mirror of
https://github.com/wassname/spaceapps2017_matches.git
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252 lines
48 KiB
Plaintext
252 lines
48 KiB
Plaintext
{
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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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"There is term in the fire transmission equation in the spread equations that I didn't expect. \n",
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"Let's look at the graph of how it varies. It is:\n",
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"\n",
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"$e^{0.069*\\theta}$ where $\\theta$ is slope in degrees.\n",
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"\n",
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"paper: http://www.bushfirecrc.com/sites/default/files/managed/resource/ctr_010.pdf"
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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": 30,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2017-04-28T00:41:33.684884Z",
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"start_time": "2017-04-28T08:41:33.679476+08:00"
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}
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},
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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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"Using matplotlib backend: agg\n",
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"Populating the interactive namespace from numpy and matplotlib\n"
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]
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}
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],
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"source": [
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"%pylab\n",
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"%matplotlib inline"
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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": 31,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2017-04-28T00:41:37.061870Z",
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"start_time": "2017-04-28T08:41:36.926833+08:00"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[<matplotlib.lines.Line2D at 0x7f05e5d24c50>]"
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]
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},
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"execution_count": 31,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": 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JGwW9iIwZ2w98wL6jHUV5ucCzUdCLyJixYVsTFWUl3Hxpcbc86E9BLyJjwo6DH/D0G+9x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\nBb2ISJH7/9o7eKZhLh3UAAAAAElFTkSuQmCC\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x7f05e585e860>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"slope = np.arange(-90,90,10)\n",
|
|
"r=np.exp(0.069*slope)\n",
|
|
"plt.plot(slope,r)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"the graph explains it, it has trouble spreading down (negative degrees) but not up (positive)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"collapsed": true
|
|
},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2017-04-28T00:42:38.601013Z",
|
|
"start_time": "2017-04-28T08:42:38.596928+08:00"
|
|
}
|
|
},
|
|
"source": [
|
|
"# can I make an approximation \n",
|
|
"\n",
|
|
"Since we start with height we need to derive slope. Compare to a neighbouring cell.\n",
|
|
"\n",
|
|
"$e^{0.069*\\theta}$ where $\\theta$ is calculated from the height (h) and width (w)\n",
|
|
"\n",
|
|
"$\\theta = tan^{-1}(h/w) * 180/pi$\n",
|
|
"\n",
|
|
"$e^{0.069*(tan^{-1}(h/w) * 180/pi)}$\n",
|
|
"\n",
|
|
"The small tan approximation is \n",
|
|
"\n",
|
|
"$e^{0.069*(h/w * 180/pi)}$\n",
|
|
"\n",
|
|
"let see how well it holds up"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 37,
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2017-04-28T00:45:54.116757Z",
|
|
"start_time": "2017-04-28T08:45:53.973117+08:00"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[<matplotlib.lines.Line2D at 0x7f05e5681208>]"
|
|
]
|
|
},
|
|
"execution_count": 37,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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y8gV9ObFXB7fTSQBSGYiEkqoSZ2C5Na+SH9GVSZ6/kB89kPsu7MO5gzrrKyPlJ6kMRELF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\nTkSuQmCC\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x7f05e56812b0>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"h = np.arange(-60,60,5)\n",
|
|
"plt.plot(h,np.tanh(h/30) * 180/np.pi)\n",
|
|
"plt.plot(h,h/30* 180/pi)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"It holds up well to ~20 deg, good enougth to give a try"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2017-04-28T00:08:21.412455Z",
|
|
"start_time": "2017-04-28T08:08:21.170569+08:00"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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SSqEvIhJn/pot3PLsXEZUlXP7edl7P/6+KPRFREKbPtnJtY/PpntJEQ9eNiwr/ihKW6lP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\n5H8BmZJtgduxrdsAAAAASUVORK5CYII=\n",
|
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"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x7f05e577fa20>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[<matplotlib.lines.Line2D at 0x7f05e5aa5048>]"
|
|
]
|
|
},
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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lhR2VhV29iMggqq1PFPTQB90U9CIivWg9cIi61oMFfyIWFPQiIr3aFJMTsaCgFxHp1YbD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\nxNz/B6+ak6LY/k5qAAAAAElFTkSuQmCC\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x7f05e5990208>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"h = np.arange(-60,60,5)\n",
|
|
"slope = np.rad2deg(np.tanh(h/30))\n",
|
|
"r=np.exp(0.069*slope)\n",
|
|
"plt.plot(slope,r)\n",
|
|
"plt.title('non approx')\n",
|
|
"plt.ylim(0,100)\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"h = np.arange(-60,60,5)\n",
|
|
"slope = np.rad2deg(h/30)\n",
|
|
"r=np.exp(0.069*slope)/10\n",
|
|
"plt.title('small tan approx')\n",
|
|
"plt.ylim(0,100)\n",
|
|
"plt.plot(slope,r)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"collapsed": true
|
|
},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "jupyter3",
|
|
"language": "python",
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"name": "jupyter3"
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},
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"name": "ipython",
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"version": 3
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},
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"name": "python",
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}
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},
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}
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