{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "bc559df2", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:26.007227Z", "iopub.status.busy": "2026-10-02T14:46:26.006969Z", "iopub.status.idle": "2026-10-02T14:46:26.014062Z", "shell.execute_reply": "2026-10-02T14:46:26.013316Z" }, "papermill": { "duration": 0.012963, "end_time": "2026-10-02T14:46:26.014723+00:00", "exception": false, "start_time": "2026-10-02T14:46:26.001760+00:00", "status": "completed" }, "tags": [ "remove-input", "remove-output", "active-ipynb" ] }, "outputs": [], "source": [ "try:\n", " from openmdao.utils.notebook_utils import notebook_mode # noqa: F401\n", "except ImportError:\n", " !python -m pip install openmdao[notebooks]" ] }, { "cell_type": "code", "execution_count": 2, "id": "0907ee01", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:26.019165Z", "iopub.status.busy": "2026-10-02T14:46:26.018996Z", "iopub.status.idle": "2026-10-02T14:46:26.877379Z", "shell.execute_reply": "2026-10-02T14:46:26.876812Z" }, "papermill": { "duration": 0.863541, "end_time": "2026-10-02T14:46:26.880213+00:00", "exception": false, "start_time": "2026-10-02T14:46:26.016672+00:00", "status": "completed" }, "tags": [ "remove-input", "remove-output" ] }, "outputs": [], "source": [ "from openmdao.utils.assert_utils import assert_near_equal\n", "\n" ] }, { "cell_type": "markdown", "id": "ecca6536", "metadata": { "papermill": { "duration": 0.002131, "end_time": "2026-10-02T14:46:26.883975+00:00", "exception": false, "start_time": "2026-10-02T14:46:26.881844+00:00", "status": "completed" }, "tags": [] }, "source": [ "# Problem Recording\n", "\n", "You might also want to attach a recorder to the `Problem` itself. This allows you to record an arbitrary case at a point of your choosing. This feature can be useful if you only record a limited number of variables during the run but would like to see a more complete list of values after the run.\n", "\n", "The options are a subset of those for driver recording." ] }, { "cell_type": "code", "execution_count": 3, "id": "c16224f0", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:26.896454Z", "iopub.status.busy": "2026-10-02T14:46:26.896124Z", "iopub.status.idle": "2026-10-02T14:46:28.927046Z", "shell.execute_reply": "2026-10-02T14:46:28.926349Z" }, "papermill": { "duration": 2.042324, "end_time": "2026-10-02T14:46:28.927865+00:00", "exception": false, "start_time": "2026-10-02T14:46:26.885541+00:00", "status": "completed" }, "scrolled": true, "tags": [ "remove-input" ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[1790952388.914965] [runnervm8df0l:10552:0] ib_iface.c:1269 UCX ERROR mana_0: iface 0x5618132dad30 failed to create UD QP TX wr:256 sge:6 inl:64 resp:0 RX wr:4096 sge:1 resp:0 failed: Operation not supported\n", "[1790952388.915212] [runnervm8df0l:10552:0] ucp_worker.c:1412 UCX ERROR uct_iface_open(ud_verbs/mana_0:1) failed: Input/output error\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "[runnervm8df0l:10552] pml_ucx.c:313 Error: Failed to create UCP worker\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", " \n", "\n", "\n", "

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
OptionDefaultAcceptable ValuesAcceptable TypesDescription
excludes[]N/A['list']Patterns for vars to exclude in recording (processed post-includes). Uses fnmatch wildcards
includes['*']N/A['list']Patterns for variables to include in recording. Uses fnmatch wildcards
record_abs_errorTrue[True, False]['bool']Set to True to record absolute error of model nonlinear solver
record_constraintsTrue[True, False]['bool']Set to True to record constraints at the problem level
record_derivativesFalse[True, False]['bool']Set to True to record derivatives for the problem level
record_desvarsTrue[True, False]['bool']Set to True to record design variables at the problem level
record_inputsFalse[True, False]['bool']Set True to record inputs at the problem level.
record_objectivesTrue[True, False]['bool']Set to True to record objectives at the problem level
record_outputsTrue[True, False]['bool']Set True to record outputs at the problem level.
record_rel_errorTrue[True, False]['bool']Set to True to record relative error of model nonlinear solver
record_residualsFalse[True, False]['bool']Set True to record residuals at the problem level.
record_responsesFalse[True, False]['bool']Set True to record constraints and objectives at the problem level.
\n", "\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import openmdao.api as om\n", "om.show_options_table(\"openmdao.core.problem.Problem\", options_dict=\"recording_options\")" ] }, { "cell_type": "markdown", "id": "ace496d9", "metadata": { "papermill": { "duration": 0.040456, "end_time": "2026-10-02T14:46:28.970212+00:00", "exception": false, "start_time": "2026-10-02T14:46:28.929756+00:00", "status": "completed" }, "tags": [] }, "source": [ "```{note}\n", "Note that the `excludes` option takes precedence over the `includes` option.\n", "```" ] }, { "cell_type": "markdown", "id": "0c4cbfcd", "metadata": { "papermill": { "duration": 0.001949, "end_time": "2026-10-02T14:46:29.042499+00:00", "exception": false, "start_time": "2026-10-02T14:46:29.040550+00:00", "status": "completed" }, "tags": [] }, "source": [ "## Problem Recording Example" ] }, { "cell_type": "code", "execution_count": 4, "id": "3ee6d354", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:29.048271Z", "iopub.status.busy": "2026-10-02T14:46:29.047800Z", "iopub.status.idle": "2026-10-02T14:46:30.210110Z", "shell.execute_reply": "2026-10-02T14:46:30.209415Z" }, "papermill": { "duration": 1.166302, "end_time": "2026-10-02T14:46:30.210966+00:00", "exception": false, "start_time": "2026-10-02T14:46:29.044664+00:00", "status": "completed" }, "tags": [ "remove-input", "remove-output" ] }, "outputs": [ { "data": { "application/papermill.record/text/html": "
class SellarDerivatives(om.Group):\n    """\n    Group containing the Sellar MDA. This version uses the disciplines with derivatives.\n    """\n\n    def setup(self):\n        self.add_subsystem('d1', SellarDis1withDerivatives(), promotes=['x', 'z', 'y1', 'y2'])\n        self.add_subsystem('d2', SellarDis2withDerivatives(), promotes=['z', 'y1', 'y2'])\n\n        self.add_subsystem('obj_cmp', om.ExecComp('obj = x**2 + z[1] + y1 + exp(-y2)', obj=0.0,\n                                                  x=0.0, z=np.array([0.0, 0.0]), y1=0.0, y2=0.0),\n                           promotes=['obj', 'x', 'z', 'y1', 'y2'])\n\n        self.add_subsystem('con_cmp1', om.ExecComp('con1 = 3.16 - y1', con1=0.0, y1=0.0),\n                           promotes=['con1', 'y1'])\n        self.add_subsystem('con_cmp2', om.ExecComp('con2 = y2 - 24.0', con2=0.0, y2=0.0),\n                           promotes=['con2', 'y2'])\n\n        self.set_input_defaults('x', 1.0)\n        self.set_input_defaults('z', np.array([5.0, 2.0]))\n
\n", "application/papermill.record/text/latex": "\\begin{Verbatim}[commandchars=\\\\\\{\\}]\n\\PY{k}{class}\\PY{+w}{ }\\PY{n+nc}{SellarDerivatives}\\PY{p}{(}\\PY{n}{om}\\PY{o}{.}\\PY{n}{Group}\\PY{p}{)}\\PY{p}{:}\n\\PY{+w}{ }\\PY{l+s+sd}{\\PYZdq{}\\PYZdq{}\\PYZdq{}}\n\\PY{l+s+sd}{ Group containing the Sellar MDA. This version uses the disciplines with derivatives.}\n\\PY{l+s+sd}{ \\PYZdq{}\\PYZdq{}\\PYZdq{}}\n\n \\PY{k}{def}\\PY{+w}{ }\\PY{n+nf}{setup}\\PY{p}{(}\\PY{n+nb+bp}{self}\\PY{p}{)}\\PY{p}{:}\n \\PY{n+nb+bp}{self}\\PY{o}{.}\\PY{n}{add\\PYZus{}subsystem}\\PY{p}{(}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{d1}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{n}{SellarDis1withDerivatives}\\PY{p}{(}\\PY{p}{)}\\PY{p}{,} \\PY{n}{promotes}\\PY{o}{=}\\PY{p}{[}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{x}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{z}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{y1}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{y2}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{]}\\PY{p}{)}\n \\PY{n+nb+bp}{self}\\PY{o}{.}\\PY{n}{add\\PYZus{}subsystem}\\PY{p}{(}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{d2}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{n}{SellarDis2withDerivatives}\\PY{p}{(}\\PY{p}{)}\\PY{p}{,} \\PY{n}{promotes}\\PY{o}{=}\\PY{p}{[}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{z}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{y1}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{y2}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{]}\\PY{p}{)}\n\n \\PY{n+nb+bp}{self}\\PY{o}{.}\\PY{n}{add\\PYZus{}subsystem}\\PY{p}{(}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{obj\\PYZus{}cmp}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{n}{om}\\PY{o}{.}\\PY{n}{ExecComp}\\PY{p}{(}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{obj = x**2 + z[1] + y1 + exp(\\PYZhy{}y2)}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{n}{obj}\\PY{o}{=}\\PY{l+m+mf}{0.0}\\PY{p}{,}\n \\PY{n}{x}\\PY{o}{=}\\PY{l+m+mf}{0.0}\\PY{p}{,} \\PY{n}{z}\\PY{o}{=}\\PY{n}{np}\\PY{o}{.}\\PY{n}{array}\\PY{p}{(}\\PY{p}{[}\\PY{l+m+mf}{0.0}\\PY{p}{,} \\PY{l+m+mf}{0.0}\\PY{p}{]}\\PY{p}{)}\\PY{p}{,} \\PY{n}{y1}\\PY{o}{=}\\PY{l+m+mf}{0.0}\\PY{p}{,} \\PY{n}{y2}\\PY{o}{=}\\PY{l+m+mf}{0.0}\\PY{p}{)}\\PY{p}{,}\n \\PY{n}{promotes}\\PY{o}{=}\\PY{p}{[}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{obj}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{x}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{z}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{y1}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{y2}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{]}\\PY{p}{)}\n\n \\PY{n+nb+bp}{self}\\PY{o}{.}\\PY{n}{add\\PYZus{}subsystem}\\PY{p}{(}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{con\\PYZus{}cmp1}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{n}{om}\\PY{o}{.}\\PY{n}{ExecComp}\\PY{p}{(}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{con1 = 3.16 \\PYZhy{} y1}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{n}{con1}\\PY{o}{=}\\PY{l+m+mf}{0.0}\\PY{p}{,} \\PY{n}{y1}\\PY{o}{=}\\PY{l+m+mf}{0.0}\\PY{p}{)}\\PY{p}{,}\n \\PY{n}{promotes}\\PY{o}{=}\\PY{p}{[}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{con1}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{y1}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{]}\\PY{p}{)}\n \\PY{n+nb+bp}{self}\\PY{o}{.}\\PY{n}{add\\PYZus{}subsystem}\\PY{p}{(}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{con\\PYZus{}cmp2}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{n}{om}\\PY{o}{.}\\PY{n}{ExecComp}\\PY{p}{(}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{con2 = y2 \\PYZhy{} 24.0}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{n}{con2}\\PY{o}{=}\\PY{l+m+mf}{0.0}\\PY{p}{,} \\PY{n}{y2}\\PY{o}{=}\\PY{l+m+mf}{0.0}\\PY{p}{)}\\PY{p}{,}\n \\PY{n}{promotes}\\PY{o}{=}\\PY{p}{[}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{con2}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{y2}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{]}\\PY{p}{)}\n\n \\PY{n+nb+bp}{self}\\PY{o}{.}\\PY{n}{set\\PYZus{}input\\PYZus{}defaults}\\PY{p}{(}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{x}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{l+m+mf}{1.0}\\PY{p}{)}\n \\PY{n+nb+bp}{self}\\PY{o}{.}\\PY{n}{set\\PYZus{}input\\PYZus{}defaults}\\PY{p}{(}\\PY{l+s+s1}{\\PYZsq{}}\\PY{l+s+s1}{z}\\PY{l+s+s1}{\\PYZsq{}}\\PY{p}{,} \\PY{n}{np}\\PY{o}{.}\\PY{n}{array}\\PY{p}{(}\\PY{p}{[}\\PY{l+m+mf}{5.0}\\PY{p}{,} \\PY{l+m+mf}{2.0}\\PY{p}{]}\\PY{p}{)}\\PY{p}{)}\n\\end{Verbatim}\n", "application/papermill.record/text/plain": "class SellarDerivatives(om.Group):\n \"\"\"\n Group containing the Sellar MDA. This version uses the disciplines with derivatives.\n \"\"\"\n\n def setup(self):\n self.add_subsystem('d1', SellarDis1withDerivatives(), promotes=['x', 'z', 'y1', 'y2'])\n self.add_subsystem('d2', SellarDis2withDerivatives(), promotes=['z', 'y1', 'y2'])\n\n self.add_subsystem('obj_cmp', om.ExecComp('obj = x**2 + z[1] + y1 + exp(-y2)', obj=0.0,\n x=0.0, z=np.array([0.0, 0.0]), y1=0.0, y2=0.0),\n promotes=['obj', 'x', 'z', 'y1', 'y2'])\n\n self.add_subsystem('con_cmp1', om.ExecComp('con1 = 3.16 - y1', con1=0.0, y1=0.0),\n promotes=['con1', 'y1'])\n self.add_subsystem('con_cmp2', om.ExecComp('con2 = y2 - 24.0', con2=0.0, y2=0.0),\n promotes=['con2', 'y2'])\n\n self.set_input_defaults('x', 1.0)\n self.set_input_defaults('z', np.array([5.0, 2.0]))" }, "metadata": { "scrapbook": { "mime_prefix": "application/papermill.record/", "name": "code_src90" } }, "output_type": "display_data" } ], "source": [ "from openmdao.utils.notebook_utils import get_code\n", "from myst_nb import glue\n", "glue(\"code_src90\", get_code(\"openmdao.test_suite.components.sellar_feature.SellarDerivatives\"), display=False)" ] }, { "cell_type": "markdown", "id": "853e3fd4", "metadata": { "papermill": { "duration": 0.001805, "end_time": "2026-10-02T14:46:30.215034+00:00", "exception": false, "start_time": "2026-10-02T14:46:30.213229+00:00", "status": "completed" }, "tags": [] }, "source": [ ":::{dropdown} `SellarDerivatives` class definition \n", "\n", "{glue:}`code_src90`\n", ":::" ] }, { "cell_type": "code", "execution_count": 5, "id": "427bc212", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:30.219457Z", "iopub.status.busy": "2026-10-02T14:46:30.219234Z", "iopub.status.idle": "2026-10-02T14:46:30.691154Z", "shell.execute_reply": "2026-10-02T14:46:30.690588Z" }, "papermill": { "duration": 0.474983, "end_time": "2026-10-02T14:46:30.691784+00:00", "exception": false, "start_time": "2026-10-02T14:46:30.216801+00:00", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "NL: NLBGS Converged in 8 iterations\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "NL: NLBGS Converged in 1 iterations\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "NL: NLBGS Converged in 9 iterations\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "NL: NLBGS Converged in 10 iterations\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "NL: NLBGS Converged in 10 iterations\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "NL: NLBGS Converged in 9 iterations\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "NL: NLBGS Converged in 6 iterations\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Optimization terminated successfully (Exit mode 0)\n", " Current function value: 3.183393951730529\n", " Iterations: 6\n", " Function evaluations: 6\n", " Gradient evaluations: 6\n", "Optimization Complete\n", "-----------------------------------\n" ] }, { "data": { "text/plain": [ "Problem: problem_recording\n", "Driver: ScipyOptimizeDriver\n", " success : True\n", " iterations : 7\n", " runtime : 5.4111E-02 s\n", " model_evals : 7\n", " model_time : 5.7645E-03 s\n", " deriv_evals : 6\n", " deriv_time : 4.2671E-02 s\n", " exit_status : SUCCESS" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import openmdao.api as om\n", "from openmdao.test_suite.components.sellar_feature import SellarDerivatives\n", "\n", "import numpy as np\n", "\n", "model = SellarDerivatives()\n", "\n", "model.nonlinear_solver = om.NonlinearBlockGS()\n", "model.linear_solver = om.ScipyKrylov()\n", "\n", "\n", "model.add_design_var('z', lower=np.array([-10.0, 0.0]),\n", " upper=np.array([10.0, 10.0]))\n", "model.add_design_var('x', lower=0.0, upper=10.0)\n", "model.add_objective('obj')\n", "model.add_constraint('con1', upper=0.0)\n", "model.add_constraint('con2', upper=0.0)\n", "\n", "driver = om.ScipyOptimizeDriver(optimizer='SLSQP', tol=1e-9)\n", "\n", "prob = om.Problem(name='problem_recording', model=model, driver=driver)\n", "\n", "prob.add_recorder(om.SqliteRecorder(\"problem_recording.sql\"))\n", "\n", "prob.recording_options['includes'] = []\n", "prob.recording_options['record_objectives'] = True\n", "prob.recording_options['record_constraints'] = True\n", "prob.recording_options['record_desvars'] = True\n", "\n", "prob.setup()\n", "prob.run_driver()" ] }, { "cell_type": "code", "execution_count": 6, "id": "542f463e", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:30.707956Z", "iopub.status.busy": "2026-10-02T14:46:30.707507Z", "iopub.status.idle": "2026-10-02T14:46:30.876209Z", "shell.execute_reply": "2026-10-02T14:46:30.875338Z" }, "papermill": { "duration": 0.182631, "end_time": "2026-10-02T14:46:30.876728+00:00", "exception": false, "start_time": "2026-10-02T14:46:30.694097+00:00", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", " \n", "\n", "\n", "

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\n", "\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "prob.record('final')\n", "prob.cleanup()\n", "\n", "cr = om.CaseReader(prob.get_outputs_dir() / \"problem_recording.sql\")\n", "\n", "# get list of cases recorded on problem\n", "problem_cases = cr.list_cases('problem')" ] }, { "cell_type": "code", "execution_count": 7, "id": "41ccd2c9", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:30.881187Z", "iopub.status.busy": "2026-10-02T14:46:30.880966Z", "iopub.status.idle": "2026-10-02T14:46:30.883685Z", "shell.execute_reply": "2026-10-02T14:46:30.882994Z" }, "papermill": { "duration": 0.00556, "end_time": "2026-10-02T14:46:30.884178+00:00", "exception": false, "start_time": "2026-10-02T14:46:30.878618+00:00", "status": "completed" }, "tags": [ "remove-input", "remove-output" ] }, "outputs": [], "source": [ "assert problem_cases == ['final']" ] }, { "cell_type": "code", "execution_count": 8, "id": "39d07a9c", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:30.917892Z", "iopub.status.busy": "2026-10-02T14:46:30.917750Z", "iopub.status.idle": "2026-10-02T14:46:30.922703Z", "shell.execute_reply": "2026-10-02T14:46:30.921977Z" }, "papermill": { "duration": 0.007997, "end_time": "2026-10-02T14:46:30.923147+00:00", "exception": false, "start_time": "2026-10-02T14:46:30.915150+00:00", "status": "completed" }, "scrolled": true, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", " \n", "\n", "\n", "

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con2
obj
\n", "\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "{'inputs': [], 'outputs': ['x', 'z', 'con1', 'con2', 'obj'], 'residuals': []}" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# get list of output variables recorded on problem\n", "cr.list_source_vars('problem')" ] }, { "cell_type": "code", "execution_count": 9, "id": "06261b04", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:30.927223Z", "iopub.status.busy": "2026-10-02T14:46:30.927083Z", "iopub.status.idle": "2026-10-02T14:46:30.930193Z", "shell.execute_reply": "2026-10-02T14:46:30.929619Z" }, "papermill": { "duration": 0.005867, "end_time": "2026-10-02T14:46:30.930675+00:00", "exception": false, "start_time": "2026-10-02T14:46:30.924808+00:00", "status": "completed" }, "tags": [ "remove-input", "remove-output" ] }, "outputs": [], "source": [ "problem_vars = cr.list_source_vars('problem', out_stream=None)\n", "assert sorted(problem_vars['outputs']) == ['con1', 'con2', 'obj', 'x', 'z']" ] }, { "cell_type": "code", "execution_count": 10, "id": "782af4f8", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:30.953097Z", "iopub.status.busy": "2026-10-02T14:46:30.952968Z", "iopub.status.idle": "2026-10-02T14:46:30.955583Z", "shell.execute_reply": "2026-10-02T14:46:30.954970Z" }, "papermill": { "duration": 0.023675, "end_time": "2026-10-02T14:46:30.956326+00:00", "exception": false, "start_time": "2026-10-02T14:46:30.932651+00:00", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# get the recorded case\n", "case = cr.get_case('final')" ] }, { "cell_type": "code", "execution_count": 11, "id": "7063cdf4", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:30.985328Z", "iopub.status.busy": "2026-10-02T14:46:30.985209Z", "iopub.status.idle": "2026-10-02T14:46:30.988777Z", "shell.execute_reply": "2026-10-02T14:46:30.987985Z" }, "papermill": { "duration": 0.030775, "end_time": "2026-10-02T14:46:30.989224+00:00", "exception": false, "start_time": "2026-10-02T14:46:30.958449+00:00", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "{'obj': array([3.18339395])}" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "case.get_objectives()" ] }, { "cell_type": "code", "execution_count": 12, "id": "40304d37", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:31.029746Z", "iopub.status.busy": "2026-10-02T14:46:31.029599Z", "iopub.status.idle": "2026-10-02T14:46:31.032870Z", "shell.execute_reply": "2026-10-02T14:46:31.032231Z" }, "papermill": { "duration": 0.006663, "end_time": "2026-10-02T14:46:31.033342+00:00", "exception": false, "start_time": "2026-10-02T14:46:31.026679+00:00", "status": "completed" }, "tags": [ "remove-input", "remove-output" ] }, "outputs": [ { "data": { "text/plain": [ "np.float64(5.436113407797904e-10)" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "assert_near_equal(case.get_objectives()['obj'], 3.18339395, 1e-8)" ] }, { "cell_type": "code", "execution_count": 13, "id": "4cf1c8c3", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:31.037337Z", "iopub.status.busy": "2026-10-02T14:46:31.037206Z", "iopub.status.idle": "2026-10-02T14:46:31.040333Z", "shell.execute_reply": "2026-10-02T14:46:31.039772Z" }, "papermill": { "duration": 0.00596, "end_time": "2026-10-02T14:46:31.041010+00:00", "exception": false, "start_time": "2026-10-02T14:46:31.035050+00:00", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "{'z': array([1.97763888, 0. ]), 'x': array([5.63626006e-15])}" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "case.get_design_vars()" ] }, { "cell_type": "code", "execution_count": 14, "id": "ef6dba7f", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:31.045061Z", "iopub.status.busy": "2026-10-02T14:46:31.044939Z", "iopub.status.idle": "2026-10-02T14:46:31.048123Z", "shell.execute_reply": "2026-10-02T14:46:31.047459Z" }, "papermill": { "duration": 0.00592, "end_time": "2026-10-02T14:46:31.048579+00:00", "exception": false, "start_time": "2026-10-02T14:46:31.042659+00:00", "status": "completed" }, "tags": [ "remove-input", "remove-output" ] }, "outputs": [ { "data": { "text/plain": [ "np.float64(5.636260060859323e-15)" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "des_vars = case.get_design_vars()\n", "assert_near_equal(des_vars['z'], [1.97763888, 5.87897722e-15], 1e-8)\n", "assert_near_equal(des_vars['x'], 0., 1e-8)" ] }, { "cell_type": "code", "execution_count": 15, "id": "90f4387a", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:31.077891Z", "iopub.status.busy": "2026-10-02T14:46:31.077713Z", "iopub.status.idle": "2026-10-02T14:46:31.081612Z", "shell.execute_reply": "2026-10-02T14:46:31.080914Z" }, "papermill": { "duration": 0.031899, "end_time": "2026-10-02T14:46:31.082157+00:00", "exception": false, "start_time": "2026-10-02T14:46:31.050258+00:00", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "{'con1': array([-9.11004605e-11]), 'con2': array([-20.24472223])}" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "case.get_constraints()" ] }, { "cell_type": "code", "execution_count": 16, "id": "c7ada097", "metadata": { "execution": { "iopub.execute_input": "2026-10-02T14:46:31.096245Z", "iopub.status.busy": "2026-10-02T14:46:31.096077Z", "iopub.status.idle": "2026-10-02T14:46:31.099437Z", "shell.execute_reply": "2026-10-02T14:46:31.098719Z" }, "papermill": { "duration": 0.015475, "end_time": "2026-10-02T14:46:31.099946+00:00", "exception": false, "start_time": "2026-10-02T14:46:31.084471+00:00", "status": "completed" }, "tags": [ "remove-input", "remove-output" ] }, "outputs": [ { "data": { "text/plain": [ "np.float64(1.4932798340865912e-10)" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "constraints = case.get_constraints()\n", "assert_near_equal(constraints['con1'], 0, 1e-8)\n", "assert_near_equal(constraints['con2'], -20.24472223, 1e-8)" ] } ], "metadata": { "celltoolbar": "Tags", "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.13.14" }, "orphan": true, "papermill": { "default_parameters": {}, "duration": 6.732334, "end_time": "2026-10-02T14:46:31.891424+00:00", "environment_variables": {}, "exception": null, "input_path": "/home/runner/work/OpenMDAO/OpenMDAO/openmdao/docs/openmdao_book/features/recording/problem_recording.ipynb", "output_path": "/home/runner/work/OpenMDAO/OpenMDAO/openmdao/docs/_executed_book/features/recording/problem_recording.ipynb", "parameters": {}, "start_time": "2026-10-02T14:46:25.159090+00:00", "version": "2.7.0" } }, "nbformat": 4, "nbformat_minor": 5 }