mpl

check.py

@@ -211,6 +211,9 @@ def check_SV1():
 
 if __name__ == '__main__':
 
+    from optifik.utils import is_latex_installed
+    print(is_latex_installed())
+
     #check_basic()
     #check_SV1()
     #play()

optifik/analysis.py

@@ -10,11 +10,11 @@ plt.rcParams.update({
     'legend.fontsize': 23,
 })
 
-
+from .utils import setup_matplotlib
 
 def plot_spectrum(wavelengths, intensities, title=''):
-
+    setup_matplotlib()
-    plt.figure(figsize=(10, 6), dpi=300)
+    plt.figure()
     plt.plot(wavelengths, intensities, 'o-', markersize=2)
     plt.xlabel(r'$\lambda$ (nm)')
     plt.ylabel(r'$I^*$')
@@ -46,11 +46,14 @@ def finds_peak(wavelengths, intensities, min_peak_prominence, min_peak_distance=
     (peaks_min, peaks_max)
 
     """
+    if plot:
+        setup_matplotlib()
+
     peaks_max, _ = find_peaks(intensities, prominence=min_peak_prominence, distance=min_peak_distance)
     peaks_min, _ = find_peaks(-intensities, prominence=min_peak_prominence, distance=min_peak_distance)
 
     if plot:
-        plt.figure(figsize=(10, 6), dpi=300)
+        plt.figure()
         plt.plot(wavelengths, intensities, 'o-', markersize=2, label="Smoothed data")
         plt.plot(wavelengths[peaks_max], intensities[peaks_max], 'ro')
         plt.plot(wavelengths[peaks_min], intensities[peaks_min], 'ro')

optifik/fft.py

@@ -4,16 +4,8 @@ from scipy.fftpack import fft, ifft, fftfreq
 
 
 import matplotlib.pyplot as plt
-plt.rc('text', usetex=True)
-plt.rcParams.update({
-    'axes.labelsize': 26,
-    'xtick.labelsize': 32,
-    'ytick.labelsize': 32,
-    'legend.fontsize': 23,
-})
 
-
+from .utils import OptimizeResult, setup_matplotlib
-from .utils import OptimizeResult
 
 
 
@@ -43,6 +35,9 @@ def thickness_from_fft(wavelengths, intensities,
     results : Instance of `OptimizeResult` class.
         The attribute `thickness` gives the thickness value in nm.
     """
+    if plot:
+        setup_matplotlib()
+
     if num_half_space is None:
         num_half_space = 10 * len(wavelengths)
 
@@ -74,7 +69,7 @@ def thickness_from_fft(wavelengths, intensities,
     thickness_fft = freq_max / 2.
 
     if plot:
-        plt.figure(figsize=(10, 6), dpi=300)
+        plt.figure()
         plt.loglog(inverse_wavelengths_fft, np.abs(intensities_fft))
         plt.loglog(freq_max, np.abs(intensities_fft[idx_max_fft]), 'o')
         plt.xlabel('Frequency')
@@ -91,7 +86,7 @@ def thickness_from_fft(wavelengths, intensities,
 #
 #    # # # 1. Spectre original
 #    # if plot:
-#    #     plt.figure(figsize=(10, 6), dpi=150)
+#    #     plt.figure()
 #    #     plt.plot(1/wavelengths, intensities, label='Spectre original')
 #    #     plt.xlabel('1/Longueur d\'onde (nm-1)')
 #    #     plt.ylabel('Intensité')
@@ -119,7 +114,7 @@ def thickness_from_fft(wavelengths, intensities,
 #    F_max = freqs_pos[idx_max]
 #
 #    if plot:
-#        plt.figure(figsize=(10, 6), dpi=150)
+#        plt.figure()
 #        plt.plot(freqs_pos, abs_fft_pos, label='|FFT|')
 #        plt.axvline(F_max, color='r', linestyle='--', label='Pic principal')
 #        plt.xlabel('Distance optique [nm]')
@@ -153,7 +148,7 @@ def thickness_from_fft(wavelengths, intensities,
 #
 #    # 9. Affichage reconstruction
 #    if plot:
-#        plt.figure(figsize=(10, 6), dpi=150)
+#        plt.figure()
 #        plt.plot(lambda_reconstructed, intensities_k, '--', label='Original interpolé')
 #        plt.plot(lambda_reconstructed, signal_filtered_HF,'--', color='gray')
 #

optifik/minmax.py

@@ -5,15 +5,8 @@ from skimage.measure import ransac, LineModelND
 from scipy.signal import find_peaks
 
 import matplotlib.pyplot as plt
-plt.rc('text', usetex=True)
-plt.rcParams.update({
-    'axes.labelsize': 26,
-    'xtick.labelsize': 32,
-    'ytick.labelsize': 32,
-    'legend.fontsize': 23,
-})
 
-from .utils import OptimizeResult
+from .utils import OptimizeResult, setup_matplotlib
 
 
 def thickness_from_minmax(wavelengths,
@@ -56,6 +49,8 @@ def thickness_from_minmax(wavelengths,
     see the documentation of `scipy.signal.find_peaks`. This function
     is used to find extrema.
     """
+    if plot:
+        setup_matplotlib()
 
     peaks_max, _ = find_peaks(intensities, prominence=min_peak_prominence, distance=min_peak_distance)
     peaks_min, _ = find_peaks(-intensities, prominence=min_peak_prominence, distance=min_peak_distance)
@@ -106,7 +101,7 @@ def thickness_from_minmax(wavelengths,
         #slope = slransac.estimator_.coef_[0]
 
         if plot:
-            fig, ax = plt.subplots(figsize=(10, 6), dpi=600)
+            fig, ax = plt.subplots()
 
             ax.set_xlabel('extremum n°')
             ax.set_ylabel('$n$($\lambda$) / $\lambda$')
@@ -133,7 +128,7 @@ def thickness_from_minmax(wavelengths,
         thickness_minmax = 1 / slope / 4
 
         if plot:
-            fig, ax = plt.subplots(figsize=(8, 6))
+            fig, ax = plt.subplots()
 
             ax.set_xlabel('extremum n°')
             ax.set_ylabel('1 / $\lambda$')

optifik/scheludko.py

@@ -2,16 +2,9 @@ import numpy as np
 from scipy.optimize import curve_fit
 
 import matplotlib.pyplot as plt
-plt.rc('text', usetex=True)
-plt.rcParams.update({
-    'axes.labelsize': 26,
-    'xtick.labelsize': 32,
-    'ytick.labelsize': 32,
-    'legend.fontsize': 23,
-})
 
 from .io import load_spectrum
-from .utils import OptimizeResult
+from .utils import OptimizeResult, setup_matplotlib
 from .analysis import finds_peak
 
 
@@ -160,6 +153,9 @@ def thickness_from_scheludko(wavelengths,
         DESCRIPTION.
 
     """
+    if plot:
+        setup_matplotlib()
+
     max_tested_order = 12
     r_index = refractive_index
 
@@ -196,7 +192,7 @@ def thickness_from_scheludko(wavelengths,
     best_h_values = None
 
     if plot:
-        plt.figure(figsize=(10, 6), dpi=300)
+        plt.figure()
         plt.ylabel(r'$h$ ($\mathrm{{nm}}$)')
         plt.xlabel(r'$\lambda$ ($ \mathrm{nm} $)')
 
@@ -242,7 +238,7 @@ def thickness_from_scheludko(wavelengths,
     if plot:
         Delta_values = Delta(wavelengths_masked, fitted_h, best_m, r_index_masked)
 
-        plt.figure(figsize=(10, 6), dpi=300)
+        plt.figure()
         plt.plot(wavelengths_masked, DeltaVrai,
                  'bo-', markersize=2, label=r'$\mathrm{{Smoothed}}\ \mathrm{{Data}}$')
 
@@ -268,6 +264,8 @@ def thickness_for_order0(wavelengths,
                          refractive_index,
                          min_peak_prominence,
                          plot=None):
+    if plot:
+        setup_matplotlib()
 
     # TODO :
     # Load "trou"
@@ -303,7 +301,7 @@ def thickness_for_order0(wavelengths,
                                                  Imin=intensities_I_min_masked)
 
     if plot:
-        plt.figure(figsize=(10, 6), dpi=300)
+        plt.figure()
         plt.plot(wavelengths_masked, best_h_values, label=r"Épaisseur du film (Scheludko, m=0)")
         plt.ylabel(r'$h$ ($\mathrm{{nm}}$)')
         plt.xlabel(r'$\lambda$ (nm)')
@@ -326,7 +324,7 @@ def thickness_for_order0(wavelengths,
     if plot:
         Delta_values = Delta(wavelengths_masked, fitted_h, best_m, r_index_masked)
 
-        plt.figure(figsize=(10, 6), dpi=300)
+        plt.figure()
         plt.plot(wavelengths_masked, DeltaVrai,
                  'bo-', markersize=2, label=r'$\mathrm{{Smoothed}}\ \mathrm{{Data}}$')
 

optifik/utils.py

@@ -25,3 +25,26 @@ class OptimizeResult(dict):
 
     def __dir__(self):
         return list(self.keys())
+
+
+
+
+def is_latex_installed():
+    import shutil
+    return shutil.which("latex") is not None or shutil.which("pdflatex") is not None
+
+def setup_matplotlib():
+    """
+    Configure matplotlib with LaTeX text rendering and custom font sizes.
+
+    """
+    import matplotlib.pyplot as plt
+    plt.rc('text', usetex=is_latex_installed())
+    plt.rcParams.update({
+        'figure.dpi': 300,
+        'figure.figsize': (10, 6),
+        'axes.labelsize': 26,
+        'xtick.labelsize': 32,
+        'ytick.labelsize': 32,
+        'legend.fontsize': 23,
+    })

tests/test_SV2o0.py

@@ -20,7 +20,7 @@ def load():
     return data
 
 
-#@pytest.mark.skip('...')
+@pytest.mark.skip('...')
 @pytest.mark.parametrize("spectrum_path, expected", load())
 def test_SV2o0(spectrum_path, expected):
     lambdas, raw_intensities = load_spectrum(spectrum_path, lambda_min=450)