f927636698
This PR has two main changes: 1. Adding a jupyter notebook example to the reactors folder for a constant-volume, adiabatic reactor. This is employed within the context of IDT calculations in high-pressure shock tubes. I'd be happy to add Comparison to experimental data, pending publication of a manuscript currently under consideration (and coauthor permission). This largely follows the routines established in the batch reactor example, and states as much in the notebook. 2. It occurs to me that some users might be interested in seeing the examples as py files, but don't want to bother with installing Jupyter and figuring out how to use it (while these steps are easy, they still might represent a barrier to some users). For the three notebooks in this folder, then, I've saved the notebooks as simple py files and added them to a folder labeled as such.
1249 lines
78 KiB
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1249 lines
78 KiB
Text
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Non-Ideal Shock Tube Example\n",
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"## Ignition delay time computations in a high-pressure reflected shock tube reactor\n",
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" \n",
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"In this example we will illustrate how to setup and use a constant volume, adiabatic reactor to simulate reflected shock tube experiments. This reactor will then be used to compute the ignition delay of a gas at any temperature and pressure. The example very explicitly follows the form set in batch_reactor_ignition_delay_NTC.pynb, which does very similar calculations, but with an IdealGasReactor. All credit is due to the developer of that example. This example generalizes that work to use a Reactor with no pre-assumed EoS. One can also run ideal gas phases through this simulation, simply by specifying a cti file with that thermodynamic EoS.\n",
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"\n",
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"Other than the typical Cantera dependencies, plotting functions require that you have matplotlib installed, and data storing and analysis requires pandas. See https://matplotlib.org/ and http://pandas.pydata.org/index.html, respectively, for additional info.\n",
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" \n",
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"The example here demonstrates the calculations carried out by G. Kogekar, et al., \"Impact of non-ideal behavior on ignition delay and chemical kinetics in high-pressure shock tube reactors,\" Combust. Flame., 2017.\n",
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"\n",
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"The reflected shock tube reactor is modeled as a constant-volume, adiabatic reactor. The heat transfer and the work rates are therefore both zero. With no mass inlets or exits, the 1st law energy balance reduces to:\n",
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"\n",
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"\\begin{equation*}\n",
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"\\frac{dU}{dt} = \\dot{Q} - \\dot{W} = 0.\n",
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"\\end{equation*}\n",
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" \n",
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"Because of the constant-mass and constant-volume assumptions, the density is also therefore constant:\n",
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"\n",
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"\\begin{equation*}\n",
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"\\frac{d\\rho}{dt} = 0.\n",
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"\\end{equation*}\n",
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"\n",
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"Along with the evolving gas composition, then, the thermodynamic state of the gas is defined by the initial total internal energy $U = mu = m\\sum_k\\left(Y_ku_k\\right)$, where $u_k$ and $Y_k$ are the specific internal energy (kJ/kg) and mass fraction of species $k$, respectively. \n",
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"\n",
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"The species mass fractions evolve according to the nety chemical production rates due to homogeneous gas-phase reactions:\n",
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"\n",
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"\\begin{equation*}\n",
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"\\frac{dY_k}{dt} = \\frac{W_k}{\\rho}\\dot{\\omega}_k,\n",
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"\\end{equation*}\n",
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"\n",
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"where $W_k$ is the molecular weight of species $k$ $\\left({\\rm kg}\\,{\\rm kmol}^{-3}\\right)$, $\\rho$ is the (constant) gas-phase density $\\left({\\rm kg}\\,{\\rm m^{-3}}\\right)$, and $\\dot{\\omega}_k$ is the net production rate of species $k$ $\\left({\\rm kmol}\\,{\\rm m^{-3}}\\,{\\rm s^{-1}}\\right)$."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Runnning Cantera version: 2.4.0a1\n"
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]
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}
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||
],
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"source": [
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"from __future__ import division\n",
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"from __future__ import print_function\n",
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"\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"\n",
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"import time\n",
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"\n",
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"import cantera as ct\n",
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"print('Runnning Cantera version: ' + ct.__version__)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Define the gas\n",
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"\n",
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"In this example we will choose a stoichiometric mixture of n-dodecane and air as the gas. For a representative kinetic model, we use that developed by Wang, Ra, Jia, and Reitz (https://www.erc.wisc.edu/chem_mech/nC12-PAH_mech.zip) by [H.Wang, Y.Ra, M.Jia, R.Reitz, Development of a reduced n-dodecane-PAH mechanism and its application for n-dodecane soot predictions, $Fuel$ 136 (2014) 25–36].\n",
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"\n",
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"To fun a different model or use a different EoS, simply replace this cti file with a different mechanism file."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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||
"outputs": [
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{
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||
"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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"**** WARNING ****\n",
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"For species c5h11, discontinuity in cp/R detected at Tmid = 1000\n",
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"\tValue computed using low-temperature polynomial: 32.0653\n",
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"\tValue computed using high-temperature polynomial: 32.1675\n",
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"\n",
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"\n",
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"**** WARNING ****\n",
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"For species c4h4, discontinuity in cp/R detected at Tmid = 1000\n",
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"\tValue computed using low-temperature polynomial: 16.6543\n",
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"\tValue computed using high-temperature polynomial: 16.6734\n",
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"\n",
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"\n",
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"**** WARNING ****\n",
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"For species A3-, discontinuity in cp/R detected at Tmid = 1000\n",
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"\tValue computed using low-temperature polynomial: 52.2095\n",
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"\tValue computed using high-temperature polynomial: 52.364\n"
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]
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}
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],
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"source": [
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"gas = ct.Solution('data/WangMechanismRK.cti')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Define reactor conditions : temperature, pressure, fuel, stoichiometry"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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||
"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# Define the reactor temperature and pressure:\n",
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"reactorTemperature = 1000 #Kelvin\n",
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"reactorPressure = 40.0*101325.0 #Pascals\n",
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"\n",
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"# Set the state of the gas object:\n",
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"gas.TP = reactorTemperature, reactorPressure\n",
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"\n",
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"# Define the fuel, oxidizer and set the stoichiometry:\n",
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"gas.set_equivalence_ratio(phi=1.0, fuel='c12h26', oxidizer={'o2':1.0, 'n2':3.76})\n",
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"\n",
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"# Create a reactor object and add it to a reactor network\n",
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"# In this example, this will be the only reactor in the network\n",
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"r = ct.Reactor(contents=gas)\n",
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"reactorNetwork = ct.ReactorNet([r])\n",
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"\n",
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"# now compile a list of all variables for which we will store data\n",
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"stateVariableNames = [r.component_name(item) for item in range(r.n_vars)]\n",
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"\n",
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"# Use the above list to create a DataFrame\n",
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"timeHistory = pd.DataFrame(columns=stateVariableNames)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Define useful functions"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {
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||
"collapsed": true
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||
},
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"outputs": [],
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"source": [
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"def ignitionDelay(df, species):\n",
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" \"\"\"\n",
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" This function computes the ignition delay from the occurence of the\n",
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" peak in species' concentration.\n",
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" \"\"\"\n",
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" return df[species].argmax()"
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]
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},
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{
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||
"cell_type": "code",
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||
"execution_count": 11,
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||
"metadata": {},
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||
"outputs": [
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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"text": [
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"Computed Ignition Delay: 4.093e-04 seconds. Took 3.12s to compute\n"
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]
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}
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],
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"source": [
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"#Tic\n",
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"t0 = time.time()\n",
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"\n",
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"# This is a starting estimate. If you do not get an ignition within this time, increase it\n",
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"estimatedIgnitionDelayTime = 0.005\n",
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"t = 0\n",
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"\n",
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"counter = 1;\n",
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"while(t < estimatedIgnitionDelayTime):\n",
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" t = reactorNetwork.step()\n",
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" if (counter%20 == 0):\n",
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" # We will save only every 20th value. Otherwise, this takes too long\n",
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" # Note that the species concentrations are mass fractions\n",
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" timeHistory.loc[t] = reactorNetwork.get_state()\n",
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" counter+=1\n",
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"\n",
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"# We will use the 'oh' species to compute the ignition delay\n",
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"tau = ignitionDelay(timeHistory, 'oh')\n",
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"\n",
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"#Toc\n",
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"t1 = time.time()\n",
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"\n",
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"print('Computed Ignition Delay: {:.3e} seconds. Took {:3.2f}s to compute'.format(tau, t1-t0))\n",
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"\n",
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"# If you want to save all the data - molefractions, temperature, pressure, etc\n",
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"# uncomment the next line\n",
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"# timeHistory.to_csv(\"time_history.csv\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Plot the result"
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||
]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Import modules and set plotting defaults"
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]
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},
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{
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"cell_type": "code",
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||
"execution_count": 12,
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||
"metadata": {
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||
"collapsed": true
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||
},
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||
"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"import matplotlib as mpl\n",
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"\n",
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"plt.rcParams['axes.labelsize'] = 16\n",
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"plt.rcParams['xtick.labelsize'] = 12\n",
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"plt.rcParams['ytick.labelsize'] = 12\n",
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||
"plt.rcParams['figure.autolayout'] = True"
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||
]
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||
},
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{
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"cell_type": "markdown",
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||
"metadata": {},
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||
"source": [
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||
"### Figure illustrating the definition of ignition delay"
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]
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},
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{
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||
"cell_type": "code",
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||
"execution_count": 14,
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||
"metadata": {
|
||
"collapsed": true
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||
},
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||
"outputs": [],
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"source": [
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"plt.figure()\n",
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"plt.plot(timeHistory.index, timeHistory['oh'],'-o',color='b',markersize=4)\n",
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"plt.xlabel('Time (s)',fontname='Times New Roman')\n",
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"plt.ylabel('$\\mathdefault{OH\\, mass\\, fraction,}\\, Y_{OH}}$',fontname='Times New Roman')\n",
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"\n",
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"# Figure formatting:\n",
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"plt.xlim([0,0.00075])\n",
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"ax = plt.gca()\n",
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"font = plt.matplotlib.font_manager.FontProperties(family='Times New Roman',size=14)\n",
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"ax.annotate(\"\",xy=(tau,0.005), xytext=(0,0.005),arrowprops=dict(arrowstyle=\"<|-|>\",color='r',linewidth=2.0),fontsize=14,)\n",
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"plt.annotate('Ignition Delay Time (IDT)', xy=(0,0), xytext=(0.00004, 0.00525), family='Times New Roman',fontsize=16);\n",
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"\n",
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"for tick in ax.xaxis.get_major_ticks():\n",
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" tick.label1.set_fontsize(12)\n",
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" tick.label1.set_fontname('Times New Roman')\n",
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"for tick in ax.yaxis.get_major_ticks():\n",
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" tick.label1.set_fontsize(12)\n",
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||
" tick.label1.set_fontname('Times New Roman')"
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||
]
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||
},
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||
{
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||
"cell_type": "markdown",
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||
"metadata": {},
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||
"source": [
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"## Illustration : NTC behavior\n",
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"In the paper by Kogekar, et al., the reactor model is used to demonstrate the impacts of non-ideal behavior on IDTs in the **N**egative **T**emperature **C**oefficient region, where observed IDTs, counter to intuition, increase with increasing temperature."
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||
]
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},
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{
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||
"cell_type": "markdown",
|
||
"metadata": {},
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||
"source": [
|
||
"### Define the temperatures for which we will run the simulations"
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]
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||
},
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{
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||
"cell_type": "code",
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||
"execution_count": 20,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
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||
"outputs": [],
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"source": [
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"# Make a list of all the temperatures we would like to run simulations at\n",
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"T = [1800, 1600, 1400, 1200, 1100, 1075, 1050, 1025, 1000, 975, 950, 925, 900, 850, 825, 800,\n",
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" 750, 700]\n",
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"\n",
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"estimatedIgnitionDelayTimes = np.ones(len(T))\n",
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"\n",
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"# Set the initial guesses to a common value. We could probably speed up simulations \n",
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"# by tuning this guess, but as seen in the figure above, the 'extra' time after igntion \n",
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"# does not add many data points or simulation steps. The time savings would be small.\n",
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"estimatedIgnitionDelayTimes[:] = 0.005\n",
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"\n",
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"# Now create a dataFrame out of these\n",
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"ignitionDelays = pd.DataFrame(data={'T':T})\n",
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"ignitionDelays['ignDelay'] = np.nan"
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]
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},
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{
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||
"cell_type": "markdown",
|
||
"metadata": {},
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"source": [
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"Run the code above for each temperature, and save the IDT for each."
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]
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},
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||
{
|
||
"cell_type": "code",
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||
"execution_count": 21,
|
||
"metadata": {
|
||
"scrolled": false
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||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Computed Ignition Delay: 6.354e-07 seconds for T=1800K. Took 2.02s to compute\n",
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"Computed Ignition Delay: 1.586e-06 seconds for T=1600K. Took 2.11s to compute\n",
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"Computed Ignition Delay: 5.786e-06 seconds for T=1400K. Took 2.34s to compute\n",
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||
"Computed Ignition Delay: 3.911e-05 seconds for T=1200K. Took 2.67s to compute\n",
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"Computed Ignition Delay: 1.326e-04 seconds for T=1100K. Took 2.94s to compute\n",
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"Computed Ignition Delay: 1.839e-04 seconds for T=1075K. Took 2.77s to compute\n",
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"Computed Ignition Delay: 2.533e-04 seconds for T=1050K. Took 2.90s to compute\n",
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"Computed Ignition Delay: 3.365e-04 seconds for T=1025K. Took 3.04s to compute\n",
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"Computed Ignition Delay: 4.093e-04 seconds for T=1000K. Took 3.13s to compute\n",
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"Computed Ignition Delay: 4.289e-04 seconds for T=975K. Took 3.06s to compute\n",
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||
"Computed Ignition Delay: 3.911e-04 seconds for T=950K. Took 3.34s to compute\n",
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"Computed Ignition Delay: 3.407e-04 seconds for T=925K. Took 3.21s to compute\n",
|
||
"Computed Ignition Delay: 3.145e-04 seconds for T=900K. Took 3.30s to compute\n",
|
||
"Computed Ignition Delay: 3.233e-04 seconds for T=850K. Took 3.51s to compute\n",
|
||
"Computed Ignition Delay: 3.439e-04 seconds for T=825K. Took 3.48s to compute\n",
|
||
"Computed Ignition Delay: 3.852e-04 seconds for T=800K. Took 3.63s to compute\n",
|
||
"Computed Ignition Delay: 6.824e-04 seconds for T=750K. Took 3.92s to compute\n",
|
||
"Computed Ignition Delay: 2.056e-03 seconds for T=700K. Took 4.04s to compute\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"for i, temperature in enumerate(T):\n",
|
||
" # Setup the gas and reactor\n",
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" reactorTemperature = temperature\n",
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" reactorPressure = 40.0*101325.0\n",
|
||
" gas.TP = reactorTemperature, reactorPressure\n",
|
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" gas.set_equivalence_ratio(phi=1.0, fuel='c12h26', oxidizer={'o2':1.0, 'n2':3.76})\n",
|
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" r = ct.Reactor(contents=gas)\n",
|
||
" reactorNetwork = ct.ReactorNet([r])\n",
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"\n",
|
||
" # Create and empty data frame\n",
|
||
" timeHistory = pd.DataFrame(columns=timeHistory.columns)\n",
|
||
"\n",
|
||
" t0 = time.time()\n",
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"\n",
|
||
" t = 0\n",
|
||
" counter = 0\n",
|
||
" while t < estimatedIgnitionDelayTimes[i]:\n",
|
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" t = reactorNetwork.step()\n",
|
||
" if not counter % 20:\n",
|
||
" timeHistory.loc[t] = r.get_state()\n",
|
||
" counter += 1\n",
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||
"\n",
|
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" tau = ignitionDelay(timeHistory, 'oh')\n",
|
||
" t1 = time.time()\n",
|
||
"\n",
|
||
" print('Computed Ignition Delay: {:.3e} seconds for T={}K. Took {:3.2f}s to compute'.format(tau, temperature, t1-t0))\n",
|
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"\n",
|
||
" ignitionDelays.set_value(index=i, col='ignDelay', value=tau)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Figure: ignition delay ($\\tau$) vs. the inverse of temperature ($\\frac{1000}{T}$). "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"metadata": {
|
||
"scrolled": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"application/javascript": [
|
||
"/* Put everything inside the global mpl namespace */\n",
|
||
"window.mpl = {};\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.get_websocket_type = function() {\n",
|
||
" if (typeof(WebSocket) !== 'undefined') {\n",
|
||
" return WebSocket;\n",
|
||
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
|
||
" return MozWebSocket;\n",
|
||
" } else {\n",
|
||
" alert('Your browser does not have WebSocket support.' +\n",
|
||
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
|
||
" 'Firefox 4 and 5 are also supported but you ' +\n",
|
||
" 'have to enable WebSockets in about:config.');\n",
|
||
" };\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
|
||
" this.id = figure_id;\n",
|
||
"\n",
|
||
" this.ws = websocket;\n",
|
||
"\n",
|
||
" this.supports_binary = (this.ws.binaryType != undefined);\n",
|
||
"\n",
|
||
" if (!this.supports_binary) {\n",
|
||
" var warnings = document.getElementById(\"mpl-warnings\");\n",
|
||
" if (warnings) {\n",
|
||
" warnings.style.display = 'block';\n",
|
||
" warnings.textContent = (\n",
|
||
" \"This browser does not support binary websocket messages. \" +\n",
|
||
" \"Performance may be slow.\");\n",
|
||
" }\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.imageObj = new Image();\n",
|
||
"\n",
|
||
" this.context = undefined;\n",
|
||
" this.message = undefined;\n",
|
||
" this.canvas = undefined;\n",
|
||
" this.rubberband_canvas = undefined;\n",
|
||
" this.rubberband_context = undefined;\n",
|
||
" this.format_dropdown = undefined;\n",
|
||
"\n",
|
||
" this.image_mode = 'full';\n",
|
||
"\n",
|
||
" this.root = $('<div/>');\n",
|
||
" this._root_extra_style(this.root)\n",
|
||
" this.root.attr('style', 'display: inline-block');\n",
|
||
"\n",
|
||
" $(parent_element).append(this.root);\n",
|
||
"\n",
|
||
" this._init_header(this);\n",
|
||
" this._init_canvas(this);\n",
|
||
" this._init_toolbar(this);\n",
|
||
"\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" this.waiting = false;\n",
|
||
"\n",
|
||
" this.ws.onopen = function () {\n",
|
||
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
|
||
" fig.send_message(\"send_image_mode\", {});\n",
|
||
" if (mpl.ratio != 1) {\n",
|
||
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
|
||
" }\n",
|
||
" fig.send_message(\"refresh\", {});\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.imageObj.onload = function() {\n",
|
||
" if (fig.image_mode == 'full') {\n",
|
||
" // Full images could contain transparency (where diff images\n",
|
||
" // almost always do), so we need to clear the canvas so that\n",
|
||
" // there is no ghosting.\n",
|
||
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
|
||
" }\n",
|
||
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
|
||
" };\n",
|
||
"\n",
|
||
" this.imageObj.onunload = function() {\n",
|
||
" this.ws.close();\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.ws.onmessage = this._make_on_message_function(this);\n",
|
||
"\n",
|
||
" this.ondownload = ondownload;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_header = function() {\n",
|
||
" var titlebar = $(\n",
|
||
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
|
||
" 'ui-helper-clearfix\"/>');\n",
|
||
" var titletext = $(\n",
|
||
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
|
||
" 'text-align: center; padding: 3px;\"/>');\n",
|
||
" titlebar.append(titletext)\n",
|
||
" this.root.append(titlebar);\n",
|
||
" this.header = titletext[0];\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
|
||
"\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
|
||
"\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_canvas = function() {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var canvas_div = $('<div/>');\n",
|
||
"\n",
|
||
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
|
||
"\n",
|
||
" function canvas_keyboard_event(event) {\n",
|
||
" return fig.key_event(event, event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
|
||
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
|
||
" this.canvas_div = canvas_div\n",
|
||
" this._canvas_extra_style(canvas_div)\n",
|
||
" this.root.append(canvas_div);\n",
|
||
"\n",
|
||
" var canvas = $('<canvas/>');\n",
|
||
" canvas.addClass('mpl-canvas');\n",
|
||
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
|
||
"\n",
|
||
" this.canvas = canvas[0];\n",
|
||
" this.context = canvas[0].getContext(\"2d\");\n",
|
||
"\n",
|
||
" var backingStore = this.context.backingStorePixelRatio ||\n",
|
||
"\tthis.context.webkitBackingStorePixelRatio ||\n",
|
||
"\tthis.context.mozBackingStorePixelRatio ||\n",
|
||
"\tthis.context.msBackingStorePixelRatio ||\n",
|
||
"\tthis.context.oBackingStorePixelRatio ||\n",
|
||
"\tthis.context.backingStorePixelRatio || 1;\n",
|
||
"\n",
|
||
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
|
||
"\n",
|
||
" var rubberband = $('<canvas/>');\n",
|
||
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
|
||
"\n",
|
||
" var pass_mouse_events = true;\n",
|
||
"\n",
|
||
" canvas_div.resizable({\n",
|
||
" start: function(event, ui) {\n",
|
||
" pass_mouse_events = false;\n",
|
||
" },\n",
|
||
" resize: function(event, ui) {\n",
|
||
" fig.request_resize(ui.size.width, ui.size.height);\n",
|
||
" },\n",
|
||
" stop: function(event, ui) {\n",
|
||
" pass_mouse_events = true;\n",
|
||
" fig.request_resize(ui.size.width, ui.size.height);\n",
|
||
" },\n",
|
||
" });\n",
|
||
"\n",
|
||
" function mouse_event_fn(event) {\n",
|
||
" if (pass_mouse_events)\n",
|
||
" return fig.mouse_event(event, event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" rubberband.mousedown('button_press', mouse_event_fn);\n",
|
||
" rubberband.mouseup('button_release', mouse_event_fn);\n",
|
||
" // Throttle sequential mouse events to 1 every 20ms.\n",
|
||
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
|
||
"\n",
|
||
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
|
||
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
|
||
"\n",
|
||
" canvas_div.on(\"wheel\", function (event) {\n",
|
||
" event = event.originalEvent;\n",
|
||
" event['data'] = 'scroll'\n",
|
||
" if (event.deltaY < 0) {\n",
|
||
" event.step = 1;\n",
|
||
" } else {\n",
|
||
" event.step = -1;\n",
|
||
" }\n",
|
||
" mouse_event_fn(event);\n",
|
||
" });\n",
|
||
"\n",
|
||
" canvas_div.append(canvas);\n",
|
||
" canvas_div.append(rubberband);\n",
|
||
"\n",
|
||
" this.rubberband = rubberband;\n",
|
||
" this.rubberband_canvas = rubberband[0];\n",
|
||
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
|
||
" this.rubberband_context.strokeStyle = \"#000000\";\n",
|
||
"\n",
|
||
" this._resize_canvas = function(width, height) {\n",
|
||
" // Keep the size of the canvas, canvas container, and rubber band\n",
|
||
" // canvas in synch.\n",
|
||
" canvas_div.css('width', width)\n",
|
||
" canvas_div.css('height', height)\n",
|
||
"\n",
|
||
" canvas.attr('width', width * mpl.ratio);\n",
|
||
" canvas.attr('height', height * mpl.ratio);\n",
|
||
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
|
||
"\n",
|
||
" rubberband.attr('width', width);\n",
|
||
" rubberband.attr('height', height);\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
|
||
" // upon first draw.\n",
|
||
" this._resize_canvas(600, 600);\n",
|
||
"\n",
|
||
" // Disable right mouse context menu.\n",
|
||
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
|
||
" return false;\n",
|
||
" });\n",
|
||
"\n",
|
||
" function set_focus () {\n",
|
||
" canvas.focus();\n",
|
||
" canvas_div.focus();\n",
|
||
" }\n",
|
||
"\n",
|
||
" window.setTimeout(set_focus, 100);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_toolbar = function() {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var nav_element = $('<div/>')\n",
|
||
" nav_element.attr('style', 'width: 100%');\n",
|
||
" this.root.append(nav_element);\n",
|
||
"\n",
|
||
" // Define a callback function for later on.\n",
|
||
" function toolbar_event(event) {\n",
|
||
" return fig.toolbar_button_onclick(event['data']);\n",
|
||
" }\n",
|
||
" function toolbar_mouse_event(event) {\n",
|
||
" return fig.toolbar_button_onmouseover(event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" for(var toolbar_ind in mpl.toolbar_items) {\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) {\n",
|
||
" // put a spacer in here.\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
" var button = $('<button/>');\n",
|
||
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
|
||
" 'ui-button-icon-only');\n",
|
||
" button.attr('role', 'button');\n",
|
||
" button.attr('aria-disabled', 'false');\n",
|
||
" button.click(method_name, toolbar_event);\n",
|
||
" button.mouseover(tooltip, toolbar_mouse_event);\n",
|
||
"\n",
|
||
" var icon_img = $('<span/>');\n",
|
||
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
|
||
" icon_img.addClass(image);\n",
|
||
" icon_img.addClass('ui-corner-all');\n",
|
||
"\n",
|
||
" var tooltip_span = $('<span/>');\n",
|
||
" tooltip_span.addClass('ui-button-text');\n",
|
||
" tooltip_span.html(tooltip);\n",
|
||
"\n",
|
||
" button.append(icon_img);\n",
|
||
" button.append(tooltip_span);\n",
|
||
"\n",
|
||
" nav_element.append(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fmt_picker_span = $('<span/>');\n",
|
||
"\n",
|
||
" var fmt_picker = $('<select/>');\n",
|
||
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
|
||
" fmt_picker_span.append(fmt_picker);\n",
|
||
" nav_element.append(fmt_picker_span);\n",
|
||
" this.format_dropdown = fmt_picker[0];\n",
|
||
"\n",
|
||
" for (var ind in mpl.extensions) {\n",
|
||
" var fmt = mpl.extensions[ind];\n",
|
||
" var option = $(\n",
|
||
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
|
||
" fmt_picker.append(option)\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Add hover states to the ui-buttons\n",
|
||
" $( \".ui-button\" ).hover(\n",
|
||
" function() { $(this).addClass(\"ui-state-hover\");},\n",
|
||
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
|
||
" );\n",
|
||
"\n",
|
||
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
|
||
" nav_element.append(status_bar);\n",
|
||
" this.message = status_bar[0];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
|
||
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
|
||
" // which will in turn request a refresh of the image.\n",
|
||
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_message = function(type, properties) {\n",
|
||
" properties['type'] = type;\n",
|
||
" properties['figure_id'] = this.id;\n",
|
||
" this.ws.send(JSON.stringify(properties));\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_draw_message = function() {\n",
|
||
" if (!this.waiting) {\n",
|
||
" this.waiting = true;\n",
|
||
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
|
||
" }\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
|
||
" var format_dropdown = fig.format_dropdown;\n",
|
||
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
|
||
" fig.ondownload(fig, format);\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
|
||
" var size = msg['size'];\n",
|
||
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
|
||
" fig._resize_canvas(size[0], size[1]);\n",
|
||
" fig.send_message(\"refresh\", {});\n",
|
||
" };\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
|
||
" var x0 = msg['x0'] / mpl.ratio;\n",
|
||
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
|
||
" var x1 = msg['x1'] / mpl.ratio;\n",
|
||
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
|
||
" x0 = Math.floor(x0) + 0.5;\n",
|
||
" y0 = Math.floor(y0) + 0.5;\n",
|
||
" x1 = Math.floor(x1) + 0.5;\n",
|
||
" y1 = Math.floor(y1) + 0.5;\n",
|
||
" var min_x = Math.min(x0, x1);\n",
|
||
" var min_y = Math.min(y0, y1);\n",
|
||
" var width = Math.abs(x1 - x0);\n",
|
||
" var height = Math.abs(y1 - y0);\n",
|
||
"\n",
|
||
" fig.rubberband_context.clearRect(\n",
|
||
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
|
||
"\n",
|
||
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
|
||
" // Updates the figure title.\n",
|
||
" fig.header.textContent = msg['label'];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
|
||
" var cursor = msg['cursor'];\n",
|
||
" switch(cursor)\n",
|
||
" {\n",
|
||
" case 0:\n",
|
||
" cursor = 'pointer';\n",
|
||
" break;\n",
|
||
" case 1:\n",
|
||
" cursor = 'default';\n",
|
||
" break;\n",
|
||
" case 2:\n",
|
||
" cursor = 'crosshair';\n",
|
||
" break;\n",
|
||
" case 3:\n",
|
||
" cursor = 'move';\n",
|
||
" break;\n",
|
||
" }\n",
|
||
" fig.rubberband_canvas.style.cursor = cursor;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
|
||
" fig.message.textContent = msg['message'];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
|
||
" // Request the server to send over a new figure.\n",
|
||
" fig.send_draw_message();\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
|
||
" fig.image_mode = msg['mode'];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function() {\n",
|
||
" // Called whenever the canvas gets updated.\n",
|
||
" this.send_message(\"ack\", {});\n",
|
||
"}\n",
|
||
"\n",
|
||
"// A function to construct a web socket function for onmessage handling.\n",
|
||
"// Called in the figure constructor.\n",
|
||
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
|
||
" return function socket_on_message(evt) {\n",
|
||
" if (evt.data instanceof Blob) {\n",
|
||
" /* FIXME: We get \"Resource interpreted as Image but\n",
|
||
" * transferred with MIME type text/plain:\" errors on\n",
|
||
" * Chrome. But how to set the MIME type? It doesn't seem\n",
|
||
" * to be part of the websocket stream */\n",
|
||
" evt.data.type = \"image/png\";\n",
|
||
"\n",
|
||
" /* Free the memory for the previous frames */\n",
|
||
" if (fig.imageObj.src) {\n",
|
||
" (window.URL || window.webkitURL).revokeObjectURL(\n",
|
||
" fig.imageObj.src);\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
|
||
" evt.data);\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" }\n",
|
||
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
|
||
" fig.imageObj.src = evt.data;\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var msg = JSON.parse(evt.data);\n",
|
||
" var msg_type = msg['type'];\n",
|
||
"\n",
|
||
" // Call the \"handle_{type}\" callback, which takes\n",
|
||
" // the figure and JSON message as its only arguments.\n",
|
||
" try {\n",
|
||
" var callback = fig[\"handle_\" + msg_type];\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (callback) {\n",
|
||
" try {\n",
|
||
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
|
||
" callback(fig, msg);\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
|
||
" }\n",
|
||
" }\n",
|
||
" };\n",
|
||
"}\n",
|
||
"\n",
|
||
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
|
||
"mpl.findpos = function(e) {\n",
|
||
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
|
||
" var targ;\n",
|
||
" if (!e)\n",
|
||
" e = window.event;\n",
|
||
" if (e.target)\n",
|
||
" targ = e.target;\n",
|
||
" else if (e.srcElement)\n",
|
||
" targ = e.srcElement;\n",
|
||
" if (targ.nodeType == 3) // defeat Safari bug\n",
|
||
" targ = targ.parentNode;\n",
|
||
"\n",
|
||
" // jQuery normalizes the pageX and pageY\n",
|
||
" // pageX,Y are the mouse positions relative to the document\n",
|
||
" // offset() returns the position of the element relative to the document\n",
|
||
" var x = e.pageX - $(targ).offset().left;\n",
|
||
" var y = e.pageY - $(targ).offset().top;\n",
|
||
"\n",
|
||
" return {\"x\": x, \"y\": y};\n",
|
||
"};\n",
|
||
"\n",
|
||
"/*\n",
|
||
" * return a copy of an object with only non-object keys\n",
|
||
" * we need this to avoid circular references\n",
|
||
" * http://stackoverflow.com/a/24161582/3208463\n",
|
||
" */\n",
|
||
"function simpleKeys (original) {\n",
|
||
" return Object.keys(original).reduce(function (obj, key) {\n",
|
||
" if (typeof original[key] !== 'object')\n",
|
||
" obj[key] = original[key]\n",
|
||
" return obj;\n",
|
||
" }, {});\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
|
||
" var canvas_pos = mpl.findpos(event)\n",
|
||
"\n",
|
||
" if (name === 'button_press')\n",
|
||
" {\n",
|
||
" this.canvas.focus();\n",
|
||
" this.canvas_div.focus();\n",
|
||
" }\n",
|
||
"\n",
|
||
" var x = canvas_pos.x * mpl.ratio;\n",
|
||
" var y = canvas_pos.y * mpl.ratio;\n",
|
||
"\n",
|
||
" this.send_message(name, {x: x, y: y, button: event.button,\n",
|
||
" step: event.step,\n",
|
||
" guiEvent: simpleKeys(event)});\n",
|
||
"\n",
|
||
" /* This prevents the web browser from automatically changing to\n",
|
||
" * the text insertion cursor when the button is pressed. We want\n",
|
||
" * to control all of the cursor setting manually through the\n",
|
||
" * 'cursor' event from matplotlib */\n",
|
||
" event.preventDefault();\n",
|
||
" return false;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
|
||
" // Handle any extra behaviour associated with a key event\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.key_event = function(event, name) {\n",
|
||
"\n",
|
||
" // Prevent repeat events\n",
|
||
" if (name == 'key_press')\n",
|
||
" {\n",
|
||
" if (event.which === this._key)\n",
|
||
" return;\n",
|
||
" else\n",
|
||
" this._key = event.which;\n",
|
||
" }\n",
|
||
" if (name == 'key_release')\n",
|
||
" this._key = null;\n",
|
||
"\n",
|
||
" var value = '';\n",
|
||
" if (event.ctrlKey && event.which != 17)\n",
|
||
" value += \"ctrl+\";\n",
|
||
" if (event.altKey && event.which != 18)\n",
|
||
" value += \"alt+\";\n",
|
||
" if (event.shiftKey && event.which != 16)\n",
|
||
" value += \"shift+\";\n",
|
||
"\n",
|
||
" value += 'k';\n",
|
||
" value += event.which.toString();\n",
|
||
"\n",
|
||
" this._key_event_extra(event, name);\n",
|
||
"\n",
|
||
" this.send_message(name, {key: value,\n",
|
||
" guiEvent: simpleKeys(event)});\n",
|
||
" return false;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
|
||
" if (name == 'download') {\n",
|
||
" this.handle_save(this, null);\n",
|
||
" } else {\n",
|
||
" this.send_message(\"toolbar_button\", {name: name});\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
|
||
" this.message.textContent = tooltip;\n",
|
||
"};\n",
|
||
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
|
||
"\n",
|
||
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
|
||
"\n",
|
||
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
|
||
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
|
||
" // object with the appropriate methods. Currently this is a non binary\n",
|
||
" // socket, so there is still some room for performance tuning.\n",
|
||
" var ws = {};\n",
|
||
"\n",
|
||
" ws.close = function() {\n",
|
||
" comm.close()\n",
|
||
" };\n",
|
||
" ws.send = function(m) {\n",
|
||
" //console.log('sending', m);\n",
|
||
" comm.send(m);\n",
|
||
" };\n",
|
||
" // Register the callback with on_msg.\n",
|
||
" comm.on_msg(function(msg) {\n",
|
||
" //console.log('receiving', msg['content']['data'], msg);\n",
|
||
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
|
||
" ws.onmessage(msg['content']['data'])\n",
|
||
" });\n",
|
||
" return ws;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.mpl_figure_comm = function(comm, msg) {\n",
|
||
" // This is the function which gets called when the mpl process\n",
|
||
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
|
||
"\n",
|
||
" var id = msg.content.data.id;\n",
|
||
" // Get hold of the div created by the display call when the Comm\n",
|
||
" // socket was opened in Python.\n",
|
||
" var element = $(\"#\" + id);\n",
|
||
" var ws_proxy = comm_websocket_adapter(comm)\n",
|
||
"\n",
|
||
" function ondownload(figure, format) {\n",
|
||
" window.open(figure.imageObj.src);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fig = new mpl.figure(id, ws_proxy,\n",
|
||
" ondownload,\n",
|
||
" element.get(0));\n",
|
||
"\n",
|
||
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
|
||
" // web socket which is closed, not our websocket->open comm proxy.\n",
|
||
" ws_proxy.onopen();\n",
|
||
"\n",
|
||
" fig.parent_element = element.get(0);\n",
|
||
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
|
||
" if (!fig.cell_info) {\n",
|
||
" console.error(\"Failed to find cell for figure\", id, fig);\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var output_index = fig.cell_info[2]\n",
|
||
" var cell = fig.cell_info[0];\n",
|
||
"\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
|
||
" var width = fig.canvas.width/mpl.ratio\n",
|
||
" fig.root.unbind('remove')\n",
|
||
"\n",
|
||
" // Update the output cell to use the data from the current canvas.\n",
|
||
" fig.push_to_output();\n",
|
||
" var dataURL = fig.canvas.toDataURL();\n",
|
||
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
|
||
" // the notebook keyboard shortcuts fail.\n",
|
||
" IPython.keyboard_manager.enable()\n",
|
||
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
|
||
" fig.close_ws(fig, msg);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
|
||
" fig.send_message('closing', msg);\n",
|
||
" // fig.ws.close()\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
|
||
" // Turn the data on the canvas into data in the output cell.\n",
|
||
" var width = this.canvas.width/mpl.ratio\n",
|
||
" var dataURL = this.canvas.toDataURL();\n",
|
||
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function() {\n",
|
||
" // Tell IPython that the notebook contents must change.\n",
|
||
" IPython.notebook.set_dirty(true);\n",
|
||
" this.send_message(\"ack\", {});\n",
|
||
" var fig = this;\n",
|
||
" // Wait a second, then push the new image to the DOM so\n",
|
||
" // that it is saved nicely (might be nice to debounce this).\n",
|
||
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_toolbar = function() {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var nav_element = $('<div/>')\n",
|
||
" nav_element.attr('style', 'width: 100%');\n",
|
||
" this.root.append(nav_element);\n",
|
||
"\n",
|
||
" // Define a callback function for later on.\n",
|
||
" function toolbar_event(event) {\n",
|
||
" return fig.toolbar_button_onclick(event['data']);\n",
|
||
" }\n",
|
||
" function toolbar_mouse_event(event) {\n",
|
||
" return fig.toolbar_button_onmouseover(event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" for(var toolbar_ind in mpl.toolbar_items){\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) { continue; };\n",
|
||
"\n",
|
||
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
|
||
" button.click(method_name, toolbar_event);\n",
|
||
" button.mouseover(tooltip, toolbar_mouse_event);\n",
|
||
" nav_element.append(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Add the status bar.\n",
|
||
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
|
||
" nav_element.append(status_bar);\n",
|
||
" this.message = status_bar[0];\n",
|
||
"\n",
|
||
" // Add the close button to the window.\n",
|
||
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
|
||
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
|
||
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
|
||
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
|
||
" buttongrp.append(button);\n",
|
||
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
|
||
" titlebar.prepend(buttongrp);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._root_extra_style = function(el){\n",
|
||
" var fig = this\n",
|
||
" el.on(\"remove\", function(){\n",
|
||
"\tfig.close_ws(fig, {});\n",
|
||
" });\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
|
||
" // this is important to make the div 'focusable\n",
|
||
" el.attr('tabindex', 0)\n",
|
||
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
|
||
" // off when our div gets focus\n",
|
||
"\n",
|
||
" // location in version 3\n",
|
||
" if (IPython.notebook.keyboard_manager) {\n",
|
||
" IPython.notebook.keyboard_manager.register_events(el);\n",
|
||
" }\n",
|
||
" else {\n",
|
||
" // location in version 2\n",
|
||
" IPython.keyboard_manager.register_events(el);\n",
|
||
" }\n",
|
||
"\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
|
||
" var manager = IPython.notebook.keyboard_manager;\n",
|
||
" if (!manager)\n",
|
||
" manager = IPython.keyboard_manager;\n",
|
||
"\n",
|
||
" // Check for shift+enter\n",
|
||
" if (event.shiftKey && event.which == 13) {\n",
|
||
" this.canvas_div.blur();\n",
|
||
" // select the cell after this one\n",
|
||
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
|
||
" IPython.notebook.select(index + 1);\n",
|
||
" }\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
|
||
" fig.ondownload(fig, null);\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.find_output_cell = function(html_output) {\n",
|
||
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
|
||
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
|
||
" // IPython event is triggered only after the cells have been serialised, which for\n",
|
||
" // our purposes (turning an active figure into a static one), is too late.\n",
|
||
" var cells = IPython.notebook.get_cells();\n",
|
||
" var ncells = cells.length;\n",
|
||
" for (var i=0; i<ncells; i++) {\n",
|
||
" var cell = cells[i];\n",
|
||
" if (cell.cell_type === 'code'){\n",
|
||
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
|
||
" var data = cell.output_area.outputs[j];\n",
|
||
" if (data.data) {\n",
|
||
" // IPython >= 3 moved mimebundle to data attribute of output\n",
|
||
" data = data.data;\n",
|
||
" }\n",
|
||
" if (data['text/html'] == html_output) {\n",
|
||
" return [cell, data, j];\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
"}\n",
|
||
"\n",
|
||
"// Register the function which deals with the matplotlib target/channel.\n",
|
||
"// The kernel may be null if the page has been refreshed.\n",
|
||
"if (IPython.notebook.kernel != null) {\n",
|
||
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
|
||
"}\n"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.Javascript object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<img 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\" width=\"640\">"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"fig = plt.figure()\n",
|
||
"ax = fig.add_subplot(111)\n",
|
||
"ax.semilogy(1000/ignitionDelays['T'], ignitionDelays['ignDelay'],'o-',color='b')\n",
|
||
"ax.set_ylabel('Ignition Delay (s)',fontname='Times New Roman',fontsize=16)\n",
|
||
"ax.set_xlabel(r'$\\mathdefault{1000/T\\, (K^{-1})}$', fontsize=16,fontname='Times New Roman')\n",
|
||
"\n",
|
||
"# Add a second axis on top to plot the temperature for better readability\n",
|
||
"ax2 = ax.twiny()\n",
|
||
"ticks = ax.get_xticks()\n",
|
||
"ax2.set_xticks(ticks)\n",
|
||
"ax2.set_xticklabels((1000/ticks).round(1))\n",
|
||
"ax2.set_xlim(ax.get_xlim())\n",
|
||
"ax2.set_xlabel('Temperature (K)',fontname='Times New Roman',fontsize=16);\n",
|
||
"\n",
|
||
"for tick in ax.xaxis.get_major_ticks():\n",
|
||
" tick.label1.set_fontsize(12)\n",
|
||
" tick.label1.set_fontname('Times New Roman')\n",
|
||
"for tick in ax.yaxis.get_major_ticks():\n",
|
||
" tick.label1.set_fontsize(12)\n",
|
||
" tick.label1.set_fontname('Times New Roman')\n",
|
||
"for tick in ax2.xaxis.get_major_ticks():\n",
|
||
" tick.label1.set_fontsize(12)\n",
|
||
" tick.label1.set_fontname('Times New Roman')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"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": "3.5.2"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 1
|
||
}
|