{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fitting for an extended source polarization with `LeakageLib`\n",
    "\n",
    "_Weights used:_\n",
    "* Spatial\n",
    "* Spectral\n",
    "\n",
    "This jupyter notebook fits for the polarization of an extended source, with a photon and particle background. Here, the source is a simulated 60 arcsecond-radius uniform disk, though because of the IXPE PSF, it appears wider in the IXPE data.\n",
    "\n",
    "The source is assumed to have constant polarization, though we provide guidance on variable polarization sources at the end."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[93m>>> PyXSPEC is not installed, you will no be able to use it.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import leakagelib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first step is to load the mock Moments data. We'll center it on pixel (300, 300), and cut to 280 arcseconds around that point. See the point source fit example for a description of these functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ">>> Reading (in memory) /opt/homebrew/anaconda3/lib/python3.12/site-packages/ixpeobssim/caldb/ixpe/xrt/bcf/vign/ixpe_d1_obssim20240101_vign_v013.fits...\n"
     ]
    }
   ],
   "source": [
    "# Load the extended source data\n",
    "datas = leakagelib.IXPEData.load_all_detectors_with_path(\"data\", \"extended\")\n",
    "\n",
    "for data in datas:\n",
    "    data.explicit_center(300,300)\n",
    "    data.retain(data.evt_energies > 2)\n",
    "    data.retain(data.evt_energies < 8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have to create a custom `Source` object to model where the source photons came from. This source object should not be blurred by the PSF; i.e. it should depict the source as seen by Chandra, not IXPE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pixel_size = 2.9729 # This is the size of the sky PSF pixels; use it for best results\n",
    "source_pixel_edges = np.arange(0, 280+pixel_size, pixel_size)\n",
    "source_pixel_edges = np.concatenate([-np.flip(source_pixel_edges)[:-1], source_pixel_edges])\n",
    "# source_pixel_edges now ranges from -280 to 280, centered on zero, and spaced by `pixel_size`\n",
    "source_pixel_centers = (source_pixel_edges[1:] + source_pixel_edges[:-1]) / 2\n",
    "\n",
    "xs, ys = np.meshgrid(source_pixel_centers, source_pixel_centers)\n",
    "image = (np.sqrt(xs**2 + ys**2) < 60).astype(float)\n",
    "\n",
    "source = leakagelib.Source(image, pixel_size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we give the source object to the fitter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "settings = leakagelib.FitSettings(datas)\n",
    "settings.add_source(source, \"src-ext\")\n",
    "settings.fix_flux(\"src-ext\", 1)\n",
    "settings.set_initial_qu(\"src-ext\", (0, 0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The background, spectral weights, and ROI are added in the same way as the previous fits."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ">>> Reading (in memory) /opt/homebrew/anaconda3/lib/python3.12/site-packages/ixpeobssim/caldb/ixpe/gpd/cpf/arf/ixpe_d1_obssim20240101_v013.arf...\n",
      ">>> Using cached xEffectiveArea object at /opt/homebrew/anaconda3/lib/python3.12/site-packages/ixpeobssim/caldb/ixpe/gpd/cpf/arf/ixpe_d1_obssim20240101_v013.arf...\n",
      "6393 events were cut for being outside the region of interest.\n"
     ]
    }
   ],
   "source": [
    "settings.add_background(\"bkg\")\n",
    "settings.set_initial_flux(\"bkg\", 0.1)\n",
    "settings.fix_qu(\"bkg\", (0, 0))\n",
    "\n",
    "settings.set_spectrum(\"bkg\", lambda e: e**-2.5)\n",
    "settings.set_spectrum(\"src-ext\", lambda e: e**-1.5)\n",
    "\n",
    "settings.apply_circular_roi(280)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's view what the sources look like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Data set extended DU 1 had no exposure map loaded. Please load an exposure map if you are fitting to events in the vignetted portion.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x900 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fitter = leakagelib.Fitter(settings)\n",
    "fitter.display_sources(data_pixel_size=8);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It appears that the blurred source does indeed match the data well. If you had loaded the IXPE exposure map, the edges of the ROI would be correspondingly dimmed (although the exposure map is rather flat within 280 arcsec).\n",
    "\n",
    "We can also view what the fitter thinks the data should look like, based on the starting parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jtd/Documents/research/ixpepl/code/leakagelib/src/leakagelib/ps_fit/fitter.py:197: RuntimeWarning: invalid value encountered in divide\n",
      "  pred /= counts\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fitter.plot(n_bins=40);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we perform the fit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FitResult:\n",
       "\tq (src-ext) = 0.4390 +/- 0.0732\n",
       "\tu (src-ext) = -0.0510 +/- 0.0729\n",
       "\tf (bkg) = 2.1649 +/- 0.0447\n",
       "\n",
       "Polarization:\n",
       "\tPD (src-ext): 0.4419 +/- 0.0732\n",
       "\tPA (src-ext): -3.3164 deg +/- 4.7291\n",
       "Likelihood 12022.660277209434, dof 16042\n",
       "Optimization terminated successfully."
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = fitter.fit()\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The true source polarization was q=0.5, u=0, which the fit agrees with. We can also check whether the best-fit image matches the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fitter.plot(result.best_params, n_bins=40);"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}