6_Code_reusability.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Code reusability\n",
    "\n",
    "Some fuzzy jargon:\n",
    "- **Scripts:** Python files that contain commands in logical order, is run directly and does something (i.e., has an output). Scripts may include functions, but those functions are called within the script.\n",
    "- **Modules:** Files containing classes, functions, and variables that are designed to be imported by scripts or other modules (e.g., the Utilities.py file)\n",
    "- **Packages:** A collection of related modules. Can be either local or called from the Python Package Index (PyPI, pip install x). Has an \"__init__\" file.\n",
    "- **Libraries:** A bundle of packages, such as the python standard library.\n",
    "\n",
    "Making Modules and Packages makes code more reuseable and shareable. They also clean up your working code and make it easier for you to focus on the analysis and results."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example of a script"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "''"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#\n",
    "# Input parameters\n",
    "#\n",
    "\n",
    "Pp = 30 # MPa for 4400 psi from Zoback homework\n",
    "Sv = 75.8 # MPa for 11000 psi from Zoback homework\n",
    "mu = 0.6 # coefficient of friction\n",
    "\n",
    "\n",
    "# \n",
    "# Functions\n",
    "# \n",
    "\n",
    "# Extension limit of the stress polygon\n",
    "# S_hmin = S_Hmax << S_v\n",
    "\n",
    "def minstress(S1,Pp,mu):\n",
    "    '''Use the stress ratio and frictional faulting theroy to constrain minimum stress\n",
    "    \n",
    "    My calculations assume MPa, but other pressure units (Pa, psi) could be used\n",
    "    \n",
    "        Args:       Pp pore pressure \n",
    "                    S1 maximum stress\n",
    "        \n",
    "        Returns:    S3 minimum stress\n",
    "    '''\n",
    "    S3 = ((S1-Pp)/(((mu**2 + 1.)**0.5 + mu)**2))+Pp\n",
    "    return S3\n",
    "\n",
    "\n",
    "# Compression limit of the stress polygon\n",
    "# S_hmin = S_Hmax >> S_v\n",
    "\n",
    "def maxstress(S3,Pp,mu):\n",
    "    '''Use the stress ratio and frictional faulting theory to constrain the maximum stress\n",
    "    \n",
    "        My calculations assume MPa, but other pressure units (Pa, psi) could be used\n",
    "    \n",
    "        Args:       Pp pore pressure \n",
    "                    S3 minimum stress\n",
    "        \n",
    "        Returns:    S1 maximum stress\n",
    "    '''\n",
    "    S1 = ((S3-Pp)*(((mu**2 + 1.)**0.5 + mu)**2))+Pp\n",
    "    return S1\n",
    "\n",
    "\n",
    "#\n",
    "# Define stress limits using the functions\n",
    "#\n",
    "\n",
    "minSh = minstress(Sv,Pp,mu)\n",
    "maxSh = maxstress(Sv,Pp,mu)\n",
    "minSH = minSh \n",
    "maxSH = maxSh\n",
    "\n",
    "#\n",
    "# Plot stress polygon\n",
    "#\n",
    "\n",
    "fig, ax = plt.subplots(1,1,figsize=(6,6))\n",
    "\n",
    "# Vertical stress\n",
    "ax.plot(Sv,Sv,'o',color='k')\n",
    "\n",
    "# Connecting lines\n",
    "ax.plot([minSh,minSh],[minSh,Sv],color='k',alpha=0.5) \n",
    "ax.plot([minSh,Sv],[Sv,maxSH],color='k',alpha=0.5)\n",
    "ax.plot([Sv,maxSh],[maxSH,maxSH],color='k',alpha=0.5)\n",
    "ax.plot([minSh,Sv],[Sv,Sv],color='k',linestyle=':',alpha=0.5)\n",
    "ax.plot([Sv,Sv],[Sv,maxSH],color='k',linestyle=':',alpha=0.5)\n",
    "ax.plot([minSh,maxSH],[minSh,maxSH],color='k',alpha=0.5)\n",
    "\n",
    "# Labels\n",
    "ax.text((maxSH-Sv)/4+Sv,(maxSH-Sv)/1.5+Sv, 'RF', fontsize=10)\n",
    "ax.text((Sv-minSh)/2+minSh,(maxSH-Sv)/8+Sv, 'SS', fontsize=10)\n",
    "ax.text((Sv-minSh)/4+minSh,(Sv-minSh)/1.5+minSh, 'NF', fontsize=10)\n",
    "\n",
    "# Format plot\n",
    "\n",
    "ax.set_xlim(minSh-20, maxSh+20)\n",
    "ax.set_ylim(minSh-20, maxSh+20)\n",
    "\n",
    "ax.set_xlabel('$S_{hmin}$ [MPa]')\n",
    "ax.set_ylabel('$S_{Hmin}$ [MPa]')\n",
    "\n",
    ";"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Same script, but uses a module - Utilities.py\n",
    "\n",
    "Enables you to focus on the science, rather than the code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from Utilities import *\n",
    "\n",
    "Pp = 30 # Pore pressure, MPa \n",
    "Sv = 75.8 # Vertical stress, MPa\n",
    "mu = 0.6 # Coefficient of friction\n",
    "\n",
    "plot = stress_polygon(Sv, Pp, mu)\n",
    "\n",
    "#plot.savefig('Stress_polygon_figure.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "sgw_env_int",
   "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": "3.9.18"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "28e95de71bbcf09c1444ff7d54651fdf8c668d7cd239aea4b3daa2d866405411"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}