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()