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Randomized Response Function for Differential Privacy
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{
"cells": [
{
"cell_type": "code",
"execution_count": 245,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import random\n",
"import math"
]
},
{
"cell_type": "code",
"execution_count": 246,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def randomized_response(true_response):\n",
" \"\"\"\n",
" Return a randomized response giving plausible deniability to a query about our true response value. This allows us to run\n",
" queries across a population while preserving individual privacy.\n",
" \n",
" Parameters\n",
" ---\n",
" true_response : boolean\n",
" A boolean value that is our true response value.\n",
" \n",
" Returns\n",
" ---\n",
" boolean\n",
" A boolean value that is our randomized response value.\n",
" \"\"\"\n",
" if random.choice([True, False]):\n",
" return true_response\n",
" return random.choice([True, False])"
]
},
{
"cell_type": "code",
"execution_count": 274,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"class Employee:\n",
" def __init__(self, happy):\n",
" self.happy = happy\n",
" \n",
" def is_happy(self):\n",
" return randomized_response(self.happy)\n",
"\n",
"def run_employee_simulation(employee_count, happy_count, tolerance=0):\n",
" \"\"\"\n",
" Simulate employee happiness and return whether most are happy.\n",
" \n",
" Parameters\n",
" ---\n",
" employee_count : integer\n",
" The number of employees to simulate.\n",
" happy_count : integer\n",
" The number of employees who are happy.\n",
" tolerance : float\n",
" The scale of difference from mean employee happiness = 0.5\n",
" \n",
" Returns\n",
" ---\n",
" boolean\n",
" A boolean value that is True if approximately most users are happy, False otherwise.\n",
" \"\"\"\n",
" happiness = [False for i in xrange(employee_count)]\n",
" for i in xrange(happy_count):\n",
" happiness[i] = True\n",
" employees = [Employee(happy) for happy in happiness]\n",
" survey_happies = sum([employee.is_happy() for employee in employees])\n",
" return survey_happies > employee_count / 2.0 + tolerance"
]
},
{
"cell_type": "code",
"execution_count": 311,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import matplotlib\n",
"%matplotlib inline\n",
"matplotlib.style.use('ggplot')\n",
"\n",
"def plot_employee_simulations(employee_count, sample_count=20, iteration_count=1000, tolerance=0):\n",
" j_scale = employee_count / float(sample_count - 1)\n",
" xs = [int(j_scale*j) for j in xrange(sample_count)]\n",
" ys = [sum([run_employee_simulation(employee_count, x, tolerance) for i in xrange(iteration_count)]) / float(iteration_count) for x in xs] \n",
" plt.plot(xs, ys)\n",
" plt.axvline(employee_count/2.0)\n",
" plt.xlabel(\"#Happy\")\n",
" plt.ylabel(\"Percent Happy Simulations\")\n",
" plt.ylim([0, 1])\n",
" plt.title(\"%d Simulations of %d Employees' Happiness\" % (iteration_count, employee_count))\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 312,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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FixZISkrCixcv8vyRdnBwUJe5e/cuFApFnjK2trbqbVWuXBn9+vXD6tWrceXKFdy6dUsr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\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1099790d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_employee_simulations(10, sample_count=10)"
]
},
{
"cell_type": "code",
"execution_count": 316,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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bmjdvLi4XBAHDhg177P2zsrJgbf3g+P8qlQpJSUlabfr3749PPvkEb775JvLz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\nKpDKAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x109d6d550>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_employee_simulations(100, sample_count=30)"
]
},
{
"cell_type": "code",
"execution_count": 317,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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yYGFhwUWDsVqIT9BU90la47CxscEXX3yB9u3bo379+uJyQRAwYMCAp94/PT0d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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10999be90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_employee_simulations(100, sample_count=30, tolerance=math.sqrt(100)/2)"
]
},
{
"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",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.9"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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