{ "cells": [ { "cell_type": "raw", "metadata": {}, "source": [ "Content under Creative Commons Attribution license CC-BY 4.0, code under BSD 3-Clause License © 2017 L.A. Barba, N.C. Clementi" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Linear regression with real data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Earth temperature over time\n", "\n", "In this lesson, we will apply all that we've learned (and more) to analyze real data of Earth temperature over time.\n", "\n", "Is global temperature rising? How much? This is a question of burning importance in today's world!\n", "\n", "Data about global temperatures are available from several sources: NASA, the National Climatic Data Center (NCDC) and the University of East Anglia in the UK. Check out an article by the [University Corporation for Atmospheric Research](https://scied.ucar.edu/learning-zone/how-climate-works/why-earth-warming) (UCAR) for an in-depth discussion.\n", "\n", "The NASA Goddard Space Flight Center Scientific Visualization Studio is one of our sources of global climate data. They have produced animations showing a color map of the changing global surface **temperature anomalies** since 1880—see the updated [video with 2023 data](https://svs.gsfc.nasa.gov/5207/) on their website.\n", "\n", "The term [global temperature anomaly](https://www.ncdc.noaa.gov/monitoring-references/faq/anomalies.php) means the difference in temperature with respect to a reference value or a long-term average. It is a very useful way of looking at the problem and in many ways better than absolute temperature. For example, a winter month may be colder than average in Washington DC, and also in Miami, but the absolute temperatures will be different in both places.\n", "\n", "The YouTube video embedded below shows the global temperature anomaly from 1880 to 2022." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "image/jpeg": 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"text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from IPython.display import YouTubeVideo\n", "YouTubeVideo('LwRTw_7NNJs')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How would we go about understanding the _trends_ from the data on global temperature?\n", "\n", "The first step in analyzing unknown data is to generate some simple plots using **Matplotlib**. We are going to look at the temperature-anomaly history, contained in a file, and make our first plot to explore this data. \n", "\n", "We are going to smooth the data and then we'll fit a line to it to find a trend, plotting along the way to see how it all looks.\n", "\n", "Let's get started!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 1: Read a data file\n", "\n", "We obtained time-series data from the [NOAA](https://www.ncei.noaa.gov/access/monitoring/climate-at-a-glance/global/time-series) (National Oceanic and Atmospheric Administration) webpage. Feel free to play around with the webpage and analyze data on your own, but for now, let's make sure we're working with the same dataset.\n", "\n", "\n", "If you made a copy of the full set of files for this module, you will have a file named `land_global_temperature_anomaly-1850-2023.csv` in the `data` folder. This comma-separated data file shows the year on the first column, and averages of land temperature anomaly on the second column, between the years 1850 and 2023. We will load the file, then make an initial plot to see what it looks like.\n", "\n", "\n", "**Note:**\n", "\n", "If you downloaded this notebook alone, or are following along in your own notebook, you may not have the data file on the location we assume below. In that case, you can download the data if you add a code cell, and execute the following code in it:\n", "\n", "\n", "```Python\n", "from urllib.request import urlretrieve\n", "URL = 'http://go.gwu.edu/engcomp1data5'\n", "urlretrieve(URL, 'land_global_temperature_anomaly-1850-2023.csv')\n", "```\n", "
\n", "\n", "The data file will be downloaded to your working directory, and you will then need to remove the path information, i.e., the string `'../data/'`, from the definition of the variable `fname` below.\n", "\n", "Let's start by taking a peek at the data." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Global Land and Ocean December Temperature Anomalies\n", "Units: Degrees Celsius\n", "Base Period: 1901-2000\n", "Missing: -999\n", "Year,Anomaly\n", "1850,-0.07\n", "1851,-0.03\n", "1852,-0.09\n", "1853,-0.22\n", "1854,0.01\n" ] } ], "source": [ "# modify the path to the data file as needed\n", "!head ../data/land_global_temperature_anomaly-1850-2023.csv" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "One thing we notice right away is that a few lines in the file have some header information. Count the lines: including the column labels, five lines should be skipped if we want to load the numeric data into NumPy arrays.\n", "\n", "Next, import the fantastic NumPy library for array operations, and let the fun begin!" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import numpy" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To load our data from the file, we'll use the function [`numpy.loadtxt()`](https://numpy.org/doc/stable/reference/generated/numpy.loadtxt.html), which lets us immediately save the data into NumPy arrays. (We encourage you to read the documentation for details on how the function works.) Here, we'll save the data into the arrays `year` and `temp_anomaly`. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "fname = '../data/land_global_temperature_anomaly-1850-2023.csv'\n", "\n", "year, temp_anomaly = numpy.loadtxt(fname, delimiter=',', skiprows=5, unpack=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "_Exercise:_\n", "\n", "Inspect the data by printing a slice of`year` and `temp_anomaly`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 2: Plot the data\n", "\n", "Let's first load the **Matplotlib** module called `pyplot`, for making 2D plots. Remember that to get the plots inside the notebook, we use a special \"magic\" command, `%matplotlib inline`:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "from matplotlib import pyplot\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The `plot()` function of the `pyplot` module makes simple line plots. We avoid that stuff that appeared on top of the figure, that `Out[x]: [< ...>]` ugliness, by adding a semicolon at the end of the plotting command." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pyplot.plot(year, temp_anomaly);" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true, "jupyter": { "outputs_hidden": true } }, "source": [ "Now we have a line plot, but if you see this plot without any information you would not be able to figure out what kind of data it is! We need labels on the axes, a title and why not a better color, font and size of the ticks.\n", "\n", "*Publication quality* plots should always be your standard for plotting. \n", "How you present your data will allow others (and probably you in the future) to better understand your work. \n", "\n", "We can customize the style of our plots using parameters for the lines, text, font and other plot options. We set some style options that apply for all the plots in the current session with [`pyplot.rc()`](https://matplotlib.org/api/_as_gen/matplotlib.pyplot.rc.html)\n", "Here, we'll make the font of a specific type and size (serif and 16 points). You can also customize other parameters like line width, color, and so on (check out the documentation)." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "pyplot.rc('font', family='serif', size='16')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We'll redo the same plot, but now we'll add a few things to make it prettier and **publication quality**. We'll add a title, label the axes and, show a background grid. Study the commands below and look at the result!" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#You can set the size of the figure by doing:\n", "pyplot.figure(figsize=(10,5))\n", "\n", "#Plotting\n", "pyplot.plot(year, temp_anomaly, color='#2929a3', linestyle='-', linewidth=1) \n", "pyplot.title('Land global temperature anomalies. \\n')\n", "pyplot.xlabel('Year')\n", "pyplot.ylabel('Land temperature anomaly [°C]')\n", "pyplot.grid();" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true, "jupyter": { "outputs_hidden": true } }, "source": [ "Better, no? Feel free to play around with the parameters and see how the plot changes. There's nothing like trial and error to get the hang of it. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 3: Least-squares linear regression \n", "\n", "In order to have an idea of the general behavior of our data, we can find a smooth curve that (approximately) fits the points. We generally look for a curve that's simple (e.g., a polynomial), and does not reproduce the noise that's always present in experimental data. \n", "\n", "Let $f(x)$ be the function that we'll fit to the $n+1$ data points: $(x_i, y_i)$, $i = 0, 1, ... ,n$:\n", "\n", "$$ \n", " f(x) = f(x; a_0, a_1, ... , a_m) \n", "$$\n", "\n", "
\n", "\n", "The notation above means that $f$ is a function of $x$, with $m+1$ variable parameters $a_0, a_1, ... , a_m$, where $m < n$. We need to choose the form of $f(x)$ a priori, by inspecting the experimental data and knowing something about the phenomenon we've measured. Thus, curve fitting consists of two steps: \n", "\n", "1. Choosing the form of $f(x)$.\n", "2. Computing the parameters that will give us the \"best fit\" to the data. \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### What is the \"best\" fit to the data?\n", "\n", "When the noise in the data is limited to the $y$-coordinate, it's common to use a **least-squares fit**, which minimizes the function\n", "\n", "$$\n", "\\begin{align} \n", " S(a_0, a_1, ... , a_m) = \\sum_{i=0}^{n} [y_i - f(x_i)]^2 \n", "\\end{align} \n", "$$\n", "\n", "with respect to each $a_j$. \n", "Here, the terms $r_i = y_i - f(x_i)$ are called _residuals_: they are the discrepancy between the data and the fitting function at the $x_i$ values, as illustrated in the figure below.\n", "\n", "\"A" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We compute the parameters for the best fit by taking the derivative of $S$ with respect to the parameters and equating to zero, then solving the resulting equations:\n", "\n", "$$\n", "\\begin{align}\n", " \\frac{\\partial{S}}{\\partial{a_k}} = 0, \\quad k = 0, 1, ... , m.\n", "\\end{align}\n", "$$\n", "\n", "You may remember this from calculus, but if not, look at the figure below and imagine that the curve represents the function $S$ with respect to some parameter $a_k$. Visualize the slope of the tangent to the curve at several points, and you can see that when the slope is horizontal (zero) we've found the minimum of the function.\n", "\n", "\"A" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Take another look at the function $S$: what we want to minimize is the sum of the squares of the residuals. The equations in $(2)$ are generally nonlinear with respect to $a_k$ and might be difficult to solve. Therefore, the fitting function is commonly chosen as a linear combination of functions $f_j(x)$ with a simple form:\n", "\n", "$$\n", "\\begin{equation*}\n", " f(x) = a_0f_0(x) + a_1f_1(x) + ... + a_mf_m(x)\n", "\\end{equation*}\n", "$$\n", "\n", "resulting in equations (2) being linear. For a polynomial fitting function, we have have $f_0(x) = 1, \\; f_1(x) = x, \\; f_2(x) = x^2$, and so on. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Linear regression \n", "\n", "When we talk about linear regression we mean \"fitting a straight line to the data.\" Thus,\n", "\n", "$$\n", "\\begin{align}\n", " f(x) = a_0 + a_1x\n", "\\end{align}\n", "$$\n", "\n", "In this case, the function that we need to minimize is:\n", "\n", "$$\n", "\\begin{align}\n", " S(a_0, a_1) = \\sum_{i=0}^{n} [y_i - f(x_i)]^2 = \\sum_{i=0}^{n} (y_i - a_0 - a_1x_i)^2\n", "\\end{align} \n", "$$\n", "\n", "Equations $(2)$ become:\n", "\n", "$$\n", "\\begin{align}\n", " \\frac{\\partial{S}}{\\partial{a_0}} &= \\sum_{i=0}^{n} -2(y_i - a_0 - a_1x_i) = 2 \\left[ a_0(n+1) + a_1\\sum_{i=0}^{n} x_i - \\sum_{i=0}^{n} y_i \\right] = 0 \\\\\n", " \\frac{\\partial{S}}{\\partial{a_1}} &= \\sum_{i=0}^{n} -2(y_i - a_0 - a_1x_i)x_i = 2 \\left[ a_0\\sum_{i=0}^{n} x_i + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i \\right] = 0\n", "\\end{align} \n", "$$\n", "\n", "Let's divide both equations by $2(n+1)$ and rearrange term: the first equation gives an expression for $a_0$ as follows,\n", "\n", "$$\n", "\\begin{align}\n", " 2 \\left[ a_0(n+1) + a_1\\sum_{i=0}^{n} x_i - \\sum_{i=0}^{n} y_i \\right] &= 0 \\nonumber \\\\ \n", " \\frac{a_0(n+1)}{n+1} + a_1 \\frac{\\sum_{i=0}^{n} x_i}{n+1} - \\frac{\\sum_{i=0}^{n} y_i}{n+1} &= 0 \\\\\n", " a_0 &= \\bar{y} - a_1\\bar{x},\n", "\\end{align}\n", "$$\n", "\n", "where $\\bar{x} = \\frac{\\sum_{i=0}^{n} x_i}{n+1}$ and $\\bar{y} = \\frac{\\sum_{i=0}^{n} y_i}{n+1}$.\n", "\n", "Rearranging the second equation:\n", "\n", "$$\n", "\\begin{align}\n", " 2 \\left[ a_0\\sum_{i=0}^{n} x_i + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i \\right] &= 0 \\nonumber \\\\\n", " a_0\\sum_{i=0}^{n} x_i + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i &=0 \\\\\n", "\\end{align}\n", "$$\n", "\n", "Now we can replace the expression we found for $a_0$:\n", "\n", "$$\n", "\\begin{align*}\n", " (\\bar{y} - a_1\\bar{x})\\sum_{i=0}^{n} x_i + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i &= 0 \\\\ \n", "\\end{align*}\n", "$$\n", "\n", "Replacing the definitions of the mean values into the equation, \n", "\n", "$$\n", "\\begin{align*}\n", " \\left[\\frac{1}{n+1}\\sum_{i=0}^{n} y_i - \\frac{a_1}{n+1}\\sum_{i=0}^{n} x_i \\right]\\sum_{i=0}^{n} x_i + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i &= 0 \\\\ \n", " \\frac{1}{n+1}\\sum_{i=0}^{n} y_i \\sum_{i=0}^{n} x_i - \\frac{a_1}{n+1}\\sum_{i=0}^{n} x_i \\sum_{i=0}^{n} x_i + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i &= 0 \\\\ \n", "\\end{align*}\n", "$$\n", "\n", "Leaving everything in terms of $\\bar{x}$, \n", "\n", "$$\n", "\\begin{align*}\n", " \\sum_{i=0}^{n} y_i \\bar{x} - a_1\\sum_{i=0}^{n} x_i \\bar{x} + a_1\\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_iy_i = 0 \n", "\\end{align*}\n", "$$\n", "\n", "Grouping the terms that have $a_1$ on the left-hand side and the rest on the right-hand side:\n", "\n", "$$\n", "\\begin{align*}\n", " a_1\\left[ \\sum_{i=0}^{n} x_{i}^2 - \\sum_{i=0}^{n} x_i \\bar{x}\\right] &= \\sum_{i=0}^{n} x_iy_i - \\sum_{i=0}^{n} y_i \\bar{x} \\\\\n", " a_1 \\sum_{i=0}^{n} (x_{i}^2 - x_i \\bar{x}) &= \\sum_{i=0}^{n} (x_iy_i - y_i \\bar{x}) \\\\\n", " a_1 \\sum_{i=0}^{n} x_{i}(x_{i} -\\bar{x}) &= \\sum_{i=0}^{n} y_i(x_i - \\bar{x}) \n", "\\end{align*}\n", "$$\n", "\n", "Finally, we get that:\n", "\n", "$$\n", "\\begin{align}\n", " a_1 = \\frac{ \\sum_{i=0}^{n} y_{i} (x_i - \\bar{x})}{\\sum_{i=0}^{n} x_i (x_i - \\bar{x})}\n", "\\end{align}\n", "$$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Thus, the values for the two coefficients are found from the data with the following formulas:\n", "\n", "$$\n", "\\begin{align}\n", " a_1 = \\frac{ \\sum_{i=0}^{n} y_{i} (x_i - \\bar{x})}{\\sum_{i=0}^{n} x_i (x_i - \\bar{x})} \\quad , \\quad a_0 = \\bar{y} - a_1\\bar{x}\n", "\\end{align}\n", "$$\n", "\n", "_Exercise:_\n", "\n", "- On a piece of paper, write out the first few terms for the coefficient $a_1$, that is, expand the formula writing explicitly the terms for $i=1, 2, 3$j (or more)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Let's fit!\n", "\n", "Let's now fit a straight line through the temperature-anomaly data, to see the trend over time. We'll use least-squares linear regression to find the slope and intercept of a line \n", "\n", "$$y = a_1x+a_0$$\n", "\n", "that fits our data.\n", "\n", "In our case, the $x$-data corresponds to `year`, and the $y$-data is `temp_anomaly`. To calculate our coefficients with the formula above, we need the mean values of our data. Since we'll need to compute the mean for both data arrays, it might be useful to have a custom Python _function_ that computes the mean for any array, so we can reuse it.\n", "\n", "It is good coding practice to *avoid repeating* ourselves: we want to write code that is reusable, not only because it leads to less typing but also because it reduces errors. If you find yourself doing the same calculation multiple times, it's better to encapsulate it into a *function*. \n", "\n", "Remember the _key concept_ from [Lesson 1](http://go.gwu.edu/engcomp1lesson1): A function is a compact collection of code that executes some action on its arguments. \n", "\n", "Once *defined*, you can *call* a function as many times as you want. When we *call* a function, we execute all the code inside the function. The result of the execution depends on the *definition* of the function and on the values that are *passed* into it as *arguments*. Functions might or might not *return* values in their last operation. \n", "\n", "The syntax for defining custom Python functions is:\n", "\n", "```python\n", "def function_name(arg_1, arg_2, ...):\n", " '''\n", " docstring: description of the function\n", " '''\n", " \n", "```\n", "
\n", "\n", "The **docstring** of a function is a message from the programmer documenting what he or she built. Docstrings should be descriptive and concise. They are important because they explain (or remind) the intended use of the function to the users. You can later access the docstring of a function using the function `help()` and passing the name of the function. If you are in a notebook, you can also prepend a question mark `'?'` before the name of the function and run the cell to display the information of a function. \n", "\n", "Try it!" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\u001b[0;31mSignature:\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msep\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m' '\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'\\n'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflush\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\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", "Prints the values to a stream, or to sys.stdout by default.\n", "\n", "sep\n", " string inserted between values, default a space.\n", "end\n", " string appended after the last value, default a newline.\n", "file\n", " a file-like object (stream); defaults to the current sys.stdout.\n", "flush\n", " whether to forcibly flush the stream.\n", "\u001b[0;31mType:\u001b[0m builtin_function_or_method" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "?print" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using the `help` function instead:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on built-in function print in module builtins:\n", "\n", "print(*args, sep=' ', end='\\n', file=None, flush=False)\n", " Prints the values to a stream, or to sys.stdout by default.\n", " \n", " sep\n", " string inserted between values, default a space.\n", " end\n", " string appended after the last value, default a newline.\n", " file\n", " a file-like object (stream); defaults to the current sys.stdout.\n", " flush\n", " whether to forcibly flush the stream.\n", "\n" ] } ], "source": [ "help(print)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's define a custom function that calculates the mean value of any array. Study the code below carefully. " ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "def mean_value(array):\n", " \"\"\" Calculate the mean value of an array \n", " \n", " Arguments\n", " ---------\n", " array: Numpy array \n", " \n", " Returns\n", " ------- \n", " mean: mean value of the array\n", " \"\"\"\n", " sum_elem = 0\n", " for element in array:\n", " sum_elem += element # this is the same as sum_elem = sum_elem + element\n", " \n", " mean = sum_elem / len(array)\n", " \n", " return mean\n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once you execute the cell above, the function`mean_value()` becomes available to use on any argument of the correct type. This function works on arrays of any length. We can try it now with our data." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1936.5\n" ] } ], "source": [ "year_mean = mean_value(year)\n", "print(year_mean)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.049942528735632215\n" ] } ], "source": [ "temp_anomaly_mean = mean_value(temp_anomaly)\n", "print(temp_anomaly_mean)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Neat! You learned how to write a Python function, and we wrote one for computing the mean value of an array of numbers. We didn't have to, though, because NumPy has a built-in function to do just what we needed: [`numpy.mean()`](https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.mean.html).\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "_Exercise:_\n", "\n", "Calculate the mean of the `year` and `temp_anomaly` arrays using the NumPy built-in function, and compare the results with the ones obtained using our custom `mean_value` function\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have mean values, we can compute our coefficients by following the equations derived above. We first calculate $a_1$ and then use that value to calculate $a_0$.\n", "\n", "Our coefficients are:\n", "\n", "$$\n", " a_1 = \\frac{ \\sum_{i=0}^{n} y_{i} (x_i - \\bar{x})}{\\sum_{i=0}^{n} x_i (x_i - \\bar{x})} \\quad , \\quad a_0 = \\bar{y} - a_1\\bar{x}\n", "$$ \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We already calculated the mean values of the data arrays, but the formula requires two sums over new derived arrays. Guess what, NumPy has a built-in function for that: [`numpy.sum()`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.sum.html). Study the code below." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "a_1 = numpy.sum(temp_anomaly*(year - year_mean)) / numpy.sum(year*(year - year_mean)) " ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.0058621145249010504\n" ] } ], "source": [ "print(a_1)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "a_0 = temp_anomaly_mean - a_1*year_mean" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-11.302042248735251\n" ] } ], "source": [ "print(a_0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "_Exercise:_\n", "\n", "Write a function that computes the coefficients, call the function to compute them and compare the result with the values we obtained before. As a hint, we give you the structure that you should follow:\n", "\n", "```python\n", "def coefficients(x, y, x_mean, y_mean):\n", " \"\"\"\n", " Write docstrings here\n", " \"\"\"\n", "\n", " a_1 = \n", " a_0 = \n", " \n", " return a_1, a_0\n", "```\n", "\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now have the coefficients of a linear function that best fits our data. With them, we can compute the predicted values of temperature anomaly, according to our fit. Check again the equations above: the values we are going to compute are $f(x_i)$. \n", "\n", "Let's call `reg` the array obtined from evaluating $f(x_i)$ for all years." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "reg = a_0 + a_1 * year" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "With the values of our linear regression, we can plot it on top of the original data to see how they look together. Study the code below. " ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pyplot.figure(figsize=(10, 5))\n", "\n", "pyplot.plot(year, temp_anomaly, color='#2929a3', linestyle='-', linewidth=1, alpha=0.5) \n", "pyplot.plot(year, reg, 'k--', linewidth=2, label='Linear regression')\n", "pyplot.xlabel('Year')\n", "pyplot.ylabel('Land temperature anomaly [°C]')\n", "pyplot.legend(loc='best', fontsize=15)\n", "pyplot.grid();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 4: Apply regression using NumPy" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Above, we coded linear regression from scratch. But, guess what: we didn't have to because NumPy has built-in functions that do what we need!\n", "\n", "Yes! Python and NumPy are here to help! With [`polyfit()`](https://numpy.org/doc/stable/reference/generated/numpy.polyfit.html), we get the slope and $y$-intercept of the line that best fits the data. With [`poly1d()`](https://numpy.org/doc/stable/reference/generated/numpy.poly1d.html), we can build the linear function from its slope and $y$-intercept. (Be sure to review the documentation for these NumPy functions.)\n", "\n", "Check it out:" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "# First fit with NumPy, then name the coefficients obtained a_1n, a_0n:\n", "a_1n, a_0n = numpy.polyfit(year, temp_anomaly, 1)\n", "\n", "f_linear = numpy.poly1d((a_1n, a_0n)) " ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.005862114524901034\n" ] } ], "source": [ "print(a_1n)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-11.302042248735212\n" ] } ], "source": [ "print(a_0n)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " \n", "0.005862 x - 11.3\n" ] } ], "source": [ "print(f_linear)" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pyplot.figure(figsize=(10, 5))\n", "\n", "pyplot.plot(year, temp_anomaly, color='#2929a3', linestyle='-', linewidth=1, alpha=0.5) \n", "pyplot.plot(year, f_linear(year), 'k--', linewidth=2, label='Linear regression')\n", "pyplot.xlabel('Year')\n", "pyplot.ylabel('Land temperature anomaly [°C]')\n", "pyplot.legend(loc='best', fontsize=15)\n", "pyplot.grid();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that here `f_linear` is not an array, but a kind of function—a polynomial function, to be exact. Thus, we give it the array `year` as argument when calling it to obtain the corresponding $y$-values to plot for the regression line. If we enquire for the type of `f_linear`, we get:" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "numpy.poly1d" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "type(f_linear)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Split regression" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you carefully look at the plot above, you might notice that the temperature seems to be increasing faster in the later years. So maybe one single straight line does not give us a good-enough idea of what is happening.\n", "\n", "What if we break the data in two ranges and do a linear regression in each segment? \n", "\n", "To do that, we first need to pick a particular year to split the data, find its location in the `year` array, then slice the data to make two linear regressions. \n", "NumPy offers a few ways to go about this. We can use a conditional statement with the array: this will give us an array of equal size that has truth values: `True` or `False`. \n", "The Boolean values `True` and `False` can be treated as ones and zeros in NumPy, so we could use [`numpy.nonzero()`](https://numpy.org/doc/stable/reference/generated/numpy.nonzero.html#numpy.nonzero) to find the index of the only true value. That function works with multi-dimensional arrays, returning a tuple of index arrays (for each dimension). \n", "You can use [`numpy.flatnonzero()`](https://numpy.org/doc/stable/reference/generated/numpy.flatnonzero.html#numpy.flatnonzero) to get a single array as output. Try it! (But also explore the documentation of the\n" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([90])" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "numpy.flatnonzero(year==1940)" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "90\n" ] } ], "source": [ "# save the index into a variable to use in the plotting below\n", "idx = numpy.flatnonzero(year==1940)[0]\n", "print(idx)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "To split the data, we use the powerful instrument of _slicing_ with the colon notation. Remember that a colon between two indices indicates a range of values from a `start` to an `end`. The rule is that `[start:end]` includes the element at index `start` but excludes the one at index `end`.\n", "\n", "We will split our data in two sets, to get two regression lines. We need two slices of the arrays `year` and `temp_anomaly`, which we'll save in new variable names below. After that, we complete two linear fits using the helpful NumPy functions we learned above." ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "year_1 , temp_anomaly_1 = year[0:idx], temp_anomaly[0:idx]\n", "year_2 , temp_anomaly_2 = year[idx:], temp_anomaly[idx:]\n", "\n", "m1, b1 = numpy.polyfit(year_1, temp_anomaly_1, 1)\n", "m2, b2 = numpy.polyfit(year_2, temp_anomaly_2, 1)\n", "\n", "f_linear_1 = numpy.poly1d((m1, b1))\n", "f_linear_2 = numpy.poly1d((m2, b2))" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pyplot.figure(figsize=(10, 5))\n", "\n", "pyplot.plot(year, temp_anomaly, color='#2929a3', linestyle='-', linewidth=1, alpha=0.5) \n", "pyplot.plot(year_1, f_linear_1(year_1), 'g--', linewidth=2, label='Before')\n", "pyplot.plot(year_2, f_linear_2(year_2), 'r--', linewidth=2, label='After')\n", "\n", "pyplot.xlabel('Year')\n", "pyplot.ylabel('Land temperature anomaly [°C]')\n", "pyplot.legend(loc='best', fontsize=15)\n", "pyplot.grid();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We have two different curves for two different parts of our data set. A little problem with this and is that the end point of our first regression doesn't necessarily match the starting point of the second regression. \n", "Go ahead and try the split regression a few times, with different choices of the year to split the data at. It should be interesting!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Final challenge\n", "\n", "Suppose you used a color scale to represent the temperature anomalies, and you plot one vertical stripe of the color corresponding to each year's value of temperature anomaly. You might get a plot that looks like this (using the Viridis [colormap](https://matplotlib.org/stable/users/explain/colors/colormaps.html)):\n", "\"Vertical\n", "\n", "Isn't that striking? The colors very vividly show the rising temperature over time!\n", "_Can you make a plot like this?_\n", "Search online and see if you can figure it out!\n", "\n", "> This challenge was inspired by the [Warming Stripes](https://www.climate-lab-book.ac.uk/2018/warming-stripes/) post in the Climate Lab Book, by UK climate scientist Ed Hawkins." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## We learned:\n", "\n", "* Making our plots more beautiful\n", "* Defining and calling custom Python functions\n", "* Applying linear regression to data\n", "* NumPy built-ins for linear regression\n", "* The Earth is warming up!!!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## References\n", "\n", "1. [_Essential skills for reproducible research computing_](https://barbagroup.github.io/essential_skills_RRC/) (2017). Lorena A. Barba, Natalia C. Clementi, Gilbert Forsyth. \n", "2. _Numerical Methods in Engineering with Python 3_ (2013). Jaan Kiusalaas. Cambridge University Press.\n", "3. _Effective Computation in Physics: Field Guide to Research with Python_ (2015). Anthony Scopatz & Kathryn D. Huff. O'Reilly Media, Inc.\n" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Execute this cell to load the notebook's style sheet, then ignore it\n", "from IPython.core.display import HTML\n", "HTML(open('../../../styles/custom.css', \"r\").read())" ] } ], "metadata": { "anaconda-cloud": {}, "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": "3.11.6" }, "widgets": { "state": {}, "version": "1.1.2" } }, "nbformat": 4, "nbformat_minor": 4 }