Functions.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Functions in Python\n",
    "This is mostly copied and modified from Solfware Carpentry for the use of the LDEO python class\n",
    "See http://swcarpentry.github.io/python-novice-inflammation/06-func.html for full lesson "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Writing a basic function within a piece of code - simple example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def fahr_to_kelvin(temp):\n",
    "    return ((temp - 32) * (5/9)) + 273.15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "273.15"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fahr_to_kelvin(32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "freezing point of water: 273.15\n"
     ]
    }
   ],
   "source": [
    "print('freezing point of water:', fahr_to_kelvin(32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "absolute zero in Celsius: -273.15\n"
     ]
    }
   ],
   "source": [
    "def kelvin_to_celsius(temp):\n",
    "    return temp - 273.15\n",
    "\n",
    "print('absolute zero in Celsius:', kelvin_to_celsius(0.0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "freezing point of water in Celsius: 0.0\n"
     ]
    }
   ],
   "source": [
    "def fahr_to_celsius(temp):\n",
    "    temp_k = fahr_to_kelvin(temp)\n",
    "    result = kelvin_to_celsius(temp_k)\n",
    "    return result\n",
    "\n",
    "print('freezing point of water in Celsius:', fahr_to_celsius(32.0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26.850000000000023"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_var = kelvin_to_celsius(300)\n",
    "temp_var"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## multiple outputs and input example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def test_function(a,b,c):\n",
    "    d=a+b+c\n",
    "    e=a-b+c\n",
    "    f=10\n",
    "    return d,e,f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[6, 2, 10]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[d_r,e_r,f_r]=test_function(1,2,3)\n",
    "[d_r,e_r,f_r]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d_r+f_r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example 2: Plotting fuction\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def import_and_plot_gridded_data(matfile):\n",
    "    th=matfile.get('th_pr_l')\n",
    "    sa=matfile.get('sa_pr_l')\n",
    "    pr=matfile.get('pr_g')\n",
    "    ox=matfile.get('ox_pr_l')\n",
    "    lat=matfile.get('lat_l')\n",
    "    lon=matfile.get('lon')\n",
    "    \n",
    "    X,Y=np.meshgrid(lat,pr)\n",
    "\n",
    "    fig = plt.figure(figsize=(15, 6))\n",
    "\n",
    "    ax1=fig.add_subplot(311)\n",
    "    plt.contourf(X,Y,th)\n",
    "\n",
    "    ax2=fig.add_subplot(312)\n",
    "    plt.contourf(X,Y,sa)\n",
    "\n",
    "    ax3=fig.add_subplot(313)\n",
    "    plt.contourf(X,Y,ox)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy.io import loadmat as loadmat \n",
    "%matplotlib inline "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA30AAAFrCAYAAABlmuAWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nHXvQ+gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1165fe128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matfile_1 = loadmat('/Users/Purkey/SMGP/2014_AABW_ages/Analysis/S4P_2011_gridded.mat') \n",
    "import_and_plot_gridded_data(matfile_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA3MAAAFrCAYAAAB7U9ClAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1165fe7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matfile_1 = loadmat('/Users/Purkey/SMGP/2014_AABW_ages/Analysis/S4P_1992_gridded.mat') \n",
    "import_and_plot_gridded_data(matfile_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}