{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Run a larger benchmark" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# import olympus\n", "from olympus import Olympus" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# create olympus\n", "olymp = Olympus()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['BasinHopping',\n", " 'Cma',\n", " 'ConjugateGradient',\n", " 'DifferentialEvolution',\n", " 'Genetic',\n", " 'Gpyopt',\n", " 'Grid',\n", " 'Hyperopt',\n", " 'LatinHypercube',\n", " 'Lbfgs',\n", " 'ParticleSwarms',\n", " 'Phoenics',\n", " 'RandomSearch',\n", " 'Simplex',\n", " 'Slsqp',\n", " 'Snobfit',\n", " 'Sobol',\n", " 'SteepestDescent']" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from olympus import list_planners\n", "list_planners()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "planners=['Gpyopt', 'Hyperopt', 'ConjugateGradient']" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m\u001b[0;37m[INFO] Loading emulator using a BayesNeuralNet model for the dataset alkox...\n", "\u001b[0m" ] } ], "source": [ "olymp.benchmark(dataset='alkox', planners=planners, num_iter=20)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot results" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "from olympus import Plotter" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plotter = Plotter()\n", "plotter.plot_from_db(olymp.evaluator.database)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "olympus", "language": "python", "name": "olympus" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 4 }