No Powerpoint version I know supports SVG (or any vector graphics format useful
in this case) and Matplotlib does not
export WMF graphics anymore. So the easiest way is to use PNGs, if you can live
with raster graphics.
Alternatively, if you need vector graphics, you can export the Matplotlib
at conferences because they were using Windows and I only had access to
Linux and Macs at home.
Cheers!
Ben Root
On Mon, Apr 21, 2014 at 7:34 AM, Juergen Hasch pyt...@elbonia.de
mailto:pyt...@elbonia.de wrote:
No Powerpoint version I know supports SVG (or any vector graphics format
Have you tried latex_float() as suggested here ?
http://stackoverflow.com/questions/13490292/format-number-using-latex-notation-in-python
def latex_float(f):
float_str = {0:.2g}.format(f)
if e in float_str:
base, exponent = float_str.split(e)
return r{0} \times
The solution I use when I want all sans-serif out of TeX is to use the
cmbright package, which can be turned on by adding:
rc('text.latex', preamble=r'\usepackage{cmbright}')
That may require installing the cmbright LaTeX package if you don't already
have it.
I am using the sfmath
Am 31.03.2013 08:50, schrieb Pawel Chojnacki:
Thank you very much - hovewer, your solution isn't enough. Adding your lines
generate:
The problem is this:
RuntimeError: LaTeX was not able to process the following string:
u''
Here is the full report generated by LaTeX:
Latex doesn't like
Am 30.03.2013 16:29, schrieb Pawel Chojnacki:
Please pardon me, but what object is math.usetex attribute of? I can't find
it in the documentation.
http://matplotlib.org/users/usetex.html Mentions only text.usetex.
You need to set
mpl.rcParams['text.usetex'] = True
For text you
Am 05.10.2012 11:13, schrieb Matthias BUSSONNIER:
Le 4 oct. 2012 à 23:09, Juergen Hasch a écrit :
Here is my take on it as an IPython notebook, based on Damon's code:
http://nbviewer.ipython.org/3835181/
I took the engineering approach and filtered the random function instead of
doing
If you like to use qt4 as backend, you can also do it like this:
import sys
from PySide import QtGui
import numpy as np
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt4agg \
import FigureCanvasQTAgg as FigureCanvas
fig = Figure()
axes = fig.add_subplot(111)
x =
Here is my take on it as an IPython notebook, based on Damon's code:
http://nbviewer.ipython.org/3835181/
I took the engineering approach and filtered the random function instead of
doing some fft/ifft magic.
Also, X and Y of the functions are affected now, giving them a more natural
look in
