{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "expmkveO04pw"
      },
      "source": [
        "## A NMC/Gr parameterisation example using PyBOP\n",
        "\n",
        "This notebook introduces a synthetic re-parameterisation of the single-particle model with corrupted observations. To start, we import the PyBOP package for parameterisation and the PyBaMM package to generate the initial synethic data,"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X87NUGPW04py",
        "outputId": "0d785b07-7cff-4aeb-e60a-4ff5a669afbf"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.1/2.1 MB\u001b[0m \u001b[31m19.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m139.4/139.4 kB\u001b[0m \u001b[31m14.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m15.9/15.9 MB\u001b[0m \u001b[31m78.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.3/2.3 MB\u001b[0m \u001b[31m79.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m44.9/44.9 kB\u001b[0m \u001b[31m5.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m160.1/160.1 kB\u001b[0m \u001b[31m17.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m75.3/75.3 MB\u001b[0m \u001b[31m8.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m561.4/561.4 kB\u001b[0m \u001b[31m27.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m51.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m423.7/423.7 kB\u001b[0m \u001b[31m6.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m260.7/260.7 kB\u001b[0m \u001b[31m15.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m284.9/284.9 kB\u001b[0m \u001b[31m15.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for pybop (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "%pip install --upgrade pip ipywidgets pybamm -q\n",
        "%pip install git+https://github.com/pybop-team/PyBOP.git@develop -q"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jAvD5fk104p0"
      },
      "source": [
        "Next, we import the added packages plus any additional dependencies,"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "SQdt4brD04p1"
      },
      "outputs": [],
      "source": [
        "import pybop\n",
        "import pybamm\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5XU-dMtU04p2"
      },
      "source": [
        "## Generate Synthetic Data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MlBYO-xK04p3"
      },
      "source": [
        "We need to generate the synthetic data required for later reparameterisation. To do this we will run the PyBaMM forward model and store the generated data. This will be integrated into PyBOP in a future release for fast synthetic generation. For now, we define the PyBaMM model with a default parameter set,"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "id": "sBasxv8U04p3"
      },
      "outputs": [],
      "source": [
        "synthetic_model = pybamm.lithium_ion.SPM()\n",
        "params = synthetic_model.default_parameter_values"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wRDiC_dj04p5"
      },
      "source": [
        "We can now modify individual parameters with the bespoke values and run the simulation."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "id": "JgN4C76x04p6"
      },
      "outputs": [],
      "source": [
        "params.update(\n",
        "    {\n",
        "        \"Negative electrode active material volume fraction\": 0.52,\n",
        "        \"Positive electrode active material volume fraction\": 0.63,\n",
        "    }\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KWA5Fmbv04p7"
      },
      "source": [
        "Define the experiment and run the forward model to capture the synthetic data."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "id": "LvQ7eXGf04p7"
      },
      "outputs": [],
      "source": [
        "experiment = pybamm.Experiment(\n",
        "    [\n",
        "        (\n",
        "            \"Discharge at 1C for 15 minutes (1 second period)\",\n",
        "            \"Rest for 2 minutes (1 second period)\",\n",
        "            \"Charge at 1C for 15 minutes (1 second period)\",\n",
        "            \"Rest for 2 minutes (1 second period)\",\n",
        "        ),\n",
        "    ]\n",
        "    * 2\n",
        ")\n",
        "sim = pybamm.Simulation(synthetic_model, experiment=experiment, parameter_values=params)\n",
        "synthetic_sol = sim.solve()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u6QbgzJD04p-"
      },
      "source": [
        "Plot the synthetic data,"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 602,
          "referenced_widgets": [
            "8d003c14da5f4fa68284b28c15cee6e6",
            "aef2fa7adcc14ad0854b73d5910ae3b4",
            "7d46516469314b88be3500e2afcafcf6",
            "423bffea3a1c42b49a9ad71218e5811b",
            "06f2374f91c8455bb63252092512f2ed",
            "56ff19291e464d63b23e63b8e2ac9ea3",
            "646a8670cb204a31bb56bc2380898093"
          ]
        },
        "id": "_F-7UPUl04p-",
        "outputId": "cf548842-64ae-4389-b16d-d3cf3239ce8f"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "8d003c14da5f4fa68284b28c15cee6e6",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "interactive(children=(FloatSlider(value=0.0, description='t', max=1.1333333333333333, step=0.01133333333333333…"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<pybamm.plotting.quick_plot.QuickPlot at 0x7d7b2d770eb0>"
            ]
          },
          "execution_count": 25,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 1500x700 with 8 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "sim.plot()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kPlPy2oo04p-"
      },
      "source": [
        "Now, let's corrupt the synthetic data with 1mV of gaussian noise centered around zero,"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "id": "IW9PFOV904p-"
      },
      "outputs": [],
      "source": [
        "corrupt_V = synthetic_sol[\"Terminal voltage [V]\"].data\n",
        "corrupt_V += np.random.normal(0, 0.001, len(corrupt_V))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X8-tubYY04p_"
      },
      "source": [
        "## Identify the Parameters"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PQqhvSZN04p_"
      },
      "source": [
        "Now, to blind fit the synthetic parameters we need to define the observation variables as well as update the forward model to be of PyBOP type (This composes PyBaMM's model class). For the observed voltage variable, we used the newly corrupted voltage array,"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 64,
      "metadata": {
        "id": "zuvGHWID04p_"
      },
      "outputs": [],
      "source": [
        "pyb_model = pybop.lithium_ion.SPM()\n",
        "dataset = pybop.Dataset(\n",
        "    {\n",
        "        \"Time [s]\": synthetic_sol[\"Time [s]\"].data,\n",
        "        \"Current function [A]\": synthetic_sol[\"Current [A]\"].data,\n",
        "        \"Terminal voltage [V]\": corrupt_V,\n",
        "    }\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ffS3CF_704qA"
      },
      "source": [
        "Next, we define the targeted forward model parameters for estimation. Furthermore, PyBOP provides functionality to define a prior for the parameters. The initial parameters values used in the estimiation will be randomly drawn from the prior distribution."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 65,
      "metadata": {
        "id": "WPCybXIJ04qA"
      },
      "outputs": [],
      "source": [
        "parameters = [\n",
        "    pybop.Parameter(\n",
        "        \"Negative electrode active material volume fraction\",\n",
        "        prior=pybop.Gaussian(0.5, 0.02),\n",
        "        bounds=[0.48, 0.625],\n",
        "    ),\n",
        "    pybop.Parameter(\n",
        "        \"Positive electrode active material volume fraction\",\n",
        "        prior=pybop.Gaussian(0.65, 0.02),\n",
        "        bounds=[0.525, 0.75],\n",
        "    ),\n",
        "]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n4OHa-aF04qA"
      },
      "source": [
        "We can now define the fitting signal, a problem (which combines the model with the dataset) and construct a cost function."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 66,
      "metadata": {
        "id": "etMzRtx404qA"
      },
      "outputs": [],
      "source": [
        "# Define the cost to optimise\n",
        "signal = \"Terminal voltage [V]\"\n",
        "problem = pybop.FittingProblem(pyb_model, parameters, dataset, signal=signal)\n",
        "cost = pybop.RootMeanSquaredError(problem)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eQiGurUV04qB"
      },
      "source": [
        "Let's construct PyBOP's optimisation class. This class provides the methods needed to fit the forward model. For this example, we use a root-mean square cost function with the BOBYQA algorithm implemented in NLOpt."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 67,
      "metadata": {
        "id": "N3FtAhrT04qB"
      },
      "outputs": [],
      "source": [
        "parameterisation = pybop.Optimisation(\n",
        "    cost=cost,\n",
        "    optimiser=pybop.NLoptOptimize,\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "caprp-bV04qB"
      },
      "source": [
        "Finally, we run the estimation algorithm."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 68,
      "metadata": {
        "id": "-9OVt0EQ04qB"
      },
      "outputs": [],
      "source": [
        "x, final_cost = parameterisation.run()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-4pZsDmS04qC"
      },
      "source": [
        "Let's view the identified parameters:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 69,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hgz8SV4i04qC",
        "outputId": "e1e42ae7-5075-4c47-dd68-1b22ecc170f6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([0.48367449, 0.63380314])"
            ]
          },
          "execution_count": 69,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "x"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KxKURtH704qC"
      },
      "source": [
        "## Plotting"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-cWCOiqR04qC"
      },
      "source": [
        "First, run the SPM forward model with the estimated parameters,"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 70,
      "metadata": {
        "id": "ZVfozY0A04qC"
      },
      "outputs": [],
      "source": [
        "params.update(\n",
        "    {\n",
        "        \"Negative electrode active material volume fraction\": x[0],\n",
        "        \"Positive electrode active material volume fraction\": x[1],\n",
        "    }\n",
        ")\n",
        "optsol = sim.solve()[\"Terminal voltage [V]\"].data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ntIvAJmA04qD"
      },
      "source": [
        "Now, we plot the estimated forward model against the corrupted synthetic observation,"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 71,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        },
        "id": "tJUJ80Ve04qD",
        "outputId": "855fbaa2-1e09-4935-eb1a-8caf7f99eb75"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7d7b24dc6d40>"
            ]
          },
          "execution_count": 71,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.plot(corrupt_V, label=\"Groundtruth\")\n",
        "plt.plot(optsol, label=\"Estimated\")\n",
        "plt.xlabel(\"Time (s)\")\n",
        "plt.ylabel(\"Voltage (V)\")\n",
        "plt.legend()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 71,
      "metadata": {
        "id": "N5XYkevi04qD"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "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": "3.10.12"
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "06f2374f91c8455bb63252092512f2ed": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "2.0.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "2.0.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "2.0.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border_bottom": null,
            "border_left": null,
            "border_right": null,
            "border_top": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "423bffea3a1c42b49a9ad71218e5811b": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "2.0.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "2.0.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "2.0.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border_bottom": null,
            "border_left": null,
            "border_right": null,
            "border_top": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "56ff19291e464d63b23e63b8e2ac9ea3": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "2.0.0",
          "model_name": "SliderStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "2.0.0",
            "_model_name": "SliderStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "2.0.0",
            "_view_name": "StyleView",
            "description_width": "",
            "handle_color": null
          }
        },
        "646a8670cb204a31bb56bc2380898093": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "2.0.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "2.0.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "2.0.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border_bottom": null,
            "border_left": null,
            "border_right": null,
            "border_top": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "7d46516469314b88be3500e2afcafcf6": {
          "model_module": "@jupyter-widgets/output",
          "model_module_version": "1.0.0",
          "model_name": "OutputModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/output",
            "_model_module_version": "1.0.0",
            "_model_name": "OutputModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/output",
            "_view_module_version": "1.0.0",
            "_view_name": "OutputView",
            "layout": "IPY_MODEL_646a8670cb204a31bb56bc2380898093",
            "msg_id": "",
            "outputs": [],
            "tabbable": null,
            "tooltip": null
          }
        },
        "8d003c14da5f4fa68284b28c15cee6e6": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "2.0.0",
          "model_name": "VBoxModel",
          "state": {
            "_dom_classes": [
              "widget-interact"
            ],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "2.0.0",
            "_model_name": "VBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "2.0.0",
            "_view_name": "VBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_aef2fa7adcc14ad0854b73d5910ae3b4",
              "IPY_MODEL_7d46516469314b88be3500e2afcafcf6"
            ],
            "layout": "IPY_MODEL_423bffea3a1c42b49a9ad71218e5811b",
            "tabbable": null,
            "tooltip": null
          }
        },
        "aef2fa7adcc14ad0854b73d5910ae3b4": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "2.0.0",
          "model_name": "FloatSliderModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "2.0.0",
            "_model_name": "FloatSliderModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "2.0.0",
            "_view_name": "FloatSliderView",
            "behavior": "drag-tap",
            "continuous_update": true,
            "description": "t",
            "description_allow_html": false,
            "disabled": false,
            "layout": "IPY_MODEL_06f2374f91c8455bb63252092512f2ed",
            "max": 1.1333333333333333,
            "min": 0,
            "orientation": "horizontal",
            "readout": true,
            "readout_format": ".2f",
            "step": 0.011333333333333332,
            "style": "IPY_MODEL_56ff19291e464d63b23e63b8e2ac9ea3",
            "tabbable": null,
            "tooltip": null,
            "value": 0
          }
        }
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}