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@alchemyst
Created August 9, 2019 14:56
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Weight loss notebook
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{
"cells": [
{
"cell_type": "code",
"execution_count": 105,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 106,
"metadata": {},
"outputs": [],
"source": [
"import numpy"
]
},
{
"cell_type": "code",
"execution_count": 178,
"metadata": {},
"outputs": [],
"source": [
"Ndays = 14"
]
},
{
"cell_type": "code",
"execution_count": 179,
"metadata": {},
"outputs": [],
"source": [
"x = numpy.arange(Ndays + 1)"
]
},
{
"cell_type": "code",
"execution_count": 198,
"metadata": {},
"outputs": [],
"source": [
"lossrate = 1/7"
]
},
{
"cell_type": "code",
"execution_count": 199,
"metadata": {},
"outputs": [],
"source": [
"startweight = 75\n",
"endweight = startweight - lossrate*Ndays"
]
},
{
"cell_type": "code",
"execution_count": 200,
"metadata": {},
"outputs": [],
"source": [
"stddev = 1"
]
},
{
"cell_type": "code",
"execution_count": 201,
"metadata": {},
"outputs": [],
"source": [
"realweight = startweight - lossrate*x"
]
},
{
"cell_type": "code",
"execution_count": 202,
"metadata": {},
"outputs": [],
"source": [
"def decorate():\n",
" plt.xlabel('Day')\n",
" plt.ylabel('Weight / kg')\n",
" plt.ylim(70, 80)"
]
},
{
"cell_type": "code",
"execution_count": 240,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x, realweight)\n",
"decorate()"
]
},
{
"cell_type": "code",
"execution_count": 270,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fluctuation = numpy.random.normal(0, stdev, size=len(x))\n",
"measured = realweight + fluctuation\n",
"weekly = [0, 7, 14]\n",
"plt.plot(x, realweight)\n",
"plt.scatter(x, measured)\n",
"plt.scatter(x[weekly], measured[weekly], s=100, alpha=0.3, color='red')\n",
"decorate()\n",
"plt.legend(['True weight', 'Measurements', 'Weekly'])\n",
"plt.savefig('fig1.png')"
]
},
{
"cell_type": "code",
"execution_count": 284,
"metadata": {},
"outputs": [],
"source": [
"def partialfit(x, measured, start, end):\n",
" fit = numpy.polyfit(x[start:end], measured[start:end], 1)\n",
" plt.plot(x[start:end], numpy.polyval(fit, x[start:end]), '--')"
]
},
{
"cell_type": "code",
"execution_count": 286,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x, realweight)\n",
"plt.scatter(x, measured)\n",
"partialfit(x, measured, 0, 8)\n",
"partialfit(x, measured, 8, 15)\n",
"partialfit(x, measured, 0, 15)\n",
"plt.legend(['True weight', 'Regression (wk 1)', 'Regression(wk 2)', 'Overall regression', 'Measurements'])\n",
"decorate()\n",
"plt.savefig('fig2.png')"
]
},
{
"cell_type": "code",
"execution_count": 243,
"metadata": {},
"outputs": [],
"source": [
"!open ."
]
},
{
"cell_type": "code",
"execution_count": 287,
"metadata": {},
"outputs": [],
"source": [
"import scipy.stats"
]
},
{
"cell_type": "code",
"execution_count": 315,
"metadata": {},
"outputs": [],
"source": [
"N = 50000\n",
"measured_start = numpy.random.normal(startweight, 1, size=N)\n",
"measured_end = numpy.random.normal(endweight, 1, size=N)"
]
},
{
"cell_type": "code",
"execution_count": 316,
"metadata": {},
"outputs": [],
"source": [
"loss = measured_start - measured_end"
]
},
{
"cell_type": "code",
"execution_count": 317,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x1a2b5f8588>]"
]
},
"execution_count": 317,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.hist(loss, bins=100, density=True);\n",
"smoothx = numpy.linspace(-4, 5)\n",
"fit = scipy.stats.norm.pdf(smoothx, startweight - endweight, numpy.sqrt(2))\n",
"plt.plot(smoothx, fit)"
]
},
{
"cell_type": "code",
"execution_count": 318,
"metadata": {},
"outputs": [],
"source": [
"error_rate = scipy.stats.norm.cdf(0, lossrate*x, numpy.sqrt(2))"
]
},
{
"cell_type": "code",
"execution_count": 319,
"metadata": {},
"outputs": [],
"source": [
"def errorplot():\n",
" plt.plot(x, error_rate*100)\n",
" # plt.plot(x[1:], numpy.array(chances)*100)\n",
" plt.xlabel('Days')\n",
" plt.ylabel('Chance of seeing no weight loss')\n",
" plt.ylim(0, 50)\n",
" plt.xlim(left=0)\n",
" plt.axvline(7, color='lightgrey')\n",
" plt.axhline(scipy.stats.norm.cdf(0, lossrate*7, numpy.sqrt(2))*100, color='lightgrey')"
]
},
{
"cell_type": "code",
"execution_count": 320,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"errorplot()\n",
"plt.savefig('twopoint.png')"
]
},
{
"cell_type": "code",
"execution_count": 328,
"metadata": {},
"outputs": [],
"source": [
"chances = []\n",
"for days in range(1, Ndays+1):\n",
" measurements = []\n",
" fits = []\n",
" for i in range(N):\n",
" series = numpy.random.normal(startweight - lossrate*x[:days+1], 1)\n",
" measurements.append(series)\n",
" fit = numpy.polyfit(x[:days+1], series, 1)\n",
" fits.append(fit)\n",
" measurements = numpy.vstack(measurements)\n",
" fits = numpy.vstack(fits)\n",
" chance = numpy.mean(fits[:, 0] >= 0)\n",
" chances.append(chance)"
]
},
{
"cell_type": "code",
"execution_count": 329,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x, error_rate*100)\n",
"plt.plot(range(1, Ndays+1), numpy.array(chances)*100)\n",
"plt.xlabel('Days')\n",
"plt.ylabel('Chance of seeing no weight loss')\n",
"plt.ylim(0, 50)\n",
"plt.xlim(left=0)\n",
"plt.legend(['Two-point', 'Linear slope'])\n",
"plt.axvline(7, color='lightgrey')\n",
"plt.savefig('twopoint_vs_slope.png')"
]
},
{
"cell_type": "code",
"execution_count": 216,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.hist(fits[:, 0], 100);"
]
},
{
"cell_type": "code",
"execution_count": 218,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.hist(fits[:, 1], 100);\n",
"plt.hist(fits[:, 0]*Ndays + fits[:, 1], 100);"
]
},
{
"cell_type": "code",
"execution_count": 219,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.4930641745969022"
]
},
"execution_count": 219,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"numpy.std(fits[:, 1])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"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": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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