{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import pearsonr, spearmanr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test Case 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test case 1 pearson coeficient: \u001b[1m1.0.\n"
     ]
    }
   ],
   "source": [
    "x1 = [4, 5, 6, 7]\n",
    "y1 = [5, 6, 7, 8]\n",
    "p1 = pearsonr(x1, y1)\n",
    "print('Test case 1 pearson coeficient: \\033[1m{0:.8}.'.format(p1[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test Case 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test case 2 pearson coeficient: \u001b[1m1.0.\n"
     ]
    }
   ],
   "source": [
    "x2 = [9, 8, 7, 6]\n",
    "y2 = [8, 7, 6, 5]\n",
    "p2 = pearsonr(x2, y2)\n",
    "print('Test case 2 pearson coeficient: \\033[1m{0:.8}.'.format(p2[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test Case 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test case 3 pearson coeficient: \u001b[1m-0.58913542.\n"
     ]
    }
   ],
   "source": [
    "x3 = [48, 84, 39, 54]\n",
    "y3 = [84, 39, 54, 77]\n",
    "p3 = pearsonr(x3, y3)\n",
    "print('Test case 3 pearson coeficient: \\033[1m{0:.8}.'.format(p3[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test Cases 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test case 4 pearson coeficient: \u001b[1m-0.037601474.\n"
     ]
    }
   ],
   "source": [
    "x4 = [86, 97, 99, 100, 101, 103, 106, 110, 112, 113]\n",
    "y4 = [0, 20, 28, 27, 50, 29, 7, 17, 6, 12]\n",
    "p4 = pearsonr(x4, y4)\n",
    "print('Test case 4 pearson coeficient: \\033[1m{0:.8}.'.format(p4[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test Cases 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test case  0 - x=[ 93 76 18 38 27 ] y=[ 76 18 38 27 48 ] r= 0.34670807201\n",
      "Test case  1 - x=[ 76 18 38 27 48 ] y=[ 18 38 27 48 22 ] r= -0.821747728214\n",
      "Test case  2 - x=[ 18 38 27 48 22 ] y=[ 38 27 48 22 73 ] r= -0.701175297732\n",
      "Test case  3 - x=[ 38 27 48 22 73 ] y=[ 27 48 22 73 54 ] r= -0.233376493759\n"
     ]
    }
   ],
   "source": [
    "data = [93, 76, 18, 38, 27, 48, 22, 73, 54, 68]\n",
    "n = len(data)\n",
    "window = 5\n",
    "for i in range(n-window-1):\n",
    "    x = data[i:i+window]\n",
    "    y = data[i+1:i+window+1]\n",
    "    p = pearsonr(x, y)\n",
    "    print('Test case ', i, '- x=[', *x, '] y=[', *y, '] r=', p[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test Case Wikipedia's [article](https://en.wikipedia.org/wiki/Spearman%27s_rank_correlation_coefficient)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test case from Wikipedia Article PEARSON coeficient: \u001b[1m-0.037601474.\n",
      "Test case from Wikipedia Article SPEARMAN coeficient: \u001b[1m-0.17575758.\n"
     ]
    }
   ],
   "source": [
    "x5 = [86, 97, 99, 100, 101, 103, 106, 110, 112, 113]\n",
    "y5 = [0, 20, 28, 27, 50, 29, 7, 17, 6, 12]\n",
    "p5 = pearsonr(x5, y5)\n",
    "s = spearmanr(x5, y5)\n",
    "print('Test case from Wikipedia Article PEARSON coeficient: \\033[1m{0:.8}.'.format(p5[0]))\n",
    "print('Test case from Wikipedia Article SPEARMAN coeficient: \\033[1m{0:.8}.'.format(s[0]))"
   ]
  }
 ],
 "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": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}