matplotlib-users Mailing List for matplotlib (Page 104)

On Sep 19, 2013, at 10:14AM, Skip Montanaro wrote:
> 
>> Separately, if your blue data are so quantized, you might use the blue data to choose a color for an axvspan (or axhspan, I  forget which is which) to indicate how certain regions of time have different values of blue data.  Then you would only need one set of axes, and your x,y labels would indicate what you want.
> 
> This also works, though I (and anyone looking at the graph) would have
> to remember the mapping between color and numeric value. If I was a
> synethete this might work, but I doubt most people would automatically
> recall the mapping. :-)

No assumption of super-human recollection or inference abilities . I would add a figure or axes legend with proxy artists for the appropriate color mappings, or even just a bunch of text boxes with the text label colored appropriately.  You may be interested in my answer to a stackoverflow question [1].

-Sterling

[1] http://stackoverflow.com/questions/17086847/box-around-text-in-matplotlib/17092777#17092777

> I assume that you are using a twinx call to get the second y axis.  I think that this question has come up before, and I think the solution was to switch which data are put on the second set of axes.  (Of course to keep the same visual layout you would have to play with the y axis spine locations.)

Good point.  I just changed the command line options so the plot whose
Y values are of interest are plotted on the right Y axis.

> Separately, if your blue data are so quantized, you might use the blue data to choose a color for an axvspan (or axhspan, I  forget which is which) to indicate how certain regions of time have different values of blue data.  Then you would only need one set of axes, and your x,y labels would indicate what you want.

This also works, though I (and anyone looking at the graph) would have
to remember the mapping between color and numeric value. If I was a
synethete this might work, but I doubt most people would automatically
recall the mapping. :-)

Thx,

Skip

Skip,

I assume that you are using a twinx call to get the second y axis.  I think that this question has come up before, and I think the solution was to switch which data are put on the second set of axes.  (Of course to keep the same visual layout you would have to play with the y axis spine locations.)  

Separately, if your blue data are so quantized, you might use the blue data to choose a color for an axvspan (or axhspan, I  forget which is which) to indicate how certain regions of time have different values of blue data.  Then you would only need one set of axes, and your x,y labels would indicate what you want.

-Sterling

On Sep 19, 2013, at 7:46AM, Skip Montanaro wrote:

> I have a plot which uses both the left and right y axes.  See
> attached. Note that the feedback in the lower right-hand corner
> displays the value on the right y axis (the blue plot). That's not a
> very interesting value though. How can I control which value is
> displayed as I move the cursor around the graph? Is it something
> control interactively with a modifier key?  I tried a few, but saw no
> change. I'm currently using matplotlib v 1.1.0 (alas, something which
> is also out of my control).
> 
> Thanks,
> 
> Skip
> <axes.png>------------------------------------------------------------------------------
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I have a plot which uses both the left and right y axes.  See
attached. Note that the feedback in the lower right-hand corner
displays the value on the right y axis (the blue plot). That's not a
very interesting value though. How can I control which value is
displayed as I move the cursor around the graph? Is it something
control interactively with a modifier key?  I tried a few, but saw no
change. I'm currently using matplotlib v 1.1.0 (alas, something which
is also out of my control).

Thanks,

Skip

Hi all,

I am trying to plot the time evolution of a probability distribution, but I
don't know how to use it. I have a different histogram for each time step.
I tried plt.ion()  but I'm not sure how to use it. I'm sure it must be a
simple solution, but I haven't really found out how to do it! If I use
plt.show() as written below, I have to close the window every time for it
to reopen. Here is my code, can you help me?

import matplotlib.pyplot as plt
import numpy
import math

def p(N, Na, fa,  fb):
    return float(Na)*fa/(Na*fa + (N-Na)*fb)

def binomial(n,k):
   if k > n-k:
       k = n-k
   accum = 1
   for i in range(1,k+1):
      accum *= (n - (k - i))
      accum /= i
   return accum

def pk(N, k, p):
    return binomial(N, k)*math.pow(p,k)*math.pow((1-p),(N-k))

def expected(N, dist):
    soma = 0
    for k in range(N + 1):
        soma += k*dist[k]
    return soma

def drawhist(menMeans):

    N = len(menMeans)

    ind = numpy.arange(N)

    width = 1.0

    plt.clf()

    plt.ylabel('Probability')
    plt.xlabel('k')
    plt.xlim(0.0,N)
    plt.ylim(0.0,1.0)
    plt.bar(ind, menMeans, width)
    plt.draw()
    plt.show()



N = 100
Na = 50
fa = 10
fb = 5



pks = [0]*(N+1)
pks[Na] = 1
pkst = [0]*(N+1)
expect = [Na]

drawhist(pks)
p = [p(N, n, fa, fb) for n in range(N + 1)]

for t in range(5):
    for Na in range(N + 1):
        for k in range(N + 1):
            pkst[k] += pks[Na]*pk(N, k, p[Na])
    drawhist(pkst)
    pks = pkst
    pkst = [0]*(N+1)
    expect.append(expected(N, pks))

On Tue, Sep 17, 2013 at 11:55 AM, Chad Kidder <cck...@gm...> wrote:

> I'm following the MPL Qt4 example given at
> http://matplotlib.org/examples/user_interfaces/embedding_in_qt4.html and
> it looks like I am timing out somewhere in the setup.  The error I am
> getting is:
>
> RuntimeError: super-class __init__() of type MyDynamicMplCanvas was never
> called
>
> It's timing out on a function that goes and talks to a piece of test
> equipment to get some data to plot.  That function takes on the order of a
> second to complete and is located in compute_initial_figure(self): for the
> previously mentioned class.  I will need to make these calls whenever I go
> into the update routine and they may take a few seconds to update.
>
> First, where is the "timeout" that I am violating?  Second, how do I fix
> this?  Thanks for your help.
>
>
>     --Chad Kidder
>
>
Hi Chad,

I think the timeout is right over here:

class MyDynamicMplCanvas(MyMplCanvas):
    """A canvas that updates itself every second with a new plot."""
    def __init__(self, *args, **kwargs):
        MyMplCanvas.__init__(self, *args, **kwargs)
        timer = QtCore.QTimer(self)
        QtCore.QObject.connect(timer, QtCore.SIGNAL("timeout()"),
self.update_figure)
        timer.start(1000)

My suspicion would be to either bump up that timer to take more than a
second, or come up with a different signal function to more intelligently
handle refreshes.

Cheers!
Ben Root

I'm following the MPL Qt4 example given at
http://matplotlib.org/examples/user_interfaces/embedding_in_qt4.html and it
looks like I am timing out somewhere in the setup.  The error I am getting
is:

RuntimeError: super-class __init__() of type MyDynamicMplCanvas was never
called

It's timing out on a function that goes and talks to a piece of test
equipment to get some data to plot.  That function takes on the order of a
second to complete and is located in compute_initial_figure(self): for the
previously mentioned class.  I will need to make these calls whenever I go
into the update routine and they may take a few seconds to update.

First, where is the "timeout" that I am violating?  Second, how do I fix
this?  Thanks for your help.


    --Chad Kidder

Hi Ben,

It works for me. Thank you very much !

Best wishes
                        Nils



On Tue, Sep 17, 2013 at 3:25 PM, Benjamin Root <ben...@ou...> wrote:

>
>
>
> On Tue, Sep 17, 2013 at 4:25 AM, Nils Wagner <ni...@go...>wrote:
>
>> Hi all,
>>
>> How can I modify the grid linewidth and grid line color of an Axes3D
>> object ?
>> is it possible to use white instead of gray for the background color ?
>>
>> The following snippet doesn't show the desired effect.
>>
>> from mpl_toolkits.mplot3d import Axes3D
>> import matplotlib.pyplot as plt
>> fig = plt.figure(figsize=(10,8))
>> ax = fig.gca(projection='3d')
>> ax.grid(color='r',linestyle='-',linewdith=2)
>>
>>
> A (somewhat) undocumented feature (and is not guaranteed to work in the
> future!) is the axis's _axinfo dictionary.
>
>         # This is a temporary member variable.
>         # Do not depend on this existing in future releases!
>         self._axinfo = self._AXINFO[adir].copy()
>         self._axinfo.update({'label' : {'space_factor': 1.6,
>                                         'va': 'center',
>                                         'ha': 'center'},
>                              'tick' : {'inward_factor': 0.2,
>                                        'outward_factor': 0.1},
>                              'ticklabel': {'space_factor': 0.7},
>                              'axisline': {'linewidth': 0.75,
>                                           'color': (0, 0, 0, 1)},
>                              'grid' : {'color': (0.9, 0.9, 0.9, 1),
>                                        'linewidth': 1.0},
>                             })
>
> where _AXINFO is a class-level attribute defined as:
>     # Some properties for the axes
>     _AXINFO = {
>         'x': {'i': 0, 'tickdir': 1, 'juggled': (1, 0, 2),
>             'color': (0.95, 0.95, 0.95, 0.5)},
>         'y': {'i': 1, 'tickdir': 0, 'juggled': (0, 1, 2),
>             'color': (0.90, 0.90, 0.90, 0.5)},
>         'z': {'i': 2, 'tickdir': 0, 'juggled': (0, 2, 1),
>             'color': (0.925, 0.925, 0.925, 0.5)},
>     }
>
> This information used to be hard-coded throughout the axis3d.py module. I
> consolidated it all into this dictionary for each Axis3D instance. So, you
> should be able to create your Axes3D object, and then do something like the
> following:
>
> ax = fig.gca(projection='3d')
> ax.xaxis._axinfo['grid'].update({'color': 'r', 'linewidth': 2})
> ax.xaxis._axinfo['color'] = 'white'
>
> (Note: untested code!) I don't think the linestyle can be specified,
> though. At some point, I probably should get the Axes3D.grid() function
> defined to mess around with this _axinfo modify the _axinfo dictionary.
>
> I hope that helps!
> Ben Root
>

On Tue, Sep 17, 2013 at 4:25 AM, Nils Wagner <ni...@go...> wrote:

> Hi all,
>
> How can I modify the grid linewidth and grid line color of an Axes3D
> object ?
> is it possible to use white instead of gray for the background color ?
>
> The following snippet doesn't show the desired effect.
>
> from mpl_toolkits.mplot3d import Axes3D
> import matplotlib.pyplot as plt
> fig = plt.figure(figsize=(10,8))
> ax = fig.gca(projection='3d')
> ax.grid(color='r',linestyle='-',linewdith=2)
>
>
A (somewhat) undocumented feature (and is not guaranteed to work in the
future!) is the axis's _axinfo dictionary.

        # This is a temporary member variable.
        # Do not depend on this existing in future releases!
        self._axinfo = self._AXINFO[adir].copy()
        self._axinfo.update({'label' : {'space_factor': 1.6,
                                        'va': 'center',
                                        'ha': 'center'},
                             'tick' : {'inward_factor': 0.2,
                                       'outward_factor': 0.1},
                             'ticklabel': {'space_factor': 0.7},
                             'axisline': {'linewidth': 0.75,
                                          'color': (0, 0, 0, 1)},
                             'grid' : {'color': (0.9, 0.9, 0.9, 1),
                                       'linewidth': 1.0},
                            })

where _AXINFO is a class-level attribute defined as:
    # Some properties for the axes
    _AXINFO = {
        'x': {'i': 0, 'tickdir': 1, 'juggled': (1, 0, 2),
            'color': (0.95, 0.95, 0.95, 0.5)},
        'y': {'i': 1, 'tickdir': 0, 'juggled': (0, 1, 2),
            'color': (0.90, 0.90, 0.90, 0.5)},
        'z': {'i': 2, 'tickdir': 0, 'juggled': (0, 2, 1),
            'color': (0.925, 0.925, 0.925, 0.5)},
    }

This information used to be hard-coded throughout the axis3d.py module. I
consolidated it all into this dictionary for each Axis3D instance. So, you
should be able to create your Axes3D object, and then do something like the
following:

ax = fig.gca(projection='3d')
ax.xaxis._axinfo['grid'].update({'color': 'r', 'linewidth': 2})
ax.xaxis._axinfo['color'] = 'white'

(Note: untested code!) I don't think the linestyle can be specified,
though. At some point, I probably should get the Axes3D.grid() function
defined to mess around with this _axinfo modify the _axinfo dictionary.

I hope that helps!
Ben Root

Hi all,

How can I modify the grid linewidth and grid line color of an Axes3D object
?
is it possible to use white instead of gray for the background color ?

The following snippet doesn't show the desired effect.

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(10,8))
ax = fig.gca(projection='3d')
ax.grid(color='r',linestyle='-',linewdith=2)


Nils

On Sat, Sep 14, 2013 at 2:45 PM, Alexandre Voitenok <
avo...@ac...> wrote:

>  Hi
> I am trying to figure out how to change font color (as opposed to the fill
> color) in select cells in Table. Is there a way to do this?
> Below is an example:
>
> import matplotlib.pyplot as plt
> import numpy as np
> import pandas as pd
> from matplotlib.table import Table
> def main():
>     data = pd.DataFrame(np.random.random((12,8)),
>                 columns=['A','B','C','D','E','F','G','H'])
>     returnsTable(data)
>     plt.show()
>
> def returnsTable(data, fmt='{:.2f}/{:.1f}'):
>     fig=plt.figure(figsize=(8,5))
>     ax=plt.subplot(111)
>     ax.set_axis_off()
>     tb = Table(ax, bbox=[0,0,1,1])
>     tb.auto_set_font_size(False)
>
> colorDict={-3:"#D00000",-2:"#FF5050",-1:"#FFBFBF",0:"#FFFFFF",1:"#D0FFD0",2:"#40FF40",3:"#00C000"}
>
>     nrows, ncols = data.shape
>     width, height = 1.0 / ncols, 1.0 / nrows
>
>     dArray=data.values.reshape(np.product(data.shape))
>     # mean&sigma..
>     mean=np.average(dArray)
>     sigma=np.std(dArray)
>
>     # Add cells
>     for (i,j), val in np.ndenumerate(data):
>         z=(val-mean)/sigma
>         idx = 0 if int(z)==0 else (max((int(z),-3)) if z<0 else
> min((int(z),3)))
>         color = colorDict[idx]
>
> ##############################################
> ## IS THERE  A WAY TO ALSO CHANGE FONT COLOR?
>         tb.add_cell(i+1, j+1, width, height, text=fmt.format(val,z),
>                     loc='center', facecolor=color)
>
>
>     # Row labels in cells themselves
>     # use -1 with edgecolor='none' for outside the grid
>     for i, label in enumerate(data.index):
>         tb.add_cell(i+1, 0, width*2, height, text=label, loc='right',
> facecolor='none')
>
>
>     # Column Labels...
>     for j, label in enumerate(data.columns):
>         tb.add_cell(0, j+1, width, height/2, text=label, loc='center',
> facecolor='none')
>     tb.set_fontsize(8)
>     ax.add_table(tb)
>     return fig
>
> main()
>
>
>
Hmm, it doesn't look like you can do it from the add_cell() function. It
creates a Cell object, which in turn creates a Text object, but provides no
means of passing much down to that Text object. The Table object has a
dictionary of Cell objects: self._cells[(row, col)] = cell, keyed by the
tuple of row and column numbers. You could do something like this:

tb._cells[(i+1, j+1)]._text.set_color('yellow')

Note, I did not test the above line, but I suspect that should work.

Cheers!
Ben Root

On Sun, Sep 15, 2013 at 11:59 PM, C M <cmp...@gm...> wrote:

> Just a follow-up on this problem...
>
> I've found now that the index is only off if the plot is zoomed, and in
> the following way.  When I zoom, the first point that is visible in the
> plot window will have index = 0, the next point will have index = 1, and so
> forth.  If I zoom another section of the points, the indices are "reset" in
> this same way.
>
> What's really bizarre is that this is only occurring on one plot.  When I
> try to reproduce the problem on other plots (so far at least), I can't.
>
> Any suggestions for how to chase this down would be very welcome.
>
> Thanks.
>
>
That is a very useful observation. I am not very familiar with the artist
picking code, but if I have to guess, I would wonder if indices are being
determined from a path created *after* clip_to_rect() is used internally.
Given that you are having difficulties in reproducing this issue in other
plots, I would suggest trying to pare down your badly behaving code as much
as you can and post it here.  Furthermore, it would also be useful to
determine if the issue still occurs in v1.3 or in the master branch.

Cheers!
Ben Root

Just a follow-up on this problem...

I've found now that the index is only off if the plot is zoomed, and in the
following way.  When I zoom, the first point that is visible in the plot
window will have index = 0, the next point will have index = 1, and so
forth.  If I zoom another section of the points, the indices are "reset" in
this same way.

What's really bizarre is that this is only occurring on one plot.  When I
try to reproduce the problem on other plots (so far at least), I can't.

Any suggestions for how to chase this down would be very welcome.

Thanks.


On Sun, Sep 15, 2013 at 5:30 PM, C M <cmp...@gm...> wrote:

> I have Matplotlib 1.1.0, and am doing point picking (using the OO approach
> to Matplotlib, and embedded in wxPython).  My relevant code is as follows:
>
> #connect the pick event to the pick event handler:
> self.cid = self.canvas.mpl_connect('pick_event', self.on_pick)
>
> #This is the relevant part of the pick event handler:
> def on_pick(self, event):
>     if isinstance(event.artist, Line2D):
>             ind = event.ind
>             print 'ind is: ', str(ind)
>
> This had been working in some cases, but I've found a case in which it
> appears to be giving me a value for ind that doesn't make sense.  For
> example, I have a plot with two lines on it (and two y axes), each with
> over 50 points.  When I pick one of the points right near the end, I expect
> the ind here will be about 50.  However, it prints ind is: 3.  In other
> words, the wrong index value.  This is a serious issue for me, because I
> then use that index to look up information about that point.
>
> What could be going on here?
>
> Thanks,
> Che
>

I have Matplotlib 1.1.0, and am doing point picking (using the OO approach
to Matplotlib, and embedded in wxPython).  My relevant code is as follows:

#connect the pick event to the pick event handler:
self.cid = self.canvas.mpl_connect('pick_event', self.on_pick)

#This is the relevant part of the pick event handler:
def on_pick(self, event):
    if isinstance(event.artist, Line2D):
            ind = event.ind
            print 'ind is: ', str(ind)

This had been working in some cases, but I've found a case in which it
appears to be giving me a value for ind that doesn't make sense.  For
example, I have a plot with two lines on it (and two y axes), each with
over 50 points.  When I pick one of the points right near the end, I expect
the ind here will be about 50.  However, it prints ind is: 3.  In other
words, the wrong index value.  This is a serious issue for me, because I
then use that index to look up information about that point.

What could be going on here?

Thanks,
Che

Hi
I am trying to figure out how to change font color (as opposed to the fill color) in select cells in Table. Is there a way to do this?
Below is an example:

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from matplotlib.table import Table
def main():
    data = pd.DataFrame(np.random.random((12,8)),
                columns=['A','B','C','D','E','F','G','H'])
    returnsTable(data)
    plt.show()

def returnsTable(data, fmt='{:.2f}/{:.1f}'):
    fig=plt.figure(figsize=(8,5))
    ax=plt.subplot(111)
    ax.set_axis_off()
    tb = Table(ax, bbox=[0,0,1,1])
    tb.auto_set_font_size(False)
    colorDict={-3:"#D00000",-2:"#FF5050",-1:"#FFBFBF",0:"#FFFFFF",1:"#D0FFD0",2:"#40FF40",3:"#00C000"}

    nrows, ncols = data.shape
    width, height = 1.0 / ncols, 1.0 / nrows

    dArray=data.values.reshape(np.product(data.shape))
    # mean&sigma..
    mean=np.average(dArray)
    sigma=np.std(dArray)

    # Add cells
    for (i,j), val in np.ndenumerate(data):
        z=(val-mean)/sigma
        idx = 0 if int(z)==0 else (max((int(z),-3)) if z<0 else min((int(z),3)))
        color = colorDict[idx]

##############################################
## IS THERE  A WAY TO ALSO CHANGE FONT COLOR?
        tb.add_cell(i+1, j+1, width, height, text=fmt.format(val,z),
                    loc='center', facecolor=color)


    # Row labels in cells themselves
    # use -1 with edgecolor='none' for outside the grid
    for i, label in enumerate(data.index):
        tb.add_cell(i+1, 0, width*2, height, text=label, loc='right', facecolor='none')


    # Column Labels...
    for j, label in enumerate(data.columns):
        tb.add_cell(0, j+1, width, height/2, text=label, loc='center', facecolor='none')
    tb.set_fontsize(8)
    ax.add_table(tb)
    return fig

main()



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[AAM_2010_v1.3]

________________________________

Hello

Finally (after long time) I managed to get time and courage to make my
first PR with this little modification
https://github.com/matplotlib/matplotlib/pull/2417

Federico



On Tue, Mar 13, 2012 at 3:17 PM, John Hunter <jd...@gm...> wrote:

>
>
> On Tue, Mar 13, 2012 at 1:20 PM, Federico Ariza <ari...@gm...>wrote:
>
>> Hi
>>
>> That is exactly what I am doing, but I thought it was kept somewhere.
>>
>> I like the idea of upstream modification of relim.
>>
>>
> It would be trivial to add a kwarg to relim:
>
> include_invisible=True
>
> which defaults to the current behavior.
>     def relim(self, include_invisible=True):
>         """
>         Recompute the data
>         limits based on current artists.  If you want to exclude
>         invisible artists from the calculation, set
>         `include_invisible=False`
>
>         At present, :class:`~matplotlib.collections.Collection`
>         instances are not supported.
>         """
>         # Collections are deliberately not supported (yet); see
>         # the TODO note in artists.py.
>         self.dataLim.ignore(True)
>         self.ignore_existing_data_limits = True
>         for line in self.lines:
>     if include_invisible or line.get_visible():
>                 self._update_line_limits(line)
>
>         for p in self.patches:
>     if include_invisible or p.get_visible():
>                 self._update_patch_limits(p)
>
>
> But include_invisible isn't the most intuitive name...
>
> JDH
>
>
>
>



-- 
Y yo que culpa tengo de que ellas se crean todo lo que yo les digo?

-- Antonio Alducin --

I tried rendering some TeX in a figure today but it didn't work. I realized, text.usetex in the matplotlibrc file was set to False. When I add rc('text', usetex=True) to my script, the axis labels are rendered as TeX as well which is undesirable. I don't remember ever having to set this before matplotlib 1.3.0 and I definitely don't remember any difficulty rendering TeX.

Anyone else experiencing this behavior?

Example:

import matplotlib.patheffects as PathEffects

# matplotlib.rc('text', usetex=True)

fig = plt.figure(figsize=(4,4))
ax = fig.add_axes([0,0,0.9,1])
ax.imshow(randn(20,20))
txt = ax.text(0.1, 0.5, r"Some \LaTeX\ $\alpha=\beta$", transform=ax.transAxes,fontsize=16)
txt.set_path_effects([PathEffects.Stroke(linewidth=3, foreground="w"), PathEffects.Normal()])
Produces:



Uncommenting the `matplotlib.rc('text', usetex=True)' line, produces:

Hi all,

I'm trying to refresh a map within a gtk application everytime a button 
is pressed. But whatever I do, it doesn't work. Somehow I need to clear 
the axes. But even that doesn't work. A short hint what I'm missing 
would be great.

Here comes the reduced code:

#!/usr/bin/env python
import pygtk
import gtk

from matplotlib.figure import Figure
from matplotlib.backends.backend_gtkagg import FigureCanvasGTKAgg as 
FigureCanvas
from mpl_toolkits.basemap import Basemap

class BGui:
     def destroy(self, widget, data=None):
         gtk.main_quit()

     def change_zoom(self,button,zoom):
     self.plot_map(zoom)

     def __init__(self):
         self.window = gtk.Window(gtk.WINDOW_TOPLEVEL)
         self.window.connect("destroy", self.destroy)
     self.zoom = 1.
         self.table = gtk.Table(2,1,True)
         self.window.add(self.table)
     self.plot_map(self.zoom)
         self.table.attach(self.canvasMap, 0,1,0,1)
         self.button = gtk.Button("Change Zoom")
         self.button.connect("clicked", self.change_zoom, self.zoom+1.)
     self.table.attach(self.button,0,1,1,2)
         self.window.show_all()

     def plot_map(self,zoom):
         print "plot_map called with zoom:" , zoom
         w = 1.2e6/zoom
         h = 1.2e6/zoom
         self.figMap = Figure()
         self.canvasMap = FigureCanvas(self.figMap)  # a gtk.DrawingArea
         self.canvasMap.set_size_request(200, 200)
         self.axMap = self.figMap.add_axes([0.02, 0.02, 0.96, 0.96])
     #if hasattr(self,'map'):
       #print "clearing axes"
       #del(self.map)
         self.map = Basemap(projection='tmerc', resolution='c',\
             lat_0=52., lon_0=9.5, width=w,height=h,ax=self.axMap)
         self.map.fillcontinents(color='green')
         self.canvasMap.draw()
         self.canvasMap.Refresh(True)

if __name__ == "__main__":
     bah = BGui()
     gtk.main()

Thanks in advance.

Cheers

Mario

-- 
Dr. Mario Mech

Institute for Geophysics and Meteorology
University of Cologne
Zuelpicher Str. 49a
50674 Cologne
Germany

t: +49 (0)221 - 470 - 1776
f: +49 (0)221 - 470 - 5198
e: me...@me...
w: http://www.uni-koeln.de/~mmech/

Hi!
I'm having problem with data plotting in matplotlib. Tried versions, 1.2.0
and 1.3.0 too, the same thing occurs except the error message. On 1.2.0 the
error message is Agg complexity exceeded on 1.3.0 it is Allocated too many
blocks.
The data i need to plot is 1M pts long and it's a bit complex (have a lot of
big changes). 

data = []
for a in range(0,1000000):
    data.append(int(random.random()*256))

I can catch the Overflow excepton, and i recover the matplotlib widget by
resetting the renderer, but the memory allocated by the previous plot is
still allocated until i close the app.
Is there a way to find where that memory leaked and how could i free it up?
Tried to clear the variables where i store the data, also cleared the figure
with .clear(), .clf(), .close() the memory is still used.



--
View this message in context: http://matplotlib.1069221.n5.nabble.com/Agg-complexity-exceeded-or-allocated-too-many-blocks-tp41998.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

> Sourav Chatterjee <mailto:sr...@gm...>
> September 11, 2013 3:48 AM
> I am using 'spstere' for polar stereo graphic projection over 
> Antarctica. The specifications llcrnrlat, llcrnrlon etc are specified 
> in a python module. When I am doing it over north pole it is okay. But 
> in South pole the latitude circles are not appearing. Can anyone tell 
> where is the fault?
>
> Thanks in advance

Sample code please?

-Jeff
>
> -- 
> Sourav Chatterjee
> ------------------------------------------------------------------------------
> How ServiceNow helps IT people transform IT departments:
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> ------------------------------------------------------------------------

I am using 'spstere' for polar stereo graphic projection over Antarctica.
The specifications llcrnrlat, llcrnrlon etc are specified in a python
module. When I am doing it over north pole it is okay. But in South pole
the latitude circles are not appearing. Can anyone tell where is the fault?

Thanks in advance

-- 
Sourav Chatterjee

Hello,

I create a plot on which I need to place small bitmaps at a given
location with a given size. Something like sprites but not for animation
or a game.  Can someone explain to me how to do that?

Thanks

On Sun, Sep 8, 2013 at 12:37 PM, Skip Montanaro <ski...@gm...>wrote:

> (Apologies that this is not plain text. I'm trying to find an alternative
> to the broken Gmail compose functionality and haven't yet figured out if
> Apple Mail allows me to compose plain text emails.)
>
> On Sep 8, 2013, at 10:51 AM, Rita wrote:
>
> > Trying to compile matplotlib on Linux and it seems when I set
> CFLAGS="-L/software/gcc-7.3/lib64" these settings aren't taking affect
> >
> > export CFLAGS
> > python setup.py build
> >
> > is there any thing else I should be setting?
>
> A couple things come to mind. First, since you are setting link flags, you
> might try LDFLAGS instead of CFLAGS. Second, try running
>
>     python setup.py build --help
>
> to see what flags you can apply to the build command.
>
> Skip
>
>
>
Skip, thankyou. I had a slight typo in my script. sorry for wasting your
time.



-- 
--- Get your facts first, then you can distort them as you please.--

Trying to compile matplotlib on Linux and it seems when I set
CFLAGS="-L/software/gcc-7.3/lib64" these settings aren't taking affect

export CFLAGS
python setup.py build

is there any thing else I should be setting?



-- 
--- Get your facts first, then you can distort them as you please.--

2013/9/3 Michael Droettboom <md...@st...>:

> That's correct.  We could probably do a better job reporting that to the
> user, though.  Would you mind creating an issue for that?

https://github.com/matplotlib/matplotlib/issues/2379