import argparse
from test_function import run
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Step methods')
parser.add_argument('-f', '--function', default="rosenbrock", type=str, help='Function to minimize: rosenbrock, wood')
parser.add_argument('-m', '--method', default="dfp", type=str, help='Quasi-Newton optimization method: dfp, bfgs')
args = parser.parse_args()
run(args.function, args.method)
import argparse
from test_function import run
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Step methods')
parser.add_argument('-p',
'--point',
default="const",
type=str,
help='Type of starting point x: const, rand')
parser.add_argument('-f',
'--function',
default="rosenbrock",
type=str,
help='Function to minimize: rosenbrock, wood')
parser.add_argument('-b',
'--beta',
default="fr",
type=str,
help='Function to minimize: fr, pr, hs')
args = parser.parse_args()
run(args.point, args.function, args.beta)
import argparse
from test_function import run
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Newton method')
parser.add_argument('-s', '--step', default="fijo", type=str, help='Gradient step size method to use: fijo, hess, back')
parser.add_argument('-p', '--point', default="const", type=str, help='Type of starting point x: const, rand')
parser.add_argument('-l', '--lambda_', default=1, type=int, help='Function parameter: 1, 100, 1000')
parser.add_argument('-m', '--method', default="newton", type=str, help='Optimization method: gd, newton')
args = parser.parse_args()
run(args.step, args.point, args.lambda_, args.method)
import argparse
from test_function import run
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Step methods')
parser.add_argument(
'-s',
'--step',
default="cubic",
type=str,
help='Gradient step size method to use: cubic, barzilai, zhang')
parser.add_argument('-p',
'--point',
default="const",
type=str,
help='Type of starting point x: const, rand')
parser.add_argument('-f',
'--function',
default="rosenbrock",
type=str,
help='Function to minimize: rosenbrock, wood, mnist')
args = parser.parse_args()
run(args.step, args.point, "gd", args.function)
import argparse
from test_function import run
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Step methods')
parser.add_argument('-p', '--point', default="const", type=str, help='Type of starting point x: const, rand')
parser.add_argument('-f', '--function', default="quadratic", type=str, help='Function to minimize: quadratic')
parser.add_argument('-d', '--dim', default=128, type=int, help='Dimension of function matrix')
parser.add_argument('-l', '--penalization', default=1, type=int, help='Regularization parameter')
args = parser.parse_args()
run(args.point, args.dim, args.penalization, args.function)
import argparse
from test_function import run
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Newton method')
parser.add_argument('-m',
'--method',
default="dogleg",
type=str,
help='Method to use: dogleg, lstr')
parser.add_argument('-p',
'--point',
default="const",
type=str,
help='Type of starting point x: const, rand')
args = parser.parse_args()
run(args.method, args.point)