def pdf1d(d, imp, bins, smooth, color):
from scipy import ndimage
pylab.xlim([bins[0], bins[-1]])
# Bin the data in 1D, return histogram h(x):
h, x = numpy.histogram(d,
weights=imp,
bins=bins,
range=[bins[0], bins[-1]])
norm = numpy.sum(h)
h = h / norm
# Report some statistics:
median, errplus, errminus = pappy.compress_histogram(h, x, ci=68)
result = pappy.format_point_estimate(median, errplus, errminus)
# Smooth and normalise the histogram into a PDF:
p = ndimage.gaussian_filter1d(h, smooth)
norm = numpy.sum(p)
p = p / norm
# Plot:
pylab.plot(x[:-1], p, drawstyle='line', color=color)
return p.max(), result
def pdf1d(d,imp,bins,smooth,color): from scipy import ndimage pylab.xlim([bins[0],bins[-1]]) # Bin the data in 1D, return histogram h(x): h,x = numpy.histogram(d,weights=imp,bins=bins,range=[bins[0],bins[-1]]) norm = numpy.sum(h) h = h/norm # Report some statistics: median,errplus,errminus = pappy.compress_histogram(h,x,ci=68) result = pappy.format_point_estimate(median,errplus,errminus) # Smooth and normalise the histogram into a PDF: p = ndimage.gaussian_filter1d(h,smooth) norm = numpy.sum(p) p = p/norm # Plot: pylab.plot(x[:-1],p,drawstyle='line',color=color) return p.max(),result
mean,stdev,Neff,N95 = pappy.meansd(d,wht=wht)
if histogram:
dylimits = numpy.zeros([2])
dylimits[0] = mean - 10*stdev
dylimits[1] = mean + 10*stdev
nbins = 161
bins = numpy.linspace(dylimits[0],dylimits[1],nbins)
h,x = numpy.histogram(d,weights=wht,bins=bins,range=[bins[0],bins[-1]])
norm = numpy.sum(h)
h = h/norm
median,errplus,errminus = pappy.compress_histogram(h,x,ci=cred)
else:
median,errplus,errminus = pappy.compress_samples(d,wht=wht,ci=cred)
estimate = pappy.format_point_estimate(median,errplus,errminus)
if longwinded:
print " Par no.",col+1,":",labels[col].strip(),"=",estimate
else:
print estimate
if vb:
print " Par no.",col+1," mean,stdev,Neff,N95 = ",mean,stdev,Neff,N95
# --------------------------------------------------------------------
return
# ======================================================================
if __name__ == '__main__':
