From ff2c251f95c07802c9173012c71313be5f4706d9 Mon Sep 17 00:00:00 2001 From: Jakob Vanhoefer Date: Tue, 21 Apr 2020 10:34:52 +0200 Subject: [PATCH 1/9] set allow_failed_starts to TRUE, closes #280 --- pypesto/optimize/options.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pypesto/optimize/options.py b/pypesto/optimize/options.py index 6e99beac1..ea29b6bd1 100644 --- a/pypesto/optimize/options.py +++ b/pypesto/optimize/options.py @@ -17,7 +17,7 @@ class OptimizeOptions(dict): def __init__(self, startpoint_resample: bool = False, - allow_failed_starts: bool = False): + allow_failed_starts: bool = True): super().__init__() self.startpoint_resample: bool = startpoint_resample From 88b4c11e5fbe7cc46fc49a4792825900fdb15735 Mon Sep 17 00:00:00 2001 From: Jakob Vanhoefer Date: Fri, 24 Apr 2020 12:48:45 +0200 Subject: [PATCH 2/9] add notebook plotting before writing --- doc/example/hdf5_storage.ipynb | 1766 ++++++++++++++++++++++++++++++++ doc/example/history.hdf5 | Bin 0 -> 59829272 bytes 2 files changed, 1766 insertions(+) create mode 100644 doc/example/hdf5_storage.ipynb create mode 100644 doc/example/history.hdf5 diff --git a/doc/example/hdf5_storage.ipynb b/doc/example/hdf5_storage.ipynb new file mode 100644 index 000000000..1e444b073 --- /dev/null +++ b/doc/example/hdf5_storage.ipynb @@ -0,0 +1,1766 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Save and load results as HDF5 files" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pypesto\n", + "import numpy as np\n", + "import scipy as sp\n", + "import matplotlib.pyplot as plt\n", + "from pypesto.storage import (save_to_hdf5, read_from_hdf5)\n", + "import tempfile\n", + "\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Define the objective and problem" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "objective = pypesto.Objective(fun=sp.optimize.rosen, \n", + " grad=sp.optimize.rosen_der, \n", + " hess=sp.optimize.rosen_hess)\n", + "\n", + "dim_full = 10\n", + "lb = -5 * np.ones((dim_full, 1))\n", + "ub = 5 * np.ones((dim_full, 1))\n", + "\n", + "problem = pypesto.Problem(objective=objective, lb=lb, ub=ub)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Define history options and run optimization" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "# create optimizers\n", + "optimizer = pypesto.ScipyOptimizer(method='l-bfgs-b')\n", + "\n", + "# set number of starts\n", + "n_starts = 20\n", + "\n", + "# save optimizer trace (to temporary file fn)\n", + "fn = tempfile.mktemp(\".hdf5\")\n", + "history_options = pypesto.HistoryOptions(trace_record=True, storage_file=fn)\n", + "\n", + "# Run optimizaitons\n", + "result = pypesto.minimize(\n", + " problem=problem, optimizer=optimizer,\n", + " n_starts=n_starts, history_options=history_options)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'id': '11',\n", + " 'x': array([1.00000005, 1.00000002, 0.99999997, 0.99999994, 0.99999998,\n", + " 0.99999995, 0.99999987, 0.9999997 , 0.99999938, 0.99999876]),\n", + " 'fval': 2.7682066563449697e-12,\n", + " 'grad': array([ 3.56917101e-05, 6.21783821e-06, -1.29678566e-05, -3.54813057e-05,\n", + " 2.10642260e-05, 7.77788988e-06, 1.40060932e-05, -4.14461009e-06,\n", + " -2.09261122e-06, -1.06297240e-06]),\n", + " 'hess': None,\n", + " 'res': None,\n", + " 'sres': None,\n", + " 'n_fval': 71,\n", + " 'n_grad': 71,\n", + " 'n_hess': 0,\n", + " 'n_res': 0,\n", + " 'n_sres': 0,\n", + " 'x0': array([1.00000005, 1.00000002, 0.99999997, 0.99999994, 0.99999998,\n", + " 0.99999995, 0.99999987, 0.9999997 , 0.99999938, 0.99999876]),\n", + " 'fval0': 81560.13716677667,\n", + " 'history': 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'time': 0.34848999977111816,\n", + " 'message': b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'},\n", + " {'id': '0',\n", + " 'x': array([1.00000087, 1.00000067, 0.99999959, 1.00000103, 1.00000022,\n", + " 0.9999995 , 0.99999973, 0.99999934, 0.99999864, 0.99999857]),\n", + " 'fval': 1.417826114528777e-09,\n", + " 'grad': array([ 4.33966920e-04, 4.82555895e-04, -1.08882267e-03, 1.10755548e-03,\n", + " 1.18694455e-05, -4.81428949e-04, 1.93116898e-04, -8.63375236e-06,\n", + " -5.28979151e-04, 2.58920220e-04]),\n", + " 'hess': None,\n", + " 'res': None,\n", + " 'sres': None,\n", + " 'n_fval': 76,\n", + " 'n_grad': 76,\n", + " 'n_hess': 0,\n", + " 'n_res': 0,\n", + " 'n_sres': 0,\n", + " 'x0': array([1.00000087, 1.00000067, 0.99999959, 1.00000103, 1.00000022,\n", + " 0.9999995 , 0.99999973, 0.99999934, 0.99999864, 0.99999857]),\n", + " 'fval0': 63130.89834100058,\n", + " 'history': ,\n", + " 'exitflag': 0,\n", + " 'time': 0.3766148090362549,\n", + " 'message': b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'},\n", + " {'id': '12',\n", + " 'x': array([-0.9932634 , 0.99660607, 0.99824064, 0.99898849, 0.99922613,\n", + " 0.9990736 , 0.99845425, 0.99705653, 0.99417999, 0.98839388]),\n", + " 'fval': 3.986579112354771,\n", + " 'grad': array([-6.29293794e-06, 1.46194378e-05, -1.02797014e-05, 5.09143111e-05,\n", + " -2.19220241e-05, -7.36653388e-05, -1.60499003e-05, 3.53453576e-06,\n", + " 2.34854848e-06, 5.28048829e-06]),\n", + " 'hess': None,\n", + " 'res': None,\n", + " 'sres': None,\n", + " 'n_fval': 90,\n", + " 'n_grad': 90,\n", + " 'n_hess': 0,\n", + " 'n_res': 0,\n", + " 'n_sres': 0,\n", + " 'x0': array([-0.9932634 , 0.99660607, 0.99824064, 0.99898849, 0.99922613,\n", + " 0.9990736 , 0.99845425, 0.99705653, 0.99417999, 0.98839388]),\n", + " 'fval0': 80827.98262715929,\n", + " 'history': ,\n", + " 'exitflag': 0,\n", + " 'time': 0.3358290195465088,\n", + " 'message': b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'},\n", + " {'id': '19',\n", + " 'x': array([-0.99326355, 0.99660602, 0.99824056, 0.99898832, 0.99922611,\n", + " 0.99907386, 0.9984544 , 0.99705634, 0.99417969, 0.98839315]),\n", + " 'fval': 3.9865791123923526,\n", + " 'grad': array([-1.42137766e-04, -6.19557824e-05, -2.52311345e-06, -7.80811712e-05,\n", + " -7.88294376e-05, 1.38404103e-04, 1.05327202e-04, -1.24875181e-04,\n", + " 6.74884048e-05, -2.03548953e-05]),\n", + " 'hess': None,\n", + " 'res': None,\n", + " 'sres': None,\n", + " 'n_fval': 83,\n", + " 'n_grad': 83,\n", + " 'n_hess': 0,\n", + " 'n_res': 0,\n", + " 'n_sres': 0,\n", + " 'x0': array([-0.99326355, 0.99660602, 0.99824056, 0.99898832, 0.99922611,\n", + " 0.99907386, 0.9984544 , 0.99705634, 0.99417969, 0.98839315]),\n", + " 'fval0': 152367.63738010806,\n", + " 'history': ,\n", + " 'exitflag': 0,\n", + " 'time': 0.3397550582885742,\n", + " 'message': b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'},\n", + " {'id': '8',\n", + " 'x': array([-0.99326354, 0.99660635, 0.9982411 , 0.99898911, 0.99922665,\n", + " 0.99907414, 0.99845445, 0.99705619, 0.99417957, 0.98839336]),\n", + " 'fval': 3.9865791125647974,\n", + " 'grad': array([-6.81398759e-06, 5.15410274e-05, 9.36531764e-05, 2.81724800e-04,\n", + " 2.80954190e-05, 1.83201765e-04, 1.03438984e-04, -2.46692514e-04,\n", + " -7.22555838e-05, 6.79444861e-05]),\n", + " 'hess': None,\n", + " 'res': None,\n", + " 'sres': None,\n", + " 'n_fval': 69,\n", + " 'n_grad': 69,\n", + " 'n_hess': 0,\n", + " 'n_res': 0,\n", + " 'n_sres': 0,\n", + " 'x0': array([-0.99326354, 0.99660635, 0.9982411 , 0.99898911, 0.99922665,\n", + " 0.99907414, 0.99845445, 0.99705619, 0.99417957, 0.98839336]),\n", + " 'fval0': 67684.45327793146,\n", + " 'history': ,\n", + " 'exitflag': 0,\n", + " 'time': 0.26124000549316406,\n", + " 'message': b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'},\n", + " {'id': '14',\n", + " 'x': array([-0.99326353, 0.99660592, 0.99824049, 0.99898737, 0.99922562,\n", + " 0.99907349, 0.99845565, 0.99705897, 0.99418739, 0.98840851]),\n", + " 'fval': 3.986579113853082,\n", + " 'grad': array([-1.69915409e-04, -1.34285870e-04, 3.52549034e-04, -8.05284701e-04,\n", + " -4.37775280e-05, -5.35826265e-04, 4.49405632e-04, -1.07724058e-03,\n", + " 5.61790161e-04, -1.25127227e-05]),\n", + " 'hess': None,\n", + " 'res': None,\n", + " 'sres': None,\n", + " 'n_fval': 82,\n", + " 'n_grad': 82,\n", + " 'n_hess': 0,\n", + " 'n_res': 0,\n", + " 'n_sres': 0,\n", + " 'x0': array([-0.99326353, 0.99660592, 0.99824049, 0.99898737, 0.99922562,\n", + " 0.99907349, 0.99845565, 0.99705897, 0.99418739, 0.98840851]),\n", + " 'fval0': 142757.01333794554,\n", + " 'history': ,\n", + " 'exitflag': 0,\n", + " 'time': 0.30585289001464844,\n", + " 'message': b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'}]" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result.optimize_result.list" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import pypesto.visualize\n", + "\n", + "# plot waterfalls\n", + "pypesto.visualize.waterfall(result, size=(15,6))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plot trace" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "pypesto.visualize.optimizer_history(result,\n", + " legends=['L-BFGS-B'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Save optimization result as HDF5 file" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "fn = tempfile.mktemp(\".hdf5\")\n", + "\n", + "# Write result\n", + "hdf5_writer = save_to_hdf5.OptimizationResultHDF5Writer(fn)\n", + "hdf5_writer.write(result)\n", + "\n", + "# Write problem\n", + "hdf5_writer = save_to_hdf5.ProblemHDF5Writer(fn)\n", + "hdf5_writer.write(problem)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Reload results" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "# Read result and problem\n", + "hdf5_reader = read_from_hdf5.OptimizationResultHDF5Reader(fn)\n", + "result = hdf5_reader.read()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'id': '6',\n", + " 'x': array([0.99999999, 0.99999996, 0.99999996, 1. , 0.99999992,\n", + " 0.99999989, 0.99999985, 0.99999981, 0.99999959, 0.9999992 ]),\n", + " 'fval': 3.876916587530421e-12,\n", + " 'grad': array([ 4.74249170e-06, -1.83388892e-05, -2.31891516e-05, 4.39123554e-05,\n", + " -3.07140007e-05, -1.74172713e-05, -3.65503147e-05, 4.02846163e-05,\n", + " -2.25797193e-05, 6.82685417e-06]),\n", + " 'hess': None,\n", + " 'res': None,\n", + " 'sres': None,\n", + " 'n_fval': 85,\n", + " 'n_grad': 85,\n", + " 'n_hess': 0,\n", + " 'n_res': 0,\n", + " 'n_sres': 0,\n", + " 'x0': array([0.99999999, 0.99999996, 0.99999996, 1. , 0.99999992,\n", + " 0.99999989, 0.99999985, 0.99999981, 0.99999959, 0.9999992 ]),\n", + " 'fval0': 105515.07553734496,\n", + " 'history': None,\n", + 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None,\n", + " 'exitflag': 0,\n", + " 'time': 0.3000340461730957,\n", + " 'message': b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'},\n", + " {'id': '10',\n", + " 'x': array([-0.9932629 , 0.99660567, 0.99824045, 0.99898859, 0.99922651,\n", + " 0.9990742 , 0.99845501, 0.99705765, 0.99418221, 0.98839845]),\n", + " 'fval': 3.986579112466846,\n", + " 'grad': array([ 2.20074474e-04, -1.21263380e-04, -7.37896144e-05, 7.44582788e-05,\n", + " 7.53255343e-05, 7.73048243e-05, 5.31259262e-05, -7.08765952e-05,\n", + " -6.08179400e-05, 3.86485501e-05]),\n", + " 'hess': None,\n", + " 'res': None,\n", + " 'sres': None,\n", + " 'n_fval': 65,\n", + " 'n_grad': 65,\n", + " 'n_hess': 0,\n", + " 'n_res': 0,\n", + " 'n_sres': 0,\n", + " 'x0': array([-0.9932629 , 0.99660567, 0.99824045, 0.99898859, 0.99922651,\n", + " 0.9990742 , 0.99845501, 0.99705765, 0.99418221, 0.98839845]),\n", + " 'fval0': 106491.98982000217,\n", + " 'history': None,\n", + " 'exitflag': 0,\n", + " 'time': 0.25257396697998047,\n", + " 'message': b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'},\n", + " {'id': '15',\n", + " 'x': array([-0.9932635 , 0.9966062 , 0.99824082, 0.99898879, 0.99922684,\n", + " 0.99907452, 0.99845525, 0.99705774, 0.99418212, 0.98839847]),\n", + " 'fval': 3.9865791124939296,\n", + " 'grad': array([-3.27058045e-05, 2.64119397e-05, 6.57207294e-06, -8.65558968e-06,\n", + " 2.00923405e-04, 1.72555548e-04, 1.24018660e-04, -3.96865343e-05,\n", + " -1.86500732e-04, 7.47144277e-05]),\n", + " 'hess': None,\n", + " 'res': None,\n", + " 'sres': None,\n", + " 'n_fval': 66,\n", + " 'n_grad': 66,\n", + " 'n_hess': 0,\n", + " 'n_res': 0,\n", + " 'n_sres': 0,\n", + " 'x0': array([-0.9932635 , 0.9966062 , 0.99824082, 0.99898879, 0.99922684,\n", + " 0.99907452, 0.99845525, 0.99705774, 0.99418212, 0.98839847]),\n", + " 'fval0': 39307.68087077288,\n", + " 'history': None,\n", + " 'exitflag': 0,\n", + " 'time': 0.25472187995910645,\n", + " 'message': b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'},\n", + " {'id': '18',\n", + " 'x': array([-0.99326368, 0.99660588, 0.99824062, 0.99898839, 0.99922577,\n", + " 0.99907376, 0.99845427, 0.99705613, 0.99417909, 0.98839181]),\n", + " 'fval': 3.9865791125196637,\n", + " 'grad': array([-3.02141656e-04, -2.82989363e-04, 8.74940334e-05, 1.07420996e-04,\n", + " -4.10223375e-04, 2.23413295e-04, 9.98441590e-05, -4.33465227e-05,\n", + " 9.09187114e-05, -5.07586687e-05]),\n", + " 'hess': None,\n", + " 'res': None,\n", + " 'sres': None,\n", + " 'n_fval': 78,\n", + " 'n_grad': 78,\n", + " 'n_hess': 0,\n", + " 'n_res': 0,\n", + " 'n_sres': 0,\n", + " 'x0': array([-0.99326368, 0.99660588, 0.99824062, 0.99898839, 0.99922577,\n", + " 0.99907376, 0.99845427, 0.99705613, 0.99417909, 0.98839181]),\n", + " 'fval0': 147867.31795910455,\n", + " 'history': None,\n", + " 'exitflag': 0,\n", + " 'time': 0.3003520965576172,\n", + " 'message': b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'},\n", + " {'id': '11',\n", + " 'x': array([-0.9932625 , 0.9966052 , 0.99824012, 0.99898824, 0.99922657,\n", + " 0.99907502, 0.99845714, 0.99706221, 0.99419136, 0.98841687]),\n", + " 'fval': 3.986579112935861,\n", + " 'grad': array([ 3.53600810e-04, -2.95150656e-04, -7.60865258e-05, -1.66523568e-04,\n", + " -5.29650360e-05, 1.95965090e-05, 3.50347994e-05, -2.31912259e-05,\n", + " -1.14270294e-04, 8.03849501e-05]),\n", + " 'hess': None,\n", + " 'res': None,\n", + " 'sres': None,\n", + " 'n_fval': 73,\n", + " 'n_grad': 73,\n", + " 'n_hess': 0,\n", + " 'n_res': 0,\n", + " 'n_sres': 0,\n", + " 'x0': array([-0.9932625 , 0.9966052 , 0.99824012, 0.99898824, 0.99922657,\n", + " 0.99907502, 0.99845714, 0.99706221, 0.99419136, 0.98841687]),\n", + " 'fval0': 222926.8837400755,\n", + " 'history': None,\n", + " 'exitflag': 0,\n", + " 'time': 0.290647029876709,\n", + " 'message': b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'}]" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result.optimize_result.list" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plot (reloaded) results" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot waterfalls\n", + "pypesto.visualize.waterfall(result, size=(15,6))" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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"execution_count": 12, + "metadata": {}, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'NoneType' object has no attribute 'options'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m pypesto.visualize.optimizer_history(result,\n\u001b[0;32m----> 2\u001b[0;31m legends=['L-BFGS-B'])\n\u001b[0m", + "\u001b[0;32m~/Dokumente/PhD/Code/GitHub/DCM_Software/PESTO/PESTO SCRUM/pyPESTO/pypesto/visualize/optimizer_history.py\u001b[0m in \u001b[0;36moptimizer_history\u001b[0;34m(results, ax, size, trace_x, trace_y, scale_y, offset_y, colors, y_limits, start_indices, reference, legends)\u001b[0m\n\u001b[1;32m 94\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresult\u001b[0m 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y-axis\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/Dokumente/PhD/Code/GitHub/DCM_Software/PESTO/PESTO SCRUM/pyPESTO/pypesto/visualize/optimizer_history.py\u001b[0m in \u001b[0;36mget_trace\u001b[0;34m(result, trace_x, trace_y)\u001b[0m\n\u001b[1;32m 259\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 260\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mhistory\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mhistories\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 261\u001b[0;31m \u001b[0moptions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhistory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 262\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtrace_y\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'gradnorm'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 263\u001b[0m \u001b[0;31m# retrieve gradient trace, if saved\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'options'" + ] + } + ], + "source": [ + "pypesto.visualize.optimizer_history(result,\n", + " legends=['L-BFGS-B'])" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'trace_record': True,\n", + " 'trace_record_grad': True,\n", + " 'trace_record_hess': True,\n", + " 'trace_record_res': True,\n", + " 'trace_record_sres': True,\n", + " 'trace_record_chi2': True,\n", + " 'trace_record_schi2': True,\n", + " 'trace_save_iter': 10,\n", + " 'storage_file': '/var/folders/wc/jkrt0kcn4bxf7xgp20rphv5h0000gn/T/tmp27df5y7w.hdf5'}" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "history_options" + ] + }, + { + "cell_type": "code", + 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