{
"cells": [
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [
],
"source": [
"# Configure Jupyter so figures appear in the notebook\n",
"%matplotlib inline\n",
"\n",
"# Configure Jupyter to display the assigned value after an assignment\n",
"%config InteractiveShell.ast_node_interactivity='last_expr_or_assign'\n",
"\n",
"# import functions from the modsim library\n",
"from modsim import *\n",
"\n",
"from pandas import read_html"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"0.4"
]
},
"execution_count": 25,
"metadata": {
},
"output_type": "execute_result"
}
],
"source": [
"# Definitions; Variables\n",
"\n",
"hour= UNITS.hour\n",
"parking= 10\n",
"\n",
"cars1= State(parking=10)\n",
"\n",
"cars2= State(parking=10)\n",
"\n",
"# Parameters for cars1 ($25/h)\n",
"p1= .6\n",
"p2= .7\n",
"p3= .4\n",
"\n",
"# Parameters for cars2 ($35/h)\n",
"p4= .5\n",
"p5= .6\n",
"p6= .4"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [
],
"source": [
"# Definitions; Functions\n",
"\n",
"# One car leaves per hour, so adding zero cars is the same as the total number of cars in the lot decreasing by one. The same is true for adding one car, two cars, etc.\n",
"\n",
"#$25 lot\n",
"def minus_one_car1():\n",
" cars1.parking -= 1\n",
"\n",
"def add_zero_cars1():\n",
" cars1.parking += 0\n",
"\n",
"def add_two_cars1():\n",
" cars1.parking += 2\n",
"\n",
"#$35 lot\n",
"def minus_one_car2():\n",
" cars2.parking -= 1\n",
"\n",
"def add_zero_cars2():\n",
" cars2.parking += 0\n",
"\n",
"def add_two_cars2():\n",
" cars2.parking += 2"
]
},
{
"cell_type": "code",
"execution_count": 0,
"metadata": {
"collapsed": false
},
"outputs": [
],
"source": [
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false
},
"outputs": [
{
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