populate git ignore

.gitignore

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

CHANGELOG.md

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

README.md

@@ -1,5 +1,7 @@
 # Optifik
 
+TODO: write a paragraph here...
+
 
 This library replaces oospectro.
 
@@ -48,3 +50,7 @@ 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-or-later"
+license = "GPL-3.0"
 readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [

tests/test_thickness.py

@@ -0,0 +1,67 @@
+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)