matplotlib-users Mailing List for matplotlib

Hi Stefan,
> I've hit a problem when using the button_press_event to pop up a
> wx.MessageBox. After the messagebox is loaded the mouse becomes completely
> unresponsive (even outside the application) until the application is shut
> down (by using ALT+F4). I'm making a feature where the user, after right
> clicking on the figure (after doing some manipulations etc), are requested
> to answer a question in a message box.
>
> This problem seems only to occur on Linux..
>
> Am I doing something wrong or is this a bug?
>
> I've attached the source that demonstrates the problem.
Oddly, I saw very similar behavior recently (I didn't see the
attachment...). What I found was that the canvas was still
responsive, but that it "stole" the mouse from any other window (wx
widgets or system widgets) and that this happened on Linux but not
Windows.
I believe that adding
 self.ReleaseMouse()
at the end of the event handler will alleviate this problem. It might
be best to do (assuming you bound mouse events with the
 Canvas.mpl_connect() ) to do
 evt.guiEvent.Skip()
 if self.HasCapture(): self.ReleaseMouse()
I haven't fully explored this problem myself, but I am no longer
experiencing it...
Cheers,
--Matt Newville <newville at cars.uchicago.edu>

On Mon, May 3, 2010 at 4:02 PM, Darren Dale <dsd...@gm...> wrote:
> On Sun, Apr 18, 2010 at 12:55 PM, Gökhan Sever <gok...@gm...> wrote:
>>
>>
>> On Sun, Apr 18, 2010 at 11:47 AM, Darren Dale <dsd...@gm...> wrote:
>>>
>>> On Tue, Apr 13, 2010 at 8:14 PM, Gökhan Sever <gok...@gm...>
>>> wrote:
>>> > Hello,
>>> >
>>> > Could someone confirm me if there is any malfunctioning using these
>>> > simple
>>> > figure functions?
>>> >
>>> > plt.figure(figsize=(2,3))
>>> >
>>> > plt.figure(figsize=(5,6))
>>> >
>>> > plt.figure(figsize=(9,15))
>>> >
>>> > plt.figure(figsize=(19,5))
>>> >
>>> > For some reason I can't get Qt4Agg creating last two figures in
>>> > specified
>>> > sizes. (WXAgg works fine.)
>>> >
>>> > matplotlib.__version__
>>> > '1.0.svn'
>>> >
>>> > matplotlib.__revision__
>>> > '$Revision: 8226 $'
>>> >
>>> > from PyQt4 import QtCore
>>> > QtCore.PYQT_VERSION_STR
>>> > '4.7'
>>>
>>> I can reproduce this behavior with a pure pyqt4 example with no mpl
>>> code, see below. I asked for advice on the pyqt mailing list.
>>>
>>> import sys
>>> from PyQt4 import QtCore, QtGui
>>>
>>> class Test(QtGui.QWidget):
>>>
>>>  def __init__(self, width, height):
>>>    QtGui.QWidget.__init__(self)
>>>    #self.setSizePolicy(QtGui.QSizePolicy.Fixed,
>>> QtGui.QSizePolicy.Fixed)
>>>    print 'Central widget should have width=%d, height=%d' %(width,
>>> height)
>>>    self._width = width
>>>    self._height = height
>>>
>>>  def sizeHint(self):
>>>    return QtCore.QSize(self._width, self._height)
>>>
>>> app = QtGui.QApplication([])
>>> m = QtGui.QMainWindow()
>>> c = Test(1000, 700)
>>> m.setCentralWidget(c)
>>> m.show()
>>> s = c.size()
>>> print 'but central widget has width=%d, height=%d'% (s.width(),
>>> s.height())
>>> sys.exit(app.exec_())
>>
>> Same here with your sample:
>>
>> Central widget should have width=1000, height=700
>> but central widget has width=960, height=600
>>
>> I resorted to WXAgg for the time being. Waiting for some updates till I hear
>> a resolution. The annoying part is when I created a plot using specified
>> width and height Qt4Agg doesn't follow these dimensions as in this case and
>> resulting savefig(file.pdf) produces wrongly sized file unless I manually
>> extend the figure area and re-issue a savefig afterwards.
>
> I got a suggestion at the PyQt4 mailing list, and the following patch
> appears to resolve the problem. However, before I commit the change,
> I'd like to hear from John or Andrew: What is the protocol for dealing
> with a change that may affect unit tests?
This shouldn't affects tests I don't think because it is a change to a
GUI backend and we are only doing unit tests on hardcopy images at
this point.
In general, run matplotlib.test
 > python -c 'import matplotlib; matplotlib.test()'
and look to see if any tests are failing. If any are, either fix the
problem or if you decide the baseline image is broken update that in
lib/matplotlib/tests/baseline_images. There is more in
doc/devel/coding_guide.rst under "Testing". Andrew may have more to
add...
JDH

On Sun, Apr 18, 2010 at 12:55 PM, Gökhan Sever <gok...@gm...> wrote:
>
>
> On Sun, Apr 18, 2010 at 11:47 AM, Darren Dale <dsd...@gm...> wrote:
>>
>> On Tue, Apr 13, 2010 at 8:14 PM, Gökhan Sever <gok...@gm...>
>> wrote:
>> > Hello,
>> >
>> > Could someone confirm me if there is any malfunctioning using these
>> > simple
>> > figure functions?
>> >
>> > plt.figure(figsize=(2,3))
>> >
>> > plt.figure(figsize=(5,6))
>> >
>> > plt.figure(figsize=(9,15))
>> >
>> > plt.figure(figsize=(19,5))
>> >
>> > For some reason I can't get Qt4Agg creating last two figures in
>> > specified
>> > sizes. (WXAgg works fine.)
>> >
>> > matplotlib.__version__
>> > '1.0.svn'
>> >
>> > matplotlib.__revision__
>> > '$Revision: 8226 $'
>> >
>> > from PyQt4 import QtCore
>> > QtCore.PYQT_VERSION_STR
>> > '4.7'
>>
>> I can reproduce this behavior with a pure pyqt4 example with no mpl
>> code, see below. I asked for advice on the pyqt mailing list.
>>
>> import sys
>> from PyQt4 import QtCore, QtGui
>>
>> class Test(QtGui.QWidget):
>>
>>  def __init__(self, width, height):
>>    QtGui.QWidget.__init__(self)
>>    #self.setSizePolicy(QtGui.QSizePolicy.Fixed,
>> QtGui.QSizePolicy.Fixed)
>>    print 'Central widget should have width=%d, height=%d' %(width,
>> height)
>>    self._width = width
>>    self._height = height
>>
>>  def sizeHint(self):
>>    return QtCore.QSize(self._width, self._height)
>>
>> app = QtGui.QApplication([])
>> m = QtGui.QMainWindow()
>> c = Test(1000, 700)
>> m.setCentralWidget(c)
>> m.show()
>> s = c.size()
>> print 'but central widget has width=%d, height=%d'% (s.width(),
>> s.height())
>> sys.exit(app.exec_())
>
> Same here with your sample:
>
> Central widget should have width=1000, height=700
> but central widget has width=960, height=600
>
> I resorted to WXAgg for the time being. Waiting for some updates till I hear
> a resolution. The annoying part is when I created a plot using specified
> width and height Qt4Agg doesn't follow these dimensions as in this case and
> resulting savefig(file.pdf) produces wrongly sized file unless I manually
> extend the figure area and re-issue a savefig afterwards.
I got a suggestion at the PyQt4 mailing list, and the following patch
appears to resolve the problem. However, before I commit the change,
I'd like to hear from John or Andrew: What is the protocol for dealing
with a change that may affect unit tests?
Darren
Index: lib/matplotlib/backends/backend_qt4.py
===================================================================
--- lib/matplotlib/backends/backend_qt4.py	(revision 8292)
+++ lib/matplotlib/backends/backend_qt4.py	(working copy)
@@ -318,6 +318,11 @@
 QtCore.QObject.connect(self.toolbar, QtCore.SIGNAL("message"),
 self.window.statusBar().showMessage)
+ cs = canvas.sizeHint()
+ tbs = self.toolbar.sizeHint()
+ sbs = self.window.statusBar().sizeHint()
+ self.window.resize(cs.width(), cs.height()+tbs.height()+sbs.height())
+
 self.window.setCentralWidget(self.canvas)
 if matplotlib.is_interactive():

I don't know why this happens, but did note that using a 
"button_release_event" instead seems to work fine.
Mike
Søren Nielsen wrote:
> Hi,
>
> I've hit a problem when using the button_press_event to pop up a 
> wx.MessageBox. After the messagebox is loaded the mouse becomes 
> completely unresponsive (even outside the application) until the 
> application is shut down (by using ALT+F4). I'm making a feature where 
> the user, after right clicking on the figure (after doing some 
> manipulations etc), are requested to answer a question in a message box.
>
> This problem seems only to occur on Linux..
>
> Am I doing something wrong or is this a bug?
>
> I've attached the source that demonstrates the problem.
>
> Thanks,
> Soren
>
> ------------------------------------------------------------------------
>
> ------------------------------------------------------------------------------
> 
> ------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

On Mon, May 3, 2010 at 1:12 PM, Christopher Brown <c-...@as...> wrote:
> Hi List,
>
> How can I change the (fore)color of a figure title (pp.title('Wow!'))
> after it has been added to the figure? I can do this with axes labels
> like this:
>
> pp.gca().axes.xaxis.label.set_color(color)
pp.gca().axes.title.set_color(color)
You can also save the return value from pp.title:
t = pp.title('Wow!')
t.set_color(color)
Ryan
-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma

Hi List,
How can I change the (fore)color of a figure title (pp.title('Wow!')) 
after it has been added to the figure? I can do this with axes labels 
like this:
pp.gca().axes.xaxis.label.set_color(color)
-- 
Christopher Brown, Ph.D.
Associate Research Professor
Department of Speech and Hearing Science
Arizona State University
http://pal.asu.edu

Hello Eric,
thank you so much fo your feedback and the fix! it works as expected.
bye for now
Margherita
----- Original Message -----
From: Eric Firing <ef...@ha...>
Date: Friday, April 30, 2010 6:01 pm
Subject: Re: [Matplotlib-users] question about axis scale multiplier
> Margherita Vittone wiersma wrote:
> > HI,
> > i am making a scatter plot and i simply use defaults for tick 
> formatting etc;
> > when i plot the data the plot show on the x axis a multiplier 
> scaling with scintific notation;
> > i would like to get rid of it , the data looks like this:
> > 
> > values5 = [-102.44,-102.51,-102.47,-102.52,-102.52,-102.51,-102.44,-102.51,-102.47
> > -102.52,-102.52,-102.51,-102.52,-102.49,-102.51,-102.51,-102.51,-102.52
> > -102.57,-102.46,-102.55,-102.51,-102.49,-102.51,-102.51,-102.51,-102.52
> > ......]
> > 
> > values6 = [-98.58,-98.48,-98.5,-98.47,-98.52,-98.48,-98.58,-98.48,-98.5,-98.47,-98.52,
> > -98.48,-98.48,-98.48,-98.48,-98.53,-98.48,-98.52,-98.58,-98.58,-98.47,
> > -98.55,-98.48,-98.48,-98.53,-98.48,-98.52,-98.58,-98.58,-98.47,-98.55,
> > -98.53,-98.48,-98.47,-98.42,-98.48,-98.45,-98.47,-98.52,-98.45,-98.58,
> > ....]
> > 
> > 
> > and when the plot is shown as in the the attachement it show the 
> scintific notation
> > at the x scale.
> 
> If it were just a matter of scientific notation, you would be able to 
> 
> use the ticklabel_format Axes method with style='plain' to turn it 
> off. 
> The real problem, though, is that an offset is being used. With 
> mpl 
> from svn, you can also turn that off with the ticklabel_format() 
> function or method, but with released versions you need something a 
> little more arcane, e.g.
> 
> import pyplot as plt
> plt.scatter(values5, values6)
> ax = plt.gca()
> ax.xaxis.set_major_formatter(plt.ScalarFormatter(useOffset=False))
> #ax.xaxis.set_major_locator(plt.MaxNLocator(nbins=6, steps=[1,2,5,10]))
> plt.draw()
> 
> The commented-out line reduces the number of tick marks; you may want 
> to 
> do this because without the offset, the tick labels can get a bit 
> long 
> and crowded.
> 
> Eric
> 
> 
> > 
> > Any input is appreciated. Thank you much
> > bye for now
> > 
> > Margherita
> > 
> > 
> > 
> > 
> > ------------------------------------------------------------------------
> > 
> > HI,
> > i am making a scatter plot and i simply use defaults for tick 
> formatting etc;
> > when i plot the data the plot show on the x axis a multiplier 
> scaling with scintific notation;
> > i would like to get rid of it , the data looks like this:
> > 
> > values5 = [-102.44,-102.51,-102.47,-102.52,-102.52,-102.51,-102.44,-102.51,-102.47
> > -102.52,-102.52,-102.51,-102.52,-102.49,-102.51,-102.51,-102.51,-102.52
> > -102.57,-102.46,-102.55,-102.51,-102.49,-102.51,-102.51,-102.51,-102.52
> > ......]
> > 
> > values6 = [-98.58,-98.48,-98.5,-98.47,-98.52,-98.48,-98.58,-98.48,-98.5,-98.47,-98.52,
> > -98.48,-98.48,-98.48,-98.48,-98.53,-98.48,-98.52,-98.58,-98.58,-98.47,
> > -98.55,-98.48,-98.48,-98.53,-98.48,-98.52,-98.58,-98.58,-98.47,-98.55,
> > -98.53,-98.48,-98.47,-98.42,-98.48,-98.45,-98.47,-98.52,-98.45,-98.58,
> > ....]
> > 
> > 
> > and when the plot is shown as in the the attachement it show the 
> scintific notation
> > at the x scale.
> > 
> > Any input is appreciated. Thank you much
> > bye for now
> > 
> > Margherita
> > 
> > 
> > 
> > 
> > ------------------------------------------------------------------------
> > 
> > 
> > ------------------------------------------------------------------------
> > 
> > ------------------------------------------------------------------------------
> > 
> > 
> > ------------------------------------------------------------------------
> > 
> > _______________________________________________
> > Matplotlib-users mailing list
> > Mat...@li...
> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
> 

Hello,
I send this message because I have a problem with "On-Pick" Funtion.
When I use this function with my datas, cartesian coordinates don't
correspond. 
Seems to work with the example, but not with my data, somebody knows why ?
Thanks you for your reply !!!
My code : 
"""
compute the mean and stddev of 100 data sets and plot mean vs stddev.
When you click on one of the mu, sigma points, plot the raw data from
the dataset that generated the mean and stddev
"""
import numpy as np
import matplotlib.pyplot as plt
compteurdata = 0 
positif = 0
datas = [0]
myrange = []
xs = range(2500)
chemin = "C:/Users/utilisateur/Desktop/ProtoData/1902-1/plotcolonne.txt"
fichier = open(chemin,'r')
# 5 points tolerance
#declaration de variables 
# Lecture de la table 
 
for l in fichier.readlines():
 if compteurdata < 2499 :
 l = float(l)
 datas.append(l)
 compteurdata = compteurdata + 1 
 else: 
 pass
 
 
ys = datas 
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_title('click on point to plot time series')
line, = ax.plot(xs, ys, 'o', picker=5)
def onpick(event):
 if event.artist!=line: return True
 N = len(event.ind)
 
 if not N: return True
 print xs[event.ind],ys[event.ind]
 
fig.canvas.mpl_connect('pick_event', onpick)
plt.show()
-- 
View this message in context: http://old.nabble.com/Why-when-I-Use--ZooM%2C-On-Pick-Event-don%27t-correspond-to-my-plots-datas-tp28433072p28433072.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

2010年05月02日 20:19, aditya bhargava skrev:
> Is there a straightforward way of plotting a vector in matplotlib?
> Suppose I want to plot the vector [1 2]'. If I pass this vector in to
> plot(), I get the line that passes through (0,1), (1,2). Instead I want
> the line that passes through (0,0),(1,2).
>
I use pyplot.Arrow to visualize displacement fields.
This is a snippet copied from the code I use (it sits in a loop over all 
vectors I want to plot):
 arr = plt.Arrow(x, y, dx, dy)
 plt.gca().add_patch(arr)
In your case, you would have (x, y) = (0, 0) and (dx, dy) = (1, 2).
Regards
Johan

I'm using wxagg, but actually it's working now... I put show()s a bit
everywhere in my code so I must confess I don't really know how it's
working, though I'll probably have to go back and clean the mess at some
point.
Antony
2010年4月22日 Michiel de Hoon <mjl...@ya...>
> Actually which backend are you using? I'd like to try this to see what
> happens if show() is called more than once.
>
> --Michiel.
>
>
> --- On *Tue, 4/20/10, Antony Lee <ant...@en...>* wrote:
>
> That would be a solution, indeed. However, is there really no way of
> coming back to a pre-plt.show() state once all windows are closed? What
> kind of irreversible things does plt.show() do?
>
>
>

On 05/02/2010 05:48 PM, Kun Hong wrote:
> Hi,
>
> I am new to matplotlib. So if I ask sth stupid, please bear with me.
>
> I am using matplotlib to present large data set in different graph
> types,
> bar, dot, line, etc. I find that the bar graph has very bad performance.
> Say, I draw data points of about ten thousand. Using dot graph, it draws
> in a second. But using bar graph, it draws in tens of seconds.
>
> I was wondering what causes this difference. Is there a way to improve
> the
> bar graph performace? (Maybe I am not drawing it right, then, please
> give
> me a pointer)
>
Also check out step().
http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.step
Eric
> Below is a simple example:
>
> from np.random import uniform
> from numpy.random import uniform
> x = uniform(0, 10, 14000)
> y = uniform(0, 100, 14000)
> plt.plot(x, y, 'bo')
> plt.bar(x, y)
>
>
> Thanks,
> Kun
>
>
> ------------------------------------------------------------------------------
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

On 05/02/2010 05:48 PM, Kun Hong wrote:
> Hi,
>
> I am new to matplotlib. So if I ask sth stupid, please bear with me.
>
> I am using matplotlib to present large data set in different graph
> types,
> bar, dot, line, etc. I find that the bar graph has very bad performance.
> Say, I draw data points of about ten thousand. Using dot graph, it draws
> in a second. But using bar graph, it draws in tens of seconds.
>
> I was wondering what causes this difference. Is there a way to improve
> the
> bar graph performace? (Maybe I am not drawing it right, then, please
> give
> me a pointer)
Bar is intended for plots in which the bars are individually visible, so 
it makes sense only for a small number--say 10 or 20 bars. It is 
implemented using an individual patch for each bar, and this is 
inherently slow in mpl--but for under 100 bars, it doesn't matter at all.
If you have a large number of points, maybe what you are looking for is 
fill() or fill_between(). Check the links for these in 
http://matplotlib.sourceforge.net/.
Eric
>
> Below is a simple example:
>
> from np.random import uniform
> from numpy.random import uniform
> x = uniform(0, 10, 14000)
> y = uniform(0, 100, 14000)
> plt.plot(x, y, 'bo')
> plt.bar(x, y)
>
>
> Thanks,
> Kun

Hi,
I am new to matplotlib. So if I ask sth stupid, please bear with me.
I am using matplotlib to present large data set in different graph 
types,
bar, dot, line, etc. I find that the bar graph has very bad performance.
Say, I draw data points of about ten thousand. Using dot graph, it draws
in a second. But using bar graph, it draws in tens of seconds.
I was wondering what causes this difference. Is there a way to improve 
the
bar graph performace? (Maybe I am not drawing it right, then, please 
give
me a pointer)
Below is a simple example:
from np.random import uniform
from numpy.random import uniform
x = uniform(0, 10, 14000)
y = uniform(0, 100, 14000)
plt.plot(x, y, 'bo')
plt.bar(x, y)
Thanks,
Kun

Hi,
I am new to matplotlib. So if I ask sth stupid, please bear with me.
I am using matplotlib to present large data set in different graph types,
bar, dot, line, etc. I find that the bar graph has very bad performance.
Say, I draw data points of about ten thousand. Using dot graph, it draws
in a second. But using bar graph, it draws in tens of seconds.
I was wondering what causes this difference. Is there a way to improve the
bar graph performace? (Maybe I am not drawing it right, then, please give
me a pointer)
Below is a simple example:
from np.random import uniform
from numpy.random import uniform
x = uniform(0, 10, 14000)
y = uniform(0, 100, 14000)
plt.plot(x, y, 'bo')
plt.bar(x, y)
Thanks,
Kun