Ajout du materiel pour TP3

TP3/tp3-data.csv

+x,y
+0.0,1.7562656254169835
+0.5,3.3478933570678633
+1.0,4.6624545488463776
+1.5,5.125083079978194
+2.0,4.769628703005167
+2.5,3.815725656824885
+3.0,2.205250223212375
+3.5,1.0152716559103214
+4.0,-0.27440408274510014
+4.5,-1.3166591796810758
+5.0,-0.9482172345959369
+5.5,-0.27143471990585943
+6.0,1.2668984010815398
+6.5,2.5331431932836015
+7.0,3.8707778121598366
+7.5,4.986432853548176
+8.0,4.564295893398583
+8.5,4.046935739152962
+9.0,3.267502080592287
+9.5,2.1900301490557426
+10.0,-0.0184758061439797
+10.5,-0.43140929023368724
+11.0,-1.1009941045071576
+11.5,-0.767555722690707
+12.0,0.3265505097367498
+12.5,1.553778850694469

TP3/tp3.py

+from scipy.optimize import curve_fit
+import matplotlib.pyplot as plt
+
+import numpy as np
+import pandas as pd
+
+import sys
+
+def load_data(fn):
+    data = pd.read_csv(fn, sep=',')
+    return data
+
+def model_function(x, a, b):
+    return a * np.sin(x) + b
+
+def fit_data(x, y):
+    params, cov = curve_fit(model_function, x, y)
+
+    err = np.sqrt(np.diag(cov))
+
+    return params, err
+
+def plot_fit(x, y, params, errors):
+    plt.plot(
+        x, y, ls='', marker='o',
+        label='data'
+    )
+    plt.plot(
+        x, model_function(x, *params), '--',
+        label='fit'.format(*params)
+    )
+    plt.title(
+        r'$f(x) = a \times sin(x) + b$, with a = {:.2f} $\pm$ {:.2f}, b = {:.2f} $\pm$ {:.2f}'.format(
+            *np.transpose((params, errors)).flatten()
+        )
+    )
+    plt.xlabel('x')
+    plt.ylabel('y')
+    plt.legend()
+    plt.show()
+
+def main():
+    """ TBD """
+    fn = sys.argv[1]
+
+    data = load_data(fn)
+
+    params, errors = fit_data(data['x'], data['y'])
+
+    plot_fit(data['x'], data['y'], params, errors)
+
+
+if __name__ == "__main__":
+    main()