{
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    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-input",
     "remove-output",
     "active-ipynb"
    ]
   },
   "outputs": [],
   "source": [
    "try:\n",
    "    from openmdao.utils.notebook_utils import notebook_mode\n",
    "except ImportError:\n",
    "    !python -m pip install openmdao[notebooks]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adding Design Variables\n",
    "\n",
    "To add a design variable to an optimization, use the `add_design_var` method on System."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```{eval-rst}\n",
    "    .. automethod:: openmdao.core.system.System.add_design_var\n",
    "        :noindex:\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Specifying units\n",
    "\n",
    "You can specify units when adding a design variable. When this is done, the quanitity is converted from the target output’s units to the desired unit before giving it to the optimizer. When the optimizer commands a new design variable, it is assumed to be in the given units, and converted to the units of the input before setting the value in your model. If you also specify scaling, that scaling is applied after the unit conversion when being passed from the model to the optimizer, and before the unit conversion when being passed back into the model. Moreover, the upper and lower bound should be specified using these units."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": [
     "remove-output"
    ]
   },
   "outputs": [],
   "source": [
    "import openmdao.api as om\n",
    "\n",
    "prob = om.Problem()\n",
    "model = prob.model\n",
    "\n",
    "model.add_subsystem('comp1', om.ExecComp('y1 = 2.0*x',\n",
    "                                         x={'val': 2.0, 'units': 'degF'},\n",
    "                                         y1={'val': 2.0, 'units': 'degF'}),\n",
    "                    promotes=['x', 'y1'])\n",
    "\n",
    "model.add_subsystem('comp2', om.ExecComp('y2 = 3.0*x',\n",
    "                                         x={'val': 2.0, 'units': 'degF'},\n",
    "                                         y2={'val': 2.0, 'units': 'degF'}),\n",
    "                    promotes=['x', 'y2'])\n",
    "\n",
    "model.set_input_defaults('x', 35.0, units='degF')\n",
    "\n",
    "model.add_design_var('x', units='degC', lower=0.0, upper=100.0)\n",
    "model.add_constraint('y1', units='degC', lower=0.0, upper=100.0)\n",
    "model.add_objective('y2', units='degC')\n",
    "\n",
    "prob.setup()\n",
    "prob.run_driver()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "print('Model variables')\n",
    "print(prob.get_val('x', indices=[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "print(prob.get_val('comp2.y2', indices=[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "print(prob.get_val('comp1.y1', indices=[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "print('Driver variables')\n",
    "dv = prob.driver.get_design_var_values()\n",
    "print(dv['x'][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "obj = prob.driver.get_objective_values(driver_scaling=True)\n",
    "print(obj['comp2.y2'][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "con = prob.driver.get_constraint_values(driver_scaling=True)\n",
    "print(con['comp1.y1'][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "remove-input",
     "remove-output"
    ]
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from openmdao.utils.assert_utils import assert_near_equal\n",
    "\n",
    "assert_near_equal(prob.get_val('x', indices=[0]), 35.)\n",
    "assert_near_equal(prob.get_val('comp2.y2', indices=[0]), 105.)\n",
    "assert_near_equal(prob.get_val('comp1.y1', indices=[0]), 70.)\n",
    "assert_near_equal(dv['x'][0], 1.6666666666666983)\n",
    "assert_near_equal(obj['comp2.y2'][0], 40.555555555555586)\n",
    "assert_near_equal(con['comp1.y1'][0], 21.111111111111143)"
   ]
  }
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