def __init__(self, function, args=(), bounds=None,
callback=None, options=None, processes=None):
ParallelResources().arguments = args
ParallelResources().custom_function = function
self.xval = None
self.function_value = None
self.jacobian_value = None
self.precision = self.K.np.finfo(self.K.qnp.dtypes("DTYPE")).eps
self.bounds = bounds
self.callback = callback
self.options = options
self.processes = processes
def run(self, x0):
"""Executes parallel L-BFGS-B minimization.
Args:
x0 (numpy.array): guess for initial solution.
Returns:
scipy.minimize result object
"""
ParallelResources().lock = self.mp.Lock()
with self.mp.Pool(processes=self.processes) as self.pool:
from scipy.optimize import minimize
out = minimize(fun=self.fun, x0=x0, jac=self.jac, method='L-BFGS-B',
bounds=self.bounds, callback=self.callback, options=self.options)
ParallelResources().reset()
out.hess_inv = out.hess_inv * self.K.np.identity(len(x0))
return out