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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h1>5. Modules and Exception Handling</h1>\n",
+    "<h2>10/09/2023</h2>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h2>5.0 Last Time...</h2>\n",
+    "\n",
+    "<ul>\n",
+    "    <li>A <b>for loop</b> lets you repeat an operation a specified  number of times.</li>\n",
+    "    <li>Indentation is critical for loops in Python.</li>\n",
+    "    <li>The range() function will create a list of all values up to the specified integer.</li>\n",
+    "    <li>Hardcoding is the act of (often unnecessarily) restricting a piece of code so it only works under specific circumstances.</li>\n",
+    "    <li>A <b>while loop</b> lets you repeat an operation until a particular condition is met.</li>\n",
+    "    <li>The index in a while loop must be initialized and care should be taken to avoid infinite loops.</li>\n",
+    "</ul>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h2>5.1 Modules</h2>\n",
+    "\n",
+    "A <b>module</b> is just a library of Python source code files that will give you access to new (frequently more specialized) functions.\n",
+    "\n",
+    "To import a module, the syntax is simply: <b>import \\<module name\\></b>."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-0.7568024953079283\n"
+     ]
+    }
+   ],
+   "source": [
+    "# An extremely useful module in the atmospheric science world is NumPy.\n",
+    "# This package lets you use a variety of mathematical (and array-based) functions and variables.\n",
+    "import numpy\n",
+    "\n",
+    "\n",
+    "# As soon as the module is imported, you have access to all its contents.\n",
+    "\n",
+    "# To refer to a function or variable within numpy, just follow it with a \n",
+    "# period, then the function or variable in question.\n",
+    "\n",
+    "# As an example, numpy will let you calculate the sine of a given number.\n",
+    "a = numpy.sin(4)\n",
+    "print(a)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Some modules have what are called <b>submodules</b> that can be referred to in a similar way. For instance, the module NumPy has a submodule called ma, which in turn has particular functions defined within it. If you wanted to run the <b>array</b> function inside the <b>ma</b> submodule inside the <b>NumPy</b> module, it would look like <b>numpy.ma.array</b>.\n",
+    "\n",
+    "Modules have detailed documentation (typically easily found via Google) that will let you browse all the available functions at your disposal. This instance of Jupyter has several modules preinstalled; they may be missing if you try running them on a Python build at home. Fortunately, there are generally helpful instructions online for downloading new modules so they can be imported into your code."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-0.7568024953079282"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# If you find yourself typing the same module name again and again, \n",
+    "# you can rename it to something a little quicker!\n",
+    "\n",
+    "import numpy as np\n",
+    "\n",
+    "a = np.sin(4)\n",
+    "a"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As a meteorological example, let's return to our list of Celsius temperatures from yesterday. NumPy will enable us to easily calculate the maximum and minimum temperatures."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The maximum temperature is 36.5 and the minimum temperature is 13.5.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# First, here's our temperature list.\n",
+    "\n",
+    "temp = [23.5,24.5,18.0,26.8,17.7,17.0,27.1,24.6,13.5,36.5]\n",
+    "\n",
+    "# Let's import NumPy.\n",
+    "\n",
+    "import numpy as np\n",
+    "\n",
+    "# Now, use the max() and min() functions within the NumPy module\n",
+    "# to calculate the maximum and minimum temperatures.\n",
+    "\n",
+    "maxT = np.max(temp)\n",
+    "minT = np.min(temp)\n",
+    "\n",
+    "# We can even output a nice sentence summing it up!\n",
+    "\n",
+    "print(\"The maximum temperature is \"+str(maxT)+\" and the minimum temperature is \"+str(minT)+\".\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<b>An example!</b>\n",
+    "\n",
+    "In the box below, write a block of code that will apply a NumPy mathematical function of your choice to the list of temperatures <b>(temp)</b> above: https://numpy.org/doc/stable/reference/routines.math.html. Don't forget to include your module import statement!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[-0.99808203 -0.59135753 -0.75098725  0.9953511  -0.91258245 -0.96139749\n",
+      "  0.92243282 -0.50789659  0.80378443 -0.93171689]\n",
+      "[-0.06190529  0.80640949  0.66031671 -0.09631292  0.40889274 -0.27516334\n",
+      " -0.38615761  0.86141805  0.59492066  0.36318541]\n",
+      "[ 16.12272495  -0.73332164  -1.13731371 -10.33455467  -2.23183823\n",
+      "   3.49391565  -2.38874697  -0.58960523   1.35107835  -2.56540287]\n"
+     ]
+    }
+   ],
+   "source": [
+    "temp = [23.5,24.5,18.0,26.8,17.7,17.0,27.1,24.6,13.5,36.5]\n",
+    "import numpy as np\n",
+    "\n",
+    "# Mathematical function #1.\n",
+    "print(np.sin(temp))\n",
+    "\n",
+    "# Mathematical function #2.\n",
+    "print(np.cos(temp))\n",
+    "print(np.tan(temp))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h2>5.2 Exception Handling</h2>\n",
+    "\n",
+    "An \"exception\" is a very polite way of saying \"error\" in programming-speak. Often we use an if statement to determine whether something is going to cause a problem, and then use a <b>raise</b> statement to tell the code to stop and output a particular error."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "6\n",
+      "12.566370614359172\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Let's say we have a code that will attempt to calculate the area of a circle\n",
+    "# based on its radius.\n",
+    "# It works well for positive values of radius, but we want to allow for the\n",
+    "# possibility that someone might enter a negative radius.\n",
+    "\n",
+    "import numpy as np\n",
+    "\n",
+    "def circle_area(radius):\n",
+    "    if radius < 0:\n",
+    "        raise ValueError('Radius cannot be negative, you fool!')\n",
+    "    area = np.pi * (radius**2)\n",
+    "    return area\n",
+    "\n",
+    "def quadarea(base, height):\n",
+    "    if base < 0:\n",
+    "        raise ValueError('enter a POSITIVE number')\n",
+    "    elif height < 0:\n",
+    "        raise ValueError('POSITIVE integer please')\n",
+    "    x = base*height\n",
+    "    return x\n",
+    "# Now try calling this function with a positive radius to make sure it works.\n",
+    "print(quadarea(2,3))\n",
+    "print(circle_area(2))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "Radius cannot be negative, you fool!",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[15], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Now try calling this function with a negative radius.\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mcircle_area\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m)\u001b[49m)\n",
+      "Cell \u001b[0;32mIn[14], line 10\u001b[0m, in \u001b[0;36mcircle_area\u001b[0;34m(radius)\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcircle_area\u001b[39m(radius):\n\u001b[1;32m      9\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m radius \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m---> 10\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mRadius cannot be negative, you fool!\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m     11\u001b[0m     area \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mpi \u001b[38;5;241m*\u001b[39m (radius\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[1;32m     12\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m area\n",
+      "\u001b[0;31mValueError\u001b[0m: Radius cannot be negative, you fool!"
+     ]
+    }
+   ],
+   "source": [
+    "# Now try calling this function with a negative radius.\n",
+    "\n",
+    "print(circle_area(-2))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The syntax for <b>raise</b> is the exception class (for instance, ValueError() if a value is forbidden; this is the most common type of exception you'll have, but we'll see others as we go) followed by user-defined text that will give you more information about the error.\n",
+    "\n",
+    "Luckily, Python also lets you build in ways to deal with common exceptions if you're pretty sure you know where the user went wrong. For example, they may have accidentally put a negative sign on the radius, but you're pretty sure they just meant the positive value. In that case, you can use a <b>try/except</b> block, which will attempt to resolve the error."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "28.274333882308138\n"
+     ]
+    }
+   ],
+   "source": [
+    "# As an example, this code will call the area() function, and if it gets\n",
+    "# a ValueError exception, it'll try again with the absolute value\n",
+    "# of the range.\n",
+    "\n",
+    "radius = -3\n",
+    "try:\n",
+    "    a = circle_area(radius)\n",
+    "except ValueError:\n",
+    "    a = circle_area(abs(radius))\n",
+    "    \n",
+    "print(a)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<h2>TAKE-HOME POINTS</h2>\n",
+    "\n",
+    "<ul>\n",
+    "    <li>A <b>module</b> is a library of Python source code that gives access to new variables and functions.</li>\n",
+    "    <li>Modules can be imported as whatever name you like.</li>\n",
+    "    <li>A <b>raise</b> statement lets you define your own error conditions and stop code when they're met.</li>\n",
+    "    <li>A <b>try/except</b> block will let you fix common issues that would otherwise result in exceptions.</li>\n",
+    "</ul>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# you can import modules with any name you want"
+   ]
+  }
+ ],
+ "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": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}