GBMPlots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "lb=[\"I01\",\"I02\",\"I03\",\"I04\",\"I05\",\"I06\",\"I07\",\"I08\",\"I09\",\"I10\",\"I11\",\"I12\",\"I13\",\"I14\",\"I15\",\"I16\",\"I17\",\"I18\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "plt.figure(figsize=(12,7))\n",
    "plt.boxplot([t1.IO1,t1.IO2,t1.IO3,t1.IO4,t1.IO5,t1.IO6,t1.IO7,t1.IO8,t1.IO9,t1.I10,t1.I11,t1.I12,t1.I13,t1.I14,t1.I15,t1.I16,t1.I17,t1.I18],0,\"gD\",labels=lb,)\n",
    "plt.xlabel(\"Indices\")\n",
    "plt.ylabel(\"T1\",rotation=0)\n",
    "plt.savefig(\"t1GBMJumpSqueeze\",fExpansionormat=\"png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb402b4cc18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=pd.ExcelFile('/home/sharan/Desktop/Transport/IISER/ClusterOutput/Squeeze/GBM/t1FinalSqueeze.xlsx')\n",
    "t1=x.parse(0)\n",
    "\n",
    "y=pd.ExcelFile('/home/sharan/Desktop/Transport/IISER/ClusterOutput/Squeeze/Stat.xlsx')\n",
    "page=y.parse(0)\n",
    "t1star=np.array(page.Mean)\n",
    "# t2star=np.append(t2star,t2star[len(t2star)-1])\n",
    "plt.figure(figsize=(12,7))\n",
    "plt.boxplot([t1.IO1,t1.IO2,t1.IO3,t1.IO4,t1.IO5,t1.IO6,t1.IO7,t1.IO8,t1.IO9,t1.I10,t1.I11,t1.I12,t1.I13,t1.I14,t1.I15,t1.I16,t1.I17,t1.I18],0,\" \",labels=lb)\n",
    "plt.scatter(x=range(1,19),y=t1star,marker=\"D\",c=\"g\")\n",
    "# print(len(t2star))\n",
    "# print(len(lb))\n",
    "plt.xlabel(\"Indices\")\n",
    "plt.ylabel(\"T1\",rotation=0)\n",
    "plt.savefig(\"t1GBMJumpSqueeze\",format=\"png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb3f9d02470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=pd.ExcelFile('/home/sharan/Desktop/Transport/IISER/ClusterOutput/Squeeze/GBM/t2FinalSqueeze.xlsx')\n",
    "t2=x.parse(0)\n",
    "\n",
    "# y=pd.ExcelFile('/home/thegodfather/Desktop/IISER/Codes&Data2/Squeeze/GBM/MainSqueezeMax.xlsx')\n",
    "# page=y.parse(0)\n",
    "t2star=np.array(page.SD)\n",
    "# t2star=np.append(t2star,t2star[len(t2star)-1])\n",
    "plt.figure(figsize=(12,7))\n",
    "plt.boxplot([t2.IO1,t2.IO2,t2.IO3,t2.IO4,t2.IO5,t2.IO6,t2.IO7,t2.IO8,t2.IO9,t2.I10,t2.I11,t2.I12,t2.I13,t2.I14,t2.I15,t2.I16,t2.I17,t2.I18],0,\" \",labels=lb)\n",
    "plt.scatter(x=range(1,19),y=t2star,marker=\"D\",c=\"g\")\n",
    "# print(len(t2star))\n",
    "# print(len(lb))\n",
    "plt.xlabel(\"Indices\")\n",
    "plt.ylabel(\"T2\",rotation=0)\n",
    "plt.savefig(\"t2GBMJumpSqueeze\",format=\"png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb3fa05d8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=pd.ExcelFile('/home/sharan/Desktop/Transport/IISER/ClusterOutput/Squeeze/GBM/t3FinalSqueeze.xlsx')\n",
    "t3=x.parse(0)\n",
    "\n",
    "# y=pd.ExcelFile('/home/thegodfather/Desktop/IISER/Codes&Data2/Squeeze/GBM/MainSqueezeMax.xlsx')\n",
    "# page=y.parse(0)\n",
    "t3star=np.array(page.Skew)\n",
    "\n",
    "plt.figure(figsize=(12,7))\n",
    "plt.boxplot([t3.IO1,t3.IO2,t3.IO3,t3.IO4,t3.IO5,t3.IO6,t3.IO7,t3.IO8,t3.IO9,t3.I10,t3.I11,t3.I12,t3.I13,t3.I14,t3.I15,t3.I16,t3.I17,t3.I18],0,\" \",labels=lb)\n",
    "plt.scatter(x=range(1,19),y=t3star,marker=\"D\",c=\"g\")\n",
    "plt.xlabel(\"Indices\")\n",
    "plt.ylabel(\"T3\",rotation=0)\n",
    "# plt.ylabe(rotation=90)\n",
    "plt.savefig(\"t3GBMJumpSqueeze\",format=\"png\")\n",
    "plt.show()\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb3f9d028d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=pd.ExcelFile('/home/sharan/Desktop/Transport/IISER/ClusterOutput/Squeeze/GBM/t4FinalSqueeze.xlsx')\n",
    "t4=x.parse(0)\n",
    "\n",
    "# y=pd.ExcelFile('/home/thegodfather/Desktop/IISER/Codes&Data2/Squeeze/GBM/MainSqueezeMax.xlsx')\n",
    "# page=y.parse(0)\n",
    "t4star=np.array(page.Kurtosis)\n",
    "\n",
    "plt.figure(figsize=(12,7))\n",
    "plt.boxplot([t4.IO1,t4.IO2,t4.IO3,t4.IO4,t4.IO5,t4.IO6,t4.IO7,t4.IO8,t4.IO9,t4.I10,t4.I11,t4.I12,t4.I13,t4.I14,t4.I15,t4.I16,t4.I17,t4.I18],0,\" \",labels=lb)\n",
    "plt.scatter(x=range(1,19),y=t4star,marker=\"D\",c=\"g\")\n",
    "plt.xlabel(\"Indices\")\n",
    "plt.ylabel(\"T4\",rotation=0)\n",
    "# plt.ylabe(rotation=90)\n",
    "plt.savefig(\"t4GBMJumpSqueeze\",format=\"png\")\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}