plt.contourf(X, Y, d_yx, 40)
plt.colorbar()
for atom in atom_a:
pos = atom['pos']
plt.scatter(pos[2], pos[0], s=50, c='k', marker='o')
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.xlim([x[0], x[-1]])
plt.ylim([y[0], y[-1]])
ax.set_aspect('equal')
# Read InducedField object as standard numpy arrays, so
# - no GPAW's GridDescriptor is required
# - this code is not parallel safe
data = read_data('na2_td_field.ind')
# Choose array
w = 1 # Frequency index
freq = data['freq_w'][w] # Frequency
box = np.diag(data['cell_cv']) # Calculation box
d_g = data['Ffe_wg'][w] # Data array
ng = d_g.shape # Size of grid
atom_a = data['atom_a'] # Atoms
do_plot(d_g, ng, box, atom_a)
plt.title('Field enhancement @ %.2f eV' % freq)
plt.savefig('na2_td_Ffe.png', bbox_inches='tight')
# Imaginary part of density
d_g = data['Frho_wg'][w].imag
plt.contourf(X, Y, d_yx, 40)
plt.colorbar()
for atom in atom_a:
pos = atom['pos']
plt.scatter(pos[2], pos[0], s=50, c='k', marker='o')
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.xlim([x[0], x[-1]])
plt.ylim([y[0], y[-1]])
ax.set_aspect('equal')
# Read InducedField object as standard numpy arrays, so
# - no GPAW's GridDescriptor is required
# - this code is not parallel safe
data = read_data('na2_casida_field.ind')
# Choose array
w = 1 # Frequency index
freq = data['freq_w'][w] # Frequency
box = np.diag(data['cell_cv']) # Calculation box
d_g = data['Ffe_wg'][w] # Data array
ng = d_g.shape # Size of grid
atom_a = data['atom_a'] # Atoms
do_plot(d_g, ng, box, atom_a)
plt.title('Field enhancement @ %.2f eV' % freq)
plt.savefig('na2_casida_Ffe.png', bbox_inches='tight')
# Imaginary part of density
d_g = data['Frho_wg'][w].imag * 1e-3 # Multiply by kick strength
plt.contourf(X, Y, d_yx, 40)
plt.colorbar()
for atom in atom_a:
pos = atom['pos']
plt.scatter(pos[2], pos[0], s=50, c='k', marker='o')
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.xlim([x[0], x[-1]])
plt.ylim([y[0], y[-1]])
ax.set_aspect('equal')
# Read InducedField object as standard numpy arrays, so
# - no GPAW's GridDescriptor is required
# - this code is not parallel safe
data = read_data('na2_td_field.ind')
# Choose array
w = 1 # Frequency index
freq = data['freq_w'][w] # Frequency
box = np.diag(data['cell_cv']) # Calculation box
d_g = data['Ffe_wg'][w] # Data array
ng = d_g.shape # Size of grid
atom_a = data['atom_a'] # Atoms
do_plot(d_g, ng, box, atom_a)
plt.title('Field enhancement @ %.2f eV' % freq)
plt.savefig('na2_td_Ffe.png', bbox_inches='tight')
# Imaginary part of density
d_g = data['Frho_wg'][w].imag
plt.contourf(X, Y, d_yx, 40)
plt.colorbar()
for atom in atom_a:
pos = atom['pos']
plt.scatter(pos[2], pos[0], s=50, c='k', marker='o')
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.xlim([x[0], x[-1]])
plt.ylim([y[0], y[-1]])
ax.set_aspect('equal')
# Read InducedField object as standard numpy arrays, so
# - no GPAW's GridDescriptor is required
# - this code is not parallel safe
data = read_data('na2_casida_field.ind')
# Choose array
w = 1 # Frequency index
freq = data['freq_w'][w] # Frequency
box = np.diag(data['cell_cv']) # Calculation box
d_g = data['Ffe_wg'][w] # Data array
ng = d_g.shape # Size of grid
atom_a = data['atom_a'] # Atoms
do_plot(d_g, ng, box, atom_a)
plt.title('Field enhancement @ %.2f eV' % freq)
plt.savefig('na2_casida_Ffe.png', bbox_inches='tight')
# Imaginary part of density
d_g = data['Frho_wg'][w].imag * 1e-3 # Multiply by kick strength
