{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "name": "2021-06-19-methods-for-effective-online-testing.ipynb", "provenance": [], "collapsed_sections": [], "authorship_tag": "ABX9TyOD8Qfr0hIOMsufh42zwBGv" }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" } }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "wZNHBjSxcMCb" }, "source": [ "# Methods for effective online testing\n", "> Testing out different bandit methods for effective online testing methods\n", "\n", "- toc: true\n", "- badges: true\n", "- comments: true\n", "- categories: [bandit]\n", "- image: " ] }, { "cell_type": "code", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "YNBy2YeFsXqV", "outputId": "78926dfb-c275-4191-f612-b89c48779007" }, "source": [ "!pip install git+https://github.com/sparsh-ai/recochef.git" ], "execution_count": 1, "outputs": [ { "output_type": "stream", "text": [ "Collecting git+https://github.com/sparsh-ai/recochef.git\n", " Cloning https://github.com/sparsh-ai/recochef.git to /tmp/pip-req-build-1qpnc3ak\n", " Running command git clone -q https://github.com/sparsh-ai/recochef.git /tmp/pip-req-build-1qpnc3ak\n", " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", " Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n", "Requirement already satisfied: importlib-metadata; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from recochef==0.0.post1.dev7+g49ee6bc) (4.5.0)\n", "Requirement already satisfied: typing-extensions>=3.6.4; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from importlib-metadata; python_version < \"3.8\"->recochef==0.0.post1.dev7+g49ee6bc) (3.7.4.3)\n", "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata; python_version < \"3.8\"->recochef==0.0.post1.dev7+g49ee6bc) (3.4.1)\n", "Building wheels for collected packages: recochef\n", " Building wheel for recochef (PEP 517) ... \u001b[?25l\u001b[?25hdone\n", " Created wheel for recochef: filename=recochef-0.0.post1.dev7+g49ee6bc-cp37-none-any.whl size=19052 sha256=8ee4ffa07f9b2f40145e765690655b013d98cd50fb0c039a062e00207c28032b\n", " Stored in directory: /tmp/pip-ephem-wheel-cache-tvyexl4d/wheels/4c/90/0f/19e93713ae38e283b3ea7281df324a99bd704095da42261514\n", "Successfully built recochef\n", "Installing collected packages: recochef\n", "Successfully installed recochef-0.0.post1.dev7+g49ee6bc\n" ], "name": "stdout" } ] }, { "cell_type": "code", "metadata": { "id": "kXRUQmKuxaKP" }, "source": [ "import math\n", "from typing import List\n", "\n", "import numpy as np\n", "import pandas as pd\n", "from scipy import stats\n", "from matplotlib import pyplot as plt\n", "\n", "from recochef.models.epsilon import EpsilonGreedyRunner\n", "from recochef.models.thompson import ThompsonSamplingRunner" ], "execution_count": 2, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "-S4iEXbfxypa" }, "source": [ "class SplitTestRunner:\n", " \"\"\"\n", " Class that is used to run simulations of split tests.\n", "\n", " Attributes:\n", " bandit_returns: List of average returns per bandit.\n", " batch_size: Number of examples per batch.\n", " batches: Number of batches.\n", " simulations: Number of simulations.\n", " \n", " Methods:\n", " init_bandits: Prepares everything for new simulation.\n", " run: Runs the simulations and tracks performance.\n", " \"\"\"\n", "\n", " def __init__(self, bandit_returns: List[float], batch_size: int=1000, batches: int=10, simulations: int=100):\n", " \"\"\"\n", " Initializes a new RunSplitTest class with passed parameters.\n", "\n", " Args:\n", " bandit_returns: List of average returns per bandit.\n", " batch_size: Number of examples per batch.\n", " batches: Number of batches.\n", " simulations: Number of simulations.\n", " \"\"\"\n", "\n", " self.bandit_returns = bandit_returns\n", " self.n_bandits = len(bandit_returns)\n", " self.bandits = list(range(self.n_bandits))\n", " self.bandit_positive_examples = [0] * self.n_bandits\n", " self.bandit_total_examples = [0] * self.n_bandits\n", "\n", " self.batch_size = batch_size\n", " self.batches = batches\n", " self.simulations = simulations\n", "\n", " self.df_bids = pd.DataFrame(columns=self.bandit_returns)\n", " self.df_clicks = pd.DataFrame(columns=self.bandit_returns)\n", " \n", " def init_bandits(self):\n", " \"\"\"\n", " Prepares everything for new simulation.\n", " \"\"\"\n", "\n", " self.bandit_positive_examples = [0] * self.n_bandits\n", " self.bandit_total_examples = [0] * self.n_bandits\n", " \n", " def run(self):\n", " \"\"\"\n", " Runs the simulations and tracks performance.\n", " \"\"\"\n", "\n", " for j in range(self.simulations):\n", " self.init_bandits()\n", " for i in range(self.batches):\n", " examples = self.batch_size // self.n_bandits\n", " for idx in self.bandits:\n", " self.bandit_total_examples[idx] += examples\n", " self.bandit_positive_examples[idx] += np.random.binomial(examples, self.bandit_returns[idx])\n", " if self.df_bids.shape[0] < self.batches:\n", " self.df_bids.loc[i] = self.bandit_total_examples\n", " self.df_clicks.loc[i] = self.bandit_positive_examples\n", " else:\n", " self.df_bids.loc[i] += self.bandit_total_examples\n", " self.df_clicks.loc[i] += self.bandit_positive_examples\n", " self.df_bids /= self.simulations\n", " self.df_clicks /= self.simulations" ], "execution_count": 3, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "6IcZBM8Kxn3x" }, "source": [ "def line_plot(df: pd.DataFrame, title:str, x_label: str, y_label: str):\n", " \"\"\"\n", " Plots a line plot of the passed DataFrame.\n", "\n", " Args:\n", " df: DataFrame containing data to be plotted.\n", " title: Title of the plot.\n", " x_label: Title of the x-axis.\n", " y_label: Title of the y-axis.\n", " \"\"\"\n", " stacked_data = df.apply(lambda x: x*100/sum(x), axis=1)\n", " stacked_data.plot(kind=\"line\", stacked=True)\n", " plt.title(title)\n", " plt.xlabel(x_label)\n", " plt.ylabel(y_label)\n", "\n", "\n", "def stacked_plot(df: pd.DataFrame, title:str, x_label: str, y_label: str):\n", " \"\"\"\n", " Plots a stacked area plot of the passed DataFrame.\n", "\n", " Args:\n", " df: DataFrame containing data to be plotted.\n", " title: Title of the plot.\n", " x_label: Title of the x-axis.\n", " y_label: Title of the y-axis.\n", " \"\"\"\n", " stacked_data = df.apply(lambda x: x*100/sum(x), axis=1)\n", " stacked_data.plot(kind=\"area\", stacked=True, figsize=(12,6))\n", " plt.title(title)\n", " plt.xlabel(x_label)\n", " plt.ylabel(y_label)\n", "\n", "\n", "def plot_line_plots(rst: SplitTestRunner, reg: EpsilonGreedyRunner, rts: ThompsonSamplingRunner):\n", " \"\"\"\n", " Plots a line plots for each type of test.\n", "\n", " Args:\n", " rst: Split test simulation class.\n", " reg: Epsilon-greedy MAB test simulation class.\n", " rts: Thompson sampling test simulation class.\n", " \"\"\"\n", " line_plot(rst.df_bids,\n", " title='A/B Test Bandit Resources Allocation',\n", " x_label='Batch',\n", " y_label='Bandit Allocation (%)')\n", "\n", " line_plot(reg.df_bids,\n", " title='Epsilon Greedy Bandit Resources Allocation',\n", " x_label='Batch',\n", " y_label='Bandit Allocation (%)')\n", "\n", " line_plot(rts.df_bids,\n", " title='Thompson Sampling Bandit Resources Allocation',\n", " x_label='Batch',\n", " y_label='Bandit Allocation (%)')\n", "\n", "\n", "def plot_stacked_plots(rst: SplitTestRunner, reg: EpsilonGreedyRunner, rts: ThompsonSamplingRunner):\n", " \"\"\"\n", " Plots a stacked area plots for each type of test.\n", "\n", " Args:\n", " rst: Split test simulation class.\n", " reg: Epsilon-greedy MAB test simulation class.\n", " rts: Thompson sampling test simulation class.\n", " \"\"\"\n", " stacked_plot(rst.df_bids,\n", " title='A/B Test Bandit Resources Allocation',\n", " x_label='Batch',\n", " y_label='Bandit Allocation (%)')\n", "\n", " stacked_plot(reg.df_bids,\n", " title='Epsilon Greedy Bandit Resources Allocation',\n", " x_label='Batch',\n", " y_label='Bandit Allocation (%)')\n", "\n", " stacked_plot(rts.df_bids,\n", " title='Thompson Sampling Bandit Resources Allocation',\n", " x_label='Batch',\n", " y_label='Bandit Allocation (%)')\n", "\n", "\n", "def plot_gain(rst: SplitTestRunner, reg: EpsilonGreedyRunner, rts: ThompsonSamplingRunner):\n", " \"\"\"\n", " Plots the returns of each kind of test over the batches it ran.\n", "\n", " Args:\n", " rst: Split test simulation class.\n", " reg: Epsilon-greedy MAB test simulation class.\n", " rts: Thompson sampling test simulation class.\n", " \"\"\"\n", " rst_gain = rst.df_clicks.sum(axis=1)\n", " reg_gain = reg.df_clicks.sum(axis=1)\n", " rts_gain = rts.df_clicks.sum(axis=1)\n", " df_gains = pd.concat([rst_gain, reg_gain, rts_gain], axis=1)\n", " df_gains.rename(columns={0: 'Split Test', 1: 'Epsilon Greedy MAB', 2: 'Thompson Sampling'}, inplace=True)\n", " df_gains.plot(figsize=(12,6))" ], "execution_count": 4, "outputs": [] }, { "cell_type": "code", "metadata": { "id": "uYNw6wzduKCk" }, "source": [ "def z_calc(p1: float, p2: float, n1: int, n2: int) -> float:\n", " \"\"\"\n", " Calculates the z value for the difference of two sample means.\n", "\n", " Args:\n", " p1: Mean of first sample.\n", " p2: Mean of second sample.\n", " n1: Sample size of the first sample.\n", " n2: Sample size of the second sample.\n", " Returns:\n", " The calculated z value.\n", " \"\"\"\n", " p_star = (p1*n1 + p2*n2) / (n1 + n2)\n", " return (p2 - p1) / math.sqrt(p_star*(1 - p_star)*((1.0 / n1) + (1.0 / n2)))\n", "\n", "\n", "def sample_required(p1: float, p2: float, alpha: float=0.01) -> int:\n", " \"\"\"\n", " Calculates the sample size needed to provide a test power of (1-alpha)\n", " in which we are testing h0: p2-p1==0.\n", "\n", " Args:\n", " p1: Mean of first sample.\n", " p2: Mean of second sample.\n", " alpha: Type one error.\n", " Returns:\n", " The calculated sample size.\n", " \"\"\"\n", " n = 1\n", " while True:\n", " z = z_calc(p1, p2, n1=n, n2=n)\n", " p = 1 - stats.norm.cdf(z)\n", " if p < alpha:\n", " break\n", " n += 1\n", " return n\n", "\n", "\n", "def closest_pair(bandits: List[float]) -> (float, float):\n", " \"\"\"\n", " Finds the two bandits that have the closest average return\n", " and returns their returns.\n", "\n", " Args:\n", " bandits: list of average bandit returns.\n", " Returns:\n", " The average return of the two bandits that are the most\n", " similar.\n", " \"\"\"\n", " bandits.sort()\n", " min_diff = float(\"inf\")\n", " p1 = -1\n", " p2 = -1\n", " for i in range(len(bandits)-1):\n", " if bandits[i+1] - bandits[i] < min_diff:\n", " p1 = bandits[i]\n", " p2 = bandits[i+1]\n", " min_diff = p2 - p1\n", " return p1, p2\n", "\n", "\n", "def get_minimum_sample(bandits: List[float], alpha: float=0.01) -> int:\n", " \"\"\"\n", " Gets the minimum sample size required to provide a test power of\n", " (1-alpha/len(bandits)), this includes the p-value Bonferroni correction.\n", "\n", " Args:\n", " bandits: list of average bandit returns.\n", " alpha: Type one error.\n", " Returns:\n", " Needed sample size.\n", " \"\"\"\n", " p1, p2 = closest_pair(bandits)\n", " return sample_required(p1, p2, alpha/len(bandits))\n", "\n", "\n", "def get_number_batches(examples_needed: int, batch_size: int) -> int:\n", " \"\"\"\n", " Gets the number of batches based on the number of needed examples\n", " and provided batch size.\n", "\n", " Args:\n", " examples_needed: Total number of examples needed.\n", " batch_size: Number of examples per batch.\n", " Returns:\n", " The number of batches.\n", " \"\"\"\n", " return math.ceil(examples_needed / batch_size)\n", "\n", "\n", "def simulate(bandits: List[float], alpha: float=0.001, batch_size: int=5000, simulations: int=1000, epsilon: float=0.1, sample_size: int=1000) -> (SplitTestRunner, EpsilonGreedyRunner, ThompsonSamplingRunner):\n", " \"\"\"\n", " Runs simulations for split tests, Epsilon-greedy multi-armed bandits\n", " and Thompson sampling based on the provided parameters.\n", "\n", " Args:\n", " bandits: list of average bandit returns.\n", " alpha: Type one error.\n", " batch_size: Number of examples per batch.\n", " simulations: Number of simaltions per test type.\n", " epsilon: percentage of exploration in epsilon-greedy MAB\n", " sample_size: sample size per bandit for each Thompson sampling batch\n", " Returns:\n", " The classes for each type of test.\n", " \"\"\"\n", " examples_needed = get_minimum_sample(bandits, alpha)\n", " batches = get_number_batches(examples_needed, batch_size)\n", "\n", " rst = SplitTestRunner(bandits,\n", " batch_size=batch_size,\n", " batches=batches,\n", " simulations=simulations)\n", "\n", " reg = EpsilonGreedyRunner(bandits,\n", " epsilon=epsilon, \n", " batch_size=batch_size,\n", " batches=batches,\n", " simulations=simulations)\n", "\n", " rts = ThompsonSamplingRunner(bandits,\n", " alpha_priors=None,\n", " beta_priors=None,\n", " sample_size=sample_size,\n", " batch_size=batch_size,\n", " batches=batches,\n", " simulations=simulations)\n", "\n", " rst.run()\n", " reg.run()\n", " rts.run()\n", " return rst, reg, rts\n", "\n", "\n", "def run_simulations(bandits: List[float], alpha: float=0.001, batch_size: int=1000,\n", " simulations: int=1000, epsilon: float=0.1, sample_size: int=1000):\n", " \"\"\"\n", " Starts the simulation process, gets the results and makes plots.\n", "\n", " Args:\n", " bandits: list of average bandit returns.\n", " alpha: Type one error.\n", " batch_size: Number of examples per batch.\n", " simulations: Number of simaltions per test type.\n", " epsilon: percentage of exploration in epsilon-greedy MAB\n", " sample_size: sample size per bandit for each Thompson sampling batch\n", " \"\"\"\n", " rst, reg, rts = simulate(bandits=bandits,\n", " alpha=alpha,\n", " batch_size=batch_size,\n", " simulations=simulations,\n", " epsilon=epsilon,\n", " sample_size=sample_size)\n", "\n", " plot_stacked_plots(rst=rst,\n", " reg=reg,\n", " rts=rts)\n", "\n", " plot_gain(rst=rst,\n", " reg=reg,\n", " rts=rts)\n", "\n", "\n", "def simulate_ts(bandits: List[float], alpha_priors: List[float], beta_priors: List[float], batch_size: int=5000, simulations: int=1000, sample_size: int=1000):\n", " batches = 700\n", "\n", " rts = ThompsonSamplingRunner(bandits,\n", " alpha_priors=None,\n", " beta_priors=None,\n", " sample_size=sample_size,\n", " batch_size=batch_size,\n", " batches=batches,\n", " simulations=simulations)\n", " \n", " rts.run()\n", " \n", " stacked_plot(rts.df_bids,\n", " title='Thompson Sampling Resources Allocation',\n", " x_label='Batch',\n", " y_label='Bandit Allocation (%)')\n", " return rts.df_bids, rts.df_clicks" ], "execution_count": 9, "outputs": [] }, { "cell_type": "code", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "CGlVHb7cyMDR", "outputId": "1f8fcbce-b670-488d-889f-5d625afa7c56" }, "source": [ "bandit_returns = [.001, .004, .0042, 0, 0.006]\n", "alpha = 0.01\n", "batch_size = 5000\n", "simulations = 100\n", "epsilon = 0.1\n", "sample_size = 1000\n", "\n", "run_simulations(bandits=bandit_returns,\n", " alpha=alpha,\n", " batch_size=batch_size,\n", " simulations=simulations,\n", " epsilon=epsilon,\n", " sample_size=sample_size)" ], "execution_count": 6, "outputs": [ { "output_type": "display_data", "data": { "image/png": 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\n", 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\n", 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "tags": [], "needs_background": "light" } } ] }, { "cell_type": "code", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 404 }, "id": "PAngKsXKygwc", "outputId": "49ad737d-7d40-43a4-8026-130a2ab60b3a" }, "source": [ "bandit_returns = [.006, .004, .0041, 0, 0.0062]\n", "alpha_priors = [1., 1., 1., 1., 1.]\n", "beta_priors = [1., 1., 1., 1., 1.]\n", "batch_size = 5000\n", "simulations = 2\n", "sample_size = 1000\n", "\n", "b, c = simulate_ts(bandits=bandit_returns,\n", " alpha_priors=alpha_priors,\n", " beta_priors=beta_priors,\n", " batch_size=batch_size,\n", " simulations=simulations,\n", " sample_size=sample_size)" ], "execution_count": 10, "outputs": [ { "output_type": "display_data", "data": { "image/png": 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\n", 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" ] }, "metadata": { "tags": [], "needs_background": "light" } } ] }, { "cell_type": "code", "metadata": { "id": "cLCc2RKXyv0l", "colab": { "base_uri": "https://localhost:8080/", "height": 404 }, "outputId": "d3b28b82-6276-41d7-8710-7ea384c7a8f8" }, "source": [ "bandit_returns = [.006, .004, .0041, 0, 0.0058]\n", "alpha_priors = [1., 1., 1., 1., 1.]\n", "beta_priors = [1., 1., 1., 1., 1.]\n", "batch_size = 5000\n", "simulations = 2\n", "sample_size = 1000\n", "\n", "b, c = simulate_ts(bandits=bandit_returns,\n", " alpha_priors=alpha_priors,\n", " beta_priors=beta_priors,\n", " batch_size=batch_size,\n", " simulations=simulations,\n", " sample_size=sample_size)" ], "execution_count": 11, "outputs": [ { "output_type": "display_data", "data": { "image/png": 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\n", 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