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This commit is contained in:
François Boulogne 2025-06-20 09:23:40 +02:00
parent 9e77fc8f03
commit c8868c3e63
15 changed files with 63 additions and 817 deletions
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48
optifik/scheludko.py
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@ -8,13 +8,13 @@ from .utils import OptimizeResult, setup_matplotlib
from .analysis import finds_peak
def thickness_scheludko_at_order(wavelengths,
def _thicknesses_scheludko_at_order(wavelengths,
intensities,
interference_order,
refractive_index,
Imin=None):
"""
Compute the film thickness for a given interference order.
Compute thicknesses vs wavelength for a given interference order.
Parameters
----------
@ -56,7 +56,7 @@ def thickness_scheludko_at_order(wavelengths,
return prefactor * (term1 + term2)
def Delta(wavelengths, thickness, interference_order, refractive_index):
def _Delta(wavelengths, thickness, interference_order, refractive_index):
"""
Compute the Delta values.
@ -103,7 +103,7 @@ def Delta(wavelengths, thickness, interference_order, refractive_index):
return (A * (1 + alpha)) / (1 + A * alpha)
def Delta_fit(xdata, thickness, interference_order):
def _Delta_fit(xdata, thickness, interference_order):
"""
Wrapper on Delta() for curve_fit.
@ -123,7 +123,7 @@ def Delta_fit(xdata, thickness, interference_order):
"""
lambdas, r_index = xdata
return Delta(lambdas, thickness, interference_order, r_index)
return _Delta(lambdas, thickness, interference_order, r_index)
@ -156,9 +156,11 @@ def thickness_from_scheludko(wavelengths,
if plot:
setup_matplotlib()
# A bit extreme...
max_tested_order = 12
r_index = refractive_index
# idx_min idx max
peaks_min, peaks_max = finds_peak(wavelengths, intensities,
min_peak_prominence=min_peak_prominence,
plot=plot)
@ -181,12 +183,18 @@ def thickness_from_scheludko(wavelengths,
lambda_start = min(lambda_min, lambda_max)
lambda_stop = max(lambda_min, lambda_max)
# Guess the order...
# mask input data
mask = (wavelengths >= lambda_start) & (wavelengths <= lambda_stop)
wavelengths_masked = wavelengths[mask]
r_index_masked = r_index[mask]
intensities_masked = intensities[mask]
min_difference = np.inf
best_m = None
best_h_values = None
@ -197,7 +205,7 @@ def thickness_from_scheludko(wavelengths,
plt.xlabel(r'$\lambda$ ($ \mathrm{nm} $)')
for m in range(0, max_tested_order+1):
h_values = thickness_scheludko_at_order(wavelengths_masked,
h_values = _thicknesses_scheludko_at_order(wavelengths_masked,
intensities_masked,
m, r_index_masked)
@ -216,30 +224,32 @@ def thickness_from_scheludko(wavelengths,
print(f"Optimized: m={best_m}")
# Compute the thickness for the selected order
# Delta
num = intensities_masked - np.min(intensities_masked)
denom = np.max(intensities_masked) - np.min(intensities_masked)
DeltaVrai = num / denom
Delta_from_data = num / denom
# DeltaVrai = (intensities_masked -np.min(intensities_masked))/(np.max(intensities_masked) -np.min(intensities_masked))
# DeltaVrai = (intensities_raw_masked -np.min(intensities_raw_masked))/(np.max(intensities_raw_masked) -np.min(intensities_raw_masked))
# Delta_from_data = (intensities_masked -np.min(intensities_masked))/(np.max(intensities_masked) -np.min(intensities_masked))
# Delta_from_data = (intensities_raw_masked -np.min(intensities_raw_masked))/(np.max(intensities_raw_masked) -np.min(intensities_raw_masked))
DeltaScheludko = Delta(wavelengths_masked,
DeltaScheludko = _Delta(wavelengths_masked,
np.mean(best_h_values),
best_m,
r_index_masked)
xdata = (wavelengths_masked, r_index_masked)
popt, pcov = curve_fit(lambda x, h: Delta_fit(x, h, m), xdata, DeltaVrai, p0=[np.mean(best_h_values)])
popt, pcov = curve_fit(lambda x, h: _Delta_fit(x, h, m), xdata, Delta_from_data, p0=[np.mean(best_h_values)])
fitted_h = popt[0]
std_err = np.sqrt(pcov[0][0])
if plot:
Delta_values = Delta(wavelengths_masked, fitted_h, best_m, r_index_masked)
Delta_values = _Delta(wavelengths_masked, fitted_h, best_m, r_index_masked)
plt.figure()
plt.plot(wavelengths_masked, DeltaVrai,
plt.plot(wavelengths_masked, Delta_from_data,
'bo-', markersize=2, label=r'$\mathrm{{Smoothed}}\ \mathrm{{Data}}$')
# Scheludko
@ -294,7 +304,7 @@ def thickness_for_order0(wavelengths,
# We assume to be at order zero.
best_m = 0
best_h_values = thickness_scheludko_at_order(wavelengths_masked,
best_h_values = _thicknesses_scheludko_at_order(wavelengths_masked,
intensities_masked,
best_m,
r_index_masked,
@ -311,21 +321,21 @@ def thickness_for_order0(wavelengths,
# Delta
num = intensities_masked - np.min(intensities_I_min_masked)
denom = np.max(intensities_masked) - np.min(intensities_I_min_masked)
DeltaVrai = num / denom
Delta_from_data = num / denom
DeltaScheludko = Delta(wavelengths_masked, np.mean(best_h_values), best_m, r_index_masked)
DeltaScheludko = _Delta(wavelengths_masked, np.mean(best_h_values), best_m, r_index_masked)
#print(np.mean(best_h_values),np.std(best_h_values))
xdata = (wavelengths_masked, r_index_masked)
popt, pcov = curve_fit(lambda x, h: Delta_fit(x, h, best_m), xdata, DeltaVrai, p0=[np.mean(best_h_values)])
popt, pcov = curve_fit(lambda x, h: _Delta_fit(x, h, best_m), xdata, Delta_from_data, p0=[np.mean(best_h_values)])
fitted_h = popt[0]
std_err = np.sqrt(pcov[0][0])
if plot:
Delta_values = Delta(wavelengths_masked, fitted_h, best_m, r_index_masked)
Delta_values = _Delta(wavelengths_masked, fitted_h, best_m, r_index_masked)
plt.figure()
plt.plot(wavelengths_masked, DeltaVrai,
plt.plot(wavelengths_masked, Delta_from_data,
'bo-', markersize=2, label=r'$\mathrm{{Smoothed}}\ \mathrm{{Data}}$')
# Scheludko