On 7/9/2010 12:02 AM, per freem wrote:
> How can I plot the empirical CDF of an array of numbers in matplotlib
> in Python?
I recalled David Huard posted the below,
which apparently was once in the sandbox...
hth,
Alan Isaac
def empiricalcdf(data, method='Hazen'):
"""Return the empirical cdf.
Methods available (here i goes from 1 to N)
Hazen: (i-0.5)/N
Weibull: i/(N+1)
Chegodayev: (i-.3)/(N+.4)
Cunnane: (i-.4)/(N+.2)
Gringorten: (i-.44)/(N+.12)
California: (i-1)/N
:see:
http://svn.scipy.org/svn/scipy/trunk/scipy/sandbox/dhuard/stats.py
:author: David Huard
"""
i = np.argsort(np.argsort(data)) + 1.
nobs = len(data)
method = method.lower()
if method == 'hazen':
cdf = (i-0.5)/nobs
elif method == 'weibull':
cdf = i/(nobs+1.)
elif method == 'california':
cdf = (i-1.)/nobs
elif method == 'chegodayev':
cdf = (i-.3)/(nobs+.4)
elif method == 'cunnane':
cdf = (i-.4)/(nobs+.2)
elif method == 'gringorten':
cdf = (i-.44)/(nobs+.12)
else:
raise 'Unknown method. Choose among Weibull, Hazen, Chegodayev,
Cunnane, Gringorten and California.'
return cdf
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