def plot_pdf(kernel=exppow_lim(), N=10):
my_pdf = optsky.build_pdf(kernel)
X, Y = np.meshgrid(np.linspace(-1.0,1.0,N), np.linspace(-1.0,1.0,N))
for model_emag in np.linspace(0.0,0.5,6):
Z = my_pdf(np.array([model_emag*np.ones(X.size), X.ravel(), Y.ravel()]))
Z = Z.reshape(X.shape)
plt.figure()
plt.pcolor(X, Y, Z)
plt.colorbar()
plt.hold(True)
plt.scatter(model_emag, 0.0, s=15, color='white')
plt.axis([-1.0,1.0,-1.0,1.0])
#plt.title("model_emag " + str(model_emag))
plt.xlabel(r'$\tilde{e}_1$',fontsize=18)
plt.ylabel(r'$\tilde{e}_2$',fontsize=18)
plt.show()
def plot_likelihood(skynum, pdf=None, kernel=exppow_lim(), N=20):
if (pdf == None):
pdf = optsky.build_pdf(kernel)
nhalo, halo_coords = read_halos(skynum)
sky = read_sky(skynum)
gal_x, gal_y, gal_e1, gal_e2 = sky.T
f = optsky.fwrapper(gal_x=gal_x, gal_y=gal_y,
gal_e1=gal_e1, gal_e2=gal_e2,
nhalo=nhalo, kernel=kernel, pdf=pdf)
margin = 0
xplot = np.linspace(0.0, 4200.0, N)
yplot = np.linspace(0.0, 4200.0, N)
X,Y = np.meshgrid(xplot,yplot)
Z = np.zeros(X.shape)
for idx, x in enumerate(xplot):
for idy, y in enumerate(yplot):
Z[idy, idx] = f(np.array([x,y]))
#plt.contourf(X, Y, Z)
plt.pcolor(X, Y, Z)
plt.colorbar()
plt.hold(True)
nhalo, halo_coords = read_halos(skynum)
for ihalo in range(nhalo):
plt.scatter(halo_coords[ihalo], halo_coords[ihalo + nhalo],\
color='white', s=50)
plt.axis((min(gal_x)-margin, max(gal_x)+margin, min(gal_y)-margin, max(gal_y)+margin))
plt.show()
