for i in range(n_frames):
phi = phi_array[i]
for j in range(n_points):
r = r_array[j]
for k in range(n_points):
theta = theta_array[k]
pos = np.array(sp2cart(r, theta, phi))
V_Tensor[i][j][k] = myChargeDist.V(pos)
print('Finished calculating V_Tensor')
X, Y = np.meshgrid(r_array, theta_array * 180 / np.pi, indexing='ij')
fig = plt.figure(figsize=(16, 10))
ax = fig.gca(projection='3d')
surf = [ax.plot_surface(X, Y, V_Tensor[0], cmap='magma', rstride=1, cstride=1)]
def update(i):
Axes3D.set_title(ax,
label=(r'$\phi$ = ' +
str(round(phi_array[i] * 180 / np.pi)) + r'$^o$'))
for i in range(n_points):
x = x_array[i]
for j in range(n_points):
y = y_array[j]
for k in range(n_points):
z = z_array[k]
pos = np.array([x, y, z])
V_Tensor[i][j][k] = C_ChargeDist.V(pos) + H1.V(pos) + H2.V(
pos) + H3.V(pos) + H4.V(pos)
print('Finished calculating V_Tensor')
X, Y, Z = np.meshgrid(x_array, y_array, z_array, indexing='ij')
V_Tensor[np.isinf(V_Tensor)] = np.nan
contour3d(X,
Y,
Z,
V_Tensor,
name='Equipotential surfaces for Methane Molecule',
contours=50,
opacity=0.5,
z_array = np.linspace(r_min, r_max, n_points)
V_Tensor = np.zeros((n_points, n_points, n_points))
print('Started calculating V_Tensor')
for i in range(n_points) :
x = x_array[i]
for j in range(n_points) :
y = y_array[j]
for k in range(n_points) :
z = z_array[k]
V_Tensor[i][j][k] = myChargeDist.V( np.array([x,y,z]) )
print('Finished calculating V_Tensor')
X, Y, Z = np.meshgrid( x_array, y_array, z_array, indexing='ij')
V_Tensor[ np.isinf(V_Tensor) ] = np.nan
contour3d( X, Y, Z, V_Tensor,
name='Equipotential surfaces for Octahedral Charge Distribution',
contours=50, opacity='0.5', colormap='magma')
waitkey = input()