{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5d475da2-ff82-40d5-8809-4804ee5973a9",
   "metadata": {},
   "source": [
    "# Generic Notebook for NeuroML Models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ea359be-5028-45d5-8944-2e73df46036b",
   "metadata": {
    "tags": []
   },
   "source": [
    "## *Source path and LEMS filename*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d35178bf-2df3-42ab-be25-975d6ffa68c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c16e3aa514f84de687804ec6107782e3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HTML(value=\"<font size='+2'><i>Enter Path to NeuroML Model and LEMS filename below: </i></font>\")"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "09600b89ebcc4e0695f83137defddfde",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Text(value='../../Tutorial/Source/', description='Path:', layout=Layout(width='80%'), pl…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import ipywidgets\n",
    "import ui_widget\n",
    "from importlib.machinery import SourceFileLoader\n",
    "%matplotlib widget\n",
    "\n",
    "#widget to read input files\n",
    "display(ui_widget.header,ui_widget.loader)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4956041-c21f-40ea-ab03-3cc19ac2a498",
   "metadata": {
    "tags": []
   },
   "source": [
    "## *Parse NML files and build dashboard*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5f912104-c914-4f01-a3f4-2c9f01707b55",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skipping file : Cells.xml  <- not in source directory\n",
      "Skipping file : Networks.xml  <- not in source directory\n",
      "Skipping file : Simulation.xml  <- not in source directory\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "16839e9e06924d13a8c659c7271db7e5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Tab(children=(Accordion(children=(VBox(children=(HBox(children=(Text(value='component', disabled=True, layout=…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3df6439f5aee4ba1b1df8da601429f21",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(Button(button_style='info', description='Update Model', style=ButtonStyle(), tooltip='Update Ne…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cf3d8e6602fa407c98499114c9e8b3bd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b40e20ed899e4fb295c9fc06e4b3be57",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output(layout=Layout(border='1px solid'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d28dff9ca6e44fddb74d8006a3713219",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Button(button_style='success', description='Plot Output', style=ButtonStyle(), tooltip='Plot outputs recorded …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d7576cdda6a24b3c9b5fe5d0dd79277d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get path and filename from above widget----------------------------------------------------#\n",
    "path2source = ui_widget.loader.result[0]\n",
    "fname_LEMS  = ui_widget.loader.result[1]\n",
    "\n",
    "# imports the python module-----------------------------------------------------------------#\n",
    "nmlPython = SourceFileLoader(\"nml2jupyter_ver2.py\",\"nml2jupyter_ver2.py\").load_module()\n",
    "runner = nmlPython.nml2jupyter(path2source, fname_LEMS)\n",
    "\n",
    "runner.parseNML()\n",
    "runner.generateDashboard()\n",
    "runner.loadGUI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef9e271b-45b6-4864-be3d-e55628cb1735",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}