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September 23, 2023 16:37
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vijayassignment.ipynb
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| { | |
| "nbformat": 4, | |
| "nbformat_minor": 0, | |
| "metadata": { | |
| "colab": { | |
| "provenance": [], | |
| "include_colab_link": true | |
| }, | |
| "kernelspec": { | |
| "name": "python3", | |
| "display_name": "Python 3" | |
| }, | |
| "language_info": { | |
| "name": "python" | |
| } | |
| }, | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/tensorvijay/8cd1a1eb7e105c0f2a42f49ad43a2434/vijayassignment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "HV6NkCZDzV6M" | |
| }, | |
| "source": [ | |
| "The constants asked in the asssignment are given below\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "pwTpkGUkzc22" | |
| }, | |
| "source": [ | |
| "" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "Lwb2DV_N0CN9" | |
| }, | |
| "source": [ | |
| "The code is long and lot of trial and errors have been carried out , and it has been a time consuming process. To ensure the readability is good I will include the following rules. The plots which are explicitly bigger than other plots are the ones specifically asked in the assignment. I will also mark it with **** whichever part is important." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "lnbWcUou0UBB" | |
| }, | |
| "source": [ | |
| "A lot of trial and error and error involved, this has been a time consuming process for me , I have not been able to delete the additional portion. Inconvenience is regretted\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "fZcljXJvkJ47" | |
| }, | |
| "source": [ | |
| "import numpy as np\n", | |
| "import matplotlib.pyplot as plt\n" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "_zZqw-2_kkkU" | |
| }, | |
| "source": [ | |
| "Load the data" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "oGAtJGHakeaO", | |
| "outputId": "1e9c7d9f-61a9-483c-f7c6-84e9ebacd311" | |
| }, | |
| "source": [ | |
| "Xmm='/content/drive/MyDrive/PUlsar/Pulsar_XMM_Newton/PNSPEC'\n", | |
| "Xmm_t=np.loadtxt(Xmm)\n", | |
| "Xmm_t" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "array([4.19192093e+08, 4.19192095e+08, 4.19192097e+08, ...,\n", | |
| " 4.19274596e+08, 4.19274604e+08, 4.19274605e+08])" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 143 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "WEczTAOFoMzr" | |
| }, | |
| "source": [ | |
| "Define the functions under consideration" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "EOKQ16rTkhu0" | |
| }, | |
| "source": [ | |
| "# The time difference from the median value\n", | |
| "def f_t(t,t_0):\n", | |
| " return t-t_0\n", | |
| "\n", | |
| "#find the taylor expansion and the phase\n", | |
| "def taylor(v):\n", | |
| " T=np.array([v*ft,((1/2)*f_dot)*ft**2])\n", | |
| " return np.sum(T.T,axis=1)\n", | |
| "#Find the Z statistic for 1 and 2 to estimate frequency\n", | |
| "def Zstat(t):\n", | |
| " # calculation of the first two harmonics of the Z statistic\n", | |
| " Z_1=(np.sum(np.cos(t))**2+np.sum(np.sin(t))**2)*(2/N)\n", | |
| " Z_2=(np.sum(np.cos(2*t))**2+np.sum(np.sin(2*t))**2)*(2/N)\n", | |
| " Z2=Z_1+Z_2\n", | |
| " return Z_1,Z2\n", | |
| "\n", | |
| "#first find the number of terms\n", | |
| "def n_terms(ran,d):\n", | |
| " n=((2*ran)/d)+1\n", | |
| " return np.round(n)\n", | |
| "#The main function associated with the loop\n", | |
| "def maxest(v):\n", | |
| " s=taylor(v)\n", | |
| " z1,z2=Zstat(s)\n", | |
| "\n" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "IiEwn-6botNk" | |
| }, | |
| "source": [ | |
| "Useful constants" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "6zHMrxPyonyA" | |
| }, | |
| "source": [ | |
| "freq=20.585119830\n", | |
| "f_dot=-3.648E-11\n", | |
| "N=9755" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "XGm2bz3ho1Yz" | |
| }, | |
| "source": [ | |
| "Now let us dive into the code" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "EelCFkE5nI1f" | |
| }, | |
| "source": [ | |
| "The time difference from the median" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "vhFFHhcClOzV", | |
| "outputId": "5c3ce0ac-563b-4f42-c973-82f5163cbb8c" | |
| }, | |
| "source": [ | |
| "t_0=np.median(Xmm_t)\n", | |
| "ft=f_t(Xmm_t,t_0)\n", | |
| "ft" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "array([-40243.06155598, -40241.19992197, -40239.39111096, ...,\n", | |
| " 42259.71416205, 42267.90318304, 42269.266029 ])" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 146 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "t6_2yj1tnMtt" | |
| }, | |
| "source": [ | |
| "The number of terms" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "kAq5WRVGlPli", | |
| "outputId": "c4970d97-0303-48d2-a8d0-6dd5d07ccb13" | |
| }, | |
| "source": [ | |
| "nt=n_terms(0.01,1E-5)\n", | |
| "nt" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "2001.0" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 147 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "uRp5fOB4oGGZ" | |
| }, | |
| "source": [ | |
| "The range of frequency" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "aku4DetBnTUs" | |
| }, | |
| "source": [ | |
| "f_r=np.linspace(freq-0.01,freq+0.01,2001)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "7JLWWYzSpd2W", | |
| "outputId": "afa57298-c738-4a33-e1f6-1ab0c8f3f46c" | |
| }, | |
| "source": [ | |
| "len(f_r)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "2001" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 149 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "yfftJZqcymbB" | |
| }, | |
| "source": [ | |
| "Z__1=[]\n", | |
| "Z__2=[]\n", | |
| "for i in range(0,2001):\n", | |
| " a=taylor(f_r[i])\n", | |
| " l,m=Zstat(a)\n", | |
| " #print(l,m)\n", | |
| " Z__1.append(l)\n", | |
| " Z__2.append(m)\n", | |
| "\n" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 282 | |
| }, | |
| "id": "_sPx_aFBBKaO", | |
| "outputId": "07d95194-36e2-4020-d845-e9e47439d94e" | |
| }, | |
| "source": [ | |
| "plt.plot(Z__1,f_r)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7fbe8f1e3850>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 63 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 282 | |
| }, | |
| "id": "wzPIFJ88Chea", | |
| "outputId": "d49482e6-ce71-4df6-e11b-e4ff77c03802" | |
| }, | |
| "source": [ | |
| "plt.plot(Z__2,f_r)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7fbe8f153ed0>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 64 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "Kz7XsDsxHOl6", | |
| "outputId": "d96191f2-978b-4835-c523-45ef7e782cdc" | |
| }, | |
| "source": [ | |
| "zmax1=np.argmax(Z__2)\n", | |
| "s_fr=f_r[zmax1]\n", | |
| "s_fr" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "20.58472983" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 72 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "8sRYpJDaFdGR" | |
| }, | |
| "source": [ | |
| "Let us try this for 0.0001 range and 10E-10" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "jg_yaH8cBjSx", | |
| "outputId": "8eae1e71-0dda-4106-a11f-be8e31bfbcc9" | |
| }, | |
| "source": [ | |
| "nt2=n_terms(0.0001,1E-8)\n", | |
| "nt2\n", | |
| "f_rab=np.linspace(s_fr-0.0001,s_fr+0.0001,np.int(nt2))\n", | |
| "f_rab\n", | |
| "#f_r_=np.linspace(freq-0.0001,freq+0.0001,nt2)\n", | |
| "#f_r_" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "array([20.58462983, 20.58462984, 20.58462985, ..., 20.58482981,\n", | |
| " 20.58482982, 20.58482983])" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 86 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "vgK_SdotO-iT", | |
| "outputId": "6d73d654-a15a-4f26-c039-22d87968b4a6" | |
| }, | |
| "source": [ | |
| "np.int(nt2)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "20001" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 88 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "_Cupw6CrPlfz", | |
| "outputId": "f3d56651-9500-4034-e6bf-531719bd29d7" | |
| }, | |
| "source": [], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "0.06105977286173666" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 89 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "u9SAyThuGVAC", | |
| "outputId": "01895a18-d838-45b6-e2af-303260e9f327" | |
| }, | |
| "source": [ | |
| "Z___1=[]\n", | |
| "Z___2=[]\n", | |
| "for i in range(0,np.int(nt2)):\n", | |
| " print('here',i)\n", | |
| " a_=taylor(f_rab[i])\n", | |
| " l_,m_=Zstat(a_)\n", | |
| " #print(l,m)\n", | |
| " print('there',i)\n", | |
| " Z___1.append(l_)\n", | |
| " Z___2.append(m_)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n", | |
| "here 17501\n", | |
| "there 17501\n", | |
| "here 17502\n", | |
| "there 17502\n", | |
| "here 17503\n", | |
| "there 17503\n", | |
| "here 17504\n", | |
| "there 17504\n", | |
| "here 17505\n", | |
| "there 17505\n", | |
| "here 17506\n", | |
| "there 17506\n", | |
| "here 17507\n", | |
| "there 17507\n", | |
| "here 17508\n", | |
| "there 17508\n", | |
| "here 17509\n", | |
| "there 17509\n", | |
| "here 17510\n", | |
| "there 17510\n", | |
| "here 17511\n", | |
| "there 17511\n", | |
| "here 17512\n", | |
| "there 17512\n", | |
| "here 17513\n", | |
| "there 17513\n", | |
| "here 17514\n", | |
| "there 17514\n", | |
| "here 17515\n", | |
| "there 17515\n", | |
| "here 17516\n", | |
| "there 17516\n", | |
| "here 17517\n", | |
| "there 17517\n", | |
| "here 17518\n", | |
| "there 17518\n", | |
| "here 17519\n", | |
| "there 17519\n", | |
| "here 17520\n", | |
| "there 17520\n", | |
| "here 17521\n", | |
| "there 17521\n", | |
| "here 17522\n", | |
| "there 17522\n", | |
| "here 17523\n", | |
| "there 17523\n", | |
| "here 17524\n", | |
| "there 17524\n", | |
| "here 17525\n", | |
| "there 17525\n", | |
| "here 17526\n", | |
| "there 17526\n", | |
| "here 17527\n", | |
| "there 17527\n", | |
| "here 17528\n", | |
| "there 17528\n", | |
| "here 17529\n", | |
| "there 17529\n", | |
| "here 17530\n", | |
| "there 17530\n", | |
| "here 17531\n", | |
| "there 17531\n", | |
| "here 17532\n", | |
| "there 17532\n", | |
| "here 17533\n", | |
| "there 17533\n", | |
| "here 17534\n", | |
| "there 17534\n", | |
| "here 17535\n", | |
| "there 17535\n", | |
| "here 17536\n", | |
| "there 17536\n", | |
| "here 17537\n", | |
| "there 17537\n", | |
| "here 17538\n", | |
| "there 17538\n", | |
| "here 17539\n", | |
| "there 17539\n", | |
| "here 17540\n", | |
| "there 17540\n", | |
| "here 17541\n", | |
| "there 17541\n", | |
| "here 17542\n", | |
| "there 17542\n", | |
| "here 17543\n", | |
| "there 17543\n", | |
| "here 17544\n", | |
| "there 17544\n", | |
| "here 17545\n", | |
| "there 17545\n", | |
| "here 17546\n", | |
| "there 17546\n", | |
| "here 17547\n", | |
| "there 17547\n", | |
| "here 17548\n", | |
| "there 17548\n", | |
| "here 17549\n", | |
| "there 17549\n", | |
| "here 17550\n", | |
| "there 17550\n", | |
| "here 17551\n", | |
| "there 17551\n", | |
| "here 17552\n", | |
| "there 17552\n", | |
| "here 17553\n", | |
| "there 17553\n", | |
| "here 17554\n", | |
| "there 17554\n", | |
| "here 17555\n", | |
| "there 17555\n", | |
| "here 17556\n", | |
| "there 17556\n", | |
| "here 17557\n", | |
| "there 17557\n", | |
| "here 17558\n", | |
| "there 17558\n", | |
| "here 17559\n", | |
| "there 17559\n", | |
| "here 17560\n", | |
| "there 17560\n", | |
| "here 17561\n", | |
| "there 17561\n", | |
| "here 17562\n", | |
| "there 17562\n", | |
| "here 17563\n", | |
| "there 17563\n", | |
| "here 17564\n", | |
| "there 17564\n", | |
| "here 17565\n", | |
| "there 17565\n", | |
| "here 17566\n", | |
| "there 17566\n", | |
| "here 17567\n", | |
| "there 17567\n", | |
| "here 17568\n", | |
| "there 17568\n", | |
| "here 17569\n", | |
| "there 17569\n", | |
| "here 17570\n", | |
| "there 17570\n", | |
| "here 17571\n", | |
| "there 17571\n", | |
| "here 17572\n", | |
| "there 17572\n", | |
| "here 17573\n", | |
| "there 17573\n", | |
| "here 17574\n", | |
| "there 17574\n", | |
| "here 17575\n", | |
| "there 17575\n", | |
| "here 17576\n", | |
| "there 17576\n", | |
| "here 17577\n", | |
| "there 17577\n", | |
| "here 17578\n", | |
| "there 17578\n", | |
| "here 17579\n", | |
| "there 17579\n", | |
| "here 17580\n", | |
| "there 17580\n", | |
| "here 17581\n", | |
| "there 17581\n", | |
| "here 17582\n", | |
| "there 17582\n", | |
| "here 17583\n", | |
| "there 17583\n", | |
| "here 17584\n", | |
| "there 17584\n", | |
| "here 17585\n", | |
| "there 17585\n", | |
| "here 17586\n", | |
| "there 17586\n", | |
| "here 17587\n", | |
| "there 17587\n", | |
| "here 17588\n", | |
| "there 17588\n", | |
| "here 17589\n", | |
| "there 17589\n", | |
| "here 17590\n", | |
| "there 17590\n", | |
| "here 17591\n", | |
| "there 17591\n", | |
| "here 17592\n", | |
| "there 17592\n", | |
| "here 17593\n", | |
| "there 17593\n", | |
| "here 17594\n", | |
| "there 17594\n", | |
| "here 17595\n", | |
| "there 17595\n", | |
| "here 17596\n", | |
| "there 17596\n", | |
| "here 17597\n", | |
| "there 17597\n", | |
| "here 17598\n", | |
| "there 17598\n", | |
| "here 17599\n", | |
| "there 17599\n", | |
| "here 17600\n", | |
| "there 17600\n", | |
| "here 17601\n", | |
| "there 17601\n", | |
| "here 17602\n", | |
| "there 17602\n", | |
| "here 17603\n", | |
| "there 17603\n", | |
| "here 17604\n", | |
| "there 17604\n", | |
| "here 17605\n", | |
| "there 17605\n", | |
| "here 17606\n", | |
| "there 17606\n", | |
| "here 17607\n", | |
| "there 17607\n", | |
| "here 17608\n", | |
| "there 17608\n", | |
| "here 17609\n", | |
| "there 17609\n", | |
| "here 17610\n", | |
| "there 17610\n", | |
| "here 17611\n", | |
| "there 17611\n", | |
| "here 17612\n", | |
| "there 17612\n", | |
| "here 17613\n", | |
| "there 17613\n", | |
| "here 17614\n", | |
| "there 17614\n", | |
| "here 17615\n", | |
| "there 17615\n", | |
| "here 17616\n", | |
| "there 17616\n", | |
| "here 17617\n", | |
| "there 17617\n", | |
| "here 17618\n", | |
| "there 17618\n", | |
| "here 17619\n", | |
| "there 17619\n", | |
| "here 17620\n", | |
| "there 17620\n", | |
| "here 17621\n", | |
| "there 17621\n", | |
| "here 17622\n", | |
| "there 17622\n", | |
| "here 17623\n", | |
| "there 17623\n", | |
| "here 17624\n", | |
| "there 17624\n", | |
| "here 17625\n", | |
| "there 17625\n", | |
| "here 17626\n", | |
| "there 17626\n", | |
| "here 17627\n", | |
| "there 17627\n", | |
| "here 17628\n", | |
| "there 17628\n", | |
| "here 17629\n", | |
| "there 17629\n", | |
| "here 17630\n", | |
| "there 17630\n", | |
| "here 17631\n", | |
| "there 17631\n", | |
| "here 17632\n", | |
| "there 17632\n", | |
| "here 17633\n", | |
| "there 17633\n", | |
| "here 17634\n", | |
| "there 17634\n", | |
| "here 17635\n", | |
| "there 17635\n", | |
| "here 17636\n", | |
| "there 17636\n", | |
| "here 17637\n", | |
| "there 17637\n", | |
| "here 17638\n", | |
| "there 17638\n", | |
| "here 17639\n", | |
| "there 17639\n", | |
| "here 17640\n", | |
| "there 17640\n", | |
| "here 17641\n", | |
| "there 17641\n", | |
| "here 17642\n", | |
| "there 17642\n", | |
| "here 17643\n", | |
| "there 17643\n", | |
| "here 17644\n", | |
| "there 17644\n", | |
| "here 17645\n", | |
| "there 17645\n", | |
| "here 17646\n", | |
| "there 17646\n", | |
| "here 17647\n", | |
| "there 17647\n", | |
| "here 17648\n", | |
| "there 17648\n", | |
| "here 17649\n", | |
| "there 17649\n", | |
| "here 17650\n", | |
| "there 17650\n", | |
| "here 17651\n", | |
| "there 17651\n", | |
| "here 17652\n", | |
| "there 17652\n", | |
| "here 17653\n", | |
| "there 17653\n", | |
| "here 17654\n", | |
| "there 17654\n", | |
| "here 17655\n", | |
| "there 17655\n", | |
| "here 17656\n", | |
| "there 17656\n", | |
| "here 17657\n", | |
| "there 17657\n", | |
| "here 17658\n", | |
| "there 17658\n", | |
| "here 17659\n", | |
| "there 17659\n", | |
| "here 17660\n", | |
| "there 17660\n", | |
| "here 17661\n", | |
| "there 17661\n", | |
| "here 17662\n", | |
| "there 17662\n", | |
| "here 17663\n", | |
| "there 17663\n", | |
| "here 17664\n", | |
| "there 17664\n", | |
| "here 17665\n", | |
| "there 17665\n", | |
| "here 17666\n", | |
| "there 17666\n", | |
| "here 17667\n", | |
| "there 17667\n", | |
| "here 17668\n", | |
| "there 17668\n", | |
| "here 17669\n", | |
| "there 17669\n", | |
| "here 17670\n", | |
| "there 17670\n", | |
| "here 17671\n", | |
| "there 17671\n", | |
| "here 17672\n", | |
| "there 17672\n", | |
| "here 17673\n", | |
| "there 17673\n", | |
| "here 17674\n", | |
| "there 17674\n", | |
| "here 17675\n", | |
| "there 17675\n", | |
| "here 17676\n", | |
| "there 17676\n", | |
| "here 17677\n", | |
| "there 17677\n", | |
| "here 17678\n", | |
| "there 17678\n", | |
| "here 17679\n", | |
| "there 17679\n", | |
| "here 17680\n", | |
| "there 17680\n", | |
| "here 17681\n", | |
| "there 17681\n", | |
| "here 17682\n", | |
| "there 17682\n", | |
| "here 17683\n", | |
| "there 17683\n", | |
| "here 17684\n", | |
| "there 17684\n", | |
| "here 17685\n", | |
| "there 17685\n", | |
| "here 17686\n", | |
| "there 17686\n", | |
| "here 17687\n", | |
| "there 17687\n", | |
| "here 17688\n", | |
| "there 17688\n", | |
| "here 17689\n", | |
| "there 17689\n", | |
| "here 17690\n", | |
| "there 17690\n", | |
| "here 17691\n", | |
| "there 17691\n", | |
| "here 17692\n", | |
| "there 17692\n", | |
| "here 17693\n", | |
| "there 17693\n", | |
| "here 17694\n", | |
| "there 17694\n", | |
| "here 17695\n", | |
| "there 17695\n", | |
| "here 17696\n", | |
| "there 17696\n", | |
| "here 17697\n", | |
| "there 17697\n", | |
| "here 17698\n", | |
| "there 17698\n", | |
| "here 17699\n", | |
| "there 17699\n", | |
| "here 17700\n", | |
| "there 17700\n", | |
| "here 17701\n", | |
| "there 17701\n", | |
| "here 17702\n", | |
| "there 17702\n", | |
| "here 17703\n", | |
| "there 17703\n", | |
| "here 17704\n", | |
| "there 17704\n", | |
| "here 17705\n", | |
| "there 17705\n", | |
| "here 17706\n", | |
| "there 17706\n", | |
| "here 17707\n", | |
| "there 17707\n", | |
| "here 17708\n", | |
| "there 17708\n", | |
| "here 17709\n", | |
| "there 17709\n", | |
| "here 17710\n", | |
| "there 17710\n", | |
| "here 17711\n", | |
| "there 17711\n", | |
| "here 17712\n", | |
| "there 17712\n", | |
| "here 17713\n", | |
| "there 17713\n", | |
| "here 17714\n", | |
| "there 17714\n", | |
| "here 17715\n", | |
| "there 17715\n", | |
| "here 17716\n", | |
| "there 17716\n", | |
| "here 17717\n", | |
| "there 17717\n", | |
| "here 17718\n", | |
| "there 17718\n", | |
| "here 17719\n", | |
| "there 17719\n", | |
| "here 17720\n", | |
| "there 17720\n", | |
| "here 17721\n", | |
| "there 17721\n", | |
| "here 17722\n", | |
| "there 17722\n", | |
| "here 17723\n", | |
| "there 17723\n", | |
| "here 17724\n", | |
| "there 17724\n", | |
| "here 17725\n", | |
| "there 17725\n", | |
| "here 17726\n", | |
| "there 17726\n", | |
| "here 17727\n", | |
| "there 17727\n", | |
| "here 17728\n", | |
| "there 17728\n", | |
| "here 17729\n", | |
| "there 17729\n", | |
| "here 17730\n", | |
| "there 17730\n", | |
| "here 17731\n", | |
| "there 17731\n", | |
| "here 17732\n", | |
| "there 17732\n", | |
| "here 17733\n", | |
| "there 17733\n", | |
| "here 17734\n", | |
| "there 17734\n", | |
| "here 17735\n", | |
| "there 17735\n", | |
| "here 17736\n", | |
| "there 17736\n", | |
| "here 17737\n", | |
| "there 17737\n", | |
| "here 17738\n", | |
| "there 17738\n", | |
| "here 17739\n", | |
| "there 17739\n", | |
| "here 17740\n", | |
| "there 17740\n", | |
| "here 17741\n", | |
| "there 17741\n", | |
| "here 17742\n", | |
| "there 17742\n", | |
| "here 17743\n", | |
| "there 17743\n", | |
| "here 17744\n", | |
| "there 17744\n", | |
| "here 17745\n", | |
| "there 17745\n", | |
| "here 17746\n", | |
| "there 17746\n", | |
| "here 17747\n", | |
| "there 17747\n", | |
| "here 17748\n", | |
| "there 17748\n", | |
| "here 17749\n", | |
| "there 17749\n", | |
| "here 17750\n", | |
| "there 17750\n", | |
| "here 17751\n", | |
| "there 17751\n", | |
| "here 17752\n", | |
| "there 17752\n", | |
| "here 17753\n", | |
| "there 17753\n", | |
| "here 17754\n", | |
| "there 17754\n", | |
| "here 17755\n", | |
| "there 17755\n", | |
| "here 17756\n", | |
| "there 17756\n", | |
| "here 17757\n", | |
| "there 17757\n", | |
| "here 17758\n", | |
| "there 17758\n", | |
| "here 17759\n", | |
| "there 17759\n", | |
| "here 17760\n", | |
| "there 17760\n", | |
| "here 17761\n", | |
| "there 17761\n", | |
| "here 17762\n", | |
| "there 17762\n", | |
| "here 17763\n", | |
| "there 17763\n", | |
| "here 17764\n", | |
| "there 17764\n", | |
| "here 17765\n", | |
| "there 17765\n", | |
| "here 17766\n", | |
| "there 17766\n", | |
| "here 17767\n", | |
| "there 17767\n", | |
| "here 17768\n", | |
| "there 17768\n", | |
| "here 17769\n", | |
| "there 17769\n", | |
| "here 17770\n", | |
| "there 17770\n", | |
| "here 17771\n", | |
| "there 17771\n", | |
| "here 17772\n", | |
| "there 17772\n", | |
| "here 17773\n", | |
| "there 17773\n", | |
| "here 17774\n", | |
| "there 17774\n", | |
| "here 17775\n", | |
| "there 17775\n", | |
| "here 17776\n", | |
| "there 17776\n", | |
| "here 17777\n", | |
| "there 17777\n", | |
| "here 17778\n", | |
| "there 17778\n", | |
| "here 17779\n", | |
| "there 17779\n", | |
| "here 17780\n", | |
| "there 17780\n", | |
| "here 17781\n", | |
| "there 17781\n", | |
| "here 17782\n", | |
| "there 17782\n", | |
| "here 17783\n", | |
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| "there 19141\n", | |
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| "there 19426\n", | |
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| "there 19431\n", | |
| "here 19432\n", | |
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| "here 19433\n", | |
| "there 19433\n", | |
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| "there 19439\n", | |
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| "there 19440\n", | |
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| "there 19441\n", | |
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| "there 19442\n", | |
| "here 19443\n", | |
| "there 19443\n", | |
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| "there 19444\n", | |
| "here 19445\n", | |
| "there 19445\n", | |
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| "there 19448\n", | |
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| "there 19449\n", | |
| "here 19450\n", | |
| "there 19450\n", | |
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| "there 19451\n", | |
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| "there 19452\n", | |
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| "there 19453\n", | |
| "here 19454\n", | |
| "there 19454\n", | |
| "here 19455\n", | |
| "there 19455\n", | |
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| "there 19457\n", | |
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| "there 19458\n", | |
| "here 19459\n", | |
| "there 19459\n", | |
| "here 19460\n", | |
| "there 19460\n", | |
| "here 19461\n", | |
| "there 19461\n", | |
| "here 19462\n", | |
| "there 19462\n", | |
| "here 19463\n", | |
| "there 19463\n", | |
| "here 19464\n", | |
| "there 19464\n", | |
| "here 19465\n", | |
| "there 19465\n", | |
| "here 19466\n", | |
| "there 19466\n", | |
| "here 19467\n", | |
| "there 19467\n", | |
| "here 19468\n", | |
| "there 19468\n", | |
| "here 19469\n", | |
| "there 19469\n", | |
| "here 19470\n", | |
| "there 19470\n", | |
| "here 19471\n", | |
| "there 19471\n", | |
| "here 19472\n", | |
| "there 19472\n", | |
| "here 19473\n", | |
| "there 19473\n", | |
| "here 19474\n", | |
| "there 19474\n", | |
| "here 19475\n", | |
| "there 19475\n", | |
| "here 19476\n", | |
| "there 19476\n", | |
| "here 19477\n", | |
| "there 19477\n", | |
| "here 19478\n", | |
| "there 19478\n", | |
| "here 19479\n", | |
| "there 19479\n", | |
| "here 19480\n", | |
| "there 19480\n", | |
| "here 19481\n", | |
| "there 19481\n", | |
| "here 19482\n", | |
| "there 19482\n", | |
| "here 19483\n", | |
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| "there 19488\n", | |
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| "there 19490\n", | |
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| "here 19495\n", | |
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| "here 19760\n", | |
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| "here 19764\n", | |
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| "there 19774\n", | |
| "here 19775\n", | |
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| "here 19780\n", | |
| "there 19780\n", | |
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| "here 19784\n", | |
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| "there 19789\n", | |
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| "there 19790\n", | |
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| "here 19794\n", | |
| "there 19794\n", | |
| "here 19795\n", | |
| "there 19795\n", | |
| "here 19796\n", | |
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| "there 19798\n", | |
| "here 19799\n", | |
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| "here 19800\n", | |
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| "there 19804\n", | |
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| "here 19806\n", | |
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| "there 19807\n", | |
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| "there 19808\n", | |
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| "there 19809\n", | |
| "here 19810\n", | |
| "there 19810\n", | |
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| "there 19811\n", | |
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| "there 19812\n", | |
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| "there 19813\n", | |
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| "there 19814\n", | |
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| "there 19816\n", | |
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| "there 19817\n", | |
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| "there 19818\n", | |
| "here 19819\n", | |
| "there 19819\n", | |
| "here 19820\n", | |
| "there 19820\n", | |
| "here 19821\n", | |
| "there 19821\n", | |
| "here 19822\n", | |
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| "here 20000\n", | |
| "there 20000\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 293 | |
| }, | |
| "id": "Kyo3bGBRGpor", | |
| "outputId": "b058a3c6-39b1-4ab3-f091-4a22a661f18e" | |
| }, | |
| "source": [ | |
| "plt.plot(Z___1,f_rab)\n", | |
| "\n" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7fbe8c3bbd90>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 91 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 293 | |
| }, | |
| "id": "FNUCtnqPGwTf", | |
| "outputId": "675e4aaf-bb4b-42b9-9c43-3c8192eb732b" | |
| }, | |
| "source": [ | |
| "plt.plot(Z___2,f_rab)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7fbe8d23ab90>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 92 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "--FmYa_oQYAV", | |
| "outputId": "5aac740c-00b5-43ac-f8e7-384c512d8014" | |
| }, | |
| "source": [ | |
| "f_rab[np.argmax(Z__2)]\n" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "20.58463944" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 93 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "StrSjK24QhGR" | |
| }, | |
| "source": [ | |
| "Above is for the frequency obtained in the 0.001 given in the short list determined earlier not let us try the more assignment friendly values" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "gsw5du7hQdSi", | |
| "outputId": "eabfa39a-8738-44f4-eb37-8da5de41bdc4" | |
| }, | |
| "source": [ | |
| "nt2=n_terms(0.0001,1E-8)\n", | |
| "nt2\n", | |
| "f_rab=np.linspace(freq-0.0001,freq+0.0001,np.int(nt2))\n", | |
| "f_rab\n", | |
| "#f_r_=np.linspace(freq-0.0001,freq+0.0001,nt2)\n", | |
| "#f_r_" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "array([20.58501983, 20.58501984, 20.58501985, ..., 20.58521981,\n", | |
| " 20.58521982, 20.58521983])" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 94 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "e_LMpjBfRDhA", | |
| "outputId": "7503dc72-35d7-4d2b-9c01-277984b37cc8" | |
| }, | |
| "source": [ | |
| "Z___1=[]\n", | |
| "Z___2=[]\n", | |
| "for i in range(0,np.int(nt2)):\n", | |
| " print('here',i)\n", | |
| " a_=taylor(f_rab[i])\n", | |
| " l_,m_=Zstat(a_)\n", | |
| " #print(l,m)\n", | |
| " print('there',i)\n", | |
| " Z___1.append(l_)\n", | |
| " Z___2.append(m_)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n", | |
| "here 17501\n", | |
| "there 17501\n", | |
| "here 17502\n", | |
| "there 17502\n", | |
| "here 17503\n", | |
| "there 17503\n", | |
| "here 17504\n", | |
| "there 17504\n", | |
| "here 17505\n", | |
| "there 17505\n", | |
| "here 17506\n", | |
| "there 17506\n", | |
| "here 17507\n", | |
| "there 17507\n", | |
| "here 17508\n", | |
| "there 17508\n", | |
| "here 17509\n", | |
| "there 17509\n", | |
| "here 17510\n", | |
| "there 17510\n", | |
| "here 17511\n", | |
| "there 17511\n", | |
| "here 17512\n", | |
| "there 17512\n", | |
| "here 17513\n", | |
| "there 17513\n", | |
| "here 17514\n", | |
| "there 17514\n", | |
| "here 17515\n", | |
| "there 17515\n", | |
| "here 17516\n", | |
| "there 17516\n", | |
| "here 17517\n", | |
| "there 17517\n", | |
| "here 17518\n", | |
| "there 17518\n", | |
| "here 17519\n", | |
| "there 17519\n", | |
| "here 17520\n", | |
| "there 17520\n", | |
| "here 17521\n", | |
| "there 17521\n", | |
| "here 17522\n", | |
| "there 17522\n", | |
| "here 17523\n", | |
| "there 17523\n", | |
| "here 17524\n", | |
| "there 17524\n", | |
| "here 17525\n", | |
| "there 17525\n", | |
| "here 17526\n", | |
| "there 17526\n", | |
| "here 17527\n", | |
| "there 17527\n", | |
| "here 17528\n", | |
| "there 17528\n", | |
| "here 17529\n", | |
| "there 17529\n", | |
| "here 17530\n", | |
| "there 17530\n", | |
| "here 17531\n", | |
| "there 17531\n", | |
| "here 17532\n", | |
| "there 17532\n", | |
| "here 17533\n", | |
| "there 17533\n", | |
| "here 17534\n", | |
| "there 17534\n", | |
| "here 17535\n", | |
| "there 17535\n", | |
| "here 17536\n", | |
| "there 17536\n", | |
| "here 17537\n", | |
| "there 17537\n", | |
| "here 17538\n", | |
| "there 17538\n", | |
| "here 17539\n", | |
| "there 17539\n", | |
| "here 17540\n", | |
| "there 17540\n", | |
| "here 17541\n", | |
| "there 17541\n", | |
| "here 17542\n", | |
| "there 17542\n", | |
| "here 17543\n", | |
| "there 17543\n", | |
| "here 17544\n", | |
| "there 17544\n", | |
| "here 17545\n", | |
| "there 17545\n", | |
| "here 17546\n", | |
| "there 17546\n", | |
| "here 17547\n", | |
| "there 17547\n", | |
| "here 17548\n", | |
| "there 17548\n", | |
| "here 17549\n", | |
| "there 17549\n", | |
| "here 17550\n", | |
| "there 17550\n", | |
| "here 17551\n", | |
| "there 17551\n", | |
| "here 17552\n", | |
| "there 17552\n", | |
| "here 17553\n", | |
| "there 17553\n", | |
| "here 17554\n", | |
| "there 17554\n", | |
| "here 17555\n", | |
| "there 17555\n", | |
| "here 17556\n", | |
| "there 17556\n", | |
| "here 17557\n", | |
| "there 17557\n", | |
| "here 17558\n", | |
| "there 17558\n", | |
| "here 17559\n", | |
| "there 17559\n", | |
| "here 17560\n", | |
| "there 17560\n", | |
| "here 17561\n", | |
| "there 17561\n", | |
| "here 17562\n", | |
| "there 17562\n", | |
| "here 17563\n", | |
| "there 17563\n", | |
| "here 17564\n", | |
| "there 17564\n", | |
| "here 17565\n", | |
| "there 17565\n", | |
| "here 17566\n", | |
| "there 17566\n", | |
| "here 17567\n", | |
| "there 17567\n", | |
| "here 17568\n", | |
| "there 17568\n", | |
| "here 17569\n", | |
| "there 17569\n", | |
| "here 17570\n", | |
| "there 17570\n", | |
| "here 17571\n", | |
| "there 17571\n", | |
| "here 17572\n", | |
| "there 17572\n", | |
| "here 17573\n", | |
| "there 17573\n", | |
| "here 17574\n", | |
| "there 17574\n", | |
| "here 17575\n", | |
| "there 17575\n", | |
| "here 17576\n", | |
| "there 17576\n", | |
| "here 17577\n", | |
| "there 17577\n", | |
| "here 17578\n", | |
| "there 17578\n", | |
| "here 17579\n", | |
| "there 17579\n", | |
| "here 17580\n", | |
| "there 17580\n", | |
| "here 17581\n", | |
| "there 17581\n", | |
| "here 17582\n", | |
| "there 17582\n", | |
| "here 17583\n", | |
| "there 17583\n", | |
| "here 17584\n", | |
| "there 17584\n", | |
| "here 17585\n", | |
| "there 17585\n", | |
| "here 17586\n", | |
| "there 17586\n", | |
| "here 17587\n", | |
| "there 17587\n", | |
| "here 17588\n", | |
| "there 17588\n", | |
| "here 17589\n", | |
| "there 17589\n", | |
| "here 17590\n", | |
| "there 17590\n", | |
| "here 17591\n", | |
| "there 17591\n", | |
| "here 17592\n", | |
| "there 17592\n", | |
| "here 17593\n", | |
| "there 17593\n", | |
| "here 17594\n", | |
| "there 17594\n", | |
| "here 17595\n", | |
| "there 17595\n", | |
| "here 17596\n", | |
| "there 17596\n", | |
| "here 17597\n", | |
| "there 17597\n", | |
| "here 17598\n", | |
| "there 17598\n", | |
| "here 17599\n", | |
| "there 17599\n", | |
| "here 17600\n", | |
| "there 17600\n", | |
| "here 17601\n", | |
| "there 17601\n", | |
| "here 17602\n", | |
| "there 17602\n", | |
| "here 17603\n", | |
| "there 17603\n", | |
| "here 17604\n", | |
| "there 17604\n", | |
| "here 17605\n", | |
| "there 17605\n", | |
| "here 17606\n", | |
| "there 17606\n", | |
| "here 17607\n", | |
| "there 17607\n", | |
| "here 17608\n", | |
| "there 17608\n", | |
| "here 17609\n", | |
| "there 17609\n", | |
| "here 17610\n", | |
| "there 17610\n", | |
| "here 17611\n", | |
| "there 17611\n", | |
| "here 17612\n", | |
| "there 17612\n", | |
| "here 17613\n", | |
| "there 17613\n", | |
| "here 17614\n", | |
| "there 17614\n", | |
| "here 17615\n", | |
| "there 17615\n", | |
| "here 17616\n", | |
| "there 17616\n", | |
| "here 17617\n", | |
| "there 17617\n", | |
| "here 17618\n", | |
| "there 17618\n", | |
| "here 17619\n", | |
| "there 17619\n", | |
| "here 17620\n", | |
| "there 17620\n", | |
| "here 17621\n", | |
| "there 17621\n", | |
| "here 17622\n", | |
| "there 17622\n", | |
| "here 17623\n", | |
| "there 17623\n", | |
| "here 17624\n", | |
| "there 17624\n", | |
| "here 17625\n", | |
| "there 17625\n", | |
| "here 17626\n", | |
| "there 17626\n", | |
| "here 17627\n", | |
| "there 17627\n", | |
| "here 17628\n", | |
| "there 17628\n", | |
| "here 17629\n", | |
| "there 17629\n", | |
| "here 17630\n", | |
| "there 17630\n", | |
| "here 17631\n", | |
| "there 17631\n", | |
| "here 17632\n", | |
| "there 17632\n", | |
| "here 17633\n", | |
| "there 17633\n", | |
| "here 17634\n", | |
| "there 17634\n", | |
| "here 17635\n", | |
| "there 17635\n", | |
| "here 17636\n", | |
| "there 17636\n", | |
| "here 17637\n", | |
| "there 17637\n", | |
| "here 17638\n", | |
| "there 17638\n", | |
| "here 17639\n", | |
| "there 17639\n", | |
| "here 17640\n", | |
| "there 17640\n", | |
| "here 17641\n", | |
| "there 17641\n", | |
| "here 17642\n", | |
| "there 17642\n", | |
| "here 17643\n", | |
| "there 17643\n", | |
| "here 17644\n", | |
| "there 17644\n", | |
| "here 17645\n", | |
| "there 17645\n", | |
| "here 17646\n", | |
| "there 17646\n", | |
| "here 17647\n", | |
| "there 17647\n", | |
| "here 17648\n", | |
| "there 17648\n", | |
| "here 17649\n", | |
| "there 17649\n", | |
| "here 17650\n", | |
| "there 17650\n", | |
| "here 17651\n", | |
| "there 17651\n", | |
| "here 17652\n", | |
| "there 17652\n", | |
| "here 17653\n", | |
| "there 17653\n", | |
| "here 17654\n", | |
| "there 17654\n", | |
| "here 17655\n", | |
| "there 17655\n", | |
| "here 17656\n", | |
| "there 17656\n", | |
| "here 17657\n", | |
| "there 17657\n", | |
| "here 17658\n", | |
| "there 17658\n", | |
| "here 17659\n", | |
| "there 17659\n", | |
| "here 17660\n", | |
| "there 17660\n", | |
| "here 17661\n", | |
| "there 17661\n", | |
| "here 17662\n", | |
| "there 17662\n", | |
| "here 17663\n", | |
| "there 17663\n", | |
| "here 17664\n", | |
| "there 17664\n", | |
| "here 17665\n", | |
| "there 17665\n", | |
| "here 17666\n", | |
| "there 17666\n", | |
| "here 17667\n", | |
| "there 17667\n", | |
| "here 17668\n", | |
| "there 17668\n", | |
| "here 17669\n", | |
| "there 17669\n", | |
| "here 17670\n", | |
| "there 17670\n", | |
| "here 17671\n", | |
| "there 17671\n", | |
| "here 17672\n", | |
| "there 17672\n", | |
| "here 17673\n", | |
| "there 17673\n", | |
| "here 17674\n", | |
| "there 17674\n", | |
| "here 17675\n", | |
| "there 17675\n", | |
| "here 17676\n", | |
| "there 17676\n", | |
| "here 17677\n", | |
| "there 17677\n", | |
| "here 17678\n", | |
| "there 17678\n", | |
| "here 17679\n", | |
| "there 17679\n", | |
| "here 17680\n", | |
| "there 17680\n", | |
| "here 17681\n", | |
| "there 17681\n", | |
| "here 17682\n", | |
| "there 17682\n", | |
| "here 17683\n", | |
| "there 17683\n", | |
| "here 17684\n", | |
| "there 17684\n", | |
| "here 17685\n", | |
| "there 17685\n", | |
| "here 17686\n", | |
| "there 17686\n", | |
| "here 17687\n", | |
| "there 17687\n", | |
| "here 17688\n", | |
| "there 17688\n", | |
| "here 17689\n", | |
| "there 17689\n", | |
| "here 17690\n", | |
| "there 17690\n", | |
| "here 17691\n", | |
| "there 17691\n", | |
| "here 17692\n", | |
| "there 17692\n", | |
| "here 17693\n", | |
| "there 17693\n", | |
| "here 17694\n", | |
| "there 17694\n", | |
| "here 17695\n", | |
| "there 17695\n", | |
| "here 17696\n", | |
| "there 17696\n", | |
| "here 17697\n", | |
| "there 17697\n", | |
| "here 17698\n", | |
| "there 17698\n", | |
| "here 17699\n", | |
| "there 17699\n", | |
| "here 17700\n", | |
| "there 17700\n", | |
| "here 17701\n", | |
| "there 17701\n", | |
| "here 17702\n", | |
| "there 17702\n", | |
| "here 17703\n", | |
| "there 17703\n", | |
| "here 17704\n", | |
| "there 17704\n", | |
| "here 17705\n", | |
| "there 17705\n", | |
| "here 17706\n", | |
| "there 17706\n", | |
| "here 17707\n", | |
| "there 17707\n", | |
| "here 17708\n", | |
| "there 17708\n", | |
| "here 17709\n", | |
| "there 17709\n", | |
| "here 17710\n", | |
| "there 17710\n", | |
| "here 17711\n", | |
| "there 17711\n", | |
| "here 17712\n", | |
| "there 17712\n", | |
| "here 17713\n", | |
| "there 17713\n", | |
| "here 17714\n", | |
| "there 17714\n", | |
| "here 17715\n", | |
| "there 17715\n", | |
| "here 17716\n", | |
| "there 17716\n", | |
| "here 17717\n", | |
| "there 17717\n", | |
| "here 17718\n", | |
| "there 17718\n", | |
| "here 17719\n", | |
| "there 17719\n", | |
| "here 17720\n", | |
| "there 17720\n", | |
| "here 17721\n", | |
| "there 17721\n", | |
| "here 17722\n", | |
| "there 17722\n", | |
| "here 17723\n", | |
| "there 17723\n", | |
| "here 17724\n", | |
| "there 17724\n", | |
| "here 17725\n", | |
| "there 17725\n", | |
| "here 17726\n", | |
| "there 17726\n", | |
| "here 17727\n", | |
| "there 17727\n", | |
| "here 17728\n", | |
| "there 17728\n", | |
| "here 17729\n", | |
| "there 17729\n", | |
| "here 17730\n", | |
| "there 17730\n", | |
| "here 17731\n", | |
| "there 17731\n", | |
| "here 17732\n", | |
| "there 17732\n", | |
| "here 17733\n", | |
| "there 17733\n", | |
| "here 17734\n", | |
| "there 17734\n", | |
| "here 17735\n", | |
| "there 17735\n", | |
| "here 17736\n", | |
| "there 17736\n", | |
| "here 17737\n", | |
| "there 17737\n", | |
| "here 17738\n", | |
| "there 17738\n", | |
| "here 17739\n", | |
| "there 17739\n", | |
| "here 17740\n", | |
| "there 17740\n", | |
| "here 17741\n", | |
| "there 17741\n", | |
| "here 17742\n", | |
| "there 17742\n", | |
| "here 17743\n", | |
| "there 17743\n", | |
| "here 17744\n", | |
| "there 17744\n", | |
| "here 17745\n", | |
| "there 17745\n", | |
| "here 17746\n", | |
| "there 17746\n", | |
| "here 17747\n", | |
| "there 17747\n", | |
| "here 17748\n", | |
| "there 17748\n", | |
| "here 17749\n", | |
| "there 17749\n", | |
| "here 17750\n", | |
| "there 17750\n", | |
| "here 17751\n", | |
| "there 17751\n", | |
| "here 17752\n", | |
| "there 17752\n", | |
| "here 17753\n", | |
| "there 17753\n", | |
| "here 17754\n", | |
| "there 17754\n", | |
| "here 17755\n", | |
| "there 17755\n", | |
| "here 17756\n", | |
| "there 17756\n", | |
| "here 17757\n", | |
| "there 17757\n", | |
| "here 17758\n", | |
| "there 17758\n", | |
| "here 17759\n", | |
| "there 17759\n", | |
| "here 17760\n", | |
| "there 17760\n", | |
| "here 17761\n", | |
| "there 17761\n", | |
| "here 17762\n", | |
| "there 17762\n", | |
| "here 17763\n", | |
| "there 17763\n", | |
| "here 17764\n", | |
| "there 17764\n", | |
| "here 17765\n", | |
| "there 17765\n", | |
| "here 17766\n", | |
| "there 17766\n", | |
| "here 17767\n", | |
| "there 17767\n", | |
| "here 17768\n", | |
| "there 17768\n", | |
| "here 17769\n", | |
| "there 17769\n", | |
| "here 17770\n", | |
| "there 17770\n", | |
| "here 17771\n", | |
| "there 17771\n", | |
| "here 17772\n", | |
| "there 17772\n", | |
| "here 17773\n", | |
| "there 17773\n", | |
| "here 17774\n", | |
| "there 17774\n", | |
| "here 17775\n", | |
| "there 17775\n", | |
| "here 17776\n", | |
| "there 17776\n", | |
| "here 17777\n", | |
| "there 17777\n", | |
| "here 17778\n", | |
| "there 17778\n", | |
| "here 17779\n", | |
| "there 17779\n", | |
| "here 17780\n", | |
| "there 17780\n", | |
| "here 17781\n", | |
| "there 17781\n", | |
| "here 17782\n", | |
| "there 17782\n", | |
| "here 17783\n", | |
| "there 17783\n", | |
| "here 17784\n", | |
| "there 17784\n", | |
| "here 17785\n", | |
| "there 17785\n", | |
| "here 17786\n", | |
| "there 17786\n", | |
| "here 17787\n", | |
| "there 17787\n", | |
| "here 17788\n", | |
| "there 17788\n", | |
| "here 17789\n", | |
| "there 17789\n", | |
| "here 17790\n", | |
| "there 17790\n", | |
| "here 17791\n", | |
| "there 17791\n", | |
| "here 17792\n", | |
| "there 17792\n", | |
| "here 17793\n", | |
| "there 17793\n", | |
| "here 17794\n", | |
| "there 17794\n", | |
| "here 17795\n", | |
| "there 17795\n", | |
| "here 17796\n", | |
| "there 17796\n", | |
| "here 17797\n", | |
| "there 17797\n", | |
| "here 17798\n", | |
| "there 17798\n", | |
| "here 17799\n", | |
| "there 17799\n", | |
| "here 17800\n", | |
| "there 17800\n", | |
| "here 17801\n", | |
| "there 17801\n", | |
| "here 17802\n", | |
| "there 17802\n", | |
| "here 17803\n", | |
| "there 17803\n", | |
| "here 17804\n", | |
| "there 17804\n", | |
| "here 17805\n", | |
| "there 17805\n", | |
| "here 17806\n", | |
| "there 17806\n", | |
| "here 17807\n", | |
| "there 17807\n", | |
| "here 17808\n", | |
| "there 17808\n", | |
| "here 17809\n", | |
| "there 17809\n", | |
| "here 17810\n", | |
| "there 17810\n", | |
| "here 17811\n", | |
| "there 17811\n", | |
| "here 17812\n", | |
| "there 17812\n", | |
| "here 17813\n", | |
| "there 17813\n", | |
| "here 17814\n", | |
| "there 17814\n", | |
| "here 17815\n", | |
| "there 17815\n", | |
| "here 17816\n", | |
| "there 17816\n", | |
| "here 17817\n", | |
| "there 17817\n", | |
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| "here 19494\n", | |
| "there 19494\n", | |
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| "there 19495\n", | |
| "here 19496\n", | |
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| "there 19498\n", | |
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| "there 19499\n", | |
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| "there 19503\n", | |
| "here 19504\n", | |
| "there 19504\n", | |
| "here 19505\n", | |
| "there 19505\n", | |
| "here 19506\n", | |
| "there 19506\n", | |
| "here 19507\n", | |
| "there 19507\n", | |
| "here 19508\n", | |
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| "here 19513\n", | |
| "there 19513\n", | |
| "here 19514\n", | |
| "there 19514\n", | |
| "here 19515\n", | |
| "there 19515\n", | |
| "here 19516\n", | |
| "there 19516\n", | |
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| "here 19857\n", | |
| "there 19857\n", | |
| "here 19858\n", | |
| "there 19858\n", | |
| "here 19859\n", | |
| "there 19859\n", | |
| "here 19860\n", | |
| "there 19860\n", | |
| "here 19861\n", | |
| "there 19861\n", | |
| "here 19862\n", | |
| "there 19862\n", | |
| "here 19863\n", | |
| "there 19863\n", | |
| "here 19864\n", | |
| "there 19864\n", | |
| "here 19865\n", | |
| "there 19865\n", | |
| "here 19866\n", | |
| "there 19866\n", | |
| "here 19867\n", | |
| "there 19867\n", | |
| "here 19868\n", | |
| "there 19868\n", | |
| "here 19869\n", | |
| "there 19869\n", | |
| "here 19870\n", | |
| "there 19870\n", | |
| "here 19871\n", | |
| "there 19871\n", | |
| "here 19872\n", | |
| "there 19872\n", | |
| "here 19873\n", | |
| "there 19873\n", | |
| "here 19874\n", | |
| "there 19874\n", | |
| "here 19875\n", | |
| "there 19875\n", | |
| "here 19876\n", | |
| "there 19876\n", | |
| "here 19877\n", | |
| "there 19877\n", | |
| "here 19878\n", | |
| "there 19878\n", | |
| "here 19879\n", | |
| "there 19879\n", | |
| "here 19880\n", | |
| "there 19880\n", | |
| "here 19881\n", | |
| "there 19881\n", | |
| "here 19882\n", | |
| "there 19882\n", | |
| "here 19883\n", | |
| "there 19883\n", | |
| "here 19884\n", | |
| "there 19884\n", | |
| "here 19885\n", | |
| "there 19885\n", | |
| "here 19886\n", | |
| "there 19886\n", | |
| "here 19887\n", | |
| "there 19887\n", | |
| "here 19888\n", | |
| "there 19888\n", | |
| "here 19889\n", | |
| "there 19889\n", | |
| "here 19890\n", | |
| "there 19890\n", | |
| "here 19891\n", | |
| "there 19891\n", | |
| "here 19892\n", | |
| "there 19892\n", | |
| "here 19893\n", | |
| "there 19893\n", | |
| "here 19894\n", | |
| "there 19894\n", | |
| "here 19895\n", | |
| "there 19895\n", | |
| "here 19896\n", | |
| "there 19896\n", | |
| "here 19897\n", | |
| "there 19897\n", | |
| "here 19898\n", | |
| "there 19898\n", | |
| "here 19899\n", | |
| "there 19899\n", | |
| "here 19900\n", | |
| "there 19900\n", | |
| "here 19901\n", | |
| "there 19901\n", | |
| "here 19902\n", | |
| "there 19902\n", | |
| "here 19903\n", | |
| "there 19903\n", | |
| "here 19904\n", | |
| "there 19904\n", | |
| "here 19905\n", | |
| "there 19905\n", | |
| "here 19906\n", | |
| "there 19906\n", | |
| "here 19907\n", | |
| "there 19907\n", | |
| "here 19908\n", | |
| "there 19908\n", | |
| "here 19909\n", | |
| "there 19909\n", | |
| "here 19910\n", | |
| "there 19910\n", | |
| "here 19911\n", | |
| "there 19911\n", | |
| "here 19912\n", | |
| "there 19912\n", | |
| "here 19913\n", | |
| "there 19913\n", | |
| "here 19914\n", | |
| "there 19914\n", | |
| "here 19915\n", | |
| "there 19915\n", | |
| "here 19916\n", | |
| "there 19916\n", | |
| "here 19917\n", | |
| "there 19917\n", | |
| "here 19918\n", | |
| "there 19918\n", | |
| "here 19919\n", | |
| "there 19919\n", | |
| "here 19920\n", | |
| "there 19920\n", | |
| "here 19921\n", | |
| "there 19921\n", | |
| "here 19922\n", | |
| "there 19922\n", | |
| "here 19923\n", | |
| "there 19923\n", | |
| "here 19924\n", | |
| "there 19924\n", | |
| "here 19925\n", | |
| "there 19925\n", | |
| "here 19926\n", | |
| "there 19926\n", | |
| "here 19927\n", | |
| "there 19927\n", | |
| "here 19928\n", | |
| "there 19928\n", | |
| "here 19929\n", | |
| "there 19929\n", | |
| "here 19930\n", | |
| "there 19930\n", | |
| "here 19931\n", | |
| "there 19931\n", | |
| "here 19932\n", | |
| "there 19932\n", | |
| "here 19933\n", | |
| "there 19933\n", | |
| "here 19934\n", | |
| "there 19934\n", | |
| "here 19935\n", | |
| "there 19935\n", | |
| "here 19936\n", | |
| "there 19936\n", | |
| "here 19937\n", | |
| "there 19937\n", | |
| "here 19938\n", | |
| "there 19938\n", | |
| "here 19939\n", | |
| "there 19939\n", | |
| "here 19940\n", | |
| "there 19940\n", | |
| "here 19941\n", | |
| "there 19941\n", | |
| "here 19942\n", | |
| "there 19942\n", | |
| "here 19943\n", | |
| "there 19943\n", | |
| "here 19944\n", | |
| "there 19944\n", | |
| "here 19945\n", | |
| "there 19945\n", | |
| "here 19946\n", | |
| "there 19946\n", | |
| "here 19947\n", | |
| "there 19947\n", | |
| "here 19948\n", | |
| "there 19948\n", | |
| "here 19949\n", | |
| "there 19949\n", | |
| "here 19950\n", | |
| "there 19950\n", | |
| "here 19951\n", | |
| "there 19951\n", | |
| "here 19952\n", | |
| "there 19952\n", | |
| "here 19953\n", | |
| "there 19953\n", | |
| "here 19954\n", | |
| "there 19954\n", | |
| "here 19955\n", | |
| "there 19955\n", | |
| "here 19956\n", | |
| "there 19956\n", | |
| "here 19957\n", | |
| "there 19957\n", | |
| "here 19958\n", | |
| "there 19958\n", | |
| "here 19959\n", | |
| "there 19959\n", | |
| "here 19960\n", | |
| "there 19960\n", | |
| "here 19961\n", | |
| "there 19961\n", | |
| "here 19962\n", | |
| "there 19962\n", | |
| "here 19963\n", | |
| "there 19963\n", | |
| "here 19964\n", | |
| "there 19964\n", | |
| "here 19965\n", | |
| "there 19965\n", | |
| "here 19966\n", | |
| "there 19966\n", | |
| "here 19967\n", | |
| "there 19967\n", | |
| "here 19968\n", | |
| "there 19968\n", | |
| "here 19969\n", | |
| "there 19969\n", | |
| "here 19970\n", | |
| "there 19970\n", | |
| "here 19971\n", | |
| "there 19971\n", | |
| "here 19972\n", | |
| "there 19972\n", | |
| "here 19973\n", | |
| "there 19973\n", | |
| "here 19974\n", | |
| "there 19974\n", | |
| "here 19975\n", | |
| "there 19975\n", | |
| "here 19976\n", | |
| "there 19976\n", | |
| "here 19977\n", | |
| "there 19977\n", | |
| "here 19978\n", | |
| "there 19978\n", | |
| "here 19979\n", | |
| "there 19979\n", | |
| "here 19980\n", | |
| "there 19980\n", | |
| "here 19981\n", | |
| "there 19981\n", | |
| "here 19982\n", | |
| "there 19982\n", | |
| "here 19983\n", | |
| "there 19983\n", | |
| "here 19984\n", | |
| "there 19984\n", | |
| "here 19985\n", | |
| "there 19985\n", | |
| "here 19986\n", | |
| "there 19986\n", | |
| "here 19987\n", | |
| "there 19987\n", | |
| "here 19988\n", | |
| "there 19988\n", | |
| "here 19989\n", | |
| "there 19989\n", | |
| "here 19990\n", | |
| "there 19990\n", | |
| "here 19991\n", | |
| "there 19991\n", | |
| "here 19992\n", | |
| "there 19992\n", | |
| "here 19993\n", | |
| "there 19993\n", | |
| "here 19994\n", | |
| "there 19994\n", | |
| "here 19995\n", | |
| "there 19995\n", | |
| "here 19996\n", | |
| "there 19996\n", | |
| "here 19997\n", | |
| "there 19997\n", | |
| "here 19998\n", | |
| "there 19998\n", | |
| "here 19999\n", | |
| "there 19999\n", | |
| "here 20000\n", | |
| "there 20000\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "RLGlzpfYbSK0" | |
| }, | |
| "source": [ | |
| "Plot for the Z1 statistic" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "HrdA0Pgp0mYs" | |
| }, | |
| "source": [ | |
| "******************************************************" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "OlmHo4nBmHmD" | |
| }, | |
| "source": [ | |
| "Here the peak width is not very prominent due to lack of accuracy of this method" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 293 | |
| }, | |
| "id": "nNEX1YJNRc7Q", | |
| "outputId": "1bd23877-3c2e-41a1-befd-633525b40514" | |
| }, | |
| "source": [ | |
| "plt.plot(Z___1,f_rab)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7fbe8f4278d0>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 96 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", 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| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "605sF7Yqa7dh" | |
| }, | |
| "source": [ | |
| "Maximum frequency estimation for the Z2 Statistic, y axis is the frequency and x axis is the z2 statistic. The plot is for the maximum frequency estimation using Z2" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 293 | |
| }, | |
| "id": "VenamCyERd0i", | |
| "outputId": "b67e85a4-a390-47ca-ab02-614df98acdd6" | |
| }, | |
| "source": [ | |
| "plt.plot(Z___2,f_rab)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7fbe8d24eb50>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 97 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "OBY_re7ObIYh" | |
| }, | |
| "source": [ | |
| "This is the explicit alue of the maximum frequency estimated using the procedure given in the assignment" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "bJpBuaF9SDRq", | |
| "outputId": "176f6baa-f2e6-41c2-8170-24b2df870384" | |
| }, | |
| "source": [ | |
| "f_rab[np.argmax(Z__2)]" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "20.58502944" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 98 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "JIVrbD1qSmc4" | |
| }, | |
| "source": [ | |
| "We see a sharper value when we take it around the given frequency\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "-NOSHfzrSrOe", | |
| "outputId": "b13cb7e0-e4db-40ca-dc02-a82fa6d5e911" | |
| }, | |
| "source": [ | |
| "np.argmax(Z___2)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "15542" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 100 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "Bwvk4-SWbSOm" | |
| }, | |
| "source": [ | |
| "Two make the pulse profile more clearly visible" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 293 | |
| }, | |
| "id": "ZTJPU9g5awLP", | |
| "outputId": "130046c3-a543-4a76-e829-4eb2b45db300" | |
| }, | |
| "source": [ | |
| "plt.plot(Z___2[8000:20001],f_rab[8000:20001])" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7fbe8e8d3350>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 104 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "GRNSViZ_O4jo" | |
| }, | |
| "source": [ | |
| "y axis is the frequency and x asis is the z static parameter" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "NhpH8BfecF4X" | |
| }, | |
| "source": [ | |
| "ph=taylor(freq)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "_pAsrehFcMPC" | |
| }, | |
| "source": [ | |
| "pph=ph[ph>0]" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "KFnOh1HRgGUQ" | |
| }, | |
| "source": [ | |
| "inpart=[]\n", | |
| "for i in range(0,len(pph)):\n", | |
| " inpart.append(np.int(pph[i]))\n" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "7ymDVZtKl7FH", | |
| "outputId": "8e681335-5edd-470a-f433-df0a83ccb357" | |
| }, | |
| "source": [ | |
| "np.int(11.89)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "11" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 17 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "18PoJcbUidAv" | |
| }, | |
| "source": [ | |
| "dec=pph-inpart\n" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "id": "FJ_aHAnlikpu", | |
| "outputId": "ca7c8280-486a-4c69-ca21-f171140b8f67" | |
| }, | |
| "source": [ | |
| "plt.hist(dec,bins=250)\n", | |
| "plt.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "q-446NlQnr8T" | |
| }, | |
| "source": [ | |
| "nph=ph[ph<0]\n", | |
| "ninpart=[]\n", | |
| "for i in range(0,len(nph)):\n", | |
| " ninpart.append(np.int(nph[i]))" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "zNb4XztiqECG", | |
| "outputId": "8bbe6c89-81e2-44b5-cbc4-a93b2e54271d" | |
| }, | |
| "source": [ | |
| "nph" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "array([-8.28408274e+05, -8.28369952e+05, -8.28332717e+05, ...,\n", | |
| " -6.03623624e+02, -5.40096214e+02, -4.52648505e+02])" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 152 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "Sx9LJXepoPkv", | |
| "outputId": "25129863-9e59-46c5-ab80-315253e2efe8" | |
| }, | |
| "source": [ | |
| "ndec=nph-ninpart\n", | |
| "ndec" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "array([-0.2739957 , -0.95203367, -0.71743964, ..., -0.62362355,\n", | |
| " -0.09621443, -0.64850466])" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 153 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "gNVc8_YxOoAA" | |
| }, | |
| "source": [ | |
| "Take the pulse profile for the ngative section of the pulse" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 592 | |
| }, | |
| "id": "9AiGiLuUozK5", | |
| "outputId": "c21e5b9b-a268-4df9-efa0-183cd68cebf5" | |
| }, | |
| "source": [ | |
| "plt.figure(figsize=[10,10])\n", | |
| "hist=plt.hist(abs(ndec),density=True,bins=250)\n", | |
| "plt.plot(kind='kde')\n", | |
| "plt.xticks(np.arange(0, 1, step=0.05))\n", | |
| "plt.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 720x720 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "fNygMwvxVd5C", | |
| "outputId": "f4ff32fc-9d06-4f42-93e5-0296710c37a6" | |
| }, | |
| "source": [ | |
| "len(density)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "250" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 58 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "OPO4MEtG077a" | |
| }, | |
| "source": [ | |
| "*************************************************************************************" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "uj99Zay2WYtq" | |
| }, | |
| "source": [ | |
| "The Density estimation from the histogram plot and the pulse width" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 621 | |
| }, | |
| "id": "02kxEPaPTrDS", | |
| "outputId": "ffc253fd-6d78-4a84-f21a-7abffa3f2cae" | |
| }, | |
| "source": [ | |
| "density, bins, patches = hist\n", | |
| "plt.figure(figsize=[10,10])\n", | |
| "x=np.linspace(0,1,num=250)\n", | |
| "plt.plot(x,density)\n", | |
| "plt.xticks(np.arange(0, 1, step=0.05))\n", | |
| "plt.vlines(0.08,0,7,colors='r')\n", | |
| "plt.vlines(0.157,0,7,colors='r')\n", | |
| "plt.vlines(0.59,0,7,colors='k')\n", | |
| "plt.vlines(0.675,0,7,colors='k')\n", | |
| "plt.title('J2022')\n", | |
| "plt.xlabel('phase')\n", | |
| "plt.ylabel\n", | |
| "plt.show()\n", | |
| "#len(x)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 720x720 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "YyVHgFjBKd2z" | |
| }, | |
| "source": [ | |
| "From the above plot one can clearly seen that the Pulse width for the main pulse (bigger peak) is 0.077 (through visual inspection of the above graph) and for the interpulse the distinct pulse base width is not clearly visible since we are haing issues with the non smoothness of the profile in the histogra plot but in the desnsity plot of the histogram we can clearly see the pulse width , approximately at points where we see a distinct peak one can see it is 0.075. The above estimates are approximate. This is the result for the negative pulse. \n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "Eqws-jaYam11" | |
| }, | |
| "source": [ | |
| "Let us go for the error histogram" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "C5VldhgHbXd7" | |
| }, | |
| "source": [ | |
| "The frequency estimaged using the Z2 statistic 20.58502944 now let us plot the phase plot for this frequency" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 282 | |
| }, | |
| "id": "uP3bX9Fyg37g", | |
| "outputId": "95cd7f16-983a-44e4-b760-7e92b00f62d7" | |
| }, | |
| "source": [ | |
| "ph_=taylor(20.585119830)\n", | |
| "plt.plot(ph_)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7f600efbae10>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 114 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 282 | |
| }, | |
| "id": "S_XN2jJEblrz", | |
| "outputId": "8b87cd0c-1d48-4bd9-cdeb-2221a541c6c8" | |
| }, | |
| "source": [ | |
| "zfreq=20.58502944\n", | |
| "#20.585119830\n", | |
| "\n", | |
| "20.58502944\n", | |
| "phz=taylor(zfreq)\n", | |
| "plt.plot(phz)\n" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7f600faf2210>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 115 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "psp08gg2cOLQ" | |
| }, | |
| "source": [ | |
| "Let us extimate the fractional plot for this case as well" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "etWd0aN2cHgl" | |
| }, | |
| "source": [ | |
| "nphz=phz[phz<0]\n", | |
| "nphz\n", | |
| "zninpart=[]\n", | |
| "for i in range(0,len(nphz)):\n", | |
| " zninpart.append(np.int(nphz[i]))" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "E6p2RC3zjxDe", | |
| "outputId": "bc817c65-3d46-4a75-f7ed-c3f99d580e04" | |
| }, | |
| "source": [ | |
| "zninpart[0:10]" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[-828404,\n", | |
| " -828366,\n", | |
| " -828329,\n", | |
| " -828257,\n", | |
| " -828241,\n", | |
| " -828210,\n", | |
| " -828171,\n", | |
| " -828171,\n", | |
| " -828129,\n", | |
| " -828076]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 134 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "-HidWVWvjlbD", | |
| "outputId": "f2b6690a-f342-409b-ccd4-12a1426709ca" | |
| }, | |
| "source": [ | |
| "nphz" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "array([-8.28404636e+05, -8.28366315e+05, -8.28329080e+05, ...,\n", | |
| " -6.03620973e+02, -5.40093843e+02, -4.52646517e+02])" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 135 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "SoJGhrzliCif", | |
| "outputId": "9de2112d-2d40-4f1f-b9b7-f24fe92e6ebb" | |
| }, | |
| "source": [ | |
| "zndec=nphz-zninpart\n", | |
| "zndec" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "array([-0.63642537, -0.31463161, -0.08020108, ..., -0.62097302,\n", | |
| " -0.09384285, -0.64651706])" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 136 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "id": "U3cVDoFVdbSf", | |
| "outputId": "2a44ac5b-9f0a-4952-9aa5-61c3c9615f48" | |
| }, | |
| "source": [ | |
| "hist_=plt.hist(abs(zndec),bins=250)\n", | |
| "plt.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "JL7B3LGWkClY" | |
| }, | |
| "source": [ | |
| "The frequency estimated using the Z2 statistic has not given any good values for the negative plot" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "1uEO_4Wtkxfr" | |
| }, | |
| "source": [ | |
| "density_, bins_, patches_ = hist_" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 282 | |
| }, | |
| "id": "8KouRu1Sk7FI", | |
| "outputId": "aecb796f-0e36-4c6b-d9d3-b40585e9da4a" | |
| }, | |
| "source": [ | |
| "plt.plot(density_)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7f600ee9c310>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 141 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "Yg9x6kmjlLIX" | |
| }, | |
| "source": [ | |
| "error=density-density_" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "r3zdWKTblILY" | |
| }, | |
| "source": [ | |
| "density-density_" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 285 | |
| }, | |
| "id": "lgRgUNtMlQsS", | |
| "outputId": "2c49f617-832d-4b12-9618-1cfa95e29336" | |
| }, | |
| "source": [ | |
| "plt.plot(error)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7f600eeb0bd0>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 145 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "qPiTxhZylUvu" | |
| }, | |
| "source": [ | |
| "The above plot is the error between the phase plot for the negative phase for the frequency given in pulsar catalog . We can see that our frequency estimation is no where close to the actual frequency estimation. The accuracy is way off. One can clearly see that the accuracy of lower harmonics is pretty bad! There is no pulse width to estimate" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "eWYoSmAImjAI" | |
| }, | |
| "source": [ | |
| "Now let us move on to the crab pulsar . We will rewrite a lot of codes" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "px1GcpxFtlkW", | |
| "outputId": "b81f4361-67aa-4834-f723-87a9d39656f5" | |
| }, | |
| "source": [ | |
| "!unzip '/content/drive/MyDrive/PUlsar/Crab_pulsar_ObsID406_02741_laxpc_bary_t1.tar.xz'" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Archive: /content/drive/MyDrive/PUlsar/Crab_pulsar_ObsID406_02741_laxpc_bary_t1.tar.xz\n", | |
| " End-of-central-directory signature not found. Either this file is not\n", | |
| " a zipfile, or it constitutes one disk of a multi-part archive. In the\n", | |
| " latter case the central directory and zipfile comment will be found on\n", | |
| " the last disk(s) of this archive.\n", | |
| "unzip: cannot find zipfile directory in one of /content/drive/MyDrive/PUlsar/Crab_pulsar_ObsID406_02741_laxpc_bary_t1.tar.xz or\n", | |
| " /content/drive/MyDrive/PUlsar/Crab_pulsar_ObsID406_02741_laxpc_bary_t1.tar.xz.zip, and cannot find /content/drive/MyDrive/PUlsar/Crab_pulsar_ObsID406_02741_laxpc_bary_t1.tar.xz.ZIP, period.\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "XaTbh3NsAEZn" | |
| }, | |
| "source": [ | |
| "import pandas as pd\n", | |
| "import numpy as np" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "bISJyNbsyrrL" | |
| }, | |
| "source": [ | |
| "import tarfile\n", | |
| "my_tar = tarfile.open('/content/drive/MyDrive/PUlsar/Crab_pulsar_ObsID406_02741_laxpc_bary_t1.tar.xz')\n", | |
| "my_tar.extractall('/content/drive/MyDrive/PUlsar') # specify which folder to extract to\n", | |
| "my_tar.close()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "mvnNZ1OcAWIK" | |
| }, | |
| "source": [ | |
| "ast=pd.read_csv('/content/drive/MyDrive/PUlsar/ObsID406_02741_laxpc_bary_t1.dat',sep=\"\\s+\")" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "uJskquy7HRIV" | |
| }, | |
| "source": [ | |
| "Extracting the event log" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "5IqFDGaqH4lA" | |
| }, | |
| "source": [ | |
| "del ast" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "IFgxtpEsFKRq", | |
| "outputId": "bbafab3a-cc7d-4fc4-ff2a-6bb2a349a830" | |
| }, | |
| "source": [ | |
| "\n", | |
| "ev" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "0 1.970991e+08\n", | |
| "1 1.970991e+08\n", | |
| "2 1.970991e+08\n", | |
| "3 1.970991e+08\n", | |
| "4 1.970991e+08\n", | |
| " ... \n", | |
| "13614379 1.971067e+08\n", | |
| "13614380 1.971067e+08\n", | |
| "13614381 1.971067e+08\n", | |
| "13614382 1.971067e+08\n", | |
| "13614383 1.971067e+08\n", | |
| "Name: Time, Length: 13614384, dtype: float64" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 16 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "x8Na1tDXHPlU" | |
| }, | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "GfhMYKfxHfUK" | |
| }, | |
| "source": [ | |
| "Rewrite Taylor series so that new parameters can be taken into consideration\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "Z52ojph-HlxD" | |
| }, | |
| "source": [ | |
| "def f_t(t,t_0):\n", | |
| " return t-t_0\n", | |
| "\n", | |
| "#find the taylor expansion and the phase\n", | |
| "def taylor(v):\n", | |
| " T=np.array([v*ft,((1/2)*f_dot)*ft**2,((1/6)*f_ddot)*ft**3])\n", | |
| " return np.sum(T.T,axis=1)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "BJ3aX67fKKcp", | |
| "outputId": "79fbefbd-8362-407c-e8ad-d6287cb93847" | |
| }, | |
| "source": [ | |
| "2*3**3" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "54" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 23 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "dPZADlnDKad_" | |
| }, | |
| "source": [ | |
| "freqc=29.6553306828504\n", | |
| "f_dot=-3.69261197216621e-10\n", | |
| "f_ddot=-3.9353064617231e-20" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "AsHcvuQVHLAu", | |
| "outputId": "83cd1431-84a8-45c0-a1b6-30b6707707c8" | |
| }, | |
| "source": [ | |
| "t0c=np.median(ev)\n", | |
| "t0c" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "197102097.46215728" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 21 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 295 | |
| }, | |
| "id": "A2XLhazPKoRT", | |
| "outputId": "8a1f6f84-8e2d-471f-de59-59b5c23c5ae0" | |
| }, | |
| "source": [ | |
| "#t minus t not\n", | |
| "\n", | |
| "ft=f_t(ev,t0c)\n", | |
| "plt.plot(ft)\n", | |
| "\n", | |
| "#plot of time minus t 0" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7fc2f9fc5c50>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 32 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 295 | |
| }, | |
| "id": "xS1Ub2kpLLu6", | |
| "outputId": "03ffae46-c3b7-43c4-c95b-61dda18a81af" | |
| }, | |
| "source": [ | |
| "tc=taylor(freqc)\n", | |
| "plt.plot(tc)\n", | |
| "\n", | |
| "#plot of the taylor expansion" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x7fc2f9eb8290>]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 34 | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "4DHM2BT4mIJC" | |
| }, | |
| "source": [ | |
| "Taking in totality all positive and negative values" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "_4XAcYyTNQo7" | |
| }, | |
| "source": [ | |
| "nphc=tc[tc<0]\n", | |
| "nphcint=[]\n", | |
| "for i in range(0,len(nphc)):\n", | |
| " nphcint.append(np.int(nphc[i]))" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "qDlaH4kRNuGm", | |
| "outputId": "dde5a229-fed2-4410-c8ba-35b1166b80e9" | |
| }, | |
| "source": [ | |
| "ndecc=nphc-nphcint\n", | |
| "ndecc" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "array([-0.62823068, -0.33916141, -0.13821771, ..., -0.01512178,\n", | |
| " -0.00889542, -0.00385513])" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 38 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "R3UfQAxLOxUj" | |
| }, | |
| "source": [ | |
| "normndec=ndecc/np.sum(ndecc)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 265 | |
| }, | |
| "id": "snWr72CxOXPr", | |
| "outputId": "4debd1aa-74f8-4ef3-e43e-8834ee11b86a" | |
| }, | |
| "source": [ | |
| "histc=plt.hist(abs(ndecc),bins=250)\n", | |
| "plt.yticks(np.arange(0,40000,step=10000))\n", | |
| "plt.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 432x288 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "fGjKHO1uP580" | |
| }, | |
| "source": [ | |
| "densityc, binsc, patchesc = histc" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "0JqlyO8z1BIW" | |
| }, | |
| "source": [ | |
| "**********************************************************************************" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "uPtvneb2QB1X" | |
| }, | |
| "source": [ | |
| "The density peaks will indicate the peaks clearly and it does! yay!" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "xjeL-Z6dNAEv" | |
| }, | |
| "source": [ | |
| "x_=np.linspace(0,1,250)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 621 | |
| }, | |
| "id": "j4D_cH6oP-Hu", | |
| "outputId": "c347d51e-6e82-4b33-f09e-619f5f517bca" | |
| }, | |
| "source": [ | |
| "#plt.xticks(np.arange(0, 1, step=0.05))\n", | |
| "plt.figure(figsize=[10,10])\n", | |
| "plt.plot(x_,densityc)\n", | |
| "plt.xticks(np.arange(0, 1, step=0.05))\n", | |
| "plt.vlines(0.06,25000,31000,colors='r')\n", | |
| "plt.vlines(0.35,25000,31000,colors='r')\n", | |
| "plt.vlines(0.46,25000,31000,colors='k')\n", | |
| "plt.vlines(0.68,25000,31000,colors='k')\n", | |
| "plt.title('folding pulse profile crab pulsar')\n", | |
| "plt.xlabel('phase')\n", | |
| "plt.ylabel('density-counts')\n", | |
| "plt.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 720x720 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "uF9wazBMZK5c" | |
| }, | |
| "source": [ | |
| "The pulse width calculation for the crab pulsar using the frequency given in the data is 0.29 and 0.22 for the main pulse and the interpulse respectively. The peak difference between the main pulse and the interpulse is very short in this case" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "zMHI1PV3c3KZ" | |
| }, | |
| "source": [ | |
| "Assignment question 2" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "7FcaP9IGbF2x" | |
| }, | |
| "source": [ | |
| "import tarfile\n", | |
| "my_tar = tarfile.open('/content/drive/MyDrive/PUlsar/J0820-1350_317MHz_02Mar14.dat.stkic_317.0.dedispb_tseries.tar.xz')\n", | |
| "my_tar.extractall('/content/drive/MyDrive/PUlsar') # specify which folder to extract to\n", | |
| "my_tar.close()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "CMH9v2qEeWM6" | |
| }, | |
| "source": [ | |
| "radio=pd.read_csv('/content/drive/MyDrive/PUlsar/J0820-1350_317MHz_02Mar14.dat.stkic_317.0.dedispb_tseries.dat',sep=\"\\s+\",skiprows=1)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "HrAP9C-FhIF6" | |
| }, | |
| "source": [ | |
| "MJD=56718.7636637\n", | |
| "NBINS=5038\n", | |
| "TRES=0.24576 #ms\n", | |
| "FREQ=317.0\n", | |
| "BW=16.667" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 204 | |
| }, | |
| "id": "xVPQygwcfrbq", | |
| "outputId": "1040c1b6-367c-4848-ce72-42e20d48b077" | |
| }, | |
| "source": [ | |
| "radio.head()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
| " vertical-align: middle;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe tbody tr th {\n", | |
| " vertical-align: top;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe thead th {\n", | |
| " text-align: right;\n", | |
| " }\n", | |
| "</style>\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>Pulse_no</th>\n", | |
| " <th>Bins</th>\n", | |
| " <th>Data</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>0</th>\n", | |
| " <td>1</td>\n", | |
| " <td>0</td>\n", | |
| " <td>97.847618</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1</th>\n", | |
| " <td>1</td>\n", | |
| " <td>1</td>\n", | |
| " <td>100.719048</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2</th>\n", | |
| " <td>1</td>\n", | |
| " <td>2</td>\n", | |
| " <td>99.190476</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>3</th>\n", | |
| " <td>1</td>\n", | |
| " <td>3</td>\n", | |
| " <td>98.161903</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>4</th>\n", | |
| " <td>1</td>\n", | |
| " <td>4</td>\n", | |
| " <td>99.176193</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " Pulse_no Bins Data\n", | |
| "0 1 0 97.847618\n", | |
| "1 1 1 100.719048\n", | |
| "2 1 2 99.190476\n", | |
| "3 1 3 98.161903\n", | |
| "4 1 4 99.176193" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 75 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "CEabpFM2w0wG" | |
| }, | |
| "source": [ | |
| "del radio" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "apnMDAjQoy8t" | |
| }, | |
| "source": [ | |
| "radio_300=radio[0:1513219]" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "fOI5x10SrD2Y" | |
| }, | |
| "source": [ | |
| "intpro=radio_300['Data']" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "Mm4UAIENrT4x" | |
| }, | |
| "source": [ | |
| "import seaborn as sns" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "dah-osCRhQL6" | |
| }, | |
| "source": [ | |
| "#pivotting the data for heat map\n", | |
| "\n", | |
| "radiop=radio_300.pivot('Pulse_no','Bins','Data')" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 284 | |
| }, | |
| "id": "rs0Ti2L6t--r", | |
| "outputId": "eeee230b-bfed-48a3-b997-1daf8c41e4be" | |
| }, | |
| "source": [ | |
| "radiop.head()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
| " vertical-align: middle;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe tbody tr th {\n", | |
| " vertical-align: top;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe thead th {\n", | |
| " text-align: right;\n", | |
| " }\n", | |
| "</style>\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th>Bins</th>\n", | |
| " <th>0</th>\n", | |
| " <th>1</th>\n", | |
| " <th>2</th>\n", | |
| " <th>3</th>\n", | |
| " <th>4</th>\n", | |
| " <th>5</th>\n", | |
| " <th>6</th>\n", | |
| " <th>7</th>\n", | |
| " <th>8</th>\n", | |
| " <th>9</th>\n", | |
| " <th>10</th>\n", | |
| " <th>11</th>\n", | |
| " <th>12</th>\n", | |
| " <th>13</th>\n", | |
| " <th>14</th>\n", | |
| " <th>15</th>\n", | |
| " <th>16</th>\n", | |
| " <th>17</th>\n", | |
| " <th>18</th>\n", | |
| " <th>19</th>\n", | |
| " <th>20</th>\n", | |
| " <th>21</th>\n", | |
| " <th>22</th>\n", | |
| " <th>23</th>\n", | |
| " <th>24</th>\n", | |
| " <th>25</th>\n", | |
| " <th>26</th>\n", | |
| " <th>27</th>\n", | |
| " <th>28</th>\n", | |
| " <th>29</th>\n", | |
| " <th>30</th>\n", | |
| " <th>31</th>\n", | |
| " <th>32</th>\n", | |
| " <th>33</th>\n", | |
| " <th>34</th>\n", | |
| " <th>35</th>\n", | |
| " <th>36</th>\n", | |
| " <th>37</th>\n", | |
| " <th>38</th>\n", | |
| " <th>39</th>\n", | |
| " <th>...</th>\n", | |
| " <th>4998</th>\n", | |
| " <th>4999</th>\n", | |
| " <th>5000</th>\n", | |
| " <th>5001</th>\n", | |
| " <th>5002</th>\n", | |
| " <th>5003</th>\n", | |
| " <th>5004</th>\n", | |
| " <th>5005</th>\n", | |
| " <th>5006</th>\n", | |
| " <th>5007</th>\n", | |
| " <th>5008</th>\n", | |
| " <th>5009</th>\n", | |
| " <th>5010</th>\n", | |
| " <th>5011</th>\n", | |
| " <th>5012</th>\n", | |
| " <th>5013</th>\n", | |
| " <th>5014</th>\n", | |
| " <th>5015</th>\n", | |
| " <th>5016</th>\n", | |
| " <th>5017</th>\n", | |
| " <th>5018</th>\n", | |
| " <th>5019</th>\n", | |
| " <th>5020</th>\n", | |
| " <th>5021</th>\n", | |
| " <th>5022</th>\n", | |
| " <th>5023</th>\n", | |
| " <th>5024</th>\n", | |
| " <th>5025</th>\n", | |
| " <th>5026</th>\n", | |
| " <th>5027</th>\n", | |
| " <th>5028</th>\n", | |
| " <th>5029</th>\n", | |
| " <th>5030</th>\n", | |
| " <th>5031</th>\n", | |
| " <th>5032</th>\n", | |
| " <th>5033</th>\n", | |
| " <th>5034</th>\n", | |
| " <th>5035</th>\n", | |
| " <th>5036</th>\n", | |
| " <th>5037</th>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Pulse_no</th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>1</th>\n", | |
| " <td>97.847618</td>\n", | |
| " <td>100.719048</td>\n", | |
| " <td>99.190476</td>\n", | |
| " <td>98.161903</td>\n", | |
| " <td>99.176193</td>\n", | |
| " <td>99.019051</td>\n", | |
| " <td>101.690476</td>\n", | |
| " <td>99.109528</td>\n", | |
| " <td>101.319046</td>\n", | |
| " <td>99.719048</td>\n", | |
| " <td>97.123810</td>\n", | |
| " <td>98.042854</td>\n", | |
| " <td>97.438095</td>\n", | |
| " <td>100.780952</td>\n", | |
| " <td>97.514282</td>\n", | |
| " <td>98.385712</td>\n", | |
| " <td>96.304764</td>\n", | |
| " <td>98.366669</td>\n", | |
| " <td>99.266670</td>\n", | |
| " <td>97.409523</td>\n", | |
| " <td>99.738098</td>\n", | |
| " <td>100.671425</td>\n", | |
| " <td>96.371429</td>\n", | |
| " <td>99.328575</td>\n", | |
| " <td>97.533333</td>\n", | |
| " <td>96.861908</td>\n", | |
| " <td>98.114288</td>\n", | |
| " <td>98.609528</td>\n", | |
| " <td>99.947617</td>\n", | |
| " <td>96.980949</td>\n", | |
| " <td>99.695236</td>\n", | |
| " <td>97.380951</td>\n", | |
| " <td>98.390472</td>\n", | |
| " <td>100.000000</td>\n", | |
| " <td>102.547623</td>\n", | |
| " <td>99.938095</td>\n", | |
| " <td>97.123810</td>\n", | |
| " <td>100.066666</td>\n", | |
| " <td>99.752380</td>\n", | |
| " <td>96.833336</td>\n", | |
| " <td>...</td>\n", | |
| " <td>99.514282</td>\n", | |
| " <td>103.490479</td>\n", | |
| " <td>99.661903</td>\n", | |
| " <td>99.442856</td>\n", | |
| " <td>101.257141</td>\n", | |
| " <td>100.923813</td>\n", | |
| " <td>98.323807</td>\n", | |
| " <td>96.433334</td>\n", | |
| " <td>101.395241</td>\n", | |
| " <td>97.785713</td>\n", | |
| " <td>97.647621</td>\n", | |
| " <td>97.666664</td>\n", | |
| " <td>97.380951</td>\n", | |
| " <td>101.433334</td>\n", | |
| " <td>98.971428</td>\n", | |
| " <td>101.328575</td>\n", | |
| " <td>97.195236</td>\n", | |
| " <td>98.790474</td>\n", | |
| " <td>100.447617</td>\n", | |
| " <td>99.809524</td>\n", | |
| " <td>97.371429</td>\n", | |
| " <td>98.604759</td>\n", | |
| " <td>98.809524</td>\n", | |
| " <td>100.333336</td>\n", | |
| " <td>96.657143</td>\n", | |
| " <td>100.085716</td>\n", | |
| " <td>99.314285</td>\n", | |
| " <td>99.609528</td>\n", | |
| " <td>100.433334</td>\n", | |
| " <td>100.023811</td>\n", | |
| " <td>97.885712</td>\n", | |
| " <td>98.985718</td>\n", | |
| " <td>98.809524</td>\n", | |
| " <td>96.628571</td>\n", | |
| " <td>99.438095</td>\n", | |
| " <td>99.366669</td>\n", | |
| " <td>97.400002</td>\n", | |
| " <td>97.585716</td>\n", | |
| " <td>99.014282</td>\n", | |
| " <td>97.285713</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2</th>\n", | |
| " <td>100.133331</td>\n", | |
| " <td>98.495239</td>\n", | |
| " <td>98.142860</td>\n", | |
| " <td>96.290474</td>\n", | |
| " <td>96.166664</td>\n", | |
| " <td>94.895241</td>\n", | |
| " <td>99.452377</td>\n", | |
| " <td>94.842857</td>\n", | |
| " <td>97.314285</td>\n", | |
| " <td>96.509521</td>\n", | |
| " <td>99.128571</td>\n", | |
| " <td>98.723808</td>\n", | |
| " <td>97.385712</td>\n", | |
| " <td>99.714287</td>\n", | |
| " <td>99.671425</td>\n", | |
| " <td>96.219048</td>\n", | |
| " <td>97.209526</td>\n", | |
| " <td>99.009521</td>\n", | |
| " <td>100.285713</td>\n", | |
| " <td>98.242859</td>\n", | |
| " <td>96.590477</td>\n", | |
| " <td>97.566666</td>\n", | |
| " <td>98.133331</td>\n", | |
| " <td>99.300003</td>\n", | |
| " <td>99.785713</td>\n", | |
| " <td>96.890472</td>\n", | |
| " <td>97.709526</td>\n", | |
| " <td>98.566666</td>\n", | |
| " <td>96.252380</td>\n", | |
| " <td>98.828575</td>\n", | |
| " <td>99.814285</td>\n", | |
| " <td>96.971428</td>\n", | |
| " <td>95.023811</td>\n", | |
| " <td>98.042854</td>\n", | |
| " <td>96.142860</td>\n", | |
| " <td>99.442856</td>\n", | |
| " <td>100.519051</td>\n", | |
| " <td>101.166664</td>\n", | |
| " <td>99.109528</td>\n", | |
| " <td>99.261902</td>\n", | |
| " <td>...</td>\n", | |
| " <td>102.119049</td>\n", | |
| " <td>98.223808</td>\n", | |
| " <td>101.519051</td>\n", | |
| " <td>97.919044</td>\n", | |
| " <td>97.666664</td>\n", | |
| " <td>96.957146</td>\n", | |
| " <td>98.119049</td>\n", | |
| " <td>99.909523</td>\n", | |
| " <td>95.976189</td>\n", | |
| " <td>97.085716</td>\n", | |
| " <td>98.323807</td>\n", | |
| " <td>101.428574</td>\n", | |
| " <td>96.766670</td>\n", | |
| " <td>96.599998</td>\n", | |
| " <td>99.023811</td>\n", | |
| " <td>100.947617</td>\n", | |
| " <td>97.490479</td>\n", | |
| " <td>98.195236</td>\n", | |
| " <td>97.209526</td>\n", | |
| " <td>97.314285</td>\n", | |
| " <td>97.861908</td>\n", | |
| " <td>98.876190</td>\n", | |
| " <td>97.423813</td>\n", | |
| " <td>97.738098</td>\n", | |
| " <td>99.266670</td>\n", | |
| " <td>96.842857</td>\n", | |
| " <td>98.466667</td>\n", | |
| " <td>98.947617</td>\n", | |
| " <td>96.585716</td>\n", | |
| " <td>99.695236</td>\n", | |
| " <td>98.785713</td>\n", | |
| " <td>98.009521</td>\n", | |
| " <td>94.300003</td>\n", | |
| " <td>97.257141</td>\n", | |
| " <td>98.157143</td>\n", | |
| " <td>98.161903</td>\n", | |
| " <td>99.457146</td>\n", | |
| " <td>94.638092</td>\n", | |
| " <td>98.300003</td>\n", | |
| " <td>97.728569</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>3</th>\n", | |
| " <td>97.585716</td>\n", | |
| " <td>97.233330</td>\n", | |
| " <td>99.633331</td>\n", | |
| " <td>100.328575</td>\n", | |
| " <td>98.861908</td>\n", | |
| " <td>99.285713</td>\n", | |
| " <td>97.438095</td>\n", | |
| " <td>94.371429</td>\n", | |
| " <td>95.952377</td>\n", | |
| " <td>101.280952</td>\n", | |
| " <td>100.457146</td>\n", | |
| " <td>99.719048</td>\n", | |
| " <td>98.314285</td>\n", | |
| " <td>97.457146</td>\n", | |
| " <td>95.119049</td>\n", | |
| " <td>99.019051</td>\n", | |
| " <td>97.852379</td>\n", | |
| " <td>96.642860</td>\n", | |
| " <td>99.757141</td>\n", | |
| " <td>97.261902</td>\n", | |
| " <td>97.261902</td>\n", | |
| " <td>98.052383</td>\n", | |
| " <td>99.666664</td>\n", | |
| " <td>99.519051</td>\n", | |
| " <td>100.895241</td>\n", | |
| " <td>94.261902</td>\n", | |
| " <td>98.285713</td>\n", | |
| " <td>98.061905</td>\n", | |
| " <td>98.495239</td>\n", | |
| " <td>96.423813</td>\n", | |
| " <td>99.199997</td>\n", | |
| " <td>101.400002</td>\n", | |
| " <td>95.976189</td>\n", | |
| " <td>98.461906</td>\n", | |
| " <td>99.571426</td>\n", | |
| " <td>100.599998</td>\n", | |
| " <td>99.552383</td>\n", | |
| " <td>96.571426</td>\n", | |
| " <td>98.809524</td>\n", | |
| " <td>98.028572</td>\n", | |
| " <td>...</td>\n", | |
| " <td>97.866669</td>\n", | |
| " <td>99.900002</td>\n", | |
| " <td>98.695236</td>\n", | |
| " <td>97.571426</td>\n", | |
| " <td>97.123810</td>\n", | |
| " <td>99.661903</td>\n", | |
| " <td>103.004761</td>\n", | |
| " <td>98.766670</td>\n", | |
| " <td>97.780952</td>\n", | |
| " <td>100.047623</td>\n", | |
| " <td>98.314285</td>\n", | |
| " <td>100.990479</td>\n", | |
| " <td>98.480949</td>\n", | |
| " <td>94.347618</td>\n", | |
| " <td>98.147621</td>\n", | |
| " <td>100.352379</td>\n", | |
| " <td>98.447617</td>\n", | |
| " <td>100.809524</td>\n", | |
| " <td>98.309524</td>\n", | |
| " <td>100.028572</td>\n", | |
| " <td>101.038094</td>\n", | |
| " <td>98.633331</td>\n", | |
| " <td>97.271431</td>\n", | |
| " <td>100.295235</td>\n", | |
| " <td>98.238098</td>\n", | |
| " <td>101.876190</td>\n", | |
| " <td>97.976189</td>\n", | |
| " <td>100.742859</td>\n", | |
| " <td>100.361908</td>\n", | |
| " <td>95.666664</td>\n", | |
| " <td>98.909523</td>\n", | |
| " <td>96.995239</td>\n", | |
| " <td>99.904762</td>\n", | |
| " <td>97.866669</td>\n", | |
| " <td>97.957146</td>\n", | |
| " <td>98.347618</td>\n", | |
| " <td>99.961906</td>\n", | |
| " <td>97.995239</td>\n", | |
| " <td>98.447617</td>\n", | |
| " <td>97.971428</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>4</th>\n", | |
| " <td>101.419044</td>\n", | |
| " <td>99.004761</td>\n", | |
| " <td>97.228569</td>\n", | |
| " <td>103.738098</td>\n", | |
| " <td>100.109528</td>\n", | |
| " <td>100.461906</td>\n", | |
| " <td>96.623810</td>\n", | |
| " <td>98.519051</td>\n", | |
| " <td>98.428574</td>\n", | |
| " <td>97.880951</td>\n", | |
| " <td>96.604759</td>\n", | |
| " <td>96.761902</td>\n", | |
| " <td>99.861908</td>\n", | |
| " <td>97.552383</td>\n", | |
| " <td>98.295235</td>\n", | |
| " <td>98.976189</td>\n", | |
| " <td>98.533333</td>\n", | |
| " <td>98.223808</td>\n", | |
| " <td>101.385712</td>\n", | |
| " <td>95.933334</td>\n", | |
| " <td>100.442856</td>\n", | |
| " <td>97.733330</td>\n", | |
| " <td>94.866669</td>\n", | |
| " <td>95.776192</td>\n", | |
| " <td>101.461906</td>\n", | |
| " <td>97.319046</td>\n", | |
| " <td>97.138092</td>\n", | |
| " <td>98.152382</td>\n", | |
| " <td>103.304764</td>\n", | |
| " <td>98.409523</td>\n", | |
| " <td>97.004761</td>\n", | |
| " <td>97.438095</td>\n", | |
| " <td>98.204765</td>\n", | |
| " <td>96.800003</td>\n", | |
| " <td>97.542854</td>\n", | |
| " <td>99.790474</td>\n", | |
| " <td>99.938095</td>\n", | |
| " <td>99.319046</td>\n", | |
| " <td>97.776192</td>\n", | |
| " <td>97.699997</td>\n", | |
| " <td>...</td>\n", | |
| " <td>94.238098</td>\n", | |
| " <td>100.404762</td>\n", | |
| " <td>100.914284</td>\n", | |
| " <td>96.157143</td>\n", | |
| " <td>102.319046</td>\n", | |
| " <td>98.376190</td>\n", | |
| " <td>97.366669</td>\n", | |
| " <td>97.090477</td>\n", | |
| " <td>98.342857</td>\n", | |
| " <td>97.900002</td>\n", | |
| " <td>97.157143</td>\n", | |
| " <td>97.685715</td>\n", | |
| " <td>103.742859</td>\n", | |
| " <td>96.109528</td>\n", | |
| " <td>97.142860</td>\n", | |
| " <td>97.447617</td>\n", | |
| " <td>99.552383</td>\n", | |
| " <td>99.676193</td>\n", | |
| " <td>99.628571</td>\n", | |
| " <td>96.895241</td>\n", | |
| " <td>97.114288</td>\n", | |
| " <td>100.833336</td>\n", | |
| " <td>97.357140</td>\n", | |
| " <td>98.680954</td>\n", | |
| " <td>98.038094</td>\n", | |
| " <td>98.604759</td>\n", | |
| " <td>99.109528</td>\n", | |
| " <td>98.166664</td>\n", | |
| " <td>101.109528</td>\n", | |
| " <td>97.785713</td>\n", | |
| " <td>98.547623</td>\n", | |
| " <td>99.009521</td>\n", | |
| " <td>99.423813</td>\n", | |
| " <td>100.380951</td>\n", | |
| " <td>95.785713</td>\n", | |
| " <td>96.780952</td>\n", | |
| " <td>99.476189</td>\n", | |
| " <td>97.323807</td>\n", | |
| " <td>100.547623</td>\n", | |
| " <td>95.957146</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>5</th>\n", | |
| " <td>98.885712</td>\n", | |
| " <td>96.442856</td>\n", | |
| " <td>97.057144</td>\n", | |
| " <td>97.561905</td>\n", | |
| " <td>99.080956</td>\n", | |
| " <td>96.090477</td>\n", | |
| " <td>98.771431</td>\n", | |
| " <td>99.580956</td>\n", | |
| " <td>99.133331</td>\n", | |
| " <td>97.114288</td>\n", | |
| " <td>95.300003</td>\n", | |
| " <td>97.257141</td>\n", | |
| " <td>100.690476</td>\n", | |
| " <td>99.857140</td>\n", | |
| " <td>96.804764</td>\n", | |
| " <td>95.199997</td>\n", | |
| " <td>99.238098</td>\n", | |
| " <td>98.876190</td>\n", | |
| " <td>98.161903</td>\n", | |
| " <td>99.842857</td>\n", | |
| " <td>99.447617</td>\n", | |
| " <td>99.990479</td>\n", | |
| " <td>98.514282</td>\n", | |
| " <td>99.985718</td>\n", | |
| " <td>100.885712</td>\n", | |
| " <td>98.995239</td>\n", | |
| " <td>98.414284</td>\n", | |
| " <td>98.295235</td>\n", | |
| " <td>97.528572</td>\n", | |
| " <td>94.095238</td>\n", | |
| " <td>97.923813</td>\n", | |
| " <td>98.123810</td>\n", | |
| " <td>97.528572</td>\n", | |
| " <td>97.223808</td>\n", | |
| " <td>100.504761</td>\n", | |
| " <td>99.633331</td>\n", | |
| " <td>98.800003</td>\n", | |
| " <td>97.276192</td>\n", | |
| " <td>93.319046</td>\n", | |
| " <td>98.866669</td>\n", | |
| " <td>...</td>\n", | |
| " <td>98.619049</td>\n", | |
| " <td>97.438095</td>\n", | |
| " <td>97.766670</td>\n", | |
| " <td>97.295235</td>\n", | |
| " <td>96.414284</td>\n", | |
| " <td>98.219048</td>\n", | |
| " <td>97.114288</td>\n", | |
| " <td>99.628571</td>\n", | |
| " <td>98.995239</td>\n", | |
| " <td>98.809524</td>\n", | |
| " <td>97.480949</td>\n", | |
| " <td>96.976189</td>\n", | |
| " <td>100.819046</td>\n", | |
| " <td>99.547623</td>\n", | |
| " <td>99.971428</td>\n", | |
| " <td>99.604759</td>\n", | |
| " <td>94.409523</td>\n", | |
| " <td>96.804764</td>\n", | |
| " <td>101.028572</td>\n", | |
| " <td>99.238098</td>\n", | |
| " <td>97.885712</td>\n", | |
| " <td>98.928574</td>\n", | |
| " <td>96.652382</td>\n", | |
| " <td>99.828575</td>\n", | |
| " <td>94.214287</td>\n", | |
| " <td>94.957146</td>\n", | |
| " <td>98.647621</td>\n", | |
| " <td>98.704765</td>\n", | |
| " <td>97.466667</td>\n", | |
| " <td>94.647621</td>\n", | |
| " <td>98.628571</td>\n", | |
| " <td>99.595238</td>\n", | |
| " <td>98.152382</td>\n", | |
| " <td>98.142860</td>\n", | |
| " <td>96.157143</td>\n", | |
| " <td>95.747620</td>\n", | |
| " <td>98.833336</td>\n", | |
| " <td>100.609528</td>\n", | |
| " <td>98.433334</td>\n", | |
| " <td>98.447617</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>5 rows × 5038 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| "Bins 0 1 2 ... 5035 5036 5037\n", | |
| "Pulse_no ... \n", | |
| "1 97.847618 100.719048 99.190476 ... 97.585716 99.014282 97.285713\n", | |
| "2 100.133331 98.495239 98.142860 ... 94.638092 98.300003 97.728569\n", | |
| "3 97.585716 97.233330 99.633331 ... 97.995239 98.447617 97.971428\n", | |
| "4 101.419044 99.004761 97.228569 ... 97.323807 100.547623 95.957146\n", | |
| "5 98.885712 96.442856 97.057144 ... 100.609528 98.433334 98.447617\n", | |
| "\n", | |
| "[5 rows x 5038 columns]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 87 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "LcWBdp3Z1GBw" | |
| }, | |
| "source": [ | |
| "********************************************************************************" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "lx2oHAAm1LhL" | |
| }, | |
| "source": [ | |
| "The Heat map showing the sub pulse window the brighter regions are probably the subpulse" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 1000 | |
| }, | |
| "id": "dPOqIXbuukSQ", | |
| "outputId": "66b04fa1-4f4a-431a-d598-18983e51c491" | |
| }, | |
| "source": [ | |
| "plt.figure(figsize=[20,20])\n", | |
| "sns.heatmap(radiop,cmap='RdBu')\n", | |
| "plt.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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