{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "
\n", "**This is a fixed-text formatted version of a Jupyter notebook.**\n", "\n", " You can contribute with your own notebooks in this\n", " [GitHub repository](https://github.com/gammapy/gammapy-extra/tree/master/notebooks).\n", "\n", "**Source files:**\n", "[image_fitting_with_sherpa.ipynb](../_static/notebooks/image_fitting_with_sherpa.ipynb) |\n", "[image_fitting_with_sherpa.py](../_static/notebooks/image_fitting_with_sherpa.py)\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# CTA 2D source fitting with Sherpa\n", "F. Acero & Y. Gallant\n", "October 2017" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Introduction\n", "\n", "Sherpa is the X-ray satellite Chandra modeling and fitting application. It enables the user to construct complex models from simple definitions and fit those models to data, using a variety of statistics and optimization methods. \n", "The issues of constraining the source position and morphology are common in X- and Gamma-ray astronomy. \n", "This notebook will show you how to apply Sherpa to CTA data.\n", "\n", "Here we will set up Sherpa to fit the counts map and loading the ancillary images for subsequent use. A relevant test statistic for data with Poisson fluctuations is the one proposed by Cash (1979). The simplex (or Nelder-Mead) fitting algorithm is a good compromise between efficiency and robustness. The source fit is best performed in pixel coordinates." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Read sky images\n", "The sky image that are loaded here have been prepared in a separated notebook. Here we start from those fits file and focus on the source fitting aspect.\n", "\n", "The info needed for sherpa are:\n", "- Count map\n", "- Background map\n", "- Exposure map\n", "- PSF map\n", "\n", "For info, the fits file are written in the following way in the Sky map generation notebook:\n", "\n", "```\n", "images['counts'] .write(\"G300-0_test_counts.fits\", clobber=True)\n", "images['exposure'] .write(\"G300-0_test_exposure.fits\", clobber=True)\n", "images['background'].write(\"G300-0_test_background.fits\", clobber=True)\n", "\n", "##As psf is an array of quantities we cannot use the images['psf'].write() function\n", "##all the other arrays do not have quantities. \n", "fits.writeto(\"G300-0_test_psf.fits\",images['psf'].data.value,overwrite=True)\n", "```\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "WARNING: imaging routines will not be available, \n", "failed to import sherpa.image.ds9_backend due to \n", "'RuntimeErr: DS9Win unusable: Could not find xpaget on your PATH'\n", "WARNING: failed to import WCS module; WCS routines will not be available\n", "WARNING: failed to import sherpa.astro.xspec; XSPEC models will not be available\n" ] } ], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "from gammapy.image import SkyImage\n", "from astropy.coordinates import SkyCoord\n", "import astropy.units as u\n", "from astropy.io import fits\n", "from astropy.wcs import WCS\n", "\n", "# You may see a Warning concerning XSPEC\n", "# As we will note use Xspec spectral models this warning is not important\n", "import sherpa.astro.ui as sh" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# Read the fits file to load them in a sherpa model\n", "hdr = fits.getheader(\"G300-0_test_counts.fits\")\n", "wcs = WCS(hdr)\n", "\n", "sh.set_stat(\"cash\")\n", "sh.set_method(\"simplex\")\n", "sh.load_image(\"G300-0_test_counts.fits\")\n", "sh.set_coord(\"logical\")\n", "\n", "sh.load_table_model(\"expo\", \"G300-0_test_exposure.fits\")\n", "sh.load_table_model(\"bkg\", \"G300-0_test_background.fits\")\n", "sh.load_psf(\"psf\", \"G300-0_test_psf.fits\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In principle one might first want to fit the background amplitude. However the background estimation method already yields the correct normalization, so we freeze the background amplitude to unity instead of adjusting it. The (smoothed) residuals from this background model are then computed and shown." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": 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r2vr6ihQmv3PuEs9XmI2iVvJXHjetfn6hkWbU+tAIS5+cq0SdYNrkCiJb7PeX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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sh.set_full_model(bkg)\n", "bkg.ampl = 1\n", "sh.freeze(bkg)\n", "\n", "data = sh.get_data_image().y - sh.get_model_image().y\n", "resid = SkyImage(data=data, wcs=wcs)\n", "\n", "resid_table = [] # Keep residual images in a list to show them later\n", "resid_smo6 = resid.smooth(radius = 6)\n", "resid_smo6.plot()\n", "resid_table.append(resid_smo6)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Find and fit the brightest source\n", "We then find the position of the maximum in the (smoothed) residuals map, and fit a (symmetrical) Gaussian source with that initial position:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47907.2\n", "Final fit statistic = 47503 at function evaluation 234\n", "Data points = 30000\n", "Degrees of freedom = 29998\n", "Change in statistic = 404.211\n", " g0.fwhm 6.43418 \n", " g0.ampl 0.400131 \n" ] } ], "source": [ "maxcoord = resid_smo6.lookup_max()\n", "maxpix = resid_smo6.wcs_skycoord_to_pixel(maxcoord[0])\n", "sh.set_full_model(bkg + psf(sh.gauss2d.g0) * expo) # creates g0 as a gauss2d instance\n", "g0.xpos = maxpix[0]\n", "g0.ypos = maxpix[1]\n", "sh.freeze(g0.xpos, g0.ypos) # fix the position in the initial fitting step\n", "\n", "expo.ampl = 1e-9 # fix exposure amplitude so that typical exposure is of order unity\n", "sh.freeze(expo)\n", "sh.thaw(g0.fwhm, g0.ampl) # in case frozen in a previous iteration\n", "\n", "g0.fwhm = 10 # give some reasonable initial values\n", "g0.ampl = maxcoord[1]\n", "sh.fit() # Performs the fit; this takes a little time." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Fit all parameters of this Gaussian component, fix them and re-compute the residuals map." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47503\n", "Final fit statistic = 47498.4 at function evaluation 354\n", "Data points = 30000\n", "Degrees of freedom = 29996\n", "Change in statistic = 4.57486\n", " g0.fwhm 6.33581 \n", " g0.xpos 41.9218 \n", " g0.ypos 81.3048 \n", " g0.ampl 0.417545 \n" ] }, { "data": { "image/png": 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P02YlqF+ghOGZbgLnUUvOU/7k8gpLCj7YwTSmMTK4XM0+yUu9ge6Z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\nH8PN+YKi9QUW6XR9M0RCXV3hcN3dpa6n8NJjWHutaL3vuh7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Y6HvlRaZpNPlm5zlwlMXU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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sh.thaw(g0.xpos, g0.ypos)\n", "sh.fit()\n", "sh.freeze(g0)\n", "\n", "data = sh.get_data_image().y - sh.get_model_image().y\n", "resid = SkyImage(data=data, wcs=wcs)\n", "\n", "resid_smo6 = resid.smooth(radius = 6)\n", "resid_smo6.show(vmin = -0.5, vmax = 1)\n", "resid_table.append(resid_smo6)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Iteratively find and fit additional sources\n", "Instantiate additional Gaussian components, and use them to iteratively fit sources, repeating the steps performed above for component g0. (The residuals map is shown after each additional source included in the model.) This takes some time..." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47498.4\n", "Final fit statistic = 47335 at function evaluation 269\n", "Data points = 30000\n", "Degrees of freedom = 29998\n", "Change in statistic = 163.402\n", " g1.fwhm 19.8613 \n", " g1.ampl 0.100529 \n", "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47335\n", "Final fit statistic = 47293.7 at function evaluation 394\n", "Data points = 30000\n", "Degrees of freedom = 29996\n", "Change in statistic = 41.3431\n", " g1.fwhm 19.9265 \n", " g1.xpos 67.2544 \n", " g1.ypos 69.3013 \n", " g1.ampl 0.116012 \n" ] }, { "data": { "image/png": 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SLhXgNHdPYYQWBjyVT973Y5RvhO/L7tPnE/F9MGbUVmo+S5b9Mw9+73OaW8zA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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47293.7\n", "Final fit statistic = 47185.5 at function evaluation 264\n", "Data points = 30000\n", "Degrees of freedom = 29998\n", "Change in statistic = 108.124\n", " g2.fwhm 6.20212 \n", " g2.ampl 0.393345 \n", "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47185.5\n", "Final fit statistic = 47182.5 at function evaluation 342\n", "Data points = 30000\n", "Degrees of freedom = 29996\n", "Change in statistic = 3.05173\n", " g2.fwhm 6.19309 \n", " g2.xpos 20.8274 \n", " g2.ypos 81.6413 \n", " g2.ampl 0.40001 \n" ] }, { "data": { "image/png": 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TGKEdA56XT16fY5RvhO/L7lPziegzGDNqe2o+S5b9Ow+u15zmFjOw3QJ3yHhq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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47182.5\n", "Final fit statistic = 47115 at function evaluation 275\n", "Data points = 30000\n", "Degrees of freedom = 29998\n", "Change in statistic = 67.4731\n", " g3.fwhm 6.43218 \n", " g3.ampl 0.235481 \n", "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47115\n", "Final fit statistic = 47114.3 at function evaluation 303\n", "Data points = 30000\n", "Degrees of freedom = 29996\n", "Change in statistic = 0.728928\n", " g3.fwhm 6.38175 \n", " g3.xpos 177.458 \n", " g3.ypos 80.2233 \n", " g3.ampl 0.239637 \n" ] }, { "data": { "image/png": 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VFRW3HLdKct/tTqU8JfH5t/LU9Sw5298K0i2yLY23vh3+/CCJrUuqaEpy91QU/46NaGdH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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47114.3\n", "Final fit statistic = 47086.6 at function evaluation 277\n", "Data points = 30000\n", "Degrees of freedom = 29998\n", "Change in statistic = 27.7341\n", " g4.fwhm 5.70151 \n", " g4.ampl 0.162191 \n", "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47086.6\n", "Final fit statistic = 47085.7 at function evaluation 304\n", "Data points = 30000\n", "Degrees of freedom = 29996\n", "Change in statistic = 0.898776\n", " g4.fwhm 5.94179 \n", " g4.xpos 135.942 \n", " g4.ypos 59.5875 \n", " g4.ampl 0.156213 \n" ] }, { "data": { "image/png": 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KiopbjlsluW+3p1Kekvj8W3nsepac7W8F6RbZlsZb3w5/vpfEliVVNCa5eyqKf8dGtIuj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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47085.7\n", "Final fit statistic = 47069 at function evaluation 262\n", "Data points = 30000\n", "Degrees of freedom = 29998\n", "Change in statistic = 16.6424\n", " g5.fwhm 2.82885 \n", " g5.ampl 0.52359 \n", "Dataset = 1\n", "Method = neldermead\n", "Statistic = cash\n", "Initial fit statistic = 47069\n", "Final fit statistic = 47068.9 at function evaluation 328\n", "Data points = 30000\n", "Degrees of freedom = 29996\n", "Change in statistic = 0.0749129\n", " g5.fwhm 2.82317 \n", " g5.xpos 76.1381 \n", " g5.ypos 73.1869 \n", " g5.ampl 0.524268 \n" ] }, { "data": { "image/png": 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aGPBUPnnfj1G+Eb4vu0+fT8T3wZRRW6n5LFn2zzz4vc9pbjEDl5fAXTKemuRu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\n2QqFl2p/bAEyPEya1gkIJ3j3W57LykOtdc8VOGX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lOPrTf1PO+YdSSpcA/gWGzK8/mnP+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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for i in range(1,6):\n", " sh.create_model_component('gauss2d', 'g' + str(i))\n", "\n", "gs = [g0, g1, g2, g3, g4, g5]\n", "sh.set_full_model(bkg + psf(g0+g1+g2+g3+g4+g5) * expo)\n", "\n", "for i in range(1, len(gs)) :\n", " gs[i].ampl = 0 # initialize components with fixed, zero amplitude\n", " sh.freeze(gs[i])\n", "\n", "for i in range(1, len(gs)) :\n", " maxcoord = resid_smo6.lookup_max()\n", " maxpix = resid_smo6.wcs_skycoord_to_pixel(maxcoord[0])\n", " gs[i].xpos = maxpix[0]\n", " gs[i].ypos = maxpix[1]\n", " gs[i].fwhm = 10\n", " gs[i].fwhm = maxcoord[1]\n", "\n", " sh.thaw(gs[i].fwhm)\n", " sh.thaw(gs[i].ampl)\n", " sh.fit()\n", "\n", " sh.thaw(gs[i].xpos)\n", " sh.thaw(gs[i].ypos)\n", " sh.fit()\n", " sh.freeze(gs[i])\n", "\n", " data = sh.get_data_image().y - sh.get_model_image().y # estimate residual map = data - model\n", " resid = SkyImage(data=data, wcs=wcs)\n", "\n", " resid_smo6 = resid.smooth(radius = 6)\n", " resid_smo6.show(vmin = -0.5, vmax = 1)\n", " resid_table.append(resid_smo6)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Generating output table and Test Statistics estimation\n", "When adding a new source, one need to check the significance of this new source. A frequently used method is the Test Statistics (TS). This is done by comparing the change of statistics when the source is included compared to the null hypothesis (no source ; in practice here we fix the amplitude to zero).\n", "\n", "$TS = Cstat(source) - Cstat(no source)$\n", "\n", "The criterion for a significant source detection is typically that it should improve the test statistic by at least 25 or 30. The last excess fitted (g5) thus not a significant source:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=5\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
idxdelstatglonglatsigma
int64float64float64float64float64
0136.582187364300.1514086140.1360681744520.0538113987742
1158.744570772299.644884821-0.1039669652790.169240266293
2111.176173057300.573056380.1427718933810.0525992264273
368.2020558775297.4412336570.1144226382120.0542015591058
428.632872396298.27120691-0.2982239275440.0504649169514
" ], "text/plain": [ "\n", " idx delstat glon glat sigma \n", "int64 float64 float64 float64 float64 \n", "----- ------------- ------------- --------------- ---------------\n", " 0 136.582187364 300.151408614 0.136068174452 0.0538113987742\n", " 1 158.744570772 299.644884821 -0.103966965279 0.169240266293\n", " 2 111.176173057 300.57305638 0.142771893381 0.0525992264273\n", " 3 68.2020558775 297.441233657 0.114422638212 0.0542015591058\n", " 4 28.632872396 298.27120691 -0.298223927544 0.0504649169514" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from astropy.stats import gaussian_fwhm_to_sigma\n", "from astropy.table import Table\n", "\n", "rows = []\n", "for idx, g in enumerate(gs):\n", " ampl = g.ampl.val\n", " g.ampl = 0\n", " stati = sh.get_stat_info()[0].statval\n", " g.ampl = ampl\n", " statf = sh.get_stat_info()[0].statval\n", " delstat = stati - statf\n", " \n", " coord = resid.wcs_pixel_to_skycoord(g.xpos.val, g.ypos.val)\n", " pix_scale = resid.wcs_pixel_scale()[0].deg\n", " sigma = g.fwhm.val * pix_scale * gaussian_fwhm_to_sigma\n", " rows.append(dict(\n", " idx=idx,\n", " delstat=delstat,\n", " glon=coord.l.deg,\n", " glat=coord.b.deg,\n", " sigma=sigma ,\n", " ))\n", "\n", "table = Table(rows=rows, names=rows[0])\n", "table[table['delstat'] > 25]" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": false }, "outputs": [], "source": [ "# Small animation to show the source detection at each iteration\n", "from ipywidgets.widgets.interaction import interact\n", "\n", "def plot_resid(i):\n", " fig, ax,cbar = resid_table[i].plot(vmin=-0.5, vmax=1,cmap='CMRmap')\n", "# ax=plt.gca()\n", " ax.set_title('CStat=%.2f'%(table['delstat'][i]))\n", " ax.scatter(\n", " table['glon'][i], table['glat'][i],\n", " transform=ax.get_transform('galactic'),\n", " color='none', edgecolor='azure', marker='o', s=400)\n", "# plt.savefig('source_%i.png'%(i))\n", " plt.show()\n", "\n", "interact(plot_resid,i=(0,5))" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## Exercises\n", "\n", "* If you look back to the original image: there's one source that looks like a shell-type supernova remnant.\n", " * Try to fit is with a shell morphology model (use ``sh.shell2d('shell')`` to create such a model).\n", " * Try to evaluate the ``TS`` and probability of the shell model compared to a Gaussian model hypothesis\n", " * You could also try a disk model (use ``sh.disk2d('disk')`` to create one)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What next?\n", "\n", "These are good resources to learn more about Sherpa:\n", "\n", "* https://python4astronomers.github.io/fitting/fitting.html\n", "* https://github.com/DougBurke/sherpa-standalone-notebooks\n", "\n", "You could read over the examples there, and try to apply a similar analysis to this dataset here to practice.\n", "\n", "If you want a deeper understanding of how Sherpa works, then these proceedings are good introductions:\n", "\n", "* http://conference.scipy.org/proceedings/scipy2009/paper_8/full_text.pdf\n", "* http://conference.scipy.org/proceedings/scipy2011/pdfs/brefsdal.pdf" ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3", "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": "3.6.3" }, "nbsphinx": { "orphan": true }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }