{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Lab 5-1: Multiple Linear Regression\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We are going to try and improve upon our simple linear regression model from Lab 4-1 with the snow water equivalent (SWE) data (if you're interested, [read about SWE and snow pillows here](https://www.nrcs.usda.gov/wps/portal/nrcs/detail/null/?cid=nrcseprd1314833)). In Lab 4-1 we used SWE observations from Slide Canyon to predict SWE at Blue Canyon. In this lab we will use two explanatory variables, SWE at Slide Canyon and time, to try and predict SWE at Blue Canyon. We can also compare both of these to the quantile regression model from Lab 4-2." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import scipy.stats as stats\n", "from scipy.linalg import lstsq # for the multiple linear regression, we'll use the scipy linear algebra least-squares function\n", "from scipy.interpolate import interp1d # for quantile regression, we'll want this 1d interpolation function\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Load the csv file with snow water equivalent (SWE) measurements from two sites in California's Sierra Nevada. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "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", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
yearsBLC_maxSLI_max
019836882446
119841121471
219852161143
319861501085
4198794569
\n", "
" ], "text/plain": [ " years BLC_max SLI_max\n", "0 1983 688 2446\n", "1 1984 112 1471\n", "2 1985 216 1143\n", "3 1986 150 1085\n", "4 1987 94 569" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Read in a .csv file\n", "data = pd.read_csv('../data/pillows_example.csv')\n", "data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These data are annual maximum SWE values (mm) for the Blue Canyon (BLC), and Slide Canyon (SLI) measurement sites." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot the original SWE data for both sites." ] }, { "cell_type": "code", "execution_count": 3, "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=(10,5))\n", "\n", "data.plot(x='years', y='SLI_max', c='r', linestyle='-', linewidth=1, marker='x', ax=ax, label='Slide Canyon')\n", "data.plot(x='years', y='BLC_max', c='b', linestyle='-', linewidth=1, marker='.', ax=ax, label='Blue Canyon')\n", "\n", "ax.set_title('Timeline of Peak Snow Water Equivalent (SWE)', fontsize=15)\n", "ax.set_xlabel('Water Year', fontsize=12)\n", "ax.set_ylabel('Peak SWE (mm)', fontsize=12);\n", "plt.legend(loc=(0.2,-0.36), fontsize=12);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**What does the above plot show?** What you see above is a plot of the maximum value of snow water equivalent (SWE) measured at two snow pillows (these weigh the snow and convert that weight into the water content of the snow). These measurements of snow are not too far from each other geographically (both in the Sierra Nevada, California, although Slide Canyon is at a higher elevation and further south), and we might expect that more snow at one site woud correspond to more snow at the other site as well. We can check this by examining a regression between the data at the two sites." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "## Simple Linear Regression\n", "\n", "We'll start off by replicating our simple linear regression model from Lab 4-1. The first step to any regression or correlation analysis is to create a scatter plot of the data." ] }, { "cell_type": "code", "execution_count": 4, "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=(4,4))\n", "\n", "# Scatterplot\n", "data.plot.scatter(x='SLI_max', y='BLC_max', c='k', ax=ax);\n", "\n", "ax.set_xlabel('Slide Canyon max SWE (mm)')\n", "ax.set_ylabel('Blue Canyon max SWE (mm)');\n", "\n", "ax.set_xlim((0,3000))\n", "ax.set_ylim((0,1000));" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Linear regression**: Could we use SWE measurements at Slide Canyon to predict SWE at Blue Canyon?\n", "\n", "The plot above suggests that this is a borderline case for applying linear regression analysis. What rules of linear regression might we worry about here? ([*heteroscedasticity*](https://en.wikipedia.org/wiki/Heteroscedasticity))\n", "\n", "We will proceed with calculating the regression and then look at the residuals to get a better idea of whether this is the best approach." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we're using the [`scipy.stats.linregress()`](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.linregress.html) function to create a least-squares linear regression model." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# use the linear regression function\n", "B1, B0, rvalue, pvalue, sB1 = stats.linregress(data.SLI_max, data.BLC_max)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Plot the result." ] }, { "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=(4,4))\n", "\n", "# Scatterplot\n", "data.plot.scatter(x='SLI_max', y='BLC_max', c='k', ax=ax);\n", "\n", "# Create points for the regression line\n", "x_line = np.array([data.SLI_max.min(), data.SLI_max.max()]) # x coordinates from min and max values of SLI_max\n", "y_line = B1 * x_line + B0 # y coordinates using the slope and intercept from our linear regression\n", "\n", "# Plot the regression line\n", "ax.plot(x_line, y_line, '-r')\n", "\n", "ax.set_xlabel('Slide Canyon max SWE (mm)')\n", "ax.set_ylabel('Blue Canyon max SWE (mm)');\n", "\n", "ax.set_xlim((0,3000))\n", "ax.set_ylim((0,1000));" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Compute the linear regression at our original x data points." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "x = data.SLI_max\n", "y = B1 * x + B0" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Print out our linear regression parameter (slope and intercept), our correlation coefficient, standard error of the gradient. Then compute the standard error of the regression from the standard error of the gradient:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "B0 : 127.9143\n", "B1 : 0.1997\n", "R^2 : 0.181\n", "R : 0.425\n", "stderr of the gradient: 0.087\n", "stderr of the regression : 204.089\n" ] } ], "source": [ "print('B0 : {}'.format(np.round(B0,4)))\n", "print('B1 : {}'.format(np.round(B1,4)))\n", "print('R^2 : {}'.format(np.round(rvalue**2,3)))\n", "print('R : {}'.format(np.round(rvalue,3)))\n", "print('stderr of the gradient: {}'.format(np.round(sB1,3)))\n", "\n", "# Compute the SST for x\n", "sst_x = np.sum( (x - np.mean(x))**2 )\n", "\n", "# Compute the standard error\n", "stderr = sB1 * np.sqrt(sst_x)\n", "print('stderr of the regression : {}'.format(np.round(stderr,3)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Plot residuals**\n", "\n", "We should make a plot of the residuals (actual - predicted values). For a good linear fit, we hope that our residuals are small, don't have any trends or patterns themselves, want them to be normally distributed:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "residuals = data.BLC_max - y\n", "\n", "f, (ax1, ax2) = plt.subplots(1,2,figsize=(9,4))\n", "\n", "ax1.plot(data.years,residuals)\n", "ax1.set_xlabel('years')\n", "ax1.set_ylabel('residuals (mm SWE)')\n", "\n", "ax2.hist(residuals)\n", "ax2.set_xlabel('residuals (mm SWE)')\n", "ax2.set_ylabel('count')\n", "\n", "f.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ideally our residuals should be \"random\" and normally distributed." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Another way of checking the validity of a model is to see if it predicts better than simply estimating the mean.**\n", "\n", "We can also make those plots and compare them to the plots above." ] }, { "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": [ "meanBC = np.mean(data.BLC_max)\n", "diffmean = data.BLC_max - meanBC\n", "\n", "f, (ax1, ax2) = plt.subplots(1,2,figsize=(9,4))\n", "\n", "ax1.plot(data.years,diffmean)\n", "ax1.set_xlabel('years')\n", "ax1.set_ylabel('difference from mean (mm SWE)')\n", "\n", "ax2.hist(diffmean)\n", "ax2.set_xlabel('difference from mean (mm SWE)')\n", "ax2.set_ylabel('count')\n", "\n", "f.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The trend with time is still apparent, and the histogram looks much less normally distributed. To me, this suggests that there is some value in our regression, but we should consider a multi-linear regression that also includes a trend with time. We will explore this more below." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Finally, make predictions with our linear model**\n", "\n", "Let's plot what the predictions of Blue Canyon SWE would look like if we were to use this linear model:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# Use our linear model to make predictions:\n", "BLC_linear_model = B1 * data.SLI_max + B0" ] }, { "cell_type": "code", "execution_count": 12, "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=(10,5))\n", "\n", "data.plot(x='years', y='SLI_max', c='r', linestyle='-', linewidth=1, marker='x', ax=ax, label='Slide Canyon')\n", "data.plot(x='years', y='BLC_max', c='b', linestyle='-', linewidth=1, marker='.', ax=ax, label='Blue Canyon')\n", "\n", "# Plot the predicted SWE at Blue Canyon\n", "ax.plot(data.years, BLC_linear_model, c='k', linestyle='--', linewidth=3, label='Blue Canyon Predicted with Linear Regression')\n", "\n", "ax.set_title('Timeline of Peak Snow Water Equivalent (SWE)', fontsize=15)\n", "ax.set_xlabel('Water Year', fontsize=12)\n", "ax.set_ylabel('Peak SWE (mm)', fontsize=12);\n", "plt.legend(loc=(0.2,-0.36), fontsize=12);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Is the slope of our linear regression significantly different from zero?** In Lab 4-3 we performed a hypothesis test on the slope of a linear regression to test the null hypothesis that the slope is zero. We can repeat that here too." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "t_critical = 2.0638985616280205\n", "t_test = 2.299628418171643\n" ] } ], "source": [ "# null hypothesis B1 = 0\n", "nullB1 = 0\n", "# our alpha for 95% confidence\n", "alpha = 0.05\n", "# length of the dataset\n", "n = len(x)\n", "# degrees of freedom\n", "dof = n - 2\n", "# find our critical t values for a two-tailed t-distribution (t-value for alpha/2 with n-2 degrees of freedom)\n", "t_critical = stats.t.ppf(1-alpha/2, dof)\n", "print('t_critical = {}'.format(t_critical))\n", "# compute the t-test statistic\n", "t_test = (B1 - nullB1) / sB1\n", "print('t_test = {}'.format(t_test))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "t-test > t-critical (at 95% confidence), therefore we can reject the null hypothesis and say that the slope is non-zero." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "## Multiple Linear Regression\n", "\n", "Now we are going to use both Slide Canyon SWE and time to try and predict Blue Canyon SWE.\n", "\n", "Start off by making scatter plots of our two independent variables (Slide Canyon SWE, time) and the dependent variable (Blue Canyon SWE)." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, [ax1, ax2] = plt.subplots(nrows=1, ncols=2, figsize=(9,4), tight_layout=True)\n", "\n", "# Scatterplot of SLI and BLC SWE\n", "data.plot.scatter(x='SLI_max', y='BLC_max', c='k', ax=ax1);\n", "ax1.set_xlabel('Slide Canyon max SWE (mm)')\n", "ax1.set_ylabel('Blue Canyon max SWE (mm)');\n", "ax1.set_xlim((0,3000))\n", "ax1.set_ylim((0,1000));\n", "\n", "# Scatterplot of Time and BLC SWE\n", "data.plot.scatter(x='years', y='BLC_max', c='k', ax=ax2);\n", "ax2.set_xlabel('Water Year')\n", "ax2.set_ylabel('Blue Canyon max SWE (mm)');\n", "ax2.set_ylim((0,1000));" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also use a function like the [scatterplot matrix](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.plotting.scatter_matrix.html) in pandas to plot each variable against each other variable (such as for visualizing correlation between all our variables). By default it's not the best looking plot, but there are plenty of options in the documentation to improve the appearance." ] }, { "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": [ "pd.plotting.scatter_matrix(data, figsize=(6,6), color='k', marker='.', alpha=1);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also calculate the correlation coefficient between the variables we plotted here to quantify (not only visualize) how well they are correlated. The below function, shared by a student taking this class, illustrates a way to calculate and plot this." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "def cross_corr(\n", " data_frame, # panda dataframe\n", " method:str='pearson', # type of correlation: either {'pearson', 'kendall', 'spearman'}\n", " title:str=None, # a string representing the title of your plot\n", " figsize:tuple=(10,10), # a tuple\n", " )->None:\n", " \n", " \"\"\"\n", " This function performs the cross correlation on all the variables in panda datafram\n", " and plots the data in the form of a matrix of cross correlation.\n", " \n", " Arguments:\n", " data_frame: a panda dataframe\n", " \n", " Optional arguments:\n", " method: default='pearson'; type of correlation: either {'pearson', 'kendall', 'spearman'}\n", " title: default=None; a string representing the tiltle of your plot\n", " figsize: default=(10,10); # a tuple\n", " \n", " This function adapted from Collins Owusu [https://github.com/collinsowusu]\n", " and modified by George Darkwah for the CEWA 465/565 - Data Analysis in Water Sciences class.\n", " \"\"\"\n", " import pandas as pd\n", " import seaborn\n", " import matplotlib.pyplot as plt\n", " import numpy as np\n", "\n", " colormap = plt.cm.RdBu\n", " # plt.figure(figsize=(6,6), dpi=300)\n", " plt.figure(figsize=figsize,)\n", " mask = np.zeros_like(data_frame.corr(method=method))\n", " mask[np.triu_indices_from(mask)]=True\n", " svm = seaborn.heatmap(data_frame.corr(method=method), mask=mask, linewidths=0.1, vmax=1.0, square=True, cmap=colormap, linecolor='white', annot=True, annot_kws={\"size\":12}).set(title=title)\n", " \n", " plt.show();" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "cross_corr(data);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The above shows what you can determine by eye from the prior plot. Blue Canyon SWE (BLC_max) is correlated with both time (year) and with Slide Canyon SWE (SLI_max), but Slide Canyon SWE is not correlated with time." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For the multiple linear regression, we'll use the scipy linear algebra least-squares function, [`scipy.linalg.lstsq()`](https://docs.scipy.org/doc/scipy/reference/generated/scipy.linalg.lstsq.html#scipy.linalg.lstsq)." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\u001b[0;31mSignature:\u001b[0m\n", "\u001b[0mlstsq\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mcond\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0moverwrite_a\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0moverwrite_b\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mcheck_finite\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m \u001b[0mlapack_driver\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", "\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mDocstring:\u001b[0m\n", "Compute least-squares solution to equation Ax = b.\n", "\n", "Compute a vector x such that the 2-norm ``|b - A x|`` is minimized.\n", "\n", "Parameters\n", "----------\n", "a : (M, N) array_like\n", " Left-hand side array\n", "b : (M,) or (M, K) array_like\n", " Right hand side array\n", "cond : float, optional\n", " Cutoff for 'small' singular values; used to determine effective\n", " rank of a. Singular values smaller than\n", " ``rcond * largest_singular_value`` are considered zero.\n", "overwrite_a : bool, optional\n", " Discard data in `a` (may enhance performance). Default is False.\n", "overwrite_b : bool, optional\n", " Discard data in `b` (may enhance performance). Default is False.\n", "check_finite : bool, optional\n", " Whether to check that the input matrices contain only finite numbers.\n", " Disabling may give a performance gain, but may result in problems\n", " (crashes, non-termination) if the inputs do contain infinities or NaNs.\n", "lapack_driver : str, optional\n", " Which LAPACK driver is used to solve the least-squares problem.\n", " Options are ``'gelsd'``, ``'gelsy'``, ``'gelss'``. Default\n", " (``'gelsd'``) is a good choice. However, ``'gelsy'`` can be slightly\n", " faster on many problems. ``'gelss'`` was used historically. It is\n", " generally slow but uses less memory.\n", "\n", " .. versionadded:: 0.17.0\n", "\n", "Returns\n", "-------\n", "x : (N,) or (N, K) ndarray\n", " Least-squares solution. Return shape matches shape of `b`.\n", "residues : (K,) ndarray or float\n", " Square of the 2-norm for each column in ``b - a x``, if ``M > N`` and\n", " ``ndim(A) == n`` (returns a scalar if b is 1-D). Otherwise a\n", " (0,)-shaped array is returned.\n", "rank : int\n", " Effective rank of `a`.\n", "s : (min(M, N),) ndarray or None\n", " Singular values of `a`. The condition number of a is\n", " ``abs(s[0] / s[-1])``.\n", "\n", "Raises\n", "------\n", "LinAlgError\n", " If computation does not converge.\n", "\n", "ValueError\n", " When parameters are not compatible.\n", "\n", "See Also\n", "--------\n", "scipy.optimize.nnls : linear least squares with non-negativity constraint\n", "\n", "Notes\n", "-----\n", "When ``'gelsy'`` is used as a driver, `residues` is set to a (0,)-shaped\n", "array and `s` is always ``None``.\n", "\n", "Examples\n", "--------\n", ">>> from scipy.linalg import lstsq\n", ">>> import matplotlib.pyplot as plt\n", "\n", "Suppose we have the following data:\n", "\n", ">>> x = np.array([1, 2.5, 3.5, 4, 5, 7, 8.5])\n", ">>> y = np.array([0.3, 1.1, 1.5, 2.0, 3.2, 6.6, 8.6])\n", "\n", "We want to fit a quadratic polynomial of the form ``y = a + b*x**2``\n", "to this data. We first form the \"design matrix\" M, with a constant\n", "column of 1s and a column containing ``x**2``:\n", "\n", ">>> M = x[:, np.newaxis]**[0, 2]\n", ">>> M\n", "array([[ 1. , 1. ],\n", " [ 1. , 6.25],\n", " [ 1. , 12.25],\n", " [ 1. , 16. ],\n", " [ 1. , 25. ],\n", " [ 1. , 49. ],\n", " [ 1. , 72.25]])\n", "\n", "We want to find the least-squares solution to ``M.dot(p) = y``,\n", "where ``p`` is a vector with length 2 that holds the parameters\n", "``a`` and ``b``.\n", "\n", ">>> p, res, rnk, s = lstsq(M, y)\n", ">>> p\n", "array([ 0.20925829, 0.12013861])\n", "\n", "Plot the data and the fitted curve.\n", "\n", ">>> plt.plot(x, y, 'o', label='data')\n", ">>> xx = np.linspace(0, 9, 101)\n", ">>> yy = p[0] + p[1]*xx**2\n", ">>> plt.plot(xx, yy, label='least squares fit, $y = a + bx^2$')\n", ">>> plt.xlabel('x')\n", ">>> plt.ylabel('y')\n", ">>> plt.legend(framealpha=1, shadow=True)\n", ">>> plt.grid(alpha=0.25)\n", ">>> plt.show()\n", "\u001b[0;31mFile:\u001b[0m /opt/conda/lib/python3.9/site-packages/scipy/linalg/basic.py\n", "\u001b[0;31mType:\u001b[0m function\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# check out the function's documentation\n", "lstsq?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that the [documentation for this function](https://docs.scipy.org/doc/scipy/reference/generated/scipy.linalg.lstsq.html#scipy.linalg.lstsq) states that it requires input of an array that includes vectors of all of the predictor variables we are considering.\n", "\n", "Below, we create an array made up of the maximum annual SWE at Slide Canyon and the year. We also need an array of ones (which allows for a constant term, the intercept, in the regression)." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(26, 3)\n", "(26,)\n" ] } ], "source": [ "years_array = np.linspace(1,data.years.size,data.years.size)\n", "\n", "# create the input array\n", "multi_input = np.array([ \n", " data.SLI_max, # SWE at slide canyon\n", " years_array, # instead of the actual year numbers, just use a count of years starting at 1\n", " np.ones_like(data.years) # array of ones so we allow a constant, y-intercept, value\n", " ]).T # Transform this array with \".T\" to swap rows and columns\n", "\n", "# Show the shapes of our two inputs to the lstsq function to make sure they have the same first dimension length\n", "print(multi_input.shape)\n", "print(data.BLC_max.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now use the lstsq function and print the resulting regression parameters." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 0.22156219 13.77959269 -83.33208798]\n" ] } ], "source": [ "B, _, _, _ = lstsq(multi_input, data.BLC_max) # I'm using \"_\" as a placeholder for the outputs I don't need\n", "print(B)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The values of B, above, show the coefficients we would assing to the Slide Canyon SWE (B[0]), the year (B[1]), and the constant offset (B[2]), in the order shown." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Make predictions with our linear model**\n", "\n", "Here we're using the [`.dot()`](https://numpy.org/doc/stable/reference/generated/numpy.dot.html) method to take the dot product between our input array and output regression coefficients." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "# Use our linear model to make predictions:\n", "BLC_multiple_linear_model = multi_input.dot(B)\n", "\n", "# We could also do it this way:\n", "#BLC_multiple_linear_model = B[0]*data.SLI_max + B[1]*years_array + B[2]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Plot residuals**\n", "\n", "We should make a plot of the residuals (actual - predicted values). For a good linear fit, we hope that our residuals are small, don't have any trends or patterns themselves, want them to be normally distributed.\n", "\n", "How do these compare to the residuals of the simple linear regression model?\n", "\n", "Generally, adding more predictors will always decrease the residual error in the region where the model is developed but may increase the error in a region outside of when it was developed. (To test this, it's best practice to keep some data separate from the regression model development and then test model performance there. You could take a subset of the data above, recalcuate the regression coefficients and then check your model prediction vs. observed for years outside of your original dataset to see if the mulitple regression actually improves your predictive capabilities.)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ml_residuals = data.BLC_max - BLC_multiple_linear_model\n", "\n", "f, (ax1, ax2) = plt.subplots(1,2,figsize=(9,4))\n", "\n", "ax1.plot(data.years,ml_residuals)\n", "ax1.set_xlabel('years')\n", "ax1.set_ylabel('residuals (mm SWE)')\n", "\n", "ax2.hist(ml_residuals)\n", "ax2.set_xlabel('residuals (mm SWE)')\n", "ax2.set_ylabel('count')\n", "\n", "f.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Now compare our simple regression model with our multi-regression model.** \n", "\n", "Plot the results from the two different regression methods. How and where are they different?" ] }, { "cell_type": "code", "execution_count": 23, "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=(10,5))\n", "\n", "# Original data\n", "data.plot(x='years', y='SLI_max', c='r', linestyle='-', linewidth=1, marker='x', ax=ax, label='Slide Canyon')\n", "data.plot(x='years', y='BLC_max', c='b', linestyle='-', linewidth=1, marker='.', ax=ax, label='Blue Canyon')\n", "\n", "# Plot the predicted SWE at Blue Canyon from the simple linear regression model\n", "ax.plot(data.years, BLC_linear_model, c='k', linestyle='--', linewidth=3, label='Blue Canyon Predicted with Simple Linear Regression')\n", "\n", "# Plot the predicted SWE at Blue Canyon from the multiple linear regression model\n", "ax.plot(data.years, BLC_multiple_linear_model, c='k', linestyle='-', linewidth=3, label='Blue Canyon Predicted with Multiple Linear Regression')\n", "\n", "ax.set_title('Timeline of Peak Snow Water Equivalent (SWE)', fontsize=15)\n", "ax.set_xlabel('Water Year', fontsize=12)\n", "ax.set_ylabel('Peak SWE (mm)', fontsize=12);\n", "plt.legend(loc=(0.2,-0.45), fontsize=12);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "---\n", "\n", "## Quantile Regression\n", "\n", "For completeness, we can also perform a quantile regression like in Lab 4-2, then compare all three types of regression models." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create empirical CDFs for both SWE data sets" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "quantiles = np.linspace(0,1,100)\n", "\n", "# This is our empirical cdf of the Slide Canyon data, which also includes values down to 0 and up to 1.\n", "SLI_ordered = stats.mstats.mquantiles(data.SLI_max, quantiles)\n", "\n", "# This is our empirical cdf of the Blue Canyon data, which also includes values down to 0 and up to 1.\n", "BLC_ordered = stats.mstats.mquantiles(data.BLC_max, quantiles)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use the CDFs to \"look up\" SWE from Slide Canyon to predict SWE in Blue Canyon" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "# Create our interpolation function for looking up a quantile given a value of SWE at Slide Canyon\n", "f_SLI = interp1d(SLI_ordered, quantiles)\n", "# Create our interpolation function for looking up SWE at Blue Canyon given a quantile\n", "g_BLC = interp1d(quantiles, BLC_ordered)\n", "\n", "# Now, we can create a prediction for every value in the Slide Canyon dataset to come up with a matching prediction for the Blue Canyon dataset\n", "BLC_predicted=g_BLC( f_SLI( data.SLI_max ) )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Plot the results from all three regression models together**" ] }, { "cell_type": "code", "execution_count": 26, "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=(10,5))\n", "\n", "# Original data\n", "data.plot(x='years', y='SLI_max', c='r', linestyle='-', linewidth=1, marker='x', ax=ax, label='Slide Canyon')\n", "data.plot(x='years', y='BLC_max', c='b', linestyle='-', linewidth=1, marker='.', ax=ax, label='Blue Canyon')\n", "\n", "# Plot the predicted SWE at Blue Canyon from the simple linear regression model\n", "ax.plot(data.years, BLC_linear_model, c='k', linestyle='--', linewidth=3, label='Blue Canyon Predicted with Simple Linear Regression')\n", "\n", "# Plot the predicted SWE at Blue Canyon from the multiple linear regression model\n", "ax.plot(data.years, BLC_multiple_linear_model, c='k', linestyle='-', linewidth=3, label='Blue Canyon Predicted with Multiple Linear Regression')\n", "\n", "# Predicted with linear regression between Slide Canyon and Blue Canyon\n", "plt.plot(data.years,BLC_predicted, c='k', linestyle=':', linewidth=3, label='Blue Canyon Predicted from Quantile Regression')\n", "\n", "ax.set_title('Timeline of Peak Snow Water Equivalent (SWE)', fontsize=15)\n", "ax.set_xlabel('Water Year', fontsize=12)\n", "ax.set_ylabel('Peak SWE (mm)', fontsize=12);\n", "plt.legend(loc=(0.2,-0.5), fontsize=12);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Which of these models do you think would be the most appropriate here? What tools could you use to decide?" ] }, { "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": "3.9.7" } }, "nbformat": 4, "nbformat_minor": 4 }