log-log plots

euler_error/diffusion_fixed_domain_euler_errors.py

@@ -45,7 +45,7 @@ def advection_diffusion(Nx, L, Nt, tmax, D):
 
 
 # parameters
 # parameters
 Nx, L, D, tmax = 32, 1, 0.1, 0.25
 Nx, L, D, tmax = 32, 1, 0.1, 0.25
-nt_array = np.array([50, 100, 200])
+nt_array = np.array([5, 10, 15, 20, 25, 50, 100, 200, 400, 800, 1600])
 dt_array = tmax/nt_array
 dt_array = tmax/nt_array
 mesh = df.IntervalMesh(Nx, 0, L)
 mesh = df.IntervalMesh(Nx, 0, L)
 x = mesh.coordinates()[:, 0]
 x = mesh.coordinates()[:, 0]
@@ -63,7 +63,7 @@ for i in range(0, len(nt_array)):
     c = advection_diffusion(Nx, L, nt_array[i], tmax, D)
     c = advection_diffusion(Nx, L, nt_array[i], tmax, D)
     error[i] = np.max(np.abs(c[-1] - c_exact[-1]))
     error[i] = np.max(np.abs(c[-1] - c_exact[-1]))
 
 
-print('Max error for dt=0.0005 at t=0.25 is',error[0])
+print('dt,t,error=', tmax/400, tmax, error[-3])
 popt, pcov = curve_fit(linear_func, np.log(dt_array), np.log(error))
 popt, pcov = curve_fit(linear_func, np.log(dt_array), np.log(error))
 print('The slope of the graph of log(error) vs log(dt) is', popt[0])
 print('The slope of the graph of log(error) vs log(dt) is', popt[0])
 fig, ax = plt.subplots(1)
 fig, ax = plt.subplots(1)