import json
 
import numpy as np
import scipy as sp
 
import scipy.optimize as opt
 
 
data = """0.4  30 0.005109202
0.4    37 0.007
0.4    45 0.014261093
0.5    30 0.007155778
0.5    37 0.009
0.5    45 0.018
0.6    30 0.008716752
0.6    37 0.010710971
0.6    45 0.020222402scipy.optimize
""".splitlines()
data = np.array([list(map(float,line.split())) for line in data])
 
Y = data[1]+272
X = data[0]
Z = data[-1]
 
xy = np.vstack([X,Y])
fun = lambda xy,w1,w2,w3: w1*np.exp(X*w2-w3/Y)
popt = opt.curve_fit(fun,xy,Z,p0=[0.1,.2,.3])
print ("GOT:%s"%popt)
print ("Expected: [6926617.247,1.848807397,6578.503923]")

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