{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"toc": true
},
"source": [
"Table of Contents
\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# restarting a notebook from a checkpoint"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Import the functions and classes you'll need from the build_2D_matrix module\n",
"\n",
"* see [vanderPlas section 13](https://jakevdp.github.io/WhirlwindTourOfPython/13-modules-and-packages.html) and\n",
" this [stack overflow entry on the dir function](https://stackoverflow.com/questions/1842414/why-is-dir-named-dir-in-python)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Boundary_Def', 'Problem_Def', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', 'avg', 'build_2D_matrix', 'index_to_row_col']\n"
]
}
],
"source": [
"import numpy as np\n",
"import build_2D_matrix\n",
"print(dir(build_2D_matrix))"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from build_2D_matrix import Boundary_Def, Problem_Def, build_2D_matrix, index_to_row_col"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Import the state from the original notebook"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['n_x', 'n_y', 'poro', 'width_x', 'width_y', 'Qsource', 'c0', 'c_init', 'Diff', 'save_date', 'case_name', 'comment', 'history', 'units']\n"
]
}
],
"source": [
"import numpy as np\n",
"in_file = 'savestate.npz'\n",
"values = np.load(in_file)\n",
"print(list(values.keys()))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Turn the npz object into a dictionary\n",
"\n",
"* This is a good time to review list, dictionary and set comprehensions:\n",
"[Vanderplas section 11](https://jakevdp.github.io/WhirlwindTourOfPython/11-list-comprehensions.html)\n",
"\n",
"* Essentially we're doing this so we can get a nicely formatted printout of the values"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'n_x': array(51),\n",
" 'n_y': array(1),\n",
" 'poro': array(0.4),\n",
" 'width_x': array(10),\n",
" 'width_y': array(0),\n",
" 'Qsource': array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]),\n",
" 'c0': array(1),\n",
" 'c_init': array([1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]),\n",
" 'Diff': array(0.01728),\n",
" 'save_date': array('March 3, 2019', dtype='