1 import FiniteVolumes2DDiffusion_SQUARE
2 import matplotlib.pyplot as plt
4 from math import log10, sqrt
7 convergence_synthesis=dict(FiniteVolumes2DDiffusion_SQUARE.test_desc)
9 def test_validation2DVF_squares():
11 ### 2D FV rectangular mesh
12 # meshList=[11,51,151,201]
13 meshList=['squareWithSquares_1','squareWithSquares_2','squareWithSquares_3','squareWithSquares_4','squareWithSquares_5']
14 mesh_path='../../../ressources/2DCartesien/'
15 meshType="Regular_squares"
17 nbMeshes=len(meshList)
18 error_tab=[0]*nbMeshes
19 mesh_size_tab=[0]*nbMeshes
20 mesh_name='squareWithSquares'
21 diag_data=[0]*nbMeshes
24 curv_abs=np.linspace(0,sqrt(2),resolution+1)
27 # Storing of numerical errors, mesh sizes and diagonal values
28 for filename in meshList:
31 # my_mesh=cdmath.Mesh(0,1,nx,0,1,nx)
32 # error_tab[i], mesh_size_tab[i], diag_data[i], min_sol_num, max_sol_num, time_tab[i] =FiniteVolumes2DDiffusion_SQUARE.solve(my_mesh,str(nx)+'x'+str(nx),resolution,meshType,testColor)
33 error_tab[i], mesh_size_tab[i], diag_data[i], min_sol_num, max_sol_num, time_tab[i] =FiniteVolumes2DDiffusion_SQUARE.solve_file(mesh_path+filename,resolution,meshType,testColor)
34 assert min_sol_num>-0.01
35 assert max_sol_num<1.2
36 plt.plot(curv_abs, diag_data[i], label= str(mesh_size_tab[i]) + ' cells')
37 error_tab[i]=log10(error_tab[i])
38 time_tab[i]=log10(time_tab[i])
39 mesh_size_tab[i] = 0.5*log10(mesh_size_tab[i])
44 # Plot over diagonal line
46 plt.xlabel('Position on diagonal line')
47 plt.ylabel('Value on diagonal line')
48 plt.title('Plot over diagonal line for finite volumes \n for the diffusion equation on 2D rectangular meshes')
49 plt.savefig(mesh_name+"_2DDiffusionFV_PlotOverDiagonalLine.png", dpi='figure')
51 # Least square linear regression
52 # Find the best a,b such that f(x)=ax+b best approximates the convergence curve
53 # The vector X=(a,b) solves a symmetric linear system AX=B with A=(a1,a2\\a2,a3), B=(b1,b2)
54 a1=np.dot(mesh_size_tab,mesh_size_tab)
55 a2=np.sum(mesh_size_tab)
57 b1=np.dot(error_tab,mesh_size_tab)
61 assert det!=0, 'test_validation2DVF_squares() : Make sure you use distinct meshes and at least two meshes'
65 print( "FV for diffusion on 2D rectangular meshes : scheme order is ", -a)
68 # Plot of convergence curve
70 plt.plot(mesh_size_tab, error_tab, label='log(|numerical-exact|)')
71 plt.plot(mesh_size_tab, a*np.array(mesh_size_tab)+b,label='least square slope : '+'%.3f' % a)
73 plt.plot(mesh_size_tab, error_tab)
74 plt.xlabel('log(sqrt(number of cells))')
75 plt.ylabel('log(error)')
76 plt.title('Convergence of finite volumes for \n the diffusion equation on 2D rectangular meshes')
77 plt.savefig(mesh_name+"_2DDiffusionFV_ConvergenceCurve.png", dpi='figure')
79 # Plot of computational time
81 plt.plot(mesh_size_tab, time_tab, label='log(cpu time)')
83 plt.xlabel('log(sqrt(number of cells))')
84 plt.ylabel('log(cpu time)')
85 plt.title('Computational time of finite volumes \n for the diffusion equation on 2D rectangular meshes')
86 plt.savefig(mesh_name+"_2DDiffusionFV_ComputationalTime.png", dpi='figure')
90 convergence_synthesis["Mesh_names"]=meshList
91 convergence_synthesis["Mesh_type"]=meshType
92 convergence_synthesis["Mesh_path"]=mesh_path
93 convergence_synthesis["Mesh_description"]=mesh_name
94 convergence_synthesis["Mesh_sizes"]=[10**x for x in mesh_size_tab]
95 convergence_synthesis["Space_dimension"]=2
96 convergence_synthesis["Mesh_dimension"]=2
97 convergence_synthesis["Mesh_cell_type"]="Squares"
98 convergence_synthesis["Errors"]=[10**x for x in error_tab]
99 convergence_synthesis["Scheme_order"]=-a
100 convergence_synthesis["Test_color"]=testColor
101 convergence_synthesis["Computational_time"]=end-start
103 with open('Convergence_Diffusion_2DVF_'+mesh_name+'.json', 'w') as outfile:
104 json.dump(convergence_synthesis, outfile)
106 if __name__ == """__main__""":
107 test_validation2DVF_squares()