arxiv_plots_RubinToO2024.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hbrxtXhzf92A"
      },
      "source": [
        "# Rubin ToO Strategies\n",
        "This notebook was put together to aid visualization of possible strategies to adopt for Target of Opportunity (ToO) observations with Vera C. Rubin Observatory. The notebook provides code for:\n",
        "- visualization of the ToO observing strategies\n",
        "- light curves plots\n",
        "- exposure time calculator (ETC) to convert exposure times to limiting magnitudes and vice-versa\n",
        "- time budget calculations\n",
        "\n",
        "Notebook template author: Igor Andreoni <<igor.andreoni@gmail.com>> <br>\n",
        "Code updated by Meet Vyas for the arxiv version plots. <br>\n",
        "Code verified by Ritwik Sharma.\n",
        "\n",
        "### Requirements\n",
        "\n",
        "Python3\n",
        "\n",
        "- numpy\n",
        "- matplotlib\n",
        "- math\n",
        "- scipy\n",
        "- collections\n",
        "- astropy\n",
        "\n",
        "Custom scripts\n",
        "- chart.py\n",
        "- etc.py\n",
        "- plot_lc.py"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "##  Instructions to create the plots using Google Colab"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "> ### 1. Clone the repository in your colab environment"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IwjF-X-9kKeV",
        "outputId": "c3fcf27a-ab70-47a8-816c-f81c295931db"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Cloning into 'RubinToO2024'...\n",
            "remote: Enumerating objects: 579, done.\u001b[K\n",
            "remote: Counting objects: 100% (103/103), done.\u001b[K\n",
            "remote: Compressing objects: 100% (63/63), done.\u001b[K\n",
            "remote: Total 579 (delta 40), reused 98 (delta 40), pack-reused 476 (from 1)\u001b[K\n",
            "Receiving objects: 100% (579/579), 4.65 MiB | 17.63 MiB/s, done.\n",
            "Resolving deltas: 100% (62/62), done.\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/igorandreoni/RubinToO2024"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "> ### 2. Make the cloned repository your current directory"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7BI9DUZWkfY3",
        "outputId": "a9e8effa-5d71-4a6e-adf0-636c8a770d2d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "/content/RubinToO2024\n"
          ]
        }
      ],
      "source": [
        "cd /content/RubinToO2024/"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "> ### General Code starts here"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Import all the required libraries and dependencies"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "DZOCf6zxf92L"
      },
      "outputs": [],
      "source": [
        "import glob\n",
        "import math\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from collections import OrderedDict\n",
        "import pandas as pd\n",
        "\n",
        "# Import the custom exposure time calculator\n",
        "import etc\n",
        "\n",
        "# Import the function to make the Gantt chart\n",
        "from chart import makeChart\n",
        "\n",
        "# Import function to complete the strategy dictionary with automatic calculations\n",
        "from chart import complete_strategies"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ltmqEN4of92N"
      },
      "source": [
        "Build a dictionary with the strategies that you want to be seen on the same plot.\n",
        "The keys of the dictionary will be the nicknames of the strategies (for example, `strategy1`, `strategy2`).\n",
        "\n",
        "Notes:\n",
        "- The LSSTCam filter wheel holds 5 filters on a given night. The bluer and redder filters, u and y, will be swapped depending on the lunation. If all 6 filters are added to the plot, we shall assume that 5 available filters will be used in the ToOs.\n",
        "- The length of the exposure time list (`exptimes_median` key) must be the same length as the cadence list (`cadence_hr` key) and the filters list (`filters` key);\n",
        "- The cadence must be given in hours, the exposure times in seconds, the filters as a list or in the form `'ugrizy'`\n",
        "- The `depths` are 5sigma limiting magnitudes in all bands, the corresponding exptime will be the median of the exposure times for the filters provided in each strategy\n",
        "- <b>Important:</b> Order of \"domination\" of the inputs: individual `depths` (list of lists of depths per individual filters) dominate over `depths_median` (list of median depths per epoch), which dominates over individual `exptimes` (list of lists of exposure times per individual filters), which dominates over `exptimes_median` (list of median exposure times per epoch). All the other values will be calculated automatically using the ETC."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AE65EktEf92Y"
      },
      "source": [
        "### Strategy dictionary for the Golden Strategy for 350 Mpc"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IDSq3NI3f92Z",
        "outputId": "2f9ddea6-a637-4936-d3e2-a3d53a3e5e07"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Gold Events: 3 Filter Deep Strategy (350 Mpc) Case 1: Using INDIVIDUAL DEPTHS to calculate the exposure times\n",
            "Gold Events: 3 Filter Deep Strategy (350 Mpc) Case 2: Using INDIVIDUAL DEPTHS to calculate the exposure times\n",
            "Gold Events: 3 Filter Deep Strategy (350 Mpc) Case 3: Using INDIVIDUAL DEPTHS to calculate the exposure times\n"
          ]
        }
      ],
      "source": [
        "# Run this block to register the 3 filter stratergies for the workshop\n",
        "strategies = {\n",
        "        'Gold Events: 3 Filter Deep Strategy (350 Mpc) Case 1' : {\"cadence_hr\": [1,5,8,24,48,72],\n",
        "                   \"exptimes_median\": [],\n",
        "                   \"exptimes\": [],\n",
        "                   \"depths_median\": [],\n",
        "                   \"depths\": [[25,24.5,23],\n",
        "                              [25,24.5,23],\n",
        "                              [25,24.5,23],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23]],\n",
        "                   \"filters\": ['gri', 'gri', 'gri','ri','ri','ri']},\n",
        "\n",
        "        'Gold Events: 3 Filter Deep Strategy (350 Mpc) Case 2' : {\"cadence_hr\": [1,5,24,48,72],\n",
        "                   \"exptimes_median\": [],\n",
        "                   \"exptimes\": [],\n",
        "                   \"depths_median\": [],\n",
        "                   \"depths\": [[25,24.5,23],\n",
        "                              [25,24.5,23],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23]],\n",
        "                   \"filters\": ['gri', 'gri', 'ri', 'ri','ri']},\n",
        "\n",
        "    'Gold Events: 3 Filter Deep Strategy (350 Mpc) Case 3' : {\"cadence_hr\": [4,6,24,48,72],\n",
        "                   \"exptimes_median\": [],\n",
        "                   \"exptimes\": [],\n",
        "                   \"depths_median\": [],\n",
        "                   \"depths\": [[25,24.5,23],\n",
        "                              [24.5],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23]],\n",
        "                   \"filters\": ['gri','r','ri', 'ri','ri']},\n",
        "}\n",
        "\n",
        "# Airmass for the observations (>= 1.)\n",
        "airmass = 1.2\n",
        "\n",
        "# When is the timeline starting? e.g., Rubin Trigger, NS-NS merger, ...\n",
        "event_name = \"start of Rubin observing window\"\n",
        "\n",
        "# Output file name\n",
        "filename_out = \"plot_strategy.pdf\"\n",
        "\n",
        "# Define the colors for the Rubin filters\n",
        "filters_color_dict = {'u':'b', 'g':'g', 'r':'r', 'i':'yellow', 'z':'k', 'y':'orange'}\n",
        "\n",
        "# Define the sequence of markers for different exposure times\n",
        "# (the sequence will be ordered by increasing exposure time)\n",
        "exptimes_marker_list = [\"o\", \"s\", \"p\", \"h\", \"8\", '^']\n",
        "\n",
        "# Complete the strategies using the ETC [do not modify the next line]\n",
        "strategies = complete_strategies(strategies, airmass=airmass)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8UnBBY_1f92Z"
      },
      "source": [
        "### Strategy dictionary for the Golden Strategy for 700 Mpc"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UCc6th7Xf92a",
        "outputId": "e7d7752f-4512-4854-ebc1-0f273631b436"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 1: Using INDIVIDUAL DEPTHS to calculate the exposure times\n",
            "Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 2: Using INDIVIDUAL DEPTHS to calculate the exposure times\n",
            "Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 3: Using INDIVIDUAL DEPTHS to calculate the exposure times\n"
          ]
        }
      ],
      "source": [
        "# Run this block to register the 3 filter stratergies for the workshop\n",
        "strategies = {\n",
        "        'Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 1' : {\"cadence_hr\": [1,5,8,24,48,72],\n",
        "                   \"exptimes_median\": [],\n",
        "                   \"exptimes\": [],\n",
        "                   \"depths_median\": [],\n",
        "                   \"depths\": [[25,24.5,23],\n",
        "                              [25,24.5,23],\n",
        "                              [25,24.5,23],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23]],\n",
        "                   \"filters\": ['gri', 'gri', 'gri','ri','ri','ri']},\n",
        "\n",
        "        'Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 2' : {\"cadence_hr\": [1,5,24,48,72],\n",
        "                   \"exptimes_median\": [],\n",
        "                   \"exptimes\": [],\n",
        "                   \"depths_median\": [],\n",
        "                   \"depths\": [[25,24.5,23],\n",
        "                              [25,24.5,23],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23]],\n",
        "                   \"filters\": ['gri', 'gri', 'ri', 'ri','ri']},\n",
        "\n",
        "    'Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 3' : {\"cadence_hr\": [4,6,24,48,72],\n",
        "                   \"exptimes_median\": [],\n",
        "                   \"exptimes\": [],\n",
        "                   \"depths_median\": [],\n",
        "                   \"depths\": [[25,24.5,23],\n",
        "                              [24.5],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23],\n",
        "                              [24.5,23]],\n",
        "                   \"filters\": ['gri', 'r','ri', 'ri','ri']},\n",
        "}\n",
        "\n",
        "# Airmass for the observations (>= 1.)\n",
        "airmass = 1.2\n",
        "\n",
        "# When is the timeline starting? e.g., Rubin Trigger, NS-NS merger, ...\n",
        "event_name = \"start of Rubin observing window\"\n",
        "\n",
        "# Output file name\n",
        "filename_out = \"plot_strategy.pdf\"\n",
        "\n",
        "# Define the colors for the Rubin filters\n",
        "filters_color_dict = {'u':'b', 'g':'g', 'r':'r', 'i':'yellow', 'z':'k', 'y':'orange'}\n",
        "\n",
        "# Define the sequence of markers for different exposure times\n",
        "# (the sequence will be ordered by increasing exposure time)\n",
        "exptimes_marker_list = [\"o\", \"s\", \"p\", \"h\", \"8\", '^']\n",
        "\n",
        "# Complete the strategies using the ETC [do not modify the next line]\n",
        "strategies = complete_strategies(strategies, airmass=airmass)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Dkk4foA5f92b"
      },
      "source": [
        "See how the `strategies` dictionary has been populated"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UieZ884Gf92b",
        "outputId": "1c4eea4d-3b97-4dd1-c6be-b1e9abaad598"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 1': {'cadence_hr': [1,\n",
              "   5,\n",
              "   8,\n",
              "   24,\n",
              "   48,\n",
              "   72],\n",
              "  'exptimes_median': [31, 31, 31, 18, 18, 18],\n",
              "  'exptimes': [[34, 31, 4],\n",
              "   [34, 31, 4],\n",
              "   [34, 31, 4],\n",
              "   [31, 4],\n",
              "   [31, 4],\n",
              "   [31, 4]],\n",
              "  'depths_median': [24.5, 24.5, 24.5, 23.75, 23.75, 23.75],\n",
              "  'depths': [[25, 24.5, 23],\n",
              "   [25, 24.5, 23],\n",
              "   [25, 24.5, 23],\n",
              "   [24.5, 23],\n",
              "   [24.5, 23],\n",
              "   [24.5, 23]],\n",
              "  'filters': ['gri', 'gri', 'gri', 'ri', 'ri', 'ri']},\n",
              " 'Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 2': {'cadence_hr': [1,\n",
              "   5,\n",
              "   24,\n",
              "   48,\n",
              "   72],\n",
              "  'exptimes_median': [31, 31, 18, 18, 18],\n",
              "  'exptimes': [[34, 31, 4], [34, 31, 4], [31, 4], [31, 4], [31, 4]],\n",
              "  'depths_median': [24.5, 24.5, 23.75, 23.75, 23.75],\n",
              "  'depths': [[25, 24.5, 23],\n",
              "   [25, 24.5, 23],\n",
              "   [24.5, 23],\n",
              "   [24.5, 23],\n",
              "   [24.5, 23]],\n",
              "  'filters': ['gri', 'gri', 'ri', 'ri', 'ri']},\n",
              " 'Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 3': {'cadence_hr': [4,\n",
              "   6,\n",
              "   24,\n",
              "   48,\n",
              "   72],\n",
              "  'exptimes_median': [31, 31, 18, 18, 18],\n",
              "  'exptimes': [[34, 31, 4], [31], [31, 4], [31, 4], [31, 4]],\n",
              "  'depths_median': [24.5, 24.5, 23.75, 23.75, 23.75],\n",
              "  'depths': [[25, 24.5, 23], [24.5], [24.5, 23], [24.5, 23], [24.5, 23]],\n",
              "  'filters': ['gri', 'r', 'ri', 'ri', 'ri']}}"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "strategies"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mqD_ibdgf92c"
      },
      "source": [
        "Print the results in a more readable format"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2msp93PSf92c",
        "outputId": "deccf4ae-de5f-4969-f172-f0409e332da8"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            " Strategy name: Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 1\n",
            "    Epoch: 1 hr\n",
            "        Filter: g Depth: 25mag, exptime: 34s\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 31s\n",
            "    Epoch: 5 hr\n",
            "        Filter: g Depth: 25mag, exptime: 34s\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 31s\n",
            "    Epoch: 8 hr\n",
            "        Filter: g Depth: 25mag, exptime: 34s\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 31s\n",
            "    Epoch: 24 hr\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 18s\n",
            "    Epoch: 48 hr\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 18s\n",
            "    Epoch: 72 hr\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 18s\n",
            "--\n",
            "\n",
            " Strategy name: Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 2\n",
            "    Epoch: 1 hr\n",
            "        Filter: g Depth: 25mag, exptime: 34s\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 31s\n",
            "    Epoch: 5 hr\n",
            "        Filter: g Depth: 25mag, exptime: 34s\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 31s\n",
            "    Epoch: 24 hr\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 18s\n",
            "    Epoch: 48 hr\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 18s\n",
            "    Epoch: 72 hr\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 18s\n",
            "--\n",
            "\n",
            " Strategy name: Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 3\n",
            "    Epoch: 4 hr\n",
            "        Filter: g Depth: 25mag, exptime: 34s\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 31s\n",
            "    Epoch: 6 hr\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Median exposure time: 31s\n",
            "    Epoch: 24 hr\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 18s\n",
            "    Epoch: 48 hr\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 18s\n",
            "    Epoch: 72 hr\n",
            "        Filter: r Depth: 24.5mag, exptime: 31s\n",
            "        Filter: i Depth: 23mag, exptime: 4s\n",
            "        Median exposure time: 18s\n",
            "--\n"
          ]
        }
      ],
      "source": [
        "\n",
        "strategy_names = list(strategies.keys())\n",
        "for i in range(len(strategy_names)):\n",
        "    print(f\"\\n Strategy name: {strategy_names[i]}\")\n",
        "    # Iterate over the epochs\n",
        "    for j in np.arange(len(strategies[strategy_names[i]][\"depths\"])):\n",
        "            print(f\"    Epoch: {strategies[strategy_names[i]]['cadence_hr'][j]} hr\")\n",
        "            # Iterate over the filters\n",
        "            for filt, exptime, depth in zip(strategies[strategy_names[i]][\"filters\"][j],\n",
        "                                            strategies[strategy_names[i]][\"exptimes\"][j],\n",
        "                                            strategies[strategy_names[i]][\"depths\"][j]):\n",
        "                print(f\"        Filter: {filt} Depth: {depth}mag, exptime: {exptime}s\")\n",
        "            print(f\"        Median exposure time: {strategies[strategy_names[i]]['exptimes_median'][j]}s\")\n",
        "    print(\"--\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "A8Wsy9dsf92d"
      },
      "source": [
        "## Survey Strategy Visualization\n",
        "\n",
        "The template code was used to produce some figures published in Andreoni et al. (2022), The Astrophysical Journal Supplement Series, Volume 260, Issue 1, id.18, 17 pp."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "9-yXbFT-f92d",
        "outputId": "b0970066-c41c-4d6b-f225-1926c3043edd"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "(0.0, 168.0)\n"
          ]
        },
        {
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ufSFFurljxBdffKH8+fOb6jz22GNatmyZ7r33Xlv7+Ph4PfDAA9q9e7dpRd9biE33sNUvAAAAAACAD8TGxprKQUFBHp/DPinqxo0bGRoTcrfhw4frzz//NB2bOHGiKlSokGbbjMazswQ/4jlnmzRpkhYvXizp5uo9X3/9dbrmwdQwxyI9UvsQKCAgQPPnz3dI+rulYMGC+vHHH9WlSxfT8ffee88hkVAiPpExX331lapWraqPP/7YZdKfJB09elRPPPGEKlWqlOZ21cQlvMFbcUY8I6scOnRI9957rxITE23HGjVqpPfeey/NtsQl0iM2NlbDhg2z/U3ZqVMnp18syWgfKRGbSEtq75vuuusuTZ482SHp75YOHTro999/N30hZf/+/fr555+d1ic23UPiHwAAAAAAgA/Yf0s1Pj7e43PExcW5PCfgrvHjxztsFfTyyy/r/vvvd6t9RuPZPpadnRM5x6lTp/TSSy/Zyg899FCqCVXpxRyL9EjtOX7ooYfUokULl239/f315Zdfmj7E2rt3r1asWJFmP8Qn3JGQkKDevXvr8ccf16lTpyRJoaGhGjlypDZs2KCLFy8qPj5eJ0+eVGRkpO655x7bVmjR0dEaNmyYhg8fnur5iUt4g7fijHhGVjh//ry6du2q8+fP246VKlVKs2fPdmulcuIS6fHWW29p//79km6uXJZy5b/MQmzCU86e38DAQH3xxRdpbsXbtm1bh+TVr7/+2q1+iE3nSPwDAAAAAADwgYIFC5rK9t9idYf9t1Ttzwm4Y/r06XruuedMx4YMGaIPPvjA7XNkNJ6dfeOaeM65nnzySdvWPqVLl9aHH36Y6X0wxyI9UnuOH374YbfaV6lSRZ06dTIdc5b4R3wiPR5//HH9+uuvtnLz5s21a9cujR49Ws2aNVORIkWUJ08elSlTRnfddZdmz56t3377zfTh5scff6wpU6Y4PT9xCW/wVpwRz8hsV65cUdeuXbVv3z7bscKFC2vBggWqXLmyW+cgLuGpLVu26JNPPrGVR44cqapVq2Z6P8QmPOXs+b3zzjvd2jFCkh555BFTef369U6T+ohN95D4BwAAAAAA4AP2/2i6fv260+0AXbl27ZrLcwJpmTdvngYPHmyKvXvvvVfffvttmt/STsk+9uxjMy329QMDA3Pkt7AhzZo1S3PmzLGVP//8cxUpUiTT+8loTBqGkSs+IIBZvnz5FBAQYDoWEhKixo0bu32Odu3amcqbNm1yqEN8wlPLly/XpEmTbOWSJUtq3rx5Kl26tMt2PXv21BdffGE6Nnz4cLcS7j2NS2dtiEvY89b8x3stZKbY2Fj17NnT9JqeP39+zZ8/Xw0bNnT7PMyz8ERiYqIefPBBJSUlSZIaNGhgWjU9MzFnwlPOnl/790GuNGvWTPny5bOVY2NjtWPHjjT7ITadI/EPAAAAAADAB4oXL25KrEpISNDZs2c9OseJEydM5ZIlS2bK2JA7LFu2TH369FFiYqLtWOfOnTVjxgyHxJe02Mfe8ePHPWpvH8slSpTwqD2yj5TbTHbv3l19+/bNkn4yGpNnzpwxXRv+/v4qXrx4powN1mYfO9WqVTNt35uWmjVrmsrOXtuJT3hq/PjxpvJzzz3n9mvlkCFDVKNGDVv5woULmj17tkO9jMalJJ08edLlOQFvzX+810JmSUhIUN++fbV8+XLbsaCgIM2ePVutWrXy6Fz2MWQfY+4gLnOPqVOnavv27ZJuznVff/21AgMDs6Qv5kx4qlSpUg7HUv69mZbAwECH1SudxRyx6R4S/wAAAAAAAHwgX758qlixounY0aNHPTqHff1atWpleFzIHdavX6+ePXuatkmJiIjQnDlzFBQU5PH57BNdiGWk5tYWv5I0f/58+fn5pfnToUMH0zmOHDniUGfbtm2mOpkdk2FhYaxCmUvUrl3bVC5UqJBH7e3rX7x40aEO8QlPGIahpUuXmo7dddddbrf39/dX9+7dTcdWrlzpUC+jcXn27FnT3xVBQUGqUqWKR+dAzuet+Y/3WsgMycnJGjRokObOnWs7FhAQoOnTp+uOO+7w+HxVqlQxJW7duHFD586d8+gcxGXukfJ9U3Jyslq2bOnWe6cVK1aYzjN06FDT7XfffbdDX8yZ8JT9eyYpa943EZvuIfEPAAAAAADAR+z/2bR7926P2u/Zs8fl+QBn/vnnH3Xt2lVXr161HWvcuLH++OMPFShQIF3nJJZhNcQk0qtOnTqmclxcnEftUyY+STe3ArRHfMITFy9e1KVLl0zHKleu7NE57Os7W2XKPo4OHjyo+Ph4t/uwj8uqVatm2cpEyL68Of8x1yIjDMPQI488opkzZ9qO+fn56dtvv9V9992XrnPmyZPHYYUrT+IyLi5Ohw4dMh0jLpFZmDPhCfv3TFLWvG+SiE13kPgHAAAAAADgI40aNTKV16xZ43bbU6dO6fDhw7Zynjx5nP7jDUhp79696ty5s+mb1LVr19aCBQtUuHDhdJ/XPpY3btxo2oYtLX///bfL8wGeqlu3rvLkyWMrHz58WKdOnXK7PTGZezVp0sRUPnPmjEft7beeKlasmEMd4hOecPYhqqcJdSnjTZKSkpIc6pQuXVqlS5c29bt582a3+yAu4Q5vzn+810JGPP/885o0aZLp2Pjx4zVkyJAMnTcjcbl582bTa0KZMmVy5JaV8A3mTHiiWLFiDivxZcX7JonYdAdftQEAAAAAAPCRHj16aOzYsbby4sWLZRiG/Pz80my7cOFCU7lDhw4qWLBgpo8ROceRI0fUqVMn0z9XK1eurEWLFqlEiRIZOnetWrVUtWpVHTx4UJJ07do1rVmzRm3btk2z7bVr17R27Vpb2c/PTz169MjQeGBdv//+uxISEjxqs337dr300ku2cqlSpTR16lRTnWrVqpnKISEhatu2rZYsWWI7tmjRIg0aNCjN/gzD0OLFi03HPNlWE9lb9+7d5e/vr+TkZElSVFSUoqOjFRoa6lZ7+0Qp+20tJeITnnH2IejJkyc9WvXPfoW/1F73u3fvbkp0WbRokW677Ta3+li0aJGpTFzCGW/Of7zXQnqNGDFCn3/+uenYe++9p6eeeirD5+7Ro4d++uknW3nRokV67bXX3GrLPJu73HfffapXr57H7V588UX9888/tvLw4cPVpUsXWzm1ZFHmTHiqZ8+emjBhgq28efNmt17PpZtJgsePHzcdq1GjhtO6xGbaSPwDAAAAAADwkYiICBUvXlznz5+XJB06dEjLly9Xhw4d0mxrv/pAr169smSMyBlOnTql22+/3fSP1XLlymnJkiUqV65cpvTRs2dPjRs3zlaeNGmSW4l/P/30k2nb4fDwcJUtWzZTxgTradeuncdt7Fe2yps3rzp16pRmu549e5oSCyZNmuTWBxHLli1TVFSUrVyqVCm1aNHCgxEjOytZsqRatWqlVatW2Y7Nnj1bDz30UJptExMTNWfOHNOx9u3bO61LfMJdQUFBKlOmjGlVtKVLl2rYsGFunyNlrEly2Grylp49e5r+xpwyZYpGjBiR5gerBw8e1IoVK2zlPHnyqFu3bm6PD7mLt+Y/3mshPT766CO9++67pmOvvfaa28l5aenWrZsCAwNtq6MvX75chw4dUpUqVVy2MwxD3333nekYcZmzVahQQRUqVPC4XdGiRU3lOnXquPXeiTkTnrrnnntMiX+//fabxo0bJ3//tDee/eWXX0zl2rVrq1SpUk7rEptpY6tfAAAAAAAAH/H393fYKmj06NEyDMNluyVLlpgSEkJCQtS3b9+sGCJygOjoaHXu3Nm2Gp90c6WfRYsWebRaUFoefPBBU2LAzJkztWfPHpdtYmNj9cEHH5iOeZLIALjSr18/FShQwFZeuXKlli5d6rKNYRgaPXq06djQoUPd+vACOcejjz5qKn/00UdOt1u198033+j06dO2cqFChXTHHXc4rUt8whO33367qfzZZ5/ZkkbSsmLFCtPKus7Od8sdd9yh8uXL28qHDx/WlClT0uxj1KhRpr9f77vvPhUuXNit8SH38db8x3steGrixIl6+eWXTceeeuopvffee5nWR2hoqO6++25b2TAMjRo1Ks12kydPNm1XGRYW5lYyF+Au5kx4ql27dqbVzY8eParvv/8+zXbXr1/XJ598YjrmKmaIzbTxbhAAAAAAAMCHXnnlFdM2EytWrDBtYWHvxIkTDqsOPfvssypevHiWjRHZ15UrV3TnnXdq165dtmNFihTRwoULVbt27Uztq169eqZ/osbHx2vw4MG6fPmy0/qGYei5557T/v37bceqVKmiBx98MFPHhdyrZMmSDluyPfTQQzp58mSqbd5//32tXLnSVi5cuLCGDx+eZWOENT3wwAOqX7++rbxv3z49+uijtu1/nVm/fr1DssATTzyRavIT8QlPDBgwwFTeuXOnnnjiCZcxKUkHDhxQ//79TceqV6+e6va9wcHBeuONN0zHXnrpJe3evTvVPqZPn27afj0gIMAhQQtIyZvzH++14K7p06friSeeMB0bOnSoxo8fn+l9jR492pS0+uOPP2rGjBmp1t+9e7deeukl07ERI0YoKCgo08eG3I05E54ICAhwWCH1+eef15YtW1Jtk5SUpGHDhplW8C1QoICefvppl30Rm675GWmlQQIAAAAAACBLvf/++3r99ddNxx5//HG9+eabti1Pk5OTFRkZqWeffVZHjx611Stbtqx27dqlIkWKeHPIyCY6dOig5cuXm469/fbbqX7g70rTpk0dtg2yd+DAATVs2FDXr1+3HWvYsKE+++wz03aX+/bt02uvvabZs2eb2v/888/q06ePx2NDzma/jU9YWJhpxRNXoqOjVbduXdMqbGFhYRo/frzuuusu2yqVx48f17vvvquJEyea2n/44YckVuVSS5YsUefOnU0rSXTq1EkffPCBmjZtajt26dIlTZo0SW+99ZZp2/IaNWpo06ZNCgkJSbUP4hOe6Ni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            "text/plain": [
              "<Figure size 2000x800 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Create the gantt chart\n",
        "fig, ax = makeChart(strategies, event=event_name,\n",
        "                    filters_color_dict=filters_color_dict,\n",
        "                    exptimes_marker_list=exptimes_marker_list)\n",
        "\n",
        "# # Save the figure and show the plot\n",
        "# plt.savefig(filename_out, bbox_inches='tight')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IlOUEA-9f92e"
      },
      "source": [
        "## Plot transient light curve"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JMkz-S0-f92e"
      },
      "source": [
        "Plot the light curve of a transient given the strategy defined above."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "uXUVp-i3f92e"
      },
      "outputs": [],
      "source": [
        "import glob\n",
        "\n",
        "import numpy as np\n",
        "from astropy.io import ascii\n",
        "import matplotlib.pyplot as plt\n",
        "from scipy import interpolate\n",
        "from matplotlib.ticker import MaxNLocator\n",
        "from astropy.cosmology import Planck18 as cosmo\n",
        "import astropy.cosmology as ac\n",
        "import astropy.units as u\n",
        "\n",
        "import plot_lc"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z_kf2TI5f92e"
      },
      "source": [
        "One important variable to be set is `delay_hr`, which is the delay time between the onset of the transient (e.g., the merger of two compact objects) and the start of the observability window. Note that `cadence_hr` starts from the beginning of the observability window, since we cannot predict when the onset is, if the event happens during the Chilean daytime.\n",
        "\n",
        "Light curve models come in ASCII or CSV files. Check out the `models/` folder and use the same format, if you want to add your favorite model. Simply assign the path to the model to the `model_filename` variable.\n",
        "\n",
        "A grid of kilonova light curves is available, which were obtained with 3D Monte Carlo radiative transfer code (Bulla 2019, 2023; Anand et al. 2023). Four parameters can be chosen: the dynamic ejecta mass `mej_dyn`, the disk wind ejecta mass `mej_wind`, the half opening angle of the lanthanide-rich dynamical-ejecta component `phi` and the viewing angle `theta` (see Dietrich et al. 2020, for more details about the adopted geometry). The grid is available for kilonovae at distances from 100Mpc to 700Mpc, which is twice the upper bound of the projected horizon for BNS mergers in O5, at intervals of 100Mpc. More of such light curves can be produced on demand (ask Igor). The best-fit parameters to GW170817, ignoring the distance, are:\n",
        "\n",
        "```\n",
        "inj_params_list = [{'mej_dyn': 0.005,\n",
        "              'mej_wind': 0.050,\n",
        "              'phi': 30,\n",
        "              'theta': 25.8,\n",
        "              'dist_Mpc': 300  #  Distance (Mpc), available from 100Mpc to 700Mpc at 100Mpc intervals\n",
        "                   }]\n",
        "```\n",
        "Suggestions for parameters that can be used to probe a good range of models can be found in Table 2 in\n",
        "[Andreoni et al. (2023)](https://ui.adsabs.harvard.edu/abs/2024APh...15502904A/abstract) and the models used in that paper are given here as a dictionary.\n",
        "\n",
        "<b>Lensed kilonova</b> light curves are also available, from [Smith et al. (2023)](https://ui.adsabs.harvard.edu/abs/2023MNRAS.520..702S/abstract). The brighter one is 170817-like in its SED and evolution and the fainter one is a more conservatively viewed and redder model. Both are placed at z=1.6. All details can be found in the paper."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "14YAgxxtf92f",
        "outputId": "db4a78a7-d69d-4d10-f77d-83bf72200b3d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Selected model file name: \n",
            " models/kilonova_Bulla/nph1.0e+06_dyn0.001-0.15-0.20_wind0.050-0.03_theta25.84_dMpc700.dat\n"
          ]
        }
      ],
      "source": [
        "# Delay between transient onset and start of the observing window\n",
        "delay_hr = 6.\n",
        "\n",
        "# Distance in Mpc, available from 100Mpc to 700Mpc at 100Mpc intervals\n",
        "distance_Mpc = 700\n",
        "\n",
        "# Here are some selected models from the Bulla+19, Anand+23 model grid. Do not modify unless necessary\n",
        "# Please look at models/kilonova_Bulla/ folder for more options.\n",
        "models = {\"GW170817 best fit polar, theta=26deg\": f\"models/kilonova_Bulla/nph1.0e+06_dyn0.001-0.15-0.20_wind0.050-0.03_theta25.84_dMpc{distance_Mpc}.dat\",\n",
        "          \"GW170817 best fit equatorial, theta=90deg\": f\"models/kilonova_Bulla/nph1.0e+06_dyn0.001-0.15-0.20_wind0.050-0.03_theta90.00_dMpc{distance_Mpc}.dat\",\n",
        "          \"Kilonova low Y_e and M_ej, theta=45deg\": f\"models/kilonova_Bulla/nph1.0e+06_dyn0.001-0.15-0.15_wind0.010-0.03_theta45.57_dMpc{distance_Mpc}.dat\",\n",
        "          \"Kilonova low Y_e, theta=26deg\": f\"models/kilonova_Bulla/nph1.0e+06_dyn0.001-0.15-0.15_wind0.050-0.03_theta25.84_dMpc{distance_Mpc}.dat\",\n",
        "          \"Kilonova low M_e, theta=26deg\": f\"models/kilonova_Bulla/nph1.0e+06_dyn0.010-0.15-0.20_wind0.010-0.03_theta25.84_dMpc{distance_Mpc}.dat\",\n",
        "          \"Kilonova high M_ej, theta=26deg\": f\"models/kilonova_Bulla/nph1.0e+06_dyn0.020-0.15-0.20_wind0.090-0.03_theta25.84_dMpc{distance_Mpc}.dat\",\n",
        "          \"Lensed kilonova z=1.6 bright\": f\"models/kilonova_lensed_Nicholl/M1.188_q0.92_z1.6_C24_d0.12_v32_forIgor.txt\",\n",
        "          \"Lensed kilonova z=1.6 faint\": f\"models/kilonova_lensed_Nicholl/M1.200_q0.90_z1.6_C0_d0.15_v60_forIgor.txt\",\n",
        "}\n",
        "\n",
        "# Pick the model\n",
        "model_filename = models[\"GW170817 best fit polar, theta=26deg\"]\n",
        "\n",
        "# Verbose\n",
        "print(f\"Selected model file name: \\n {model_filename}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AaW0qpyqf92h",
        "outputId": "19d91dda-4f52-44c6-9fa3-343d8f8f8939"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Strategy name: Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 1\n",
            "\n",
            "Detections:\n",
            "Filter      Day          Magnitude\n",
            "     g 0.333333 21.797631578947367\n",
            "     g 0.500000  22.09148275862069\n",
            "     g 0.625000  22.20183783783784\n",
            "     r 0.354167  22.42488888888889\n",
            "     r 0.520833 22.224822222222222\n",
            "     r 0.645833   22.1664009009009\n",
            "     r 1.312500 23.527272727272727\n",
            "     i 0.375000              22.68\n",
            "     i 0.541667 22.417355555555556\n",
            "     i 0.666667 22.227701754385965\n",
            "\n",
            "Non-Detections:\n",
            "Filter      Day  Limiting Magnitude\n",
            "     r 2.312500                24.5\n",
            "     r 3.312500                24.5\n",
            "     i 1.333333                23.0\n",
            "     i 2.333333                23.0\n",
            "     i 3.333333                23.0\n",
            "\n",
            "Strategy name: Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 2\n",
            "\n",
            "Detections:\n",
            "Filter      Day          Magnitude\n",
            "     g 0.333333 21.797631578947367\n",
            "     g 0.500000  22.09148275862069\n",
            "     r 0.354167  22.42488888888889\n",
            "     r 0.520833 22.224822222222222\n",
            "     r 1.312500 23.527272727272727\n",
            "     i 0.375000              22.68\n",
            "     i 0.541667 22.417355555555556\n",
            "\n",
            "Non-Detections:\n",
            "Filter      Day  Limiting Magnitude\n",
            "     r 2.312500                24.5\n",
            "     r 3.312500                24.5\n",
            "     i 1.333333                23.0\n",
            "     i 2.333333                23.0\n",
            "     i 3.333333                23.0\n",
            "\n",
            "Strategy name: Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 3\n",
            "\n",
            "Detections:\n",
            "Filter      Day          Magnitude\n",
            "     g 0.458333             21.978\n",
            "     r 0.479167 22.254283950617282\n",
            "     r 0.562500 22.164772727272727\n",
            "     r 1.312500 23.527272727272727\n",
            "     i 0.500000 22.484862068965516\n",
            "\n",
            "Non-Detections:\n",
            "Filter      Day  Limiting Magnitude\n",
            "     r 2.312500                24.5\n",
            "     r 3.312500                24.5\n",
            "     i 1.333333                23.0\n",
            "     i 2.333333                23.0\n",
            "     i 3.333333                23.0\n"
          ]
        }
      ],
      "source": [
        "# Import the function from the py file\n",
        "import strategy_detections as sd\n",
        "\n",
        "# Read the model\n",
        "t_model = ascii.read(model_filename)\n",
        "\n",
        "# Call the function (example)\n",
        "sd.detections_non_detections(strategies, t_model, delay_hr=6, offset_filt_hr=0.5)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "A-41R7cqf92h",
        "outputId": "22522deb-0338-444f-a97c-e7c8122910bb"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            " Strategy name: Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 1\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            " Strategy name: Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 2\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            " Strategy name: Gold Events: 3 Filter Deep Strategy (700 Mpc) Case 3\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Read the model\n",
        "t_model = ascii.read(model_filename)\n",
        "\n",
        "# Plot the lightcurve using the updated function from the plot_lc module\n",
        "plot_lc.doPlotLc2(strategies, t_model,\n",
        "                 delay_hr,  # delay time between merger and observing window\n",
        "                 xlim=[0, 4], # x axis limit in days\n",
        "                 ylim=[28,18],  # y axis limit in apparent mag\n",
        "                 n_interp=120,  # Number of points for the interpolation (e.g. 150)\n",
        "                 offset_filt_hr=0.5,  # offset in hours between filters (to show overlapping points)\n",
        "                 outfile_base=\"plot_lc\",  # Base name for the file to be saved\n",
        "                 outfile_format='pdf',  # Format of the output plot (pdf, png, etc)\n",
        "                 doSave=True,  # If set to False, the plot will not be saved\n",
        "                 event_name=event_name,  # Name of the event for the X label\n",
        "                 linestyle=\"-\",\n",
        "                 filters_color_dict=filters_color_dict)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UE6OR5pCf92i"
      },
      "source": [
        "## Time budget\n",
        "\n",
        "Based on the strategies adopted, compute the time budget. Some parameters need to be defined, such as:\n",
        "- overheads between exposures (readout)\n",
        "- overheads for the first slew\n",
        "- overheads for the filter change\n",
        "- number of fields (i.e., number of tiles)\n",
        "- number of events (i.e., number of GW events or other)\n",
        "- ratio of number of days in which u-band is mounted (10/30 for 10 days per month)\n",
        "\n",
        "IMPORTANT: the filter change and first slew overhead will be divided by the number of fields, assuming that Rubin will complete a full pass of the tiling before changing filter."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "iVUQp_-Tf92i"
      },
      "outputs": [],
      "source": [
        "# Overheads\n",
        "overhead_between_exposures = 7.  # in seconds\n",
        "\n",
        "# Overhead first slew per epoch, assuming it may be further away than tiling\n",
        "overhead_first_slew = 30\n",
        "\n",
        "# Overhead for filter change\n",
        "overhead_filter_change = 120.  # in seconds\n",
        "\n",
        "# Number of fields\n",
        "n_fields = 14\n",
        "\n",
        "# Number of separate compact mergers (or other type of events) to follow-up\n",
        "n_events = 1\n",
        "\n",
        "# If 6 filters are given, one must be dropped.\n",
        "# Indicate here the number of days per month in which u band is used.\n",
        "# Y band will be assumed for the other epochs. The total time budget will be a combination of the two.\n",
        "u_days_ratio = 14./30"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IzygDB5Bf92i"
      },
      "source": [
        "Look at what `strategies` are being used again for verification"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "aWc6qS0Uf92j",
        "outputId": "df9f7fba-3c42-4d61-bcd3-17d774f246a2",
        "scrolled": true
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'Lensed KN Ω=100deg2': {'cadence_hr': [24, 48, 120],\n",
              "  'exptimes_median': [600, 600, 600],\n",
              "  'exptimes': [[600, 600], [600, 600], [600, 600]],\n",
              "  'depths_median': [26.200000000000003,\n",
              "   26.200000000000003,\n",
              "   26.200000000000003],\n",
              "  'depths': [[26.64, 25.76], [26.64, 25.76], [26.64, 25.76]],\n",
              "  'filters': ['gi', 'gi', 'gi']}}"
            ]
          },
          "execution_count": 119,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "strategies"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tY57EWxlf92j"
      },
      "source": [
        "Now calculate the total time for the fields and events"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GG4HF0sUf92k",
        "outputId": "e38fc48a-78f9-4a22-f841-0653819fcbee"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            " >> Strategy name: Lensed KN Ω=100deg2\n",
            "  Epoch 24 hr:\n",
            "    exposure times: 1200s\n",
            "    overhead change filter: 240.0s\n",
            "    overhead between exposures: 7.0s\n",
            "  Epoch 48 hr:\n",
            "    exposure times: 1200s\n",
            "    overhead change filter: 240.0s\n",
            "    overhead between exposures: 7.0s\n",
            "  Epoch 120 hr:\n",
            "    exposure times: 1200s\n",
            "    overhead change filter: 240.0s\n",
            "    overhead between exposures: 7.0s\n",
            "Total exposure time per pointing: 1.00hr\n",
            "Total time for 14 fields: 14.10hr\n",
            "Total time for 14 fields and 1 events: 14.10hr\n",
            "-- \n",
            "\n"
          ]
        }
      ],
      "source": [
        "for i in range(len(strategy_names)):\n",
        "    print(f\"\\n >> Strategy name: {strategy_names[i]}\")\n",
        "    # Initialize total overhead slews\n",
        "    overhead_first_slew_total = 0\n",
        "    # Initialize total overhead readouts\n",
        "    overhead_filter_change_total = 0\n",
        "    # Initialize total overhead readouts\n",
        "    overhead_between_exposures_total = 0\n",
        "    # Initialize total exposure time\n",
        "    exptime_total = 0\n",
        "\n",
        "    # Iterate over epochs\n",
        "    for cadence_hr, exptimes_epoch, filters_epoch in zip(strategies[strategy_names[i]][\"cadence_hr\"],\n",
        "                                             strategies[strategy_names[i]][\"exptimes\"],\n",
        "                                             strategies[strategy_names[i]][\"filters\"]):\n",
        "        # Add overheads for the first slew\n",
        "        overhead_first_slew_total += overhead_first_slew\n",
        "        # Initialize\n",
        "        exptime_epoch = 0\n",
        "        # Check if 6 filters are given\n",
        "        if len(filters_epoch) == 6:\n",
        "            # add overhead between exposures\n",
        "            overhead_between_exposures_epoch = overhead_between_exposures * 4\n",
        "            # Add overhead change of filter, assuming the first filter changes, too\n",
        "            overhead_filter_change_epoch =  overhead_filter_change * 5\n",
        "            # Combine exposure times between u and y\n",
        "            for filt, exptime in zip(filters_epoch, exptimes_epoch):\n",
        "                if filt == \"u\":\n",
        "                    exptime_epoch += exptime * u_days_ratio\n",
        "                elif filt == \"y\":\n",
        "                    exptime_epoch += exptime * (1-u_days_ratio)\n",
        "                else:\n",
        "                    exptime_epoch += exptime\n",
        "        # In case <= 5 filters are given for this epoch\n",
        "        else:\n",
        "            overhead_between_exposures_epoch = overhead_between_exposures * (len(exptimes_epoch) - 1)\n",
        "            # Add overhead change of filter, assuming the first filter changes, too\n",
        "            overhead_filter_change_epoch = overhead_filter_change * len(exptimes_epoch)\n",
        "            # Exposure time\n",
        "            exptime_epoch = np.sum(exptimes_epoch)\n",
        "\n",
        "        # Add the exposure times to the epoch to the total\n",
        "        exptime_total += exptime_epoch\n",
        "        # Add overheads\n",
        "        overhead_between_exposures_total += overhead_between_exposures_epoch\n",
        "        overhead_filter_change_total += overhead_filter_change_epoch\n",
        "        # Print results for the epoch\n",
        "        print(f\"  Epoch {cadence_hr} hr:\")\n",
        "        print(f\"    exposure times: {'{:.0f}'.format(exptime_epoch)}s\")\n",
        "        print(f\"    overhead change filter: {overhead_filter_change_epoch}s\")\n",
        "        print(f\"    overhead between exposures: {overhead_between_exposures_epoch}s\")\n",
        "\n",
        "    # calculate the total overheads, convert overhead from seconds to hours\n",
        "    # IMPORTANT: the filter change and first slew overhead must to be divided by the number of fields,\n",
        "    # if we complete the tiling before changing filters\n",
        "    overheads_total_nfields = np.sum((overhead_between_exposures_total * n_fields)/60/60 +\n",
        "                       overhead_first_slew_total/n_fields/60/60 +\n",
        "                       overhead_filter_change_total/n_fields/60/60)\n",
        "\n",
        "    # calculate the total exposure time per field/pointing in hours\n",
        "    total_exposure_time_hr = exptime_total/60/60\n",
        "\n",
        "    # Calculate the total time budget in hours per event\n",
        "    budget_strategy_nfields_hr = total_exposure_time_hr * n_fields + overheads_total_nfields\n",
        "\n",
        "    print(f\"Total exposure time per pointing: {'{:.2f}'.format(total_exposure_time_hr)}hr\")\n",
        "    #print(f\"Total overheads per pointing, assuming {n_fields} fields: {'{:.2f}'.format(overheads_total_nfields)}hr ({'{:.2f}'.format(100*overheads/budget_strategy_hr)}% of total budget)\")\n",
        "    print(f\"Total time for {n_fields} fields: {'{:.2f}'.format(budget_strategy_nfields_hr)}hr\")\n",
        "    print(f\"Total time for {n_fields} fields and {n_events} events: {'{:.2f}'.format(budget_strategy_nfields_hr * n_events)}hr\")\n",
        "    print(\"-- \\n\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8p75tlDQf92k"
      },
      "source": [
        "## Exposure Time Calculator\n",
        "\n",
        "From a given filter and magnitude limit (5 sigma), get the exposure time. The formulae were obtained from Formulae from [SMTN 002](https://smtn-002.lsst.io/v/OPSIM-1134/index.html).\n",
        "\n",
        "The formula to go from the magnitude limit to the exposure time was slightly simplified, but it is accurate within 0.28s for 30s exposures."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eoRSugsif92l"
      },
      "outputs": [],
      "source": [
        "# Import the custom exposure time calculator\n",
        "import etc"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rMVo8cxNf92l"
      },
      "outputs": [],
      "source": [
        "# Define filters and magnitude limits\n",
        "filters = \"ugrizy\"\n",
        "mag_limits = [24.5, 24.5, 24.5, 24.5, 24.5, 24.5]  # in AB mag\n",
        "\n",
        "# Define airmass (>= 1)\n",
        "airmass = 1.2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "kFIaC5Ydf92l",
        "outputId": "f5b25524-4fd7-4343-cc23-df5adae6deee"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "filter, mag_limit, exptime (s)\n",
            "u, 24.5, 156\n",
            "g, 24.5, 14\n",
            "r, 24.5, 31\n",
            "i, 24.5, 62\n",
            "z, 24.5, 175\n",
            "y, 24.5, 1158\n"
          ]
        }
      ],
      "source": [
        "print(\"filter, mag_limit, exptime (s)\")\n",
        "for filt, mag in zip(filters, mag_limits):\n",
        "    exptime = int(np.round(etc.get_exptime(mag, filt, X=airmass)))\n",
        "    print(f\"{filt}, {mag}, {exptime}\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OuJ14nJCf92v"
      },
      "source": [
        "Now from a given filter and exposure time, get the magnitude limit (5 sigma)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3PprNBjAf92v"
      },
      "outputs": [],
      "source": [
        "# Define filters and exp times\n",
        "filters = \"ugrizy\"\n",
        "exptimes = [30, 30, 60, 60, 60, 60]  # in seconds\n",
        "\n",
        "# Define airmass (>= 1)\n",
        "airmass = 1."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "sRvsgXScf92w",
        "outputId": "60b3f244-b6dd-4797-a059-070f2976dc3b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "filter, mag_limit, exptime (s)\n",
            "u, 23.7, 30\n",
            "g, 25.0, 30\n",
            "r, 24.9, 60\n",
            "i, 24.5, 60\n",
            "z, 23.9, 60\n",
            "y, 22.9, 60\n"
          ]
        }
      ],
      "source": [
        "print(\"filter, mag_limit, exptime (s)\")\n",
        "for filt, exptime in zip(filters, exptimes):\n",
        "    mag = etc.get_m5(exptime, filt, X=airmass)\n",
        "    print(f\"{filt}, {'{:.1f}'.format(mag)}, {exptime}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "CcgBvjgGf92w"
      },
      "outputs": [],
      "source": []
    }
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