{ "cells": [ { "cell_type": "markdown", "id": "edfdf214", "metadata": {}, "source": [ "# GWRATES complete example\n", "\n", "This notebook is created by [Phurailatpam Hemantakumar](https://hemantaph.com).\n", "\n", "[![Documentation](https://img.shields.io/badge/ler-documentation-blue)](https://ler.hemantaph.com) \n", "\n", "GWRATES is a comprehensive framework for simulating gravitational wave (GW) events and calculating their detection rates. This notebook provides a complete example of CBC event simulation and rate calculation.\n", "\n", "## Table of Contents\n", "\n", "1. [Part 1: Basic GW Event Simulation and Rate Calculation (BBH Example)](#part-1-basic-gw-event-simulation-and-rate-calculation-bbh-example)\n", " - [1.1 Initialize GWRATES](#11-initialize-gwrates)\n", " - [1.2 Simulate GW Population](#12-simulate-gw-population)\n", " - [1.3 Calculate Detection Rates](#13-calculate-detection-rates)\n", " - [1.4 Inspect Generated Parameters](#14-inspect-generated-parameters)\n", " - [1.5 Access Saved Data Files](#15-access-saved-data-files)\n", " - [1.6 Load and Examine Saved Parameters](#16-load-and-examine-saved-parameters)\n", " - [1.7 Examine Available Prior Functions](#17-examine-available-prior-functions)\n", " - [1.8 Visualize Parameter Distributions](#18-visualize-parameter-distributions)\n", "\n", "2. [Part 2: Custom Functions and Parameters](#part-2-custom-functions-and-parameters)\n", " - [2.1 Define Custom Source Frame Masses](#21-define-custom-source-frame-masses)\n", " - [2.2 Define Event Type with Non-Spinning Configuration](#22-define-event-type-with-non-spinning-configuration)\n", " - [2.3 Define Custom Merger Rate Density](#23-define-custom-merger-rate-density)\n", " - [2.4 Define Custom Detection Criteria](#24-define-custom-detection-criteria)\n", " - [2.5 Initialize GWRATES with Custom Settings](#25-initialize-gwrates-with-custom-settings)\n", " - [2.6 Sample GW Parameters with Custom Settings](#26-sample-gw-parameters-with-custom-settings)\n", " - [2.7 Calculate Rates with Custom Settings](#27-calculate-rates-with-custom-settings)\n", " - [2.8 Compare Default and Custom Mass Distributions](#28-compare-default-and-custom-mass-distributions)\n", "\n", "3. [Part 3: Advanced Sampling - Generating Detectable Events](#part-3-advanced-sampling---generating-detectable-events)\n", " - [3.1 Initialize GWRATES for N-Event Sampling](#31-initialize-gwrates-for-n-event-sampling)\n", " - [3.2 Sample Until N Detectable Events Are Found](#32-sample-until-n-detectable-events-are-found)\n", " - [3.3 Analyze Rate Convergence](#33-analyze-rate-convergence)\n", " - [3.4 Assess Rate Stability](#34-assess-rate-stability)\n", " - [3.5 Overlapping plot between the all sampled and detectable event parameters](#35-overlapping-plot-between-the-all-sampled-and-detectable-event-parameters)" ] }, { "cell_type": "markdown", "id": "0f484508", "metadata": {}, "source": [ "---\n", "\n", "## Part 1: Basic GW Event Simulation and Rate Calculation (BBH Example)\n", "\n", "This section demonstrates a quick example to simulate binary black hole mergers and calculate their detection rates.\n", "\n" ] }, { "cell_type": "markdown", "id": "934a793a", "metadata": {}, "source": [ "### 1.1 Initialize GWRATES\n", "\n", "The `GWRATES` class is the main interface for simulating GW events and calculating rates. By default, it uses:\n", "- **Event type:** BBH (Binary Black Hole)\n", "- **Detectors:** H1, L1, V1 (LIGO Hanford, LIGO Livingston, Virgo) with O4 design sensitivity\n", "\n", "All outputs will be saved in the `./ler_data` directory." ] }, { "cell_type": "code", "execution_count": 33, "id": "2c0a5cc2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Initializing GWRATES class...\n", "\n", "\n", "Initializing CBCSourceRedshiftDistribution...\n", "\n", "luminosity_distance interpolator will be loaded from ./interpolator_json/luminosity_distance/luminosity_distance_0.json\n", "differential_comoving_volume interpolator will be loaded from ./interpolator_json/differential_comoving_volume/differential_comoving_volume_0.json\n", "using ler available merger rate density model: merger_rate_density_bbh_oguri2018\n", "merger_rate_density_bbh_oguri2018 interpolator will be loaded from ./interpolator_json/merger_rate_density/merger_rate_density_bbh_oguri2018_0.json\n", "merger_rate_density_detector_frame interpolator will be loaded from ./interpolator_json/merger_rate_density/merger_rate_density_detector_frame_1.json\n", "source_redshift interpolator will be loaded from ./interpolator_json/source_redshift/source_redshift_0.json\n", "\n", "Initializing CBCSourceParameterDistribution...\n", "\n", "using ler available zs function : source_redshift\n", "using ler available source_frame_masses function : binary_masses_BBH_popI_II_powerlaw_gaussian\n", "using ler available geocent_time function : sampler_uniform\n", "using ler available ra function : sampler_uniform\n", "using ler available dec function : sampler_cosine\n", "using ler available phase function : sampler_uniform\n", "using ler available psi function : sampler_uniform\n", "using ler available theta_jn function : sampler_sine\n", "using ler available a_1 function : sampler_uniform\n", "using ler available a_2 function : sampler_uniform\n", "\n", "Initializing GWSNR class...\n", "\n", "psds not given. Choosing bilby's default psds\n", "Interpolator will be loaded for L1 detector from ./interpolator_json/L1/partialSNR_dict_0.json\n", "Interpolator will be loaded for H1 detector from ./interpolator_json/H1/partialSNR_dict_0.json\n", "Interpolator will be loaded for V1 detector from ./interpolator_json/V1/partialSNR_dict_0.json\n", "\n", "Chosen GWSNR initialization parameters:\n", "\n", "npool: 4\n", "snr type: interpolation_aligned_spins\n", "waveform approximant: IMRPhenomD\n", "sampling frequency: 2048.0\n", "minimum frequency (fmin): 20.0\n", "reference frequency (f_ref): 20.0\n", "mtot=mass1+mass2\n", "min(mtot): 9.96\n", "max(mtot) (with the given fmin=20.0): 500.0\n", "detectors: ['L1', 'H1', 'V1']\n", "psds: [[array([ 10.21659, 10.23975, 10.26296, ..., 4972.81 ,\n", " 4984.081 , 4995.378 ], shape=(2736,)), array([4.43925574e-41, 4.22777986e-41, 4.02102594e-41, ...,\n", " 6.51153524e-46, 6.43165104e-46, 6.55252996e-46],\n", " shape=(2736,)), ], [array([ 10.21659, 10.23975, 10.26296, ..., 4972.81 ,\n", " 4984.081 , 4995.378 ], shape=(2736,)), array([4.43925574e-41, 4.22777986e-41, 4.02102594e-41, ...,\n", " 6.51153524e-46, 6.43165104e-46, 6.55252996e-46],\n", " shape=(2736,)), ], [array([ 10. , 10.02306 , 10.046173, ...,\n", " 9954.0389 , 9976.993 , 10000. ], shape=(3000,)), array([1.22674387e-42, 1.20400299e-42, 1.18169466e-42, ...,\n", " 1.51304203e-43, 1.52010157e-43, 1.52719372e-43],\n", " shape=(3000,)), ]]\n", "\n", "\n", "#----------------------------------------\n", "# GWRATES initialization input arguments:\n", "#----------------------------------------\n", "\n", " # GWRATES set up input arguments:\n", " npool = 4,\n", " z_min = 0.0,\n", " z_max = 10.0,\n", " event_type = 'BBH',\n", " cosmology = LambdaCDM(H0=70.0 km / (Mpc s), Om0=0.3, Ode0=0.7, Tcmb0=0.0 K, Neff=3.04, m_nu=None, Ob0=None),\n", " pdet_finder = >,\n", " json_file_names = dict(\n", " gwrates_params = 'gwrates_params.json',\n", " gw_param = 'gw_param.json',\n", " gw_param_detectable = 'gw_param_detectable.json',\n", " ),\n", " interpolator_directory = './interpolator_json',\n", " ler_directory = './ler_data',\n", "\n", " # GWRATES also takes other CBCSourceParameterDistribution class input arguments as kwargs, as follows:\n", " source_priors = dict(\n", " merger_rate_density = 'merger_rate_density_bbh_oguri2018',\n", " zs = 'source_redshift',\n", " source_frame_masses = 'binary_masses_BBH_popI_II_powerlaw_gaussian',\n", " geocent_time = 'sampler_uniform',\n", " ra = 'sampler_uniform',\n", " dec = 'sampler_cosine',\n", " phase = 'sampler_uniform',\n", " psi = 'sampler_uniform',\n", " theta_jn = 'sampler_sine',\n", " a_1 = 'sampler_uniform',\n", " a_2 = 'sampler_uniform',\n", " ),\n", " source_priors_params = dict(\n", " merger_rate_density = {'R0': 2.39e-08, 'b2': 1.6, 'b3': 2.1, 'b4': 30},\n", " zs = None,\n", " source_frame_masses = {'mminbh': 4.98, 'mmaxbh': 112.5, 'alpha': 3.78, 'mu_g': 32.27, 'sigma_g': 3.88, 'lambda_peak': 0.03, 'delta_m': 4.8, 'beta': 0.81},\n", " geocent_time = {'xmin': 1238166018, 'xmax': 1269702018},\n", " ra = {'xmin': 0.0, 'xmax': 6.283185307179586},\n", " dec = None,\n", " phase = {'xmin': 0.0, 'xmax': 6.283185307179586},\n", " psi = {'xmin': 0.0, 'xmax': 3.141592653589793},\n", " theta_jn = None,\n", " a_1 = {'xmin': -0.8, 'xmax': 0.8},\n", " a_2 = {'xmin': -0.8, 'xmax': 0.8},\n", " ),\n", " spin_zero = False,\n", " spin_precession = False,\n", "\n", " # GWRATES also takes other gwsnr.GWSNR input arguments as kwargs, as follows:\n", " npool = 4,\n", " snr_method = 'interpolation_aligned_spins',\n", " snr_type = 'optimal_snr',\n", " gwsnr_verbose = True,\n", " multiprocessing_verbose = True,\n", " pdet_kwargs = dict(\n", " snr_th = 10.0,\n", " snr_th_net = 10.0,\n", " pdet_type = 'boolean',\n", " distribution_type = 'noncentral_chi2',\n", " include_optimal_snr = False,\n", " include_observed_snr = False,\n", " ),\n", " mtot_min = 9.96,\n", " mtot_max = 500.0,\n", " ratio_min = 0.1,\n", " ratio_max = 1.0,\n", " spin_max = 0.99,\n", " mtot_resolution = 200,\n", " ratio_resolution = 20,\n", " spin_resolution = 10,\n", " batch_size_interpolation = 1000000,\n", " interpolator_dir = './interpolator_json',\n", " create_new_interpolator = False,\n", " sampling_frequency = 2048.0,\n", " waveform_approximant = 'IMRPhenomD',\n", " frequency_domain_source_model = 'lal_binary_black_hole',\n", " minimum_frequency = 20.0,\n", " reference_frequency = None,\n", " duration_max = None,\n", " duration_min = None,\n", " fixed_duration = None,\n", " mtot_cut = False,\n", " psds = None,\n", " ifos = None,\n", " noise_realization = None,\n", " ann_path_dict = None,\n", " snr_recalculation = False,\n", " snr_recalculation_range = [6, 14],\n", " snr_recalculation_waveform_approximant = 'IMRPhenomXPHM',\n", " psds_list = [[array([ 10.21659, 10.23975, 10.26296, ..., 4972.81 ,\n", " 4984.081 , 4995.378 ], shape=(2736,)), array([4.43925574e-41, 4.22777986e-41, 4.02102594e-41, ...,\n", " 6.51153524e-46, 6.43165104e-46, 6.55252996e-46],\n", " shape=(2736,)), ], [array([ 10.21659, 10.23975, 10.26296, ..., 4972.81 ,\n", " 4984.081 , 4995.378 ], shape=(2736,)), array([4.43925574e-41, 4.22777986e-41, 4.02102594e-41, ...,\n", " 6.51153524e-46, 6.43165104e-46, 6.55252996e-46],\n", " shape=(2736,)), ], [array([ 10. , 10.02306 , 10.046173, ...,\n", " 9954.0389 , 9976.993 , 10000. ], shape=(3000,)), array([1.22674387e-42, 1.20400299e-42, 1.18169466e-42, ...,\n", " 1.51304203e-43, 1.52010157e-43, 1.52719372e-43],\n", " shape=(3000,)), ]],\n" ] } ], "source": [ "# Import the GWRATES class from the ler package\n", "from ler.rates import GWRATES\n", "\n", "# Initialize GWRATES with default settings\n", "ler = GWRATES(verbose=True)" ] }, { "cell_type": "markdown", "id": "6f3cd4d4", "metadata": {}, "source": [ "To print all initialization input arguments, use:\n", "\n", "```python\n", " ler._print_all_init_args()\n", "```" ] }, { "cell_type": "markdown", "id": "10ac8c37", "metadata": {}, "source": [ "### 1.2 Simulate GW Population\n", "\n", "Generate a population of Compact Binary Coalescence (CBC) events. This step:\n", "- Samples intrinsic (masses and spins) and extrinsic (redshift, sky location, inclination angle, etc.) GW parameters from initialized priors\n", "- Calculates the probability of detection (Pdet) for each event based on detector network sensitivity\n", "- Stores the output in `./ler_data/gw_param.json`\n", "\n", "**Parameters:**\n", "- `size`: Total number of events to sample\n", "- `batch_size`: Events per batch (useful for resuming interrupted simulations)\n", "- `resume`: If `True` (default), resume from last saved batch; if `False`, start fresh\n", "- `save_batch`: If `True`, save after each batch; if `False` (default), save only at the end\n", "\n", "**Note:** For realistic results, use `size >= 1,000,000` with `batch_size = 100,000`" ] }, { "cell_type": "code", "execution_count": 36, "id": "29ac1c3b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Simulated GW params will be stored in ./ler_data/gw_param.json\n", "Batch no. 1\n", "sampling gw source params...\n", "calculating pdet...\n", "Batch no. 2\n", "sampling gw source params...\n", "calculating pdet...\n", "saving all gw parameters in ./ler_data/gw_param.json \n", "\n", "Total events simulated: 100000\n", "Sampled redshift values: [1.79134769 3.81532071 6.88004063 0.94640131 0.64046894]\n" ] } ], "source": [ "# Simulate 100,000 GW events in batches of 50,000\n", "gw_param_all = ler.gw_cbc_statistics(100000, resume=False)\n", "\n", "# # with all input args\n", "# gw_param_all = ler.gw_cbc_statistics(size=100000, batch_size=50000, resume=True, save_batch=False, output_jsonfile='gw_param.json') \n", "\n", "print(f\"\\nTotal events simulated: {len(gw_param_all['zs'])}\")\n", "print(f\"Sampled redshift values: {gw_param_all['zs'][:5]}\")" ] }, { "cell_type": "markdown", "id": "3430e3b0", "metadata": {}, "source": [ "### 1.3 Calculate Detection Rates\n", "\n", "Select detectable events and calculate the detection rate. This function:\n", "- Filters events using a Pdet threshold. By default, Pdet is based on observed SNR > 10, where the observed SNR follows a non-central chi-squared distribution centered at the optimal SNR.\n", "- Returns the rate in detectable events per year.\n", "- Saves detectable events to `./ler_data/gw_param_detectable.json`." ] }, { "cell_type": "code", "execution_count": 42, "id": "89f98cbb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Getting gw parameters from json file ./ler_data/gw_param.json...\n", "total GW event rate (yr^-1): 270.52624492169423\n", "number of simulated GW detectable events: 329\n", "number of simulated all GW events: 100000\n", "storing detectable params in ./ler_data/gw_param_detectable.json\n", "\n", "=== Detection Rate Summary ===\n", "Detectable event rate: 2.71e+02 events per year\n", "Total event rate: 8.22e+04 events per year\n", "Percentage fraction of the detectable events: 3.29e-01%\n" ] } ], "source": [ "# Calculate the detection rate and extract detectable events\n", "detectable_rate, gw_param_detectable = ler.gw_rate()\n", "\n", "print(f\"\\n=== Detection Rate Summary ===\")\n", "print(f\"Detectable event rate: {detectable_rate:.2e} events per year\")\n", "print(f\"Total event rate: {ler.normalization_pdf_z:.2e} events per year\")\n", "print(f\"Percentage fraction of the detectable events: {detectable_rate/ler.normalization_pdf_z*100:.2e}%\")" ] }, { "cell_type": "markdown", "id": "f8c86009", "metadata": {}, "source": [ "### 1.4 Inspect Generated Parameters\n", "\n", "View the available parameters in the generated event population." ] }, { "cell_type": "code", "execution_count": 43, "id": "3bf60d3c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Detectable event parameters:\n", "['zs', 'geocent_time', 'ra', 'dec', 'phase', 'psi', 'theta_jn', 'a_1', 'a_2', 'luminosity_distance', 'mass_1_source', 'mass_2_source', 'mass_1', 'mass_2', 'pdet_L1', 'pdet_H1', 'pdet_V1', 'pdet_net']\n", "\n", "Example values for mass_1_source (detector frame):\n", "[27.80174506 13.5874931 26.44581764 15.18232487 11.86442242]\n" ] } ], "source": [ "# List all parameters saved for detectable events\n", "print(\"Detectable event parameters:\")\n", "print(list(gw_param_detectable.keys()))\n", "\n", "print(\"\\nExample values for mass_1_source (detector frame):\")\n", "print(gw_param_detectable['mass_1_source'][:5])" ] }, { "cell_type": "markdown", "id": "f275e751", "metadata": {}, "source": [ "### 1.5 Access Saved Data Files\n", "\n", "All simulation results are saved in JSON files for future reference and analysis." ] }, { "cell_type": "code", "execution_count": 44, "id": "1ca58c88", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Output directory: ./ler_data\n", "\n", "Saved JSON files:\n", " gwrates_params: gwrates_params.json\n", " gw_param: gw_param.json\n", " gw_param_detectable: gw_param_detectable.json\n" ] } ], "source": [ "# View the directory structure and file names\n", "print(f\"Output directory: {ler.ler_directory}\")\n", "print(f\"\\nSaved JSON files:\")\n", "for key, filename in ler.json_file_names.items():\n", " print(f\" {key}: {filename}\")" ] }, { "cell_type": "markdown", "id": "f6790a36", "metadata": {}, "source": [ "### 1.6 Load and Examine Saved Parameters\n", "\n", "Reload parameters from JSON files for further analysis." ] }, { "cell_type": "code", "execution_count": 45, "id": "7dcc7dec", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Parameters loaded from file: ['zs', 'geocent_time', 'ra', 'dec', 'phase', 'psi', 'theta_jn', 'a_1', 'a_2', 'luminosity_distance', 'mass_1_source', 'mass_2_source', 'mass_1', 'mass_2', 'pdet_L1', 'pdet_H1', 'pdet_V1', 'pdet_net']\n", "\n", "Detectable event rate (from saved file): 2.7053e+02 per year\n" ] } ], "source": [ "from ler.utils import get_param_from_json, load_json\n", "\n", "# Load detectable parameters from file\n", "gw_param_from_file = get_param_from_json(\n", " ler.ler_directory + '/' + ler.json_file_names['gw_param_detectable']\n", ")\n", "\n", "print(f\"Parameters loaded from file: {list(gw_param_from_file.keys())}\")\n", "\n", "# Load the initialization parameters and rates\n", "gwrates_params = load_json(ler.ler_directory + '/gwrates_params.json')\n", "print(f\"\\nDetectable event rate (from saved file): {gwrates_params['detectable_gw_rate_per_year']:.4e} per year\")" ] }, { "cell_type": "markdown", "id": "9a62567b", "metadata": {}, "source": [ "### 1.7 Examine Available Prior Functions\n", "\n", "View the built-in GW parameter sampler functions and their default parameters." ] }, { "cell_type": "code", "execution_count": 48, "id": "d09c110f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Built-in GW parameter sampler functions and parameters:\n", "\n", "merger_rate_density:\n", " merger_rate_density_bbh_oguri2018: {'R0': 2.39e-08, 'b2': 1.6, 'b3': 2.1, 'b4': 30}\n", " sfr_madau_fragos2017: {'a': 0.01, 'b': 2.6, 'c': 3.2, 'd': 6.2}\n", " sfr_madau_dickinson2014: {'a': 0.015, 'b': 2.7, 'c': 2.9, 'd': 5.6}\n", " sfr_with_time_delay: {'R0': 2.39e-08, 'a': 0.01, 'b': 2.6, 'c': 3.2, 'd': 6.2, 'td_min': 0.01, 'td_max': 10.0}\n", " merger_rate_density_bbh_popIII_ken2022: {'n0': 1.92e-08, 'aIII': 0.66, 'bIII': 0.3, 'zIII': 11.6}\n", " merger_rate_density_bbh_primordial_ken2022: {'n0': 4.4e-11, 't0': 13.786885302009708}\n", " sfr_madau_fragos2017_with_bbh_dt: {'R0': 2.39e-08}\n", " sfr_madau_dickinson2014_with_bbh_dt: {'R0': 2.39e-08}\n", " sfr_madau_fragos2017_with_bns_dt: {'R0': 1.0550000000000001e-07}\n", " sfr_madau_dickinson2014_with_bns_dt: {'R0': 1.0550000000000001e-07}\n", "\n", "zs:\n", " source_redshift: None\n", "\n", "source_frame_masses:\n", " binary_masses_BBH_popI_II_powerlaw_gaussian: {'mminbh': 4.98, 'mmaxbh': 112.5, 'alpha': 3.78, 'mu_g': 32.27, 'sigma_g': 3.88, 'lambda_peak': 0.03, 'delta_m': 4.8, 'beta': 0.81}\n", " binary_masses_BBH_popIII_lognormal: {'m_min': 5.0, 'm_max': 150.0, 'Mc': 30.0, 'sigma': 0.3}\n", " binary_masses_BBH_primordial_lognormal: {'m_min': 1.0, 'm_max': 100.0, 'Mc': 20.0, 'sigma': 0.3}\n", " binary_masses_NSBH_broken_powerlaw: {'mminbh': 26, 'mmaxbh': 125, 'alpha_1': 6.75, 'alpha_2': 6.75, 'b': 0.5, 'delta_m': 5, 'mminns': 1.0, 'mmaxns': 3.0, 'alphans': 0.0}\n", " binary_masses_uniform: {'m_min': 1.0, 'm_max': 3.0}\n", " binary_masses_BNS_bimodal: {'w': 0.643, 'muL': 1.352, 'sigmaL': 0.08, 'muR': 1.88, 'sigmaR': 0.3, 'mmin': 1.0, 'mmax': 2.3}\n", "\n", "a_1:\n", " constant_values_n_size: {'value': 0.0}\n", " sampler_uniform: {'xmin': -0.8, 'xmax': 0.8}\n", "\n", "a_2:\n", " constant_values_n_size: {'value': 0.0}\n", " sampler_uniform: {'xmin': -0.8, 'xmax': 0.8}\n", "\n", "tilt_1:\n", " constant_values_n_size: {'value': 0.0}\n", " sampler_sine: None\n", "\n", "tilt_2:\n", " constant_values_n_size: {'value': 0.0}\n", " sampler_sine: None\n", "\n", "phi_12:\n", " constant_values_n_size: {'value': 0.0}\n", " sampler_uniform: {'xmin': 0.0, 'xmax': 6.283185307179586}\n", "\n", "phi_jl:\n", " constant_values_n_size: {'value': 0.0}\n", " sampler_uniform: {'xmin': 0.0, 'xmax': 6.283185307179586}\n", "\n", "geocent_time:\n", " sampler_uniform: {'xmin': 1238166018, 'xmax': 1269723618.0}\n", " constant_values_n_size: {'value': 1238166018}\n", "\n", "ra:\n", " sampler_uniform: {'xmin': 0.0, 'xmax': 6.283185307179586}\n", " constant_values_n_size: {'value': 0.0}\n", "\n", "dec:\n", " sampler_cosine: None\n", " constant_values_n_size: {'value': 0.0}\n", " sampler_uniform: {'xmin': -1.5707963267948966, 'xmax': 1.5707963267948966}\n", "\n", "phase:\n", " sampler_uniform: {'xmin': 0.0, 'xmax': 6.283185307179586}\n", " constant_values_n_size: {'value': 0.0}\n", "\n", "psi:\n", " sampler_uniform: {'xmin': 0.0, 'xmax': 3.141592653589793}\n", " constant_values_n_size: {'value': 0.0}\n", "\n", "theta_jn:\n", " sampler_sine: None\n", " constant_values_n_size: {'value': 0.0}\n", " sampler_uniform: {'xmin': 0.0, 'xmax': 3.141592653589793}\n", "\n" ] } ], "source": [ "# Display all available GW prior sampler functions\n", "print(\"Built-in GW parameter sampler functions and parameters:\\n\")\n", "for func_name, func_params in ler.available_gw_prior.items():\n", " print(f\"{func_name}:\")\n", " \n", " if isinstance(func_params, dict):\n", " for param_name, param_value in func_params.items():\n", " print(f\" {param_name}: {param_value}\")\n", " else:\n", " print(f\" {func_params}\")\n", " print()" ] }, { "cell_type": "markdown", "id": "5550d6a4", "metadata": {}, "source": [ "### 1.8 Visualize Parameter Distributions\n", "\n", "Create KDE (Kernel Density Estimation) plots to compare the distributions of parameters between all simulated events and detectable events." ] }, { "cell_type": "code", "execution_count": 49, "id": "62543440", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "getting gw_params from json file ler_data/gw_param_detectable.json...\n", "getting gw_params from json file ler_data/gw_param.json...\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "from ler.utils import plots as lerplt\n", "\n", "\n", "# input param_dict can be either a dictionary or a json file name that contains the parameters\n", "plt.figure(figsize=(6, 4))\n", "lerplt.param_plot(\n", " param_name='zs',\n", " param_dict='ler_data/gw_param_detectable.json',\n", " plot_label='zs (detectable)',\n", ")\n", "lerplt.param_plot(\n", " param_name='zs',\n", " param_dict='ler_data/gw_param.json',\n", " plot_label='zs (all)',\n", ")\n", "plt.xlim(0.001,8)\n", "plt.xlabel('zs')\n", "plt.ylabel('pdf')\n", "plt.grid(alpha=0.4)\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "1d8ea8dd", "metadata": {}, "source": [ "---\n", "\n", "## Part 2: Custom Functions and Parameters\n", "\n", "This section demonstrates how to customize GWRATES with your own sampling functions and detection criteria. We'll create a BNS (Binary Neutron Star) example with custom settings:\n", "\n", "| Component | Custom Configuration | Default (BBH) |\n", "| :--- | :--- | :--- |\n", "| **Event Type** | BNS (non-spinning) | BBH (spinning, aligned) |\n", "| **Merger Rate** | Madau-Dickinson (2014) | GWTC-4 based |\n", "| **Source Masses** | Uniform 1.0-2.3 $M_{\\odot}$ | Bimodal Gaussian |\n", "| **Detectors** | 3G (ET, CE), SNR > 12 | O4 (H1, L1, V1), SNR > 10 |\n", "\n", "**Notes:**\n", "- **GW parameter sampling priors**: Should be a function with `size` as the only input argument. Can also be a class object of `ler.utils.FunctionConditioning`.\n", "- **Merger rate density**: Should be a function of F(z)." ] }, { "cell_type": "markdown", "id": "def3a315", "metadata": {}, "source": [ "### 2.2 Define Event Type with Non-Spinning Configuration\n", "\n", "Using `event_type='BNS'` in the LeR class initialization will default to the following GW parameter priors corresponding to BNS. Other allowed event types are 'BBH' and 'NSBH'.\n", "\n", "```python\n", " source_priors = dict(\n", " merger_rate_density = 'merger_rate_density_madau_dickinson2014',\n", " source_frame_masses = 'binary_masses_BNS_bimodal',\n", " a_1 = 'sampler_uniform',\n", " a_2 = 'sampler_uniform',\n", " ),\n", " source_priors_params= dict(\n", " merger_rate_density = dict(\n", " R0=89 * 1e-9, \n", " a=0.015, \n", " b=2.7, \n", " c=2.9, \n", " d=5.6,\n", " ),\n", " source_frame_masses = dict(\n", " w=0.643, \n", " muL=1.352, \n", " sigmaL=0.08, \n", " muR=1.88, \n", " sigmaR=0.3, \n", " mmin=1.0, \n", " mmax=2.3,\n", " ),\n", " a_1 = dict(xmin=-0.05, xmax=0.05),\n", " a_2 = dict(xmin=-0.05, xmax=0.05),\n", " ),\n", "```\n", "\n", "We will change some of these priors with our custom ones in the next sections.\n", "\n", "For non-spinning configuration (faster calculation in our example), we can set:\n", "\n", "```python\n", " spin_zero=True,\n", " spin_precession=False,\n", "```\n", "\n", "### 2.2 Define Custom Merger Rate Density\n", "\n", "Using the default BNS merger rate density prior model, we change the local merger rate density from the default value of $R_0 = 89 \\times 10^{-9} \\, \\text{Mpc}^{-3}\\text{yr}^{-1}$ (GWTC-4) to $R_0 = 105.5 \\times 10^{-9} \\, \\text{Mpc}^{-3}\\text{yr}^{-1}$ (GWTC-3). " ] }, { "cell_type": "markdown", "id": "069fc008", "metadata": {}, "source": [ "### 2.3 Define Custom Merger Rate Density\n", "\n", "Using the default BNS merger rate density prior model, we change the local merger rate density from the default value of $R_0 = 89 \\times 10^{-9} \\, \\text{Mpc}^{-3}\\text{yr}^{-1}$ (GWTC-4) to $R_0 = 105.5 \\times 10^{-9} \\, \\text{Mpc}^{-3}\\text{yr}^{-1}$ (GWTC-3)." ] }, { "cell_type": "code", "execution_count": null, "id": "92009518", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Merger rate density function: merger_rate_density_bbh_oguri2018\n", "Parameters: {'R0': 1.0550000000000001e-07, 'b2': 1.6, 'b3': 2.1, 'b4': 30}\n" ] } ], "source": [ "# Use built-in Madau-Dickinson (2014) SFR based merger rate density for BNS\n", "merger_rate_density_function = 'merger_rate_density_madau_dickinson2014'\n", "\n", "# Custom parameters for merger rate density (Madau-Dickinson model)\n", "merger_rate_density_input_args = dict(\n", " R0=89e-9, # Local merger rate density (Mpc^-3 yr^-1)\n", " a=0.015, # Evolution parameter a\n", " b=2.7, # Evolution parameter b\n", " c=2.9, # Evolution parameter c\n", " d=5.6, # Evolution parameter d\n", ")\n", "\n", "print(\"Merger rate density function:\", merger_rate_density_function)\n", "print(\"Parameters:\", merger_rate_density_input_args)" ] }, { "cell_type": "markdown", "id": "dbf98ac9", "metadata": {}, "source": [ "### 2.1 Define Custom Source Frame Masses\n", "\n", "Use a uniform distribution to sample binary masses (mass_1 and mass_2). Ensure mass_1 >= mass_2 by swapping if necessary." ] }, { "cell_type": "code", "execution_count": null, "id": "164ca568", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Test mass samples:\n", " mass_1: [1.25390248 1.97542099 1.824485 2.15927396 1.63832471]\n", " mass_2: [1.04427987 1.2296851 1.01247127 1.54740765 1.0178791 ]\n", " mass_1 >= mass_2: True\n" ] } ], "source": [ "import numpy as np\n", "\n", "# Define mass range for BNS\n", "source_frame_masses_args = dict(\n", " mmin=1.0, # Minimum mass in solar masses\n", " mmax=2.3, # Maximum mass in solar masses\n", ")\n", "\n", "def source_frame_masses_uniform(size, mmin=source_frame_masses_args['mmin'], mmax=source_frame_masses_args['mmax']):\n", " \"\"\"\n", " Sample mass_1 and mass_2 uniformly from a specified range, ensuring mass_1 >= mass_2 by swapping if necessary.\n", " \n", " Parameters\n", " ----------\n", " size : int\n", " Number of samples to draw\n", " mmin : float, optional\n", " Minimum mass in solar masses (default: 1.0)\n", " mmax : float, optional\n", " Maximum mass in solar masses (default: 2.3)\n", " \n", " Returns\n", " -------\n", " mass_1_source : ndarray\n", " Array of primary mass samples (larger mass)\n", " mass_2_source : ndarray\n", " Array of secondary mass samples (smaller mass)\n", " \"\"\"\n", " # Sample masses uniformly\n", " mass_1_source = np.random.uniform(mmin, mmax, size)\n", " mass_2_source = np.random.uniform(mmin, mmax, size)\n", " \n", " # Ensure mass_1 >= mass_2 by swapping if necessary\n", " idx = mass_2_source > mass_1_source\n", " mass_1_source[idx], mass_2_source[idx] = mass_2_source[idx], mass_1_source[idx]\n", " \n", " return (mass_1_source, mass_2_source)\n", "\n", "# Test the function\n", "m1_test, m2_test = source_frame_masses_uniform(size=5)\n", "print(\"Test mass samples:\")\n", "print(f\" mass_1: {m1_test}\")\n", "print(f\" mass_2: {m2_test}\")\n", "print(f\" mass_1 >= mass_2: {(m1_test >= m2_test).all()}\")" ] }, { "cell_type": "markdown", "id": "28690f1e", "metadata": {}, "source": [ "### 2.4 Define Custom Detection Criteria\n", "\n", "Create a custom detection function using 3G detectors (Einstein Telescope and Cosmic Explorer) with a higher SNR threshold. We use `pdet = optimal_SNR_net > 12` instead of the default `pdet` based on `observed_SNR_net > 10`.\n", "\n", "This function takes GW parameters as input and returns Pdet as a boolean or probability array indicating detectability." ] }, { "cell_type": "code", "execution_count": null, "id": "8f421aac", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Initializing GWSNR class...\n", "\n", "Interpolator will be loaded for ET1 detector from ./interpolator_json/ET1/partialSNR_dict_0.json\n", "Interpolator will be loaded for ET2 detector from ./interpolator_json/ET2/partialSNR_dict_0.json\n", "Interpolator will be loaded for ET3 detector from ./interpolator_json/ET3/partialSNR_dict_0.json\n", "Interpolator will be loaded for CE detector from ./interpolator_json/CE/partialSNR_dict_0.json\n", "\n", "\n", "Custom detection criteria defined for 3G detectors (ET + CE)\n", "Detection network threshold: 12 SNR\n", "\n", "Test Pdet calculation:\n", " mass_1 array : [2. 2.]\n", " mass_2 array : [1. 1.]\n", " luminosity_distance array: [ 1000. 10000.]\n", " Pdet array : {'pdet_net': array([ True, False])}\n" ] } ], "source": [ "from gwsnr import GWSNR\n", "\n", "# Define mass and redshift ranges for BNS\n", "mmin = 1.0\n", "mmax = 2.3\n", "zmin = 0.0\n", "zmax = 10.0\n", "snr_threshold_network = 12 # SNR threshold for detection (default: 10) \n", "\n", "# Initialize GWSNR for 3G detectors (no spins for BNS)\n", "gwsnr_3g = GWSNR(\n", " npool=4,\n", " ifos=['ET', 'CE'], # Einstein Telescope and Cosmic Explorer\n", " snr_method='interpolation_no_spins', # No spin precession for BNS\n", " mtot_min=2*mmin*(1+zmin),\n", " mtot_max=2*mmax*(1+zmax),\n", " sampling_frequency=2048.0,\n", " waveform_approximant='IMRPhenomD',\n", " minimum_frequency=20.0,\n", " gwsnr_verbose=False,\n", ")\n", "\n", "def detection_criteria(gw_param_dict):\n", " \"\"\"\n", " Determine if a gravitational wave event is detectable based on SNR threshold.\n", " \n", " Parameters\n", " ----------\n", " gw_param_dict : dict\n", " Dictionary containing GW parameters including mass_1, mass_2, luminosity_distance, etc.\n", " \n", " Returns\n", " -------\n", " dict\n", " Dictionary with 'pdet_net' (boolean detection array) and 'optimal_snr_net'\n", " \"\"\"\n", " result_dict = {}\n", " \n", " # Calculate optimal SNR for all detectors\n", " snr_dict = gwsnr_3g.optimal_snr(gw_param_dict=gw_param_dict)\n", " \n", " # Apply detection threshold\n", " result_dict['pdet_net'] = snr_dict['optimal_snr_net'] > snr_threshold_network\n", " \n", " return result_dict\n", "\n", "print(\"Custom detection criteria defined for 3G detectors (ET + CE)\")\n", "print(f\"Detection network SNR threshold: {snr_threshold_network}\")\n", "\n", "# Test the detection criteria function\n", "gw_param_dict = dict(\n", " mass_1 = np.array([2.0, 2.0]),\n", " mass_2 = np.array([1.0, 1.0]),\n", " luminosity_distance = np.array([1000.0, 10000.0]),\n", ")\n", "pdet = detection_criteria(gw_param_dict=gw_param_dict)\n", "print(\"\\nTest detection calculation:\")\n", "print(f\" mass_1 array: {gw_param_dict['mass_1']}\")\n", "print(f\" mass_2 array: {gw_param_dict['mass_2']}\")\n", "print(f\" luminosity_distance array: {gw_param_dict['luminosity_distance']}\")\n", "print(f\" Pdet result: {pdet}\")" ] }, { "cell_type": "markdown", "id": "5f761ddd", "metadata": {}, "source": [ "### 2.5 Initialize GWRATES with Custom Settings\n", "\n", "Create a GWRATES instance with the custom functions and parameters defined above." ] }, { "cell_type": "code", "execution_count": null, "id": "b7f93795", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Initializing GWRATES class...\n", "\n", "\n", "Initializing CBCSourceRedshiftDistribution...\n", "\n", "luminosity_distance interpolator will be loaded from ./interpolator_json/luminosity_distance/luminosity_distance_2.json\n", "differential_comoving_volume interpolator will be loaded from ./interpolator_json/differential_comoving_volume/differential_comoving_volume_2.json\n", "using ler available merger rate density model: merger_rate_density_bbh_oguri2018\n", "merger_rate_density_bbh_oguri2018 interpolator will be loaded from ./interpolator_json/merger_rate_density/merger_rate_density_bbh_oguri2018_4.json\n", "merger_rate_density_detector_frame interpolator will be loaded from ./interpolator_json/merger_rate_density/merger_rate_density_detector_frame_5.json\n", "source_redshift interpolator will be loaded from ./interpolator_json/source_redshift/source_redshift_2.json\n", "\n", "Initializing CBCSourceParameterDistribution...\n", "\n", "using ler available zs function : source_redshift\n", "using user defined custom source_frame_masses function\n", "using ler available geocent_time function : sampler_uniform\n", "using ler available ra function : sampler_uniform\n", "using ler available dec function : sampler_cosine\n", "using ler available phase function : sampler_uniform\n", "using ler available psi function : sampler_uniform\n", "using ler available theta_jn function : sampler_sine\n", "using ler available a_1 function : sampler_uniform\n", "using ler available a_2 function : sampler_uniform\n", "#----------------------------------------\n", "# GWRATES initialization input arguments:\n", "#----------------------------------------\n", "\n", " # GWRATES set up input arguments:\n", " npool = 4,\n", " z_min = 0.001,\n", " z_max = 10,\n", " event_type = 'BNS',\n", " cosmology = LambdaCDM(H0=70.0 km / (Mpc s), Om0=0.3, Ode0=0.7, Tcmb0=0.0 K, Neff=3.04, m_nu=None, Ob0=None),\n", " pdet_finder = ,\n", " json_file_names = dict(\n", " gwrates_params = 'gwrates_params.json',\n", " gw_param = 'gw_param.json',\n", " gw_param_detectable = 'gw_param_detectable.json',\n", " ),\n", " interpolator_directory = './interpolator_json',\n", " ler_directory = './ler_data_custom',\n", "\n", " # GWRATES also takes other CBCSourceParameterDistribution class input arguments as kwargs, as follows:\n", " source_priors = dict(\n", " merger_rate_density = 'merger_rate_density_bbh_oguri2018',\n", " zs = 'source_redshift',\n", " source_frame_masses = ,\n", " geocent_time = 'sampler_uniform',\n", " ra = 'sampler_uniform',\n", " dec = 'sampler_cosine',\n", " phase = 'sampler_uniform',\n", " psi = 'sampler_uniform',\n", " theta_jn = 'sampler_sine',\n", " a_1 = 'sampler_uniform',\n", " a_2 = 'sampler_uniform',\n", " ),\n", " source_priors_params = dict(\n", " merger_rate_density = {'R0': 1.0550000000000001e-07, 'b2': 1.6, 'b3': 2.1, 'b4': 30},\n", " zs = None,\n", " source_frame_masses = {'mmin': 1.0, 'mmax': 2.3},\n", " geocent_time = {'xmin': 1238166018, 'xmax': 1269702018},\n", " ra = {'xmin': 0.0, 'xmax': 6.283185307179586},\n", " dec = None,\n", " phase = {'xmin': 0.0, 'xmax': 6.283185307179586},\n", " psi = {'xmin': 0.0, 'xmax': 3.141592653589793},\n", " theta_jn = None,\n", " a_1 = {'xmin': -0.05, 'xmax': 0.05},\n", " a_2 = {'xmin': -0.05, 'xmax': 0.05},\n", " ),\n", " spin_zero = False,\n", " spin_precession = False,\n" ] } ], "source": [ "from ler import GWRATES\n", "\n", "# Initialize GWRATES with custom functions\n", "ler_custom = GWRATES(\n", " # LeR setup parameters\n", " npool=6,\n", " z_min=0.001,\n", " z_max=10,\n", " verbose=True,\n", " event_type=\"BNS\", # Binary Neutron Star\n", " spin_zero=True,\n", " \n", " # Custom source parameter priors\n", " source_priors=dict(\n", " merger_rate_density=merger_rate_density_function,\n", " source_frame_masses=source_frame_masses_uniform, # Custom function\n", " ),\n", " source_priors_params=dict(\n", " merger_rate_density=merger_rate_density_input_args,\n", " source_frame_masses=source_frame_masses_args,\n", " ),\n", " \n", " # Custom detection criteria\n", " pdet_finder=detection_criteria,\n", " ler_directory='./ler_data_custom', # Save in a separate directory\n", ")" ] }, { "cell_type": "markdown", "id": "96abe05c", "metadata": {}, "source": [ "### 2.6 Sample GW Parameters with Custom Settings" ] }, { "cell_type": "code", "execution_count": 23, "id": "60125d10", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Simulated GW params will be stored in ./ler_data_custom/custom_gw_params.json\n", "Batch no. 1\n", "sampling gw source params...\n", "calculating pdet...\n", "Batch no. 2\n", "sampling gw source params...\n", "calculating pdet...\n", "saving all gw parameters in ./ler_data_custom/custom_gw_params.json \n", "\n", "Sampled 100000 custom BNS events\n" ] } ], "source": [ "# Sample GW population with custom settings\n", "gw_params_custom = ler_custom.gw_cbc_statistics(\n", " size=100000,\n", " batch_size=50000,\n", " resume=False, # Start fresh\n", " output_jsonfile='custom_gw_params.json'\n", ")\n", "\n", "print(f\"\\nSampled {len(gw_params_custom['zs'])} custom BNS events\")" ] }, { "cell_type": "markdown", "id": "07d89430", "metadata": {}, "source": [ "### 2.7 Calculate Rates with Custom Settings" ] }, { "cell_type": "code", "execution_count": null, "id": "dd1799fe", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Getting gw parameters from json file ./ler_data_custom/custom_gw_params.json...\n", "total GW event rate (yr^-1): 73925.64600292277\n", "number of simulated GW detectable events: 20367\n", "number of simulated all GW events: 100000\n", "storing detectable params in ./ler_data_custom/gw_param_detectable.json\n", "\n", "=== Custom BNS Detection Results (under 3G detectors sesitivity) ===\n", "Detectable BNS event rate: 7.3926e+04 events per year\n", "Total BNS event rate: 3.6297e+05 events per year\n", "Detectable fraction: 20.37%\n" ] } ], "source": [ "# Calculate detection rates with custom settings\n", "detectable_rate_custom, gw_param_detectable_custom = ler_custom.gw_rate()\n", "\n", "# Calculate fraction of detectable events\n", "total_rate_custom = ler_custom.normalization_pdf_z\n", "fraction_detectable = detectable_rate_custom / total_rate_custom\n", "\n", "print(f\"\\n=== Custom BNS Detection Results (3G Detectors Sensitivity) ===\")\n", "print(f\"Detectable BNS event rate: {detectable_rate_custom:.4e} events per year\")\n", "print(f\"Total BNS event rate: {total_rate_custom:.4e} events per year\")\n", "print(f\"Detectable fraction: {fraction_detectable*100:.2f}%\")" ] }, { "cell_type": "markdown", "id": "799a27d2", "metadata": {}, "source": [ "### 2.8 Compare Default and Custom Mass Distributions\n", "\n", "GWRATES uses `binary_masses_BNS_bimodal` as the default mass distribution for BNS events. Here we compare the default distribution with our custom uniform mass distribution defined earlier." ] }, { "cell_type": "code", "execution_count": 28, "id": "c3557ce5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "binary_masses_BNS_bimodal interpolator will be loaded from ./interpolator_json/source_frame_masses/binary_masses_BNS_bimodal_0.json\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "from ler.utils import plots as lerplt\n", "\n", "# Sample from default BNS mass distribution\n", "mass_1_default, mass_2_default = ler_custom.binary_masses_BNS_bimodal(size=10000)\n", "default_mass_dict = dict(mass_1_source=mass_1_default)\n", "\n", "# Sample from custom mass distribution\n", "mass_1_custom, mass_2_custom = source_frame_masses_uniform(size=10000)\n", "custom_mass_dict = dict(mass_1_source=mass_1_custom)\n", "\n", "# Create comparison plot\n", "plt.figure(figsize=(6, 4))\n", "\n", "# Plot default model\n", "lerplt.param_plot(\n", " param_name='mass_1_source',\n", " param_dict=default_mass_dict,\n", " plot_label='Default BNS bimodal model',\n", ")\n", "\n", "# Plot custom model\n", "lerplt.param_plot(\n", " param_name='mass_1_source',\n", " param_dict=custom_mass_dict,\n", " plot_label='Custom uniform model',\n", ")\n", "\n", "plt.xlabel(r'Primary mass, $m_1$ (M$_\\odot$)', fontsize=12)\n", "plt.ylabel('Probability density', fontsize=12)\n", "plt.title('Comparison of Mass Distribution Models', fontsize=14, fontweight='bold')\n", "plt.xlim(1, 2.3)\n", "plt.legend(fontsize=11)\n", "plt.grid(alpha=0.4)\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "62f6fae6", "metadata": {}, "source": [ "---\n", "\n", "## Part 3: Advanced Sampling - Generating Detectable Events\n", "\n", "This section demonstrates how to generate a specific number of detectable events and monitor detection rate convergence." ] }, { "cell_type": "markdown", "id": "6287a28d", "metadata": {}, "source": [ "### 3.1 Initialize GWRATES for N-Event Sampling" ] }, { "cell_type": "code", "execution_count": 29, "id": "2f555946", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Initializing GWRATES class...\n", "\n" ] } ], "source": [ "# Create a new GWRATES instance for N-event sampling\n", "ler_n_events = GWRATES(\n", " npool=6,\n", " verbose=False,\n", ")" ] }, { "cell_type": "markdown", "id": "bf546fb1", "metadata": {}, "source": [ "### 3.2 Sample Until N Detectable Events Are Found\n", "\n", "This function will:\n", "- Continue sampling in batches until at least N detectable events are found\n", "- Monitor rate convergence using a stopping criteria (e.g., relative rate difference < 0.5%)\n", "- Calculate rates dynamically at each batch\n", "- Allow resuming from the last batch if interrupted" ] }, { "cell_type": "code", "execution_count": null, "id": "2cd09005", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "stopping criteria set to when relative difference of total rate for the last 4 cumulative batches is less than 0.5%.\n", "sample collection will stop when the stopping criteria is met and number of detectable events exceeds the specified size.\n", "removing ./ler_data/gw_params_n_detectable.json and ./ler_data/meta_gw.json if they exist\n", "collected number of detectable events = 0\n", "collected number of detectable events = 334\n", "total number of events = 100000\n", "total rate (yr^-1): 274.6375860299267\n", "collected number of detectable events = 656\n", "total number of events = 200000\n", "total rate (yr^-1): 269.7039767000478\n", "collected number of detectable events = 948\n", "total number of events = 300000\n", "total rate (yr^-1): 259.8367580402899\n", "collected number of detectable events = 1287\n", "total number of events = 400000\n", "total rate (yr^-1): 264.56480031475724\n", "collected number of detectable events = 1657\n", "total number of events = 500000\n", "total rate (yr^-1): 272.4996886536458\n", "percentage difference of total rate for the last 4 cumulative batches = [1.02595051 4.64695232 2.91188896 0. ]\n", "collected number of detectable events = 2016\n", "total number of events = 600000\n", "total rate (yr^-1): 276.28212247321966\n", "percentage difference of total rate for the last 4 cumulative batches = [5.95238095 4.24107143 1.36904762 0. ]\n", "collected number of detectable events = 2369\n", "total number of events = 700000\n", "total rate (yr^-1): 278.2790595829326\n", "percentage difference of total rate for the last 4 cumulative batches = [4.92823976 2.07682566 0.71760236 0. ]\n", "collected number of detectable events = 2725\n", "total number of events = 800000\n", "total rate (yr^-1): 280.08511299833464\n", "percentage difference of total rate for the last 4 cumulative batches = [2.70825688 1.35779817 0.64482307 0. ]\n", "collected number of detectable events = 3108\n", "total number of events = 900000\n", "total rate (yr^-1): 283.95662587525356\n", "percentage difference of total rate for the last 4 cumulative batches = [2.7027027 1.99944843 1.36341699 0. ]\n", "collected number of detectable events = 3472\n", "total number of events = 1000000\n", "total rate (yr^-1): 285.4915265556603\n", "percentage difference of total rate for the last 4 cumulative batches = [2.52633311 1.8937212 0.53763441 0. ]\n", "collected number of detectable events = 3862\n", "total number of events = 1100000\n", "total rate (yr^-1): 288.6908974544303\n", "percentage difference of total rate for the last 4 cumulative batches = [2.98096841 1.63991024 1.10823408 0. ]\n", "collected number of detectable events = 4175\n", "total number of events = 1200000\n", "total rate (yr^-1): 286.0808187811736\n", "percentage difference of total rate for the last 4 cumulative batches = [0.74251497 0.20598802 0.9123571 0. ]\n", "collected number of detectable events = 4505\n", "total number of events = 1300000\n", "total rate (yr^-1): 284.94756450134037\n", "percentage difference of total rate for the last 4 cumulative batches = [0.190899 1.31369186 0.39770625 0. ]\n", "collected number of detectable events = 4849\n", "total number of events = 1400000\n", "total rate (yr^-1): 284.79847191170114\n", "percentage difference of total rate for the last 4 cumulative batches = [1.36672978 0.45026466 0.05235021 0. ]\n", "collected number of detectable events = 5170\n", "total number of events = 1500000\n", "total rate (yr^-1): 283.40844706082254\n", "percentage difference of total rate for the last 4 cumulative batches = [0.94294004 0.54307395 0.49046698 0. ]\n", "collected number of detectable events = 5540\n", "total number of events = 1600000\n", "total rate (yr^-1): 284.71037174509615\n", "percentage difference of total rate for the last 4 cumulative batches = [0.08331019 0.03094379 0.45728039 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 5883\n", "total number of events = 1700000\n", "total rate (yr^-1): 284.5531734086049\n", "percentage difference of total rate for the last 4 cumulative batches = [0.0862048 0.40228908 0.05524392 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 6224\n", "total number of events = 1800000\n", "total rate (yr^-1): 284.3220784182075\n", "percentage difference of total rate for the last 4 cumulative batches = [0.32133676 0.13656812 0.0812793 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 6586\n", "total number of events = 1900000\n", "total rate (yr^-1): 285.02413198756653\n", "percentage difference of total rate for the last 4 cumulative batches = [0.11008199 0.16523463 0.24631373 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 6905\n", "total number of events = 2000000\n", "total rate (yr^-1): 283.8881035234497\n", "percentage difference of total rate for the last 4 cumulative batches = [0.23427184 0.15286829 0.40016769 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 7210\n", "total number of events = 2100000\n", "total rate (yr^-1): 282.3120894319606\n", "percentage difference of total rate for the last 4 cumulative batches = [0.71197411 0.96065406 0.55825243 0. ]\n", "collected number of detectable events = 7555\n", "total number of events = 2200000\n", "total rate (yr^-1): 282.374382479055\n", "percentage difference of total rate for the last 4 cumulative batches = [0.93838169 0.53606883 0.02206045 0. ]\n", "collected number of detectable events = 7905\n", "total number of events = 2300000\n", "total rate (yr^-1): 282.6100127006731\n", "percentage difference of total rate for the last 4 cumulative batches = [0.45224541 0.10541851 0.08337646 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 8234\n", "total number of events = 2400000\n", "total rate (yr^-1): 282.1065223765489\n", "percentage difference of total rate for the last 4 cumulative batches = [0.07286859 0.09494999 0.17847525 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 8578\n", "total number of events = 2500000\n", "total rate (yr^-1): 282.1366722113426\n", "percentage difference of total rate for the last 4 cumulative batches = [0.08425359 0.16776993 0.01068625 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 8909\n", "total number of events = 2600000\n", "total rate (yr^-1): 281.75336871725204\n", "percentage difference of total rate for the last 4 cumulative batches = [0.30404037 0.12534142 0.1360422 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 9248\n", "total number of events = 2700000\n", "total rate (yr^-1): 281.6420931032116\n", "percentage difference of total rate for the last 4 cumulative batches = [0.16490052 0.17560554 0.03950958 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 9563\n", "total number of events = 2800000\n", "total rate (yr^-1): 280.833964414477\n", "percentage difference of total rate for the last 4 cumulative batches = [0.46387117 0.32738359 0.28776031 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 9906\n", "total number of events = 2900000\n", "total rate (yr^-1): 280.87548288379656\n", "percentage difference of total rate for the last 4 cumulative batches = [0.31255339 0.27293597 0.01478181 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "collected number of detectable events = 10244\n", "total number of events = 3000000\n", "total rate (yr^-1): 280.77718875155375\n", "percentage difference of total rate for the last 4 cumulative batches = [0.30803939 0.0202209 0.03500788 0. ]\n", "stopping criteria of rate relative difference of 0.5% for the last 4 cumulative batches reached.\n", "Given size=10000 reached\n", "\n", "stored detectable GW params in ./ler_data/gw_params_n_detectable.json\n", "stored meta data in ./ler_data/meta_gw.json\n", "\n", "=== N-Event Sampling Results ===\n", "Detectable event rate: 2.8078e+02 events per year\n", "Collected number of detectable events: 10244\n" ] } ], "source": [ "# Sample until we have at least 10,000 detectable events with converged rates\n", "detectable_rate_n, gw_param_detectable_n = ler_n_events.selecting_n_gw_detectable_events(\n", " size=10000, # Target number of detectable events\n", " batch_size=100000, # Events per batch\n", " stopping_criteria=dict(\n", " relative_diff_percentage=0.5, # Stop when rate change < 0.5% (use 0.1% for better convergence)\n", " number_of_last_batches_to_check=4 # Check last 4 batches\n", " ),\n", " pdet_threshold=0.5, # Probability threshold for detection\n", " resume=False, # Start fresh\n", " output_jsonfile='gw_params_n_detectable.json',\n", " meta_data_file='meta_gw.json', # Store metadata (rates per batch)\n", " pdet_type='boolean',\n", " trim_to_size=False, # Keep all events found until convergence\n", ")\n", "\n", "print(f\"\\n=== N-Event Sampling Results ===\")\n", "print(f\"Detectable event rate: {detectable_rate_n:.4e} events per year\")\n", "print(f\"Collected number of detectable events: {len(gw_param_detectable_n['zs'])}\")" ] }, { "cell_type": "markdown", "id": "4e6f6585", "metadata": {}, "source": [ "### 3.3 Analyze Rate Convergence\n", "\n", "Plot the evolution of the detection rate across batches to verify convergence." ] }, { "cell_type": "code", "execution_count": 47, "id": "0e121be3", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "from ler.utils import get_param_from_json\n", "\n", "# Load metadata containing rates for each batch\n", "meta_data = get_param_from_json(ler_n_events.ler_directory + '/meta_gw.json')\n", "\n", "# Plot rate vs sampling size\n", "plt.figure(figsize=(6, 4))\n", "plt.plot(\n", " meta_data['events_total'],\n", " meta_data['total_rate'],\n", " 'o-',\n", " linewidth=2,\n", " markersize=6,\n", " label='Detectable rate'\n", ")\n", "\n", "plt.xlabel('Total number of events sampled', fontsize=12)\n", "plt.ylabel('Detectable event rate (per year)', fontsize=12)\n", "plt.title('Rate Convergence Across Batches', fontsize=14, fontweight='bold')\n", "plt.grid(alpha=0.3)\n", "plt.legend(fontsize=11)\n", "plt.xscale('log')\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "03678554", "metadata": {}, "source": [ "### 3.4 Assess Rate Stability\n", "\n", "Calculate the average rate from the last batches to verify convergence." ] }, { "cell_type": "code", "execution_count": null, "id": "66268119", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "=== Rate Stability Analysis ===\n", "Number of converged batches: 4\n", "Mean rate (converged): 2.8103e+02 events per year\n", "Standard deviation: 3.5386e-01 events per year\n", "Relative uncertainty: 0.13%\n" ] } ], "source": [ "import numpy as np\n", "\n", "# Select rates from the last batches\n", "idx_converged = [-4, -3, -2, -1]\n", "rates_converged = np.array(meta_data['total_rate'])[idx_converged]\n", "\n", "if len(rates_converged) > 0:\n", " mean_rate = rates_converged.mean()\n", " std_rate = rates_converged.std()\n", " \n", " print(f\"\\n=== Rate Stability Analysis ===\")\n", " print(f\"Number of converged batches: {len(rates_converged)}\")\n", " print(f\"Mean rate (converged): {mean_rate:.4e} events per year\")\n", " print(f\"Standard deviation: {std_rate:.4e} events per year\")\n", " print(f\"Relative uncertainty: {(std_rate/mean_rate)*100:.2f}%\")\n", "else:\n", " print(\"Not enough batches to assess convergence.\")" ] }, { "cell_type": "markdown", "id": "732b4c2e", "metadata": {}, "source": [ "### 3.5 Compare All Sampled and Detectable Event Parameters\n", "\n", "Create an overlapping visualization comparing the parameter distributions of all sampled events with detectable events only." ] }, { "cell_type": "code", "execution_count": 49, "id": "bcd1e271", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Simulated GW params will be stored in ./ler_data/gw_param.json\n", "Batch no. 1\n", "sampling gw source params...\n", "calculating pdet...\n", "gw parameters already sampled.\n" ] } ], "source": [ "# generate CBC (all) parameters\n", "gw_param = ler_n_events.gw_cbc_statistics(10000, resume=False)" ] }, { "cell_type": "code", "execution_count": null, "id": "79ffece6", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING:root:Too few points to create valid contours\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import corner\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import matplotlib.lines as mlines\n", "from ler.utils import get_param_from_json\n", "\n", "param = get_param_from_json('ler_data/gw_param.json')\n", "param_detectable = get_param_from_json('./ler_data/gw_params_n_detectable.json')\n", "\n", "param_names = ['zs', 'ra', 'dec', 'theta_jn', 'mass_1_source', 'mass_2_source']\n", "\n", "# Prepare data for corner plot\n", "samples_unlensed = np.stack([param[p] for p in param_names], axis=1)\n", "samples_detectable = np.stack([param_detectable[p] for p in param_names], axis=1)\n", "\n", "# Generate corner plot\n", "fig = corner.corner(\n", " samples_unlensed, \n", " labels=param_names, \n", " color='C0', \n", " alpha=0.5,\n", " plot_density=False, plot_datapoints=False, smooth=0.8,\n", " hist_kwargs={'density': True}\n", ")\n", "blue_line = mlines.Line2D([], [], color='C0', label='all events')\n", "\n", "# Plot detectable events\n", "corner.corner(\n", " samples_detectable, \n", " labels=param_names, \n", " color='C1', \n", " alpha=0.5,\n", " fig=fig, \n", " plot_density=False, plot_datapoints=False, smooth=0.8,\n", " hist_kwargs={'density': True}\n", ")\n", "orange_line = mlines.Line2D([], [], color='C1', label='detectable only')\n", "\n", "# Add legend\n", "fig.legend(handles=[blue_line, orange_line], loc='upper right', bbox_to_anchor=(0.95, 0.95), fontsize=14)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "9ef4dbae", "metadata": {}, "source": [ "---\n", "\n", "## Summary\n", "\n", "This notebook demonstrated the key features of the `GWRATES` class:\n", "\n", "1. **Basic Simulation:** Simulating GW populations and calculating detection rates\n", "2. **Customization:** Using custom mass distributions, merger rate densities, and detection criteria\n", "3. **Advanced Sampling:** Generating a specific number of detectable events and monitoring rate convergence\n", "4. **Visualization:** Comparing distributions and analyzing results\n", "\n", "For more examples and detailed documentation, visit the [ler documentation](https://ler.hemantaph.com).\n", "\n", "**Key Takeaways:**\n", "- GWRATES is flexible and supports custom prior functions\n", "- Batching allows resumable simulations and memory-efficient sampling\n", "- Rate convergence can be monitored and validated\n", "- Results are automatically saved for reproducibility and further analysis" ] }, { "cell_type": "markdown", "id": "e6cdee0f", "metadata": {}, "source": [] } ], "metadata": { "kernelspec": { "display_name": "ler", "language": "python", "name": "ler" }, "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 }