Re: [Matplotlib-users] Get contourf image as array
Thanks Ben. I'll take a look through the archive. On 10/16/14, 9:43 AM, Benjamin Root wrote: What you are looking for is called rasterization. Matplotlib does this deep within the codebase and is not accessible (believe me, I tried). However, there have been other discussions in this mailing list about how to use GDAL to rasterize a set of polygons (represented as paths), including some links to stack-overflow questions. It isn't a complete end-to-end solution, but the pieces are there. Cheers! Ben Root On Wed, Oct 15, 2014 at 2:09 PM, David Hoese dho...@gmail.com mailto:dho...@gmail.com wrote: For the first question, if I save the figure (as a PNG I'm guessing, unless you can save into a more array-like format), I'd have to make sure that there were no labels or ticks and that the axes fit the whole figure. I'd also have to get the dpi and size information correct, but I suppose it would be possible that way. I was hoping for something a little easier and in-memory. This might be the simplest answer the more I think about it. If I'm starting from the paths, I'd still have to write them to the grid array. I thought maybe the backend could do that and I magically get the image. I'll look in to using savefig and getting the data out. -Dave On 10/15/14, 12:42 PM, Joy merwin monteiro wrote: pardon the query if it seems dumb, but why don't you do a savefig() after plotting the data and then convert it to any format you like? alternatively, contour() and contourf() both create paths that can be accessed: cf = contourf(.) output = cf.collections.pop() paths = output.get_paths()[i] # for the various contours the x,y coordinates can then be accessed as xcoords = paths.vertices.transpose()[0] ycoords = paths.vertices.transpose()[1] you can then do whatever you wish with them. Joy On Wed, Oct 15, 2014 at 9:11 PM, David Hoese dho...@gmail.com mailto:dho...@gmail.com mailto:dho...@gmail.com mailto:dho...@gmail.com wrote: I've been searching and reading through source code and google searches to see if this is possible, but no luck so far. I'm basically trying to map some data using Basemap, use contourf to map it to an image, and then put that image in a geotiff (or other format) for use in other GIS programs. I have other tools for remapping data and creating geotiffs, but the contour image looks better. All I would need to get this to work would be an array representing the image inside the axes of a contourf plot. I found a lot of geotiff - Basemap png results, but I would like the reverse. Since the plots are made using paths/patches I'm guessing I would have to have a backend render the image and then extract the image somehow. Does anyone have some tips or tricks to do something like this? Or am I thinking about this completely wrong? Thanks for any help and if you could CC me in any replies it would be much appreciated. -Dave -- Comprehensive Server Monitoring with Site24x7. Monitor 10 servers for $9/Month. Get alerted through email, SMS, voice calls or mobile push notifications. Take corrective actions from your mobile device. http://p.sf.net/sfu/Zoho ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net mailto:Matplotlib-users@lists.sourceforge.net mailto:Matplotlib-users@lists.sourceforge.net mailto:Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- The best ruler, when he finishes his tasks and completes his affairs, the people say “It all happened naturally” - Te Tao Ch'ing -- Comprehensive Server Monitoring with Site24x7. Monitor 10 servers for $9/Month. Get alerted through email, SMS, voice calls or mobile push notifications. Take corrective actions from your mobile device. http://p.sf.net/sfu/Zoho ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net mailto:Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
[Matplotlib-users] Get contourf image as array
I've been searching and reading through source code and google searches to see if this is possible, but no luck so far. I'm basically trying to map some data using Basemap, use contourf to map it to an image, and then put that image in a geotiff (or other format) for use in other GIS programs. I have other tools for remapping data and creating geotiffs, but the contour image looks better. All I would need to get this to work would be an array representing the image inside the axes of a contourf plot. I found a lot of geotiff - Basemap png results, but I would like the reverse. Since the plots are made using paths/patches I'm guessing I would have to have a backend render the image and then extract the image somehow. Does anyone have some tips or tricks to do something like this? Or am I thinking about this completely wrong? Thanks for any help and if you could CC me in any replies it would be much appreciated. -Dave -- Comprehensive Server Monitoring with Site24x7. Monitor 10 servers for $9/Month. Get alerted through email, SMS, voice calls or mobile push notifications. Take corrective actions from your mobile device. http://p.sf.net/sfu/Zoho ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Get contourf image as array
For the first question, if I save the figure (as a PNG I'm guessing, unless you can save into a more array-like format), I'd have to make sure that there were no labels or ticks and that the axes fit the whole figure. I'd also have to get the dpi and size information correct, but I suppose it would be possible that way. I was hoping for something a little easier and in-memory. This might be the simplest answer the more I think about it. If I'm starting from the paths, I'd still have to write them to the grid array. I thought maybe the backend could do that and I magically get the image. I'll look in to using savefig and getting the data out. -Dave On 10/15/14, 12:42 PM, Joy merwin monteiro wrote: pardon the query if it seems dumb, but why don't you do a savefig() after plotting the data and then convert it to any format you like? alternatively, contour() and contourf() both create paths that can be accessed: cf = contourf(.) output = cf.collections.pop() paths = output.get_paths()[i] # for the various contours the x,y coordinates can then be accessed as xcoords = paths.vertices.transpose()[0] ycoords = paths.vertices.transpose()[1] you can then do whatever you wish with them. Joy On Wed, Oct 15, 2014 at 9:11 PM, David Hoese dho...@gmail.com mailto:dho...@gmail.com wrote: I've been searching and reading through source code and google searches to see if this is possible, but no luck so far. I'm basically trying to map some data using Basemap, use contourf to map it to an image, and then put that image in a geotiff (or other format) for use in other GIS programs. I have other tools for remapping data and creating geotiffs, but the contour image looks better. All I would need to get this to work would be an array representing the image inside the axes of a contourf plot. I found a lot of geotiff - Basemap png results, but I would like the reverse. Since the plots are made using paths/patches I'm guessing I would have to have a backend render the image and then extract the image somehow. Does anyone have some tips or tricks to do something like this? Or am I thinking about this completely wrong? Thanks for any help and if you could CC me in any replies it would be much appreciated. -Dave -- Comprehensive Server Monitoring with Site24x7. Monitor 10 servers for $9/Month. Get alerted through email, SMS, voice calls or mobile push notifications. Take corrective actions from your mobile device. http://p.sf.net/sfu/Zoho ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net mailto:Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- The best ruler, when he finishes his tasks and completes his affairs, the people say “It all happened naturally” - Te Tao Ch'ing -- Comprehensive Server Monitoring with Site24x7. Monitor 10 servers for $9/Month. Get alerted through email, SMS, voice calls or mobile push notifications. Take corrective actions from your mobile device. http://p.sf.net/sfu/Zoho ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Matplotlib-users Digest, Vol 82, Issue 16
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, ndbeck...@gmail.com 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 -- 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 Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] real time plotting
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, ndbeck...@gmail.com 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 -- 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 Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] real time plotting
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 dho...@gmail.com
mailto:dho...@gmail.com 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, ndbeck...@gmail.com
mailto:ndbeck...@gmail.com 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
--
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
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] real time plotting
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 dho...@gmail.com
mailto:dho...@gmail.com 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 dho...@gmail.com
mailto:dho...@gmail.com 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
[Matplotlib-users] importing basemap then shapely causes error
I've asked this question on GIS stack exchange site, but thought it would be good to post here too. The SE question is here: http://gis.stackexchange.com/questions/50394/importing-matplotlib-basemap-and-shapely I have a python script that uses matplotlib's basemap and another part that uses shapely to do an intersection of 2 polygons. If basemap is imported before shapely and I run the intersection I get this exception: | intersect_poly= grid_poly.intersection(data_poly) File /sw/lib/python2.7/site-packages/shapely/geometry/base.py, line334, in intersection return geom_factory(self.impl['intersection'](self, other)) File /sw/lib/python2.7/site-packages/shapely/topology.py, line53, in __call__ This operation produced a null geometry. Reason: unknown) shapely.geos.TopologicalError: This operation produced a null geometry. Reason: unknown| If I import shapely first, everything works fine. I would assume this is because of some funkiness in the way they are accessing the GEOS library. I've checked that in both situations the same library file is loaded in shapely (print shapely.geos._lgeos). Does anyone have an idea as to why this is happening and if there is a right way of doing this? Does this happen for anyone else? In the mean time I can just make sure to import shapely first (not sure if that affects basemap yet). Otherwise maybe I'll skim through the basemap source. I'm using OSX(10.7) with a fink install that has libgeos3.3.3-shlibs, libgeos3.3.1-shlibs, libgeos3.3.1, libgeos3.3.0-shlibs, libgeos3.3.0, and shapely-py27 (1.2.16-1) installed. The current basemap version in fink is 1.0.2. And here's a simple test script that reproduces the problem (flip the imports and it works): |from mpl_toolkitsimport basemap from shapelyimport geometry g_ring= [(-88.462425, 26.992203), (-57.847187, 26.992203), (-57.847187, 17.599869), (-88.462425, 17.599869), (-88.462425, 26.992203)] grid_g_ring= [(-123.044, 59.8440001), (-49.3849998, 57.2890001), (-65.0909994, 14.3350001), (-113.133, 16.369), (-123.044, 59.8440001)] data_poly= geometry.Polygon(g_ring) grid_poly= geometry.Polygon(grid_g_ring) print grid_poly.intersection(data_poly).area| Thanks again. Please CC me in any replies. -Dave -- Free Next-Gen Firewall Hardware Offer Buy your Sophos next-gen firewall before the end March 2013 and get the hardware for free! Learn more. http://p.sf.net/sfu/sophos-d2d-feb___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] matplotlib 1.1 TypeError: a float is required problem
I experienced the same problem on the macosx backend, switched to Qt4Agg and no problems. import matplotlib matplotlib.use(Qt4Agg) -Dave On 1/6/12 10:08 AM, md...@stsci.edu wrote: I suspect this bug is specific to the macosx backend. Can you switch to another backend and confirm it doesn't happen there? (I can't reproduce it on Linux). Mike -- Ridiculously easy VDI. With Citrix VDI-in-a-Box, you don't need a complex infrastructure or vast IT resources to deliver seamless, secure access to virtual desktops. With this all-in-one solution, easily deploy virtual desktops for less than the cost of PCs and save 60% on VDI infrastructure costs. Try it free! http://p.sf.net/sfu/Citrix-VDIinabox ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] matplotlib 1.1 TypeError: a float is required problem
Hi Ken, You're getting that error because you probably don't have Qt4 installed on your Mac (I do). I'm not sure what backends come with matplotlib and will work for you (maybe someone here knows). You can use any of the following: GTK GTKAgg GTKCairo CocoaAgg FltkAgg MacOSX QtAgg Qt4Agg TkAgg WX WXAgg Agg Cairo GDK PS PDF SVG Template Like Qt4, some of those may need to be installed. I also have Gtk installed (never used it before) and GTKAgg works for me, but not GTK. It's also important to know that not all of those backends are interactive (they don't all show a window) and the figure must be saved to a file. Also make sure that the 2 lines I provided need to be BEFORE any other matplotlib/pyplot imports. Hope you find something that works for you, at least until the macosx bug is fixed. I'm not an expert, sorry. -Dave On 1/6/12 10:35 AM, Mingkui Li wrote: Hi, Dave, I tried the two lines of code you posted, but when I ran the example I mentioned above I got such error: ImportError: No module named sip Seems I can't import any other libs from matplotlib after matplotlib.use(Qt4Agg) I'm kind of a newbie, sorry. Ken On Sat, Jan 7, 2012 at 12:22 AM, David Hoese dho...@gmail.com mailto:dho...@gmail.com wrote: I experienced the same problem on the macosx backend, switched to Qt4Agg and no problems. import matplotlib matplotlib.use(Qt4Agg) -Dave On 1/6/12 10:08 AM, md...@stsci.edu mailto:md...@stsci.edu wrote: I suspect this bug is specific to the macosx backend. Can you switch to another backend and confirm it doesn't happen there? (I can't reproduce it on Linux). Mike -- Ridiculously easy VDI. With Citrix VDI-in-a-Box, you don't need a complex infrastructure or vast IT resources to deliver seamless, secure access to virtual desktops. With this all-in-one solution, easily deploy virtual desktops for less than the cost of PCs and save 60% on VDI infrastructure costs. Try it free! http://p.sf.net/sfu/Citrix-VDIinabox ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net mailto:Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- Mingkui Li -- Ridiculously easy VDI. With Citrix VDI-in-a-Box, you don't need a complex infrastructure or vast IT resources to deliver seamless, secure access to virtual desktops. With this all-in-one solution, easily deploy virtual desktops for less than the cost of PCs and save 60% on VDI infrastructure costs. Try it free! http://p.sf.net/sfu/Citrix-VDIinabox___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Matplotlib-users Digest, Vol 67, Issue 23
Eric, I installed mpl from git (git clone git://github.com/matplotlib/matplotlib.git, unless I was suppose to use one of the branches) and same problem. I looked at my code again and thought there should be a canvas.draw() before calling c.copy_from_bbox(a.bbox), but still the same problem. However, I did have it work the first time I added c.draw() and used the git mpl, and by work I mean that everything stayed visible on the figure. When people start coming in to my work I'll ask them to run my sample code and see what happens. It almost seems like mpl is handling the window activation event funny, is there an easy way to print out the callbacks being used by a mpl figure? For now, I will subclass QApplication, and implement notify() to print out events as they come in, but still...this is just weird. Thanks. -Dave On 12/14/11 10:30 PM, Eric Firing wrote: David, It works for me on linux with mpl from git. I haven't tried to figure it out, but it is conceivable that the problem you are seeing was fixed with this: commit b624546ae60dc5878e75a32f41a160d383548b8f Author: Eric Firingefir...@hawaii.edu Date: Tue Oct 18 08:06:21 2011 -1000 backend_qt4agg: draw() immediately calls FigureCanvasAgg.draw() This is the latest in a series of modifications to the Qt4Agg drawing strategy going back several years. It simplifies the code and should solve the problem introduced in 6938b0025; that is, delaying the Agg draw operation until the paintEvent breaks code expecting that draw operation to have occurred immediately. The problem was reported here: http://sourceforge.net/mailarchive/message.php?msg_id=28245744 Eric -- 10 Tips for Better Server Consolidation Server virtualization is being driven by many needs. But none more important than the need to reduce IT complexity while improving strategic productivity. Learn More! http://www.accelacomm.com/jaw/sdnl/114/51507609/ ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Blitting with qt4
Oops forgot to change subject. On 12/15/11 10:02 AM, David Hoese wrote: Eric, I installed mpl from git (git clone git://github.com/matplotlib/matplotlib.git, unless I was suppose to use one of the branches) and same problem. I looked at my code again and thought there should be a canvas.draw() before calling c.copy_from_bbox(a.bbox), but still the same problem. However, I did have it work the first time I added c.draw() and used the git mpl, and by work I mean that everything stayed visible on the figure. When people start coming in to my work I'll ask them to run my sample code and see what happens. It almost seems like mpl is handling the window activation event funny, is there an easy way to print out the callbacks being used by a mpl figure? For now, I will subclass QApplication, and implement notify() to print out events as they come in, but still...this is just weird. Thanks. -Dave On 12/14/11 10:30 PM, Eric Firing wrote: David, It works for me on linux with mpl from git. I haven't tried to figure it out, but it is conceivable that the problem you are seeing was fixed with this: commit b624546ae60dc5878e75a32f41a160d383548b8f Author: Eric Firingefir...@hawaii.edu Date: Tue Oct 18 08:06:21 2011 -1000 backend_qt4agg: draw() immediately calls FigureCanvasAgg.draw() This is the latest in a series of modifications to the Qt4Agg drawing strategy going back several years. It simplifies the code and should solve the problem introduced in 6938b0025; that is, delaying the Agg draw operation until the paintEvent breaks code expecting that draw operation to have occurred immediately. The problem was reported here: http://sourceforge.net/mailarchive/message.php?msg_id=28245744 Eric -- 10 Tips for Better Server Consolidation Server virtualization is being driven by many needs. But none more important than the need to reduce IT complexity while improving strategic productivity. Learn More! http://www.accelacomm.com/jaw/sdnl/114/51507609/ ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] Blitting with qt4
Eric, Good news I think I got it to work. So using the same code I sent you originally, I applied the following changes: 1. Install matplotlib from git (this did fix things that I wasn't noticing) 2. Add c.draw() before c.copy_from_bbox 3. Copy f.bbox instead of a.bbox (I think this makes sense since I want it to hold on to the title,ticks, and labels, a.bbox is only the content inside the axis rectangle) 4. Restore f_bbox, blit f.bbox. ...and it seems to work. The git version of mpl did fix this, although restoring just the a.bbox was only keeping the axis rectangle so it made it look like even worse of a bug. Using the new version I noticed this and then started using f.bbox which seems to work the way I want it. Now, my final question is: Is this actually doing what I want performance-wise. When I blit just f.bbox, is it really only repainting the updated line or is it redrawing most of the figure? If you need a copy of the new version of my test code let me know. Thanks for any more clarity/help you can give. -Dave P.S. Is there a book or tutorial or website where I can learn more about how the rendering/painting of stuff like this works. For example, if I could better understand why your bug fix was needed. On 12/15/11 10:04 AM, David Hoese wrote: Oops forgot to change subject. On 12/15/11 10:02 AM, David Hoese wrote: Eric, I installed mpl from git (git clone git://github.com/matplotlib/matplotlib.git, unless I was suppose to use one of the branches) and same problem. I looked at my code again and thought there should be a canvas.draw() before calling c.copy_from_bbox(a.bbox), but still the same problem. However, I did have it work the first time I added c.draw() and used the git mpl, and by work I mean that everything stayed visible on the figure. When people start coming in to my work I'll ask them to run my sample code and see what happens. It almost seems like mpl is handling the window activation event funny, is there an easy way to print out the callbacks being used by a mpl figure? For now, I will subclass QApplication, and implement notify() to print out events as they come in, but still...this is just weird. Thanks. -Dave On 12/14/11 10:30 PM, Eric Firing wrote: David, It works for me on linux with mpl from git. I haven't tried to figure it out, but it is conceivable that the problem you are seeing was fixed with this: commit b624546ae60dc5878e75a32f41a160d383548b8f Author: Eric Firingefir...@hawaii.edu Date: Tue Oct 18 08:06:21 2011 -1000 backend_qt4agg: draw() immediately calls FigureCanvasAgg.draw() This is the latest in a series of modifications to the Qt4Agg drawing strategy going back several years. It simplifies the code and should solve the problem introduced in 6938b0025; that is, delaying the Agg draw operation until the paintEvent breaks code expecting that draw operation to have occurred immediately. The problem was reported here: http://sourceforge.net/mailarchive/message.php?msg_id=28245744 Eric -- 10 Tips for Better Server Consolidation Server virtualization is being driven by many needs. But none more important than the need to reduce IT complexity while improving strategic productivity. Learn More! http://www.accelacomm.com/jaw/sdnl/114/51507609/ ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] [ploting data] Live data
I'm not sure how experienced you are with multithreaded programs, but here is some sample code (I mentioned it can get complicated). I suggest you research Qt4 QThreads and also Qt4 Signals and slots to better understand the code below. It is a working sample so you should be able to run it in a terminal and notice that the GUI is responsive and that you have messages being printed out on the terminal. The code I provided below is more complicated than you may need for a proof-of-concept kind of program, but if you will be communicating with physical devices I suggest something like this. I am by no means and expert, but I have been doing something similar to what you are doing. I also suggest maybe separating the device communication into another module/class, especially if others are going to (re)use your code. Good Luck, Dave P.S. There are a lot of Qt4/PyQt4 threading examples online, but not all of them correct. What I posted below is what I have found to be considered correct by most people. # ### Sample Code ### # import time from PyQt4 import QtGui,QtCore class MyWindow(QtGui.QWidget): def __init__(self): QtGui.QWidget.__init__(self) # Sample GUI elements to test responsiveness the_choices = [item]*20 self.choices = QtGui.QComboBox() self.choices.addItems(the_choices) self.layout = QtGui.QVBoxLayout(self) self.layout.addWidget(self.choices) self.setLayout(self.layout) def handle_new_data(self): # This is where you could redraw any matplotlib plots # Maybe send data through the signal/slot connection print Updating data class MyInstrument(QtCore.QObject): signal_new_data = QtCore.pyqtSignal(name=signal_new_data) signal_closing = QtCore.pyqtSignal(name=signal_closing) def run(self): self._timer = QtCore.QTimer() self._timer.timeout.connect(self._run) self._timer.start(0) def _run(self): time.sleep(1) print Running the instrument function time.sleep(1) self.signal_new_data.emit() def close(self): print Closing instrument thread self._timer.stop() # Redundant timer stop self._timer.timeout.disconnect() self.signal_closing.emit() if __name__ == __main__: app = QtGui.QApplication([ ]) w = MyWindow() w.show() instrument = MyInstrument() instrument_thread = QtCore.QThread() instrument.moveToThread(instrument_thread) instrument_thread.started.connect(instrument.run) instrument.signal_new_data.connect(w.handle_new_data) # Make the close function run in the main thread so you can interrupt the sleeps app.lastWindowClosed.connect(instrument.close, QtCore.Qt.DirectConnection) # You could also call quit manually after exec_() returns instrument.signal_closing.connect(instrument_thread.quit) instrument_thread.start() app.exec_() #instrument_thread.quit() print Waiting for instrument thread... instrument_thread.wait() print SUCCESS ## ### End of Sample Code ### ## On 12/14/11 3:51 AM, Fabien Lafont wrote: I prefer to use the multi-thread method beacause it's easier for me and my colaborators to have the entire acquisition process at the same place. Until then I use a simple one but I hope to use a more complex one in few weeks ( put different voltages on different devices then measure many voltages or current). If I use the domino technique (call the next operation by the end of the previous) it can be complex to read and to edit. Thank you very much anyway! How can I write a multi-thread process? I've just tried to add qApp.processEvents() at the end of my while loop but it doesn't change anything... Thanks again, Fabien 2011/12/13 David Hoesedho...@gmail.com: Yeah I didn't think about suggesting that, but I think it might get complicated. I think he would have to start a one shot timer to call a function to set the voltage. Then that function would also start another one shot timer to call another function that would read from the sample. That function then would start a one shot timer to call the first function again. This way he can be sure that things are called in order and that timing is consistent, just in case the GUI gets complicated or something makes the event loop slow down. He could also use multiple threads. Whatever works for Fabien I guess. -Dave On 12/13/11 1:00 PM, matplotlib-users-requ...@lists.sourceforge.net wrote: From: Drain, Theodore R (343P)theodore.r.dr...@jpl.nasa.gov Subject: Re: [Matplotlib-users] [ploting data] Live data Perhaps I'm missing something, but why not use QTimer? You can't really every call sleep in a single threaded gui (for reasons you've encountered). If you need to poll something, create
Re: [Matplotlib-users] [ploting data] Live data
I don't know what you mean by ApplicationWindow, is that a class or just a name for the main GUI window. I also don't really know what calling the graphical application means, but I'm sure the book can help you more than I can. Again, good luck. -Dave On 12/14/11 10:17 AM, Fabien Lafont wrote: Thanks David, I start to read the Mark summerfield' book about PyQt programming. In fact I realized I don't need multi-threading because I can remove the Timer and just need to call the graphical application from the while loop. How can I call the ApplicationWindow class from my while loop? I'll try to read a bit more about PyQt to understand how it works :) thanks again! Fabien 2011/12/14 David Hoesedho...@gmail.com: I'm not sure how experienced you are with multithreaded programs, but here is some sample code (I mentioned it can get complicated). I suggest you research Qt4 QThreads and also Qt4 Signals and slots to better understand the code below. It is a working sample so you should be able to run it in a terminal and notice that the GUI is responsive and that you have messages being printed out on the terminal. The code I provided below is more complicated than you may need for a proof-of-concept kind of program, but if you will be communicating with physical devices I suggest something like this. I am by no means and expert, but I have been doing something similar to what you are doing. I also suggest maybe separating the device communication into another module/class, especially if others are going to (re)use your code. Good Luck, Dave P.S. There are a lot of Qt4/PyQt4 threading examples online, but not all of them correct. What I posted below is what I have found to be considered correct by most people. # ### Sample Code ### # import time from PyQt4 import QtGui,QtCore class MyWindow(QtGui.QWidget): def __init__(self): QtGui.QWidget.__init__(self) # Sample GUI elements to test responsiveness the_choices = [item]*20 self.choices = QtGui.QComboBox() self.choices.addItems(the_choices) self.layout = QtGui.QVBoxLayout(self) self.layout.addWidget(self.choices) self.setLayout(self.layout) def handle_new_data(self): # This is where you could redraw any matplotlib plots # Maybe send data through the signal/slot connection print Updating data class MyInstrument(QtCore.QObject): signal_new_data = QtCore.pyqtSignal(name=signal_new_data) signal_closing = QtCore.pyqtSignal(name=signal_closing) def run(self): self._timer = QtCore.QTimer() self._timer.timeout.connect(self._run) self._timer.start(0) def _run(self): time.sleep(1) print Running the instrument function time.sleep(1) self.signal_new_data.emit() def close(self): print Closing instrument thread self._timer.stop() # Redundant timer stop self._timer.timeout.disconnect() self.signal_closing.emit() if __name__ == __main__: app = QtGui.QApplication([ ]) w = MyWindow() w.show() instrument = MyInstrument() instrument_thread = QtCore.QThread() instrument.moveToThread(instrument_thread) instrument_thread.started.connect(instrument.run) instrument.signal_new_data.connect(w.handle_new_data) # Make the close function run in the main thread so you can interrupt the sleeps app.lastWindowClosed.connect(instrument.close, QtCore.Qt.DirectConnection) # You could also call quit manually after exec_() returns instrument.signal_closing.connect(instrument_thread.quit) instrument_thread.start() app.exec_() #instrument_thread.quit() print Waiting for instrument thread... instrument_thread.wait() print SUCCESS ## ### End of Sample Code ### ## On 12/14/11 3:51 AM, Fabien Lafont wrote: I prefer to use the multi-thread method beacause it's easier for me and my colaborators to have the entire acquisition process at the same place. Until then I use a simple one but I hope to use a more complex one in few weeks ( put different voltages on different devices then measure many voltages or current). If I use the domino technique (call the next operation by the end of the previous) it can be complex to read and to edit. Thank you very much anyway! How can I write a multi-thread process? I've just tried to add qApp.processEvents() at the end of my while loop but it doesn't change anything... Thanks again, Fabien 2011/12/13 David Hoesedho...@gmail.com: Yeah I didn't think about suggesting that, but I think it might get complicated. I think he would have to start a one shot timer to call a function to set the voltage. Then that function would also start another one shot timer to call another function that
[Matplotlib-users] Blitting with qt4
Does anyone know if using the blit method from FigureCanvasQTAgg is not fully supported? I'm having a problem where I'm animating a plot using the blit method and I click on/activate the window the background of the figure disappears (axes and line stay visible). I'm not sure if this is just me (Mac OS X Lion, Qt4 4.8.6, Matplotlib 1.1.0), but the following code reproduces the error: ### from PyQt4 import QtGui,QtCore from matplotlib.figure import Figure from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg from time import sleep app = QtGui.QApplication([ ]) f = Figure() c = FigureCanvasQTAgg(f) a = f.add_subplot(111) a.set_title(A Title) bbox = c.copy_from_bbox(a.bbox) lines = a.plot([1,2,3],[1,2,3]) c.draw() c.show() wait = raw_input(Press a key to continue...) def update(i): a.lines[0].set_ydata([i,1,i]) print a.bbox.bounds c.restore_region(bbox, bbox=a.bbox) a.draw_artist(a.lines[0]) c.blit(a.bbox) sleep(1) app.processEvents() for i in range(20): update(i) wait = raw_input(Press a key to continue...) ### To see the problem, run the code, watch the plot to make sure its updating properly, then click on the window to put it in focus/activate it. I'm hoping that I'm just doing something stupid and its an easy fix. It seems to work until I click on the window (in Mac OS X Lion Terminal the window is opened in the background and the Terminal window stays in focus). Thanks for any help. -Dave -- Cloud Computing - Latest Buzzword or a Glimpse of the Future? This paper surveys cloud computing today: What are the benefits? Why are businesses embracing it? What are its payoffs and pitfalls? http://www.accelacomm.com/jaw/sdnl/114/51425149/ ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] [ploting data] Live data
Fabien,
The GUI not being responsive might be my fault, I've never used a timer
of 0 and processEvents(). I think what might be happening is that when
you call processEvents, the timer of 0 calls your principal function
again, which calls processEvents again, and so on. Try a timer of 2
again, that should stop the timer from being constantly triggered.
Later today, once I get to work, I'll run some tests of my own and
figure out if that's really the problem. Email me if you make any progress.
-Dave
On 12/13/2011 2:30 AM, Fabien Lafont wrote:
Hey David,
I'm doing this program to control an experiment, so I want to put the
voltage on the sample, then wait two seconds to be sure there is no
current fluctuations then measure the curent with multimeters and
finally plot the datas. That's why I need the sleep... In fact I
wanted to use in parallel the timer to refresh the graph and a while
loop to extract the datas.
If I use startTimer(0) it works but the GUI is almost unresponsive.
I'm trying to use qApp.processEvents() but up to now I don't manage to
see the window appears...
Thanks again for your help
Fabien
2011/12/12 David Hoesedho...@gmail.com:
Hey Fabien,
So you made your principal function run on a timer every 2 seconds? And by
lag do you mean that the GUI is unresponsive? I'm still not seeing when
the loop stops, but what you can do is set the timer at a 0 interval so it
will call the principal function as fast as it can (but with no loop). The
problem with this is that you have those 2 sleep calls in the function. I'm
not sure why you have the sleeps, but if you need them you have two choices:
1. Make you GUI multi-threaded and you could emit a Qt signal from the data
thread when the GUI thread needs to update the GUI. Yes this could get
complicated, but if the sleeps are required then its probably the best way.
2. (From what I've been told, the Qt experts don't approve this) You can use
app.processEvents() in your loop (after each sleep maybe) and this will
pause your function and tell the main event loop to process any queued
events (like GUI actions/events) which will make your GUI more responsive.
If that doesn't make sense let me know.
-Dave
On 12/12/11 9:16 AM, Fabien Lafont wrote:
Hi David! Sorry about the delay I was abroad and without any way to
connect to the internet.
Thank you very much. I've tried to put the principal inside the
timerEvent. It work but it lags. In fact I've set the interval of the
Timer to 2 seconds because the principal loop takes roughly 2seconds
but it's not very accurate...
Is there a way to do the principal loop, show it on the screen, then
redo the loop?
Thanks again!
Fabien
2011/12/5 David Hoesedho...@gmail.com:
If I'm understanding your question correctly and reading your code
correctly, you're asking why the timer method of doing things works, but
the
principal() while loop method does not.
I had a couple solutions that involved the main event loop, but I just
noticed 2 main things that are probably wrong with your code:
1. You are calling 'principal' from inside __init__ so you never actually
return from __init__ which means that you never call window.show() and
therefore never call qApp.exec_(). If you really want to use the
'principal' method you would have to connect it to a one shot timer anyway
to have it run after you have started the application ('qApp.exec_()'). I
think the recommended way would be to use the timer the way you did in your
latest email.
2. At least in the way my email client reads your original code, your
calls to the matplotlib drawing functions aren't inside the while loop and
the while loop never ends...although this doesn't matter if you don't fix
#1
above.
Hope that made sense.
-Dave
On 12/5/11 1:44 PM, matplotlib-users-requ...@lists.sourceforge.net wrote:
Message: 3
Date: Mon, 5 Dec 2011 15:46:02 +0100
From: Fabien Lafontlafont.fab...@gmail.com
Subject: Re: [Matplotlib-users] [ploting data] Live data
Cc:matplotlib-users@lists.sourceforge.net
Message-ID:
CAC9H_cjrgQBE6e6+jzZHyfYHonTeAg0XwU7c_2G-hu=s+z7...@mail.gmail.com
Content-Type: text/plain; charset=ISO-8859-1
Thx all for your remarks,
I can't understand why this code works (when I use the timer method):
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Re: [Matplotlib-users] [ploting data] Live data
Yeah I didn't think about suggesting that, but I think it might get complicated. I think he would have to start a one shot timer to call a function to set the voltage. Then that function would also start another one shot timer to call another function that would read from the sample. That function then would start a one shot timer to call the first function again. This way he can be sure that things are called in order and that timing is consistent, just in case the GUI gets complicated or something makes the event loop slow down. He could also use multiple threads. Whatever works for Fabien I guess. -Dave On 12/13/11 1:00 PM, matplotlib-users-requ...@lists.sourceforge.net wrote: From: Drain, Theodore R (343P)theodore.r.dr...@jpl.nasa.gov Subject: Re: [Matplotlib-users] [ploting data] Live data Perhaps I'm missing something, but why not use QTimer? You can't really every call sleep in a single threaded gui (for reasons you've encountered). If you need to poll something, create a QTimer for 2 seconds and have it call a measurement function to update the data. You shouldn't need any processEvents calls or sleep. -- Systems Optimization Self Assessment Improve efficiency and utilization of IT resources. Drive out cost and improve service delivery. Take 5 minutes to use this Systems Optimization Self Assessment. http://www.accelacomm.com/jaw/sdnl/114/51450054/ ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] [ploting data] Live data
Hey Fabien,
So you made your principal function run on a timer every 2 seconds? And
by lag do you mean that the GUI is unresponsive? I'm still not seeing
when the loop stops, but what you can do is set the timer at a 0
interval so it will call the principal function as fast as it can (but
with no loop). The problem with this is that you have those 2 sleep
calls in the function. I'm not sure why you have the sleeps, but if you
need them you have two choices:
1. Make you GUI multi-threaded and you could emit a Qt signal from the
data thread when the GUI thread needs to update the GUI. Yes this could
get complicated, but if the sleeps are required then its probably the
best way.
2. (From what I've been told, the Qt experts don't approve this) You can
use app.processEvents() in your loop (after each sleep maybe) and this
will pause your function and tell the main event loop to process any
queued events (like GUI actions/events) which will make your GUI more
responsive.
If that doesn't make sense let me know.
-Dave
On 12/12/11 9:16 AM, Fabien Lafont wrote:
Hi David! Sorry about the delay I was abroad and without any way to
connect to the internet.
Thank you very much. I've tried to put the principal inside the
timerEvent. It work but it lags. In fact I've set the interval of the
Timer to 2 seconds because the principal loop takes roughly 2seconds
but it's not very accurate...
Is there a way to do the principal loop, show it on the screen, then
redo the loop?
Thanks again!
Fabien
2011/12/5 David Hoesedho...@gmail.com:
If I'm understanding your question correctly and reading your code
correctly, you're asking why the timer method of doing things works, but the
principal() while loop method does not.
I had a couple solutions that involved the main event loop, but I just
noticed 2 main things that are probably wrong with your code:
1. You are calling 'principal' from inside __init__ so you never actually
return from __init__ which means that you never call window.show() and
therefore never call qApp.exec_(). If you really want to use the
'principal' method you would have to connect it to a one shot timer anyway
to have it run after you have started the application ('qApp.exec_()'). I
think the recommended way would be to use the timer the way you did in your
latest email.
2. At least in the way my email client reads your original code, your calls
to the matplotlib drawing functions aren't inside the while loop and the
while loop never ends...although this doesn't matter if you don't fix #1
above.
Hope that made sense.
-Dave
On 12/5/11 1:44 PM, matplotlib-users-requ...@lists.sourceforge.net wrote:
Message: 3
Date: Mon, 5 Dec 2011 15:46:02 +0100
From: Fabien Lafontlafont.fab...@gmail.com
Subject: Re: [Matplotlib-users] [ploting data] Live data
Cc:matplotlib-users@lists.sourceforge.net
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CAC9H_cjrgQBE6e6+jzZHyfYHonTeAg0XwU7c_2G-hu=s+z7...@mail.gmail.com
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Thx all for your remarks,
I can't understand why this code works (when I use the timer method):
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Re: [Matplotlib-users] [ploting data] Live data
If I'm understanding your question correctly and reading your code correctly,
you're asking why the timer method of doing things works, but the principal()
while loop method does not.
I had a couple solutions that involved the main event loop, but I just noticed
2 main things that are probably wrong with your code:
1. You are calling 'principal' from inside __init__ so you never actually
return from __init__ which means that you never call window.show() and
therefore never call qApp.exec_(). If you really want to use the 'principal'
method you would have to connect it to a one shot timer anyway to have it run
after you have started the application ('qApp.exec_()'). I think the
recommended way would be to use the timer the way you did in your latest email.
2. At least in the way my email client reads your original code, your calls to
the matplotlib drawing functions aren't inside the while loop and the while
loop never ends...although this doesn't matter if you don't fix #1 above.
Hope that made sense.
-Dave
On 12/5/11 1:44 PM, matplotlib-users-requ...@lists.sourceforge.net wrote:
Message: 3
Date: Mon, 5 Dec 2011 15:46:02 +0100
From: Fabien Lafontlafont.fab...@gmail.com
Subject: Re: [Matplotlib-users] [ploting data] Live data
Cc:matplotlib-users@lists.sourceforge.net
Message-ID:
CAC9H_cjrgQBE6e6+jzZHyfYHonTeAg0XwU7c_2G-hu=s+z7...@mail.gmail.com
Content-Type: text/plain; charset=ISO-8859-1
Thx all for your remarks,
I can't understand why this code works (when I use the timer method):
--
All the data continuously generated in your IT infrastructure
contains a definitive record of customers, application performance,
security threats, fraudulent activity, and more. Splunk takes this
data and makes sense of it. IT sense. And common sense.
http://p.sf.net/sfu/splunk-novd2d
___
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Matplotlib-users@lists.sourceforge.net
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Re: [Matplotlib-users] [ploting data] Live data
I think you forget to set the layout on your central widget. self.main_widget.setLayout(vbl) # in your case -Dave On 12/4/2011 9:57 AM, matplotlib-users-requ...@lists.sourceforge.net wrote: 2011/12/2 Daniel Hyamsdhy...@gmail.com: I don't have PyQt installed, so I couldn't test the code, but don't you want to be using extend and not append, if you are returning a list from your two get_info() functions? On Fri, Dec 2, 2011 at 8:13 AM, Fabien Lafontlafont.fab...@gmail.com wrote: Hello everyone, I'm trying to plot live data extracting from remote devices (here it's simulated by get_info1 and 2 the result is always 0.8 or 0.9 I can't understand why it doesnt plot the graph at the end of the while loop. Does somebody has an idea? -- All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-novd2d ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] how would you do this (animated bargraph) (Neal Becker)
Neal, I do something similar to this where data that I'm plotting in a 2D line plot comes from a UDP socket and some memory mapped files. To accomplish the live updating I have a mix of your #2 and #3. I have a main GUI thread that displays the plots, then I have a second thread that gets data from a python generator and signals the GUI thread when that new data has arrived. Inside the generator is where I have socket communications and select calls. Hope this helps. -Dave On 9/30/11 9:10 AM, matplotlib-users-requ...@lists.sourceforge.net wrote: Message: 4 Date: Fri, 30 Sep 2011 07:37:49 -0400 From: Neal Beckerndbeck...@gmail.com Subject: [Matplotlib-users] how would you do this (animated bargraph) To:matplotlib-users@lists.sourceforge.net Message-ID:j649me$ug4$1...@dough.gmane.org Content-Type: text/plain; charset=ISO-8859-1 I just put together an animated bargraph to show results from a realtime process. I used this as an example: http://matplotlib.sourceforge.net/examples/animation/animation_blit_qt4.html The tricky part for me was that in the original design, there was a realtime process running. I have to write some information to my hardware (at a rate of about 1/360ms). To do this, I have a kernel driver that uses 'read' to tell the user space when an interrupt has occurred, which is when the user space should write new information to the hardware. So I don't know how or if this could be hooked into qt event processing. Just for a quick-and-dirty demo, I just removed the realtime processing from the user-space and put it in the kernel driver, so now my bargraph display can simply update on a periodic timer, and the userspace code has no realtime requirement. But this is just a kludge. So I wonder how other's would solve this? I'm thinking it would be either: 1) multi-process 2) multi-thread 3) 1 process, but somehow hook my realtime events into qt's event loop. For #3, my device driver has a filedescriptor, that could use select to detect the interrupt (rather than blocking read call). #1 and #2 seem complicated. -- All of the data generated in your IT infrastructure is seriously valuable. Why? It contains a definitive record of application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-d2dcopy2 ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
