def plot(self):
super(ShearCorrelationMinusPlot, self).plot()
nbin = 0
for i in range(1, 100):
filename = self.file_path("shear_xi_minus",
"bin_{0}_{0}".format(i))
if os.path.exists(filename):
nbin += 1
else:
break
if nbin == 0:
IOError("No data for plot: %s" % self.__class__.__name__[:-4])
theta = self.load_file("shear_xi_minus", "theta")
sz = 1.0 / (nbin + 2)
for i in range(1, nbin + 1):
for j in range(1, i + 1):
rect = (i * sz, j * sz, sz, sz)
self.figure.add_axes(rect)
#pylab.ploy()
#pylab.subplot(nbin, nbin, (nbin*nbin)-nbin*(j-1)+i)
xi = self.load_file("shear_xi_minus",
"bin_{0}_{1}".format(i, j))
pylab.loglog(theta, xi)
pylab.xlim(1e-4, 1e-1)
pylab.ylim(2e-7, 1e-3)
if i == 1 and j == 1:
pylab.xlabel("$\\theta$")
pylab.ylabel("$\\xi_+(\\theta)$")
else:
pylab.gca().xaxis.set_ticklabels([])
pylab.gca().yaxis.set_ticklabels([])
pylab.gca().tick_params(length=0.0, which='minor')
pylab.gca().tick_params(length=3.0, which='major')
pylab.gca().tick_params(labelsize=10)
pylab.text(1.5e-3,
1.8e-4,
"(%d,%d)" % (i, j),
fontsize=8,
color='red')
pylab.grid()
def plot_section(self, section):
nbin = 0
for i in range(1, 100):
filename = self.file_path(section, "bin_{0}_{0}".format(i))
if os.path.exists(filename):
nbin += 1
else:
break
if nbin == 0:
IOError("No data for plot: %s" % self.__class__.__name__[:-4])
ell = self.load_file(section, "ell")
sz = 1.0 / (nbin + 2)
for i in range(1, nbin + 1):
for j in range(1, i + 1):
rect = (i * sz, j * sz, sz, sz)
self.figure.add_axes(rect)
#pylab.ploy()
#pylab.subplot(nbin, nbin, (nbin*nbin)-nbin*(j-1)+i)
cl = self.load_file(section, "bin_{0}_{1}".format(i, j))
if all(cl <= 0):
cl *= -1
pylab.loglog(ell, ell * (ell + 1.) * cl / 2 / np.pi)
pylab.ylim(*self.ylim)
if i == 1 and j == 1:
pylab.xlabel("$\\ell$")
pylab.ylabel("$\\ell (\\ell+1) C_\\ell / 2 \\pi$")
else:
pylab.gca().xaxis.set_ticklabels([])
pylab.gca().yaxis.set_ticklabels([])
pylab.gca().tick_params(length=0.0, which='minor')
pylab.gca().tick_params(length=3.0, which='major')
pylab.gca().tick_params(labelsize=10)
if section == "shear_cl":
pylab.text(1.5 * ell.min(),
1.8e-4,
"(%d,%d)" % (i, j),
fontsize=8,
color='red')
pylab.grid()