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)
