mpl
This commit is contained in:
François Boulogne
parent
31eeb53dea
commit
9e77fc8f03
8 changed files with 57 additions and 40 deletions
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@ -10,11 +10,11 @@ plt.rcParams.update({
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'legend.fontsize': 23,
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})
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from .utils import setup_matplotlib
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def plot_spectrum(wavelengths, intensities, title=''):
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plt.figure(figsize=(10, 6), dpi=300)
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setup_matplotlib()
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plt.figure()
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plt.plot(wavelengths, intensities, 'o-', markersize=2)
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plt.xlabel(r'$\lambda$ (nm)')
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plt.ylabel(r'$I^*$')
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@ -46,11 +46,14 @@ def finds_peak(wavelengths, intensities, min_peak_prominence, min_peak_distance=
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(peaks_min, peaks_max)
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"""
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if plot:
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setup_matplotlib()
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peaks_max, _ = find_peaks(intensities, prominence=min_peak_prominence, distance=min_peak_distance)
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peaks_min, _ = find_peaks(-intensities, prominence=min_peak_prominence, distance=min_peak_distance)
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if plot:
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plt.figure(figsize=(10, 6), dpi=300)
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plt.figure()
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plt.plot(wavelengths, intensities, 'o-', markersize=2, label="Smoothed data")
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plt.plot(wavelengths[peaks_max], intensities[peaks_max], 'ro')
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plt.plot(wavelengths[peaks_min], intensities[peaks_min], 'ro')
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@ -4,16 +4,8 @@ from scipy.fftpack import fft, ifft, fftfreq
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import matplotlib.pyplot as plt
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plt.rc('text', usetex=True)
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plt.rcParams.update({
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'axes.labelsize': 26,
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'xtick.labelsize': 32,
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'ytick.labelsize': 32,
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'legend.fontsize': 23,
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})
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from .utils import OptimizeResult
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from .utils import OptimizeResult, setup_matplotlib
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@ -43,6 +35,9 @@ def thickness_from_fft(wavelengths, intensities,
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results : Instance of `OptimizeResult` class.
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The attribute `thickness` gives the thickness value in nm.
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"""
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if plot:
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setup_matplotlib()
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if num_half_space is None:
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num_half_space = 10 * len(wavelengths)
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@ -74,7 +69,7 @@ def thickness_from_fft(wavelengths, intensities,
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thickness_fft = freq_max / 2.
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if plot:
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plt.figure(figsize=(10, 6), dpi=300)
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plt.figure()
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plt.loglog(inverse_wavelengths_fft, np.abs(intensities_fft))
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plt.loglog(freq_max, np.abs(intensities_fft[idx_max_fft]), 'o')
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plt.xlabel('Frequency')
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@ -91,7 +86,7 @@ def thickness_from_fft(wavelengths, intensities,
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#
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# # # # 1. Spectre original
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# # if plot:
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# # plt.figure(figsize=(10, 6), dpi=150)
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# # plt.figure()
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# # plt.plot(1/wavelengths, intensities, label='Spectre original')
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# # plt.xlabel('1/Longueur d\'onde (nm-1)')
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# # plt.ylabel('Intensité')
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@ -119,7 +114,7 @@ def thickness_from_fft(wavelengths, intensities,
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# F_max = freqs_pos[idx_max]
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#
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# if plot:
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# plt.figure(figsize=(10, 6), dpi=150)
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# plt.figure()
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# plt.plot(freqs_pos, abs_fft_pos, label='|FFT|')
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# plt.axvline(F_max, color='r', linestyle='--', label='Pic principal')
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# plt.xlabel('Distance optique [nm]')
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@ -153,7 +148,7 @@ def thickness_from_fft(wavelengths, intensities,
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#
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# # 9. Affichage reconstruction
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# if plot:
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# plt.figure(figsize=(10, 6), dpi=150)
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# plt.figure()
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# plt.plot(lambda_reconstructed, intensities_k, '--', label='Original interpolé')
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# plt.plot(lambda_reconstructed, signal_filtered_HF,'--', color='gray')
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#
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@ -5,15 +5,8 @@ from skimage.measure import ransac, LineModelND
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from scipy.signal import find_peaks
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import matplotlib.pyplot as plt
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plt.rc('text', usetex=True)
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plt.rcParams.update({
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'axes.labelsize': 26,
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'xtick.labelsize': 32,
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'ytick.labelsize': 32,
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'legend.fontsize': 23,
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})
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from .utils import OptimizeResult
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from .utils import OptimizeResult, setup_matplotlib
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def thickness_from_minmax(wavelengths,
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@ -56,6 +49,8 @@ def thickness_from_minmax(wavelengths,
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see the documentation of `scipy.signal.find_peaks`. This function
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is used to find extrema.
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"""
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if plot:
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setup_matplotlib()
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peaks_max, _ = find_peaks(intensities, prominence=min_peak_prominence, distance=min_peak_distance)
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peaks_min, _ = find_peaks(-intensities, prominence=min_peak_prominence, distance=min_peak_distance)
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@ -106,7 +101,7 @@ def thickness_from_minmax(wavelengths,
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#slope = slransac.estimator_.coef_[0]
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if plot:
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fig, ax = plt.subplots(figsize=(10, 6), dpi=600)
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fig, ax = plt.subplots()
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ax.set_xlabel('extremum n°')
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ax.set_ylabel('$n$($\lambda$) / $\lambda$')
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@ -133,7 +128,7 @@ def thickness_from_minmax(wavelengths,
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thickness_minmax = 1 / slope / 4
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if plot:
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fig, ax = plt.subplots(figsize=(8, 6))
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fig, ax = plt.subplots()
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ax.set_xlabel('extremum n°')
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ax.set_ylabel('1 / $\lambda$')
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@ -2,16 +2,9 @@ import numpy as np
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from scipy.optimize import curve_fit
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import matplotlib.pyplot as plt
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plt.rc('text', usetex=True)
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plt.rcParams.update({
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'axes.labelsize': 26,
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'xtick.labelsize': 32,
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'ytick.labelsize': 32,
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'legend.fontsize': 23,
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})
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from .io import load_spectrum
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from .utils import OptimizeResult
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from .utils import OptimizeResult, setup_matplotlib
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from .analysis import finds_peak
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@ -160,6 +153,9 @@ def thickness_from_scheludko(wavelengths,
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DESCRIPTION.
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"""
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if plot:
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setup_matplotlib()
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max_tested_order = 12
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r_index = refractive_index
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@ -196,7 +192,7 @@ def thickness_from_scheludko(wavelengths,
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best_h_values = None
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if plot:
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plt.figure(figsize=(10, 6), dpi=300)
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plt.figure()
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plt.ylabel(r'$h$ ($\mathrm{{nm}}$)')
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plt.xlabel(r'$\lambda$ ($ \mathrm{nm} $)')
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@ -242,7 +238,7 @@ def thickness_from_scheludko(wavelengths,
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if plot:
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Delta_values = Delta(wavelengths_masked, fitted_h, best_m, r_index_masked)
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plt.figure(figsize=(10, 6), dpi=300)
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plt.figure()
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plt.plot(wavelengths_masked, DeltaVrai,
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'bo-', markersize=2, label=r'$\mathrm{{Smoothed}}\ \mathrm{{Data}}$')
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@ -268,6 +264,8 @@ def thickness_for_order0(wavelengths,
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refractive_index,
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min_peak_prominence,
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plot=None):
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if plot:
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setup_matplotlib()
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# TODO :
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# Load "trou"
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@ -303,7 +301,7 @@ def thickness_for_order0(wavelengths,
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Imin=intensities_I_min_masked)
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if plot:
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plt.figure(figsize=(10, 6), dpi=300)
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plt.figure()
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plt.plot(wavelengths_masked, best_h_values, label=r"Épaisseur du film (Scheludko, m=0)")
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plt.ylabel(r'$h$ ($\mathrm{{nm}}$)')
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plt.xlabel(r'$\lambda$ (nm)')
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@ -326,7 +324,7 @@ def thickness_for_order0(wavelengths,
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if plot:
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Delta_values = Delta(wavelengths_masked, fitted_h, best_m, r_index_masked)
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plt.figure(figsize=(10, 6), dpi=300)
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plt.figure()
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plt.plot(wavelengths_masked, DeltaVrai,
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'bo-', markersize=2, label=r'$\mathrm{{Smoothed}}\ \mathrm{{Data}}$')
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@ -25,3 +25,26 @@ class OptimizeResult(dict):
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def __dir__(self):
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return list(self.keys())
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def is_latex_installed():
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import shutil
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return shutil.which("latex") is not None or shutil.which("pdflatex") is not None
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def setup_matplotlib():
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"""
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Configure matplotlib with LaTeX text rendering and custom font sizes.
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"""
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import matplotlib.pyplot as plt
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plt.rc('text', usetex=is_latex_installed())
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plt.rcParams.update({
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'figure.dpi': 300,
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'figure.figsize': (10, 6),
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'axes.labelsize': 26,
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'xtick.labelsize': 32,
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'ytick.labelsize': 32,
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'legend.fontsize': 23,
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})
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