Created
April 29, 2018 09:19
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Sample for `gp_minimize` result problem
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": { | |
"ExecuteTime": { | |
"end_time": "2018-04-29T09:15:21.945886Z", | |
"start_time": "2018-04-29T09:15:21.586972Z" | |
} | |
}, | |
"outputs": [], | |
"source": [ | |
"from skopt import gp_minimize\n", | |
"from skopt.space import Integer" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": { | |
"ExecuteTime": { | |
"end_time": "2018-04-29T09:15:21.951330Z", | |
"start_time": "2018-04-29T09:15:21.948290Z" | |
} | |
}, | |
"outputs": [], | |
"source": [ | |
"def obj_fun(x):\n", | |
" return 1" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": { | |
"ExecuteTime": { | |
"end_time": "2018-04-29T09:15:21.967865Z", | |
"start_time": "2018-04-29T09:15:21.953400Z" | |
} | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"[Integer(low=-2.0, high=2.0)]" | |
] | |
}, | |
"execution_count": 3, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"dimensions = [Integer(low=-2.0, high=2.0, name=\"Foobar\")]\n", | |
"dimensions" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": { | |
"ExecuteTime": { | |
"end_time": "2018-04-29T09:15:22.060883Z", | |
"start_time": "2018-04-29T09:15:21.969834Z" | |
} | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
" fun: 1\n", | |
" func_vals: array([1])\n", | |
" models: [GaussianProcessRegressor(alpha=1e-10, copy_X_train=True,\n", | |
" kernel=1**2 * Matern(length_scale=1, nu=2.5) + WhiteKernel(noise_level=1),\n", | |
" n_restarts_optimizer=2, noise='gaussian', normalize_y=True,\n", | |
" optimizer='fmin_l_bfgs_b', random_state=1854753297)]\n", | |
" random_state: <mtrand.RandomState object at 0x7f7df40d0b40>\n", | |
" space: Space([Integer(low=-2.0, high=2.0)])\n", | |
" specs: {'function': 'base_minimize', 'args': {'n_restarts_optimizer': 5, 'y0': None, 'base_estimator': GaussianProcessRegressor(alpha=1e-10, copy_X_train=True,\n", | |
" kernel=1**2 * Matern(length_scale=1, nu=2.5),\n", | |
" n_restarts_optimizer=2, noise='gaussian', normalize_y=True,\n", | |
" optimizer='fmin_l_bfgs_b', random_state=1854753297), 'n_jobs': 1, 'func': <function obj_fun at 0x7f7dc8413158>, 'random_state': <mtrand.RandomState object at 0x7f7df40d0b40>, 'callback': None, 'xi': 0.01, 'n_random_starts': 1, 'dimensions': Space([Integer(low=-2.0, high=2.0)]), 'verbose': False, 'n_calls': 1, 'kappa': 1.96, 'acq_func': 'gp_hedge', 'x0': None, 'acq_optimizer': 'auto', 'n_points': 10000}}\n", | |
" x: [-1]\n", | |
" x_iters: [[-1]]" | |
] | |
}, | |
"execution_count": 4, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"res = gp_minimize(obj_fun,\n", | |
" dimensions,\n", | |
" n_calls=1,\n", | |
" n_random_starts=1)\n", | |
"res" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": { | |
"ExecuteTime": { | |
"end_time": "2018-04-29T09:15:22.168280Z", | |
"start_time": "2018-04-29T09:15:22.062777Z" | |
} | |
}, | |
"outputs": [ | |
{ | |
"ename": "AssertionError", | |
"evalue": "", | |
"output_type": "error", | |
"traceback": [ | |
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", | |
"\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", | |
"\u001b[0;32m<ipython-input-5-64e1417ccabc>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"specs\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"args\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"dimensions\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdimensions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"Foobar\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", | |
"\u001b[0;31mAssertionError\u001b[0m: " | |
] | |
} | |
], | |
"source": [ | |
"assert res[\"specs\"][\"args\"][\"dimensions\"].dimensions[0].name == \"Foobar\"" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.5.2" | |
}, | |
"varInspector": { | |
"cols": { | |
"lenName": 16, | |
"lenType": 16, | |
"lenVar": 40 | |
}, | |
"kernels_config": { | |
"python": { | |
"delete_cmd_postfix": "", | |
"delete_cmd_prefix": "del ", | |
"library": "var_list.py", | |
"varRefreshCmd": "print(var_dic_list())" | |
}, | |
"r": { | |
"delete_cmd_postfix": ") ", | |
"delete_cmd_prefix": "rm(", | |
"library": "var_list.r", | |
"varRefreshCmd": "cat(var_dic_list()) " | |
} | |
}, | |
"types_to_exclude": [ | |
"module", | |
"function", | |
"builtin_function_or_method", | |
"instance", | |
"_Feature" | |
], | |
"window_display": false | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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