fr/tmp_optifik
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

simplify finds_peak

Browse source
This commit is contained in:
François Boulogne 2025-05-21 14:05:08 +02:00
parent 022966608a
commit 56aac01151
6 changed files with 66 additions and 88 deletions
Download patch file Download diff file Expand all files Collapse all files

13
check.py
View file

@ -61,13 +61,16 @@ def check_SV1():
spectre_file = os.path.join(DATA_FOLDER, fn)
##### Affichage du spectre brut et récupération des Intesités brutes#####
raw_intensities = plot_xy(spectre_file)
lambdas, raw_intensities = load_spectrum(spectre_file, lambda_min=450)
##### Affichage du spectre lissé #####
smoothed_intensities, intensities, lambdas = Data_Smoothed(spectre_file)
#smoothed_intensities, intensities, lambdas = Data_Smoothed(spectre_file)
smoothed_intensities = smooth_intensities(raw_intensities)
# smoothed_intensities, intensities, lambdas = Data_Smoothed(spectre_file)
##### Indice Optique en fonction de Lambda #####
@ -97,4 +100,4 @@ def check_SV1():
if __name__ == '__main__':
check_basic()
#check_SV1()
check_SV1()

51
optifik/analysis.py
View file

@ -48,14 +48,7 @@ def plot_xy(file_path, plot=True):
def finds_peak(filename, min_peak_prominence, min_peak_distance=10, plot=None):
def finds_peak(lambdas, intensities, min_peak_prominence, min_peak_distance=10, plot=None):
"""
Charge un fichier .xy et affiche les données avec les extrema détectés (minima et maxima).
@ -68,10 +61,11 @@ def finds_peak(filename, min_peak_prominence, min_peak_distance=10, plot=None):
min_peak_distance : float
Distance minimale entre les pics.
"""
# Charger et lisser les données
lambdas, intensities = load_spectrum(filename, lambda_min=450)
WIN_SIZE = 11
smoothed_intensities = savgol_filter(intensities, WIN_SIZE, 3)
smoothed_intensities = intensities
# Trouver les maxima et minima sur le signal lissé
peaks_max, _ = find_peaks(smoothed_intensities, prominence=min_peak_prominence, distance=min_peak_distance)
peaks_min, _ = find_peaks(-smoothed_intensities, prominence=min_peak_prominence, distance=min_peak_distance)
@ -89,45 +83,24 @@ def finds_peak(filename, min_peak_prominence, min_peak_distance=10, plot=None):
# Nombre total d’extremums
total_extrema = len(peaks_max) + len(peaks_min)
if total_extrema >=15:
if total_extrema >= 15:
print('Number of extrema', total_extrema,'.')
print('FFT method')
if total_extrema <=15 and total_extrema >4:
if total_extrema <= 15 and total_extrema > 4:
print('Number of extrema', total_extrema,'.')
print('OOSpectro method')
if total_extrema <=4:
if total_extrema <= 4:
print('Number of extrema', total_extrema,'.')
print('Scheludko method')
return total_extrema, smoothed_intensities, intensities, lambdas, peaks_min, peaks_max
return total_extrema, peaks_min, peaks_max
def Data_Smoothed(filename):
"""
Charge un fichier .xy et affiche les données avec les extrema détectés (minima et maxima).
Parameters
----------
filename : str
Chemin vers le fichier .xy (2 colonnes : lambda et intensité).
min_peak_prominence : float
Importance minimale des pics.
min_peak_distance : float
Distance minimale entre les pics.
"""
# Charger et lisser les données
lambdas, intensities = load_spectrum(filename, lambda_min=450)
def smooth_intensities(intensities):
WIN_SIZE = 11
smoothed_intensities = savgol_filter(intensities, WIN_SIZE, 3)
return smoothed_intensities, intensities, lambdas
return smoothed_intensities

8
optifik/auto.py
View file

@ -10,11 +10,13 @@ def auto(DATA_FOLDER, FILE_NAME, plot=None):
##### Affichage du spectre brut et récupération des Intesités brutes#####
raw_intensities = load_spectrum(spectre_file)
lambdas, raw_intensities = load_spectrum(spectre_file, lambda_min=450)
##### Affichage du spectre lissé #####
smoothed_intensities, intensities, lambdas = Data_Smoothed(spectre_file)
#smoothed_intensities, intensities, lambdas = Data_Smoothed(spectre_file)
smoothed_intensities = smooth_intensities(raw_intensities)
##### Indice Optique en fonction de Lambda #####
@ -30,7 +32,7 @@ def auto(DATA_FOLDER, FILE_NAME, plot=None):
prominence = 0.03
##### Find Peak #####
total_extrema, smoothed_intensities, raw_intensities, lambdas, peaks_min, peaks_max = finds_peak(spectre_file,
total_extrema, peaks_min, peaks_max = finds_peak(lambdas, smoothed_intensities,
min_peak_prominence=prominence,
plot=plot)

18
tests/test_SV1.py
View file

@ -4,9 +4,9 @@ from numpy.testing import assert_allclose
import pytest
from optifik.minmax import thickness_from_minmax
from optifik.analysis import Data_Smoothed
from optifik.analysis import finds_peak
from optifik.io import load_spectrum
from optifik.analysis import smooth_intensities
from optifik.analysis import finds_peak
import yaml
@ -21,17 +21,17 @@ def load():
return data
@pytest.mark.parametrize("spectrum, expected", load())
def test_minmax(spectrum, expected):
raw_intensities = load_spectrum(spectrum)
smoothed_intensities, intensities, lambdas = Data_Smoothed(spectrum)
@pytest.mark.parametrize("spectrum_path, expected", load())
def test_minmax(spectrum_path, expected):
lambdas, raw_intensities = load_spectrum(spectrum_path, lambda_min=450)
smoothed_intensities = smooth_intensities(raw_intensities)
indice = 1.324188 + 3102.060378 / (lambdas**2)
prominence = 0.02
total_extrema, smoothed_intensities, raw_intensities, lambdas, peaks_min, peaks_max = finds_peak(spectrum,
min_peak_prominence=prominence)
total_extrema, peaks_min, peaks_max = finds_peak(lambdas, smoothed_intensities,
min_peak_prominence=prominence,
plot=False)
thickness_minmax = thickness_from_minmax(lambdas,
smoothed_intensities,

16
tests/test_SV2o5.py
View file

@ -5,7 +5,7 @@ import pytest
from optifik.scheludko import thickness_from_scheludko
from optifik.io import load_spectrum
from optifik.analysis import Data_Smoothed
from optifik.analysis import smooth_intensities
from optifik.analysis import finds_peak
import yaml
@ -21,17 +21,17 @@ def load():
return data
@pytest.mark.parametrize("spectrum, expected", load())
def test_minmax(spectrum, expected):
raw_intensities = load_spectrum(spectrum)
smoothed_intensities, intensities, lambdas = Data_Smoothed(spectrum)
@pytest.mark.parametrize("spectrum_path, expected", load())
def test_minmax(spectrum_path, expected):
lambdas, raw_intensities = load_spectrum(spectrum_path, lambda_min=450)
smoothed_intensities = smooth_intensities(raw_intensities)
refractive_index = 1.324188 + 3102.060378 / (lambdas**2)
prominence = 0.02
total_extrema, smoothed_intensities, raw_intensities, lambdas, peaks_min, peaks_max = finds_peak(spectrum,
min_peak_prominence=prominence)
total_extrema, peaks_min, peaks_max = finds_peak(lambdas, smoothed_intensities,
min_peak_prominence=prominence,
plot=False)
thickness_scheludko = thickness_from_scheludko(lambdas,
smoothed_intensities,

40
tests/test_basic.py
View file

@ -7,8 +7,7 @@ from optifik.analysis import thickness_from_fft
from optifik.analysis import thickness_from_minmax
from optifik.analysis import thickness_from_scheludko
from optifik.analysis import thickness_for_order0
from optifik.analysis import plot_xy
from optifik.analysis import Data_Smoothed
from optifik.analysis import smooth_intensities
from optifik.analysis import Prominence_from_fft
from optifik.analysis import finds_peak
from optifik.io import load_spectrum
@ -20,8 +19,8 @@ def test_FFT():
expected = 3524.51
spectrum_path = os.path.join(FOLDER, FILE_NAME)
raw_intensities = load_spectrum(spectrum_path)
smoothed_intensities, intensities, lambdas = Data_Smoothed(spectrum_path)
lambdas, raw_intensities = load_spectrum(spectrum_path, lambda_min=450)
smoothed_intensities = smooth_intensities(raw_intensities)
indice = 1.324188 + 3102.060378 / (lambdas**2)
thickness_FFT = thickness_from_fft(lambdas,
@ -37,8 +36,8 @@ def test_minmax_ransac():
expected = 1338.35
spectrum_path = os.path.join(FOLDER, FILE_NAME)
raw_intensities = load_spectrum(spectrum_path)
smoothed_intensities, intensities, lambdas = Data_Smoothed(spectrum_path)
lambdas, raw_intensities = load_spectrum(spectrum_path, lambda_min=450)
smoothed_intensities = smooth_intensities(raw_intensities)
indice = 1.324188 + 3102.060378 / (lambdas**2)
prominence = Prominence_from_fft(lambdas=lambdas,
@ -64,14 +63,15 @@ def test_scheludko_4peaks():
expected = 777.07
spectrum_path = os.path.join(FOLDER, FILE_NAME)
raw_intensities = load_spectrum(spectrum_path)
smoothed_intensities, intensities, lambdas = Data_Smoothed(spectrum_path)
lambdas, raw_intensities = load_spectrum(spectrum_path, lambda_min=450)
smoothed_intensities = smooth_intensities(raw_intensities)
indice = 1.324188 + 3102.060378 / (lambdas**2)
prominence = Prominence_from_fft(lambdas=lambdas, intensities=smoothed_intensities, refractive_index=indice, plot=False)
total_extrema, smoothed_intensities, raw_intensities, lambdas, peaks_min, peaks_max = finds_peak(spectrum_path,
min_peak_prominence=prominence)
total_extrema, peaks_min, peaks_max = finds_peak(lambdas, smoothed_intensities,
min_peak_prominence=prominence,
plot=False)
result = thickness_from_scheludko(lambdas, smoothed_intensities,
@ -89,15 +89,15 @@ def test_scheludko_2peaks():
expected = 495.69
spectrum_path = os.path.join(FOLDER, FILE_NAME)
raw_intensities = load_spectrum(spectrum_path)
smoothed_intensities, intensities, lambdas = Data_Smoothed(spectrum_path)
lambdas, raw_intensities = load_spectrum(spectrum_path, lambda_min=450)
smoothed_intensities = smooth_intensities(raw_intensities)
indice = 1.324188 + 3102.060378 / (lambdas**2)
prominence = 0.03
total_extrema, smoothed_intensities, raw_intensities, lambdas, peaks_min, peaks_max = finds_peak(spectrum_path,
min_peak_prominence=prominence)
total_extrema, peaks_min, peaks_max = finds_peak(lambdas, smoothed_intensities,
min_peak_prominence=prominence,
plot=False)
result = thickness_from_scheludko(lambdas, smoothed_intensities,
peaks_min, peaks_max,
@ -116,15 +116,15 @@ def test_order0():
expected = 115.33
spectrum_path = os.path.join(FOLDER, FILE_NAME)
raw_intensities = load_spectrum(spectrum_path)
smoothed_intensities, intensities, lambdas = Data_Smoothed(spectrum_path)
lambdas, raw_intensities = load_spectrum(spectrum_path, lambda_min=450)
smoothed_intensities = smooth_intensities(raw_intensities)
indice = 1.324188 + 3102.060378 / (lambdas**2)
prominence = 0.03
total_extrema, smoothed_intensities, raw_intensities, lambdas, peaks_min, peaks_max = finds_peak(spectrum_path,
min_peak_prominence=prominence)
total_extrema, peaks_min, peaks_max = finds_peak(lambdas, smoothed_intensities,
min_peak_prominence=prominence,
plot=False)
result = thickness_for_order0(lambdas, smoothed_intensities,
peaks_min, peaks_max,