Relation between odds and probability.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "790e62f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "## here we will ty to find out visual relationship between odds and probability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "77cffb7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "## odds  = (1-p)/p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "21ca6e6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b1d04229",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NQ8nD8MPURqL8dcPnRw+1k8PQzHIr+d3kudSCcAG1UPwXYM2Qe+AwNLOcynzNMPNNYD9wZbb8geyzs4fayWFoZrmVPAzfHBHH1i3fKeknzXbyFF5mllvJJ3d9UNIJ/QuS5gP3NNvJPUMzy63kPcP5wLmSdmbLbwS2SdrMEM9HOwzNLJf+yV1LbFhDhx2GZpZbmXuGw30u2mFoZrmVOQyHy2FoZrk5DM3McBiambX7sZnCOAzNLLeS300eFj90bWa5pXroWtJCSY9I6pE06LT8kt4m6SVJ70v6Reo4DM0stxRhKGk8cDW1+VLnAh+QNHeQ7f4HcGsBX+VlDkMzy6XVIGyhZzgP6ImI7RHxAnAjsGSA7S4Avgs8kfabvFKprhkefvjhnHTSScnrfvjDH05eE+DMM89MXnPBggXJawLce++9hdRdtKiYSdC3bt1aSN1p06Ylr3nJJZckrwlwwQUXJK/Z29ubpE6OGyjTJW2sW+6KiK7s/QxgV926XmpD6V4maQbwHuBd1KbxL0ypwtDMqiFHGO6LiM5B1mmg0g3LX6f2GyYvSQNtno7D0MxyS3Q3uReYVbc8E9jdsE0ncGMWhNOBxZIORsTNKRpQz2FoZrkkfM5wAzBH0mzgMWAp8MGGY83ufy/pG8D3iwhCcBia2TCkCMOIOChpBbW7xOOBayNii6Tzs/VNp+pPyWFoZrmlGoESEd1Ad8NnA4ZgRCxLctBBOAzNLDcPxzOzV70KTO46LIU+dC3pCElrJf1M0jZJJxZ5PDMbHSX/DZRhKbpneAVwS0S8T9IhwJSCj2dmo6BqQdeKwsJQ0jTgZGAZQDbc5oWijmdmo2cshmGRp8lHA3uB6yQ9KOkaSYc1biRpuaSNkjY+++yzBTbHzFIZi6fJRYbhBOA4YHVEvBV4DvitKXoioisiOiOic+rUqQU2x8xSSDhRQ6kUGYa9QG9E3J8tr6UWjmZWcX19fS29qqSwMIyIx4Fdkt6cfXQKUMxUJGY2qsZiz7Dou8kXADdkd5K3A+cVfDwzGwVVC7pWFBqGEfEQtVknzGyMqGKvrxUegWJmuTkMzcwYm7+O5zA0s1x8mmxmlnEYmpnhMCycJCZMSN+k2267LXlNgOuuuy55zUsvvTR5TYCVK1cWUveqq64qpO7+/fsLqbts2bLkNTs7i3lg4uSTT05ec8+ePUnqOAzNzHAYmpmN2cldHYZmlpt7hmZmOAzNzACHoZmZH7o2M+vnMDQzw2OTzcwA9wzNzHzN0Mysn8PQzAyHoZkZ4BsoZma+Zmhm1s9haGaGw9DMDBibYTiu3Q0ws+rpv27Y7NWMpIWSHpHUI+myAdb/laSHs9ePJB1byBfCPUMzyynV5K6SxgNXA6cBvcAGSesiYmvdZjuAd0TEryQtArqA+SM++AAchmaWW6LT5HlAT0RsB5B0I7AEeDkMI+JHddvfB8xMceCBlCoM9+7dy+rVq5PXLeoHoZYsWZK85ubNm5PXBDj++OMLqfv0008XUvfmm28upO7ZZ5+dvOaLL76YvCbAaaedlrzmD3/4wyR1coThdEkb65a7IqIrez8D2FW3rpehe30fAdJ8gQGUKgzNrBpyhOG+iBjs5wM1UOkBN5T+jFoYLmj1wHk5DM0sl4QPXfcCs+qWZwK7GzeS9BbgGmBRRDyZ4sAD8d1kM8st0d3kDcAcSbMlHQIsBdbVbyDpjcBNwIci4ueFfJmMe4ZmlluKu8kRcVDSCuBWYDxwbURskXR+tn4N8AXgdcA/SAI4OMRp94g4DM0st1QPXUdEN9Dd8NmauvcfBT6a5GBNOAzNLBdP1GBmlhmLYVjoDRRJF0naIumnkr4taVKRxzOz0ZFqOF6ZFBaGkmYAnwA6I+KPqF0gXVrU8cxs9PT19bX0qpKiT5MnAJMlvQhMYYBniMysWqrY62tFYT3DiHgM+BqwE9gDPBMRvzUuTtJySRslbSxqWJOZpeXT5BwkvZbaoOvZwFHAYZLOadwuIroiojMiOidOnFhUc8wsIYdhPqcCOyJib0S8SO0p8pMKPJ6ZjZKxGIZFXjPcCZwgaQrwPHAKsHHoXcysCqoWdK0oLAwj4n5Ja4EHgIPAg9QmZjSzCks1uWvZFHo3OSJWAiuLPIaZjT73DM3McBiamQEOQzOzSt4pboXD0MxycxiamZFmcteyKVUYjhs3jqlTpyavO3ny5OQ1AU499dTkNWfPnp28JsBZZ51VSN358wv5CVvuueeeQuoW0d5FixYlrwkwbdq05DW/9KUvJanjnqGZver5mqGZWcZhaGaGw9DMDPANFDMzXzM0M+vnMDQzw2FoZgY4DM3MAIehmZkndzUz6+eeoZkZDkMzM8BhaGbmh67NzPo5DM3M8NhkMzPAPUMzszF7zXBcuxtgZtXTH4jNXs1IWijpEUk9ki4bYL0kXZmtf1jScYV8IRyGZjYMKcJQ0njgamARMBf4gKS5DZstAuZkr+XA6vTfpsZhaGa59fX1tfRqYh7QExHbI+IF4EZgScM2S4Dro+Y+4AhJb0j/jUBlOveXtBf4ZQubTgf2FdyclKrU3iq1FarV3jK09U0RceRICki6hdp3acUk4EDdcldEdGV13gcsjIiPZssfAuZHxIq6Y30f+EpE/Gu2fAdwaURsHMl3GEipbqC0+n+SpI0R0Vl0e1KpUnur1FaoVnur1NahRMTCRKU0UPlhbJOET5PNrF16gVl1yzOB3cPYJgmHoZm1ywZgjqTZkg4BlgLrGrZZB5yb3VU+AXgmIvYU0ZhSnSbn0NXuBuRUpfZWqa1QrfZWqa2Fi4iDklYAtwLjgWsjYouk87P1a4BuYDHQA/wGOK+o9pTqBoqZWbv4NNnMDIehmRlQwTBsNnynLCTNknSnpG2Stki6sN1taoWk8ZIezJ7vKi1JR0haK+ln2d/4xHa3aSiSLsr+OfippG9LmtTuNtkrVSoMWxy+UxYHgU9FxB8AJwAfL3Fb610IbGt3I1pwBXBLRBwDHEuJ2yxpBvAJoDMi/ojazYKl7W2VNapUGNLa8J1SiIg9EfFA9v5Zav+yzmhvq4YmaSZwOnBNu9syFEnTgJOBfwSIiBci4um2Nqq5CcBkSROAKRT0rJwNX9XCcAawq265l5IHDICkDuCtwP1tbkozXwcuAco+c+fRwF7guuyU/hpJh7W7UYOJiMeArwE7gT3UnpW7rb2tskZVC8NRG5qTiqTDge8Cn4yI/e1uz2AknQE8ERGb2t2WFkwAjgNWR8RbgeeAMl8/fi21M5jZwFHAYZLOaW+rrFHVwnDUhuakIGkitSC8ISJuand7mng78G5Jj1K7/PAuSd9qb5MG1Qv0RkR/T3sttXAsq1OBHRGxNyJeBG4CTmpzm6xB1cKwleE7pSBJ1K5pbYuIVe1uTzMR8dmImBkRHdT+rv8cEaXsvUTE48AuSW/OPjoF2NrGJjWzEzhB0pTsn4tTKPENn1erSg3HG2z4TpubNZi3Ax8CNkt6KPvs8ojobl+TxpQLgBuy/yhup8BhWiMVEfdLWgs8QO0pgwfx0LzS8XA8MzOqd5psZlYIh6GZGQ5DMzPAYWhmBjgMzcwAh6GZGeAwNDMDHIaWg6SObP7Aa7J5+W6QdKqkeyT9P0nz2t1Gs+FyGFpe/5naXIJvAY4BPggsAD4NXN7GdpmNiMPQ8toREZsjog/YAtwRtWFMm4GOtrbMbAQchpbXv9e976tb7qNiY93N6jkMzcxwGJqZAZ61xswMcM/QzAxwGJqZAQ5DMzPAYWhmBjgMzcwAh6GZGeAwNDMD4D8AzxjY1+KaohEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data =np.random.rand(10,10)\n",
    "cmap = plt.cm.gray\n",
    "norm = plt.Normalize(data.min(),data.max())\n",
    "rgba = cmap(norm(data))\n",
    "\n",
    "\n",
    "plt.imshow(rgba, cmap= cmap)\n",
    "plt.xlabel('m')\n",
    "plt.ylabel('n')\n",
    "plt.title('n/m = (1-p)/p')\n",
    "plt.colorbar(label = 'prob')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a924164a",
   "metadata": {},
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}