matplotlib-users Mailing List for matplotlib

Hello Jerzy & All,

On 14 February 2012 17:55, Jerzy Karczmarczuk wrote:
> Andrea, I believe that if you find ONE good visual aspect ratio,
> according to your figure size, that should do. Yo know your
> figsize, and if you know all in your axes([bot,lft,wid, height]), that
> this visual ratio should be easy to fix.

I managed to get *almost* there, but there still is a small glitch. I
attach a self-evident sample, which generates data very similar to the
real ones I have and shows the two "parallel" curves to the main one.

You will notice that the "parallel" curves look parallel almost all
the time, except in a few areas (I have annotated the plot for
reference). I can't see the reason for this difference, but it is
obvious I am missing something.

One thing I didn't include is that in my real-life plot, the figure
size should be full screen (which on my screen means 20x13.65 inches)
and I use the subplots_adjust command like this:

fig.subplots_adjust(left=0.03, right=0.7, bottom=0.04, top=0.96)

Thank you in advance for any suggestion.

Andrea.

"Imagination Is The Only Weapon In The War Against Reality."
http://xoomer.alice.it/infinity77/

Francois Lemery :
> Hi Python World!
>
> I currently have a 2D array: A[i][j] which I can plot very nicely
> using the contourf function.  However, in this plot, the axes span
> from (0, i) and (0, j).
> I would like to multiply each axes by a scaling constant- thereby
> turning the array element values into physical quantities (distance
> and time for example).
> Could anyone help me with this?  I've looked around, but so far the
> only solution I have found is to create a new set of arrays with these
> scaling factors included.  I can do this, but I feel as though it
> would be a waste.
You want just to change your labelling?
No problemo, Baby.

xmin,xmax = ........
ymin,ymax = ........
...
tbl=...

ic=contourf(tbl,
             extent=(xmin,xmax,ymin,ymax))
axis([xmin,xmax,ymin,ymax])

show()

====

Bon courage.

Now, if you want to change your *values*, as Alexa understood, then be 
more precise, please.

Jerzy Karczmarczuk

Hi,
Sorry for not giving sufficient detail.
I open an HDF5 file and then read some EArray into a regular array:

a = f.root
MySource = a.myLineSource[:,:,1]      # the dimensions of my source
are (x, t) = (50, 15000) 50 corresponds to 50 gridpoints where I have
recorded an electric field.  and 15,000 corresponds to the number of
timesteps I have run in my simulation.

figure()
A1=contourf(MySource)         # When I do this, it gives me a
beautiful plot.  However the x axis spans (0, 50) when I would like it
to go from (0, 50)*DX.
Similarly, in time, my plot spans (0, 15,000) when I would like it to
range from (0, 15000)*DT
Where DX and DT are some real numbers (e.g. a micron, and a femtosecond.)

I would suspect there to be some 'scaling' feature already available
in python for just this kind of thing.  That is why I argued that
introducing new arrays to incorporate the adjusted/properly scaled
values would be a waste.
Thanks again!


On Fri, Feb 17, 2012 at 1:26 PM, Alexa Villaume <ale...@gm...> wrote:
> Hi François,
>
> Why would it be a waste to multiply the values in an array by the scaling
> factors?
>
> Can you provide an example of your code so everybody can get a better idea
> of what you're doing now?
>
> Thanks,
> Alexa
>
> On Fri, Feb 17, 2012 at 9:07 AM, Francois Lemery <fra...@gm...>
> wrote:
>>
>> Hi Python World!
>>
>> I currently have a 2D array: A[i][j] which I can plot very nicely
>> using the contourf function.  However, in this plot, the axes span
>> from (0, i) and (0, j).
>> I would like to multiply each axes by a scaling constant- thereby
>> turning the array element values into physical quantities (distance
>> and time for example).
>> Could anyone help me with this?  I've looked around, but so far the
>> only solution I have found is to create a new set of arrays with these
>> scaling factors included.  I can do this, but I feel as though it
>> would be a waste.
>>
>> --
>> Thanks!
>> François
>>
>>
>> ------------------------------------------------------------------------------
>> Virtualization & Cloud Management Using Capacity Planning
>> Cloud computing makes use of virtualization - but cloud computing
>> also focuses on allowing computing to be delivered as a service.
>> http://www.accelacomm.com/jaw/sfnl/114/51521223/
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>



-- 
Thanks,
François

Hi François,

Why would it be a waste to multiply the values in an array by the scaling
factors?

Can you provide an example of your code so everybody can get a better idea
of what you're doing now?

Thanks,
Alexa

On Fri, Feb 17, 2012 at 9:07 AM, Francois Lemery
<fra...@gm...>wrote:

> Hi Python World!
>
> I currently have a 2D array: A[i][j] which I can plot very nicely
> using the contourf function.  However, in this plot, the axes span
> from (0, i) and (0, j).
> I would like to multiply each axes by a scaling constant- thereby
> turning the array element values into physical quantities (distance
> and time for example).
> Could anyone help me with this?  I've looked around, but so far the
> only solution I have found is to create a new set of arrays with these
> scaling factors included.  I can do this, but I feel as though it
> would be a waste.
>
> --
> Thanks!
> François
>
>
> ------------------------------------------------------------------------------
> Virtualization & Cloud Management Using Capacity Planning
> Cloud computing makes use of virtualization - but cloud computing
> also focuses on allowing computing to be delivered as a service.
> http://www.accelacomm.com/jaw/sfnl/114/51521223/
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hi Python World!

I currently have a 2D array: A[i][j] which I can plot very nicely
using the contourf function.  However, in this plot, the axes span
from (0, i) and (0, j).
I would like to multiply each axes by a scaling constant- thereby
turning the array element values into physical quantities (distance
and time for example).
Could anyone help me with this?  I've looked around, but so far the
only solution I have found is to create a new set of arrays with these
scaling factors included.  I can do this, but I feel as though it
would be a waste.

-- 
Thanks!
François

Hi all,

I am new to Mpl, and I am making a 4x4 subplot now.
I wish to offset (downwards) the locations of the tick labels on the Y-axis of one subplot.
Actually, I just want to offset one particular tick label but its also okay if its a small (and equal) offset for the tick labels.

Can you please help me out?

Best,
Bedartha

Hi all,

I had the same problem and I implemented a small library for manipulating SVG figures (for example, matplotlib-generated). It is on github:

https://github.com/btel/svg_utils

There is also a related blog post:

http://neuroscience.telenczuk.pl/?p=331

The library does NOT allow to import svg figures into matplotlib, but it allows to combine a mpl figure exported to SVG and and a external SVG file.

I hope it helps!

Cheers,

Bartosz


On 16.02.2012, at 20:43, William Hoburg wrote:

> Hi everybody,
> Is there a way to import a svg-image into a plot?
> I know that there are some possibilities to import png (http://matplotlib.sourceforge.net/examples/pylab_examples/demo_annotation_box.html) or eps (which is then rastered).
> But till now I didn't find any way to import/embed a real vector graphic which is still a vector when I save the figure again as pdf or svg.
> Thanks in advance,
> HoWil
> -- 
> Empfehlen Sie GMX DSL Ihren Freunden und Bekannten und wir
> belohnen Sie mit bis zu 50,- Euro! https://freundschaftswerbung.gmx.de
> 
> ------------------------------------------------------------------------------
> Virtualization & Cloud Management Using Capacity Planning
> Cloud computing makes use of virtualization - but cloud computing 
> also focuses on allowing computing to be delivered as a service.
> http://www.accelacomm.com/jaw/sfnl/114/51521223/
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Bartosz Telenczuk

Institute for Theoretical Biology
Humboldt University of Berlin, Germany
Phone: +4930/2093-8838
Homepage: http://neuroscience.telenczuk.pl

On 02/15/2012 03:10 PM, Alexa Villaume wrote:
> Hi Eric,
>
> Thanks for your help, I'm still really new to python and matplotlib.
> I've got my labels defined but now I'm having another problem with the
> formatting.
>
> I'm doing -
>
> CS1.level=[14.07, 14.27]
>
> plt.clabel(CS1,CS1.level[::2],inline=True,fmt='OIII',fontize=14)

Alexa,

First, it looks like you might have slightly misunderstood my 
suggestion.  When levels are specified as a kwarg for contour or 
contourf, they are saved as the "levels" attribute of the ContourSet 
object that is returned.  So, one does not assign directly to that 
attribute.

Second, clabel is intended for use with contour, not contourf, and can 
produce odd results with the ContourSet returned by a call to contourf. 
(This might be considered a bug; I only stumbled over it while trying to 
understand your problem.  It had never occurred to me to try to use 
clabel with contourf.  I think that either it should be made to work as 
one might reasonably expect, or clabel should raise an exception if 
given a ContourSet from contourf.)

You can always use both contour and contourf as in this example:
http://matplotlib.sourceforge.net/examples/pylab_examples/contourf_demo.html
If you don't want the lines you can make them invisible and leave only 
the labels.

>
>
> Where I get a type error that says that not all string arguments are
> getting converted during formatting. This is the full error,
>
> Traceback (most recent call last):
>
>    File "ContourAttempt.py", line 81, in <module>
>
>      plt.clabel(CS1,CS1.level[::2],inline=True,fmt='OIII',fontize=14) #
> Something wrong with formmating
>

Third, in your line above, you are trying to set fmt to a string that is 
not a number formatting string; that is why you are getting the 
exception.  The code is trying to use the fmt string to format a numeric 
level, but there is no % expression in it, so it can't.

It looks like your earlier code, with the dictionary as fmt, was more 
along the right lines.  I have never tried this option myself, though.

If you run into another problem (or need more advice with the present 
problem) please try to provide a complete, self-contained example that 
illustrates it. That way someone else can run it, see exactly the 
problem, and show you exactly how to solve it.  Or in the process of 
condensing the problem down to an example in a few lines, sometimes one 
sees the solution.

Welcome to python and mpl!

Eric

>    File "/Users/alexavillaume/src/matplotlib/lib/matplotlib/pyplot.py",
> line 2176, in clabel
>
>      ret = ax.clabel(CS, *args, **kwargs)
>
>    File "/Users/alexavillaume/src/matplotlib/lib/matplotlib/axes.py",
> line 7326, in clabel
>
>      return CS.clabel(*args, **kwargs)
>
>    File "/Users/alexavillaume/src/matplotlib/lib/matplotlib/contour.py",
> line 217, in clabel
>
>      self.labels(inline,inline_spacing)
>
>    File "/Users/alexavillaume/src/matplotlib/lib/matplotlib/contour.py",
> line 624, in labels
>
>      lw = self.get_label_width(lev, self.labelFmt, fsize)
>
>    File "/Users/alexavillaume/src/matplotlib/lib/matplotlib/contour.py",
> line 284, in get_label_width
>
>      lev = self.get_text(lev, fmt)
>
>    File "/Users/alexavillaume/src/matplotlib/lib/matplotlib/contour.py",
> line 344, in get_text
>
>      return fmt%lev
>
> TypeError: not all arguments converted during string formatting
>
>
>
>
> On Wed, Feb 15, 2012 at 10:34 AM, Eric Firing <ef...@ha...
> <mailto:ef...@ha...>> wrote:
>
>     On 02/15/2012 10:15 AM, Alexa Villaume wrote:
>      > Hi Everybody,
>      >
>      >
>      > I'm trying to label the contours of my contour plot following this
>      > example -
>      >
>      >
>     http://matplotlib.sourceforge.net/examples/pylab_examples/contour_label_demo.html
>      >
>      >
>      > My actual code looks like this -
>      >
>      >
>      > import matplotlib
>      >
>      > matplotlib.use('PDF')
>      >
>      > frompylab import*
>      >
>      > import numpy as np
>      >
>      >
>      > # Define the surface of the plot
>      >
>      > metals=np.arange(-3.0, 1.1, 0.1)
>      >
>      > U=np.arange(-6.0, 0.25, 0.25)
>      >
>      >
>      > # Create the arrays that the data will be stored in
>      >
>      > o3=np.zeros([25,41])
>      >
>      > o2=np.zeros([25,41])
>      >
>      > c3=np.zeros([25,41])
>      >
>      > mg2=np.zeros([25,41])
>      >
>      > c3=np.zeros([25,41])
>      >
>      > si2=np.zeros([25,41])
>      >
>      > s3=np.zeros([25,41])
>      >
>      >
>      > CS=plt.contourf(metals, U, o3, levels=[o3col-nsig*o3sig,
>      > o3col+nsig*o3sig], alpha=0.50, colors='#f88534')
>      >
>      > CS=plt.contourf(metals, U, o2, levels=[o2col-nsig*o2sig,
>      > o2col+nsig*o2sig], alpha=0.50, colors='#f2f34f')
>      >
>      > CS=plt.contourf(metals, U, c3, levels=[c3col-nsig*c3sig,
>      > c3col+nsig*c3sig], alpha=0.50, colors='#93d3f3')
>      >
>      > CS=plt.contourf(metals, U, mg2, levels=[mg2col-nsig*mg2sig,
>      > mg2col+nsig*mg2sig], alpha=0.50, colors='#ff536d')
>      >
>      > CS=plt.contourf(metals, U, s3, levels=[s3col-nsig*s3sig,
>      > s3col+nsig*s3sig], alpha=0.50, colors='#83c460')
>      >
>      > CS=plt.contourf(metals, U, si2, levels=[si2col-nsig*si2sig,
>      > si2col+nsig*si2sig], alpha=0.50, colors='black')
>      >
>      >
>      >
>      > # Trying to label the contours
>      >
>      >
>      > fmt = {}
>      >
>      > strs = [ 'O III', 'O II', 'C III', 'Mg II', 'S III', 'Si II']
>      >
>      > for l,s in zip(levels, strs):
>      >
>      > fmt[l] = s
>      >
>      > plt.clabel(CS,levels[::2],inline=True,fmt=fmt,fontize=14)
>      >
>      >
>      > But I get an error that says that "levels" is not defined. What
>     should I do?
>
>     Define levels!
>
>     In your call to clabel, you are referencing a global "levels" which you
>     did not define; what you did define is the levels attribute of each CS
>     object.  So probably what you want is something like:
>
>     plt.clabel(CS, CS.levels[::2],inline=True,fmt=fmt,fontize=14)
>
>     but you need one such call for each CS you create, if you want all of
>     them labeled.
>
>
>     Eric
>
>      >
>      >
>      > Thanks!
>      >
>      > Alexa

Hi,

if the import filetype is not restricted to svg, you can use PyX to 
place vector eps figures into other eps figures. I used this in a two 
step approach (first create the plot with matplotlib and store is as eps 
and second, use PyX to combine the plot with a vector figure) in a 
single script.

This usually worked fine and the resulting file is still completely 
vectorized!

br
Jakob

On 02/16/2012 08:43 PM, William Hoburg wrote:
> Hi everybody,
> Is there a way to import a svg-image into a plot?
> I know that there are some possibilities to import png (http://matplotlib.sourceforge.net/examples/pylab_examples/demo_annotation_box.html) or eps (which is then rastered).
> But till now I didn't find any way to import/embed a real vector graphic which is still a vector when I save the figure again as pdf or svg.
> Thanks in advance,
> HoWil