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@karlnapf
Created July 27, 2016 12:36
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{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"X = np.linspace(10, 500, 10)\n",
"Y = 2*X + np.random.randn(1000,len(X))**2 * 100"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(10,)\n",
"(1000, 10)\n"
]
}
],
"source": [
"print X.shape\n",
"print Y.shape"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"m=np.mean(Y, axis=0)\n",
"lower = np.percentile(Y, 5, axis=0)\n",
"upper = np.percentile(Y, 95, axis=0)\n"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f4c190dbed0>]"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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4sOfN2hG8V2Y8rSQXaTeUGE/aN/oe0qri4yP4e4Fx9JY4EfgTadqwVXANwdqeRE/gNGAz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\n5ksAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f4c1915a310>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(X, m, 'b-')\n",
"plt.plot(X, lower, 'b--')\n",
"plt.plot(X, upper, 'b--')\n"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PolyCollection at 0x7f4c1907f590>"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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KmBNVFW9b6O474x2DNEUKhAIW2la2m6AJ45yLtv7mQkLf4qWEnsUxL9usaxm2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\nDCwAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f4c1909b190>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(X, m, 'b-')\n",
"plt.fill_between(X, lower, upper, alpha=0.5)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<Container object of 3 artists>"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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mYJtHKi4tAkggRIyocr3iT0g8AfwDxb2C0Tb/2ebxisuL+Au5hxAxAiQEnAOcDrwcuBI4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\nCYSIiCglECIiAoD/D3LpApV5/k1oAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f4c1904cf50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(X, m, 'b-')\n",
"plt.errorbar(X, m, yerr=[m-lower, upper-m])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
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"pygments_lexer": "ipython2",
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}
},
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}
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