{ "cells": [ { "cell_type": "markdown", "id": "4f5e5334", "metadata": {}, "source": [ "# Probability of Detection (Pdet) generation and comparison\n", "\n", "This notebook is a full guide on how to use the `gwsnr` package to generate the Pdet for a given Gravitational Wave (GW) signal parameters.\n", "\n", "## Contents of this notebook\n", "\n", "Calculation by considering $P_{\\rm det}$ as,\n", "- Boolean (detected if 1, not detected if 0)\n", " - with $\\rho_{\\rm obs}$ as non-central $\\chi$ distribution\n", " - with $\\rho_{\\rm obs}$ as Gaussian distribution\n", " - with $\\rho_{\\rm opt}$ as Fixed SNR.\n", "- Probabilistic (between 0 and 1)\n", " - with $\\rho_{\\rm obs}$ as non-central $\\chi$ distribution\n", " - with $\\rho_{\\rm obs}$ as Gaussian distribution\n", "\n", "For snr generation, in this example notebook, I will use the default snr_method, i.e. 'interpolation_aligned_spins'. Please refer to the snr_generation.ipynb for more details on snr generation methods.\n", "\n", "'pdet_kwargs' can be initialized while creating the GWSNR class object or the pdet related parameters can be passed while calling the pdet calculation method.\n", "\n", "Note: For more details on Pdet calculation methods, please refer to the [gwsnr documentation](https://gwsnr.hemantaph.com)." ] }, { "cell_type": "code", "execution_count": 98, "id": "b49df749", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Initializing GWSNR class...\n", "\n", "psds not given. Choosing bilby's default psds\n", "Interpolator will be loaded for L1 detector from ./interpolator_pickle/L1/partialSNR_dict_3.pickle\n", "Interpolator will be loaded for H1 detector from ./interpolator_pickle/H1/partialSNR_dict_3.pickle\n", "Interpolator will be loaded for V1 detector from ./interpolator_pickle/V1/partialSNR_dict_3.pickle\n", "\n", "\n", "Network Pdet (boolean, non-central chi2) : [0 1 1]\n" ] } ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from datetime import datetime\n", "import gwsnr\n", "np.random.seed(42)\n", "\n", "gwsnr = gwsnr.GWSNR(\n", " npool=4,\n", " snr_method='interpolation_aligned_spins', \n", " gwsnr_verbose=False,\n", " waveform_approximant='IMRPhenomD',\n", " # pdet_kwargs=dict(snr_th=10.0, snr_th_net=10.0, pdet_type='boolean', distribution_type='noncentral_chi2') # 'pdet_kwargs' can be initialized while creating the GWSNR class object or the pdet related settings can be passed while calling the pdet calculation method.\n", ")\n", "\n", "mass_1 = np.array([2,50.,100.,])\n", "ratio = 0.9\n", "dl = 500\n", "# pdet with default settings \n", "pdet = gwsnr.pdet(mass_1=mass_1, mass_2=mass_1*ratio, luminosity_distance=dl)\n", "\n", "print(\"Network Pdet (boolean, non-central chi2) : \", pdet['pdet_net'])" ] }, { "cell_type": "code", "execution_count": 102, "id": "96f85908", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "--2025-10-28 13:12:44-- https://raw.githubusercontent.com/hemantaph/gwsnr/refs/heads/main/tests/integration/bbh_gw_params.json\n", "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.110.133, 185.199.109.133, 185.199.108.133, ...\n", "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.110.133|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 4986213 (4.8M) [text/plain]\n", "Saving to: ‘bbh_gw_params.json’\n", "\n", "bbh_gw_params.json 100%[===================>] 4.75M 16.5MB/s in 0.3s \n", "\n", "2025-10-28 13:12:44 (16.5 MB/s) - ‘bbh_gw_params.json’ saved [4986213/4986213]\n", "\n" ] } ], "source": [ "# get `ler` package generated GW parameters for BBH\n", "!wget https://raw.githubusercontent.com/hemantaph/gwsnr/refs/heads/main/tests/integration/bbh_gw_params.json" ] }, { "cell_type": "code", "execution_count": 103, "id": "0d367158", "metadata": {}, "outputs": [], "source": [ "# # delete the downloaded json file\n", "# !rm bbh_gw_params.json" ] }, { "cell_type": "code", "execution_count": 104, "id": "005e9432", "metadata": {}, "outputs": [], "source": [ "from gwsnr.utils import get_param_from_json\n", "param_dict = get_param_from_json('bbh_gw_params.json')" ] }, { "cell_type": "markdown", "id": "c52cf0e6", "metadata": {}, "source": [ "## Boolean Pdet calculation\n", "\n", "### Non-Central $\\chi$ distribution" ] }, { "cell_type": "code", "execution_count": 105, "id": "7dab2f97", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0 0 1 0 0]\n", "[ 3.16872665 3.63206794 13.38517257 2.50378508 2.62985054]\n", "Detectable fraction of the population : 0.0036\n" ] } ], "source": [ "pdet_chi2 = gwsnr.pdet(\n", " gw_param_dict=param_dict,\n", " snr_th_net=10.0,\n", " pdet_type='boolean',\n", " distribution_type='noncentral_chi2',\n", " include_observed_snr=True, # to include observed SNR values in the output dictionary\n", ")\n", "# print the first 5 pdet values\n", "print(pdet_chi2['pdet_net'][:5])\n", "print(pdet_chi2['observed_snr_net'][:5])\n", "\n", "# find and print detectable fraction\n", "detectable_fraction = np.mean(pdet_chi2['pdet_net'])\n", "print(\"Detectable fraction of the population : \", detectable_fraction)" ] }, { "cell_type": "markdown", "id": "c477600c", "metadata": {}, "source": [ "### Gaussian distribution" ] }, { "cell_type": "code", "execution_count": 20, "id": "49aaec2e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0 1 1 0 0]\n", "[ 4.87782373 15.50141248 14.35847191 3.64935961 2.98302797]\n", "Detectable fraction of the population : 0.34\n" ] } ], "source": [ "pdet_gauss = gwsnr.pdet(\n", " gw_param_dict=param_dict,\n", " snr_th_net=10.0,\n", " pdet_type='boolean',\n", " distribution_type='gaussian',\n", " include_observed_snr=True\n", ")\n", "# print the first 5 pdet values\n", "print(pdet_gauss['pdet_net'][:5])\n", "print(pdet_gauss['observed_snr_net'][:5])\n", "\n", "# find and print detectable fraction\n", "detectable_fraction = np.mean(pdet_gauss['pdet_net'])\n", "print(\"Detectable fraction of the population : \", detectable_fraction)" ] }, { "cell_type": "markdown", "id": "d0608a28", "metadata": {}, "source": [ "### Fixed SNR" ] }, { "cell_type": "code", "execution_count": 21, "id": "d608c251", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0 1 1 0 0]\n", "[ 4.21494246 14.32793862 14.17745035 4.94619156 2.58334002]\n", "Detectable fraction of the population : 0.32\n" ] } ], "source": [ "pdet_optsnr = gwsnr.pdet(\n", " gw_param_dict=param_dict,\n", " snr_th_net=10.0,\n", " pdet_type='boolean',\n", " distribution_type='fixed_snr',\n", " include_observed_snr=True, # here observed_snr_net will be same as optimal SNR\n", ")\n", "# print the first 5 pdet values\n", "print(pdet_optsnr['pdet_net'][:5])\n", "print(pdet_optsnr['observed_snr_net'][:5])\n", "\n", "# find and print detectable fraction\n", "detectable_fraction = np.mean(pdet_optsnr['pdet_net'])\n", "print(\"Detectable fraction of the population : \", detectable_fraction)" ] }, { "cell_type": "markdown", "id": "aecf0432", "metadata": {}, "source": [ "### Visulalization and Comparison Observed SNR distributions wrt to Optimal SNR" ] }, { "cell_type": "code", "execution_count": 25, "id": "ef704dca", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "snr_opt = pdet_optsnr['observed_snr_net']\n", "snr_obs_chi2 = pdet_chi2['observed_snr_net']\n", "snr_obs_gauss = pdet_gauss['observed_snr_net']\n", "\n", "dist1 = snr_opt - snr_obs_chi2\n", "dist2 = snr_opt - snr_obs_gauss\n", "\n", "# create kde plots to compare the two distributions\n", "from scipy.stats import gaussian_kde\n", "\n", "kde1 = gaussian_kde(dist1)\n", "kde2 = gaussian_kde(dist2)\n", "x = np.linspace(-4, 4, 1000)\n", "\n", "plt.figure(figsize=(10,6))\n", "# plt.hist(dist1, bins=30, alpha=0.5, label='Non-central Chi2', color='blue', density=True, histtype='step')\n", "# plt.hist(dist2, bins=30, alpha=0.5, label='Gaussian', color='orange', density=True, histtype='step')\n", "plt.plot(x, kde1(x), label='Non-central Chi2', color='blue')\n", "plt.plot(x, kde2(x), label='Gaussian', color='orange')\n", "plt.title('Distribution of (Optimal SNR - Observed SNR)', fontsize=16)\n", "plt.xlabel('Optimal SNR - Observed SNR', fontsize=14)\n", "plt.ylabel('Density', fontsize=14)\n", "plt.legend(fontsize=12)\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "f06ecc15", "metadata": {}, "source": [ "## Probabilistic Pdet calculation\n", "\n", "\n", "### Non-Central $\\chi$ distribution" ] }, { "cell_type": "code", "execution_count": 27, "id": "db8a958e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[3.13236730e-08 9.99997133e-01 9.99994244e-01 1.26963490e-06\n", " 1.70041758e-12]\n", "[ 4.21494246 14.32793862 14.17745035 4.94619156 2.58334002]\n", "Detectable fraction of the population : 0.3272490373160273\n" ] } ], "source": [ "pdet_chi2 = gwsnr.pdet(\n", " gw_param_dict=param_dict,\n", " snr_th_net=10.0,\n", " pdet_type='probability_distribution',\n", " distribution_type='noncentral_chi2',\n", " include_optimal_snr=True, # to include optimal SNR values in the output dictionary\n", ")\n", "# print the first 5 pdet values\n", "print(pdet_chi2['pdet_net'][:5])\n", "print(pdet_chi2['optimal_snr_net'][:5])\n", "\n", "# find and print detectable fraction\n", "detectable_fraction = np.mean(pdet_chi2['pdet_net'])\n", "print(\"Detectable fraction of the population : \", detectable_fraction)" ] }, { "cell_type": "markdown", "id": "95551154", "metadata": {}, "source": [ "### Gaussian distribution" ] }, { "cell_type": "code", "execution_count": 28, "id": "3b225aea", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[3.62437580e-09 9.99992474e-01 9.99985260e-01 2.16542995e-07\n", " 6.00630656e-14]\n", "[ 4.21494246 14.32793862 14.17745035 4.94619156 2.58334002]\n", "Detectable fraction of the population : 0.32040024945890544\n" ] } ], "source": [ "pdet_gauss = gwsnr.pdet(\n", " gw_param_dict=param_dict,\n", " snr_th_net=10.0,\n", " pdet_type='probability_distribution',\n", " distribution_type='gaussian',\n", " include_optimal_snr=True\n", ")\n", "# print the first 5 pdet values\n", "print(pdet_gauss['pdet_net'][:5])\n", "print(pdet_gauss['optimal_snr_net'][:5])\n", "\n", "# find and print detectable fraction\n", "detectable_fraction = np.mean(pdet_gauss['pdet_net'])\n", "print(\"Detectable fraction of the population : \", detectable_fraction)" ] }, { "cell_type": "code", "execution_count": 97, "id": "aef9a146", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.9997810824868587\n", "0.9993681083703562\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "### Visulalization Pdet based on Probability distribution of Observed SNR wrt to Optimal SNR\n", "from scipy.stats import norm, ncx2\n", "min_snr = 7\n", "max_snr = 15\n", "x_values = np.linspace(min_snr, max_snr, 1000)\n", "# pdet_gauss['pdet_net'] between 0.2 and 0.5\n", "selected_indices = np.where((pdet_gauss['pdet_net'] >= 0.5) & (pdet_gauss['pdet_net'] <= 0.9))[0]\n", "selected_index = selected_indices[0]\n", "\n", "# Non-central Chi2 distribution case\n", "size = 1000\n", "nc_param = pdet_chi2['optimal_snr_net'][selected_index]**2\n", "df = 2 * len(gwsnr.detector_list)\n", "pdf_dist1 = ncx2.pdf(x_values**2, df=df, nc=nc_param)\n", "print(np.trapz(pdf_dist1, x_values**2))\n", "# normalize the pdf; or you might need to take care of Jacobian while plotting\n", "# pdf_dist1 /= np.trapz(pdf_dist1, x_values)\n", "\n", "# Gaussian distribution case\n", "size = 1000\n", "mu = pdet_gauss['optimal_snr_net'][selected_index]\n", "sigma = 1.0 # standard deviation\n", "pdf_dist2 = norm(loc=mu, scale=sigma)\n", "pdf_dist2 = pdf_dist2.pdf(x_values)\n", "print(np.trapz(pdf_dist2, x_values))\n", "# pdf_dist2 /= np.trapz(pdf_dist2, x_values)\n", "\n", "\n", "plt.figure(figsize=(10,6))\n", "\n", "plt.plot(x_values, pdf_dist1 * 2 * x_values, label='Non-central Chi2 Distribution', color='C0')\n", "plt.fill_between(x_values, 0, pdf_dist1 * 2 * x_values, where=(x_values >= 10.0), alpha=0.2, color='C0', label=f'Detectable region (Chi2) Pdet={pdet_chi2[\"pdet_net\"][selected_index]:.2f}')\n", "\n", "plt.plot(x_values, pdf_dist2, label='Gaussian Distribution', color='C1')\n", "plt.fill_between(x_values, 0, pdf_dist2, where=(x_values >= 10.0), alpha=0.1, color='C1', label=f'Detectable region (Gaussian) Pdet={pdet_gauss[\"pdet_net\"][selected_index]:.2f}')\n", "\n", "\n", "plt.title('Observed SNR Distributions for Optimal SNR = {:.2f}'.format(pdet_gauss['optimal_snr_net'][selected_index]), fontsize=16)\n", "# vertical line for SNR threshold\n", "plt.axvline(x=10.0, color='k', linestyle='--', label='SNR Threshold = 10.0')\n", "plt.axvline(x=pdet_chi2['optimal_snr_net'][selected_index], color='C2', linestyle='--', label=f'Optimal SNR = {pdet_chi2[\"optimal_snr_net\"][selected_index]:.2f}')\n", "\n", "plt.legend(fontsize=12, loc='upper right')\n", "plt.xlim(7, 15)\n", "plt.ylim(0, None)\n", "plt.xlabel('Observed SNR', fontsize=14)\n", "plt.ylabel('Density', fontsize=14)\n", "plt.grid()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 100, "id": "3fe900be", "metadata": {}, "outputs": [], "source": [ "# delete the downloaded json file\n", "!rm bbh_gw_params.json" ] } ], "metadata": { "kernelspec": { "display_name": "gwsnr", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.18" } }, "nbformat": 4, "nbformat_minor": 5 }