plotting routines

1d_separation.py

@@ -39,45 +39,46 @@ if __name__ == '__main__':
         energy2 = problem_iteration(energy2)
         energy3 = problem_iteration(energy3)
 
+    size = 15
     plt.figure()
     # plt.plot(data, 'k-')
     f, (ax0, ax1,ax2) = plt.subplots(3, sharex=True, sharey=True)
-    plt.suptitle('diffuse components')
+    plt.suptitle('diffuse components', size=size)
 
     ax0.plot(exp(energy1.s).val, 'k-')
     ax0.yaxis.set_label_position("right")
-    ax0.set_ylabel(r'$\alpha = 1.25$')
+    ax0.set_ylabel(r'$\alpha = 1.25$', size=size)
     ax0.set_ylim(1e-1,1e3)
     ax0.set_yscale("log")
 
     ax1.plot(exp(energy2.s).val, 'k-')
     ax1.yaxis.set_label_position("right")
-    ax1.set_ylabel(r'$\alpha = 1.5$')
+    ax1.set_ylabel(r'$\alpha = 1.5$', size=size)
 
     ax2.plot(exp(energy3.s).val, 'k-')
     ax2.yaxis.set_label_position("right")
-    ax2.set_ylabel(r'$\alpha = 1.75$')
+    ax2.set_ylabel(r'$\alpha = 1.75$', size=size)
 
     plt.savefig('1d_diffuse.pdf')
 
     plt.figure()
     f, (ax0, ax1,ax2) = plt.subplots(3, sharex=True, sharey=True)
 
-    plt.suptitle('point-like components')
+    plt.suptitle('point-like components', size=size)
 
     ax0.plot(exp(energy1.u).val, 'k-')
     ax0.yaxis.set_label_position("right")
-    ax0.set_ylabel(r'$\alpha = 1.25$')
+    ax0.set_ylabel(r'$\alpha = 1.25$', size=size)
     ax0.set_ylim(1e-1,1e3)
     ax0.set_yscale("log")
 
     ax1.plot(exp(energy2.u).val, 'k-')
     ax1.yaxis.set_label_position("right")
-    ax1.set_ylabel(r'$\alpha = 1.5$')
+    ax1.set_ylabel(r'$\alpha = 1.5$', size=size)
 
     ax2.plot(exp(energy3.u).val, 'k-')
     ax2.yaxis.set_label_position("right")
-    ax2.set_ylabel(r'$\alpha = 1.75$')
+    ax2.set_ylabel(r'$\alpha = 1.75$', size=size)
 
     ax0.set_yscale("log")
 
@@ -87,21 +88,21 @@ if __name__ == '__main__':
     plt.savefig('1d_points.pdf')
     plt.figure()
     f, (ax0, ax1,ax2) = plt.subplots(3, sharex=True, sharey=True)
-    plt.suptitle('data and true components')
+    plt.suptitle('data and true components', size=size)
 
     ax0.plot(data, 'k-')
     ax0.set_yscale("log")
     ax0.set_ylim(1e-1,1e3)
     ax0.yaxis.set_label_position("right")
-    ax0.set_ylabel(r'data')
+    ax0.set_ylabel(r'data', size=size)
 
 
     ax1.plot(exp(s).val, 'k-')
     ax1.yaxis.set_label_position("right")
-    ax1.set_ylabel(r'diffuse')
+    ax1.set_ylabel(r'diffuse', size=size)
     ax2.plot(exp(u).val, 'k-')
     ax2.yaxis.set_label_position("right")
-    ax2.set_ylabel(r'point-like')
+    ax2.set_ylabel(r'point-like', size=size)
 
     # plt.ylim(1e-0)
     plt.savefig('1d_data.pdf')

hubble_separation.py

+from point_separation import build_problem, problem_iteration, load_data
+from nifty2go import *
+import numpy as np
+from matplotlib import rc
+rc('font',**{'family':'serif','serif':['Palatino']})
+rc('text', usetex=True)
+from matplotlib import pyplot as plt
+from matplotlib.colors import LogNorm
+
+
+np.random.seed(42)
+if __name__ == '__main__':
+    path = 'hst_05195_01_wfpc2_f702w_pc_sci.fits'
+    data = load_data(path)
+    alpha = 1.3
+
+
+
+    myEnergy = build_problem(data, alpha=alpha)
+    for i in range(10):
+        myEnergy = problem_iteration(myEnergy)
+
+    size = 15
+    vmin = data.min()+0.01
+    vmax = 0.1*data.max()
+    plt.figure()
+    plt.imshow(np.exp(myEnergy.s.val),norm=LogNorm(vmin=vmin, vmax=vmax))
+    cbar = plt.colorbar()
+    cbar.set_label('flux', size=size)
+    plt.title('diffuse emission', size=size)
+    plt.axis('off')
+    plt.savefig('hubble_diffuse.pdf')
+
+    plt.figure()
+    plt.imshow(np.exp(myEnergy.u.val), norm=LogNorm(vmin=vmin, vmax=vmax))
+    cbar = plt.colorbar()
+    cbar.set_label('flux', size=size)
+    plt.title('point-like emission', size=size)
+    plt.axis('off')
+    plt.savefig('hubble_point.pdf')
+
+    plt.figure()
+    plt.imshow(data, norm=LogNorm(vmin=vmin, vmax=vmax))
+    cbar = plt.colorbar()
+    cbar.set_label('flux', size=size)
+    plt.title('data', size=size)
+    plt.axis('off')
+    plt.savefig('hubble_data.pdf')
+    plt.close()

point_separation.py

@@ -40,8 +40,8 @@ def build_problem(data, alpha):
     separationEnergy = SeparationEnergy(position=initial_x, parameters=parameters)
     return separationEnergy
 
-def problem_iteration(energy):
-    controller = GradientNormController(verbose=True, tol_abs_gradnorm=0.00000001, iteration_limit=3)
+def problem_iteration(energy, iterations=3):
+    controller = GradientNormController(verbose=True, tol_abs_gradnorm=0.00000001, iteration_limit=iterations)
     minimizer = RelaxedNewton(controller=controller)
     energy, convergence = minimizer(energy)
     new_position = energy.position
@@ -69,28 +69,7 @@ def multi_problem_iteration(energy_list):
     return new_energy
 
 if __name__ == '__main__':
-    path = 'hst_05195_01_wfpc2_f702w_pc_sci.fits'
-    data = load_data(path)
-    alpha = 1.3
-
-
-    myEnergy = build_problem(data, alpha=alpha)
-    x =np.arange(0,100)
-    y = np.sin(x/12.)
-    y **=2
-    y[50] = 10
-    y[4] = 5
-    y[70] = 3
-    y += 0.1
-    myEnergy = build_problem(y, alpha=alpha)
-
-    for i in range( 100):
-
-        myEnergy = problem_iteration(myEnergy)
-        # plt.viridis()
-        # plt.imsave('points0.png',myEnergy.u.val)
-        # plt.imsave('maps0.png',(myEnergy.s).val)
-        # plt.imsave('data0.png',myEnergy.d.val)
+    pass
 
 
 

rgb_separation.py

@@ -3,10 +3,11 @@ from matplotlib import pyplot as plt
 import numpy as np
 
 if __name__ == '__main__':
-    data = plt.imread('eso1242a.jpg')
+    # data = plt.imread('eso1242a.jpg')
+    data = plt.imread('10Keso1242a.tif')
     data = data.astype(float)
     data = data.clip(0.0001)
-    energy_list = build_multi_problem(data, 1.35)
+    energy_list = build_multi_problem(data, 1.2)
 
     for i in range(10):
         energy_list = multi_problem_iteration(energy_list)