'm trying to plot a line with an arrow
(arrow in the  middle and another with an arrow at
the end) with the following points: [1, 2] and [5, 2]
Could anyone please help me with the code?
Thanks.
Harriet A. Welbeck



      

Robert Kern wrote:
> On 2009-07-13 13:20, Robert Cimrman wrote:
>> Hi all,
>>
>> I would like to use griddata() to interpolate a function given at
>> specified points of a bunch of other points. While the method works
>> well, it slows down considerably as the number of points to interpolate
>> to increases.
>>
>> The dependence of time/(number of points) is nonlinear (see the
>> attachment) - it seems that while the Delaunay trinagulation itself is
>> fast, I wonder how to speed-up the interpolation. The docstring says,
>> that it is based on "natural neighbor interpolation" - how are the
>> neighbors searched?
> 
> Using the Delaunay triangulation. The "natural neighbors" of an interpolation 
> point are those points participating in triangles in the Delaunay triangulation 
> whose circumcircles include the interpolation point. The triangle that encloses 
> the interpolation point is found by a standard walking procedure, then the 
> neighboring triangles (natural or otherwise) are explored in a breadth-first 
> search around the starting triangle to find the natural neighbors.

I see, thanks for the explanation. The walking procedure is what is 
described e.g. in [1], right? (summary; starting from a random triangle, 
a line is made connecting that triangle with the interpolation point, 
and triangles along that line are probed.)

[1] http://www.geom.uiuc.edu/software/cglist/GeomDir/ptloc96.ps.gz

> Unfortunately, griddata() uses the unstructured-interpolation-points API rather 
> than the more efficient grid-interpolation-points API. In the former, each 
> interpolation point uses the last-found enclosing triangle as the start of the 
> walking search. This works well where adjacent interpolation points are close to 
> each other. This is not the case at the ends of the grid rows. The latter API is 
> smarter and starts a new row of the grid with the triangle from the triangle 
> from the *start* of the previous row rather than the end. I suspect this is 
> largely the cause of the poor performance.

Good to know, I will try to pass the points in groups of close points.

>> Does it use the kd-trees like scipy.spatial? I have
>> a very good experience with scipy.spatial performance.
>>
>> Also, is there a way of reusing the triangulation when interpolating
>> several times using the same grid?
> 
> One would construct a Triangulation() object with the (x,y) data points, get a 
> new NNInterpolator() object using the .nn_interpolator(z) method for each new z 
> data set, and then interpolate your grid on the NNInterpolator.

So if the above fails, I can bypass griddata() by using the delaunay 
module directly, good.

thank you,
r.

Hi,

Is there a way to interactive with the plot? For example, draw a vertical
marker on the plot, let user move the marker and shows x, y values of the
point where the curve intersect with the marker?

Thanks,

J

 
-- 
View this message in context: http://www.nabble.com/Interactive-with-the-plot%2C-moving-marker%2C-etc-tp24484499p24484499.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

On 2009-07-13 13:20, Robert Cimrman wrote:
> Hi all,
>
> I would like to use griddata() to interpolate a function given at
> specified points of a bunch of other points. While the method works
> well, it slows down considerably as the number of points to interpolate
> to increases.
>
> The dependence of time/(number of points) is nonlinear (see the
> attachment) - it seems that while the Delaunay trinagulation itself is
> fast, I wonder how to speed-up the interpolation. The docstring says,
> that it is based on "natural neighbor interpolation" - how are the
> neighbors searched?

Using the Delaunay triangulation. The "natural neighbors" of an interpolation 
point are those points participating in triangles in the Delaunay triangulation 
whose circumcircles include the interpolation point. The triangle that encloses 
the interpolation point is found by a standard walking procedure, then the 
neighboring triangles (natural or otherwise) are explored in a breadth-first 
search around the starting triangle to find the natural neighbors.

Unfortunately, griddata() uses the unstructured-interpolation-points API rather 
than the more efficient grid-interpolation-points API. In the former, each 
interpolation point uses the last-found enclosing triangle as the start of the 
walking search. This works well where adjacent interpolation points are close to 
each other. This is not the case at the ends of the grid rows. The latter API is 
smarter and starts a new row of the grid with the triangle from the triangle 
from the *start* of the previous row rather than the end. I suspect this is 
largely the cause of the poor performance.

> Does it use the kd-trees like scipy.spatial? I have
> a very good experience with scipy.spatial performance.
>
> Also, is there a way of reusing the triangulation when interpolating
> several times using the same grid?

One would construct a Triangulation() object with the (x,y) data points, get a 
new NNInterpolator() object using the .nn_interpolator(z) method for each new z 
data set, and then interpolate your grid on the NNInterpolator.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco

Question is however, are you using the GTK backend?
ie

from matplotlib.backends.backend_gtkagg import FigureCanvasGTKAgg as
FigureCanvas
from matplotlib.backends.backend_gtkagg import NavigationToolbar2GTKAgg as
NavigationToolbar

backend_gtkagg then imports matplotlib.backends._gtkagg
For matplotlib-0.98.5.2.win32-py2.5.exe
C:\Python25\Lib\site-packages\matplotlib\backends\_gtkagg.pyd  exists

For matplotlib-0.98.5.3.win32-py2.6.exe
C:\Python26\Lib\site-packages\matplotlib\backends\_gtkagg.pyd doesn't

ie gtk backend doesn't seem to be compiled.
matplotlib is the only thing holding me back in moving to python26 (on
windows). Hopefully the svn build is updated soon or a new release is due
soon (I can wait )


>Hi Christoph,
> >
> >Sorry for my delay to get back to you.
> >
> >The svn version seems to work fine with GTK support, at least my
> >application had no problems running
> >
> >The versions I tested with are as follows:
> >  python version: 2.6.0 final 0
> >   numpy version: 1.3.0

>  matplotlib version: 0.98.6svn
> >   gtk+ version: 2.16.2
> >   pyGTK version: 2.12.1
> >
> >Thank you
> >you have been a big help
>
> >Steve
>
>

Please post a standalone example that reproduces your problem.
I tried your example with some junk data but no such exception is raised.

However, there has been a report of a similar ordinal value problem
which I think is not fixed yet, but that problem only occurs when two
and more axes are shared.

See if below helps,
 * move the axhline call after the plotting commands.
 * autoscale only after all the necessary plot elements are in place.

Again, please post a standalone example that reproduces your problem.

Regards,

-JJ


On Tue, Jul 14, 2009 at 9:50 AM, M Osborne<os...@gm...> wrote:
> I am trying to plot some historical trend data, where x is a date and
> y is a percentage.
>
> When I try to insert a horizontal line with ax1.axhline(y=80,
> linewidth=1, color='r'), matplotlib breaks, with an error "
> ValueError: ordinal must be >= 1".
>
> The Traceback most recent call is,  File
> "/usr/lib64/python2.4/site-packages/matplotlib/dates.py", line 170, in
> _from_ordinalf
>    dt = datetime.datetime.fromordinal(ix)"
>
> Without the axhline element, matplotlib handles the data fine, and
> plots nice weekly dates.
>
> I'm guessing based on the error that axhline is manually forcing
> autoscale off and/or matplotlib can no longer interpret the date
> values for x?
>
> Below is the matplotlib snippet of my code:
>
>        fig = plt.figure(figsize=(20,10))
>        font = { 'fontname':'Tahoma', 'fontsize':12 }
>        ax1 = fig.add_subplot(211)
>        ax1.set_ylim(0,100)
>        ax1.autoscale_view(tight=False, scalex=True, scaley=False)
>        ax1.grid(True)
>        ax1.axhline(y=80, linewidth=1, color='r')
>        ax1.set_ylim(0,100)
>        ax1.autoscale_view(tight=False, scalex=True, scaley=False)
>        ax1.plot(timestamp, percentu, 'ko-' )
>        ax1.plot(timestamp, percentl, 'b--', linewidth=2)
>        ax2 = fig.add_subplot(212)
>        ax2.grid(True)
>        ax2.plot(predict_x, predict_y, 'bs--', linewidth=2)
>        plt.savefig("plot.pdf")
>
>
> Thank you in advance!
>
> ------------------------------------------------------------------------------
> Enter the BlackBerry Developer Challenge
> This is your chance to win up to $100,000 in prizes! For a limited time,
> vendors submitting new applications to BlackBerry App World(TM) will have
> the opportunity to enter the BlackBerry Developer Challenge. See full prize
> details at: http://p.sf.net/sfu/Challenge
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Not too long ago, I posted an example of this to the list. The code  
near the bottom of that thread is a little more general than the one  
at the top and shows, three different ways to cycle through the colors  
of a colormap.

Hope that helps,
-Tony


On Jul 14, 2009, at 9:51 AM, per freem wrote:

> Hi all,
>
> i would like to set the colors of the lines i plot (using the plot  
> function) to go from red to blue, in evenly spaced interval. that  
> is, imagine a color map from red to green, where i plot n-many  
> lines, each receiving a color from this color map, starting at the  
> red end and going to green.
>
> the docs say how to set the color cycle of lines set by plot, using:
>
> matplotlib.axes.set_default_color_cycle(['r', 'y', 'g', 'b'])
>
> but this only allows me to use named colors, and here i am looking  
> to use shades from red to green.
> my question is: first, how can i generate N evenly spaced colors  
> from the red spectrum to the green spectrum? and two, how can i make  
> it so plot uses these colors for its line plots?
>
> thanks very much.
> ------------------------------------------------------------------------------
> Enter the BlackBerry Developer Challenge
> This is your chance to win up to $100,000 in prizes! For a limited  
> time,
> vendors submitting new applications to BlackBerry App World(TM) will  
> have
> the opportunity to enter the BlackBerry Developer Challenge. See  
> full prize
> details at: http://p.sf.net/sfu/Challenge_______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Hi all,

i would like to set the colors of the lines i plot (using the plot function)
to go from red to blue, in evenly spaced interval. that is, imagine a color
map from red to green, where i plot n-many lines, each receiving a color
from this color map, starting at the red end and going to green.

the docs say how to set the color cycle of lines set by plot, using:

matplotlib.axes.set_default_color_cycle(['r', 'y', 'g', 'b'])

but this only allows me to use named colors, and here i am looking to use
shades from red to green.
my question is: first, how can i generate N evenly spaced colors from the
red spectrum to the green spectrum? and two, how can i make it so plot uses
these colors for its line plots?

thanks very much.

I am trying to plot some historical trend data, where x is a date and
y is a percentage.

When I try to insert a horizontal line with ax1.axhline(y=80,
linewidth=1, color='r'), matplotlib breaks, with an error "
ValueError: ordinal must be >= 1".

The Traceback most recent call is,  File
"/usr/lib64/python2.4/site-packages/matplotlib/dates.py", line 170, in
_from_ordinalf
    dt = datetime.datetime.fromordinal(ix)"

Without the axhline element, matplotlib handles the data fine, and
plots nice weekly dates.

I'm guessing based on the error that axhline is manually forcing
autoscale off and/or matplotlib can no longer interpret the date
values for x?

Below is the matplotlib snippet of my code:

        fig = plt.figure(figsize=(20,10))
        font = { 'fontname':'Tahoma', 'fontsize':12 }
        ax1 = fig.add_subplot(211)
        ax1.set_ylim(0,100)
        ax1.autoscale_view(tight=False, scalex=True, scaley=False)
        ax1.grid(True)
        ax1.axhline(y=80, linewidth=1, color='r')
        ax1.set_ylim(0,100)
        ax1.autoscale_view(tight=False, scalex=True, scaley=False)
        ax1.plot(timestamp, percentu, 'ko-' )
        ax1.plot(timestamp, percentl, 'b--', linewidth=2)
        ax2 = fig.add_subplot(212)
        ax2.grid(True)
        ax2.plot(predict_x, predict_y, 'bs--', linewidth=2)
        plt.savefig("plot.pdf")


Thank you in advance!

Hi Christoph,

Sorry for my delay to get back to you.

The svn version seems to work fine with GTK support, at least my 
application had no problems running

The versions I tested with are as follows:
    python version: 2.6.0 final 0
    numpy version: 1.3.0
    matplotlib version: 0.98.6svn
    gtk+ version: 2.16.2
    pyGTK version: 2.12.1

Thank you
you have been a big help

Steve

Christoph Gohlke wrote:
> Hi Steve,
>
> matplotlib-0.98.5.3.win32-py2.6.exe was compiled without support for GTK.
>
> If you don't mind trying, I have a build of the matplotlib trunk 
> available on my homepage that has GTK support enabled:
>
> http://www.lfd.uci.edu/~gohlke/#pythonlibs
>
> It should work with the PyGTK 2.12 Windows binaries from 
> http://www.pygtk.org/downloads.html.
>
> SVG support seems broken: the window.set_icon_from_file() function in 
> backend_gtk.py will raise an exception, not recognizing SVG files. The 
> PNG icon works.
>
> Christoph
>
> ------------------------------------------------------------------------------
> Enter the BlackBerry Developer Challenge  
> This is your chance to win up to $100,000 in prizes! For a limited time, 
> vendors submitting new applications to BlackBerry App World(TM) will have 
> the opportunity to enter the BlackBerry Developer Challenge. See full prize 
> details at: http://p.sf.net/sfu/blackberry
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>   

import numpy as np
import matplotlib.pylab as plt

ROIS=["1.0","0.9","0.8","0.7","0.6","0.5","0.4","0.3","0.2","0.1"]
EMINS=["100","125","150","175","200","250","300","500","700","1000"]

d=np.array([81.820974990633303,
82.905629922471107,
79.590599078715002,
83.8076661158848,
84.340371447361704,
86.470741120340406,
86.325669295272604,
78.547789147572104,
61.234561761417801,
42.336057180561099,
79.452456461883799,
78.886459859281402,
76.101705425124905,
81.152956140890893,
79.325736080403303,
81.869315277384999,
82.334627586818499,
80.751043622934901,
63.687981070736697,
42.336057180561099,
81.561434110553193,
81.733934887474803,
77.281383826158105,
81.735026440126006,
78.759069413428506,
83.011430606978095,
83.1028280527253,
84.831802384752606,
70.310404261509206,
42.336057180561099,
79.049391539046098,
80.359440097576794,
77.772159524822001,
83.654958151325204,
79.578518689189593,
83.313224279315094,
85.904971250263898,
88.016057678182506,
72.556205760527106,
43.079858727017502,
74.014083853922003,
74.991828576951406,
72.176483952900597,
79.931150578720604,
76.810283824455198,
81.319067727368093,
82.606434816726093,
79.296669680086296,
67.530619223090795,
43.830850940183701,
78.570285512017804,
80.011420916551302,
78.048745087146898,
85.986292098240298,
83.757389242109198,
85.399220867247493,
84.378739151586601,
83.838909509599304,
72.219496155423101,
54.667696386193299,
64.771390756530494,
65.179725530642799,
65.901293578971206,
70.324974696479799,
68.229487152871201,
69.183487824467093,
72.191878118072495,
75.809844472900906,
64.968437827963001,
54.162402578714399,
57.958372971901703,
57.342923745772502,
58.459763976540003,
61.621347971812597,
56.633079601774597,
56.443549659648298,
55.463724005796699,
57.973081450418903,
48.107631297574798,
40.4952182396881,
46.761865533859897,
47.869196203907997,
47.310621469889,
47.7642158774199,
45.1306027800862,
49.647667752226802,
47.310281669050198,
48.629496015722999,
40.947773761156398,
33.032212415148798,
27.819471401269102,
28.166844457481599,
26.861003210437801,
27.875138576975701,
26.295879497460898,
31.165730874019399,
29.333496744941801,
35.518932552857997,
34.476676188903603,
30.448752651955001])

d.resize(len(EMINS),len(ROIS))
plt.pcolor(d)

.... and now I would like to have EMINS and ROIS values labelling each 
"pixel" or each square of the checkerboard if you prefer.....

thanks a lot for your help.
Johann