On Thu, Jul 23, 2009 at 8:16 PM, D Whitewhite.davi...@gmail.com wrote:
I'm having no luck getting the bins option to pylab.hist() to work.
Here's an example:
fish_data=[random() for i in range(100)]
import pylab
import numpy
divats = numpy.arange(0.0,1.0,0.1)
pylab.hist(fish_data,
D White wrote:
I'm having no luck getting the bins option to pylab.hist() to work.
Here's an example:
fish_data=[random() for i in range(100)]
import pylab
import numpy
divats = numpy.arange(0.0,1.0,0.1)
pylab.hist(fish_data, bins=divats)
pylab.savefig('sage.png')
You can do lots
This should be R's home base:
# first we compute some data
b = 10
st = []
for i in range(500):
A = random_matrix(ZZ,160,160, x=-2**b, y=2**b)
t = cputime()
E = A.echelon_form()
st.append(cputime(t))
#now we plot a histogram using R
from rpy import r
On Tue, Mar 25, 2008 at 6:44 AM, Martin Albrecht
[EMAIL PROTECTED] wrote:
This should be R's home base:
# first we compute some data
b = 10
st = []
for i in range(500):
A = random_matrix(ZZ,160,160, x=-2**b, y=2**b)
t = cputime()
E = A.echelon_form()
st.append(cputime(t))
One way is, for example,
sage: J = range(3)
sage: A = [ZZ(i^2)+1 for i in J]
sage: s = IndexedSequence(A,J)
sage: s.plot_histogram()
using http://www.sagemath.org/hg/sage-main/file/211b127eab5d/sage/gsl/dft.py
I think there is another way but I don't remember the details. I think
this question
