{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "twenty-address",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nIt is also possible to add multiline comments using the triple quotes notation.\\nTechnically, this is a string and not a comment, but it can effectively be used\\nfor long, multiline comments.\\n'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lines in a Python script (*.py file) that begin using the number sign are \n",
    "# comments. It is good practice to thoroughly comment your scripts.\n",
    "# The small initial investment in time to comment your work will save you\n",
    "# large amounts of time in the long run."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "organized-magic",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Once deleted, variables cannot be recovered. Proceed (y/[n])? y\n"
     ]
    }
   ],
   "source": [
    "#A useful command to run in the IPython console before running a new script\n",
    "#is '%reset'.  This command will clear all previous variable assignments.\n",
    "%reset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "accurate-ethics",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Addition, subtraction, multiplication, and division\n",
    "3 + 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "colonial-warner",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8\n"
     ]
    }
   ],
   "source": [
    "# Alternatively, you can assign the result of the operation to a variable and \n",
    "# then print that variable.\n",
    "x = 3 + 5\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "toxic-syracuse",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.25\n"
     ]
    }
   ],
   "source": [
    "# The synatax for the other common operations are as you'd expect:\n",
    "y = (3 + 5*2)/4\n",
    "print(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "extensive-injury",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "y = 3.25\n"
     ]
    }
   ],
   "source": [
    "# You could format your outputs too:\n",
    "print('y =', y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "loaded-madrid",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9\n"
     ]
    }
   ],
   "source": [
    "# To do powers, use the ** notation.\n",
    "print (3**2)\n",
    "\n",
    "# Note that '^' is not used to evaluate powers in Python.  It is the XOR\n",
    "# (exclusive OR) logic operator."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "medieval-orlando",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hbar = 1.05e-34 Js & kB = 1.38e-23 J/K\n"
     ]
    }
   ],
   "source": [
    "# Python will accept scientific notation as follows:\n",
    "hbar = 1.05e-34\n",
    "kB = 1.38e-23\n",
    "print('hbar =', hbar, 'Js', '& kB =', kB, 'J/K')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "quality-industry",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Some of the other common mathematical functions, like trig functions,\n",
    "# exponentials, and logs require a module.  For example, cos(1) won't\n",
    "# work without the math module. I recommend the numPy module. To load the math module, use:\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "several-cancellation",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5403023058681398\n"
     ]
    }
   ],
   "source": [
    "# We can now evaluate the cosine function using\n",
    "x = np.cos(1)\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "independent-crawford",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pi = 3.141592653589793 & e = 2.718281828459045\n"
     ]
    }
   ],
   "source": [
    "# Pi and e are also available in the numPy module.\n",
    "print('pi =', np.pi, '& e =', np.e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "rental-secretariat",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.4999681658280706\n"
     ]
    }
   ],
   "source": [
    "# Here's an inverse trig function\n",
    "print(np.arctan(9999)/np.pi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "bizarre-mambo",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.36787944117144233\n",
      "-1.0\n",
      "-2.0\n"
     ]
    }
   ],
   "source": [
    "# Here are the exponential and logarithmic functions\n",
    "print(np.exp(-1))\n",
    "print(np.log(np.exp(-1))) # natural log, i.e. ln\n",
    "print(np.log10(10**-2)) # log (base 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "chemical-obligation",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7.280109889280518\n",
      "7.280109889280518\n"
     ]
    }
   ],
   "source": [
    "# There are two ways to calculate square roots\n",
    "print(53**0.5)\n",
    "print(np.sqrt(53))"
   ]
  }
 ],
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