{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3c2455f3",
   "metadata": {},
   "source": [
    "# Detector model interface\n",
    "\n",
    "In addition to the neutrino data itself, the IceCube collaboration provides some information about the detector that can be useful to construct simple simulations and fits. For example, the effective area is needed to connect between incident neutrino fluxes and expected number of events in the detector.\n",
    "\n",
    "\n",
    "`icecube_tools` also provides an quick interface to loading and working with such information. This is a work in progress and only certain datasets are currently implemented, such as the ones demonstrated below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "808c847f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:34:58.298992Z",
     "iopub.status.busy": "2024-11-08T10:34:58.298786Z",
     "iopub.status.idle": "2024-11-08T10:35:00.092313Z",
     "shell.execute_reply": "2024-11-08T10:35:00.091566Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from matplotlib.colors import LogNorm\n",
    "\n",
    "from icecube_tools.utils.data import IceCubeData\n",
    "from icecube_tools.detector.detector import IceCube, TimeDependentIceCube"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92924e3c",
   "metadata": {},
   "source": [
    "The `IceCubeData` class can be used for a quick check of the available datasets on the IceCube website."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c0b56179",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:00.094991Z",
     "iopub.status.busy": "2024-11-08T10:35:00.094768Z",
     "iopub.status.idle": "2024-11-08T10:35:00.098707Z",
     "shell.execute_reply": "2024-11-08T10:35:00.098210Z"
    }
   },
   "outputs": [],
   "source": [
    "my_data = IceCubeData()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fbca2e8",
   "metadata": {},
   "source": [
    "## Effective area, angular resolution and energy resolution of 10 year data\n",
    "\n",
    "We can now use the date string to identify certain datasets. Let's say we want to use the effective area and angular resolution from the `20210126` dataset. If you don't already have the dataset downloaded, `icecube_tools` will do this for you automatically. This 10 year data release provides more detailed IRF data.\n",
    "\n",
    "We restrict our examples to the Northern hemisphere.\n",
    "\n",
    "The simpler, earlier versions are explained afterwards.\n",
    "\n",
    "The format of the effective area has not changed, though.\n",
    "\n",
    "\n",
    "For this latest data set, we have different detector configurations available, as they changed through time (the detector was expanded). We can invoke a chosen configuration throught the second argument in `EffectiveArea.from_dataset()` for this particular data set only."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2cb735ac",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:00.100553Z",
     "iopub.status.busy": "2024-11-08T10:35:00.100355Z",
     "iopub.status.idle": "2024-11-08T10:35:00.103395Z",
     "shell.execute_reply": "2024-11-08T10:35:00.102874Z"
    }
   },
   "outputs": [],
   "source": [
    "from icecube_tools.detector.r2021 import R2021IRF\n",
    "from icecube_tools.detector.effective_area import EffectiveArea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "225776ac",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:00.105099Z",
     "iopub.status.busy": "2024-11-08T10:35:00.104908Z",
     "iopub.status.idle": "2024-11-08T10:35:31.766083Z",
     "shell.execute_reply": "2024-11-08T10:35:31.765355Z"
    }
   },
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      "20210126: 29441642it [00:15, 1471366.40it/s]"
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      "20210126: 29753344it [00:15, 1138760.64it/s]"
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      "20210126: 30113786it [00:15, 1670810.72it/s]"
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      "\r",
      "20210126: 31670266it [00:16, 3158498.05it/s]"
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      "20210126: 32489466it [00:16, 3509114.46it/s]"
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      "\r",
      "20210126: 32890488it [00:16, 3649591.72it/s]"
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     "name": "stderr",
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      "\r",
      "20210126: 33284090it [00:16, 3665614.06it/s]"
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    },
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     "name": "stderr",
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      "\r",
      "20210126: 33669120it [00:16, 3020065.89it/s]"
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     "name": "stderr",
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      "\r",
      "20210126: 34045922it [00:16, 3160029.03it/s]"
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     "name": "stderr",
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      "\r",
      "20210126: 34406394it [00:16, 3231219.90it/s]"
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      "\r",
      "20210126: 34783226it [00:17, 3361603.49it/s]"
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    },
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     "name": "stderr",
     "output_type": "stream",
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      "\r",
      "20210126: 35160058it [00:17, 3473399.04it/s]"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "\r",
      "20210126: 35536890it [00:17, 3547179.32it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 35946490it [00:17, 3636542.57it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 36315136it [00:17, 3633229.04it/s]"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 36683370it [00:17, 2888626.72it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 37052410it [00:17, 3084113.43it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 37429248it [00:17, 3254349.06it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 37806074it [00:17, 3374168.90it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 38215674it [00:18, 3513062.28it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 38625274it [00:18, 3612285.29it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 39026688it [00:18, 3654334.88it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 39411706it [00:18, 3696912.22it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 39804522it [00:18, 3571697.27it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20210126: 39843820it [00:18, 2151653.52it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "my_aeff = EffectiveArea.from_dataset(\"20210126\", \"IC86_II\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f9dc910c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:31.768301Z",
     "iopub.status.busy": "2024-11-08T10:35:31.768088Z",
     "iopub.status.idle": "2024-11-08T10:35:32.444147Z",
     "shell.execute_reply": "2024-11-08T10:35:32.443416Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "h = ax.pcolor(\n",
    "    my_aeff.true_energy_bins, my_aeff.cos_zenith_bins, my_aeff.values.T, norm=LogNorm()\n",
    ")\n",
    "cbar = fig.colorbar(h)\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_xlim(1e2, 1e9)\n",
    "ax.set_xlabel(\"True energy [GeV]\")\n",
    "ax.set_ylabel(\"cos(zenith)\")\n",
    "cbar.set_label(\"Aeff [m$^2$]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf25db71",
   "metadata": {},
   "source": [
    "### Energy resolution\n",
    "\n",
    "Angular resolution depends on the energy resolution. The [paper](https://arxiv.org/pdf/2101.09836.pdf) accompaying the data release explains the dependency: For each bin of true energy and declination a certain amount of events is simulated. These are sorted first into bins of reconstructed energy. These are then reconstructed in terms of `PSF`(the kinematic angle between the incoming neutrino and the outgoing muon after a collision) and actual angular error. Data is given as fractional counts in the bin $(E_\\mathrm{reco}, \\mathrm{PSF}, \\mathrm{ang\\_err})$ of all counts in bin (E_\\mathrm{true}, \\delta). This is nothing but a histogram, corresponding to a probability of finding an event with given true energy and true declination: $p(E_\\mathrm{reco}, \\mathrm{PSF}, \\mathrm{ang\\_err} \\vert E_\\mathrm{true}, \\delta)$.\n",
    "\n",
    "We find the energy resolution, i.e. $p(E_\\mathrm{reco} \\vert E_\\mathrm{true}, \\delta)$, by summing over (marginalising over) all entries of $\\mathrm{PSF}, \\mathrm{ang\\_err}$ for the reconstructed energy we are interested in.\n",
    "\n",
    "The `R2021IRF()`class is able to do so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "73672088",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:32.446410Z",
     "iopub.status.busy": "2024-11-08T10:35:32.445981Z",
     "iopub.status.idle": "2024-11-08T10:35:33.531618Z",
     "shell.execute_reply": "2024-11-08T10:35:33.530947Z"
    }
   },
   "outputs": [],
   "source": [
    "irf = R2021IRF.from_period(\"IC86_II\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b5a6f728",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:33.534127Z",
     "iopub.status.busy": "2024-11-08T10:35:33.533646Z",
     "iopub.status.idle": "2024-11-08T10:35:33.712989Z",
     "shell.execute_reply": "2024-11-08T10:35:33.712312Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f16fd9738e0>"
      ]
     },
     "execution_count": 7,
     "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",
    "idx = [0, 3, 6, 9, 12]\n",
    "# plotting Ereco for different true energy bins, the declination bin here is always from +10 to +90 degrees.\n",
    "for i in idx:\n",
    "\n",
    "    x = np.linspace(*irf.reco_energy[i, 2].support(), num=1000)\n",
    "    ax.plot(x, irf.reco_energy[i, 2].pdf(x), label=irf.true_energy_bins[i])\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82164e4a",
   "metadata": {},
   "source": [
    "This should look like the Fig.4, left panel, of the mentioned paper, the y-axis is only scaled by a constant factor, corresponding to a properly normalised distribution. On this topic, it should be mentioned that the quantities distributed according to these histograms are the logarithms of reconstructed energy, PSF and angular uncertainty! Accordingly, logarithmic quantities are drawn as samples and only exponentiated for calculations and final data products."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc97b98c",
   "metadata": {},
   "source": [
    "### Etrue vs. Ereco\n",
    "\n",
    "Below, a colormap of the conditional probability $P(E_\\mathrm{reco} \\vert E_\\mathrm{true})$ is shown. It is normalised for each Etrue bin."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "21ae13de",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:33.715265Z",
     "iopub.status.busy": "2024-11-08T10:35:33.714841Z",
     "iopub.status.idle": "2024-11-08T10:35:33.718012Z",
     "shell.execute_reply": "2024-11-08T10:35:33.717467Z"
    }
   },
   "outputs": [],
   "source": [
    "etrue = irf.true_energy_bins\n",
    "ereco = np.linspace(1, 8, num=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bd255e2b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:33.719833Z",
     "iopub.status.busy": "2024-11-08T10:35:33.719628Z",
     "iopub.status.idle": "2024-11-08T10:35:33.725368Z",
     "shell.execute_reply": "2024-11-08T10:35:33.724872Z"
    }
   },
   "outputs": [],
   "source": [
    "vals = np.zeros((etrue.size - 1, ereco.size - 1))\n",
    "for c, et in enumerate(etrue[:-1]):\n",
    "    vals[c, :] = irf.reco_energy[c, 2].pdf(ereco[:-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7c6b2687",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:33.727183Z",
     "iopub.status.busy": "2024-11-08T10:35:33.726982Z",
     "iopub.status.idle": "2024-11-08T10:35:34.671618Z",
     "shell.execute_reply": "2024-11-08T10:35:34.670851Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "h = ax.pcolor(np.power(10, etrue), np.power(10, ereco), vals.T, norm=LogNorm())\n",
    "cbar = fig.colorbar(h)\n",
    "ax.set_xlim(1e2, 1e9)\n",
    "ax.set_ylim(1e1, 1e8)\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(\"True energy [GeV]\")\n",
    "ax.set_ylabel(\"Reconstructed energy [GeV]\")\n",
    "cbar.set_label(\"P(Ereco|Etrue)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a7aea03",
   "metadata": {},
   "source": [
    "### Angular resolution\n",
    "\n",
    "Now that we have the reconstructed energy for an event with some $E_\\mathrm{true}, \\delta$, we can proceed in finding the angular resolution.\n",
    "\n",
    "First, from the given \"history\" of the event, we sample the matching distribution/histogram of $\\mathrm{PSF}$, again by marginalising over the uninteresting quantities, in this case only $\\mathrm{ang\\_err}$. We thus sample a value of $\\mathrm{PSF}$, to whom a distribution of $\\mathrm{ang\\_err}$ belongs, which we subsequently sample. This is now to be understood as a cone of a given angular radius, within which the true arrival direction lies with a probability of 50%.\n",
    "\n",
    "For both steps, the histograms are created by `R2021IRF()` when instructed to do so: we pass a tuple of vectors (ra, dec) in radians and a vector of $\\log_{10}(E_\\mathrm{true})$ to the method `sample()`. Returned are sampled ra, dec (both in radians), angular error (68%, in degrees) and reconstructed energy in GeV."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "fc3a1b02",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:34.673724Z",
     "iopub.status.busy": "2024-11-08T10:35:34.673493Z",
     "iopub.status.idle": "2024-11-08T10:35:34.746996Z",
     "shell.execute_reply": "2024-11-08T10:35:34.746261Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([3.14460667, 3.1122957 , 3.1715669 , 3.12988768]),\n",
       " array([0.795381  , 0.80942401, 0.78207633, 0.7897252 ]),\n",
       " array([0.81314284, 1.18484801, 0.8403489 , 1.56147217]),\n",
       " array([ 638.4537496 , 1580.39481862,  985.08856794,  837.29002682]))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "irf.sample((np.full(4, np.pi), np.full(4, np.pi / 4)), np.full(4, 2))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f46baac",
   "metadata": {},
   "source": [
    "If you are interested in the actual distributions, they are accessible through the attributes `R2021IRF().reco_energy` (2d numpy array storing `scipy.stats.rv_histogram` instances) and `R2021IRF().maginal_pdf_psf` (a modified ditionary class instance, indexed by a chain of keys):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e99ae951",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:34.749082Z",
     "iopub.status.busy": "2024-11-08T10:35:34.748861Z",
     "iopub.status.idle": "2024-11-08T10:35:34.752895Z",
     "shell.execute_reply": "2024-11-08T10:35:34.752327Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-3.13065092 -2.86582289 -2.60084567 -2.33592241 -2.07109231 -1.80631897\n",
      " -1.54136215 -1.27646224 -1.01153023 -0.74666199 -0.48174935 -0.21688286\n",
      "  0.04805317  0.31281183  0.57772152  0.84267163  1.10754913  1.37235958\n",
      "  1.63728955  1.90222053  2.1670218 ]\n",
      "<scipy.stats._continuous_distns.rv_histogram object at 0x7f16fda70760>\n"
     ]
    }
   ],
   "source": [
    "etrue_bin = 0\n",
    "dec_bin = 2\n",
    "ereco_bin = 10\n",
    "print(irf.marginal_pdf_psf(etrue_bin, dec_bin, ereco_bin, \"bins\"))\n",
    "print(irf.marginal_pdf_psf(etrue_bin, dec_bin, ereco_bin, \"pdf\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c34571c",
   "metadata": {},
   "source": [
    "The same works for `marginal_pdf_angerr`. The entries are only created once the `sample()` method needs to. See the  class defintion of `ddict` in `icecube_tools.utils.data` for more details."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa159f9e",
   "metadata": {},
   "source": [
    "### Mean angular uncertainty\n",
    "\n",
    "We can find the mean angular uncertainty by sampling a large amount of events for different true energies, assuming that the average is sensibly defined as the average of logarithmic quantities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "58a25247",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:35:34.754853Z",
     "iopub.status.busy": "2024-11-08T10:35:34.754650Z",
     "iopub.status.idle": "2024-11-08T10:36:02.547197Z",
     "shell.execute_reply": "2024-11-08T10:36:02.546505Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'mean angular uncertainty [degrees]')"
      ]
     },
     "execution_count": 13,
     "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": [
    "num = 10000\n",
    "loge = irf.true_energy_bins\n",
    "mean_uncertainty = np.zeros(loge.shape)\n",
    "for c, e in enumerate(loge[:-1]):\n",
    "    _, _, samples, _ = irf.sample(\n",
    "        (np.full(num, np.pi), np.full(num, np.pi / 4)), np.full(num, e)\n",
    "    )\n",
    "    mean_uncertainty[c] = np.power(10, np.average(np.log10(samples)))\n",
    "mean_uncertainty[-1] = mean_uncertainty[-2]\n",
    "plt.step(loge, mean_uncertainty, where=\"post\")\n",
    "plt.xlabel(\"$\\log E_\\mathrm{true} / \\mathrm{GeV}$\")\n",
    "plt.ylabel(\"mean angular uncertainty [degrees]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e94a3ddb",
   "metadata": {},
   "source": [
    "## Constructing a detector\n",
    "\n",
    "A detector used for e.g. simulations can be constructed from angular/energy uncertainties and an effective area:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b7f71e0c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:02.549682Z",
     "iopub.status.busy": "2024-11-08T10:36:02.549164Z",
     "iopub.status.idle": "2024-11-08T10:36:02.552565Z",
     "shell.execute_reply": "2024-11-08T10:36:02.552008Z"
    }
   },
   "outputs": [],
   "source": [
    "detector = IceCube(my_aeff, irf, irf, \"IC86_II\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cb927b3",
   "metadata": {},
   "source": [
    "`irf = R2021IRF()` is used both as spatial and energy resolution, because it encompasses both types of information and inherits from both classes."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0157fbc4",
   "metadata": {},
   "source": [
    "## Time dependent detector\n",
    "\n",
    "We can construct a \"meta-detector\" spanning multiple data periods through the class `TimeDependentIceCube` from strings defining the data periods. Alternatively, a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6a4954ad",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:02.554537Z",
     "iopub.status.busy": "2024-11-08T10:36:02.554335Z",
     "iopub.status.idle": "2024-11-08T10:36:03.666924Z",
     "shell.execute_reply": "2024-11-08T10:36:03.666189Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/hostedtoolcache/Python/3.9.20/x64/lib/python3.9/site-packages/icecube_tools/detector/r2021.py:89: RuntimeWarning: divide by zero encountered in log10\n",
      "  self.dataset[:, 6:-1] = np.log10(self.dataset[:, 6:-1])\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Empty true energy bins at: [(0, 0), (1, 0)]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'IC86_I': <icecube_tools.detector.detector.IceCube at 0x7f16fd942670>,\n",
       " 'IC86_II': <icecube_tools.detector.detector.IceCube at 0x7f16fc450dc0>}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tic = TimeDependentIceCube.from_periods(\"IC86_I\", \"IC86_II\")\n",
    "tic.detectors"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9b35391",
   "metadata": {},
   "source": [
    "Available periods are"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2bb34611",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:03.669239Z",
     "iopub.status.busy": "2024-11-08T10:36:03.668838Z",
     "iopub.status.idle": "2024-11-08T10:36:03.672960Z",
     "shell.execute_reply": "2024-11-08T10:36:03.672466Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['IC40', 'IC59', 'IC79', 'IC86_I', 'IC86_II']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TimeDependentIceCube._available_periods"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c49c2cf",
   "metadata": {},
   "source": [
    "# Effective area, angular resolution and energy resolution of earlier releases\n",
    "\n",
    "Repeating the prodecure for the `20181018` dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e3e0fbfa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:03.675051Z",
     "iopub.status.busy": "2024-11-08T10:36:03.674614Z",
     "iopub.status.idle": "2024-11-08T10:36:03.677849Z",
     "shell.execute_reply": "2024-11-08T10:36:03.677178Z"
    }
   },
   "outputs": [],
   "source": [
    "from icecube_tools.detector.effective_area import EffectiveArea\n",
    "from icecube_tools.detector.energy_resolution import EnergyResolution\n",
    "from icecube_tools.detector.angular_resolution import AngularResolution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b89e77d7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:03.679725Z",
     "iopub.status.busy": "2024-11-08T10:36:03.679372Z",
     "iopub.status.idle": "2024-11-08T10:36:03.711713Z",
     "shell.execute_reply": "2024-11-08T10:36:03.711012Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/hostedtoolcache/Python/3.9.20/x64/lib/python3.9/site-packages/icecube_tools/detector/effective_area.py:379: FutureWarning: The 'delim_whitespace' keyword in pd.read_csv is deprecated and will be removed in a future version. Use ``sep='\\s+'`` instead\n",
      "  output = pd.read_csv(\n",
      "/opt/hostedtoolcache/Python/3.9.20/x64/lib/python3.9/site-packages/icecube_tools/detector/angular_resolution.py:111: FutureWarning: The 'delim_whitespace' keyword in pd.read_csv is deprecated and will be removed in a future version. Use ``sep='\\s+'`` instead\n",
      "  output = pd.read_csv(\n"
     ]
    }
   ],
   "source": [
    "my_aeff = EffectiveArea.from_dataset(\"20181018\")\n",
    "my_angres = AngularResolution.from_dataset(\"20181018\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "bd5f824b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:03.714280Z",
     "iopub.status.busy": "2024-11-08T10:36:03.713579Z",
     "iopub.status.idle": "2024-11-08T10:36:05.108776Z",
     "shell.execute_reply": "2024-11-08T10:36:05.108082Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "h = ax.pcolor(\n",
    "    my_aeff.true_energy_bins, my_aeff.cos_zenith_bins, my_aeff.values.T, norm=LogNorm()\n",
    ")\n",
    "cbar = fig.colorbar(h)\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_xlabel(\"True energy [GeV]\")\n",
    "ax.set_ylabel(\"cos(zenith)\")\n",
    "cbar.set_label(\"Aeff [m$^2$]\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a1b2324d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:05.110874Z",
     "iopub.status.busy": "2024-11-08T10:36:05.110650Z",
     "iopub.status.idle": "2024-11-08T10:36:05.427142Z",
     "shell.execute_reply": "2024-11-08T10:36:05.426417Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Mean angular error [deg]')"
      ]
     },
     "execution_count": 20,
     "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(my_angres.true_energy_values, my_angres.values)\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_xlabel(\"True energy [GeV]\")\n",
    "ax.set_ylabel(\"Mean angular error [deg]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d024d1c",
   "metadata": {},
   "source": [
    "We can also easily check what datasets are supported by the different detector information classes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6e7ad926",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:05.429387Z",
     "iopub.status.busy": "2024-11-08T10:36:05.428897Z",
     "iopub.status.idle": "2024-11-08T10:36:05.433411Z",
     "shell.execute_reply": "2024-11-08T10:36:05.432755Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['20131121', '20150820', '20181018', '20210126']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EffectiveArea.supported_datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8aa839e6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:05.435414Z",
     "iopub.status.busy": "2024-11-08T10:36:05.434967Z",
     "iopub.status.idle": "2024-11-08T10:36:05.439273Z",
     "shell.execute_reply": "2024-11-08T10:36:05.438620Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['20181018']"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AngularResolution.supported_datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9ff04af8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:05.441344Z",
     "iopub.status.busy": "2024-11-08T10:36:05.440913Z",
     "iopub.status.idle": "2024-11-08T10:36:05.444948Z",
     "shell.execute_reply": "2024-11-08T10:36:05.444334Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['20150820']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EnergyResolution.supported_datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40b95b31",
   "metadata": {},
   "source": [
    "If you would like to see some other datasets supported, please feel free to open an issue or contribute your own!\n",
    "\n",
    "\n",
    "For the `20150820` dataset, for which we also have the energy resolution available..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c30addce",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:05.446911Z",
     "iopub.status.busy": "2024-11-08T10:36:05.446535Z",
     "iopub.status.idle": "2024-11-08T10:36:19.150397Z",
     "shell.execute_reply": "2024-11-08T10:36:19.149599Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20150820: 0it [00:00, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20150820: 2097152it [00:00, 17270098.70it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20150820: 12582912it [00:00, 63485531.48it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20150820: 20971520it [00:00, 70997549.66it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20150820: 31457280it [00:00, 80862464.96it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20150820: 42991616it [00:00, 91388739.89it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "20150820: 43711022it [00:00, 79686826.45it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "my_aeff = EffectiveArea.from_dataset(\"20150820\")\n",
    "my_eres = EnergyResolution.from_dataset(\"20150820\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a64fd03b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:19.152642Z",
     "iopub.status.busy": "2024-11-08T10:36:19.152411Z",
     "iopub.status.idle": "2024-11-08T10:36:19.769541Z",
     "shell.execute_reply": "2024-11-08T10:36:19.768844Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "h = ax.pcolor(\n",
    "    my_aeff.true_energy_bins, my_aeff.cos_zenith_bins, my_aeff.values.T, norm=LogNorm()\n",
    ")\n",
    "cbar = fig.colorbar(h)\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_xlabel(\"True energy [GeV]\")\n",
    "ax.set_ylabel(\"cos(zenith)\")\n",
    "cbar.set_label(\"Aeff [m$^2$]\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "ac8fdddb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:19.771510Z",
     "iopub.status.busy": "2024-11-08T10:36:19.771294Z",
     "iopub.status.idle": "2024-11-08T10:36:21.662878Z",
     "shell.execute_reply": "2024-11-08T10:36:21.662149Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "h = ax.pcolor(\n",
    "    my_eres.true_energy_bins, my_eres.reco_energy_bins, my_eres.values.T, norm=LogNorm()\n",
    ")\n",
    "cbar = fig.colorbar(h)\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(\"True energy [GeV]\")\n",
    "ax.set_ylabel(\"Reconstructed energy [GeV]\")\n",
    "cbar.set_label(\"P(Ereco|Etrue)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b98f03e6",
   "metadata": {},
   "source": [
    "## Detector model\n",
    "\n",
    "We can bring together these properties to make a detector model that can be used for simulations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "af32126f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:21.665094Z",
     "iopub.status.busy": "2024-11-08T10:36:21.664661Z",
     "iopub.status.idle": "2024-11-08T10:36:21.667914Z",
     "shell.execute_reply": "2024-11-08T10:36:21.667377Z"
    }
   },
   "outputs": [],
   "source": [
    "from icecube_tools.detector.detector import IceCube"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "cbc72962",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-08T10:36:21.669902Z",
     "iopub.status.busy": "2024-11-08T10:36:21.669490Z",
     "iopub.status.idle": "2024-11-08T10:36:21.672322Z",
     "shell.execute_reply": "2024-11-08T10:36:21.671806Z"
    }
   },
   "outputs": [],
   "source": [
    "my_detector = IceCube(my_aeff, my_eres, my_angres)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7695a06d",
   "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": "3.9.20"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}