def plotParamMargs(x, nbins=50): r = bnmin1utils.ChainToArray(x) pyxplot.histogram( [[r[:, 0] * 0.5, ""]], "o/mcmc_amp.eps", width=10, xlabel="Amplitude", nbins=nbins, relative=True, key=None ) pyxplot.histogram( [[r[:, 3], ""]], "o/mcmc_sigma.eps", width=10, xlabel="Width", nbins=nbins, relative=True, key=None ) pyxplot.histogram( [[r[:, 1], ""]], "o/mcmc_pos.eps", width=10, xlabel="Position", nbins=nbins, relative=True, key=None ) pyxplot.histogram( [[r[:, 4], ""]], "o/mcmc_rot.eps", width=10, xlabel="Rotation", nbins=nbins, relative=True, key=None ) pl = ["Amplitude", "x-position", "y-position", "width", "squint", "rotation"] for i in range(len(pl)): pyxplot.histogram( [[r[:, i], ""]], "o/mcmc-%i.eps" % (i,), width=10, xlabel="Rotation", nbins=nbins, relative=True, key=None ) for j in range(i + 1, len(pl)): twod.hist2d(r[:, i], r[:, j], "o/mcmc-%i-%i.eps" % (i, j), xlabel=pl[i], ylabel=pl[j])
def plotmode(n=1000): xx, xy = [], [] for i in range(n): x = maxpix(MkIllMap(256)) xx.append(x[0]) xy.append(x[1]) pyxplot.histogram([[xx, "x"], [xy, "y"]], "o/pixpos.eps", width=10, xlabel="position") return xx, xy
def plotchi(): xlabel = r"$-\log P(x|\theta)$" d = numpy.array(pickle.load(open(("o/ampbiasdata.p")))) d2 = numpy.array(pickle.load(open(("o/ampbiasdata-npos.p")))) pyxplot.histogram( [[d[0, :, 2] * 4, ""], [d2[0, :, 2] * 4, ""]], "o/chisqhist.eps", width=10, xlabel=xlabel, nbins=50 ) obsdst.cuml([[d[0, :, 2] * 4, ""], [d2[0, :, 2] * 4, ""]], "o/chisqcuml.eps", xlabel=xlabel, fmin=0.48, fmax=0.52)
def PlotAmpBias(fin="o/ampbiasdata.p", fout="o/amp"): r, r2 = pickle.load(open(fin)) noise = 0.5 print "%shist-%i.eps" % (fout, noise * 10) print "o/%scuml-%i.eps" % (fout, noise * 10) pyxplot.histogram([[r, ""], [r2, ""]], "%shist-%i.eps" % (fout, noise * 10), width=10, xlabel="Amplitude", nbins=50) obsdst.cuml([[r, ""], [r2, ""]], "%scuml-%i.eps" % (fout, noise * 10), xlabel="Amplitude", fmin=0.4, fmax=0.6) obsdst.cuml([[r, ""], [r2, ""]], "%suml-%i-whole.eps" % (fout, noise * 10), xlabel="Amplitude")
def plotSinlgeParDist(din, parname, fnameout, burn=0): """ Plot the distribution of a single parameter """ d=din.data.field(parname) x=d[burn*len(d):] pyxplot.histogram( [ (x, "")], fnameout, xax=pyxplot.axis(escapeAxisName(parname)), width=pyxplot.MNRAS_SC, nbins=20, key=None)
def ElHist(): "Compute histogram of measured elevations" res = [] for scandir , obsds in izip(allscans , obsscans) : el=pyfits.open(obsds)[0].header["meanel"] res.append(el) res.sort() pyxplot.histogram( [ ( res , "" ) ], "plots/el-hist.eps", width=pyxplot.THESIS , key=None , nbins=9, xax=pyxplot.axis(r"$\theta\,$(deg)", xmin=0 , xmax=90) )
def plotMCMCbias(): x = readMapMCMC() pyxplot.histogram([[x, ""]], "o/mcmc_bias.eps", width=10, xlabel="Amplitude", nbins=100, relative=True, key=None)