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Well I did tried this but it didn't work out. It actually removes the 
black color from the color_cycle but the pie still prints it. Moreover I 
noticed that this color_cycle has 7 colors that repeats after the first 
7 so it won't do what I want. I will need to find another way to set the 
colors or just avoid the pie.
Thanks though for the help!
Regards
Grigoris
On 11/30/2011 06:09 PM, Tony Yu wrote:
> On Wed, Nov 30, 2011 at 10:34 AM, Grigoris Maravelias 
> <gr....@gm... <mailto:gr....@gm...>> wrote:
>
> Hello list!
>
> I have a question regarding the colors of the pie diagram of
> matplotlib. When no colors are assigned then the pie function
> automatically selects some colors, like the example image I have
> attached. But in this case the black color covers the text. How
> can we avoid this?Is there an easy (perhaps?) way to exclude a color?
>
>
> I don't really use pie charts, but I think it just uses the default 
> color cycle. This can be altered by changing the rcParams:
>
> >>> import matplotlib.pyplot as plt
> >>> plt.rcParams['axes.color_cycle'].remove('k')
>
> The color_cycle parameter is just a python list, so I use list.remove 
> to remove black (which is the letter 'k' since 'b' is blue). There are 
> other ways of setting rcParams, as detailed in the help files 
> <http://matplotlib.sourceforge.net/users/customizing.html> (Note that 
> `rc` and `rcParams` is in both matplotlib.pyplot and the main 
> matplotlib package).
>
> Best,
> -Tony

On Wed, Nov 30, 2011 at 11:42 AM, Jeffrey Blackburne <
jbl...@al...> wrote:
> Hi Steven,
>
> Try this:
>
> import numpy as np
> import numpy.random
> import matplotlib as mpl
> import matplotlib.pyplot as plt
>
> x = np.random.randn(1000)
> h, binedg = np.histogram(x, 10)
>
> wid = binedg[1:] - binedg[:-1]
> plt.bar(binedg[:-1], h/float(x.size), width=wid)
>
>
> On Nov 30, 2011, at 10:25 AM, Steven Boada wrote:
>
> > Hi Users,
> >
> > I'm looking to make a histogram that is normalized by the total number
> > of items shown in the histogram. For example:
> >
> > Let's say that I have an array 1000 items long. If I make a
> > histogram in
> > the normal way hist(x,10) then I get a histogram showing the total
> > number of items in each bin. What I want to do is take that total
> > number
> > in each bin and divide them by 1000 and then make the plot.
> >
> > So if one of my bins has 350 objects in it, then it would be
> > changed to
> > 0.35.
> >
> > Another way to say it would be that I want the height of the histogram
> > to represent the fraction of the total. I am pretty sure that this is
> > different than using the "normed=True" flag, but I couldn't find
> > anyone
> > talking about this when I searched.
> >
> > Thanks
> >
> > Steven
>
>
One option: You can plot the normal `hist` and then change the tick labels
appropriately. Here's some code for accomplishing that:
#~~~
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter, MultipleLocator
N = 350
ytick_step = 0.05
data = np.random.normal(size=N)
def norm_num(x, pos):
 return '%g' % (x / float(N))
locator = MultipleLocator(N * ytick_step)
formatter = FuncFormatter(norm_num)
f, ax = plt.subplots()
ax.yaxis.set_major_formatter(formatter)
ax.yaxis.set_major_locator(locator)
ax.hist(data)
plt.show()
#~~~
Note that the formatter object is all you need to change to the desired
scale. But, that result will usually look ugly, because you'll get tick
labels with long, ugly floating point numbers. The locator object fixes
that issue.
Best,
-Tony

Hi Steven,
Try this:
import numpy as np
import numpy.random
import matplotlib as mpl
import matplotlib.pyplot as plt
x = np.random.randn(1000)
h, binedg = np.histogram(x, 10)
wid = binedg[1:] - binedg[:-1]
plt.bar(binedg[:-1], h/float(x.size), width=wid)
On Nov 30, 2011, at 10:25 AM, Steven Boada wrote:
> Hi Users,
>
> I'm looking to make a histogram that is normalized by the total number
> of items shown in the histogram. For example:
>
> Let's say that I have an array 1000 items long. If I make a 
> histogram in
> the normal way hist(x,10) then I get a histogram showing the total
> number of items in each bin. What I want to do is take that total 
> number
> in each bin and divide them by 1000 and then make the plot.
>
> So if one of my bins has 350 objects in it, then it would be 
> changed to
> 0.35.
>
> Another way to say it would be that I want the height of the histogram
> to represent the fraction of the total. I am pretty sure that this is
> different than using the "normed=True" flag, but I couldn't find 
> anyone
> talking about this when I searched.
>
> Thanks
>
> Steven
>
>
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On Wed, Nov 30, 2011 at 10:34 AM, Grigoris Maravelias <
gr....@gm...> wrote:
> Hello list!
>
> I have a question regarding the colors of the pie diagram of matplotlib.
> When no colors are assigned then the pie function automatically selects
> some colors, like the example image I have attached. But in this case the
> black color covers the text. How can we avoid this?Is there an easy
> (perhaps?) way to exclude a color?
>
I don't really use pie charts, but I think it just uses the default color
cycle. This can be altered by changing the rcParams:
>>> import matplotlib.pyplot as plt
>>> plt.rcParams['axes.color_cycle'].remove('k')
The color_cycle parameter is just a python list, so I use list.remove to
remove black (which is the letter 'k' since 'b' is blue). There are other
ways of setting rcParams, as detailed in the help
files<http://matplotlib.sourceforge.net/users/customizing.html>(Note
that `rc` and `rcParams` is in both matplotlib.pyplot and the main
matplotlib package).
Best,
-Tony

i use something like that:
from datetime import datetime, timedelta
import matplotlib.pyplot as pl
import matplotlib.ticker as ticker
import matplotlib.dates as mdates
dates1 = [datetime(2005,5,11)+n*timedelta(days=1) for n in range(500)]
dates2 = [datetime(...
ax1 = pl.subplot(2,1,1)
ax1.plot(dates1, y1, 'r')
ax1.fmt_xdata = mdates.DateFormatter('%Y-%m-%d')
ax2 = pl.subplot(2,1,2)
ax2.plot(dates2, ...
that's what you want?
regards, yoshi

Hello list!
I have a question regarding the colors of the pie diagram of matplotlib. 
When no colors are assigned then the pie function automatically selects 
some colors, like the example image I have attached. But in this case 
the black color covers the text. How can we avoid this?Is there an easy 
(perhaps?) way to exclude a color?
Of course there is not problem if I specifically select the colors but I 
do not know how many parts exist beforehand (and I would like to assign 
it automatically).
Thanks!
Regards
Grigoris

Hi Users,
I'm looking to make a histogram that is normalized by the total number 
of items shown in the histogram. For example:
Let's say that I have an array 1000 items long. If I make a histogram in 
the normal way hist(x,10) then I get a histogram showing the total 
number of items in each bin. What I want to do is take that total number 
in each bin and divide them by 1000 and then make the plot.
So if one of my bins has 350 objects in it, then it would be changed to 
0.35.
Another way to say it would be that I want the height of the histogram 
to represent the fraction of the total. I am pretty sure that this is 
different than using the "normed=True" flag, but I couldn't find anyone 
talking about this when I searched.
Thanks
Steven

I have a short script to plot 20 years of river flow data. I can use
the plot_date command to create a plot, using this snippet:
f = figure()
ax1 = f.add_subplot(111)
ax1.plot_date(dates0,y1,'g', label='observed', xdate=True,visible=True)
ax1.plot_date(dates1,y2,'r', label='simulated', xdate=True,visible=True)
years  = YearLocator(1, month=6, day=30)  # every year
months  = MonthLocator(1) # every month
ax1.set_xlim(date2num(datetime.date(1990,1,1)),date2num(datetime.date(1999,12,31)))
ax1.xaxis.set_major_locator(years)
ax1.xaxis.set_minor_locator(months)
labels = ax1.get_xticklabels()
setp(labels, fontsize=8,visible=True)
The problem is with the x-axis (time axis) labels when I add a second
subplot, to add the next time segment. I change the above to ax1 =
f.add_subplot(211), and then:
ax2 = f.add_subplot(212)
ax2.plot_date(dates0,y1,'g') #plots the time series
ax2.plot_date(dates1,y2,'r') #need to call twice, unlike plot,
plot_date takes one set
ax2.set_xlim(date2num(datetime.date(2000,1,1)),date2num(datetime.date(2009,12,31)))
ax2.xaxis.set_major_locator(years)
ax2.xaxis.set_minor_locator(months)
setp(labels, fontsize=8,visible=True)
The x-axis labels only appear for the last subplot. I'm guessing that
plot_date assumes that more than one subplot must share a time axis.
There must be a simple way to stop plot_date from doing this, if this
is indeed the problem. Any guidance would be appreciated.
Thanks,
Ed

On Mon, Nov 28, 2011 at 10:49 PM, Jae-Joon Lee <lee...@gm...> wrote:
> This is a bug. In the current implementation, "annotate" has a
> side-effect that modifies the arrowprops dictionary.
For a future reference, this should now be fixed in the v1.1.x branch
which also has been merged into the master branch.
https://github.com/matplotlib/matplotlib/commit/b3a2ab77c89fdb3ab860edeb1a781b5307347070
Regards,
-JJ