Issue 1079 update getting started notebooks

CHANGELOG.md

@@ -2,6 +2,7 @@
 
 ## Features
 
+-   Reformatted Getting Starte notebooks ([#1083](https://github.com/pybamm-team/PyBaMM/pull/1083))
 -   Reformatted Landesfeind electrolytes ([#1064](https://github.com/pybamm-team/PyBaMM/pull/1064))
 -   Adapted examples to be run in Google Colab ([#1061](https://github.com/pybamm-team/PyBaMM/pull/1061))
 -   Added some new solvers for algebraic models ([#1059](https://github.com/pybamm-team/PyBaMM/pull/1059))
@@ -17,7 +18,7 @@
 -   Fix `QuickPlot` to display variables discretised by FEM (in y-z) properly ([#1078](https://github.com/pybamm-team/PyBaMM/pull/1078))
 -   Add length scales to `EffectiveResistance` models ([#1071](https://github.com/pybamm-team/PyBaMM/pull/1071))
 -   Allowed for pybamm functions exp, sin, cos, sqrt to be used in expression trees that
-    are converted to casadi format ([#1067](https://github.com/pybamm-team/PyBaMM/pull/1067)
+    are converted to casadi format ([#1067](https://github.com/pybamm-team/PyBaMM/pull/1067))
 -   Fix a bug where variables that depend on y and z were transposed in `QuickPlot` ([#1055](https://github.com/pybamm-team/PyBaMM/pull/1055))
 
 ## Breaking changes

examples/notebooks/Getting Started/Tutorial 1 - How to run a model.ipynb

@@ -22,7 +22,15 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "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",
     "import pybamm"
@@ -32,7 +40,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We now load the model that we wish to run. For this notebook, we choose the single particle model with electrolyte (SPMe):"
+    "We now load the model that we wish to run. For this notebook, we choose the Doyle-Fuller-Newman (DFN) model:"
    ]
   },
   {
@@ -41,7 +49,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model = pybamm.lithium_ion.SPMe()"
+    "model = pybamm.lithium_ion.DFN()"
    ]
   },
   {
@@ -71,7 +79,18 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pybamm.solvers.solution.Solution at 0x7fa3273a5a90>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "sim.solve()"
    ]
@@ -91,12 +110,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "089df7a7f1f24690b734df6cf83bd550",
+       "model_id": "1c41a48411a94ff9a6fc19096bb4a0f5",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "interactive(children=(FloatSlider(value=0.0, description='t', max=0.9999999999999999, step=0.05), Output()), _…"
+       "interactive(children=(FloatSlider(value=0.0, description='t', max=3599.9999999999995, step=35.99999999999999),…"
       ]
      },
      "metadata": {},
@@ -113,22 +132,15 @@
    "source": [
     "In this tutorial, we have solved a model with the inbuilt default settings. However, PyBaMM is designed to be highly customisable. Over the course of the getting started tutorials, we will see how various settings can be changed so that the model is appropriate for your situation. \n",
     "\n",
-    "In [Tutorial 2](./Tutorial%202%20-%20Setting%20Parameter%20Values.ipynb) we cover setting and changing parameter values."
+    "In [Tutorial 2](./Tutorial%202%20-%20Compare%20models.ipynb) we cover how to simulate and compare different models."
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "PyBaMM development (env)",
    "language": "python",
-   "name": "python3"
+   "name": "pybamm-dev"
   },
   "language_info": {
    "codemirror_mode": {

examples/notebooks/Getting Started/Tutorial 2 - Compare models.ipynb

@@ -0,0 +1,147 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tutorial 2 - Compare models"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In [Tutorial 1](./Tutorial%201%20-%20How%20to%20run%20a%20model.ipynb), we saw how to run a PyBaMM simulation of the DFN model. However, PyBaMM includes other standard electrochemical models such as the Single Particle Model (SPM) and the Single Particle Model with electrolyte (SPMe). In this tutorial, we will see how to simulate and compare these three models. \n",
+    "\n",
+    "Again, the first step is to import the pybamm library into the notebook:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "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",
+    "import pybamm"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We start creating a list of all the models we wish to solve"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "models = [\n",
+    "    pybamm.lithium_ion.SPM(),\n",
+    "    pybamm.lithium_ion.SPMe(),\n",
+    "    pybamm.lithium_ion.DFN(),\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "and now we can loop over the list, creating and solving simulations as we go. The solved simulations are stored in the list `sims`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sims = []\n",
+    "for model in models:\n",
+    "    sim = pybamm.Simulation(model)\n",
+    "    sim.solve()\n",
+    "    sims.append(sim)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can now pass our list of simulations to the dynamic plot method, which will plot the different outputs in the same figure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "63e7fa6511714626abc1173c35aad054",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "interactive(children=(FloatSlider(value=0.0, description='t', max=3599.9999999999995, step=35.99999999999999),…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<pybamm.plotting.quick_plot.QuickPlot at 0x7f089bff9518>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pybamm.dynamic_plot(sims, time_unit=\"seconds\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this tutorial we have seen how easy it is to run and compare different electrochemical models. In [Tutorial 3](./Tutorial%203%20-%20Basic%20plotting.ipynb) we cover how to simulate and compare different models."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "PyBaMM development (env)",
+   "language": "python",
+   "name": "pybamm-dev"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}