{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "91976a72",
   "metadata": {},
   "source": [
    "# Point source likelihood\n",
    "\n",
    "`icecube_tools` also provides an interface to the likelihoods often used in point source searches of the neutrino data (see [this paper](https://arxiv.org/abs/0801.1604) by Braun et al.).\n",
    "\n",
    "$$\n",
    "\\mathcal{L} = \\prod_{i=1}^N \\Bigg[ \\frac{n_s}{N} \\mathcal{S}(\\theta_i, E_i, \\gamma) + (1-\\frac{n_s}{N}) \\mathcal{B}(\\theta_i, E_i) \\Bigg],\n",
    "$$\n",
    "where $N$ is the total number of detected neutrino events, $n_s$ is the expected number of source events, $\\theta$ is the neutrino direction, $E$ is the reconstructed neutrino energy and $\\gamma$ is the source spectral index.\n",
    "\n",
    "The point source likelihood is a mixture model with two components: one representing possible astrophysical neutrino sources, $\\mathcal{S}(\\theta, E)$, and the other known background, $\\mathcal{B}(\\theta, E)$. Each component has terms depending on the directional or spatial source--neutrino relationship and also the energy of the neutrinos, as higher energy neutrinos are more likely to come from astrophysical sources. Depending on the search, the energy dependence may be omitted. Also, there may be a temporal dependence added, but this is not yet implemented in `icecube_tools`.\n",
    "\n",
    "Here we implement a simple likelihood and apply it to some simulated data. There are several likelihoods available, and more information can be found in the API documentation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1ee0b254",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:15.032311Z",
     "iopub.status.busy": "2024-03-22T09:57:15.032125Z",
     "iopub.status.idle": "2024-03-22T09:57:16.298404Z",
     "shell.execute_reply": "2024-03-22T09:57:16.297736Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "import h5py\n",
    "\n",
    "from icecube_tools.point_source_likelihood.spatial_likelihood import (\n",
    "    EventDependentSpatialGaussianLikelihood,\n",
    ")\n",
    "from icecube_tools.point_source_likelihood.energy_likelihood import (\n",
    "    MarginalisedEnergyLikelihood2021,\n",
    "    read_input_from_file,\n",
    "    MarginalisedIntegratedEnergyLikelihood,\n",
    ")\n",
    "from icecube_tools.point_source_likelihood.point_source_likelihood import (\n",
    "    PointSourceLikelihood,\n",
    "    TimeDependentPointSourceLikelihood,\n",
    ")\n",
    "\n",
    "from icecube_tools.detector.effective_area import EffectiveArea\n",
    "from icecube_tools.detector.r2021 import R2021IRF\n",
    "from icecube_tools.detector.detector import IceCube\n",
    "from icecube_tools.utils.data import Events, SimEvents, RealEvents"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cad2dc9b",
   "metadata": {},
   "source": [
    "## Spatial likelihood"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fce8452",
   "metadata": {},
   "source": [
    "We can start with the spatial/directional term. Let's use the energy dependent spatial likelihood. It is build from a Gaussian with an event-wise uncertainty sampled from the IRF data. The background case will simply be an isotropic distribution on the sphere."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8b4e3647",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:16.301440Z",
     "iopub.status.busy": "2024-03-22T09:57:16.301227Z",
     "iopub.status.idle": "2024-03-22T09:57:16.304382Z",
     "shell.execute_reply": "2024-03-22T09:57:16.303846Z"
    }
   },
   "outputs": [],
   "source": [
    "angular_resolution = 5\n",
    "spatial_likelihood = EventDependentSpatialGaussianLikelihood(angular_resolution)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b401c616",
   "metadata": {},
   "source": [
    "We show the likelihood profile for a single event with an assumed uncertainty of 1 degree."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e81ee224",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:16.306826Z",
     "iopub.status.busy": "2024-03-22T09:57:16.306394Z",
     "iopub.status.idle": "2024-03-22T09:57:16.480976Z",
     "shell.execute_reply": "2024-03-22T09:57:16.480386Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f807aba2dc0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "source_coord = (np.pi, np.deg2rad(30))\n",
    "test_ra = np.pi + np.linspace(-0.1, 0.1, 100)\n",
    "test_dec = np.full((100), source_coord[1])\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(np.rad2deg(test_ra), spatial_likelihood(1.0, test_ra, test_dec, source_coord))\n",
    "ax.axvline(\n",
    "    np.rad2deg(source_coord[0]), color=\"k\", linestyle=\":\", label=\"Source location\"\n",
    ")\n",
    "ax.set_xlabel(\"RA [deg]\")\n",
    "ax.set_ylabel(\"Spatial likelihood\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d58517b",
   "metadata": {},
   "source": [
    "## Energy likelihood"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a02f3b5",
   "metadata": {},
   "source": [
    "Now let's think about the energy-dependent term. The way this is handled is to marginalise over the true neutrino energies, to directly connect the reconstructed neutrino energies to the spectral index of a simple power-law source model.\n",
    "\n",
    "Doing this properly requires a knowledge of the relationship between the true and reconstructed energies as well as the details of the power law model. The most straightforward way to implement this is to simulate the a large number of events using the `Simulator` and build a likelihood using the output of this simulation and `MarginalisedEnergyLikelihoodFromSim`. We do exactly this with pre-computed lists of events, to be found in the data subdirectory: `sim_output_{index}.h5`. These were simulated using point sources with spectral index `index` at 45 degrees declination. The likelihood is restricted to a small band of declination around the assumed source. Using the same declination for our test source, this is fine. For different source declinations further simulations would be needed to account for the declination dependence of the detector acceptance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d59d0ee7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:16.483569Z",
     "iopub.status.busy": "2024-03-22T09:57:16.483176Z",
     "iopub.status.idle": "2024-03-22T09:57:18.627576Z",
     "shell.execute_reply": "2024-03-22T09:57:18.626796Z"
    }
   },
   "outputs": [],
   "source": [
    "aeff = EffectiveArea.from_dataset(\"20210126\", period=\"IC86_II\")\n",
    "irf = R2021IRF.from_period(\"IC86_II\")\n",
    "# new_reco_bins = irf.reco_energy_bins[12, 2]\n",
    "new_reco_bins = np.linspace(1, 9, num=25)\n",
    "detector = IceCube.from_period(\"IC86_II\")\n",
    "energy_likelihood = MarginalisedIntegratedEnergyLikelihood(\n",
    "    \"IC86_II\", new_reco_bins, max_index=4.5\n",
    ")\n",
    "# energy_likelihood = MarginalisedEnergyLikelihood2021([1.5, 2.0, 2.5, 3.0, 3.5, 3.7, 4.0], 'data', 'sim_output', np.pi/4,)\n",
    "# the likelihood class is backwardscompatible with the \"older\" simulation-based energy likelihood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5ba0d4ae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:18.630380Z",
     "iopub.status.busy": "2024-03-22T09:57:18.630153Z",
     "iopub.status.idle": "2024-03-22T09:57:18.634823Z",
     "shell.execute_reply": "2024-03-22T09:57:18.634200Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.        , 1.33333333, 1.66666667, 2.        , 2.33333333,\n",
       "       2.66666667, 3.        , 3.33333333, 3.66666667, 4.        ,\n",
       "       4.33333333, 4.66666667, 5.        , 5.33333333, 5.66666667,\n",
       "       6.        , 6.33333333, 6.66666667, 7.        , 7.33333333,\n",
       "       7.66666667, 8.        , 8.33333333, 8.66666667, 9.        ])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_reco_bins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2a301867",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:18.637256Z",
     "iopub.status.busy": "2024-03-22T09:57:18.636870Z",
     "iopub.status.idle": "2024-03-22T09:57:19.152409Z",
     "shell.execute_reply": "2024-03-22T09:57:19.151716Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f80734af400>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# test_energies = np.geomspace(10, 1e7) # GeV\n",
    "test_indices = [2.0, 2.5, 3, 3.5]\n",
    "energy = np.logspace(2, 7.66, num=1000, endpoint=False)\n",
    "fig, ax = plt.subplots()\n",
    "for index in test_indices:\n",
    "    ax.plot(\n",
    "        energy,\n",
    "        energy_likelihood(energy, index, np.full(energy.shape, np.deg2rad(45))),\n",
    "        label=f\"{index:.1f}\",\n",
    "    )\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(\"E_reco [GeV]\")\n",
    "ax.set_ylabel(\"Energy likelihood\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10014d1c",
   "metadata": {},
   "source": [
    "## Point source likelihood"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3025e76",
   "metadata": {},
   "source": [
    "Now we can bring together the spatial and energy terms to build a full `PointSourceLikelihood`. First, let's load some data from the simulation notebook to allow us to demonstrate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ca609d05",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:19.154951Z",
     "iopub.status.busy": "2024-03-22T09:57:19.154554Z",
     "iopub.status.idle": "2024-03-22T09:57:19.160554Z",
     "shell.execute_reply": "2024-03-22T09:57:19.160073Z"
    }
   },
   "outputs": [],
   "source": [
    "events = SimEvents.load_from_h5(\"h5_test.hdf5\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47db2b2f",
   "metadata": {},
   "source": [
    "Now lets put our likelihood structure and data in together, along with a proposed source location:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "db0daf69",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:19.163030Z",
     "iopub.status.busy": "2024-03-22T09:57:19.162635Z",
     "iopub.status.idle": "2024-03-22T09:57:19.166601Z",
     "shell.execute_reply": "2024-03-22T09:57:19.166081Z"
    }
   },
   "outputs": [],
   "source": [
    "likelihood = PointSourceLikelihood(\n",
    "    spatial_likelihood,\n",
    "    energy_likelihood,\n",
    "    events.ra[events.periods[0]],\n",
    "    events.dec[events.periods[0]],\n",
    "    events.reco_energy[events.periods[0]],\n",
    "    events.ang_err[events.periods[0]],\n",
    "    source_coord,\n",
    "    which=\"both\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f33cc51",
   "metadata": {},
   "source": [
    "The likelihood will automatically select a declination band around the proposed source location. Because of the Gaussian spatial likelihood, neutrinos far from the source will have negligible contribution. We can control the width of this band with the optional argument `band_width_factor`. Let's see how many events are there in total, in the selected declination band and in vicinity of the proposed source:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f5463c07",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:19.168744Z",
     "iopub.status.busy": "2024-03-22T09:57:19.168548Z",
     "iopub.status.idle": "2024-03-22T09:57:19.172821Z",
     "shell.execute_reply": "2024-03-22T09:57:19.172296Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(204, 204, 35)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "likelihood.Ntot, likelihood.N, likelihood.Nprime"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d51787f2",
   "metadata": {},
   "source": [
    "We also note that the background likelihood is implemented automatically, for more information on the options here, check out the API docs. This is just a function of energy, with a constant factor to account for the isotropic directional likelihood."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "71e845aa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:19.175181Z",
     "iopub.status.busy": "2024-03-22T09:57:19.174782Z",
     "iopub.status.idle": "2024-03-22T09:57:19.691235Z",
     "shell.execute_reply": "2024-03-22T09:57:19.690500Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Background likelihood')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "energy = np.logspace(new_reco_bins[0], new_reco_bins[-1], num=1000, endpoint=False)\n",
    "ax.step(\n",
    "    energy,\n",
    "    energy_likelihood(energy, 3.7, np.full(energy.shape, np.deg2rad(30))),\n",
    "    label=f\"index 3.7\",\n",
    ")\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(r\"$\\log_{10}{(E_\\mathrm{reco} / \\mathrm{GeV})}$\")\n",
    "ax.set_ylabel(\"Background likelihood\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "998e8b94",
   "metadata": {},
   "source": [
    "## Point source search\n",
    "\n",
    "A point source search is usually carried out by defining the likelihood ratio of source and background hypotheses, then maximising this ratio as a function of $n_s$ and $\\gamma$. The log likelihood ratio evaluated at the maximum likelihood values is then reffered to as the *test statistic*.\n",
    "\n",
    "`icecube_tools` includes calculation of the test statistic, with optimisation performed by `iminuit`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5de695aa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:19.693798Z",
     "iopub.status.busy": "2024-03-22T09:57:19.693418Z",
     "iopub.status.idle": "2024-03-22T09:57:19.809882Z",
     "shell.execute_reply": "2024-03-22T09:57:19.809229Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "379.3319304294439"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "likelihood.get_test_statistic()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f5333307",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:19.812196Z",
     "iopub.status.busy": "2024-03-22T09:57:19.811997Z",
     "iopub.status.idle": "2024-03-22T09:57:19.815845Z",
     "shell.execute_reply": "2024-03-22T09:57:19.815341Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "likelihood._selected_energies.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9abf5817",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:19.818128Z",
     "iopub.status.busy": "2024-03-22T09:57:19.817771Z",
     "iopub.status.idle": "2024-03-22T09:57:19.821984Z",
     "shell.execute_reply": "2024-03-22T09:57:19.821345Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<ValueView ns=25.963806381794907 index=2.301173868863804 weight=0.0 index_astro=2.5 index_atmo=3.7>,\n",
       " <ErrorView ns=4.759496039069145 index=0.1908336385491083 weight=0.05 index_astro=0.1 index_atmo=0.1>)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "likelihood.m.values, likelihood.m.errors"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd49a168",
   "metadata": {},
   "source": [
    "To understand the significance of this results, we would have to calculate the test statistic for a large number of background-only simulations. These could then be used to calculate a p-value. Given there is a strong point source in the simulation we used, we can expect the test stastic to be lower if we remove the source events. Let's try this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c754c30e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:19.824428Z",
     "iopub.status.busy": "2024-03-22T09:57:19.824075Z",
     "iopub.status.idle": "2024-03-22T09:57:22.926083Z",
     "shell.execute_reply": "2024-03-22T09:57:22.925444Z"
    }
   },
   "outputs": [],
   "source": [
    "# Get all point source events\n",
    "ps_sel = events.source_label[events.periods[0]] == 1\n",
    "ntot_ps_events = len(np.where(ps_sel == True)[0])\n",
    "\n",
    "# Remove them one by one and find test statistic\n",
    "test_statistics = []\n",
    "for n_rm in range(ntot_ps_events):\n",
    "\n",
    "    i_keep = (ntot_ps_events - n_rm) - 1\n",
    "    ps_sel[np.where(ps_sel == True)[0][i_keep]] = False\n",
    "\n",
    "    new_data = {}\n",
    "    for key in events.keys:\n",
    "        new_data[key] = events.period(events._periods[0])[key][~ps_sel]\n",
    "\n",
    "    new_likelihood = PointSourceLikelihood(\n",
    "        spatial_likelihood,\n",
    "        energy_likelihood,\n",
    "        new_data[\"ra\"],\n",
    "        new_data[\"dec\"],\n",
    "        new_data[\"reco_energy\"],\n",
    "        new_data[\"ang_err\"],\n",
    "        source_coord,\n",
    "        which=\"both\",\n",
    "    )\n",
    "    new_likelihood._bg_energy_likelihood = None\n",
    "    test_statistics.append(new_likelihood.get_test_statistic())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "16a8a71c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:22.928974Z",
     "iopub.status.busy": "2024-03-22T09:57:22.928580Z",
     "iopub.status.idle": "2024-03-22T09:57:23.074674Z",
     "shell.execute_reply": "2024-03-22T09:57:23.074065Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Test statistic value')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot([_ for _ in range(ntot_ps_events)], test_statistics)\n",
    "ax.set_xlabel(\"Number of point source events in dataset\")\n",
    "ax.set_ylabel(\"Test statistic value\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "26d7e379",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:23.077161Z",
     "iopub.status.busy": "2024-03-22T09:57:23.076767Z",
     "iopub.status.idle": "2024-03-22T09:57:23.081046Z",
     "shell.execute_reply": "2024-03-22T09:57:23.080393Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.all(np.diff(test_statistics) > 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d91766e0",
   "metadata": {},
   "source": [
    "So the more neutrinos are seen from a source, the easier that source is to detect.\n",
    "\n",
    "Let's have a look at the minuit object returned by `_minimize()`. In case something is off with the fit, we can use it as a starting point for debugging."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7567b61b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:23.083537Z",
     "iopub.status.busy": "2024-03-22T09:57:23.083157Z",
     "iopub.status.idle": "2024-03-22T09:57:23.195482Z",
     "shell.execute_reply": "2024-03-22T09:57:23.194831Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "┌─────────────────────────────────────────────────────────────────────────┐\n",
      "│                                Migrad                                   │\n",
      "├──────────────────────────────────┬──────────────────────────────────────┤\n",
      "│ FCN = -189.7                     │              Nfcn = 47               │\n",
      "│ EDM = 1.25e-06 (Goal: 0.0001)    │            time = 0.1 sec            │\n",
      "├──────────────────────────────────┼──────────────────────────────────────┤\n",
      "│          Valid Minimum           │   Below EDM threshold (goal x 10)    │\n",
      "├──────────────────────────────────┼──────────────────────────────────────┤\n",
      "│      No parameters at limit      │           Below call limit           │\n",
      "├──────────────────────────────────┼──────────────────────────────────────┤\n",
      "│             Hesse ok             │         Covariance accurate          │\n",
      "└──────────────────────────────────┴──────────────────────────────────────┘\n",
      "┌───┬─────────────┬───────────┬───────────┬────────────┬────────────┬─────────┬─────────┬───────┐\n",
      "│   │ Name        │   Value   │ Hesse Err │ Minos Err- │ Minos Err+ │ Limit-  │ Limit+  │ Fixed │\n",
      "├───┼─────────────┼───────────┼───────────┼────────────┼────────────┼─────────┼─────────┼───────┤\n",
      "│ 0 │ ns          │    26     │     5     │            │            │    0    │   204   │       │\n",
      "│ 1 │ index       │   2.30    │   0.19    │            │            │   1.5   │   4.5   │       │\n",
      "│ 2 │ weight      │   0.00    │   0.05    │            │            │    0    │    1    │  yes  │\n",
      "│ 3 │ index_astro │    2.5    │    0.1    │            │            │   1.5   │   4.5   │  yes  │\n",
      "│ 4 │ index_atmo  │    3.7    │    0.1    │            │            │   1.5   │   4.5   │  yes  │\n",
      "└───┴─────────────┴───────────┴───────────┴────────────┴────────────┴─────────┴─────────┴───────┘\n",
      "┌─────────────┬─────────────────────────────────────────────────────────────┐\n",
      "│             │          ns       index      weight index_astro  index_atmo │\n",
      "├─────────────┼─────────────────────────────────────────────────────────────┤\n",
      "│          ns │        22.7        0.00           0           0           0 │\n",
      "│       index │        0.00      0.0367        0.00        0.00        0.00 │\n",
      "│      weight │           0        0.00           0           0           0 │\n",
      "│ index_astro │           0        0.00           0           0           0 │\n",
      "│  index_atmo │           0        0.00           0           0           0 │\n",
      "└─────────────┴─────────────────────────────────────────────────────────────┘\n"
     ]
    }
   ],
   "source": [
    "m = likelihood._minimize()\n",
    "print(m)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "983b704e",
   "metadata": {},
   "source": [
    "We can also draw the likelihood profiles for `ns` and `index` and compare to the inputted values (20 source events and an index of 2.5, cf. the simulation notebook)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "09ed4f35",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:23.197994Z",
     "iopub.status.busy": "2024-03-22T09:57:23.197632Z",
     "iopub.status.idle": "2024-03-22T09:57:23.567561Z",
     "shell.execute_reply": "2024-03-22T09:57:23.566872Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = m.draw_profile(\"ns\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7ff91c44",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:23.570088Z",
     "iopub.status.busy": "2024-03-22T09:57:23.569709Z",
     "iopub.status.idle": "2024-03-22T09:57:23.574190Z",
     "shell.execute_reply": "2024-03-22T09:57:23.573561Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.nonzero(events.source_label[\"IC86_II\"] == 1)[0].size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cd53ebfc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:23.576549Z",
     "iopub.status.busy": "2024-03-22T09:57:23.576113Z",
     "iopub.status.idle": "2024-03-22T09:57:23.964634Z",
     "shell.execute_reply": "2024-03-22T09:57:23.963997Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = m.draw_profile(\n",
    "    \"index\",\n",
    "    bound=(\n",
    "        likelihood._energy_likelihood._min_index,\n",
    "        likelihood._energy_likelihood._max_index,\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9006008",
   "metadata": {},
   "source": [
    "And finally have a look at the 2d likelihood profile."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7a82276b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:23.967318Z",
     "iopub.status.busy": "2024-03-22T09:57:23.966904Z",
     "iopub.status.idle": "2024-03-22T09:57:29.861592Z",
     "shell.execute_reply": "2024-03-22T09:57:29.860948Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = m.draw_contour(\"index\", \"ns\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f3e2d0a9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:29.864548Z",
     "iopub.status.busy": "2024-03-22T09:57:29.864088Z",
     "iopub.status.idle": "2024-03-22T09:57:30.302638Z",
     "shell.execute_reply": "2024-03-22T09:57:30.302088Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'ns')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 960x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "index = np.arange(1.7, 3.4, step=0.2)\n",
    "index_pl = np.arange(1.6, 3.5, step=0.2)\n",
    "ns_pl = np.arange(14.0, 36, step=2.0)\n",
    "ns = np.arange(15, 35, step=2.0)\n",
    "ii, nn = np.meshgrid(index, ns, indexing=\"ij\")\n",
    "ll = np.zeros(ii.flatten().shape)\n",
    "\n",
    "for c, (i, n) in enumerate(zip(ii.flatten(), nn.flatten())):\n",
    "    ll[c] = likelihood._func_to_minimize(n, i)\n",
    "\n",
    "fig, ax = plt.subplots(dpi=150)\n",
    "\n",
    "pcol = ax.pcolor(index_pl, ns_pl, ll.reshape(ii.shape).T)\n",
    "pcol_ax = fig.colorbar(pcol)\n",
    "pcol_ax.set_label(\"negative loglike\")\n",
    "ax.set_xlabel(\"index\")\n",
    "ax.set_ylabel(\"ns\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b618a34",
   "metadata": {},
   "source": [
    "For the simulation-based energy likelihood used in the following, the profile o `index` has some edges. This is due to the interpolation done by the energy likelihood. We fed it simulation for discreet values of `index`. We cannot sensibly interpolate the likelihood of a given energy to any index, this leads to Heaviside-like discontinuities in the global (spatial + energy) likelihood. Instead, `PointSourceLikelihood` calculates the likelihood for the next simulated values of `index`, e.g. asking for an index 2.3 would lead to 2.0 and 2.5, and interpolate linearly between the resulting likelihoods. The precision of this method can be improved by providing simulations on a denser grid of spectral indices.\n",
    "\n",
    "The error provided by `migrad()` is unreasonably small."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0a809c96",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:30.305161Z",
     "iopub.status.busy": "2024-03-22T09:57:30.304787Z",
     "iopub.status.idle": "2024-03-22T09:57:30.323819Z",
     "shell.execute_reply": "2024-03-22T09:57:30.323191Z"
    },
    "lines_to_next_cell": 2
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data/p_IC86_II_index_1.5.h5\n",
      "data/p_IC86_II_index_1.7.h5\n",
      "data/p_IC86_II_index_1.9.h5\n",
      "data/p_IC86_II_index_2.1.h5\n",
      "data/p_IC86_II_index_2.3.h5\n",
      "data/p_IC86_II_index_2.5.h5\n",
      "data/p_IC86_II_index_2.7.h5\n",
      "data/p_IC86_II_index_2.9.h5\n",
      "data/p_IC86_II_index_3.1.h5\n",
      "data/p_IC86_II_index_3.3.h5\n",
      "data/p_IC86_II_index_3.5.h5\n",
      "data/p_IC86_II_index_3.7.h5\n",
      "data/p_IC86_II_index_3.9.h5\n"
     ]
    }
   ],
   "source": [
    "energy_likelihood = MarginalisedEnergyLikelihood2021(\n",
    "    np.round(np.arange(1.5, 4.1, 0.2), decimals=1), \"data\", \"p_IC86_II\", np.deg2rad(30)\n",
    ")\n",
    "energy_likelihood._min_index = 1.55\n",
    "energy_likelihood._max_index = 3.85\n",
    "likelihood = PointSourceLikelihood(\n",
    "    spatial_likelihood,\n",
    "    energy_likelihood,\n",
    "    events.ra[events.periods[0]],\n",
    "    events.dec[events.periods[0]],\n",
    "    events.reco_energy[events.periods[0]],\n",
    "    events.ang_err[events.periods[0]],\n",
    "    source_coord,\n",
    "    cosz_bins=np.linspace(-1, 1, num=51),\n",
    ")\n",
    "likelihood._bg_index = 3.7\n",
    "likelihood._bg_energy_likelihood = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "1110a16e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:30.326282Z",
     "iopub.status.busy": "2024-03-22T09:57:30.325904Z",
     "iopub.status.idle": "2024-03-22T09:57:30.364702Z",
     "shell.execute_reply": "2024-03-22T09:57:30.364081Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "429.37018357983"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "likelihood.get_test_statistic()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b8b5dbf6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:30.367224Z",
     "iopub.status.busy": "2024-03-22T09:57:30.366802Z",
     "iopub.status.idle": "2024-03-22T09:57:30.404278Z",
     "shell.execute_reply": "2024-03-22T09:57:30.403647Z"
    }
   },
   "outputs": [],
   "source": [
    "m = likelihood._minimize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "76fe25f1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:30.406807Z",
     "iopub.status.busy": "2024-03-22T09:57:30.406446Z",
     "iopub.status.idle": "2024-03-22T09:57:30.600273Z",
     "shell.execute_reply": "2024-03-22T09:57:30.599645Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = m.draw_profile(\"ns\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1150ea3f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:30.602687Z",
     "iopub.status.busy": "2024-03-22T09:57:30.602315Z",
     "iopub.status.idle": "2024-03-22T09:57:30.800816Z",
     "shell.execute_reply": "2024-03-22T09:57:30.800235Z"
    },
    "lines_to_next_cell": 2
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'index = 2.3 - 0.2 + 0.2')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Do this because for this interpolated function minuit can't compute reliable errors\n",
    "index, llh = m.draw_profile(\n",
    "    \"index\",\n",
    "    bound=(\n",
    "        likelihood._energy_likelihood._min_index,\n",
    "        likelihood._energy_likelihood._max_index,\n",
    "    ),\n",
    ")\n",
    "\n",
    "lower_lim = np.interp(\n",
    "    llh.min() + 0.5,\n",
    "    np.flip(llh[: np.nonzero(llh == llh.min())[0][0]]),\n",
    "    np.flip(index[: np.nonzero(llh == llh.min())[0][0]]),\n",
    ")\n",
    "upper_lim = np.interp(\n",
    "    llh.min() + 0.5,\n",
    "    llh[np.nonzero(llh == llh.min())[0][0] :],\n",
    "    index[np.nonzero(llh == llh.min())[0][0] :],\n",
    ")\n",
    "lims = plt.ylim()\n",
    "plt.fill_betweenx(\n",
    "    [lims[0] - 1, lims[1] + 1], lower_lim, upper_lim, alpha=0.4, color=\"grey\"\n",
    ")\n",
    "plt.ylim(lims)\n",
    "plt.title(\n",
    "    f\"index = {m.values['index']:.1f} - {m.values['index']-lower_lim:.1f} + {abs(m.values['index']-upper_lim):.1f}\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39826c90",
   "metadata": {},
   "source": [
    "# Time dependent point source analysis\n",
    "\n",
    "Encompassing multiple data seasons, although shown only for one (the same as above), uses a single `ns`, which is distributed among the seasons with the number of expected events for `gamma` and the provided observational times (`times`) as relative weight."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "290dac32",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:30.803394Z",
     "iopub.status.busy": "2024-03-22T09:57:30.803011Z",
     "iopub.status.idle": "2024-03-22T09:57:31.831332Z",
     "shell.execute_reply": "2024-03-22T09:57:31.830637Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th colspan=\"2\" style=\"text-align:center\" title=\"Minimizer\"> Migrad </th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"text-align:left\" title=\"Minimum value of function\"> FCN = -178.1 </td>\n",
       "        <td style=\"text-align:center\" title=\"Total number of function and (optional) gradient evaluations\"> Nfcn = 61 </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"text-align:left\" title=\"Estimated distance to minimum and goal\"> EDM = 1.47e-07 (Goal: 0.0001) </td>\n",
       "        <td style=\"text-align:center\" title=\"Total run time of algorithms\"> time = 0.2 sec </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"text-align:center;background-color:#92CCA6;color:black\"> Valid Minimum </td>\n",
       "        <td style=\"text-align:center;background-color:#92CCA6;color:black\"> Below EDM threshold (goal x 10) </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"text-align:center;background-color:#92CCA6;color:black\"> No parameters at limit </td>\n",
       "        <td style=\"text-align:center;background-color:#92CCA6;color:black\"> Below call limit </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"text-align:center;background-color:#92CCA6;color:black\"> Hesse ok </td>\n",
       "        <td style=\"text-align:center;background-color:#92CCA6;color:black\"> Covariance accurate </td>\n",
       "    </tr>\n",
       "</table><table>\n",
       "    <tr>\n",
       "        <td></td>\n",
       "        <th title=\"Variable name\"> Name </th>\n",
       "        <th title=\"Value of parameter\"> Value </th>\n",
       "        <th title=\"Hesse error\"> Hesse Error </th>\n",
       "        <th title=\"Minos lower error\"> Minos Error- </th>\n",
       "        <th title=\"Minos upper error\"> Minos Error+ </th>\n",
       "        <th title=\"Lower limit of the parameter\"> Limit- </th>\n",
       "        <th title=\"Upper limit of the parameter\"> Limit+ </th>\n",
       "        <th title=\"Is the parameter fixed in the fit\"> Fixed </th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> 0 </th>\n",
       "        <td> ns </td>\n",
       "        <td> 26 </td>\n",
       "        <td> 5 </td>\n",
       "        <td>  </td>\n",
       "        <td>  </td>\n",
       "        <td> 0 </td>\n",
       "        <td> 204 </td>\n",
       "        <td>  </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> 1 </th>\n",
       "        <td> index </td>\n",
       "        <td> 2.30 </td>\n",
       "        <td> 0.19 </td>\n",
       "        <td>  </td>\n",
       "        <td>  </td>\n",
       "        <td> 1.5 </td>\n",
       "        <td> 5 </td>\n",
       "        <td>  </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> 2 </th>\n",
       "        <td> weight </td>\n",
       "        <td> 0.0 </td>\n",
       "        <td> 0.1 </td>\n",
       "        <td>  </td>\n",
       "        <td>  </td>\n",
       "        <td> 0 </td>\n",
       "        <td> 1 </td>\n",
       "        <td> yes </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> 3 </th>\n",
       "        <td> index_astro </td>\n",
       "        <td> 2.5 </td>\n",
       "        <td> 0.1 </td>\n",
       "        <td>  </td>\n",
       "        <td>  </td>\n",
       "        <td> 1.5 </td>\n",
       "        <td> 5 </td>\n",
       "        <td> yes </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> 4 </th>\n",
       "        <td> index_atmo </td>\n",
       "        <td> 3.7 </td>\n",
       "        <td> 0.1 </td>\n",
       "        <td>  </td>\n",
       "        <td>  </td>\n",
       "        <td> 1.5 </td>\n",
       "        <td> 5 </td>\n",
       "        <td> yes </td>\n",
       "    </tr>\n",
       "</table><table>\n",
       "    <tr>\n",
       "        <td></td>\n",
       "        <th> ns </th>\n",
       "        <th> index </th>\n",
       "        <th> weight </th>\n",
       "        <th> index_astro </th>\n",
       "        <th> index_atmo </th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> ns </th>\n",
       "        <td> 22.7 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0.00 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> index </th>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0.00 </td>\n",
       "        <td> 0.0367 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0.00 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0.00 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0.00 </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> weight </th>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0.00 </td>\n",
       "        <td> 0 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> index_astro </th>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0.00 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "        <td> 0 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> index_atmo </th>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0.00 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "        <td style=\"background-color:rgb(250,250,250);color:black\"> 0 </td>\n",
       "        <td> 0 </td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "┌─────────────────────────────────────────────────────────────────────────┐\n",
       "│                                Migrad                                   │\n",
       "├──────────────────────────────────┬──────────────────────────────────────┤\n",
       "│ FCN = -178.1                     │              Nfcn = 61               │\n",
       "│ EDM = 1.47e-07 (Goal: 0.0001)    │            time = 0.2 sec            │\n",
       "├──────────────────────────────────┼──────────────────────────────────────┤\n",
       "│          Valid Minimum           │   Below EDM threshold (goal x 10)    │\n",
       "├──────────────────────────────────┼──────────────────────────────────────┤\n",
       "│      No parameters at limit      │           Below call limit           │\n",
       "├──────────────────────────────────┼──────────────────────────────────────┤\n",
       "│             Hesse ok             │         Covariance accurate          │\n",
       "└──────────────────────────────────┴──────────────────────────────────────┘\n",
       "┌───┬─────────────┬───────────┬───────────┬────────────┬────────────┬─────────┬─────────┬───────┐\n",
       "│   │ Name        │   Value   │ Hesse Err │ Minos Err- │ Minos Err+ │ Limit-  │ Limit+  │ Fixed │\n",
       "├───┼─────────────┼───────────┼───────────┼────────────┼────────────┼─────────┼─────────┼───────┤\n",
       "│ 0 │ ns          │    26     │     5     │            │            │    0    │   204   │       │\n",
       "│ 1 │ index       │   2.30    │   0.19    │            │            │   1.5   │    5    │       │\n",
       "│ 2 │ weight      │    0.0    │    0.1    │            │            │    0    │    1    │  yes  │\n",
       "│ 3 │ index_astro │    2.5    │    0.1    │            │            │   1.5   │    5    │  yes  │\n",
       "│ 4 │ index_atmo  │    3.7    │    0.1    │            │            │   1.5   │    5    │  yes  │\n",
       "└───┴─────────────┴───────────┴───────────┴────────────┴────────────┴─────────┴─────────┴───────┘\n",
       "┌─────────────┬─────────────────────────────────────────────────────────────┐\n",
       "│             │          ns       index      weight index_astro  index_atmo │\n",
       "├─────────────┼─────────────────────────────────────────────────────────────┤\n",
       "│          ns │        22.7        0.00           0           0           0 │\n",
       "│       index │        0.00      0.0367        0.00        0.00        0.00 │\n",
       "│      weight │           0        0.00           0           0           0 │\n",
       "│ index_astro │           0        0.00           0           0           0 │\n",
       "│  index_atmo │           0        0.00           0           0           0 │\n",
       "└─────────────┴─────────────────────────────────────────────────────────────┘"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "events = SimEvents.load_from_h5(\"h5_test.hdf5\")\n",
    "source_coords = (np.pi, np.deg2rad(30))\n",
    "# energy_likelihood = MarginalisedIntegratedEnergyLikelihood(irf, aeff, new_reco_bins)\n",
    "# index_list = list(np.arange(1.5, 4.25, 0.25))\n",
    "tllh = TimeDependentPointSourceLikelihood(\n",
    "    source_coords,\n",
    "    [\"IC86_II\"],\n",
    "    events.ra,\n",
    "    events.dec,\n",
    "    events.reco_energy,\n",
    "    events.ang_err,\n",
    "    which=\"both\",\n",
    "    times={\"IC86_II\": 1},\n",
    "    sigma=2,\n",
    "    band_width_factor=5,\n",
    ")\n",
    "\n",
    "m = tllh._minimize()\n",
    "\n",
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a88e6276",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:31.834009Z",
     "iopub.status.busy": "2024-03-22T09:57:31.833555Z",
     "iopub.status.idle": "2024-03-22T09:57:32.264901Z",
     "shell.execute_reply": "2024-03-22T09:57:32.264276Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = m.draw_profile(\"index\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "f50c0bcb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:32.267505Z",
     "iopub.status.busy": "2024-03-22T09:57:32.267121Z",
     "iopub.status.idle": "2024-03-22T09:57:32.680529Z",
     "shell.execute_reply": "2024-03-22T09:57:32.679872Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = m.draw_profile(\"ns\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da2f88ae",
   "metadata": {},
   "source": [
    "There is also a method to use only the events within the selected declination band and their energy to fit the background index. Default setting is one background index (`index_atmo`), using two at once does not lead to a converging fit right now."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e833f4f8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:32.683100Z",
     "iopub.status.busy": "2024-03-22T09:57:32.682687Z",
     "iopub.status.idle": "2024-03-22T09:57:32.703511Z",
     "shell.execute_reply": "2024-03-22T09:57:32.702984Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <tr>\n",
       "        <th colspan=\"2\" style=\"text-align:center\" title=\"Minimizer\"> Migrad </th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"text-align:left\" title=\"Minimum value of function\"> FCN = 470.2 </td>\n",
       "        <td style=\"text-align:center\" title=\"Total number of function and (optional) gradient evaluations\"> Nfcn = 76 </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"text-align:left\" title=\"Estimated distance to minimum and goal\"> EDM = 0 (Goal: 0.0001) </td>\n",
       "        <td style=\"text-align:center\" title=\"Total run time of algorithms\">  </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"text-align:center;background-color:#c15ef7;color:black\"> INVALID Minimum </td>\n",
       "        <td style=\"text-align:center;background-color:#92CCA6;color:black\"> Below EDM threshold (goal x 10) </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"text-align:center;background-color:#92CCA6;color:black\"> No parameters at limit </td>\n",
       "        <td style=\"text-align:center;background-color:#92CCA6;color:black\"> Below call limit </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"text-align:center;background-color:#c15ef7;color:black\"> Hesse FAILED </td>\n",
       "        <td style=\"text-align:center;background-color:#c15ef7;color:black\"> Covariance NOT pos. def. </td>\n",
       "    </tr>\n",
       "</table><table>\n",
       "    <tr>\n",
       "        <td></td>\n",
       "        <th title=\"Variable name\"> Name </th>\n",
       "        <th title=\"Value of parameter\"> Value </th>\n",
       "        <th title=\"Hesse error\"> Hesse Error </th>\n",
       "        <th title=\"Minos lower error\"> Minos Error- </th>\n",
       "        <th title=\"Minos upper error\"> Minos Error+ </th>\n",
       "        <th title=\"Lower limit of the parameter\"> Limit- </th>\n",
       "        <th title=\"Upper limit of the parameter\"> Limit+ </th>\n",
       "        <th title=\"Is the parameter fixed in the fit\"> Fixed </th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> 0 </th>\n",
       "        <td> weight </td>\n",
       "        <td> 0.0 </td>\n",
       "        <td> 0.1 </td>\n",
       "        <td>  </td>\n",
       "        <td>  </td>\n",
       "        <td> 0 </td>\n",
       "        <td> 1 </td>\n",
       "        <td> yes </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> 1 </th>\n",
       "        <td> index_astro </td>\n",
       "        <td> 2.5 </td>\n",
       "        <td> 0.1 </td>\n",
       "        <td>  </td>\n",
       "        <td>  </td>\n",
       "        <td> 1.5 </td>\n",
       "        <td> 5 </td>\n",
       "        <td> yes </td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <th> 2 </th>\n",
       "        <td> index_atmo </td>\n",
       "        <td> 3.3 </td>\n",
       "        <td> 0.0 </td>\n",
       "        <td>  </td>\n",
       "        <td>  </td>\n",
       "        <td> 1.5 </td>\n",
       "        <td> 5 </td>\n",
       "        <td>  </td>\n",
       "    </tr>\n",
       "</table>"
      ],
      "text/plain": [
       "┌─────────────────────────────────────────────────────────────────────────┐\n",
       "│                                Migrad                                   │\n",
       "├──────────────────────────────────┬──────────────────────────────────────┤\n",
       "│ FCN = 470.2                      │              Nfcn = 76               │\n",
       "│ EDM = 0 (Goal: 0.0001)           │                                      │\n",
       "├──────────────────────────────────┼──────────────────────────────────────┤\n",
       "│         INVALID Minimum          │   Below EDM threshold (goal x 10)    │\n",
       "├──────────────────────────────────┼──────────────────────────────────────┤\n",
       "│      No parameters at limit      │           Below call limit           │\n",
       "├──────────────────────────────────┼──────────────────────────────────────┤\n",
       "│           Hesse FAILED           │       Covariance NOT pos. def.       │\n",
       "└──────────────────────────────────┴──────────────────────────────────────┘\n",
       "┌───┬─────────────┬───────────┬───────────┬────────────┬────────────┬─────────┬─────────┬───────┐\n",
       "│   │ Name        │   Value   │ Hesse Err │ Minos Err- │ Minos Err+ │ Limit-  │ Limit+  │ Fixed │\n",
       "├───┼─────────────┼───────────┼───────────┼────────────┼────────────┼─────────┼─────────┼───────┤\n",
       "│ 0 │ weight      │    0.0    │    0.1    │            │            │    0    │    1    │  yes  │\n",
       "│ 1 │ index_astro │    2.5    │    0.1    │            │            │   1.5   │    5    │  yes  │\n",
       "│ 2 │ index_atmo  │    3.3    │    0.0    │            │            │   1.5   │    5    │       │\n",
       "└───┴─────────────┴───────────┴───────────┴────────────┴────────────┴─────────┴─────────┴───────┘"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tllh._minimize_bg()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "a8e1f95f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-22T09:57:32.705872Z",
     "iopub.status.busy": "2024-03-22T09:57:32.705480Z",
     "iopub.status.idle": "2024-03-22T09:57:32.849939Z",
     "shell.execute_reply": "2024-03-22T09:57:32.849310Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = tllh.m.draw_profile(\"index_atmo\", bound=(1.6, 3.9))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d44664fd",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "icecube_dev",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}