def test_one_well_numerov(method, width, depth, separation, width_bg):
r = numerov(widths=[width], depths=[depth], separations=separation, width_bg=width_bg, dx=0.01, method=method)
E = r['E']
s = one_well_energies(depth=depth, width=width)
assert np.allclose(E, s, atol=1e-1)
def test_one_well_numerov(method):
"""Test the one well analytic solution code against the original one well matlab code from Lena"""
r = numerov(widths=[3.0], depths=[10.0])
mat = loadmat('tests/numerov/get_p_1W.mat', squeeze_me=True, method=method)
E = mat['E']
assert np.allclose(r['E'], E)
def test_get_p_2W(method):
"""
Test the output for the matrix numerov method against the MATLAB implementation. This is Lena's 2-well code.
"""
mat = loadmat('tests/numerov/get_p_2W.mat', squeeze_me=True)
# Get the parameters we are going to test
d1 = mat['d1']
d2 = mat['d2']
w1 = mat['w1']
w2 = mat['w2']
w_sep = mat['w_sep']
r = numerov(widths=[w1, w2], depths=[d1, d2], separations=[w_sep], method=method)
assert np.allclose(mat['v'], r['v'])
assert np.allclose(mat['E'], r['E'])
#assert np.allclose(mat['psi'], r['psi'])
assert np.allclose(mat['dens'], r['dens'])
assert np.allclose(mat['p_1'], r['p_wells'][0, :])
assert np.allclose(mat['p_2'], r['p_wells'][1, :])
assert np.allclose(mat['p_int'], r['p_int'][0, :])
assert np.allclose(mat['p_bg'], r['p_bg'])
def test_N_wells_numerov(widths, depths, separations, width_bg):
r = numerov(widths=widths, depths=depths, separations=separations, width_bg=width_bg)
import pandas as pd
import seaborn as sns
from tise_solver.numerov import numerov
if __name__ == "__main__":
results = []
for method in ['sparse', 'dense']:
for dx in [
0.02, 0.01, 0.009, 0.008, 0.007, 0.006, 0.005, 0.004, 0.003
]:
# Run it to get the total number of steps for this dx
n_steps = numerov(widths=[3.0],
depths=[10.0],
separations=[],
dx=dx,
method=method)['n_steps']
# Run to time it
e = timeit.timeit(
stmt=
f"numerov(widths=[3.0], depths=[10.0], separations=[], dx={dx}, method='{method}')",
setup="from tise_solver.numerov import numerov",
number=1)
print(f'method={method}, dx={dx}, n_steps={n_steps}, time={e}')
results.append((method, dx, n_steps, e))
results = pd.DataFrame(
results, columns=['method', 'dx', 'n_steps', 'execution_time'])
#%%
import time
p = params[f'periodic n_wells=1']
marsiglio_E = []
marsiglio_times = []
numerov_E = []
numerov_times = []
n_steps_vals = []
dxs = [0.5, 0.2, 0.1, 0.02, 0.01, 0.009, 0.008, 0.007, 0.006, 0.005]
for dx in dxs:
t0 = time.time()
nr = numerov(**p, dx=dx, method='dense')
numerov_times.append(time.time() - t0)
numerov_E.append(nr['E'])
n_steps = nr['n_steps']
n_steps_vals.append(n_steps)
t0 = time.time()
mr = marsiglio(**p, nt=n_steps)
marsiglio_times.append(time.time() - t0)
marsiglio_E.append(mr['E'])
print(
f"dx = {dx}, numerov_time = {numerov_times[-1]}, marsiglio_time = {marsiglio_times[-1]}"
)
#%%
E1_marsiglio = np.array([E[0] for E in marsiglio_E])