examples/notebooks/initialize-model-with-solution.ipynb

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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Initializing a model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Example showing how to initialize a model with another model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
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     "name": "stdout",
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     "text": [
      "\u001b[33mWARNING: You are using pip version 21.0.1; however, version 21.1 is available.\n",
      "You should consider upgrading via the '/Users/vsulzer/Documents/Energy_storage/PyBaMM/.tox/dev/bin/python -m pip install --upgrade pip' command.\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install pybamm -q    # install PyBaMM if it is not installed\n",
    "\n",
    "import pybamm\n",
    "import pandas as pd\n",
    "import os\n",
    "\n",
    "os.chdir(pybamm.__path__[0]+'/..')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solve a model with a drive cycle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = pybamm.lithium_ion.DFN()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up drive cycle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import drive cycle from file\n",
    "drive_cycle = pd.read_csv(\n",
    "    \"pybamm/input/drive_cycles/US06.csv\", comment=\"#\", header=None\n",
    ").to_numpy()\n",
    "# create interpolant\n",
    "param = model.default_parameter_values\n",
    "timescale = param.evaluate(model.timescale)\n",
    "current_interpolant = pybamm.Interpolant(drive_cycle[:, 0], drive_cycle[:, 1], timescale * pybamm.t)\n",
    "# set drive cycle\n",
    "param[\"Current function [A]\"] = current_interpolant"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create and run simulation using the CasadiSolver in \"fast\" mode, remembering to pass in the updated parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sim_US06_1 = pybamm.Simulation(\n",
    "    model, parameter_values=param, solver=pybamm.CasadiSolver(mode=\"fast\")\n",
    ")\n",
    "sol_US06_1 = sim_US06_1.solve()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Update initial conditions based on a solution and solve again"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now pre-charge with CCCV, update the initial conditions, and solve again with the US06 drive cycle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "experiment = pybamm.Experiment(\n",
    "    [\"Charge at 1 A until 4.1 V\", \"Hold at 4.1 V until 50 mA\"]\n",
    ")\n",
    "sim_cccv = pybamm.Simulation(model, experiment=experiment)\n",
    "sol_cccv = sim_cccv.solve()\n",
    "\n",
    "# MODEL RE-INITIALIZATION: #############################################################\n",
    "# Now initialize the model with the solution of the charge, and then discharge with\n",
    "# the US06 drive cycle\n",
    "# We could also do this inplace by setting inplace to True, which modifies the original\n",
    "# model in place\n",
    "new_model = model.set_initial_conditions_from(sol_cccv, inplace=False)\n",
    "########################################################################################\n",
    "\n",
    "sim_US06_2 = pybamm.Simulation(\n",
    "    new_model, parameter_values=param, solver=pybamm.CasadiSolver(mode=\"fast\")\n",
    ")\n",
    "sol_US06_2 = sim_US06_2.solve()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot both solutions, we can clearly see the difference now that initial conditions have been updated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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     "data": {
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       "model_id": "7ad44c260ec446e0bd04a2f7dfbf8c65",
       "version_major": 2,
       "version_minor": 0
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       "interactive(children=(FloatSlider(value=0.0, description='t', max=600.0, step=6.0), Output()), _dom_classes=('…"
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     "output_type": "display_data"
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     "data": {
      "text/plain": [
       "<pybamm.plotting.quick_plot.QuickPlot at 0x1447078e0>"
      ]
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     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pybamm.dynamic_plot(\n",
    "    [sol_US06_1, sol_US06_2], labels=[\"Default initial conditions\", \"Fully charged\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize using a different model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also initialize the model using the solution of a different model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "spm = pybamm.lithium_ion.SPM()\n",
    "sim_spm_cccv = pybamm.Simulation(spm, experiment=experiment)\n",
    "sol_spm_cccv = sim_spm_cccv.solve()\n",
    "\n",
    "# MODEL RE-INITIALIZATION: #############################################################\n",
    "# Now initialize the model with the solution of the charge, and then discharge with\n",
    "# the US06 drive cycle\n",
    "# We could also do this inplace by setting inplace to True, which modifies the original\n",
    "# model in place\n",
    "new_dfn = model.set_initial_conditions_from(sol_spm_cccv, inplace=False)\n",
    "########################################################################################\n",
    "\n",
    "sim_US06_3 = pybamm.Simulation(\n",
    "    new_dfn, parameter_values=param, solver=pybamm.CasadiSolver(mode=\"fast\")\n",
    ")\n",
    "sol_US06_3 = sim_US06_3.solve()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now the model initialized by the DFN and the model initialized by the SPM give the same solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "aaf63750ed354d1987703fd2fdde83af",
       "version_major": 2,
       "version_minor": 0
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       "interactive(children=(FloatSlider(value=0.0, description='t', max=600.0, step=6.0), Output()), _dom_classes=('…"
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     },
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     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<pybamm.plotting.quick_plot.QuickPlot at 0x10437c370>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pybamm.dynamic_plot(\n",
    "    [sol_US06_1, sol_US06_2, sol_US06_3], \n",
    "    labels=[\"Default initial conditions\", \"Fully charged (from DFN)\", \"Fully charged (from SPM)\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "\n",
    "The relevant papers for this notebook are:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] Joel A. E. Andersson, Joris Gillis, Greg Horn, James B. Rawlings, and Moritz Diehl. CasADi – A software framework for nonlinear optimization and optimal control. Mathematical Programming Computation, 11(1):1–36, 2019. doi:10.1007/s12532-018-0139-4.\n",
      "[2] Marc Doyle, Thomas F. Fuller, and John Newman. Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell. Journal of the Electrochemical society, 140(6):1526–1533, 1993. doi:10.1149/1.2221597.\n",
      "[3] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n",
      "[4] Scott G. Marquis, Valentin Sulzer, Robert Timms, Colin P. Please, and S. Jon Chapman. An asymptotic derivation of a single particle model with electrolyte. Journal of The Electrochemical Society, 166(15):A3693–A3706, 2019. doi:10.1149/2.0341915jes.\n",
      "[5] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). ECSarXiv. February, 2020. doi:10.1149/osf.io/67ckj.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "pybamm.print_citations()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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