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xbasic = 10


    

    
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10

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import numpy as np
from scipy.optimize import minimize
from scipy.special import expit
import matplotlib.pyplot as plt

def cost(v,w,u,t):
    v = np.array(v)   # Don't know why but np.asarray(v) doesn't work here.
    w = np.array(w)
    u = np.array(u)
    
    fvec = np.array(trigf(t*w + u) )  # This is a vector!!!
    yt = 1 + np.sum ( t * v * fvec  )  # For a given t, this calculates the value of y(t), given the parameters, v, w, u.
    return  ( np.sum (v*fvec + t * v* fvec * ( 1 -  fvec  ) * w ) + yt )   ** 2

def trigf(x):
    #return 1/(1+np.exp(-x)) #
    return expit(x)

def costTotal(v,w,u,t):
    t = np.array(t)
    costt = 0
    for temp in t:
        costt = costt + cost(v,w,u,temp)
    return costt

costTotalF = lambda x: costTotal(np.split(x,3)[0],np.split(x,3)[1],np.split(x,3)[2],tlin)