I would like to have the percentage values shown in white instead of in
black within a pie chart.
I figured I could do something like:
def reColor(percent):
I am lost here on how to format the percentage and change
the color
axes.pie(values, labels=labels, autopct=reColor,
2009/8/21 Daniel Platz mail.to.daniel.pl...@googlemail.com:
I just realized that I did not give the correct plot object when creating
the colorbar. Now it works perfectly to pass arguments by set_xticklabels().
However, another question just arose. To format the numbers on the tick
labels I
On Fri, Aug 21, 2009 at 10:01 AM, Scott
Sinclairscott.sinclair...@gmail.com wrote:
I just realized that I did not give the correct plot object when creating
the colorbar. Now it works perfectly to pass arguments by set_xticklabels().
However, another question just arose. To format the numbers
Hi folks,
I have a (newbie) problem using csv2rec. I am a regular python user
but this is my first time using matplotlib and numpy after being
inspired by attending a talk by Dr. John Hunter.
I am trying to read a csv file that has 6000 lines that look like this:
code
8/17/2009,4:49:52
On Fri, Aug 21, 2009 at 11:27 AM, Phil Robareverisimilid...@gmail.com wrote:
I have a (newbie) problem using csv2rec. I am a regular python user
but this is my first time using matplotlib and numpy after being
inspired by attending a talk by Dr. John Hunter.
I am trying to read a csv file
The sixteen lines of data you sent work in a little histogram-
generator for me, ignoring the masking (as a nearly-newbie, I can say
that ignoring the stuff I don't yet care about usually works):
from matplotlib.mlab import csv2rec, csv
import pylab as p
import numpy as n
names = ('date',
Does anyone know how to do a contour plot of a set of X,Y data where each
contour level has the same number of data points inside it? What I want to
show is where most of the data is appearing in the x, y position for a
scatter plot of ~1,000 points, so you can't just plot all those as points.
We are working on plotting mesh (in hermes2d:
http://hpfem.math.unr.edu/projects/hermes2d-new/) We created a python
function to plot mesh but initially without curves. Later we also tried to
work on curved elements but we are having some problems.
In the hermes2d examples curves are defined as [4,
Hi all,
At the Scipy2009 conference I was recently told I could get better
performance from matplotlib through an ssh tunnel by using a different
backend. However, I can't find any introductory material on this, just
function docs for backend_bases module. What part of the matplotlib
call
On Fri, Aug 21, 2009 at 6:44 PM, Michael Cohenmco...@caltech.edu wrote:
Hi all,
At the Scipy2009 conference I was recently told I could get better
performance from matplotlib through an ssh tunnel by using a different
backend. However, I can't find any introductory material on this, just
Hello.
I was doing a simple test using a FIFOBuffer. I set the dataLim parameter
to the dataLim of a Line2D plot. After adding a value to the FIFO, it
raises an exception. It looks like the FIFO is trying to call
Bbox.update(), but that method does not exist. Other update_*() methods do.
So I can do:
plot([1,2,3], [1,4,9], marker='+')
and it'll draw 3 points each with a + marker.
What I'd really like to do is
plot([1,2,3], [1,4,9], markerlist=['A', 'B', 'C'])
and have it draw the first point with a rendered
letter 'A', the second with a 'B', and the third with
a 'C'.
1) Not
This sentence is missing to or and I think:
These helper methods will take your data (eg. numpy arrays and strings) create
primitive ...
Is in at http://matplotlib.sourceforge.net/users/artists.html
Marc Desmarais
Long Beach, CA
Hey guys,
I found another typo here:
http://matplotlib.sourceforge.net/api/axes_api.html?highlight=legend#matplotlib.axes.Axes.get_legend_handles_labels
-equibalent
+equivalent
Cheers,
N
On Fri, Aug 21, 2009 at 8:29 PM, marc desmarais mdesm2...@yahoo.com wrote:
This sentence is missing to
Erik Schweller wrote:
My overall goal is to generate contour plots for a wide range of input
data. The data points are not regularly spaced and do not align to
any grid. The data points represent measurements taken from a model
that can take on a variety of shapes. To make matters more
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