Thierry, You need either scipy or rpy2 (and R) to do this. I've attached some code below. Please keep in mind that I've written for the general case of having a censored data set, therefore I rely on masked arrays from numpy.ma and scipy.stats.mstats -- but I have apply the mask midway through the process, which is different than the numpy's standard operating procedure. Let me know if any of this isn't clear.
I also have code that generates a quick comparison of the results from scipy.stats.mstats and ryp2+R, if you're interested. HTH, -paul # code... import matplotlib.pyplot as pl import scipy.stats as st import numpy as np def censoredProbPlot(data, mask): ppos = st.mstats.plotting_positions(data) qntl = st.distributions.norm.ppf(ppos) qntlMask = np.ma.MaskedArray(qntl, mask=mask) dataMask = np.ma.MaskedArray(data, mask=mask) fit = st.mstats.linregress(dataMask, qntlMask) mu = -fit[1] sigma = fit[0] d_ = np.linspace(np.min(data),np.max(data)) q_ = sigma * d_ - mu maskedProbPlot = {"mskData" : dataMask, "mskQntl" : qntlMask, "unmskData" : data, "unmskQntl" : qntl, "bestFitD" : d_, "bestFitQ" : q_, "mu" : mu, "sigma" : sigma} return maskedProbPlot if 1: #~~ you need to put your data here: #data = np.array([]) #mask = np.array([],dtype=bool) mpp = censoredProbPlot(data, mask) fig = pl.figure() ax1 = fig.add_subplot(111) ax1.plot(mpp['mskQntl'], mpp['mskData'], 'ko', ms=6, label='Detected Samples') ax1.plot(mpp['unmskQntl'], mpp['unmskData'], 'r.', ms=6, label='Raw Samples') ax1.plot(mpp['bestFitQ'], mpp['bestFitD'], 'b-', lw=2) fig.savefig('example_censoredProbPlot.png') > -----Original Message----- > From: MONTAGU Thierry [mailto:thierry.mont...@cea.fr] > Sent: Friday, May 21, 2010 6:37 AM > To: matplotlib-users@lists.sourceforge.net > Subject: [Matplotlib-users] qqplot > > hi all > > has anyone ever tried to make a quantile-quantile plot with pylab? > is there any build in function named say "qqplot" available ? > > thanks > Thierry > > ------------------------------------------------------------------------- > ----- > > _______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-users ------------------------------------------------------------------------------ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users