matplotlib-users Mailing List for matplotlib

On 1/26/07, Fernando Perez <fpe...@gm...> wrote:
> On 1/25/07, Alan G Isaac <ai...@am...> wrote:
> > On 2007年1月24日, Fernando Perez apparently wrote:
> > > Let us know if this is not enough or if you have any other issues.
> >
> > How about for Windows users? You list as dependencies:
[...]
> We obviously need to update the windows documentation...
Done in SVN, thanks for reporting this.
regards,
f

On Mar 18, 2007, at 12:41 PM, John Hunter wrote:
> On 3/17/07, Simson Garfinkel <si...@ac...> wrote:
>> Hi. I haven't been active for a while, but now I have another paper
>> that I need to get out...
>
> Glad to have you back...
Thanks. I've taken a new job, moved to california, and have been 
flying between the two coasts every week. It doesn't leave much time 
for mailing lists...
>
>> Anyway, I need to draw a cumulative distribution function, as the
>> reviewers of my last paper really nailed me to the wall for including
>> histograms instead of CDFs. Is there any way to plot a CDF with
>> matplotlib?
>
> For analytic cdfs, see scipy.stats. I assume you need an empirical
> cdf. You can use matplotlib.mlab.hist to compute the empirical pdf
> (use normed=True to return a PDF rather than a frequency count). Then
> use numpy.cumsum to do the cumulative sum of the pdf, multiplying by
> the binsize so it approximates the integral.
>
> import matplotlib.mlab
> from pylab import figure, show, nx
>
> x = nx.mlab.randn(10000)
> p,bins = matplotlib.mlab.hist(x, 50, normed=True)
> db = bins[1]-bins[0]
> cdf = nx.cumsum(p*db)
>
> fig = figure()
> ax = fig.add_subplot(111)
> ax.bar(bins, cdf, width=0.8*db)
> show()
>
Thanks! I'll try it out and see what happens.

On 3/18/07, Allan Noriel Estrella <all...@gm...> wrote:
> I have an array of data that were sampled with a sampling rate of 1.5625
> samples/sec . I want to plot these data with the x axis showing time in
> terms of hours for the major ticks and minutes for the minor ticks in my
> custom made wx App. I have been fiddling around with the HourLocator and
> MinuteLocator classes but it seems I can't get them to work. Do you know an
> easy way to do this? I just want to plot my data in terms of the actual
> time/duration of logging they represent (in hours and/or in minutes when the
> plot is zoomed in or there is less than an hour's worth of samples)
Well, the HourLocator, MiinuteLocator, etc are for times and not
durations. If you want durations, just use plot and not plot_date.
Does that help?

On 3/17/07, Simson Garfinkel <si...@ac...> wrote:
> Hi. I haven't been active for a while, but now I have another paper
> that I need to get out...
Glad to have you back...
> Anyway, I need to draw a cumulative distribution function, as the
> reviewers of my last paper really nailed me to the wall for including
> histograms instead of CDFs. Is there any way to plot a CDF with
> matplotlib?
For analytic cdfs, see scipy.stats. I assume you need an empirical
cdf. You can use matplotlib.mlab.hist to compute the empirical pdf
(use normed=True to return a PDF rather than a frequency count). Then
use numpy.cumsum to do the cumulative sum of the pdf, multiplying by
the binsize so it approximates the integral.
import matplotlib.mlab
from pylab import figure, show, nx
x = nx.mlab.randn(10000)
p,bins = matplotlib.mlab.hist(x, 50, normed=True)
db = bins[1]-bins[0]
cdf = nx.cumsum(p*db)
fig = figure()
ax = fig.add_subplot(111)
ax.bar(bins, cdf, width=0.8*db)
show()

I have an array of data that were sampled with a sampling rate of
1.5625samples/sec . I want to plot these data with the x axis showing
time in
terms of hours for the major ticks and minutes for the minor ticks in my
custom made wx App. I have been fiddling around with the HourLocator and
MinuteLocator classes but it seems I can't get them to work. Do you know an
easy way to do this? I just want to plot my data in terms of the actual
time/duration of logging they represent (in hours and/or in minutes when the
plot is zoomed in or there is less than an hour's worth of samples)

1.please compare figure 1 and figure 2
2 How to change text color on Pie chart ?
(If fragment of Pie chart is black text is unreadable )
3. Text "0.5%" in figure 2 is unreadable, how correct this?
( i try use pctdistance= 1.1 but if value is format autopct='%1.4f%%' 
some text is unreadable )
#!/usr/bin/env python
from pylab import *
# make a square figure and axes
figure(1, figsize=(8,8))
ax = axes([0.1, 0.1, 0.8, 0.8])
labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
fracs = [50,25,24.5, 0.5]
figure(1)
pie(fracs, labels=labels)
legend(	loc='best', shadow=True)
# figure(2) show a some optional features. autopct is used to label
# the percentage of the pie, and can be a format string or a function
# which takes a percentage and returns a string. explode is a
# len(fracs) sequence which gives the fraction of the radius to
# offset that slice.
figure(2, figsize=(8,8))
explode=(0, 0.05, 0, 0)
pie(fracs, explode=explode, labels=labels, autopct='%1.1f%%', shadow=True)
legend(	loc='best', shadow=True)
savefig('pie_demo')
show()