phatime.py 文件源码

def phaserate(plotar, ms2mappings):
    if plotar.plotType!='phatime':
        raise RuntimeError, "phaserate() cannot run on plot type {0}".format( plotar.plotType )
    spm = ms2mappings.spectralMap
    # iterate over all plots and all data sets within the plots
    for k in plotar.keys():
        for d in plotar[k].keys():
            # get a reference to the data set
            dsref = plotar[k][d]
            # get the full data set label - we have access to all the data set's properties (FQ, SB, POL etc)
            n     = plots.join_label(k, d)
            # fit a line through the unwrapped phase 
            unw    = numpy.unwrap(numpy.deg2rad(dsref.yval))
            coeffs = numpy.polyfit(dsref.xval, unw, 1)
            # evaluate the fitted polynomial at the x-loci
            extray = numpy.polyval(coeffs, dsref.xval)
            # here we could compute the reliability of the fit
            diff   = unw - extray
            ss_tot = numpy.sum(numpy.square(unw - unw.mean()))
            ss_res = numpy.sum(numpy.square(diff))
            r_sq   = 1.0 - ss_res/ss_tot
            # compare std deviation and variance in the residuals after fit
            std_r  = numpy.std(diff)
            var_r  = numpy.var(diff)
            f      = spm.frequencyOfFREQ_SB(n.FQ, n.SB)
            rate   = coeffs[0]
            if var_r<std_r:
                print "{0}: {1:.8f} ps/s @ {2:5.4f}MHz [R2={3:.3f}]".format(n, rate/(2.0*numpy.pi*f*1.0e-12), f/1.0e6, r_sq )
                # before plotting wrap back to -pi,pi and transform to degrees
                dsref.extra = [ drawline_fn(n, dsref.xval, numpy.rad2deg(do_wrap(extray))) ]