{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Merge MF blind catalgoues from the 3 SPIRE bands\n", "![HELP LOGO](https://avatars1.githubusercontent.com/u/7880370?s=100&v=4>)\n", "\n", "\n", "1. Reads the 250um, 350um and 500um Blind Matched Filter catalgoue \n", "2. Merges the table with 12'' and 18'' matching radius\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Combining the MF catalgoues\n", "### Creates the file \"name_field\"_all.fits, for all fields\n", "### The RA and Dec from \"name_field\"_all.fits is used as input for XID+" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from astropy.io import fits\n", "from astropy.table import Table, vstack\n", "import os\n", "%matplotlib inline \n", "\n", "import matplotlib.pyplot as plt\n", "from astropy.wcs import WCS\n", "from matplotlib.patches import Ellipse\n", "from astropy.coordinates import SkyCoord\n", "from astropy import units as u\n", "from astropy.table import Column\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# The SPIRE fields in HELP:\n", "all_names = ['GAMA-09_SPIRE','GAMA-12_SPIRE','GAMA-15_SPIRE','HATLAS-NGP_SPIRE','HATLAS-SGP_SPIRE','SSDF_SPIRE',\\\n", " 'AKARI-SEP_SPIRE','Bootes_SPIRE','CDFS-SWIRE_SPIRE','COSMOS_SPIRE','EGS_SPIRE',\\\n", " 'ELAIS-N1_SPIRE','ELAIS-N2_SPIRE','ELAIS-S1_SPIRE','HDF-N_SPIRE','Lockman-SWIRE_SPIRE','SA13_SPIRE',\\\n", " 'SPIRE-NEP_SPIRE','xFLS_SPIRE','XMM-13hr_SPIRE','XMM-LSS_SPIRE','AKARI-SEP_SPIRE']\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "all_names=['Herschel-Stripe-82_SPIRE']" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "band = ['250','350','500']" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dmu22_Herschel-Stripe-82/data/\n" ] } ], "source": [ "j=0\n", "loc = 'dmu22_'+all_names[j][0:-6]+'/data/'\n", "print(loc)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# loops over the matched filterd catalogues and creates a merged catalgoue for every field.\n", "# Duplicated are removed in the 350um catalogue when the object is within a 12 arcsec radius of a 250um detection\n", "# Duplicated are removed in the 500um catalogue when the object is within a 18 arcsec radius of a 250um or\n", "# 350um detection\n", "\n", "\n", "for j in range(np.size(all_names)):\n", " loc = 'dmu22_'+all_names[j][0:-6]+'/data/'\n", "\n", "\n", " name = all_names[j]+'250_cat_MF.fits'\n", " cat1=Table.read(loc+name)\n", "\n", " RA,DEC = cat1['RA']*u.degree,cat1['Dec']*u.degree\n", " cat1.add_column(Column(np.zeros(np.size(RA))),name='flag')\n", "\n", " cat1['F_BLIND_pix_SPIRE_250'].name = 'F_BLIND_pix_SPIRE'\n", " cat1['FErr_BLIND_pix_SPIRE_250'].name = 'FErr_BLIND_pix_SPIRE'\n", "\n", " name = all_names[j]+'350_cat_MF.fits'\n", " cat2=Table.read(loc+name)\n", "\n", " RA_m,DEC_m = cat2['RA']*u.degree,cat2['Dec']*u.degree\n", " cat2.add_column(Column(np.zeros(np.size(RA_m))+1),name='flag')\n", "\n", " cat2['F_BLIND_pix_SPIRE_350'].name = 'F_BLIND_pix_SPIRE'\n", " cat2['FErr_BLIND_pix_SPIRE_350'].name = 'FErr_BLIND_pix_SPIRE'\n", "\n", "\n", " catalog = SkyCoord(ra=RA, dec=DEC) \n", " c = SkyCoord(ra=RA_m, dec=DEC_m)\n", "\n", " idx, d2d, d3d = c.match_to_catalog_sky(catalog) \n", " use = np.array(d2d)*3600 > 12.\n", " cat2 = cat2[use]\n", "\n", " cat_all = vstack([cat1, cat2])\n", "\n", " name = all_names[j]+'500_cat_MF.fits'\n", " cat3=Table.read(loc+name)\n", "\n", " RA_m,DEC_m = cat3['RA']*u.degree,cat3['Dec']*u.degree\n", " cat3.add_column(Column(np.zeros(np.size(RA_m))+2),name='flag')\n", "\n", " cat3['F_BLIND_pix_SPIRE_500'].name = 'F_BLIND_pix_SPIRE'\n", " cat3['FErr_BLIND_pix_SPIRE_500'].name = 'FErr_BLIND_pix_SPIRE'\n", "\n", " catalog = SkyCoord(ra=cat_all['RA']*u.degree, dec=cat_all['Dec']*u.degree) \n", " c = SkyCoord(ra=RA_m, dec=DEC_m)\n", "\n", " idx, d2d, d3d = c.match_to_catalog_sky(catalog) \n", " use = np.array(d2d)*3600 > 18.\n", " cat3 = cat3[use]\n", "\n", " cat_all = vstack([cat_all, cat3])\n", "\n", " cat_all.write(loc+all_names[j]+'_all.fits', format='fits',overwrite=True)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "*This is a default HELP jupyter notebook *\n", "\n", " ![HELP LOGO](https://avatars1.githubusercontent.com/u/7880370?s=75&v=4)\n", "\n", "**Authors**: S. Duivenvoorden, P.D. Hurley\n", "\n", " \n", "For a full description of the database and how it is organised in to `dmu_products` please the top level [readme](../readme.md).\n", " \n", "The Herschel Extragalactic Legacy Project, ([HELP](http://herschel.sussex.ac.uk/)), is a [European Commission Research Executive Agency](https://ec.europa.eu/info/departments/research-executive-agency_en)\n", "funded project under the SP1-Cooperation, Collaborative project, Small or medium-scale focused research project, FP7-SPACE-2013-1 scheme, Grant Agreement\n", "Number 607254.\n", "\n", "[Acknowledgements](http://herschel.sussex.ac.uk/acknowledgements)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "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": "3.6.6" } }, "nbformat": 4, "nbformat_minor": 1 }