Setting_PSD.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from lib.PSD.LISAcalPSD import LISAcalPSD1, LISAcalPSD2\n",
    "from lib.PSD.DECIGOcalPSD import B_DECIGOcalPSD, DECIGOcalPSD\n",
    "from pycbc.types.frequencyseries import FrequencySeries\n",
    "import pycbc.psd\n",
    "from scipy.interpolate import interp1d                   # interplate\n",
    "from scipy import signal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 参数设置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "采样频率为0.25Hz，信号持续时间65536s, 时域信号采样16384 个点\n",
      "信号中可分析最大频率为0.125000Hz\n",
      "\n",
      "采样周期，即时域分辨率为4.000000s\n",
      "信号频域的频率间隔，即频域分辨率为0.000015Hz\n"
     ]
    }
   ],
   "source": [
    "sampFreq1 = 0.25               #采样频率(Sampling frequency)，单位时间样本点个数，应大于 2f（即Nyquist频率)\n",
    "duration1 = 2**16          #信号持续时间(duration of signal)\n",
    "\n",
    "\n",
    "n1 = int(duration1 * sampFreq1)#采样点数(Sampling Number), 有时也称为信号长度(Length of Signal)\n",
    "                            #为2的幂时，快速傅里叶变化效率最高\n",
    "                            #n =  duration * sampFreqint = (duration / sampIntrvl)\n",
    "\n",
    "sampIntrvl1 = 1.0 / sampFreq1                   #采样周期(Sampling period)，隔多少时间取样一次，或步长\n",
    "freqIntrvl1 = sampFreq1 / n1                     #傅里叶变换 频率分辨率(Frequency Interval) \n",
    "                                              # freqIntrvl = 1 / duration = 1 / (n * sampIntrvl)\n",
    "                                              #            = sampFreq / n  \n",
    "        \n",
    "\n",
    "f_max1 = sampFreq1/2.0             #信号模式的最大频率\n",
    "\n",
    "print(\"采样频率为%3.2fHz，信号持续时间%ds, 时域信号采样%d 个点\"%(sampFreq1, duration1, n1))\n",
    "print(\"信号中可分析最大频率为%fHz\"%f_max1)\n",
    "print(\"\\n采样周期，即时域分辨率为%fs\"%(sampIntrvl1))\n",
    "print(\"信号频域的频率间隔，即频域分辨率为%fHz\"%freqIntrvl1);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 构建用于pyCBC的PSD频率序列"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 利用psd模拟函数生成"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "freqVec1 = np.linspace(0, freqIntrvl1 * (n1-1), n1)\n",
    "low_freq_cutoff1 = 1e-4\n",
    "\n",
    "\n",
    "#构建频率序列(必须等频率间隔)，这里我们开始于0Hz(必须开始于0，否则导入pyCBC的结果不对), 结束于1Hz，频率间隔为上面的freqIntrvl\n",
    "\n",
    "#LISA PSD 模拟函数\n",
    "psd1 = LISAcalPSD1(freqVec1) \n",
    "\n",
    "'''\n",
    "1. Babak, S., Fang, H., Gair, J. R., Glampedakis, K. & Hughes, S. A. Kludge’\n",
    "gravitational waveforms for a test-body orbiting a Kerr black hole. Phys.Rev. D 75, 024005 (2007).\n",
    "\n",
    "'''\n",
    "\n",
    "psd2 = LISAcalPSD2(freqVec1)\n",
    "\n",
    "\n",
    "'''\n",
    "1. Sathyaprakash, B. S. & Schutz, B. F. \n",
    "Physics, Astrophysics and Cosmology with Gravitational Waves. Living Rev Relativ 12, 122004 (2009).\n",
    "\n",
    "'''\n",
    "\n",
    "#构建用于pyCBC的FrequencySeries\n",
    "psd1 = pycbc.psd.read.from_numpy_arrays(freqVec1 , psd1, n1, freqIntrvl1, low_freq_cutoff1)\n",
    "psd2 = pycbc.psd.read.from_numpy_arrays(freqVec1 , psd2, n1, freqIntrvl1, low_freq_cutoff1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "采样频率为256.00Hz，信号持续时间16384s, 时域信号采样4194304 个点\n",
      "信号中可分析最大频率为128.000000Hz\n",
      "\n",
      "采样周期，即时域分辨率为0.003906s\n",
      "信号频域的频率间隔，即频域分辨率为0.000061Hz\n"
     ]
    }
   ],
   "source": [
    "# DECIGO\n",
    "\n",
    "sampFreq3 = 2**8           #采样频率(Sampling frequency)，单位时间样本点个数，应大于 2f（即Nyquist频率)\n",
    "duration3 = 2**14          #信号持续时间(duration of signal)\n",
    "\n",
    "\n",
    "n3 = int(duration3 * sampFreq3)#采样点数(Sampling Number), 有时也称为信号长度(Length of Signal)\n",
    "                            #为2的幂时，快速傅里叶变化效率最高\n",
    "                            #n =  duration * sampFreqint = (duration / sampIntrvl)\n",
    "\n",
    "sampIntrvl3 = 1.0 / sampFreq3                   #采样周期(Sampling period)，隔多少时间取样一次，或步长\n",
    "freqIntrvl3 = sampFreq3 / n3                     #傅里叶变换 频率分辨率(Frequency Interval) \n",
    "                                              # freqIntrvl = 1 / duration = 1 / (n * sampIntrvl)\n",
    "                                              #            = sampFreq / n  \n",
    "        \n",
    "\n",
    "f_max3 = sampFreq3/2.0             #信号模式的最大频率\n",
    "\n",
    "print(\"采样频率为%3.2fHz，信号持续时间%ds, 时域信号采样%d 个点\"%(sampFreq3, duration3, n3))\n",
    "print(\"信号中可分析最大频率为%fHz\"%f_max3)\n",
    "print(\"\\n采样周期，即时域分辨率为%fs\"%(sampIntrvl3))\n",
    "print(\"信号频域的频率间隔，即频域分辨率为%fHz\"%freqIntrvl3);\n",
    "\n",
    "\n",
    "freqVec3 = np.linspace(0, freqIntrvl3 * (n3-1), n3)\n",
    "low_freq_cutoff3 = 1e-2\n",
    "\n",
    "#构建频率序列(必须等频率间隔)，这里我们开始于0Hz(必须开始于0，否则导入pyCBC的结果不对), 结束于1Hz，频率间隔为上面的freqIntrvl\n",
    "\n",
    "#LISA PSD 模拟函数\n",
    "psd5 = B_DECIGOcalPSD(freqVec3) \n",
    "psd6 = DECIGOcalPSD(freqVec3) \n",
    "\n",
    "'''\n",
    "1. Multiband Gravitational-Wave Astronomy:Observing binary inspirals with a decihertz detector, B-DECIGO\n",
    "https://arxiv.org/pdf/1802.06977.pdf\n",
    "'''\n",
    "\n",
    "\n",
    "#构建用于pyCBC的FrequencySeries\n",
    "psd5 = pycbc.psd.read.from_numpy_arrays(freqVec3 , psd5, n3, freqIntrvl3, low_freq_cutoff3)\n",
    "psd6 = pycbc.psd.read.from_numpy_arrays(freqVec3 , psd6, n3, freqIntrvl3, low_freq_cutoff3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 从文件中导入"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入的psd文件要求第一列为频率(必须从0开始，不是等间隔需要进行插值)，第二列是psd，两列用空格分隔\n",
    "\n",
    "'''\n",
    "from WWW Sensitivity Curve Generator located at:\n",
    "  http://www.srl.caltech.edu/~shane/sensitivity/MakeCurve.html\n",
    "\n",
    "'''\n",
    "\n",
    "#导入\n",
    "psdfile = np.fromfile(\"lib/PSD/LISAshotPSD.txt\", dtype=float, count=-1, sep='\\n')\n",
    "psdlen = len(psdfile)\n",
    "freqVecPre = psdfile[0:psdlen:2]\n",
    "psdPre = psdfile[1:psdlen:2]\n",
    "#插值\n",
    "LISAcalPSD3 = interp1d(freqVecPre, psdPre, kind='cubic', fill_value=\"extrapolate\") \n",
    "\n",
    "#构建用于pyCBC的FrequencySeries\n",
    "psd3 = LISAcalPSD3(freqVec1)\n",
    "psd3 = FrequencySeries(psd3, delta_f=freqIntrvl1, epoch='', dtype=None, copy=True)\n",
    "\n",
    "psd3 = pycbc.psd.read.from_numpy_arrays(freqVec1, psd3, n1, freqIntrvl1, low_freq_cutoff1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## pycbc内置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['AdVBNSOptimizedSensitivityP1200087', 'AdVDesignSensitivityP1200087', 'AdVEarlyHighSensitivityP1200087', 'AdVEarlyLowSensitivityP1200087', 'AdVLateHighSensitivityP1200087', 'AdVLateLowSensitivityP1200087', 'AdVMidHighSensitivityP1200087', 'AdVMidLowSensitivityP1200087', 'AdvVirgo', 'CosmicExplorerP1600143', 'CosmicExplorerPessimisticP1600143', 'CosmicExplorerWidebandP1600143', 'EinsteinTelescopeP1600143', 'GEO', 'GEOHF', 'KAGRA', 'KAGRADesignSensitivityT1600593', 'KAGRAEarlySensitivityT1600593', 'KAGRALateSensitivityT1600593', 'KAGRAMidSensitivityT1600593', 'KAGRAOpeningSensitivityT1600593', 'TAMA', 'Virgo', 'aLIGOAPlusDesignSensitivityT1800042', 'aLIGOAdVO3LowT1800545', 'aLIGOAdVO4IntermediateT1800545', 'aLIGOAdVO4T1800545', 'aLIGOBHBH20Deg', 'aLIGOBHBH20DegGWINC', 'aLIGOBNSOptimizedSensitivityP1200087', 'aLIGODesignSensitivityP1200087', 'aLIGOEarlyHighSensitivityP1200087', 'aLIGOEarlyLowSensitivityP1200087', 'aLIGOHighFrequency', 'aLIGOHighFrequencyGWINC', 'aLIGOKAGRA128MpcT1800545', 'aLIGOKAGRA25MpcT1800545', 'aLIGOKAGRA80MpcT1800545', 'aLIGOLateHighSensitivityP1200087', 'aLIGOLateLowSensitivityP1200087', 'aLIGOMidHighSensitivityP1200087', 'aLIGOMidLowSensitivityP1200087', 'aLIGONSNSOpt', 'aLIGONSNSOptGWINC', 'aLIGONoSRMHighPower', 'aLIGONoSRMLowPower', 'aLIGONoSRMLowPowerGWINC', 'aLIGOQuantumBHBH20Deg', 'aLIGOQuantumHighFrequency', 'aLIGOQuantumNSNSOpt', 'aLIGOQuantumNoSRMHighPower', 'aLIGOQuantumNoSRMLowPower', 'aLIGOQuantumZeroDetHighPower', 'aLIGOQuantumZeroDetLowPower', 'aLIGOThermal', 'aLIGOZeroDetHighPower', 'aLIGOZeroDetHighPowerGWINC', 'aLIGOZeroDetLowPower', 'aLIGOZeroDetLowPowerGWINC', 'aLIGOaLIGO140MpcT1800545', 'aLIGOaLIGO175MpcT1800545', 'aLIGOaLIGODesignSensitivityT1800044', 'aLIGOaLIGOO3LowT1800545', 'eLIGOModel', 'eLIGOShot', 'iLIGOModel', 'iLIGOSRD', 'iLIGOSeismic', 'iLIGOShot', 'iLIGOThermal']\n"
     ]
    }
   ],
   "source": [
    "# 列出lalsuite内置的解析psd (没发现有LISA的，下面以LIGO的作为示例)\n",
    "print(pycbc.psd.get_lalsim_psd_list())\n",
    "\n",
    "sampFreq2 = 2048.0            #采样频率(Sampling frequency)，单位时间样本点个数，应大于 2f（即Nyquist频率)\n",
    "duration2 = 4.0             #信号持续时间(duration of signal)\n",
    "n2 = int(duration2 * sampFreq2)#采样点数(Sampling Number), 有时也称为信号长度(Length of Signal)\n",
    "\n",
    "sampIntrvl2 = 1.0 / sampFreq2                   #采样周期(Sampling period)，隔多少时间取样一次，或步长\n",
    "freqIntrvl2 = sampFreq2 / n2                     #傅里叶变换 频率分辨率(Frequency Interval) \n",
    "                                                # freqIntrvl = 1 / duration = 1 / (n * sampIntrvl)\n",
    "                                                #            = sampFreq / n \n",
    "\n",
    "low_frequency_cutoff2 = 10.0                     #低于此频率的psd将被设置为0\n",
    "\n",
    "#示例，psd参见， https://dcc.ligo.org/LIGO-T1800044/public\n",
    "\n",
    "psd4 = pycbc.psd.from_string('aLIGOaLIGODesignSensitivityT1800044', n2, freqIntrvl2, low_frequency_cutoff2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#绘制 频率 - sqrt(PSD) 图 \n",
    "\n",
    "#绘图字体参数设置\n",
    "matplotlib.rcParams.update({'font.size': 15, 'font.family': 'STIXGeneral', 'mathtext.fontset': 'stix'})\n",
    "\n",
    "plt.figure(figsize=(8,6))\n",
    "\n",
    "plt.loglog(psd1.sample_frequencies[psd1>0], np.sqrt(psd1[psd1>0]), label = 'LISA_1')\n",
    "plt.loglog(psd2.sample_frequencies[psd2>0], np.sqrt(psd2[psd2>0]), label = 'LISA_2')\n",
    "plt.loglog(psd3.sample_frequencies[psd3>0], np.sqrt(psd3[psd3>0]), label = 'LISA_3')\n",
    "\n",
    "plt.loglog(psd4.sample_frequencies[psd4>0], np.sqrt(psd4[psd4>0]), label = 'LIGO')\n",
    "\n",
    "plt.loglog(psd5.sample_frequencies[psd5>0], np.sqrt(psd5[psd5>0]), label = 'B_DECIGO')\n",
    "\n",
    "plt.loglog(psd6.sample_frequencies[psd6>0], np.sqrt(psd6[psd6>0]), label = 'DECIGO')\n",
    "\n",
    "\n",
    "\n",
    "plt.xlim(1e-4, 2048)\n",
    "\n",
    "plt.xlabel(\"Frequency / Hz\")\n",
    "plt.ylabel(\"$\\sqrt{S_{n}(f) \\ / \\ (Hz^{-1})}$\")\n",
    "plt.legend(loc = 'upper right')\n",
    "plt.grid(linestyle = \"dotted\", color = \"#d3d3d3\" , which=\"both\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
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   "display_name": "pycbc",
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   "title_cell": "Table of Contents",
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   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
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     "delete_cmd_postfix": ") ",
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   "types_to_exclude": [
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