{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Lab 2-4: Monte Carlo Tests & Random Numbers\n", "\n", "## Generating Random Numbers from a Given Probability Distribution" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Given any distribution for which we have a CDF available as a closed form expression, or simple lookup table (made when we create an empirical CDF), we can use the following approach to generate random numbers from that distribution.\n", "\n", "A basic approach for generating a sample of n random numbers from a desired probability distribution:\n", "\n", "1. Generate n random numbers from a uniform distribution on the interval [0,1]. (e.g. by using `np.random.uniform`) Recall that a CDF always ranges from 0 to 1 for a set of numbers, this first set of numbers we've generated from a uniform distribution are quantile values.\n", "\n", "2. Map the quantile values we just generated to the quantile value from the CDF of the desired distribution. (e.g. as a lookup table, or with a function like [`np.quantile`](https://numpy.org/doc/stable/reference/generated/numpy.quantile.html#numpy.quantile))\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Start by importing the python libraries we'll need, and load our data file for the Skykomish river annual peak flow values." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import scipy.stats as st\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.8/site-packages/openpyxl/worksheet/_reader.py:312: UserWarning: Unknown extension is not supported and will be removed\n", " warn(msg)\n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
date of peakwater yearpeak value (cfs)gage_ht (feet)
01928-10-0919291880010.55
11930-02-0519301580010.44
21931-01-2819313510014.08
\n", "
" ], "text/plain": [ " date of peak water year peak value (cfs) gage_ht (feet)\n", "0 1928-10-09 1929 18800 10.55\n", "1 1930-02-05 1930 15800 10.44\n", "2 1931-01-28 1931 35100 14.08" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "skykomish_data_file = '../data/Skykomish_peak_flow_12134500_skykomish_river_near_gold_bar.xlsx'\n", "skykomish_data = pd.read_excel(skykomish_data_file)\n", "# preview the dataframe\n", "skykomish_data.head(3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Divide the data into the early period (before 1975) and late period (after and including 1975)." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "skykomish_before = skykomish_data[ skykomish_data['water year'] < 1975 ] \n", "skykomish_after = skykomish_data[ skykomish_data['water year'] >= 1975 ] " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Define our cunnane plotting functions that work with our pandas dataframes, or generic 1d numpy arrays or lists." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "### Method 1\n", "# This function requires that the input is a pandas dataframe, with column names, and an integer index\n", "# It returns a copy of the dataframe with an extra column added that has the Cunnane plotting positions\n", "def cunnane_quantile(df, column_name):\n", " '''This function will compute the Cunnane plotting position for the values in a column of a dataframe.\n", " It requres a pandas dataframe, and the column name of interest (a text string) as inputs.\n", " The output is a new dataframe, ranked (sorted) with an extra column with the plotting position.\n", " [Steven Pestana, spestana@uw.edu, Oct. 2020]'''\n", " \n", " # Rank all our values\n", " ranked_df = df.sort_values(by=[column_name]).reset_index()\n", " \n", " # Calculate the Cunnane plotting position\n", " ranked_df['cunnane_plotting_position'] = ((ranked_df.index + 1) - (2/5)) / (ranked_df[column_name].count() + (1/5))\n", " \n", " return ranked_df\n", "\n", "### Method 2\n", "# This function should be able to accept any one-dimensional numpy array or list, of numbers\n", "# It returns two numpy arrays, one of the sorted numbers, the other of the plotting position\n", "def cunnane_quantile_array(numbers):\n", " '''This function also computes the Cunnane plotting position given an array or list of numbers (rather than a pandas dataframe).\n", " It has two outputs, first the sorted numbers, second the Cunnane plotting position for each of those numbers.\n", " [Steven Pestana, spestana@uw.edu, Oct. 2020]'''\n", " \n", " # 1) sort the data, using the numpy sort function (np.sort())\n", " sorted_numbers = np.sort(numbers)\n", " \n", " # length of the list of numbers\n", " n = len(sorted_numbers) \n", " \n", " # make an empty array, of the same length. below we will add the plotting position values to this array\n", " cunnane_plotting_position = np.empty(n)\n", " \n", " # 2) compute the Cunnane plotting position for each number, using a for loop and the enumerate function\n", " for rank, number in enumerate(sorted_numbers):\n", " cunnane_plotting_position[rank] = ( (rank+1) - (2/5) ) / ( n + (1/5) )\n", " \n", " return sorted_numbers, cunnane_plotting_position" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create the empirical CDFs with the Cunnane plotting position for our before and after 1975 datasets." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# Use the cunnane quantile function for before 1975\n", "skykomish_before_b = cunnane_quantile(skykomish_before, 'peak value (cfs)')\n", "\n", "# Use the cunnane quantile function for after 1975\n", "skykomish_after_a = cunnane_quantile(skykomish_after, 'peak value (cfs)')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot the CDFs together." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(8,6))\n", "\n", "# Empirical CDF, Before 1975\n", "ax.plot(skykomish_before_b['peak value (cfs)'], skykomish_before_b['cunnane_plotting_position'], \n", " color='tab:blue', linestyle='-', label='Empirical CDF, Before 1975')\n", "\n", "# Empirical CDF, After 1975\n", "ax.plot(skykomish_after_a['peak value (cfs)'], skykomish_after_a['cunnane_plotting_position'], \n", " color='tab:orange', linestyle='--', label='Empirical CDF, After 1975')\n", "\n", "# Add legend and labels\n", "ax.legend()\n", "ax.set_ylabel('Cumulative Probability')\n", "ax.set_xlabel('Peak Flow (cfs)')\n", "ax.set_title('Skykomish River, Annual Peak Streamflow CDF');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "\n", "**Step 1**: Generate n random numbers from a uniform distribution on the interval [0,1]. (e.g. by using `np.random.uniform`). These are quantile values." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# we want to use the same size size, or length, of the peak flow dataset before 1975\n", "size = len(skykomish_before_b['peak value (cfs)']) \n", "\n", "# generate the random quantile values\n", "random_quantiles = np.random.uniform(0,1,size)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Step 2**: Map the randomly generated quantile values to the quantile values from the empirical CDF of the \"before 1975\" data. We can use [`np.quantile`](https://numpy.org/doc/stable/reference/generated/numpy.quantile.html#numpy.quantile) here.\n", "\n", "This generates new \"peak flow\" values, drawn from the empirical CDF." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "random_peak_flows = np.quantile(skykomish_before['peak value (cfs)'].values, random_quantiles)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Step 3**: Now make a CDF from our generated random peak flow data." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "random_peak_flows_sorted, random_peak_flows_quantiles = cunnane_quantile_array(random_peak_flows)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the results to visualize what we just did:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(8,6))\n", "\n", "# Empirical CDF, Before 1975\n", "ax.plot(skykomish_before_b['peak value (cfs)'], skykomish_before_b['cunnane_plotting_position'], \n", " color='tab:blue', linestyle='-', marker='o', label='Original Points Defining Empirical CDF')\n", "\n", "\n", "ax.plot(random_peak_flows_sorted,random_peak_flows_quantiles,'kx--', label='Randomly Generated from Empirical CDF')\n", "\n", "# Add legend and labels\n", "ax.legend()\n", "ax.set_ylabel('Cumulative Probability')\n", "ax.set_xlabel('Peak Flow (cfs)')\n", "ax.set_title('Skykomish River, Annual Peak Streamflow (before 1975) CDF\\nAnd Random Peak Streamflows Generated from CDF');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also plot the original histogram of the before 1975 data, and our randomly generated values from the CDF:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Plot histograms\n", "\n", "fig, [ax1, ax2] = plt.subplots(nrows=1, ncols=2, figsize=(15,3))\n", "nbins = 15\n", "\n", "ax1.hist(skykomish_before_b['peak value (cfs)'].values, nbins, ec=\"black\")\n", "ax1.set_title('Original Peak Flow Data')\n", "ax1.set_xlabel('Peak Flows (cfs)')\n", "ax1.set_ylabel('Count')\n", "ax1.ticklabel_format(axis='x', style='sci', scilimits=(0,0))\n", " \n", " \n", "ax2.hist(random_peak_flows, nbins, ec=\"black\")\n", "ax2.set_title('Random Peak Flows, Generated from CDF')\n", "ax2.set_xlabel('Peak Flow (cfs)')\n", "ax2.set_ylabel('Count')\n", "ax2.ticklabel_format(axis='x', style='sci', scilimits=(0,0))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How do the shapes of the two distributions compare?\n", "\n", "What are the mean and standard deviation of these two samples (the original sample, and our randomly generated sample)?" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Original sample:\n", "\tmean = 40124.0\n", "\tstd = 19582.0\n", "\n", "Generated sample:\n", "\tmean = 40497.0\n", "\tstd = 17353.0\n" ] } ], "source": [ "original_sample_mean = skykomish_before_b['peak value (cfs)'].mean()\n", "original_sample_std = skykomish_before_b['peak value (cfs)'].std()\n", "print(\"Original sample:\\n\\tmean = {m}\\n\\tstd = {s}\".format(m=np.round(original_sample_mean,0), s=np.round(original_sample_std,0)))\n", "\n", "generated_sample_mean = random_peak_flows.mean()\n", "generated_sample_std = random_peak_flows.std()\n", "print(\"\\nGenerated sample:\\n\\tmean = {m}\\n\\tstd = {s}\".format(m=np.round(generated_sample_mean,0), s=np.round(generated_sample_std,0)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Monte Carlo Tests\n", "\n", "We can use these steps to generate 100s of random samples from the empirical CDF. This is like pretending that we have many more measurements than were actually taken. By looking at a large collection of random samples from the empirical CDF, we can then compare their mean and standard deviation to that of the after-1975 period, to determine the liklihood that the after-1975 peak flow values could have come from the same underlying \"true\" distribution." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Generate 500 random samples (repeat Step 1 500 times). **Step 1**: Generate n random numbers from a uniform distribution on the interval [0,1]. (e.g. by using `np.random.uniform`). These are quantile values. Use n = the length of the after-1975 dataset, and assume they come from the Empirical CDF of the pre-1975 dataset." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(45, 500)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# we want to use the same size size, or length, of the peak flow dataset after 1975,\n", "# but we also want to generate this 500 times, so we can specify that we want a 2D \"size\" of (x, y)\n", "# where x is the length of the dataset, and y is the number of times we want to make a new sample\n", "size = (len(skykomish_after_a['peak value (cfs)']), 500)\n", "\n", "# generate the random quantile values\n", "random_quantiles = np.random.uniform(0,1,size)\n", "\n", "# we can see the shape of the array we just made is 35 randomly generated numbers, 500 times\n", "random_quantiles.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "(Repeat 500 times) **Step 2**: Map the randomly generated quantile values to the quantile values from the empirical CDF of the \"before 1975\" data. We can use [`np.quantile`](https://numpy.org/doc/stable/reference/generated/numpy.quantile.html#numpy.quantile) here. This generates new \"peak flow\" values, drawn from the empirical CDF.\n", "\n", "Then also create a new CDF for each of the 500 samples." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "# Create empty placeholder arraya of the same shape as the random quantiles\n", "random_peak_flows = np.empty(random_quantiles.shape)\n", "random_peak_flows_sorted = np.empty(random_quantiles.shape)\n", "random_peak_flows_quantiles = np.empty(random_quantiles.shape)\n", "\n", "# For each of the 500 samples...\n", "for i in range(random_quantiles.shape[1]):\n", " random_peak_flows[:,i] = np.quantile(skykomish_before['peak value (cfs)'].values, random_quantiles[:,i])\n", " random_peak_flows_sorted[:,i], random_peak_flows_quantiles[:,i] = cunnane_quantile_array(random_peak_flows[:,i])" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(8,6))\n", "\n", "# All the randomly generated samples\n", "plt.plot(random_peak_flows_sorted,random_peak_flows_quantiles, alpha=0.1, color='grey');\n", "\n", "# Empirical CDF, Before 1975\n", "ax.plot(skykomish_before_b['peak value (cfs)'], skykomish_before_b['cunnane_plotting_position'], \n", " color='tab:blue', linestyle='-', marker='o')\n", "\n", "# Empirical CDF, After 1975\n", "ax.plot(skykomish_after_a['peak value (cfs)'], skykomish_after_a['cunnane_plotting_position'], \n", " color='tab:orange', linestyle='--', label='Empirical CDF, After 1975')\n", "\n", "\n", "# Add custom legend\n", "from matplotlib.lines import Line2D\n", "legend_elements = [Line2D([0], [0], color='grey', lw=1, label='500 x Randomly Generated from Before-1975 Empirical CDF'),\n", " Line2D([0], [0], color='tab:blue', lw=1, linestyle='-', marker='o', label='Before-1975 Empirical CDF'),\n", " Line2D([0], [0], color='tab:orange', linestyle='--', lw=1, label='After-1975 Empirical CDF'),]\n", "\n", "# Create the figure\n", "ax.legend(handles=legend_elements, loc='lower right')\n", "\n", "# Add labels\n", "ax.set_ylabel('Cumulative Probability')\n", "ax.set_xlabel('Peak Flow (cfs)')\n", "ax.set_title('Skykomish River, Annual Peak Streamflow (before 1975) CDF\\nAnd Random Peak Streamflows Generated from CDF');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In other words, we're interested in knowing how likely that the After-1975 sample came from the same distribution as the Before-1975 sample. We can use our randomly generated samples to represent the range of expected mean values we'd get from a sample that matches the Before-1975 CDF. \n", "\n", "(Does our orange line CDF, after-1975 come from the same underlying population CDF as represented by the blue line before-1975, and grey line random samples?)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Compute the means and standard deviations of each of the 500 random samples:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "# Using the numpy.mean and numpy.std functions, we can specify which axis we want to compute the mean and standard deviation along. \n", "# Here we choose the 0th axis, so that we compute across each of the 500 \"rows\" of data, which should leave us with 500 values\n", "random_peak_flows_means = random_peak_flows.mean(axis=0)\n", "random_peak_flows_stds = random_peak_flows.std(axis=0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Testing for a change in the mean\n", "\n", "Now, using all these means, determine the mean peak flow value above which only 5% of a random set of numbers from the basic distribution would fall into.\n", "\n", "* Take the 500 values we just calculated, and use the Cunnane-quantile method to plot them on a CDF.\n", "* Then, look up what mean value corresponds to the 0.95 value on the CDF.\n", "* Finally, see how the mean of the After-1975 period compares to the 0.95 quantile value.\n" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# Create a CDF of our means\n", "random_peak_flows_means_sorted, random_peak_flows_means_quantiles = cunnane_quantile_array(random_peak_flows_means)\n", "\n", "# Find the 95% quantile value\n", "q95 = np.quantile(random_peak_flows_means_sorted, 0.95)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Create a CDF plot\n", "fig, ax = plt.subplots(figsize=(8,6))\n", "\n", "# CDF of means from randomly generated samples\n", "ax.plot(random_peak_flows_means_sorted, random_peak_flows_means_quantiles, \n", " color='tab:blue', linestyle='-', label='CDF of Mean Peak Flow Values,\\nbased on the Pre-1975 Distribution')\n", "\n", "# Plot a line at the 95% value\n", "ax.axhline(0.95,color='red',label='95%')\n", "ax.plot(q95,0.95,linestyle='none',marker='o',color='k')\n", "ax.text(q95-6000, 0.96, '{} cfs'.format(np.round(q95,1)), fontsize=15, color='k')\n", "\n", "# Plot a line at the mean of the After-1975 value, is it higher or lower than the 95% quantile?\n", "ax.axvline(skykomish_after_a['peak value (cfs)'].mean(),color='orange',linestyle='--',label='After-1975 Mean Peak Flow')\n", "ax.text(skykomish_after_a['peak value (cfs)'].mean()-6000, 0.5, '{} cfs'.format(np.round(skykomish_after_a['peak value (cfs)'].mean(),1)), fontsize=15, color='k')\n", "\n", "ax.set_xlabel('Mean Annual Peak Flow (cfs)')\n", "ax.set_ylabel('Cumulative Probability \\n (or Probability of Non-Exceedance)')\n", "ax.set_title('Mean Peak Flows drawn from Skykomish-based Distribution')\n", "ax.ticklabel_format(axis='x', style='sci', scilimits=(0,0))\n", "ax.legend(loc='lower right');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**What does this say about the annual peak flows of the After-1975 period and how it compares to the Before-1975 period?**\n", "\n", "By repeatedly generating samples from our empirical CDF, we are creating new datasets that are \"realistic\" in that they are values we *could* have reasonably measured.\n", "\n", "When we look at these 500 sets of numbers, we can see that there is only a 5% chance that the mean of 45 numbers drawn randomly from this specific distribution would be greater than ~45000 cfs.\n", "\n", "Therefore, if we had 45 observed values and calculated their mean, we would be 95% confident that a mean of this value or larger actually came from a different population distribution (with a larger mean than that of our original population distribution).\n", "\n", "---" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.10.10" } }, "nbformat": 4, "nbformat_minor": 4 }