{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook prepare the catalogues that will be analysed by CIGALE for SED fitting and physical parameter estimation." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import numpy as np\n", "import os\n", "os.environ['LOG_LEVEL'] = 'INFO'\n", "\n", "from astropy.table import Table\n", "\n", "from herschelhelp.filters import correct_galactic_extinction\n", "from herschelhelp.external import convert_table_for_cigale" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "SUFFIX = '20180221'\n", "\n", "master_catalogue = Table.read(\"../../dmu32/dmu32_xFLS/data/xFLS_{}_cigale.fits\".format(SUFFIX))" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [ { "data": { "text/plain": [ "977148" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(master_catalogue)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Best sources\n", "\n", "Define a good far-IR measurement as:\n", "- an existing flux in the band;\n", "- the flag from XID+ must not be set;\n", "- the signal to noise ratio must be over 2." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# good = {}\n", "# for band in ['pacs_green', 'pacs_red', 'spire_250', 'spire_350', 'spire_500']:\n", "# good[band] = (~np.isnan(master_catalogue['f_{}'.format(band)]) & \n", "# ~master_catalogue['flag_{}'.format(band)])\n", "# good[band][good[band]] &= (master_catalogue[good[band]]['f_{}'.format(band)] /\n", "# master_catalogue[good[band]]['ferr_{}'.format(band)] >= 2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will keep only sources with at leat 2 good far-IR measurements (we may actually use less sources are not all may have a redshift)." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# combined_good = np.sum(list(good.values()), axis=0) >= 2" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# print(\"Number of good sources: {}\".format(np.sum(combined_good)))" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Only sources with at least two optical and at least two near infrared detections\n", "optnir = ((master_catalogue['flag_optnir_det'] == 3) \n", " | (master_catalogue['flag_optnir_det'] == 7))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Main catalogue for CIGALE" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# best_catalogue = master_catalogue[combined_good].copy()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# # Correction for galactic extinction\n", "# best_catalogue = correct_galactic_extinction(best_catalogue, inplace=True)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": true, "scrolled": false }, "outputs": [], "source": [ "# # Convertion to CIGALE format\n", "# best_catalogue = convert_table_for_cigale(best_catalogue, inplace=True, remove_zerofluxes=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Band selection\n", "\n", "We want to use only one filter for similar bands. We define an order of preference and set to NaN the flux in the lower prefered bands when a prefered band is available. Some band may have a 0 flux, we set there values to NaN." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": true }, "outputs": [], "source": [ "\n", "u_bands = [\"wfc_u\"]\n", "g_bands = [\"wfc_g\", \"90prime_g\", \"gpc1_g\"]\n", "r_bands = [\"wfc_r\", \"90prime_r\", \"mosaic_r\", \"gpc1_r\"]\n", "i_bands = [\"wfc_i\", \"gpc1_i\"]\n", "z_bands = [\"wfc_z\", \"gpc1_z\"]\n", "y_bands = [ \"mosaic_z\", \"gpc1_y\"]\n", "\n", "def remove_unneeded_fluxes(list_of_bands):\n", " for band_idx, band in enumerate(list_of_bands[:-1]):\n", " mask = ~np.isnan(best_catalogue[band])\n", " for lower_band in list_of_bands[band_idx+1:]:\n", " best_catalogue[lower_band][mask] = np.nan\n", " best_catalogue[\"{}_err\".format(lower_band)][mask] = np.nan" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": true }, "outputs": [], "source": [ "#remove_unneeded_fluxes(g_bands)\n", "#remove_unneeded_fluxes(u_bands)\n", "#remove_unneeded_fluxes(r_bands)\n", "#remove_unneeded_fluxes(i_bands)\n", "#remove_unneeded_fluxes(z_bands)\n", "#remove_unneeded_fluxes(y_bands)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": true }, "outputs": [], "source": [ "#best_catalogue.write(\"data_tmp/CDFS-SWIRE_cigale_best_extcor_20180129.fits\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Catalogue using spectroscopic redshift" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": true }, "outputs": [], "source": [ "best_catalogue = master_catalogue[optnir].copy()" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": true }, "outputs": [], "source": [ "#best_catalogue.remove_column(\"redshift\")\n", "#best_catalogue[\"zspec\"].name = \"redshift\"" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": true }, "outputs": [], "source": [ "best_catalogue = best_catalogue[~np.isnan(best_catalogue[\"redshift\"])]" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of sources with z-spec: 0\n" ] } ], "source": [ "print(\"Number of sources with z-spec: {}\".format(len(best_catalogue)))" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Correction for galactic extinction\n", "best_catalogue = correct_galactic_extinction(best_catalogue, inplace=True)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Convertion to CIGALE format\n", "os.environ['LOG_LEVEL'] = 'INFO'\n", "best_catalogue = convert_table_for_cigale(best_catalogue, inplace=True, remove_zerofluxes=True)" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": true }, "outputs": [], "source": [ "remove_unneeded_fluxes(g_bands)\n", "remove_unneeded_fluxes(u_bands)\n", "remove_unneeded_fluxes(r_bands)\n", "remove_unneeded_fluxes(i_bands)\n", "remove_unneeded_fluxes(z_bands)\n", "remove_unneeded_fluxes(y_bands)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "collapsed": true }, "outputs": [], "source": [ "best_catalogue.write(\"data_tmp/xFLS_cigale_optnir_extcor_zspec_{}.fits\".format(SUFFIX), overwrite=True)" ] } ], "metadata": { "kernelspec": { "display_name": "Python (herschelhelp_internal)", "language": "python", "name": "helpint" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 }