def compare_with_model_2D(X, Y, true_csd, indx, params):
boundary_x = [np.min(X), np.max(X)]
boundary_y = [np.min(Y), np.max(Y)]
true_pots = calculate_potential_2D(true_csd, boundary_x, boundary_y,
params['h'])
elec_pos = np.array([[X[i, j], Y[i, j]] for i, j in indx])
pots = np.array([[true_pots[i, j]] for i, j in indx])
print elec_pos
true_pots = np.atleast_2d(true_pots)
k = KCSD(elec_pos, pots, params)
k.estimate_pots()
k.estimate_csd()
rec_csd = k.solver.estimated_csd
rec_pot = k.solver.estimated_pots
csd_err = get_relative_error(true_csd[:100, :100], rec_csd[:100, :100, 0].T)
pot_err = get_relative_error(true_pots[:100, :100], rec_pot[:100, :100, 0].T)
print 'true_csd.shape: ', true_csd.shape
print 'recstr_csd.shape: ', rec_csd.shape
print 'csd_err.shape: ', csd_err.shape
plut.plot_comparison_2D(X[1:-1, 1:-1], Y[1:-1, 1:-1], elec_pos,
true_csd[1:-1, 1:-1], true_pots[1:-1, 1:-1],
rec_csd[1:-1, 1:-1, 0].T, rec_pot[1:-1, 1:-1, 0].T,
csd_err[1:-1, 1:-1], pot_err[1:-1, 1:-1])
def compare_with_model_1D(X, true_csd, indx, params):
true_pot = calculate_potential_1D(true_csd, [np.min(X), np.max(X)], 0.5)
elec_pos = np.array([[X[i]] for i in indx])
pots = np.array([[true_pot[i]] for i in indx])
k = KCSD(elec_pos, pots, params)
k.estimate_pots()
k.estimate_csd()
true_csd = np.atleast_2d(true_csd)
true_pot = np.atleast_2d(true_pot)
rec_csd = k.solver.estimated_csd
rec_pot = k.solver.estimated_pots
csd_err = true_csd - rec_csd
csd_err = get_relative_error(rec_csd[:,0], true_csd[0,:])
pot_err = true_pot - rec_pot
pot_err = get_relative_error(rec_pot[:,0], true_pot[0,:])
print 'true_csd.shape: ', true_csd.shape
print 'recstr_csd.shape: ', rec_csd.shape
print 'csd_err.shape: ', csd_err.shape
plut.plot_comparison_1D(X, elec_pos, true_csd[0, :], true_pot[0, :],
rec_csd, rec_pot, csd_err, pot_err)
def compare_with_model_2D(X, Y, true_csd, indx, params):
boundary_x = [np.min(X), np.max(X)]
boundary_y = [np.min(Y), np.max(Y)]
true_pots = calculate_potential_2D(true_csd, boundary_x, boundary_y,
params['h'])
elec_pos = np.array([[X[i, j], Y[i, j]] for i, j in indx])
pots = np.array([[true_pots[i, j]] for i, j in indx])
print elec_pos
true_pots = np.atleast_2d(true_pots)
k = KCSD(elec_pos, pots, params)
k.estimate_pots()
k.estimate_csd()
rec_csd = k.solver.estimated_csd
rec_pot = k.solver.estimated_pots
csd_err = get_relative_error(true_csd[:100, :100], rec_csd[:100, :100,
0].T)
pot_err = get_relative_error(true_pots[:100, :100], rec_pot[:100, :100,
0].T)
print 'true_csd.shape: ', true_csd.shape
print 'recstr_csd.shape: ', rec_csd.shape
print 'csd_err.shape: ', csd_err.shape
plut.plot_comparison_2D(X[1:-1, 1:-1], Y[1:-1, 1:-1], elec_pos,
true_csd[1:-1, 1:-1], true_pots[1:-1, 1:-1],
rec_csd[1:-1, 1:-1, 0].T, rec_pot[1:-1, 1:-1, 0].T,
csd_err[1:-1, 1:-1], pot_err[1:-1, 1:-1])
def compare_with_model_1D(X, true_csd, indx, params):
true_pot = calculate_potential_1D(true_csd, [np.min(X), np.max(X)], 0.5)
elec_pos = np.array([[X[i]] for i in indx])
pots = np.array([[true_pot[i]] for i in indx])
k = KCSD(elec_pos, pots, params)
k.estimate_pots()
k.estimate_csd()
true_csd = np.atleast_2d(true_csd)
true_pot = np.atleast_2d(true_pot)
rec_csd = k.solver.estimated_csd
rec_pot = k.solver.estimated_pots
csd_err = true_csd - rec_csd
csd_err = get_relative_error(rec_csd[:, 0], true_csd[0, :])
pot_err = true_pot - rec_pot
pot_err = get_relative_error(rec_pot[:, 0], true_pot[0, :])
print 'true_csd.shape: ', true_csd.shape
print 'recstr_csd.shape: ', rec_csd.shape
print 'csd_err.shape: ', csd_err.shape
plut.plot_comparison_1D(X, elec_pos, true_csd[0, :], true_pot[0, :],
rec_csd, rec_pot, csd_err, pot_err)
