.gitignore

@@ -1,10 +0,0 @@
-__pycache__
-.backups
-optifik.egg-info
-*.bak
-*.pyc
-.ipynb_checkpoints
-.venv
-build/
-_build/
-dist/

CHANGELOG.md

@@ -1,4 +0,0 @@
-
-# x.x.x
-
-First version

README.md

@@ -1,7 +1,5 @@
 # Optifik
 
-TODO: write a paragraph here...
-
 
 This library replaces oospectro.
 
@@ -50,7 +48,3 @@ cd docs
 make html
 ```
 
-## Licence
-
-The source code is released under the GNU General Public License v3.0.
-See LICENSE for details.

pyproject.toml

@@ -6,7 +6,7 @@ authors = [
   { name = "François Boulogne", email = "francois.boulogne@cnrs.fr" },
   { name = "Victor Ziapkoff", email = "victor.ziapkoff@universite-paris-saclay.fr" },
 ]
-license = "GPL-3.0"
+license = "GPL-3.0-or-later"
 readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [

tests/test_thickness.py

@@ -1,67 +0,0 @@
-import pytest
-import yaml
-from pathlib import Path
-import os.path
-
-import numpy as np
-from numpy.testing import assert_allclose
-from numpy.testing import assert_almost_equal
-
-from optifik.minmax import thickness_from_minmax
-from optifik.analysis import smooth_intensities
-from optifik.io import load_spectrum
-
-
-def load():
-    test_data_dir = Path(__file__).parent.parent / 'data'
-    FOLDER = test_data_dir / 'spectraLorene' / 'sample1'
-
-    yaml_file = os.path.join(FOLDER, 'sample1.yaml')
-    with open(yaml_file, "r") as yaml_file:
-        thickness_dict = yaml.safe_load(yaml_file)
-    #print(thickness_dict)
-    data = [(os.path.join(FOLDER, fn), val) for fn, val in thickness_dict['known_thicknesses'].items()]
-    return data
-
-
-def test_minmax_sample1():
-    min_peak_prominence = 0.02
-    min_peak_distance = 10
-    skipped = ('011137.xy',
-               '012426.xy',
-               '012795.xy',
-               '012979.xy',
-               '011321.xy', #Insufficient number of data points
-               )
-
-    for path, expected in load():
-        file = os.path.split(path)[-1]
-        if file not in skipped:
-            lambdas, raw_intensities = load_spectrum(path, wavelength_min=450)
-            smoothed_intensities = smooth_intensities(raw_intensities)
-            r_index = 1.33 #TODO
-
-            prominence = 0.02
-            distance = 10
-
-            result = thickness_from_minmax(lambdas,
-                                           smoothed_intensities,
-                                           refractive_index=r_index,
-                                           min_peak_prominence=prominence,
-                                           min_peak_distance=distance,
-                                           method='ransac',
-                                           plot=False)
-
-            assert_allclose(result.thickness, expected, rtol=2.3e-1)
-
-#def test_fft_sample1():
-#    for name, value in known_values.sample1['known_thicknesses'].items():
-#        index = known_values.sample1['refractive_index']
-#        # this method works only for large thicknesses
-#        if value < 3000:
-#            continue
-#        path = os.path.join('spectra', name)
-#        lambdas, intensities = io.load_spectrum(path, lambda_min=450)
-#        result = thickness_from_fft(lambdas, intensities, refractive_index=index,)
-#        error = 100 * np.abs(result.thickness - value) / value
-#        assert(error < 5)