def test_scinv_npts(self, nplot, show=False, reload=False, type="png"):
"""
Test accuracy as a function of the numer of points used in the
integration.
"""
dzl = 0.015
zlmin = 0.02
zlmax = 0.6
from biggles import Points, FramedPlot, PlotKey, Table, Histogram, Curve
from time import time
import lensing
import pcolors
if self.data is None or reload:
self.load_example_data()
# this is old ScinvCalculator, need to make work
# with new one
scalc1000 = ScinvCalculator(self.zs, dzl, zlmin, zlmax, npts=1000)
nptsvals = [100, 200, 300, 400, 500, 600, 700, 800, 900]
numcheck = len(nptsvals)
# colors=['black','magenta','blue','green','orange','red']
colors = pcolors.rainbow(len(nptsvals), "hex")
scalc = []
for npts in nptsvals:
scalc.append(ScinvCalculator(self.zs, dzl, zlmin, zlmax, npts=npts))
times = numpy.zeros(numcheck, dtype="f8")
time1000 = 0.0
# we'll fill this in
scinv_all = numpy.zeros((numcheck, scalc1000.zlvals.size))
xlim = [0, scalc1000.zsvals.max()]
for i in xrange(nplot):
pz = self.data["pofz"][i]
print("Doing 1000...", end="")
tm0 = time()
scinv1000 = scalc1000.calc_mean_scinv(pz)
time1000 += time() - tm0
print("done")
for j in xrange(numcheck):
npts = nptsvals[j]
print("%d " % npts, end="")
tm0 = time()
scinv_all[j, :] = scalc[j].calc_mean_scinv(pz)
times[j] += time() - tm0
print("\nplotting")
# plot the p(z)
tab = Table(3, 1)
binsize = scalc1000.zsvals[1] - scalc1000.zsvals[0]
pzh = Histogram(pz, x0=scalc1000.zsvals[0], binsize=binsize)
plt_pzh = FramedPlot()
plt_pzh.xrange = xlim
plt_pzh.xtitle = r"$z_s$"
plt_pzh.ytitle = r"$P(z_s)$"
plt_pzh.add(pzh)
tab[0, 0] = plt_pzh
# plot scinv for each npts value
plt_scinv = FramedPlot()
plt_scinv.xrange = xlim
scinv_plots = []
for j in xrange(numcheck):
npts = nptsvals[j]
p = Curve(scalc[j].zlvals, scinv_all[j, :], type="solid", color=colors[j])
p.label = "npts: %d" % npts
plt_scinv.add(p)
scinv_plots.append(p)
scinv_key = PlotKey(0.95, 0.9, scinv_plots, halign="right")
plt_scinv.add(scinv_key)
plt_scinv.ylabel = r"$\langle \Sigma_{crit}^{-1}(z_{lens}) \rangle$"
plt_scinv.xlabel = r"$z_{lens}$"
plt_scinv.yrange = [0, 2.1e-4]
tab[1, 0] = plt_scinv
# ratio to 1000 points
plt_rat = FramedPlot()
plt_rat.xrange = xlim
plt_rat.yrange = [1 - 1.0e-2, 1 + 1.0e-2]
rat_plots = []
for j in xrange(numcheck):
npts = nptsvals[j]
w = where1(scinv1000 > 0)
ratio = scinv_all[j, w] / scinv1000[w]
# ratio=scinv_all[j,:]/scinv1000[:]
p = Curve(scalc[j].zlvals[w], ratio, type="solid", color=colors[j])
p.label = "npts: %d" % npts
plt_rat.add(p)
rat_plots.append(p)
key = PlotKey(0.95, 0.9, rat_plots, halign="right")
plt_rat.add(key)
plt_rat.ylabel = r"$\langle \Sigma_{crit}^{-1} \rangle / \langle \Sigma_{crit}^{-1} \rangle_{1000}$"
plt_rat.xlabel = r"$z_{lens}$"
tab[2, 0] = plt_rat
if show:
tab.show()
plotfile = self.npts_plot_file(i, type)
print("writing to file:", plotfile)
if type == "png":
tab.write_img(1000, 1000, plotfile)
else:
tab.write_eps(plotfile)
print("time npts=1000:", time1000)
for j in xrange(numcheck):
npts = nptsvals[j]
print("time npts=%s: %s" % (npts, times[j]))
def test_scinv_dz(self, beg, end, yrange=[0, 2.1e-4], show=False, reload=False, type="png"):
"""
Test accuracy of interpolating scinv as a function of dzl, the
lens redshift spacing.
"""
import biggles
from biggles import Points, FramedPlot, PlotKey, Table, Histogram, Curve
from time import time
import lensing
import pcolors
biggles.configure("default", "fontface", "HersheySans")
biggles.configure("default", "fontsize_min", 1.3)
zsmin = self.zs[0]
zsmax = self.zs[-1]
zlmin = 0.00
zlmax = 1.0
# dzl_vals = numpy.linspace(0.001,0.015,10)
dzl_vals = numpy.linspace(0.001, 0.015, 4)
nzl_vals = ((zlmax - zlmin) / dzl_vals).astype("i8")
numcheck = len(dzl_vals)
colors = pcolors.rainbow(numcheck, "hex")
scalc = []
for nzl in nzl_vals:
s = ScinvCalculator(zlmin, zlmax, nzl, zsmin, zsmax, npts=100)
scalc.append(s)
times = numpy.zeros(numcheck, dtype="f8")
# we'll fill this in
# scinv_all = numpy.zeros( (numcheck, scalc[0].zlvals.size) )
xlim = [0, zsmax]
for i in xrange(beg, end):
scinv_all = []
pz = self.data["pofz"][i]
# print(pz)
for j in xrange(numcheck):
dzl = dzl_vals[j]
nzl = nzl_vals[j]
print(" nzl: %s dzl: %g" % (nzl, dzl))
tm0 = time()
# scinv_all[j,:] = scalc[j].calc_mean_scinv(pz)
sc = scalc[j].calc_mean_scinv(self.zs, pz)
# sc=sc.clip(min=0.0)
# print("sc",j,sc)
scinv_all.append(sc)
times[j] += time() - tm0
print("\nplotting")
# plot the p(z)
tab = Table(3, 1)
binsize = self.zs[1] - self.zs[0]
pzh = Histogram(pz, x0=self.zs[0], binsize=binsize)
plt_pzh = FramedPlot()
plt_pzh.xrange = xlim
plt_pzh.xtitle = r"$z_s$"
plt_pzh.ytitle = r"$P(z_s)$"
plt_pzh.add(pzh)
tab[0, 0] = plt_pzh
# plt_pzh.show()
# plot scinv for each dzl
plt_scinv = FramedPlot()
plt_scinv.xrange = xlim
scinv_plots = []
for j in xrange(numcheck):
dzl = dzl_vals[j]
nzl = nzl_vals[j]
p = Curve(scalc[j].zlvals, scinv_all[j], type="solid", color=colors[j])
p.label = r"$nz_{lens}: %s dz_{lens}: %0.3f$" % (nzl, dzl)
plt_scinv.add(p)
scinv_plots.append(p)
scinv_key = PlotKey(0.95, 0.9, scinv_plots, halign="right")
plt_scinv.add(scinv_key)
plt_scinv.ylabel = r"$\Sigma_{crit}^{-1}(z_{lens})$"
plt_scinv.xlabel = r"$z_{lens}$"
plt_scinv.yrange = yrange
# plt_scinv.show()
tab[1, 0] = plt_scinv
# %diff to best dz
plt_pdiff = FramedPlot()
plt_pdiff.xrange = xlim
plt_pdiff.yrange = [-0.05, 0.05]
pdiff_plots = []
zl_interp = numpy.linspace(zlmin, zlmax, 1000)
scinv_interp_best = esutil.stat.interplin(scinv_all[0], scalc[0].zlvals, zl_interp)
w = where1(scinv_interp_best > 0)
for j in xrange(numcheck):
dzl = dzl_vals[j]
nzl = nzl_vals[j]
scinv_interp = esutil.stat.interplin(scinv_all[j], scalc[j].zlvals, zl_interp)
if w.size > 0:
pdiff = scinv_interp[w] / scinv_interp_best[w] - 1.0
p = Curve(zl_interp[w], pdiff, type="solid", color=colors[j])
else:
pdiff = numpy.ones(scinv_interp.size)
p = Curve(zl_interp, pdiff, type="solid", color=colors[j])
p.label = r"$nz_{lens}: %s dz_{lens}: %0.3f$" % (nzl, dzl)
plt_pdiff.add(p)
pdiff_plots.append(p)
key = PlotKey(0.95, 0.9, pdiff_plots, halign="right")
plt_pdiff.add(key)
plt_pdiff.ylabel = r"$\Sigma_{crit}^{-1} / \Sigma_{crit}^{-1}_{best} - 1$"
plt_pdiff.xlabel = r"$z_{lens}$"
tab[2, 0] = plt_pdiff
if show:
tab.show()
plotfile = self.dzl_plot_file(i, type)
print("writing to file:", plotfile)
if type == "png":
tab.write_img(1000, 1000, plotfile)
else:
tab.write_eps(plotfile)
for j in xrange(numcheck):
dzl = dzl_vals[j]
print("time dzl=%s: %s" % (dzl, times[j]))
