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From: Sudheer J. <sud...@ya...> - 2013-03-12 00:04:43
|
Dear experts, Is there a way to get back to the prompt after a plot is made and displayed with out closing the plot? The objective is to compare to plots or check some aspect about the plot made from the loaded variables. This is the standard behavior of matlab after plotting we get the prompt and we can make another plot if we want to compare 2. I know there is subplot option but it will be of small size if I need to make a spatial map at to time intervals and compare. The detail of my matplotlib is below %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% I use Ubuntu 12.04 64 bit version and In [3]: matplotlib.get_backend() Out[3]: 'WXAgg' In [4]: matplotlib.__version__ Out[4]: '1.2.0' with best regards, Sudheer *************************************************************** Sudheer Joseph Indian National Centre for Ocean Information Services Ministry of Earth Sciences, Govt. of India POST BOX NO: 21, IDA Jeedeemetla P.O. Via Pragathi Nagar,Kukatpally, Hyderabad; Pin:5000 55 Tel:+91-40-23886047(O),Fax:+91-40-23895011(O), Tel:+91-40-23044600(R),Tel:+91-40-9440832534(Mobile) E-mail:sjo...@gm...;sud...@ya... Web- http://oppamthadathil.tripod.com *************************************************************** ________________________________ . |
|
From: Nathaniel A. F. <naf...@vt...> - 2013-03-11 22:07:58
|
Hi, everyone. I think I found a couple of bugs, but maybe someone knows something about this before I go filing a bug report. Matplotlib version: 1.1.1rc Bug 1: I'm using axis.twiny() to plot two data sets on top of each other using a shared y-axis. If the values are large, an exponent multiplier appears off to the right of the axis labels. The regular ticklabels for the second data set are correctly plotted on top of the figure. However, the exponent does not follow. Here is an example plot (code is attached): http://sd-work1.ece.vt.edu/offsettext.png Bug 2: In trying to come up with a work around for bug 1, I tried to use the axis.xaxis.get_offset_text().get_text() method to grab the text and then plot it else where. However, it returns an empty string when I try to assign it to a variable. It will do this until I change the state of the memory some how, such as creating another figure or dropping to the debugger. After that, produces the correct value. Please see the attached code, lines 24-33. Thanks for any help you may have, Nathaniel |
|
From: Alan G I. <ala...@gm...> - 2013-03-11 21:08:19
|
On 3/11/2013 1:59 PM, Neal Becker wrote: > I go through a compute loop that takes maybe a few seconds per pass, then plot a new point on the graph. If you are willing to use TkAgg, see the TSPlot class here: https://econpy.googlecode.com/svn-history/r175/trunk/abm/gridworld/gridworld.py Alan Isaac |
|
From: Hearne, M. <mh...@us...> - 2013-03-11 20:44:27
|
I have an issue with basemap.imshow() at higher latitudes - namely the image (high-res topography, in this case) becomes distorted with respect to the coastlines the higher I go. I assume it has to do with the image pixels becoming more non-square the higher I go in latitude. I found this discussion: http://matplotlib.1069221.n5.nabble.com/Basemap-and-imshow-td14115.html where Jeff indicates that the user is using a non-rectangular map projection. I'm thinking that is perhaps my problem (I'm using Transverse Mercator), but I'm not sure which projections Basemap supports that *are* rectangular. Or perhaps it's something else entirely. Any hints? Thanks, Mike Hearne |
|
From: Brendan B. <bre...@br...> - 2013-03-11 19:23:35
|
I'm 64-bit Windows 7 with matplotlib 1.2.0 and WxPython 2.8.12.1. I
was fiddling around with some of the different backends to see what
they look like and I found that the WxAgg backend doesn't work:
Python 2.7.3 (default, Apr 10 2012, 23:24:47) [MSC v.1500 64 bit
(AMD64)] on win
32
Type "help", "copyright", "credits" or "license" for more information.
>>> import matplotlib as mpl
>>> mpl.use('WxAgg')
>>> from matplotlib import pyplot
>>> pyplot.ion()
>>> pyplot.plot([1, 2, 3])
[<matplotlib.lines.Line2D object at 0x0000000006757DA0>]
>>>
When I do the plot, the figure windows appears, but it's blank
(without even a proper blank background, just a white area) and
immediately shows "Not responding". I have to kill the window, and
doing so crashes the Python session. However, it works without the
"ion()" call: I can then call show() and see the plot fine.
I have wxPython working fine in other apps. In fact, what's
especially odd is that I actually have an app that directly uses
FigureCanvasWxAgg to embed matplotlib graphs in a GUI, and this seems
to work fine. So it seems the problem is somehow in matplotlib's own
management of the interactive figure window.
There was a previous question about a similar WxAgg issue on the list
(
http://matplotlib.1069221.n5.nabble.com/trouble-with-show-not-drawing-in-interactive-mode-w-WxAgg-td39110.html
), but there was no real answer: the poster just decided not to use
WxAgg. But aren't we really supposed to be able to use WxAgg
interactively?
Thanks,
--
Brendan Barnwell
"Do not follow where the path may lead. Go, instead, where there is
no path, and leave a trail."
--author unknown
|
|
From: Werner F. B. <wer...@fr...> - 2013-03-11 19:01:18
|
Hi,
Some time ago I tried to upgrade from an old version of mpl 0.99 to 1.0
but couldn't get it to work with py2exe and running on a Athlon PC.
I finally got around to upgrade things and have another go at this.
I am now on:
Python 2.7
Numpy 1.6.1 /arch nosse
mpl 1.2.0
I see a hard crash on the Athlon PC (i.e. no traceback and the MS Win
error "App encountered a problem, do you want to report to MS".
Trying to narrow it down I don't think it has to do with numpy as I use
it elsewhere in the app together with wxPython/FloatCanvas without any
issue and when I track where the crash is happening with print
statements it happens on this line:
print 'plot panel 1'
# initialize matplotlib stuff
self.figure = mpl.figure.Figure(figsize=(5, 4), dpi=75,
facecolor='white',
edgecolor='white')
print 'plot panel 2'
I still see the first print statement but not the second, my imports are
as follows:
import matplotlib as mpl
mpl.use('WXAgg')
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as
FigureCanvas
I know I don't provide a lot of information (at least not yet), but has
anyone come across some similar crash with py2exe and mpl when one
creates a Figure?
Any tips on how to further narrow this down or even better on what is
needed to fix it are very welcome.
Best regards
Werner
|
|
From: David H. <dh...@gm...> - 2013-03-11 18:23:36
|
I agree, I don't think that will work with mpl's animation stuff or at
least I wouldn't want to do it that way. I've created GUIs that received
data from a weather instrument in real-time. I did method 3 that I
mentioned before because I knew the scientists using it were going to
want more and more features.
...I FOUND A WAY FOR YOU TO CHEAT:
You can use the Qt "processEvents()" method to have it process
drawing/painting operation between the event loop iterations. This
method is frowned upon when doing real Qt GUIs, but eh go for it. If you
aren't doing anything more serious than watching the output of your
processing as it goes then try this:
import matplotlib
matplotlib.use('qt4agg')
import matplotlib as mpl
import matplotlib.pyplot as plt
plt.ion()
import numpy as np
from time import sleep
from PyQt4 import QtGui,QtCore
fig=plt.figure()
plt.axis([0,1000,0,1])
i=0
x=list()
y=list()
while i <1000:
temp_y=np.random.random()
x.append(i)
y.append(temp_y)
plt.scatter(i,temp_y)
i+=1
plt.draw()
sleep(1)
QtGui.qApp.processEvents()
Good luck,
Dave
On 3/11/13 12:59 PM, Neal Becker wrote:
> I go through a compute loop that takes maybe a few seconds per pass,
> then plot a new point on the graph. Do I have to? No - I thought mpl
> was supposed to do this and wanted to learn how. If it really doesn't
> work I'll do something else.
>
> I don't think animation is correct here - I had the impression
> animation is where my update would be run as a callback, with a main
> loop that calls me periodically. Could that fit the model I
> described, where a lengthy computation produces a new value every
> few/10s of seconds?
>
>
> On Mon, Mar 11, 2013 at 1:55 PM, David Hoese <dh...@gm...
> <mailto:dh...@gm...>> wrote:
>
> Someone may have to correct me, but I think this has to do with
> the Qt4 event loop and it not being run properly. When you get
> into real time plotting it can get kind of tricky. In your case (I
> got the same results). I have made real-time PyQt4 GUIs before and
> have always used separate QThreads and Qt signals/slots to update
> the plot. I've never used GTK so I'm not sure why that worked vs
> Qt, I would think they would use similar principles but matplotlib
> does some magic behind the scenes sometimes. You can see different
> results if you comment out the while loop and import the module
> into your python/ipython interpreter. After doing this you'll see
> the figure pop up (you don't even need the fig.canvas.show() for
> this part if interactive mode is on. I went one step further and
> turned the while loop into a function:
>
> def one_iter(i):
> # Contents of while loop
>
> Calling this in the interpreter shows the figure updating after
> each call, but running in a loop (even with sleep) won't show any
> updates until the loop is done. In my opinion you have a few
> choices that really depend on your programming comfort level:
>
> 1. Don't make a real-time plot.
> Do you really need a real-time plot that updates from some
> external source?
> 2. Maybe you should look at the matplotlib animation functionality
> (http://matplotlib.org/api/animation_api.html). I like this
> tutorial:
> http://jakevdp.github.com/blog/2012/08/18/matplotlib-animation-tutorial/.
> This won't get you a real-time GUI exactly, but it can help if
> what you're doing isn't too complicated. It can also be nice for
> making videos of plot animations.
> 3. If you need a GUI with multiple plots and you need for future
> feature creep, I would research making PyQt4 GUIs, QThreads, Qt
> signals and slots, and putting matplotlib figures into a PyQt4
> GUI. This is complex if you are not familiar with GUI programming
> and will take a while.
>
> Sorry I couldn't be of more help, but it really depends on what
> exactly you are doing. Mainly, what do you mean by real-time? Do
> you really mean animation? Let me know what you come up with, I'm
> interested.
>
> -Dave
>
> P.S. Why use a while loop? You can do the same thing with:
>
> for i in range(1000):
> # Do stuff
>
>
> On 3/11/13 10:34 AM, Neal Becker wrote:
>> I added fig.canvas.show(). It still does nothing.
>>
>> If I add
>> mpl.use ('GTK'), now it seems to be doing realtime plotting.
>>
>> import matplotlib as mpl
>>
>> import matplotlib.pyplot as plt
>> plt.ion()
>> import numpy as np
>> fig=plt.figure()
>> plt.axis([0,1000,0,1])
>>
>> i=0
>> x=list()
>> y=list()
>>
>> fig.canvas.show()
>> while i <1000:
>> temp_y=np.random.random()
>> x.append(i)
>> y.append(temp_y)
>> plt.scatter(i,temp_y)
>> i+=1
>> plt.draw()
>>
>>
>>
>> On Mon, Mar 11, 2013 at 10:35 AM, David Hoese <dh...@gm...
>> <mailto:dh...@gm...>> wrote:
>>
>> Oops forgot to change the subject line.
>>
>> On 3/11/13 9:34 AM, David Hoese wrote:
>>
>> You likely need to "show()" the canvas. I usually do this
>> by calling "fig.canvas.show()" before the for loop.
>> Since you are using a Qt4 backend the canvas used by the
>> figure is a QWidget, the basic component of a Qt4 GUI. I
>> don't know if there is a more matplotlib specific way of
>> doing this, but when dealing with a larger system this is
>> how I do it.
>>
>> I would also add a sleep ("from time import sleep") of a
>> couple seconds for testing to make sure you are getting
>> through the entire for loop before you can see it.
>>
>> Please CC in any replies, thanks.
>>
>> -Dave
>>
>>
>> On 3/11/13 8:58 AM, ndb...@gm...
>> <mailto:ndb...@gm...> wrote:
>>
>> I want to update a plot in real time. I did some
>> goog search, and saw various
>> answers. Trouble is, they aren't working.
>>
>> Here's a typical example:
>>
>> import matplotlib.pyplot as plt
>> import numpy as np
>> fig=plt.figure()
>> plt.axis([0,1000,0,1])
>>
>> i=0
>> x=list()
>> y=list()
>>
>> while i <1000:
>> temp_y=np.random.random()
>> x.append(i)
>> y.append(temp_y)
>> plt.scatter(i,temp_y)
>> i+=1
>> plt.draw()
>>
>> If I run this, it draws nothing.
>>
>> This is my matplotlibrc:
>> backend : Qt4Agg
>> mathtext.fontset: stix
>>
>>
>>
>>
>
>
|
|
From: Neal B. <ndb...@gm...> - 2013-03-11 17:59:16
|
I go through a compute loop that takes maybe a few seconds per pass, then plot a new point on the graph. Do I have to? No - I thought mpl was supposed to do this and wanted to learn how. If it really doesn't work I'll do something else. I don't think animation is correct here - I had the impression animation is where my update would be run as a callback, with a main loop that calls me periodically. Could that fit the model I described, where a lengthy computation produces a new value every few/10s of seconds? On Mon, Mar 11, 2013 at 1:55 PM, David Hoese <dh...@gm...> wrote: > Someone may have to correct me, but I think this has to do with the Qt4 > event loop and it not being run properly. When you get into real time > plotting it can get kind of tricky. In your case (I got the same results). > I have made real-time PyQt4 GUIs before and have always used separate > QThreads and Qt signals/slots to update the plot. I've never used GTK so > I'm not sure why that worked vs Qt, I would think they would use similar > principles but matplotlib does some magic behind the scenes sometimes. You > can see different results if you comment out the while loop and import the > module into your python/ipython interpreter. After doing this you'll see > the figure pop up (you don't even need the fig.canvas.show() for this part > if interactive mode is on. I went one step further and turned the while > loop into a function: > > def one_iter(i): > # Contents of while loop > > Calling this in the interpreter shows the figure updating after each call, > but running in a loop (even with sleep) won't show any updates until the > loop is done. In my opinion you have a few choices that really depend on > your programming comfort level: > > 1. Don't make a real-time plot. > Do you really need a real-time plot that updates from some > external source? > 2. Maybe you should look at the matplotlib animation functionality ( > http://matplotlib.org/api/animation_api.html). I like this tutorial: > http://jakevdp.github.com/blog/2012/08/18/matplotlib-animation-tutorial/. > This won't get you a real-time GUI exactly, but it can help if what you're > doing isn't too complicated. It can also be nice for making videos of plot > animations. > 3. If you need a GUI with multiple plots and you need for future feature > creep, I would research making PyQt4 GUIs, QThreads, Qt signals and slots, > and putting matplotlib figures into a PyQt4 GUI. This is complex if you are > not familiar with GUI programming and will take a while. > > Sorry I couldn't be of more help, but it really depends on what exactly > you are doing. Mainly, what do you mean by real-time? Do you really mean > animation? Let me know what you come up with, I'm interested. > > -Dave > > P.S. Why use a while loop? You can do the same thing with: > > for i in range(1000): > # Do stuff > > > On 3/11/13 10:34 AM, Neal Becker wrote: > > I added fig.canvas.show(). It still does nothing. > > If I add > mpl.use ('GTK'), now it seems to be doing realtime plotting. > > import matplotlib as mpl > > import matplotlib.pyplot as plt > plt.ion() > import numpy as np > fig=plt.figure() > plt.axis([0,1000,0,1]) > > i=0 > x=list() > y=list() > > fig.canvas.show() > while i <1000: > temp_y=np.random.random() > x.append(i) > y.append(temp_y) > plt.scatter(i,temp_y) > i+=1 > plt.draw() > > > > On Mon, Mar 11, 2013 at 10:35 AM, David Hoese <dh...@gm...> wrote: > >> Oops forgot to change the subject line. >> >> On 3/11/13 9:34 AM, David Hoese wrote: >> >>> You likely need to "show()" the canvas. I usually do this by calling >>> "fig.canvas.show()" before the for loop. >>> Since you are using a Qt4 backend the canvas used by the figure is a >>> QWidget, the basic component of a Qt4 GUI. I don't know if there is a more >>> matplotlib specific way of doing this, but when dealing with a larger >>> system this is how I do it. >>> >>> I would also add a sleep ("from time import sleep") of a couple seconds >>> for testing to make sure you are getting through the entire for loop before >>> you can see it. >>> >>> Please CC in any replies, thanks. >>> >>> -Dave >>> >>> >>> On 3/11/13 8:58 AM, ndb...@gm... wrote: >>> >>>> I want to update a plot in real time. I did some goog search, and saw >>>> various >>>> answers. Trouble is, they aren't working. >>>> >>>> Here's a typical example: >>>> >>>> import matplotlib.pyplot as plt >>>> import numpy as np >>>> fig=plt.figure() >>>> plt.axis([0,1000,0,1]) >>>> >>>> i=0 >>>> x=list() >>>> y=list() >>>> >>>> while i <1000: >>>> temp_y=np.random.random() >>>> x.append(i) >>>> y.append(temp_y) >>>> plt.scatter(i,temp_y) >>>> i+=1 >>>> plt.draw() >>>> >>>> If I run this, it draws nothing. >>>> >>>> This is my matplotlibrc: >>>> backend : Qt4Agg >>>> mathtext.fontset: stix >>>> >>> >>> >> > > |
|
From: David H. <dh...@gm...> - 2013-03-11 17:55:22
|
Someone may have to correct me, but I think this has to do with the Qt4
event loop and it not being run properly. When you get into real time
plotting it can get kind of tricky. In your case (I got the same
results). I have made real-time PyQt4 GUIs before and have always used
separate QThreads and Qt signals/slots to update the plot. I've never
used GTK so I'm not sure why that worked vs Qt, I would think they would
use similar principles but matplotlib does some magic behind the scenes
sometimes. You can see different results if you comment out the while
loop and import the module into your python/ipython interpreter. After
doing this you'll see the figure pop up (you don't even need the
fig.canvas.show() for this part if interactive mode is on. I went one
step further and turned the while loop into a function:
def one_iter(i):
# Contents of while loop
Calling this in the interpreter shows the figure updating after each
call, but running in a loop (even with sleep) won't show any updates
until the loop is done. In my opinion you have a few choices that really
depend on your programming comfort level:
1. Don't make a real-time plot.
Do you really need a real-time plot that updates from some
external source?
2. Maybe you should look at the matplotlib animation functionality
(http://matplotlib.org/api/animation_api.html). I like this tutorial:
http://jakevdp.github.com/blog/2012/08/18/matplotlib-animation-tutorial/. This
won't get you a real-time GUI exactly, but it can help if what you're
doing isn't too complicated. It can also be nice for making videos of
plot animations.
3. If you need a GUI with multiple plots and you need for future feature
creep, I would research making PyQt4 GUIs, QThreads, Qt signals and
slots, and putting matplotlib figures into a PyQt4 GUI. This is complex
if you are not familiar with GUI programming and will take a while.
Sorry I couldn't be of more help, but it really depends on what exactly
you are doing. Mainly, what do you mean by real-time? Do you really
mean animation? Let me know what you come up with, I'm interested.
-Dave
P.S. Why use a while loop? You can do the same thing with:
for i in range(1000):
# Do stuff
On 3/11/13 10:34 AM, Neal Becker wrote:
> I added fig.canvas.show(). It still does nothing.
>
> If I add
> mpl.use ('GTK'), now it seems to be doing realtime plotting.
>
> import matplotlib as mpl
>
> import matplotlib.pyplot as plt
> plt.ion()
> import numpy as np
> fig=plt.figure()
> plt.axis([0,1000,0,1])
>
> i=0
> x=list()
> y=list()
>
> fig.canvas.show()
> while i <1000:
> temp_y=np.random.random()
> x.append(i)
> y.append(temp_y)
> plt.scatter(i,temp_y)
> i+=1
> plt.draw()
>
>
>
> On Mon, Mar 11, 2013 at 10:35 AM, David Hoese <dh...@gm...
> <mailto:dh...@gm...>> wrote:
>
> Oops forgot to change the subject line.
>
> On 3/11/13 9:34 AM, David Hoese wrote:
>
> You likely need to "show()" the canvas. I usually do this by
> calling "fig.canvas.show()" before the for loop.
> Since you are using a Qt4 backend the canvas used by the
> figure is a QWidget, the basic component of a Qt4 GUI. I don't
> know if there is a more matplotlib specific way of doing this,
> but when dealing with a larger system this is how I do it.
>
> I would also add a sleep ("from time import sleep") of a
> couple seconds for testing to make sure you are getting
> through the entire for loop before you can see it.
>
> Please CC in any replies, thanks.
>
> -Dave
>
>
> On 3/11/13 8:58 AM, ndb...@gm...
> <mailto:ndb...@gm...> wrote:
>
> I want to update a plot in real time. I did some goog
> search, and saw various
> answers. Trouble is, they aren't working.
>
> Here's a typical example:
>
> import matplotlib.pyplot as plt
> import numpy as np
> fig=plt.figure()
> plt.axis([0,1000,0,1])
>
> i=0
> x=list()
> y=list()
>
> while i <1000:
> temp_y=np.random.random()
> x.append(i)
> y.append(temp_y)
> plt.scatter(i,temp_y)
> i+=1
> plt.draw()
>
> If I run this, it draws nothing.
>
> This is my matplotlibrc:
> backend : Qt4Agg
> mathtext.fontset: stix
>
>
>
>
|
|
From: Neal B. <ndb...@gm...> - 2013-03-11 17:49:56
|
Doesn't matter, still doesn't rescale without calling ax.axis
On Mon, Mar 11, 2013 at 1:48 PM, Sterling Smith <sm...@fu...>wrote:
> Neal,
>
> You might try
> mpl.use('GTKAgg')
> as I have seen problems with lone GTK. Also you might change this in your
> .matplotlibrc file if possible.
>
> -Sterling
>
> On Mar 11, 2013, at 10:43AM, Neal Becker wrote:
>
> > According to other examples I see on the web, use of 'relim' and
> > 'autoscale_view' should result in rescaling and drawing new axes.
> Doesn't.
> > Unless I explicity call
> > ax.axis ([...])
> > I don't get any rescaling.
> >
> > Here's an example:
> >
> > import matplotlib as mpl
> > mpl.use ('GTK')
> > import matplotlib.pyplot as plt
> > plt.ion()
> > import numpy as np
> > fig=plt.figure()
> > ax = fig.add_subplot(111)
> > x_values = [0]
> > ax.axis ([0, 10, -1, 1])
> > y_values = [0]
> >
> > i=0
> > x=list()
> > y=list()
> >
> > while i <1000:
> > x.append (i)
> > y.append (2*i)
> > line, = plt.plot (x, y, 'x-')
> >
> > ## ax.axis ([min(x),max(x),min(y),max(y)])
> >
> > ax.relim()
> > # update ax.viewLim using the new dataLim
> > ax.autoscale_view()
> > plt.draw()
> > i+=1
> >
> >
> >
> >
> ------------------------------------------------------------------------------
> > Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester
> > Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the
> > endpoint security space. For insight on selecting the right partner to
> > tackle endpoint security challenges, access the full report.
> > http://p.sf.net/sfu/symantec-dev2dev
> > _______________________________________________
> > Matplotlib-users mailing list
> > Mat...@li...
> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
|
|
From: Sterling S. <sm...@fu...> - 2013-03-11 17:48:47
|
Neal,
You might try
mpl.use('GTKAgg')
as I have seen problems with lone GTK. Also you might change this in your .matplotlibrc file if possible.
-Sterling
On Mar 11, 2013, at 10:43AM, Neal Becker wrote:
> According to other examples I see on the web, use of 'relim' and
> 'autoscale_view' should result in rescaling and drawing new axes. Doesn't.
> Unless I explicity call
> ax.axis ([...])
> I don't get any rescaling.
>
> Here's an example:
>
> import matplotlib as mpl
> mpl.use ('GTK')
> import matplotlib.pyplot as plt
> plt.ion()
> import numpy as np
> fig=plt.figure()
> ax = fig.add_subplot(111)
> x_values = [0]
> ax.axis ([0, 10, -1, 1])
> y_values = [0]
>
> i=0
> x=list()
> y=list()
>
> while i <1000:
> x.append (i)
> y.append (2*i)
> line, = plt.plot (x, y, 'x-')
>
> ## ax.axis ([min(x),max(x),min(y),max(y)])
>
> ax.relim()
> # update ax.viewLim using the new dataLim
> ax.autoscale_view()
> plt.draw()
> i+=1
>
>
>
> ------------------------------------------------------------------------------
> Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester
> Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the
> endpoint security space. For insight on selecting the right partner to
> tackle endpoint security challenges, access the full report.
> http://p.sf.net/sfu/symantec-dev2dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
|
|
From: Neal B. <ndb...@gm...> - 2013-03-11 17:44:26
|
According to other examples I see on the web, use of 'relim' and
'autoscale_view' should result in rescaling and drawing new axes. Doesn't.
Unless I explicity call
ax.axis ([...])
I don't get any rescaling.
Here's an example:
import matplotlib as mpl
mpl.use ('GTK')
import matplotlib.pyplot as plt
plt.ion()
import numpy as np
fig=plt.figure()
ax = fig.add_subplot(111)
x_values = [0]
ax.axis ([0, 10, -1, 1])
y_values = [0]
i=0
x=list()
y=list()
while i <1000:
x.append (i)
y.append (2*i)
line, = plt.plot (x, y, 'x-')
## ax.axis ([min(x),max(x),min(y),max(y)])
ax.relim()
# update ax.viewLim using the new dataLim
ax.autoscale_view()
plt.draw()
i+=1
|
|
From: Neal B. <ndb...@gm...> - 2013-03-11 15:34:42
|
I added fig.canvas.show(). It still does nothing.
If I add
mpl.use ('GTK'), now it seems to be doing realtime plotting.
import matplotlib as mpl
import matplotlib.pyplot as plt
plt.ion()
import numpy as np
fig=plt.figure()
plt.axis([0,1000,0,1])
i=0
x=list()
y=list()
fig.canvas.show()
while i <1000:
temp_y=np.random.random()
x.append(i)
y.append(temp_y)
plt.scatter(i,temp_y)
i+=1
plt.draw()
On Mon, Mar 11, 2013 at 10:35 AM, David Hoese <dh...@gm...> wrote:
> Oops forgot to change the subject line.
>
> On 3/11/13 9:34 AM, David Hoese wrote:
>
>> You likely need to "show()" the canvas. I usually do this by calling
>> "fig.canvas.show()" before the for loop.
>> Since you are using a Qt4 backend the canvas used by the figure is a
>> QWidget, the basic component of a Qt4 GUI. I don't know if there is a more
>> matplotlib specific way of doing this, but when dealing with a larger
>> system this is how I do it.
>>
>> I would also add a sleep ("from time import sleep") of a couple seconds
>> for testing to make sure you are getting through the entire for loop before
>> you can see it.
>>
>> Please CC in any replies, thanks.
>>
>> -Dave
>>
>>
>> On 3/11/13 8:58 AM, ndb...@gm... wrote:
>>
>>> I want to update a plot in real time. I did some goog search, and saw
>>> various
>>> answers. Trouble is, they aren't working.
>>>
>>> Here's a typical example:
>>>
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> fig=plt.figure()
>>> plt.axis([0,1000,0,1])
>>>
>>> i=0
>>> x=list()
>>> y=list()
>>>
>>> while i <1000:
>>> temp_y=np.random.random()
>>> x.append(i)
>>> y.append(temp_y)
>>> plt.scatter(i,temp_y)
>>> i+=1
>>> plt.draw()
>>>
>>> If I run this, it draws nothing.
>>>
>>> This is my matplotlibrc:
>>> backend : Qt4Agg
>>> mathtext.fontset: stix
>>>
>>
>>
>
|
|
From: David H. <dh...@gm...> - 2013-03-11 14:35:22
|
Oops forgot to change the subject line.
On 3/11/13 9:34 AM, David Hoese wrote:
> You likely need to "show()" the canvas. I usually do this by calling
> "fig.canvas.show()" before the for loop.
> Since you are using a Qt4 backend the canvas used by the figure is a
> QWidget, the basic component of a Qt4 GUI. I don't know if there is a
> more matplotlib specific way of doing this, but when dealing with a
> larger system this is how I do it.
>
> I would also add a sleep ("from time import sleep") of a couple
> seconds for testing to make sure you are getting through the entire
> for loop before you can see it.
>
> Please CC in any replies, thanks.
>
> -Dave
>
> On 3/11/13 8:58 AM, ndb...@gm... wrote:
>> I want to update a plot in real time. I did some goog search, and
>> saw various
>> answers. Trouble is, they aren't working.
>>
>> Here's a typical example:
>>
>> import matplotlib.pyplot as plt
>> import numpy as np
>> fig=plt.figure()
>> plt.axis([0,1000,0,1])
>>
>> i=0
>> x=list()
>> y=list()
>>
>> while i <1000:
>> temp_y=np.random.random()
>> x.append(i)
>> y.append(temp_y)
>> plt.scatter(i,temp_y)
>> i+=1
>> plt.draw()
>>
>> If I run this, it draws nothing.
>>
>> This is my matplotlibrc:
>> backend : Qt4Agg
>> mathtext.fontset: stix
>
|
|
From: David H. <dh...@gm...> - 2013-03-11 14:34:20
|
You likely need to "show()" the canvas. I usually do this by calling
"fig.canvas.show()" before the for loop.
Since you are using a Qt4 backend the canvas used by the figure is a
QWidget, the basic component of a Qt4 GUI. I don't know if there is a
more matplotlib specific way of doing this, but when dealing with a
larger system this is how I do it.
I would also add a sleep ("from time import sleep") of a couple seconds
for testing to make sure you are getting through the entire for loop
before you can see it.
Please CC in any replies, thanks.
-Dave
On 3/11/13 8:58 AM, ndb...@gm... wrote:
> I want to update a plot in real time. I did some goog search, and saw various
> answers. Trouble is, they aren't working.
>
> Here's a typical example:
>
> import matplotlib.pyplot as plt
> import numpy as np
> fig=plt.figure()
> plt.axis([0,1000,0,1])
>
> i=0
> x=list()
> y=list()
>
> while i <1000:
> temp_y=np.random.random()
> x.append(i)
> y.append(temp_y)
> plt.scatter(i,temp_y)
> i+=1
> plt.draw()
>
> If I run this, it draws nothing.
>
> This is my matplotlibrc:
> backend : Qt4Agg
> mathtext.fontset: stix
|
|
From: Neal B. <ndb...@gm...> - 2013-03-11 13:58:29
|
mpl is 1.2.0 Fedora linux On Mon, Mar 11, 2013 at 9:57 AM, Neal Becker <ndb...@gm...> wrote: > Tried with/and without plt.ion(), no difference. Nothing is drawn. When > I kill it with C-c, briefly a window is flashed. > > import matplotlib as mpl > > import matplotlib.pyplot as plt > plt.ion() > import numpy as np > fig=plt.figure() > plt.axis([0,1000,0,1]) > > i=0 > x=list() > y=list() > > while i <1000: > temp_y=np.random.random() > x.append(i) > y.append(temp_y) > plt.scatter(i,temp_y) > i+=1 > plt.draw() > > > > On Mon, Mar 11, 2013 at 9:55 AM, Francesco Montesano < > fra...@gm...> wrote: > >> Dear Neal, >> >> 2013/3/11 Neal Becker <ndb...@gm...> >> >>> I want to update a plot in real time. I did some goog search, and saw >>> various >>> answers. Trouble is, they aren't working. >>> >>> Here's a typical example: >>> >>> import matplotlib.pyplot as plt >>> import numpy as np >>> fig=plt.figure() >>> plt.axis([0,1000,0,1]) >>> >>> i=0 >>> x=list() >>> y=list() >>> >>> while i <1000: >>> temp_y=np.random.random() >>> x.append(i) >>> y.append(temp_y) >>> plt.scatter(i,temp_y) >>> i+=1 >>> plt.draw() >>> >>> If I run this, it draws nothing. >>> >>> This is my matplotlibrc: >>> backend : Qt4Agg >>> mathtext.fontset: stix >>> >> >> do you use interactive mode? (plt.ion() before creating the figure) >> Francesco >> >> >> >>> >> >> >>> >>> >>> ------------------------------------------------------------------------------ >>> Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester >>> Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the >>> endpoint security space. For insight on selecting the right partner to >>> tackle endpoint security challenges, access the full report. >>> http://p.sf.net/sfu/symantec-dev2dev >>> _______________________________________________ >>> Matplotlib-users mailing list >>> Mat...@li... >>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >>> >> >> > |
|
From: Neal B. <ndb...@gm...> - 2013-03-11 13:57:53
|
Tried with/and without plt.ion(), no difference. Nothing is drawn. When I
kill it with C-c, briefly a window is flashed.
import matplotlib as mpl
import matplotlib.pyplot as plt
plt.ion()
import numpy as np
fig=plt.figure()
plt.axis([0,1000,0,1])
i=0
x=list()
y=list()
while i <1000:
temp_y=np.random.random()
x.append(i)
y.append(temp_y)
plt.scatter(i,temp_y)
i+=1
plt.draw()
On Mon, Mar 11, 2013 at 9:55 AM, Francesco Montesano <
fra...@gm...> wrote:
> Dear Neal,
>
> 2013/3/11 Neal Becker <ndb...@gm...>
>
>> I want to update a plot in real time. I did some goog search, and saw
>> various
>> answers. Trouble is, they aren't working.
>>
>> Here's a typical example:
>>
>> import matplotlib.pyplot as plt
>> import numpy as np
>> fig=plt.figure()
>> plt.axis([0,1000,0,1])
>>
>> i=0
>> x=list()
>> y=list()
>>
>> while i <1000:
>> temp_y=np.random.random()
>> x.append(i)
>> y.append(temp_y)
>> plt.scatter(i,temp_y)
>> i+=1
>> plt.draw()
>>
>> If I run this, it draws nothing.
>>
>> This is my matplotlibrc:
>> backend : Qt4Agg
>> mathtext.fontset: stix
>>
>
> do you use interactive mode? (plt.ion() before creating the figure)
> Francesco
>
>
>
>>
>
>
>>
>>
>> ------------------------------------------------------------------------------
>> Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester
>> Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the
>> endpoint security space. For insight on selecting the right partner to
>> tackle endpoint security challenges, access the full report.
>> http://p.sf.net/sfu/symantec-dev2dev
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
>
|
|
From: Francesco M. <fra...@gm...> - 2013-03-11 13:55:59
|
Dear Neal, 2013/3/11 Neal Becker <ndb...@gm...> > I want to update a plot in real time. I did some goog search, and saw > various > answers. Trouble is, they aren't working. > > Here's a typical example: > > import matplotlib.pyplot as plt > import numpy as np > fig=plt.figure() > plt.axis([0,1000,0,1]) > > i=0 > x=list() > y=list() > > while i <1000: > temp_y=np.random.random() > x.append(i) > y.append(temp_y) > plt.scatter(i,temp_y) > i+=1 > plt.draw() > > If I run this, it draws nothing. > > This is my matplotlibrc: > backend : Qt4Agg > mathtext.fontset: stix > do you use interactive mode? (plt.ion() before creating the figure) Francesco > > > > ------------------------------------------------------------------------------ > Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester > Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the > endpoint security space. For insight on selecting the right partner to > tackle endpoint security challenges, access the full report. > http://p.sf.net/sfu/symantec-dev2dev > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > |
|
From: Chao Y. <cha...@gm...> - 2013-03-11 13:43:23
|
Dear all,
I searched the internet but still get confused by how can I save a figure
with high dpi value to jpeg format.
I am using matplotlib 1.2.0 with ubuntu system.
In [14]: mat.__version__
Out[14]: '1.2.0'
I tried both setting the flag "savefig.dpi" flag in matplotlibrc as 300,
and use fig.savefig('temp.jpg',dpi=300) when saving the figure.
But when I checked the figure dpi with GIMP, it says 72.
Under Windows system, it also says the dpi is 72.
In the example above, the "figure.dpi" value is 80.
In [21]: mat.rcParams['figure.dpi']
Out[21]: 80
I tried to set the "figure.dpi" as 300, But then when I check the figure
with interactive window
(I use GTKAgg backend), the figure is too big (getting out of the screen)
to veiw. [But I think this
is fine as the figure size will be depend on dpi, No?]
My workflow is like I always make plot in the interactive mode,
then I adjust the figure size (by draging) or the vertical space and other
things.
Then I click the save button on the interative window or use
"fig = gcf(); fig.savefig" command to save when I feel comfortable with the
figure.
I never published yet and now is working on my first one. So I don't know
if this procedure is good or not.
but anyway, how can I save jpg figures with dpi >300 with the normal size I
see on the screen?
thanks for the help,
Chao
--
***********************************************************************************
Chao YUE
Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL)
UMR 1572 CEA-CNRS-UVSQ
Batiment 712 - Pe 119
91191 GIF Sur YVETTE Cedex
Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16
************************************************************************************
|
|
From: Neal B. <ndb...@gm...> - 2013-03-11 13:07:52
|
I want to update a plot in real time. I did some goog search, and saw various
answers. Trouble is, they aren't working.
Here's a typical example:
import matplotlib.pyplot as plt
import numpy as np
fig=plt.figure()
plt.axis([0,1000,0,1])
i=0
x=list()
y=list()
while i <1000:
temp_y=np.random.random()
x.append(i)
y.append(temp_y)
plt.scatter(i,temp_y)
i+=1
plt.draw()
If I run this, it draws nothing.
This is my matplotlibrc:
backend : Qt4Agg
mathtext.fontset: stix
|
|
From: Aditya G. <adi...@ya...> - 2013-03-10 15:24:08
|
Hi Ben, Thanks for the pointer to "spines". Much cleaner way to hide/play around with axes. I switched to using spines to hide right and top axes. However, the misalignment of ticks and axes remains (TkAgg backend). So I'll just have to switch to a different backend I suppose... -Aditya. >________________________________ > From: Benjamin Root <ben...@ou...> >To: Aditya Gilra <adi...@ya...> >Cc: "mat...@li..." <mat...@li...> >Sent: Friday, 1 March 2013 12:10 AM >Subject: Re: [Matplotlib-users] Line2D and ticks are misaligned in TkAgg backend > > > > > >On Thu, Feb 28, 2013 at 7:00 AM, Aditya Gilra <adi...@ya...> wrote: > >Hi, >> >> >>I need to set the frame off for my plots, so that I can have axes only on the sides I want, rather than on all four sides. >>I do it this way: >> >> >>from pylab import * >> >>fig = figure(figsize=(3,2),dpi=300,facecolor='w') >>ax = fig.add_subplot(111,frameon=False) >>ax.add_artist(Line2D((0, 0), (0, 1),color='k',linewidth=0.5)) >>ax.add_artist(Line2D((1, 1), (0, 1),color='k',linewidth=0.5)) >>ax.set_yticks([0,1]) >>ax.set_xticks([0,1]) >>show() >> >> > >Much easier way is to use "spines": http://matplotlib.org/examples/pylab_examples/spine_placement_demo.html > > >Unfortunately, now the ticks and axes-lines are misaligned, as seen in the screenshots attached. In the second screenshot, I've panned the plot, so the misalignment is even more visible. >> >> >>matplotlib.__version__ gives '1.1.1rc' >>matplotlib.get_backend() gives 'TkAgg' >> >> >>------- >> >> >>If I use 'WX' backend by adding these two line before the above code (before pylab import): >> >> >>import matplotlib >>matplotlib.use('WX') >> >> >>then the misalignment still appears to be there, but that is because the Line2Ds are clipped in their width, but the ticks are not. This is seen by panning the plot. >> >> >>I can set the clipping of the Line2Ds off by doing: >>l1 = ax.add_artist(Line2D((0, 0), (0, 1),color='k',linewidth=0.5)) >>l1.set_clip_on(False) >>l2 = ax.add_artist(Line2D((1, 1), (0, 1),color='k',linewidth=0.5)) >>l2.set_clip_on(False) >> >> >>So, WX backend is fine. >> >> >>Backend 'GTK' doesn't even have the above clipping problem. >> >> > >Now that is interesting and should be investigated further. > >Ben Root > > > > |
|
From: Sudheer J. <sud...@ya...> - 2013-03-09 07:33:32
|
Dear Users, Are there any body who use matplotlib on AIX5.3, I tried to make it on our IBN pwer 6 machine with AIX 5.3 on it and getting below errors any advice on this matter will be of great help. Apparently there is a library error, is there a way to look at errors more specifically during python setup.py install I exported export CC=xlc++_r and CXX=" " with best regards, Sudheer be attained by recompiling and specifying MAXMEM option with a value greater than 8192. 1500-030: (I) INFORMATION: Py::String::as_std_string() const: Additional optimization may be attained by recompiling and specifying MAXMEM option with a value greater than 8192. ld: 0711-317 ERROR: Undefined symbol: __dl__FPv ld: 0711-317 ERROR: Undefined symbol: __UnsupportedConditionalExpressionDestruction__FPvl ld: 0711-317 ERROR: Undefined symbol: ._Xlen__Q2_3std12_String_baseCFv ld: 0711-317 ERROR: Undefined symbol: .__ThrowV6 ld: 0711-317 ERROR: Undefined symbol: .__dl__FPv ld: 0711-317 ERROR: Undefined symbol: .__ct__Q2_3std7_LockitFi ld: 0711-317 ERROR: Undefined symbol: .clear__Q2_3std8ios_baseFib ld: 0711-317 ERROR: Undefined symbol: .__ReThrowV6 ld: 0711-317 ERROR: Undefined symbol: .__setUncaughtExceptionFlag__3stdFb ld: 0711-317 ERROR: Undefined symbol: .__CleanupCatchV6a ld: 0711-317 ERROR: Undefined symbol: .__dt__Q2_3std7_LockitFv ld: 0711-317 ERROR: Undefined symbol: .uncaught_exception__3stdFv ld: 0711-317 ERROR: Undefined symbol: .unexpected__3stdFv ld: 0711-317 ERROR: Undefined symbol: .terminate__3stdFv ld: 0711-317 ERROR: Undefined symbol: .__nw__FUl ld: 0711-317 ERROR: Undefined symbol: ._Xran__Q2_3std12_String_baseCFv ld: 0711-317 ERROR: Undefined symbol: .__vd__FPv ld: 0711-317 ERROR: Undefined symbol: __PureVirtualCalled ld: 0711-317 ERROR: Undefined symbol: .__CatchMatch ld: 0711-317 ERROR: Undefined symbol: .__vn__FUl ld: 0711-317 ERROR: Undefined symbol: .__DynamicPtrCast ld: 0711-317 ERROR: Undefined symbol: cerr__3std ld: 0711-317 ERROR: Undefined symbol: id__Q2_3std7num_putXTcTQ2_3std19ostreambuf_iteratorXTcTQ2_3std11char_traitsXTc___ ld: 0711-317 ERROR: Undefined symbol: _Id_cnt__Q3_3std6locale2id ld: 0711-317 ERROR: Undefined symbol: ._Getfacet__Q2_3std6localeCFUl ld: 0711-317 ERROR: Undefined symbol: id__Q2_3std5ctypeXTc_ ld: 0711-317 ERROR: Undefined symbol: ._Init__Q2_3std8ios_baseFv ld: 0711-317 ERROR: Undefined symbol: ._Addstd__Q2_3std8ios_baseFv ld: 0711-317 ERROR: Undefined symbol: ._Init__Q2_3std6localeFv ld: 0711-317 ERROR: Undefined symbol: .__dt__Q2_3std8ios_baseFv ld: 0711-317 ERROR: Undefined symbol: .__ct__Q2_3std8_LocinfoFPCci ld: 0711-317 ERROR: Undefined symbol: .__dt__Q2_3std8_LocinfoFv ld: 0711-317 ERROR: Undefined symbol: _Cltab__Q2_3std5ctypeXTc_ ld: 0711-317 ERROR: Undefined symbol: ._Getctype__FPCc ld: 0711-317 ERROR: Undefined symbol: ._Tolower ld: 0711-317 ERROR: Undefined symbol: ._Toupper ld: 0711-317 ERROR: Undefined symbol: _BADOFF__3std ld: 0711-317 ERROR: Undefined symbol: _Fpz__3std ld: 0711-317 ERROR: Undefined symbol: ._Nomemory__3stdFv ld: 0711-317 ERROR: Undefined symbol: id__Q2_3std8numpunctXTc_ ld: 0711-317 ERROR: Undefined symbol: ._Getnumpunct__FPCc ld: 0711-317 ERROR: Undefined symbol: ._GetCatName__FiPCc ld: 0711-345 Use the -bloadmap or -bnoquiet option to obtain more information. *************************************************************** Sudheer Joseph Indian National Centre for Ocean Information Services Ministry of Earth Sciences, Govt. of India POST BOX NO: 21, IDA Jeedeemetla P.O. Via Pragathi Nagar,Kukatpally, Hyderabad; Pin:5000 55 Tel:+91-40-23886047(O),Fax:+91-40-23895011(O), Tel:+91-40-23044600(R),Tel:+91-40-9440832534(Mobile) E-mail:sjo...@gm...;sud...@ya... Web- http://oppamthadathil.tripod.com *************************************************************** |
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From: Tejashri K. <tej...@gm...> - 2013-03-08 10:17:24
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On Fri, Mar 8, 2013 at 3:46 PM, Tejashri Kandolkar < tej...@gm...> wrote: > Thanks Christoph, thanks for the help. > > However I found the issue. > The issue is that somehow matplotlib_release variant linked to the debug > lib of libpng. > And so on a non-developer machine, which dosent have msvcr90d.dll (debug > crt), DLL Load fails. > > So now I have another question: > > I have built the static libs of freetype, libpng (and zlib which is > required by libpng) from source > And I mention the paths of these static libs in setupext.py (by modifying > "basedir") while building matplotlib. > > Now when matplotlib builds, and generates a _png.pyd, will it still need > the static libs to be present in the location where the _png.pyd is present? > What I understand is that it shouldn't since it is a static library and > should be built into the binary. > > Why I am asking this is because I am unable to build the libpng DLLs (for > some reason I dont know). > So I have to go forward with the static lib approach. > > Thanks, > Regards, > Tej. > > > On Thu, Mar 7, 2013 at 10:53 PM, Christoph Gohlke <cg...@uc...> wrote: > >> On 3/7/2013 8:39 AM, Christoph Gohlke wrote: >> > On 3/7/2013 6:00 AM, Tejashri Kandolkar wrote: >> >> Hi, >> >> >> >> I built matplotlib1.2.0 with python3.2 on Windows7 from source. >> >> I built the libpng and freetype libs and linked them statically to >> >> matplotlib. >> >> >> >> Everything works fine on my machine, I can run the matplotlib examples >> etc >> >> But on a new Win7 machine(with the exact same configuration as mine, >> >> except a few softwares), I get the following error when i try to import >> >> png module like this: >> >> >> >> import matplotlib._png >> >> >> >> ImportError: DLL load failed: The application has failed to start >> >> because its side-by-side configuration is incorrect. Please see the >> >> application event log or use the command-line sxstrace.exe tool for >> more >> >> detail. >> >> >> >> >> >> I used the dependency walker and found that pyd_ DLL was indeed having >> >> issues during load. >> >> >> >> What could be the reason. Surprisingly it works all fine on my machine. >> >> >> >> >> >> Regards, >> >> Tej >> >> >> > >> > Assuming this is 32 bit Python, install the Microsoft Visual C++ 2008 >> > Redistributable Package (x86) <from >> > http://www.microsoft.com/en-us/download/details.aspx?id=29> >> > >> >> Besides that, look for extra msvcp90.dll or msvcr90.dll files in PATH >> (for example MikteX is known for that) and resolve conflicts. >> >> Christoph >> >> >> ------------------------------------------------------------------------------ >> Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester >> Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the >> endpoint security space. For insight on selecting the right partner to >> tackle endpoint security challenges, access the full report. >> http://p.sf.net/sfu/symantec-dev2dev >> _______________________________________________ >> Matplotlib-users mailing list >> Mat...@li... >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >> > > |
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From: Nelle V. <nel...@gm...> - 2013-03-08 06:42:10
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On 8 March 2013 03:19, Brickle Macho <bri...@gm...> wrote: > On 8/03/13 8:37 AM, Damon McDougall wrote: > > Correct me if I'm wrong, but would a 2D quiver plot on top of a > > contour plot work? What spaces does the surface map to/from? If your > > surface can be expressed as a function f:R^2 -> R then it's equivalent > > to look at its level sets, rather than the 3D picture. You can then > > project the surface normals onto the plane and plot them with a 2D > > quiver plot. If you want to keep the z-component information, then > > you could colour the arrows according to the angle they make with the > > x-y plane. > > > > Does that make sense? > > My source is an image, so technically f:R^2 -> R. Specifically I am > using depth maps or (range image) what to visualise the > surfaces/normals. I was planing on plotting the image as surface > (hadn't work out how yet) and overlay the normal vectors. I think a 2D > quiver plot on top of a contour plot may provide a useful > visualisation/interpretation of the process. > You always have the solution to install mayavi, a 3D plotting library. The API resemble maptlotlib's and it supports 3D quiver plots. Cheers, N > > Thanks for the idea. > > Brickle. > -- > > > > > > > > I put the original feature request in, and I think it would be useful, > > but often I still find it easier to process two dimensional > > information. > > > > N.B. The above will only work for *functions* f:R^2 -> R. To > > clarify, a sphere cannot be expressed this way, because the resulting > > mapping would be multivalued. Using this method, two distinct surface > > normals may have the same colour. > > > > Hope that makes sense. > > > > Best wishes, > > Damon > > > >> Brickle. > >> -- > >> > >> > >> On 8/03/13 5:43 AM, Benjamin Root wrote: > >> > >> > >> > >> On Thu, Mar 7, 2013 at 4:25 PM, Eric Firing <ef...@ha...> wrote: > >>> On 2013/03/07 9:19 AM, Benjamin Root wrote: > >>>> > >>>> On Thu, Mar 7, 2013 at 2:14 PM, Brickle Macho <bri...@gm... > >>>> <mailto:bri...@gm...>> wrote: > >>>> > >>>> I have a list of surface normals I would like to plot. Is there > a > >>>> way > >>>> to plot a 3D vectors in matplotlib similar to how quiver plots 2D > >>>> vectors? > >>>> > >>>> > >>>> Not at this time, but that would make a great feature request! I > think > >>>> the current roadblock to such a function is a bug with converting 2d > >>>> arrow objects into 3d arrows. > >>> Quiver uses a PolyCollection, and I see that there is a > Poly3DCollection. > >>> > >>> Eric > >>> > >>>> Ben Root > >>> > >> Took a bit of digging, but I knew I remembered this question before: > >> > >> > http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CDMQFjAA&url=http%3A%2F%2Fmatplotlib.1069221.n5.nabble.com%2F2D-Quiver-in-Axes3D-td27944.html&ei=Pwk5UfGdLufv0QHuroD4BA&usg=AFQjCNEqlWv2vY5l2IPcje-g6B0U21wDNw&bvm=bv.43287494,d.dmQ > >> > >> And the feature request is here: > >> https://github.com/matplotlib/matplotlib/issues/1026 > >> > >> In the thread I pointed out a bug that I encountered. I really hope I > get > >> some free time soon so that I can work on the various feature requests > in > >> mplot3d. > >> > >> Cheers! > >> Ben Root > >> > >> > >> > >> > ------------------------------------------------------------------------------ > >> Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester > >> Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the > >> endpoint security space. For insight on selecting the right partner to > >> tackle endpoint security challenges, access the full report. > >> http://p.sf.net/sfu/symantec-dev2dev > >> > >> > >> > >> _______________________________________________ > >> Matplotlib-users mailing list > >> Mat...@li... > >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users > >> > >> > >> > >> > ------------------------------------------------------------------------------ > >> Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester > >> Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the > >> endpoint security space. For insight on selecting the right partner to > >> tackle endpoint security challenges, access the full report. > >> http://p.sf.net/sfu/symantec-dev2dev > >> _______________________________________________ > >> Matplotlib-users mailing list > >> Mat...@li... > >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users > >> > > > > > > > > ------------------------------------------------------------------------------ > Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester > Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the > endpoint security space. For insight on selecting the right partner to > tackle endpoint security challenges, access the full report. > http://p.sf.net/sfu/symantec-dev2dev > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > |
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From: Brickle M. <bri...@gm...> - 2013-03-08 02:19:21
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On 8/03/13 8:37 AM, Damon McDougall wrote: > Correct me if I'm wrong, but would a 2D quiver plot on top of a > contour plot work? What spaces does the surface map to/from? If your > surface can be expressed as a function f:R^2 -> R then it's equivalent > to look at its level sets, rather than the 3D picture. You can then > project the surface normals onto the plane and plot them with a 2D > quiver plot. If you want to keep the z-component information, then > you could colour the arrows according to the angle they make with the > x-y plane. > > Does that make sense? My source is an image, so technically f:R^2 -> R. Specifically I am using depth maps or (range image) what to visualise the surfaces/normals. I was planing on plotting the image as surface (hadn't work out how yet) and overlay the normal vectors. I think a 2D quiver plot on top of a contour plot may provide a useful visualisation/interpretation of the process. Thanks for the idea. Brickle. -- > > I put the original feature request in, and I think it would be useful, > but often I still find it easier to process two dimensional > information. > > N.B. The above will only work for *functions* f:R^2 -> R. To > clarify, a sphere cannot be expressed this way, because the resulting > mapping would be multivalued. Using this method, two distinct surface > normals may have the same colour. > > Hope that makes sense. > > Best wishes, > Damon > >> Brickle. >> -- >> >> >> On 8/03/13 5:43 AM, Benjamin Root wrote: >> >> >> >> On Thu, Mar 7, 2013 at 4:25 PM, Eric Firing <ef...@ha...> wrote: >>> On 2013/03/07 9:19 AM, Benjamin Root wrote: >>>> >>>> On Thu, Mar 7, 2013 at 2:14 PM, Brickle Macho <bri...@gm... >>>> <mailto:bri...@gm...>> wrote: >>>> >>>> I have a list of surface normals I would like to plot. Is there a >>>> way >>>> to plot a 3D vectors in matplotlib similar to how quiver plots 2D >>>> vectors? >>>> >>>> >>>> Not at this time, but that would make a great feature request! I think >>>> the current roadblock to such a function is a bug with converting 2d >>>> arrow objects into 3d arrows. >>> Quiver uses a PolyCollection, and I see that there is a Poly3DCollection. >>> >>> Eric >>> >>>> Ben Root >>> >> Took a bit of digging, but I knew I remembered this question before: >> >> http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CDMQFjAA&url=http%3A%2F%2Fmatplotlib.1069221.n5.nabble.com%2F2D-Quiver-in-Axes3D-td27944.html&ei=Pwk5UfGdLufv0QHuroD4BA&usg=AFQjCNEqlWv2vY5l2IPcje-g6B0U21wDNw&bvm=bv.43287494,d.dmQ >> >> And the feature request is here: >> https://github.com/matplotlib/matplotlib/issues/1026 >> >> In the thread I pointed out a bug that I encountered. I really hope I get >> some free time soon so that I can work on the various feature requests in >> mplot3d. >> >> Cheers! >> Ben Root >> >> >> >> ------------------------------------------------------------------------------ >> Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester >> Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the >> endpoint security space. For insight on selecting the right partner to >> tackle endpoint security challenges, access the full report. >> http://p.sf.net/sfu/symantec-dev2dev >> >> >> >> _______________________________________________ >> Matplotlib-users mailing list >> Mat...@li... >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >> >> >> >> ------------------------------------------------------------------------------ >> Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester >> Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the >> endpoint security space. For insight on selecting the right partner to >> tackle endpoint security challenges, access the full report. >> http://p.sf.net/sfu/symantec-dev2dev >> _______________________________________________ >> Matplotlib-users mailing list >> Mat...@li... >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >> > > |