Homework_2018_1_11_1032478036.ipynb

Kernel: Python 3

%pylab inline
import scipy.optimize as opt
import numpy as np


# Datos
T_values = np.array([222, 284, 308.5, 333, 358, 411, 477, 518, 880, 1080, 1259])
C_values = np.array([0.1282, 0.2308, 0.2650, 0.3120 , 0.3547, 0.4530, 0.5556, 0.6154, 0.8932, 0.9103, 0.9316])

x_samp = T_values
y_samp = C_values  

Populating the interactive namespace from numpy and matplotlib

def func(x, A, c, d):
    return A*np.exp(c*x) + d

plt.plot(x_samp, y_samp, "ko", label="Data")

x_lin = np.linspace(0, x_samp.max(), 50)                   

# Intentos
A, c, d = -1, -1e-2, 1
y_trial1 = func(x_lin,  A,     c, d)
y_trial2 = func(x_lin, -1, -1e-3, 1)
y_trial3 = func(x_lin, -1, -3e-3, 1)
y_trial4 = func(x_lin, -1, -1.5e-3, 1)

plt.plot(x_lin, y_trial1, "--", label="Trial 1")
plt.plot(x_lin, y_trial2, "--", label="Trial 2")
plt.plot(x_lin, y_trial3, "--", label="Trial 3")
plt.plot(x_lin, y_trial4, "--", label="Trial 4")
plt.legend()

<matplotlib.legend.Legend at 0x7f258b55e9e8>