{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Event Rates with 3G detectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from ler.rates import LeR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "ler = LeR(batch_size=50000, ifos=['CE', 'ET'], verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unlensed params will be store in unlensed_3G_1M.json\n",
      "chosen batch size = 50000 with total size = 1000000\n",
      "There will be 20 batche(s)\n",
      "resuming from ./ler_data/unlensed_3G_1M.json\n",
      "saving all unlensed_params in ./ler_data/unlensed_3G_1M.json...\n"
     ]
    }
   ],
   "source": [
    "ler.unlensed_cbc_statistics(size=1000000, save_batch=False, resume=True, output_jsonfile='unlensed_3G_1M.json');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "getting unlensed_params from json file unlensed_3G_1M.json...\n",
      "total unlensed rate (yr^-1) (with step function): 91843.65042655931\n",
      "number of simulated unlensed detectable events: 887182\n",
      "number of all simulated unlensed events: 1000000\n",
      "storing detectable unlensed params in unlensed_param_detectable.json\n"
     ]
    }
   ],
   "source": [
    "ler.unlensed_rate();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "getting unlensed_params from json file unlensed_3G_1M.json...\n",
      "total unlensed rate (yr^-1) (with step function): 94258.63255779142\n",
      "number of simulated unlensed detectable events: 910510\n",
      "number of all simulated unlensed events: 1000000\n",
      "storing detectable unlensed params in unlensed_param_detectable.json\n"
     ]
    }
   ],
   "source": [
    "ler.unlensed_rate(snr_threshold=6);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lensed params will be store in lensed_3G_1M.json\n",
      "chosen batch size = 50000 with total size = 1000000\n",
      "There will be 20 batche(s)\n",
      "resuming from ./ler_data/lensed_3G_1M.json\n",
      "saving all lensed_params in ./ler_data/lensed_3G_1M.json...\n"
     ]
    }
   ],
   "source": [
    "ler.lensed_cbc_statistics(size=1000000, save_batch=False, resume=True, output_jsonfile='lensed_3G_1M.json');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "getting lensed_params from json file lensed_3G_1M.json...\n",
      "total lensed rate (yr^-1) (with step function): 152.3718678085319\n",
      "number of simulated lensed detectable events: 613339\n",
      "number of simulated all lensed events: 1000000\n",
      "storing detectable lensed params in lensed_param_detectable.json\n"
     ]
    }
   ],
   "source": [
    "ler.lensed_rate();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "getting lensed_params from json file lensed_3G_1M.json...\n",
      "total lensed rate (yr^-1) (with step function): 167.8888117226168\n",
      "number of simulated lensed detectable events: 675799\n",
      "number of simulated all lensed events: 1000000\n",
      "storing detectable lensed params in lensed_param_detectable.json\n"
     ]
    }
   ],
   "source": [
    "ler.lensed_rate(snr_threshold=[6,6], num_img=[1,1]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'ler_param': './ler_params.json',\n",
       " 'unlensed_param': 'unlensed_3G_1M.json',\n",
       " 'unlensed_param_detectable': './unlensed_param_detectable.json',\n",
       " 'lensed_param': 'lensed_3G_1M.json',\n",
       " 'lensed_param_detectable': './lensed_param_detectable.json'}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ler.json_file_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unlensed_rate: 91843.65042655931\n",
      "lensed_rate: 152.3718678085319\n",
      "ratio: 602.7598909660187\n"
     ]
    }
   ],
   "source": [
    "ler.rate_ratio();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## With ANN snr (IMRphenomXPHM)\n",
    "* (under development)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ler.rates import LeR\n",
    "ler = LeR(\n",
    "    batch_size=50000, \n",
    "    verbose=False, \n",
    "    spin_zero=False, \n",
    "    spin_precession=True, \n",
    "    # ifos=['CE', 'ET'], # This will be implemented in the next version\n",
    "    snr_type='ann', \n",
    "    waveform_approximant='IMRPhenomXPHM'\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lensed params will be store in ./lensed_param.json\n",
      "chosen batch size = 50000 with total size = 100000\n",
      "There will be 2 batche(s)\n",
      "Batch no. 1\n",
      "sampling lensed params...\n",
      "solving lens equations...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████| 50000/50000 [00:14<00:00, 3389.90it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "calculating snrs...\n",
      "Batch no. 2\n",
      "sampling lensed params...\n",
      "solving lens equations...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████| 50000/50000 [00:14<00:00, 3358.70it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "calculating snrs...\n"
     ]
    }
   ],
   "source": [
    "ler.lensed_cbc_statistics(size=100000, save_batch=False);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "getting lensed_params from json file ./lensed_param.json...\n",
      "total lensed rate (yr^-1) (with step function): 1.488096286349158\n",
      "number of simulated lensed detectable events: 599\n",
      "number of simulated all lensed events: 100000\n",
      "storing detectable lensed params in ./lensed_param_detectable.json\n"
     ]
    }
   ],
   "source": [
    "ler.lensed_rate();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "getting lensed_params from json file ./lensed_param.json...\n",
      "calculating snrs...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████| 840/840 [00:04<00:00, 177.26it/s]\n",
      "100%|████████████████████████████████████████████████████████████| 840/840 [00:04<00:00, 201.31it/s]\n",
      "100%|████████████████████████████████████████████████████████████| 729/729 [00:03<00:00, 193.07it/s]\n",
      "100%|████████████████████████████████████████████████████████████| 570/570 [00:03<00:00, 160.27it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total lensed rate (yr^-1) (with step function): 1.1800429649680302\n",
      "number of simulated lensed detectable events: 475\n",
      "number of simulated all lensed events: 100000\n",
      "storing detectable lensed params in ./lensed_param_detectable.json\n"
     ]
    }
   ],
   "source": [
    "ler.lensed_rate(snr_recalculation=True,);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "ler",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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   "file_extension": ".py",
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