qubx.optimize

Module optimize

Globally available pluggable optimizer framework.

QUB Express is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

QUB Express is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License, named LICENSE.txt, in the QUB Express program directory. If not, see <http://www.gnu.org/licenses/>.

Functions

[hide private]

add_opt(name, optimize, defaults, priority=5)

source code

bfgs_optimize(options, pars, func, on_iter, grad_func=None)

source code

del_opt(name)

source code

dfp_optimize(options, pars, func, on_iter, grad_func=None)

source code

get_opt(profile='default_optimize', options={}) source code

get_options(profile='default_optimize', options={}, method=None) source code

get_opts(profile='default_optimize', options={}, on_start=<__builtin__.function object>, on_end=<__builtin__.function object>) source code

node_pydata(node)

source code

null_optimize(options, pars, func, on_iter, grad_func=None)

source code

num_grad(func, nx, dx=1e-06)

source code

optimize(pars, func, on_iter, grad_func=None, profile='default_optimize', options={}, multi_method=False) source code

set_opt_priority(profile, method, priority)

source code

set_options(profile='default_optimize', options={}, method=None) source code

setup_opt(profile, defaults={}, method=None) source code

setup_opts(profile, defaults={}) source code

simplex_optimize(options, pars, func, on_iter, grad_func=None)

source code

Variables

[hide private]

OnOptOptions = <qubx.util_types.WeakEvent object>

OnOptimizerAdded = <qubx.util_types.WeakEvent object>

__package__ = 'qubx'

g_opt_ix = {'BFGS': 1, 'DFP': 0, 'Simplex': 2}

g_optimizers = [{'defaults': {'conv LL': 1e-06, 'conv grad': 1...

Variables Details

[hide private]

g_optimizers

Value:

[{'defaults': {'conv LL': 1e-06,
               'conv grad': 1e-06,
               'max iterations': 100,
               'max restarts': 0,
               'max step': 0.1,
               'num grad dx': 0.0001,
               'perturb': 0.01},
  'name': 'DFP',
...