Update Trapz.py

Trapz.py

@@ -3,6 +3,8 @@
 import matplotlib.pyplot as plt
 from scipy.integrate import ode
 from scipy.interpolate import interp1d
+from scipy.interpolate import UnivariateSpline
+from scipy import interpolate
 
 c=299792458*100  # cm/s
 
@@ -27,30 +29,41 @@ def sigma(energy_nu, g, M, m=1.e-10):  # cm^2
     return (g**4/(16*np.pi))*(2*energy_nu*m)/((2*energy_nu*m-M**2)**2+((M**4*g**4)/(16*np.pi**2)))* 0.389379e-27
 
 
-def Adiabatic_Energy_Losses(z, energy_nu, nu_density):
-    return H(z)*nu_density
+def Adiabatic_Energy_Losses(z, energy_nu, nu_density, lst_energy_nu, interp_nu_density):
+    h = 0.06
+    diff = (np.log10(np.e)/energy_nu)*(interp_nu_density(10**(np.log10(energy_nu)+h))-interp_nu_density(10**(np.log10(energy_nu)-h)))/(2*h)#interpolate.splev(energy_nu, interp_nu_density, der=1)
+
+    return H(z)*(nu_density + energy_nu*diff)
+
+    #index = list(lst_energy_nu).index(energy_nu)
+#    if index == 0:
+#        diff = (np.log10(np.e)/energy_nu)*(lst_nu_density[index+1]-lst_nu_density[index])/(np.log10(lst_energy_nu[index+1])-np.log10(lst_energy_nu[index]))
+#    elif index < len(lst_energy_nu)-1: 
+#        diff = (np.log10(np.e)/energy_nu)*(lst_nu_density[index+1]-lst_nu_density[index-1])/(np.log10(lst_energy_nu[index+1]) - np.log10(lst_energy_nu[index-1]))
+#    else: 
+#        diff = (np.log10(np.e)/energy_nu)*(lst_nu_density[index]-lst_nu_density[index-1])/(np.log10(lst_energy_nu[index])-np.log10(lst_energy_nu[index-1]))
+#    return H(z)*(nu_density + energy_nu*diff)
+
+
 
 def Attenuation(z, energy_nu, nu_density, g, M, m=1.e-10):
     return -c*nt(z)*sigma(energy_nu, g, M, m)*nu_density
 
-
 
 def Regeneration(z, energy_nu, lst_energy_nu, lst_nu_density, g, M, m=1.e-10):
     regen = 0
     index = list(lst_energy_nu).index(energy_nu)
-    #print(index)
     for j in range (index, len(lst_energy_nu)-1):
         regen += sigma(lst_energy_nu[j], g, M, m)*lst_nu_density[j]*(lst_energy_nu[j+1]-lst_energy_nu[j])
 
     regen=c*nt(z)*regen/(energy_nu)
-
 
     return regen
 
 def Propagation_Eq(z, nu_density, energy_nu, lst_energy_nu, lst_nu_density, interp_nu_density, g, M, m=1.e-10):
     rhs = 0
 
-    rhs += Adiabatic_Energy_Losses(z, energy_nu, nu_density)
+    rhs += Adiabatic_Energy_Losses(z, energy_nu, nu_density, lst_energy_nu, interp_nu_density)
     rhs += L(z, energy_nu)
     rhs += Attenuation(z, energy_nu, nu_density, g, M, m=1.e-10)
     rhs += Regeneration(z, energy_nu, lst_energy_nu, lst_nu_density, g, M, m=1.e-10)
@@ -68,47 +81,58 @@ def Integrand(z, nu_density, energy_nu, interp_nu_density):
 
     lst_nu_density = [0.0]*len(lst_energy_nu)
 
-
     dz = 1.e-1 
 
     z = z_max
+
+    print(z-5*dz)
+
+    vals = np.array([z-5*dz, z-10*dz, z-20*dz])
+    import time
 
     while (z > z_min):
         lst_nu_density_new = np.zeros(lst_energy_nu.size)
-
+        interp_nu_density = interp1d(lst_energy_nu, lst_nu_density, kind = 'cubic' , fill_value = 'extrapolate')
+#        interp_nu_density = interpolate.splrep(lst_energy_nu, lst_nu_density)
+        if z in vals:
+            x = np.linspace(np.min(lst_energy_nu), np.max(lst_energy_nu), 100)
+            plt.plot(x, interp_nu_density(x))
+            plt.xscale('log')
+            plt.show()
+
+            print('Trap')
+            time.sleep(10)
+
+
         for i in range(len(lst_energy_nu)):
 
             solver.set_initial_value(lst_nu_density[i], z)
-            solver.set_f_params(lst_energy_nu[i], lst_nu_density)
+            solver.set_f_params(lst_energy_nu[i], interp_nu_density)#lst_nu_density)
             sol = solver.integrate(solver.t-dz)
 
             lst_nu_density_new[i]=sol
-            #print(lst_nu_density_new)
 
         lst_nu_density = [x for x in lst_nu_density_new]
-
-        #print(lst_nu_density)
+
         z = z-dz
 
     return lst_nu_density
 
-log10_E_test_min = 2
+
+log10_E_test_min = 3
 log10_E_test_max = 8
 E_test_npts = 100
 E_test=np.power(10, np.linspace(log10_E_test_min, log10_E_test_max, E_test_npts))
-#E_test=np.append(E_test, [5e3, 4.5e4, 5e5, 5e7 ])
-E_test=np.append(E_test, np.log10(5e5))
-E_test=np.sort(E_test)
-flux = Neutrino_Flux(0, 4, E_test, 0.01, 0.001, 1e-10)
+flux = Neutrino_Flux(0, 4, E_test, 0.03, 0.01, 1e-10)
 flux = [E_test[i]*E_test[i]*flux[i] for i in range(len(E_test))]
 norm = 1/flux[0]
 flux = [norm*nu_flux for nu_flux in flux]
 
-plt.figure()
-plt.plot(E_test,flux)
-plt.xlabel('Neutrino energy $E[GeV]$')
-plt.ylabel('$ E^2 J \ [10^{-8}GeV \ cm^{-2} s^{-1} sr^{-1}]$')
-plt.xscale('log')
-#plt.ylim([0.0, 1.5])
-plt.xlim([10**3.0, 10**8.0])
-plt.savefig('TestSimpleD.png')
+#plt.figure()
+#plt.plot(E_test,flux)
+#plt.xlabel('Neutrino energy $E[GeV]$')
+#plt.ylabel('$ E^2 J \ [10^{-8}GeV \ cm^{-2} s^{-1} sr^{-1}]$')
+#plt.xscale('log')
+#plt.xlim([1e3, 1e8])
+#plt.savefig('TestB.png')
+