Code for optimization 4

optimization4.py

import pyswarm as pso

# Define objective function. "pipe" as model
def f(X):
  return -pipe.predict(X.reshape(1,-1)) # Minus sign to optimize

# Lower bounds of feature variables in the order of X.columns
lb = np.array([3480, 2e4, 1.5, 0.09, 0.1, 1, 0.001])

# Upper bounds of feature variables in the order of X.columns
ub = np.array([3480, 9e4, 2.5, 0.09, 0.1, 1, 0.001])
ub += 1e-10

# Solve optimization
xopt, fopt = pso(f, lb, ub, swarmsize=200, omega=0.3, phip=.5, 
                 phig=0.7, maxiter=1000, minstep=1e-8)

# Print values that causes maximum ROP from xopt
for i in range(len(X.columns)):
  print(f'{X.columns[i]}: {xopt[i]:.2f}')

# Print value of maximum ROP from popt
print(f'Maximum ROP achieved: {-fopt}')