matplotlib-users Mailing List for matplotlib

Hi,
I have a question related to use of pyproj.
I am trying to calculate the azimuth orientation of vectors in a general coordinate system, defined by a proj4 string.
My approach is to calculate the azimuth angle of the y-axis of the given projection, and add this to the angle relative to the given coordinate system.
The illustration code below uses pyproj.Geod to calculate azimuth angle along the projection y-axis, but the output (bottom) does not make sense; the azimuth angle is found to be nearly the same for points at very different latitudes. This is the same for other projections such as e.g.:
proj4 = '+proj=lcc +lon_0=15 +lat_0=63 +lat_1=63 +lat_2=63 +R=6.371e+06 +units=m +no_defs'
However, using simply proj4 = '+proj=stere', I get results as expected. But as soon as I add '+lat_0' to the proj4-string, output is clearly wrong.
Does anyone have a clue what is going on here?
Best regards from Knut-Frode
--------------------------------------
import numpy as np
from mpl_toolkits.basemap import pyproj
proj4 = '+proj=stere +lat_0=90 +lon_0=70 +lat_ts=60 +units=m +a=6.371e+06 +e=0 +no_defs'
p = pyproj.Proj(proj4)
# Create three points for testing
lon_1 = np.array([30., 30., 30.])
lat_1 = np.array([60., 80., 89.])
x_1, y_1 = p(lon_1, lat_1) # Calculate projection (x,y) coordinates
lon_2, lat_2 = p(x_1, y_1 + 1000.0, inverse=True, errchk=True) # Find (lon,lat) of a point 1000 m away along y-axis
# Calculate azimuth from p1 to p2 (i.e. along projection y-axis)
g = pyproj.Geod(ellps='WGS84') 
az = g.inv(lon_1, lat_1, lon_2, lat_2, radians=False)
# Output: [-40.04826805 -40.00599836 -40.00008458] - does not make sense
print az[0]
 		 	 		 

Oops, Julian. Didn't mean to take this off list. Hopefully an updated
matplotlib will help. (1.2.1 is pretty old. Numerous bug fixes, features,
and improvements have been added.)
Ryan
On Feb 22, 2015 1:23 PM, "Julian Irwin" <jul...@gm...> wrote:
> Ryan,
>
> My version is 1.2.1 so I guess that answers that! Thanks, I didn't think
> to check this.
>
> Julian
>
>
> On Sun, Feb 22, 2015 at 10:53 AM, Ryan Nelson <rne...@gm...>
> wrote:
>
>> Julian,
>>
>> What version of matplotlib are you using? The attached rc file works fine
>> for me with MPLv1.4.2.
>>
>> Ryan
>>
>> On Sat, Feb 21, 2015 at 11:56 PM, Julian Irwin <jul...@gm...>
>> wrote:
>>
>>> In the Ticker API docs <http://matplotlib.org/api/ticker_api.html> the
>>> following is listed as a valid rc parameter:
>>>
>>> axes.formatter.useoffset=False
>>>
>>> Is there a way to put this in my matplotlibrc?
>>>
>>> I have tried the obvious choice:
>>>
>>> axes.formatter.useoffset : False
>>>
>>> but that give the error
>>>
>>> Bad key "axes.formatter.useoffset"
>>>
>>> upon importing matplotlib.
>>>
>>> Thanks,
>>>
>>> Julian
>>>
>>>
>>> ------------------------------------------------------------------------------
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>>>
>>>
>>
>

Eric,
I took your suggestion and it worked. Thank you.
To all the others who responded so quickly, thank you as well.
P.S. - I'm still wondering what other differences between vers. 1.1.1rc and
1.4.3 I'll run into. I'll worry about those when I run into them.
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On 2015年02月21日 5:32 PM, Starfighter wrote:
> Per request my question is being resubmitted here.
>
> I'm attempting to generate contour and a color map in Matplotlib ver. 1.4.3
> on a MacBook Pro under Mac OS X ver. 10.10.2 in Python 2.7.3 with the
> Anaconda environment.
>
> A zip file has been attached to this note. Two sub-directories,
> mathplotlib_1.4.3 and mathplotlib_1.1.1rc are included.
>
> mathplotlib_1.4.3 contains the python script that generates the contour and
> color map plots, jpeg files showing the resultant plots and the input data.
>
> mathplotlib_1.1.1rc contains the screen snaps (jpeg files) showing the
> correct contour and color map plots generated by the same python script and
> input data under Linux2 using Python 2.7.3 and Matplotlib 1.1.1rc.
>
> The questions I have include:
> 1. What are the differences between Matplotlib vers. 1.1.1rc and 1.4.3?
Well, you just found one of them. You should be able to find most 
substantial changes in http://matplotlib.org/users/whats_new.html.
> 2. What is going on where?
The plt.axis('scaled') call is freezing the xlim and ylim at values 
resulting from a call to "nonsingular", which is handling the fact that 
when you call axis(), nothing has been plotted and there is no 
information about what you want the limits to be. In addition, 'scaled' 
is one of the axis options that turns off autoscaling. It has always 
been intended to be called *after* plotting with autoscaling on, or 
otherwise setting the xlim and ylim to the desired values. I don't know 
why it worked for you in 1.1.1rc; I think it was long before this that 
it had the behavior of turning off autoscaling, but I haven't checked.
> 3. How can I fix this problem?
Put the "plt.axis('scaled')" line after your pcolor or plot line.
As a side note, in general pcolormesh will yield the same result as 
pcolor, but *much* faster, so it is recommended in most cases.
Eric
>
>
> Please advise.
>
>
>
>
> mathplotlib_issues.zip
> <http://matplotlib.1069221.n5.nabble.com/file/n45004/mathplotlib_issues.zip>
>
>
>
> --
> View this message in context: http://matplotlib.1069221.n5.nabble.com/Problems-with-pyplot-and-cm-in-Matplotlib-ver-1-4-3-tp45002p45004.html
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>
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In the Ticker API docs <http://matplotlib.org/api/ticker_api.html> the
following is listed as a valid rc parameter:
 axes.formatter.useoffset=False
Is there a way to put this in my matplotlibrc?
I have tried the obvious choice:
 axes.formatter.useoffset : False
but that give the error
 Bad key "axes.formatter.useoffset"
upon importing matplotlib.
Thanks,
Julian

This posting contains:
 1. The python script file used to input the data and produce the contour
and color map plots
 2. The input data
 3. JPG files containing screen snaps of the actual contour and color map
plots
Hope this helps.
solution.txt
<http://matplotlib.1069221.n5.nabble.com/file/n45006/solution.txt> 
plot_solution.py
<http://matplotlib.1069221.n5.nabble.com/file/n45006/plot_solution.py> 
contour.jpg
<http://matplotlib.1069221.n5.nabble.com/file/n45006/contour.jpg> 
pcolor.jpg <http://matplotlib.1069221.n5.nabble.com/file/n45006/pcolor.jpg> 
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Hey Starfighter, 
I want to help, but I also don't like unzipping files from strangers. Can you make a simple script that generates some fake with numoy and the handful of matplotib commands you need to make the figure. 
-p
—
Sent from Mailbox
On Sat, Feb 21, 2015 at 7:34 PM, Starfighter <sd...@sp...>
wrote:
> Per request my question is being resubmitted here.
> I'm attempting to generate contour and a color map in Matplotlib ver. 1.4.3
> on a MacBook Pro under Mac OS X ver. 10.10.2 in Python 2.7.3 with the
> Anaconda environment. 
> A zip file has been attached to this note. Two sub-directories,
> mathplotlib_1.4.3 and mathplotlib_1.1.1rc are included.
> mathplotlib_1.4.3 contains the python script that generates the contour and
> color map plots, jpeg files showing the resultant plots and the input data. 
> mathplotlib_1.1.1rc contains the screen snaps (jpeg files) showing the
> correct contour and color map plots generated by the same python script and
> input data under Linux2 using Python 2.7.3 and Matplotlib 1.1.1rc.
> The questions I have include:
> 1. What are the differences between Matplotlib vers. 1.1.1rc and 1.4.3?
> 2. What is going on where?
> 3. How can I fix this problem?
> Please advise.
> mathplotlib_issues.zip
> <http://matplotlib.1069221.n5.nabble.com/file/n45004/mathplotlib_issues.zip> 
> --
> View this message in context: http://matplotlib.1069221.n5.nabble.com/Problems-with-pyplot-and-cm-in-Matplotlib-ver-1-4-3-tp45002p45004.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
> ------------------------------------------------------------------------------
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> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users 

Per request my question is being resubmitted here.
I'm attempting to generate contour and a color map in Matplotlib ver. 1.4.3
on a MacBook Pro under Mac OS X ver. 10.10.2 in Python 2.7.3 with the
Anaconda environment. 
A zip file has been attached to this note. Two sub-directories,
mathplotlib_1.4.3 and mathplotlib_1.1.1rc are included.
mathplotlib_1.4.3 contains the python script that generates the contour and
color map plots, jpeg files showing the resultant plots and the input data. 
mathplotlib_1.1.1rc contains the screen snaps (jpeg files) showing the
correct contour and color map plots generated by the same python script and
input data under Linux2 using Python 2.7.3 and Matplotlib 1.1.1rc.
The questions I have include:
 1. What are the differences between Matplotlib vers. 1.1.1rc and 1.4.3?
 2. What is going on where?
 3. How can I fix this problem?
Please advise.
mathplotlib_issues.zip
<http://matplotlib.1069221.n5.nabble.com/file/n45004/mathplotlib_issues.zip> 
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Can you re-send this with that error message formatted a bit better (It is
really hard to make any sense of it all squashed into one line like that).
>From what I can make it out looks like it is mostly warnings, not errors.
Does it correctly save the figure? Can you show us the two outputs?
v1.1.1 is from Jun, 2012, there are over 5k new commits across 301 files
between the two versions (see
https://github.com/matplotlib/matplotlib/compare/v1.1.1...v1.4.3 but it
chokes and only will show you 250 commits)
Can you put together a minimal working example (which does not rely on any
external files)? That will really help the list pin down exactly what is
wrong and how to fix it.
Tom
On Sat Feb 21 2015 at 9:04:47 PM Starfighter <sd...@sp...> wrote:
> I'm attempting to generate contour and a color map in Matplotlib ver.
> 1.4.3 on a MacBook Pro under Mac OS X ver. 10.10.2 in Python 2.7.3 with the
> Anaconda environment. Now the messages from Matplotlib I get are:
> users-MacBook-Pro:lecture1 user$ python plot_solution.py Saved pseudocolor
> plot as pcolor.png
> /Users/user/anaconda/lib/python2.7/site-packages/matplotlib/text.py:52:
> UnicodeWarning: Unicode equal comparison failed to convert both arguments
> to Unicode - interpreting them as being unequal if rotation in
> ('horizontal', None):
> /Users/user/anaconda/lib/python2.7/site-packages/matplotlib/text.py:54:
> UnicodeWarning: Unicode equal comparison failed to convert both arguments
> to Unicode - interpreting them as being unequal elif rotation ==
> 'vertical': Saved contour plot as contour.png users-MacBook-Pro:lecture1
> user$ The python script is attached to this note. Now I've observed that
> the same python script and input data generated the correct contour and
> color map under Linux2 using Python 2.7.3 and Matplotlib 1.1.1rc. The
> questions I have include: 1. What are the differences between Matplotlib
> vers. 1.1.1rc and 1.4.3? 2. What is going on where? 3. How can I fix this
> problem? Please advise. plot_solution.py
> <http://matplotlib.1069221.n5.nabble.com/file/n45002/plot_solution.py>
> ------------------------------
> View this message in context: Problems with pyplot and cm in Matplotlib
> ver. 1.4.3
> <http://matplotlib.1069221.n5.nabble.com/Problems-with-pyplot-and-cm-in-Matplotlib-ver-1-4-3-tp45002.html>
> Sent from the matplotlib - users mailing list archive
> <http://matplotlib.1069221.n5.nabble.com/matplotlib-users-f3.html> at
> Nabble.com.
> ------------------------------------------------------------
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>

I'm attempting to generate contour and a color map in Matplotlib ver. 1.4.3
on a MacBook Pro under Mac OS X ver. 10.10.2 in Python 2.7.3 with the
Anaconda environment. Now the messages from Matplotlib I get
are:users-MacBook-Pro:lecture1 user$ python plot_solution.pySaved
pseudocolor plot as
pcolor.png/Users/user/anaconda/lib/python2.7/site-packages/matplotlib/text.py:52:
UnicodeWarning: Unicode equal comparison failed to convert both arguments to
Unicode - interpreting them as being unequal if rotation in ('horizontal',
None):/Users/user/anaconda/lib/python2.7/site-packages/matplotlib/text.py:54:
UnicodeWarning: Unicode equal comparison failed to convert both arguments to
Unicode - interpreting them as being unequal elif rotation ==
'vertical':Saved contour plot as contour.pngusers-MacBook-Pro:lecture1 user$
The python script is attached to this note. Now I've observed that the same
python script and input data generated the correct contour and color map
under Linux2 using Python 2.7.3 and Matplotlib 1.1.1rc.The questions I have
include: 1. What are the differences between Matplotlib vers. 1.1.1rc
and 1.4.3? 2. What is going on where? 3. How can I fix this
problem?Please advise. plot_solution.py
<http://matplotlib.1069221.n5.nabble.com/file/n45002/plot_solution.py> 
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Peter,
You’re welcome.
While I appreciate that you are trying to cut down on unnecessary emails (as per emailcharter.org - interesting read), it is appropriate to include the list in your responses, especially one indicating that a solution has been found, so that others on the list stop thinking about how they could help, and so that a person reading the archived list messages can feel confident that the suggestions were worthwhile. :-) NNTR
-Sterling
On Feb 20, 2015, at 3:20PM, Peter Rowat <pe...@pe...> wrote:
> Thank you both for your help, my problem is solved. You both had similar suggestions, and now I have a slightly better understanding of matplotlib.
> 
> Peter
> Save our in-boxes! http://emailcharter.org 
> 
> 
> 
>> On Feb 20, 2015, at 12:48 AM, Fabrice Silva <si...@lm...> wrote:
>> 
>> Le jeudi 19 février 2015 à 23:10 -0800, Peter Rowat a écrit :
>>> I apologize for asking such a trivial question, but I’ve spent a long time trying to fix this:
>>> 
>>> I have a large 2D array that displays as an image, with a colorbar on the side.
>>> I also display 2 curves on top of the image. i.e. in same axes.
>>> The following code does it:
>>> 
>>> fig,ax = plt.subplots()
>>> cax = ax.imshow(bighistT, extent=myextent, cmap = cm.coolwarm, aspect = myaspect,\
>>> interpolation='nearest')
>>> ax.set_title("Dummy title")
>>> # Add colorbar
>>> cbar = fig.colorbar(cax)
>>> ax.set_ylabel('mV')
>>> 
>>> ax.plot(emtrate, emrate, '.r') #curve 1
>>> ax.plot(tt, rate*50 - 25.0, '-k', linewidth=3) #curve 2
>>> 
>>> plt.show()
>>> ========
>>> IN FACT,
>>> I want the curves in separate axes, below the image while the colorbar remains immediately to the right
>>> of the image.
>>> 
>>> I've tried many minor variations, for way over an hour..
>>> I've looked at demos, read about colorbar in several different parts of matplotlib docs...
>>> 
>>> Can someone help?? .... Either the colorbar is next to the last plot, or else I
>>> get an error.
>>> 
>>> Here is code that I've tried: It puts the colorbar in the wrong place, and in addition the image size
>>> is very small while the ax2 and ax3 curve plots are much wider. 
>>> I want the image and the second 2 plots the same width.
>>> 
>>> 
>>> fig, (ax1, ax2,ax3) = plt.subplots(3,1)
>>> cax = ax1.imshow(bighistT, extent=myextent, cmap = cm.coolwarm, aspect = myaspect,\
>>> interpolation='nearest')
>>> ax1.set_title("Dummy title")
>>> # Add colorbar
>>> # cbar = fig.colorbar(cax) # this places the colorbar next to the third subplot
>>> plt.colorbar(cax) # so does this
>> 
>> cax is not the Axes containing the image, but the image itself. It seems
>> that you want to "steal" some space to the first subplot so:
>> 
>> fig, (ax1, ax2,ax3) = plt.subplots(3,1)
>> im = ax1.imshow(bighistT, extent=myextent, cmap=cm.coolwarm,
>> 		aspect=myaspect, interpolation='nearest')
>> ax1.set_title("Dummy title")
>> cbar = fig.colorbar(im, ax=ax1)
>> 
>> or you can also create a new Axes between ax1 and ax2, and tell
>> colorbar() to put the Colorbar into (with the cax keyword argument)
>> 
>> See
>> http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure.colorbar
>> 
>> -- 
>> Fabrice
>> 
>> 
>> ------------------------------------------------------------------------------
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> 

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Le jeudi 19 février 2015 à 23:10 -0800, Peter Rowat a écrit :
> I apologize for asking such a trivial question, but I’ve spent a long time trying to fix this:
> 
> I have a large 2D array that displays as an image, with a colorbar on the side.
> I also display 2 curves on top of the image. i.e. in same axes.
> The following code does it:
> 
> fig,ax = plt.subplots()
> cax = ax.imshow(bighistT, extent=myextent, cmap = cm.coolwarm, aspect = myaspect,\
> interpolation='nearest')
> ax.set_title("Dummy title")
> # Add colorbar
> cbar = fig.colorbar(cax)
> ax.set_ylabel('mV')
> 
> ax.plot(emtrate, emrate, '.r') #curve 1
> ax.plot(tt, rate*50 - 25.0, '-k', linewidth=3) #curve 2
> 
> plt.show()
> ========
> IN FACT,
> I want the curves in separate axes, below the image while the colorbar remains immediately to the right
> of the image.
> 
> I've tried many minor variations, for way over an hour..
> I've looked at demos, read about colorbar in several different parts of matplotlib docs...
> 
> Can someone help?? .... Either the colorbar is next to the last plot, or else I
> get an error.
> 
> Here is code that I've tried: It puts the colorbar in the wrong place, and in addition the image size
> is very small while the ax2 and ax3 curve plots are much wider. 
> I want the image and the second 2 plots the same width.
> 
> 
> fig, (ax1, ax2,ax3) = plt.subplots(3,1)
> cax = ax1.imshow(bighistT, extent=myextent, cmap = cm.coolwarm, aspect = myaspect,\
> interpolation='nearest')
> ax1.set_title("Dummy title")
> # Add colorbar
> # cbar = fig.colorbar(cax) # this places the colorbar next to the third subplot
> plt.colorbar(cax) # so does this
cax is not the Axes containing the image, but the image itself. It seems
that you want to "steal" some space to the first subplot so:
 fig, (ax1, ax2,ax3) = plt.subplots(3,1)
 im = ax1.imshow(bighistT, extent=myextent, cmap=cm.coolwarm,
 		aspect=myaspect, interpolation='nearest')
 ax1.set_title("Dummy title")
 cbar = fig.colorbar(im, ax=ax1)
or you can also create a new Axes between ax1 and ax2, and tell
colorbar() to put the Colorbar into (with the cax keyword argument)
See
http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure.colorbar
-- 
Fabrice

Peter,
I think that you want
cax = ax1.imshow(...)
cbar = fig.colorbar(cax,ax=ax1) # Where the ax keyword tells the colorbar which axes to steal space from. [1]
If you want the colorbar to be to the right of the first axes, and have the second and third axes line up with the first, then you need to create your own axes instance [2] {cbarax = fig.add_axes([...]) } for the colorbar and give that instance to the cax keyword of fig.colorbar (without an ax keyword). [1]
Also, I wouldn’t refer to the object returned by imshow as cax, as that is confusing when looking at the possible arguments of fig.colorbar. I would call the image object im or something similar. 
-Sterling
[1] http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure.colorbar
[2] http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure.add_axes
On Feb 19, 2015, at 11:10PM, Peter Rowat <pe...@pe...> wrote:
> I apologize for asking such a trivial question, but I’ve spent a long time trying to fix this:
> 
> I have a large 2D array that displays as an image, with a colorbar on the side.
> I also display 2 curves on top of the image. i.e. in same axes.
> The following code does it:
> 
> fig,ax = plt.subplots()
> cax = ax.imshow(bighistT, extent=myextent, cmap = cm.coolwarm, aspect = myaspect,\
> interpolation='nearest')
> ax.set_title("Dummy title")
> # Add colorbar
> cbar = fig.colorbar(cax)
> ax.set_ylabel('mV')
> 
> ax.plot(emtrate, emrate, '.r') #curve 1
> ax.plot(tt, rate*50 - 25.0, '-k', linewidth=3) #curve 2
> 
> plt.show()
> ========
> IN FACT,
> I want the curves in separate axes, below the image while the colorbar remains immediately to the right
> of the image.
> 
> I've tried many minor variations, for way over an hour..
> I've looked at demos, read about colorbar in several different parts of matplotlib docs...
> 
> Can someone help?? .... Either the colorbar is next to the last plot, or else I
> get an error.
> 
> Here is code that I've tried: It puts the colorbar in the wrong place, and in addition the image size
> is very small while the ax2 and ax3 curve plots are much wider. 
> I want the image and the second 2 plots the same width.
> 
> 
> fig, (ax1, ax2,ax3) = plt.subplots(3,1)
> cax = ax1.imshow(bighistT, extent=myextent, cmap = cm.coolwarm, aspect = myaspect,\
> interpolation='nearest')
> ax1.set_title("Dummy title")
> # Add colorbar
> # cbar = fig.colorbar(cax) # this places the colorbar next to the third subplot
> plt.colorbar(cax) # so does this
> ax1.set_ylabel('mV')
> ax2.plot(emtrate, emrate, '.r')
> ax3.plot(tt, rate*50 - 25.0, '-k', linewidth=3)
> 
> plt.show()
> Thanks for any help,
> 
> Peter
> Save our in-boxes! http://emailcharter.org 
> 
> 
> 
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I apologize for asking such a trivial question, but I’ve spent a long time trying to fix this:
I have a large 2D array that displays as an image, with a colorbar on the side.
I also display 2 curves on top of the image. i.e. in same axes.
The following code does it:
 fig,ax = plt.subplots()
 cax = ax.imshow(bighistT, extent=myextent, cmap = cm.coolwarm, aspect = myaspect,\
 interpolation='nearest')
 ax.set_title("Dummy title")
 # Add colorbar
 cbar = fig.colorbar(cax)
 ax.set_ylabel('mV')
 ax.plot(emtrate, emrate, '.r') #curve 1
 ax.plot(tt, rate*50 - 25.0, '-k', linewidth=3) #curve 2
 plt.show()
========
IN FACT,
I want the curves in separate axes, below the image while the colorbar remains immediately to the right
of the image.
I've tried many minor variations, for way over an hour..
I've looked at demos, read about colorbar in several different parts of matplotlib docs...
Can someone help?? .... Either the colorbar is next to the last plot, or else I
get an error.
Here is code that I've tried: It puts the colorbar in the wrong place, and in addition the image size
is very small while the ax2 and ax3 curve plots are much wider. 
I want the image and the second 2 plots the same width.
 fig, (ax1, ax2,ax3) = plt.subplots(3,1)
 cax = ax1.imshow(bighistT, extent=myextent, cmap = cm.coolwarm, aspect = myaspect,\
 interpolation='nearest')
 ax1.set_title("Dummy title")
 # Add colorbar
# cbar = fig.colorbar(cax) # this places the colorbar next to the third subplot
 plt.colorbar(cax) # so does this
 ax1.set_ylabel('mV')
 ax2.plot(emtrate, emrate, '.r')
 ax3.plot(tt, rate*50 - 25.0, '-k', linewidth=3)
 plt.show()
Thanks for any help,
Peter
Save our in-boxes! http://emailcharter.org 

Thomas Caswell <tcaswell@...> writes:
> 
> 
> Jorge,I have put in a PR to fix this issue. Can you confirm that it is
equivalent to your fix? For aesthetic reasons I chose to pass guiEvent as a
kwarg to all of the event related functions.
> 
> https://github.com/matplotlib/matplotlib/pull/4130
> 
> 
> Tom
I can confirm this fixes the issue I had. 
Jorge

Hi,
NumFOCUS has promotes and supports the ongoing research and development of
open-source computing tools including Matplotlib.
This year NumFOCUS want to try be a Google Summer of Code
"umbrella" mentoring organization,
 Umbrella organizations are mentoring organizations accepted into the Google
 Summer of Code program that have other open source organizations working
 "under" them. Sometime organizations that work very closely or have very
 similar goals or communities may get put together under an "umbrella."
 Google stills expects all organizations under the umbrella, whether accepted
 into the program under their title or not, to adhere to all the rules and
 regulations of the program.
 From https://www.google-melange.com/gsoc/document/show/gsoc_program/google/gsoc2015/help_page#umbrella_organization
To help promote and support Matplotlib.
We encourage Matplotlib to apply to Google Summer of Code under your own title
and will be very happy if you can also do with us.
If you are interested, please check https://github.com/swcarpentry/gsoc2015
and https://github.com/swcarpentry/gsoc2015/blob/master/CONTRIBUTING.md.
If you have any question, please email me directly.
Thanks in advance,
Raniere

Ok, axes.apply_aspect() seems to work. The other obvious kluge I had found
was to save the figure twice, once before and once after I accessed the axes
position. 
It seems the more elegant solution might be to use a somewhat-complicated
transform, so that that the two endpoints of a Line2d segment can have
coordinates in different coordinate systems (e.g. one end is in data
coordinates on ax1, and the other end is in data coordinates on ax2). The
"axes zoom effect" is similar to what I'm trying to do: 
http://matplotlib.org/users/annotations_guide.html#zoom-effect-between-axes
Thanks!
--
View this message in context: http://matplotlib.1069221.n5.nabble.com/axes-get-position-inaccurate-until-after-savefig-tp44954p44990.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

On 2015年02月18日 7:51 AM, Ryan Nelson wrote:
> I don't have an answer to your question exactly. But I'll just say that
> this does make sense. The aspect-corrected axes (after show) is a subset
> of what you originally asked for, i.e. the bottom is higher, and the
> height is smaller. My guess is that this is not calculated until the
> final rendering on save on some computational effort. Otherwise, these
> values might need to be recalculated every time you add e.g. a colorbar.
> There is certainly a way to "trick" the plot into rendering, but I
> wonder if you could post a small (maybe two axes) version that
> demonstrates the effect your trying to accomplish. Perhaps someone might
> have a simpler/more robust solution.
There is an Axes method called apply_aspect() that is called by the 
Axes.draw() method. Normally there is no need to call it before that, 
but I think you could do so.
I think the problem, though, is that until the figure is rendered to a 
real device or saved in a file, its dimensions in inches are not known, 
and apply_aspect needs that information.
Try including the figsize_inches kwarg when you make the figure, and 
then see if calling apply_aspect makes the position settle down to its 
final value.
Eric
>
> Ryan
>
> On Wed, Feb 18, 2015 at 4:27 AM, gdm <jga...@gm...
> <mailto:jga...@gm...>> wrote:
>
> New matplotlib user here. Sometimes I like to make figures with
> multiple
> axes, and have lines that cross multiple axes. I've run in to
> problems with
> coordinates when doing this. One such problem is that
> axes.get_position()
> seems to return incorrect coordinates for an axes with a fixed
> aspect ratio.
> However, after calling pyplot.show() (or fig.savefig()), it returns the
> correct coordinates.
>
> Here is some example code:
> #########################
> import numpy
> import matplotlib.pyplot as plt
>
> # make up some data
> x = numpy.arange(10)
> y = numpy.sin(x)
> y2 = numpy.cos(x)
>
> # generate the figure
> fig = plt.figure()
>
> # setup the first axes
> ax1 = fig.add_subplot(121)
> plt.plot(x,y)
>
> # setup the second axes with axis ratio
> ax2 = fig.add_subplot(122, aspect=6)
> plt.plot(x, y2)
>
> # Print out the axes position after various operations
> print "aaa", ax2.get_position()
>
> plt.draw()
> print "bbb", ax2.get_position()
>
> fig.canvas.draw()
> print "ccc", ax2.get_position()
>
> plt.show(block=False)
> print "yyy", ax2.get_position()
> ##########################
>
> Running this code produces the following output:
> aaa Bbox('array([[ 0.54772727, 0.1 ],\n [ 0.9 , 0.9
> ]])')
> bbb Bbox('array([[ 0.54772727, 0.1 ],\n [ 0.9 , 0.9
> ]])')
> ccc Bbox('array([[ 0.54772727, 0.1 ],\n [ 0.9 , 0.9
> ]])')
> yyy Bbox('array([[ 0.54772727, 0.18686869],\n [ 0.9 ,
> 0.81313131]])')
>
> P.S.: I think this might be related to an issue noted here:
> http://stackoverflow.com/questions/11900654/get-position-does-strange-things-when-using-a-colorbar
>
>
>
>
>
> --
> View this message in context:
> http://matplotlib.1069221.n5.nabble.com/axes-get-position-inaccurate-until-after-savefig-tp44954.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
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Jorge,
I have put in a PR to fix this issue. Can you confirm that it is
equivalent to your fix? For aesthetic reasons I chose to pass guiEvent as
a kwarg to all of the event related functions.
https://github.com/matplotlib/matplotlib/pull/4130
Tom
On Wed Feb 18 2015 at 5:32:04 PM Thomas Caswell <tca...@gm...> wrote:
> Can you put in a pull request with those changes please?
>
> On Wed, Feb 18, 2015, 17:03 Jorge Scandaliaris <jor...@ya...>
> wrote:
>
>> Hi,
>> A recent commit against lib/matplotlib/backends/backend_qt5.py [1] causes
>> some errors in code that was working fine before. The error is as follows:
>>
>> ------------------------------------------------------------
>> ---------------
>> TypeError Traceback (most recent call
>> last)
>> /home/jscandal/sw/matplotlib/matplotlib.py3/lib/matplotlib/backends
>> /backend_qt5.py
>> in enterEvent(self, event)
>> 249
>> 250 def enterEvent(self, event):
>> --> 251 FigureCanvasBase.enter_notify_event(self, event,
>> guiEvent=event)
>> 252
>> 253 def leaveEvent(self, event):
>>
>> TypeError: enter_notify_event() got multiple values for argument
>> 'guiEvent'
>>
>> ------------------------------------------------------------
>> ---------------
>> TypeError Traceback (most recent call
>> last)
>> /home/jscandal/sw/matplotlib/matplotlib.py3/lib/matplotlib/backends
>> /backend_qt5.py
>> in leaveEvent(self, event)
>> 253 def leaveEvent(self, event):
>> 254 QtWidgets.QApplication.restoreOverrideCursor()
>> --> 255 FigureCanvasBase.leave_notify_event(self, event,
>> guiEvent=event)
>> 256
>> 257 def mousePressEvent(self, event):
>>
>> TypeError: leave_notify_event() got multiple values for argument
>> 'guiEvent'
>>
>>
>>
>> Reverting the changes introduced by the commit in lines 251 and 255 of
>> backend_qt5.py seems to fix the issue, in my particular use case.
>>
>> Regards,
>>
>> Jorge
>>
>>
>> 1.
>> b72e0cd9e63f7cf4bec2908143c62c23666b674a
>> Author: Steven Silvester <ste...@ie...>
>> Date: Sun Feb 15 09:38:21 2015 -0600
>>
>> Add guiEvent data to Qt backend
>>
>>
>>
>> ------------------------------------------------------------
>> ------------------
>> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
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>

On Wed, Feb 18, 2015 at 4:57 PM, Thomas Caswell <tca...@gm...> wrote:
> Interesting, I was going off what the IPython devs said here
> https://github.com/ipython/ipython/issues/7774
>
That was just adding the "notebook" alias to the `%matplotlib` magic. The
actual underlying functionality has been around for a while longer.
-- 
Fernando Perez (@fperez_org; http://fperez.org)
fperez.net-at-gmail: mailing lists only (I ignore this when swamped!)
fernando.perez-at-berkeley: contact me here for any direct mail

Interesting, I was going off what the IPython devs said here
https://github.com/ipython/ipython/issues/7774
On Wed Feb 18 2015 at 7:48:32 PM Eric Firing <ef...@ha...> wrote:
> On 2015年02月18日 2:31 PM, Thomas Caswell wrote:
> > Recent means IPython > 2.4.
>
> Did you mean 2.2? It works on 2.3.
>
> Eric
>
> >
> > For 3.0
> >
> > %matplotlib notebook
> >
> > will also work.
> >
> > Tom
> >
> > On Wed Feb 18 2015 at 7:25:41 PM Eric Firing <ef...@ha...
> > <mailto:ef...@ha...>> wrote:
> >
> > On 2015年02月18日 6:44 AM, Emilia Petrisor wrote:
> > > Hi all,
> > >
> > > I looked for a link where I could find out what’s new in
> |matplotlib
> > > 1.4.3|, but there is no one.
> > >
> > > Especially I’m interested in the new features of |nbagg backend|.
> > All I
> > > know is what I read in an email here, namely that /The nbagg
> > backend is
> > > looking great - some pretty swish new features/.
> > > Thanks,
> > >
> > > Emilia
> > >
> >
> > In a recent IPython, try starting up a notebook and using
> >
> > %matplotlib nbagg
> >
> > You will find that the embedded plot is fully interactive, complete
> with
> > a cursor readout and navigation buttons. I think that's the new
> part.
> >
> > Eric
> >
> >
> >
> > ------------------------------__----------------------------
> --__------------------
> > Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
> > from Actuate! Instantly Supercharge Your Business Reports and
> Dashboards
> > with Interactivity, Sharing, Native Excel Exports, App Integration &
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> FREE
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> iu=/4140/ostg.clktrk
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> > _________________________________________________
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> > <https://lists.sourceforge.net/lists/listinfo/matplotlib-users>
> >
>
>

On 2015年02月18日 2:31 PM, Thomas Caswell wrote:
> Recent means IPython > 2.4.
Did you mean 2.2? It works on 2.3.
Eric
>
> For 3.0
>
> %matplotlib notebook
>
> will also work.
>
> Tom
>
> On Wed Feb 18 2015 at 7:25:41 PM Eric Firing <ef...@ha...
> <mailto:ef...@ha...>> wrote:
>
> On 2015年02月18日 6:44 AM, Emilia Petrisor wrote:
> > Hi all,
> >
> > I looked for a link where I could find out what’s new in |matplotlib
> > 1.4.3|, but there is no one.
> >
> > Especially I’m interested in the new features of |nbagg backend|.
> All I
> > know is what I read in an email here, namely that /The nbagg
> backend is
> > looking great - some pretty swish new features/.
> > Thanks,
> >
> > Emilia
> >
>
> In a recent IPython, try starting up a notebook and using
>
> %matplotlib nbagg
>
> You will find that the embedded plot is fully interactive, complete with
> a cursor readout and navigation buttons. I think that's the new part.
>
> Eric
>
>
>
> ------------------------------__------------------------------__------------------
> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
> from Actuate! Instantly Supercharge Your Business Reports and Dashboards
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> <https://lists.sourceforge.net/lists/listinfo/matplotlib-users>
>

Recent means IPython > 2.4.
For 3.0
%matplotlib notebook
 will also work.
Tom
On Wed Feb 18 2015 at 7:25:41 PM Eric Firing <ef...@ha...> wrote:
> On 2015年02月18日 6:44 AM, Emilia Petrisor wrote:
> > Hi all,
> >
> > I looked for a link where I could find out what’s new in |matplotlib
> > 1.4.3|, but there is no one.
> >
> > Especially I’m interested in the new features of |nbagg backend|. All I
> > know is what I read in an email here, namely that /The nbagg backend is
> > looking great - some pretty swish new features/.
> > Thanks,
> >
> > Emilia
> >
>
> In a recent IPython, try starting up a notebook and using
>
> %matplotlib nbagg
>
> You will find that the embedded plot is fully interactive, complete with
> a cursor readout and navigation buttons. I think that's the new part.
>
> Eric
>
>
>
> ------------------------------------------------------------
> ------------------
> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
> from Actuate! Instantly Supercharge Your Business Reports and Dashboards
> with Interactivity, Sharing, Native Excel Exports, App Integration & more
> Get technology previously reserved for billion-dollar corporations, FREE
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> iu=/4140/ostg.clktrk
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

On 2015年02月18日 6:44 AM, Emilia Petrisor wrote:
> Hi all,
>
> I looked for a link where I could find out what’s new in |matplotlib
> 1.4.3|, but there is no one.
>
> Especially I’m interested in the new features of |nbagg backend|. All I
> know is what I read in an email here, namely that /The nbagg backend is
> looking great - some pretty swish new features/.
> Thanks,
>
> Emilia
>
In a recent IPython, try starting up a notebook and using
%matplotlib nbagg
You will find that the embedded plot is fully interactive, complete with 
a cursor readout and navigation buttons. I think that's the new part.
Eric