{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Make a full overview of number counts by band by field\n", "\n", "The reviewer requested that we produce number counts for each band on each field" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/rs548/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/__init__.py:1405: UserWarning: \n", "This call to matplotlib.use() has no effect because the backend has already\n", "been chosen; matplotlib.use() must be called *before* pylab, matplotlib.pyplot,\n", "or matplotlib.backends is imported for the first time.\n", "\n", " warnings.warn(_use_error_msg)\n" ] } ], "source": [ "%matplotlib inline\n", "#%config InlineBackend.figure_format = 'svg'\n", "\n", "import matplotlib as mpl\n", "mpl.use('pdf')\n", "import matplotlib.pyplot as plt\n", "import matplotlib.gridspec as gridspec\n", "\n", "import numpy as np\n", "#plt.rc('figure', figsize=(10, 6))\n", "from matplotlib_venn import venn3\n", "\n", "import herschelhelp \n", "from herschelhelp.utils import clean_table\n", "\n", "from astropy.table import Table, vstack\n", "\n", "import pyvo as vo\n", "\n", "from pymoc import MOC\n", "\n", "import time\n", "\n", "import yaml\n", "\n", "\n", "\n", "import warnings\n", "warnings.filterwarnings('ignore')" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "#Then we establish the VO connection to our database\n", "service = vo.dal.TAPService(\"https://herschel-vos.phys.sussex.ac.uk/__system__/tap/run/tap\"\n", " )" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "fields = yaml.load(open('../../../dmu2/meta_main.yml', 'r'))['fields']" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "bands = [\n", " 'mmt_g', \n", " 'omegacam_g', \n", " 'suprime_g', \n", " 'megacam_g', \n", " 'wfc_g', \n", " 'gpc1_g', \n", " 'decam_g', \n", " '90prime_g', \n", " 'sdss_g',\n", " 'isaac_k', \n", " 'moircs_k', \n", " 'ukidss_k', \n", " 'newfirm_k', \n", " 'wircs_k', \n", " 'hawki_k',\n", " 'wircam_ks', \n", " 'vista_ks', \n", " 'moircs_ks', \n", " 'omega2000_ks', \n", " 'tifkam_ks'\n", "]\n", "mag_tables = {}\n", "\n", "\n", "for band in bands:\n", " mag_tables[band] = {}\n", " for f in fields:\n", " \n", " mag_tables[band].update({f['name']: None})" ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "mmt_g\n", "Querying VOX for mmt_g mags on HATLAS-NGP\n", "COMPLETED\n", "omegacam_g\n", "Querying VOX for omegacam_g mags on HATLAS-NGP\n", "COMPLETED\n", "suprime_g\n", "Querying VOX for suprime_g mags on HATLAS-NGP\n", "COMPLETED\n", "megacam_g\n", "Querying VOX for megacam_g mags on HATLAS-NGP\n", "COMPLETED\n", "wfc_g\n", "Querying VOX for wfc_g mags on HATLAS-NGP\n", "COMPLETED\n", "gpc1_g\n", "Querying VOX for gpc1_g mags on HATLAS-NGP\n", "COMPLETED\n", "Band gpc1_g field HATLAS-NGP done in 69 seconds with 3089817 objects\n", "decam_g\n", "Querying VOX for decam_g mags on HATLAS-NGP\n", "COMPLETED\n", "90prime_g\n", "Querying VOX for 90prime_g mags on HATLAS-NGP\n", "COMPLETED\n", "Band 90prime_g field HATLAS-NGP done in 35 seconds with 1099257 objects\n", "sdss_g\n", "Querying VOX for sdss_g mags on HATLAS-NGP\n", "COMPLETED\n", "isaac_k\n", "Querying VOX for isaac_k mags on HATLAS-NGP\n", "COMPLETED\n", "moircs_k\n", "Querying VOX for moircs_k mags on HATLAS-NGP\n", "COMPLETED\n", "ukidss_k\n", "Querying VOX for ukidss_k mags on HATLAS-NGP\n", "COMPLETED\n", "Band ukidss_k field HATLAS-NGP done in 43 seconds with 1778877 objects\n", "newfirm_k\n", "Querying VOX for newfirm_k mags on HATLAS-NGP\n", "COMPLETED\n", "wircs_k\n", "Querying VOX for wircs_k mags on HATLAS-NGP\n", "COMPLETED\n", "hawki_k\n", "Querying VOX for hawki_k mags on HATLAS-NGP\n", "COMPLETED\n", "wircam_ks\n", "Querying VOX for wircam_ks mags on HATLAS-NGP\n", "COMPLETED\n", "vista_ks\n", "Querying VOX for vista_ks mags on HATLAS-NGP\n", "COMPLETED\n", "moircs_ks\n", "Querying VOX for moircs_ks mags on HATLAS-NGP\n", "COMPLETED\n", "omega2000_ks\n", "Querying VOX for omega2000_ks mags on HATLAS-NGP\n", "COMPLETED\n", "tifkam_ks\n", "Querying VOX for tifkam_ks mags on HATLAS-NGP\n", "COMPLETED\n", "Total time: 395 seconds\n" ] } ], "source": [ "start = time.time()\n", "for band in bands:\n", " print(band)\n", " \n", " for f in fields:\n", " \n", " \n", " try:\n", " \n", " mag_tables[band].update({f['name'] : Table.read('./data/{}_{}.fits'.format(band, f['name']))})\n", " print(\"loaded {} from file ({} objects)\".format(band, len(mag_tables[band][f['name']])))\n", " continue\n", " except FileNotFoundError:\n", " print(\"Querying VOX for {} mags on {}\".format(band, f['name']))\n", " \n", " query = \"\"\"\n", " SELECT \n", " m_{}\n", " FROM herschelhelp.main\n", " WHERE herschelhelp.main.m_{} IS NOT NULL\n", " AND herschelhelp.main.field='{}'\"\"\".format(\n", " band, band, \n", " f['name'].replace('Lockman-SWIRE','Lockman SWIRE' ).replace('HATLAS-NGP','NGP' ))\n", "\n", " job = service.submit_job(query, maxrec=100000000)\n", " job.run()\n", " job_url = job.url\n", " job_result = vo.dal.tap.AsyncTAPJob(job_url)\n", " start_time = time.time()\n", " wait = 10.\n", " while job.phase == 'EXECUTING':\n", " #print('Job still running after {} seconds.'.format(round(time.time() - start_time)))\n", " time.sleep(wait) \n", " #wait *=2\n", "\n", " print(job.phase)\n", " result = job_result.fetch_result()\n", " mag_tables[band].update({ f['name']: result.table})\n", " if len(mag_tables[band][f['name']]) != 0:\n", " print(\"Band {} field {} done in {} seconds with {} objects\".format(\n", " band, \n", " f['name'], \n", " round(time.time() - start_time), \n", " len(mag_tables[band][f['name']])\n", " ))\n", " \n", "print(\"Total time: {} seconds\".format(round(time.time() - start)))" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'mmt_g': {'AKARI-NEP': \n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'AKARI-SEP':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'Bootes':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'CDFS-SWIRE':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'COSMOS':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'EGS':
\n", " m_mmt_g \n", " mag \n", " float64 \n", " ----------------\n", " 25.0262350814973\n", " 24.8055004271999\n", " 26.7586308878581\n", " 26.8136303557976\n", " 26.5265249833877\n", " 25.3982665621918\n", " 24.7932205745817\n", " 25.0049695460861\n", " 25.3133781743952\n", " ...\n", " 24.9616550650424\n", " 25.4603839092271\n", " 24.8054754283809\n", " 24.69364457401\n", " 26.6493553539056\n", " 24.9149306939346\n", " 24.3272071325981\n", " 25.2301662011606\n", " 25.1957844406397\n", " 25.1038138580834, 'ELAIS-N1':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'ELAIS-N2':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'ELAIS-S1':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'GAMA-09':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'GAMA-12':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'GAMA-15':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'HDF-N':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'Herschel-Stripe-82':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'Lockman-SWIRE':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'HATLAS-NGP':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'SA13':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'HATLAS-SGP':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'SPIRE-NEP':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'SSDF':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'xFLS':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'XMM-13hr':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------, 'XMM-LSS':
\n", " m_mmt_g\n", " mag \n", " float64\n", " -------}, 'omegacam_g': {'AKARI-NEP':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'AKARI-SEP':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'Bootes':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'CDFS-SWIRE':
\n", " m_omegacam_g \n", " mag \n", " float64 \n", " ----------------\n", " 22.2159099578857\n", " 22.4423580169678\n", " 22.6238136291504\n", " 22.3810195922852\n", " 22.1104164123535\n", " 25.1483058929443\n", " 22.980224609375\n", " 22.5294170379639\n", " 21.4012470245361\n", " ...\n", " 18.8314304351807\n", " 23.1851692199707\n", " 22.273323059082\n", " 22.1166095733643\n", " 18.8611106872559\n", " 21.1975383758545\n", " 21.0377502441406\n", " 21.0957508087158\n", " 21.7127418518066\n", " 17.7055912017822, 'COSMOS':
\n", " m_omegacam_g \n", " mag \n", " float64 \n", " ----------------\n", " 26.0588760375977\n", " 24.6088943481445\n", " 26.1141185760498\n", " 21.7713928222656\n", " 23.7152004241943\n", " 24.1655578613281\n", " 24.3694019317627\n", " 23.4960289001465\n", " 24.3179836273193\n", " ...\n", " 26.1417427062988\n", " 24.2834911346436\n", " 22.3109893798828\n", " 22.7364025115967\n", " 20.4745826721191\n", " 25.3823680877686\n", " 24.9297695159912\n", " 21.6366577148438\n", " 17.112678527832\n", " 23.5597476959229, 'EGS':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'ELAIS-N1':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'ELAIS-N2':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'ELAIS-S1':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'GAMA-09':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------\n", " 15.66098\n", " 24.879473\n", " 23.083426\n", " 24.57502\n", " 23.499004\n", " 23.405088\n", " 19.901829\n", " 22.098906\n", " 23.68417\n", " ...\n", " 22.375662\n", " 25.305157\n", " 22.50269\n", " 25.361929\n", " 22.916521\n", " 26.31349\n", " 26.50019\n", " 25.103107\n", " 22.605324\n", " 25.608948, 'GAMA-12':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------\n", " 24.19675\n", " 25.84538\n", " 26.282864\n", " 25.566612\n", " 22.101114\n", " 24.230942\n", " 25.324774\n", " 25.75528\n", " 19.859446\n", " ...\n", " 20.948233\n", " 25.576973\n", " 32.94739\n", " 22.813984\n", " 23.942245\n", " 26.0821\n", " 19.160912\n", " 24.494522\n", " 20.677063\n", " 22.785294, 'GAMA-15':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------\n", " 25.664982\n", " 25.724543\n", " 26.030485\n", " 24.19449\n", " 23.67388\n", " 24.62253\n", " 26.395514\n", " 25.973484\n", " 24.245886\n", " ...\n", " 22.883194\n", " 25.02119\n", " 26.733015\n", " 23.77022\n", " 32.642162\n", " 26.635843\n", " 24.727531\n", " 23.822786\n", " 25.697876\n", " 28.630592, 'HDF-N':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'Herschel-Stripe-82':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'Lockman-SWIRE':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'HATLAS-NGP':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'SA13':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'HATLAS-SGP':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------\n", " 21.793266\n", " 22.570494\n", " 22.282597\n", " 21.758881\n", " 21.023148\n", " 22.067949\n", " 20.511028\n", " 21.18508\n", " 17.901398\n", " ...\n", " 11.795041\n", " 22.492682\n", " 22.043037\n", " 22.378239\n", " 22.156565\n", " 21.087481\n", " 19.442417\n", " 22.163731\n", " 22.223745\n", " 22.488333, 'SPIRE-NEP':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'SSDF':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'xFLS':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'XMM-13hr':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------, 'XMM-LSS':
\n", " m_omegacam_g\n", " mag \n", " float64 \n", " ------------}, 'suprime_g': {'AKARI-NEP':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'AKARI-SEP':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'Bootes':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'CDFS-SWIRE':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'COSMOS':
\n", " m_suprime_g \n", " mag \n", " float64 \n", " ----------------\n", " 31.5735244750977\n", " 27.0510215759277\n", " 26.2303657531738\n", " 25.2811126708984\n", " 24.8446769714355\n", " 25.8066558837891\n", " 27.5760879516602\n", " 25.8722152709961\n", " 26.0041427612305\n", " ...\n", " 29.4460201263428\n", " 24.8022003173828\n", " 26.2482318878174\n", " 27.0974655151367\n", " 27.2159328460693\n", " 27.2186965942383\n", " 27.2599411010742\n", " 25.2253360748291\n", " 24.8442554473877\n", " 26.2352390289307, 'EGS':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------\n", " 26.03445\n", " 26.25376\n", " 26.501303\n", " 25.836636\n", " 24.340424\n", " 22.98474\n", " 25.980633\n", " 25.424639\n", " 24.87691\n", " ...\n", " 26.51951\n", " 25.731945\n", " 26.193508\n", " 24.729471\n", " 27.418257\n", " 26.30471\n", " 25.457598\n", " 23.629965\n", " 25.608225\n", " 25.037588, 'ELAIS-N1':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------\n", " 26.190187\n", " 25.094297\n", " 24.23316\n", " 25.272518\n", " 24.488167\n", " 23.021973\n", " 25.279636\n", " 24.54289\n", " 24.911102\n", " ...\n", " 24.880207\n", " 24.845541\n", " 25.315401\n", " 27.498764\n", " 26.653355\n", " 25.571619\n", " 26.099335\n", " 22.800299\n", " 24.621151\n", " 24.06807, 'ELAIS-N2':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'ELAIS-S1':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'GAMA-09':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------\n", " 25.785698\n", " 25.799252\n", " 24.980556\n", " 25.64302\n", " 25.144138\n", " 27.288345\n", " 26.234924\n", " 26.609074\n", " 29.86832\n", " ...\n", " 25.815693\n", " 23.412716\n", " 25.66861\n", " 21.20838\n", " 25.187708\n", " 25.712542\n", " 27.039783\n", " 25.168047\n", " 24.60846\n", " 29.02539, 'GAMA-12':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'GAMA-15':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------\n", " 30.41225\n", " 25.911913\n", " 26.203278\n", " 21.178776\n", " 26.22332\n", " 25.332819\n", " 26.285103\n", " 24.476484\n", " 25.050694\n", " ...\n", " 25.198397\n", " 26.607622\n", " 25.992533\n", " 25.827847\n", " 26.544422\n", " 25.705206\n", " 27.32314\n", " 23.311092\n", " 25.23658\n", " 27.235424, 'HDF-N':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'Herschel-Stripe-82':
\n", " m_suprime_g \n", " mag \n", " float64 \n", " ----------------\n", " 24.064136505127\n", " 25.0604648590088\n", " 25.9485549926758\n", " 24.4544219970703\n", " 24.0442085266113\n", " 24.7659702301025\n", " 25.8915004730225\n", " 25.0403537750244\n", " 26.0955333709717\n", " ...\n", " 23.3482990264893\n", " 24.3442935943604\n", " 24.4636077880859\n", " 22.1284160614014\n", " 22.634895324707\n", " 24.0288467407227\n", " 26.3355388641357\n", " 24.2477035522461\n", " 23.4948272705078\n", " 24.9456634521484, 'Lockman-SWIRE':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'HATLAS-NGP':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'SA13':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'HATLAS-SGP':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'SPIRE-NEP':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'SSDF':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'xFLS':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'XMM-13hr':
\n", " m_suprime_g\n", " mag \n", " float64 \n", " -----------, 'XMM-LSS':
\n", " m_suprime_g \n", " mag \n", " float64 \n", " ----------------\n", " 26.5896625518799\n", " 23.8388195037842\n", " 25.5500030517578\n", " 25.2816257476807\n", " 25.6866340637207\n", " 24.574104309082\n", " 27.1703109741211\n", " 26.3370418548584\n", " 25.5840015411377\n", " ...\n", " 29.8266696929932\n", " 24.5326175689697\n", " 24.7520694732666\n", " 25.4663715362549\n", " 26.4062652587891\n", " 26.2194805145264\n", " 26.0118598937988\n", " 27.2758655548096\n", " 25.1217651367188\n", " 25.809154510498}, 'megacam_g': {'AKARI-NEP':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------\n", " 23.762\n", " 23.67\n", " 22.961\n", " 23.556\n", " 24.86\n", " 23.059\n", " 19.993\n", " 21.353\n", " 18.051\n", " ...\n", " 23.3\n", " 24.54\n", " 23.001\n", " 23.461\n", " 20.813\n", " 22.916\n", " 23.181\n", " 20.968\n", " 22.757\n", " 22.457,\n", " 'AKARI-SEP':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'Bootes':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'CDFS-SWIRE':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'COSMOS':
\n", " m_megacam_g \n", " mag \n", " float64 \n", " ----------------\n", " 25.6350994110107\n", " 27.8379993438721\n", " 23.8320007324219\n", " 28.3479995727539\n", " 22.5149993896484\n", " 26.2509994506836\n", " 24.9740009307861\n", " 26.4909992218018\n", " 27.4349994659424\n", " ...\n", " 25.3409996032715\n", " 26.2910003662109\n", " 26.568000793457\n", " 28.1709995269775\n", " 28.3409996032715\n", " 26.7859992980957\n", " 20.2779998779297\n", " 24.8470001220703\n", " 25.0410003662109\n", " 26.0200004577637,\n", " 'EGS':
\n", " m_megacam_g \n", " mag \n", " float64 \n", " ----------------\n", " 26.0709991455078\n", " 25.8400001525879\n", " 24.9619998931885\n", " 25.257999420166\n", " 24.9899997711182\n", " 25.0020008087158\n", " 25.4060001373291\n", " 25.507999420166\n", " 25.496000289917\n", " ...\n", " 25.7299995422363\n", " 26.0130004882812\n", " 25.0669994354248\n", " 25.5209999084473\n", " 23.1410007476807\n", " 25.0289993286133\n", " 25.32200050354\n", " 26.7730007171631\n", " 25.4570007324219\n", " 26.8290004730225,\n", " 'ELAIS-N1':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------\n", " 25.047508\n", " 25.736942\n", " 25.54196\n", " 21.962635\n", " 22.442259\n", " 26.234413\n", " 21.021275\n", " 26.374535\n", " 25.849514\n", " ...\n", " 26.913055\n", " 24.15323\n", " 22.76754\n", " 25.75749\n", " 25.023285\n", " 24.054537\n", " 27.394762\n", " 25.842901\n", " 25.180197\n", " 25.92887,\n", " 'ELAIS-N2':
\n", " m_megacam_g \n", " mag \n", " float64 \n", " ----------------\n", " 25.4323997497559\n", " 24.6644992828369\n", " 25.0660991668701\n", " 24.289400100708\n", " 25.2894992828369\n", " 24.2119007110596\n", " 24.6096000671387\n", " 24.0695991516113\n", " 22.5398006439209\n", " ...\n", " 25.456600189209\n", " 25.2653999328613\n", " 25.4120998382568\n", " 23.7581005096436\n", " 25.1035003662109\n", " 24.7528991699219\n", " 22.99880027771\n", " 25.5995998382568\n", " 24.5995998382568\n", " 23.6103000640869,\n", " 'ELAIS-S1':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'GAMA-09':
\n", " m_megacam_g \n", " mag \n", " float64 \n", " ----------------\n", " 25.9659996032715\n", " 25.7189998626709\n", " 26.3349990844727\n", " 24.8969993591309\n", " 24.8439998626709\n", " 25.6140003204346\n", " 23.9519996643066\n", " 26.6280002593994\n", " 24.9750003814697\n", " ...\n", " 25.9930000305176\n", " 25.7490005493164\n", " 23.923999786377\n", " 25.6840000152588\n", " 23.8850002288818\n", " 25.8269996643066\n", " 23.9090003967285\n", " 24.2350006103516\n", " 25.3589992523193\n", " 26.9459991455078,\n", " 'GAMA-12':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'GAMA-15':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'HDF-N':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'Herschel-Stripe-82':
\n", " m_megacam_g \n", " mag \n", " float64 \n", " ----------------\n", " 23.6809997558594\n", " 23.738899230957\n", " 24.7856998443604\n", " 24.6847991943359\n", " 25.2180995941162\n", " 24.7966995239258\n", " 23.7185001373291\n", " 26.0919990539551\n", " 25.3090991973877\n", " ...\n", " 25.3341007232666\n", " 24.3460998535156\n", " 21.2206001281738\n", " 24.3197994232178\n", " 22.5373992919922\n", " 24.4083995819092\n", " 23.2150001525879\n", " 25.7726001739502\n", " 25.271900177002\n", " 25.2430000305176,\n", " 'Lockman-SWIRE':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'HATLAS-NGP':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'SA13':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'HATLAS-SGP':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'SPIRE-NEP':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'SSDF':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'xFLS':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'XMM-13hr':
\n", " m_megacam_g\n", " mag \n", " float64 \n", " -----------,\n", " 'XMM-LSS':
\n", " m_megacam_g \n", " mag \n", " float64 \n", " ----------------\n", " 23.996000289917\n", " 25.1550006866455\n", " 25.8099994659424\n", " 25.5179996490479\n", " 25.3579998016357\n", " 26.3299999237061\n", " 25.9169998168945\n", " 26.3589992523193\n", " 25.3920001983643\n", " ...\n", " 25.073657989502\n", " 25.7915077209473\n", " 22.515100479126\n", " 24.1873970031738\n", " 21.8046131134033\n", " 24.5894298553467\n", " 24.8643779754639\n", " 25.5356121063232\n", " 24.6423110961914\n", " 24.0928211212158}, 'wfc_g': {'AKARI-NEP':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'AKARI-SEP':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'Bootes':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'CDFS-SWIRE':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'COSMOS':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'EGS':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'ELAIS-N1':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------\n", " 22.356\n", " 23.972\n", " 23.274\n", " 21.983\n", " 24.006\n", " 24.637\n", " 22.367\n", " 22.845\n", " 21.82\n", " ...\n", " 19.596\n", " 16.828\n", " 23.961\n", " 24.301\n", " 22.437\n", " 20.151\n", " 24.374\n", " 22.876\n", " 22.804\n", " 24.382, 'ELAIS-N2':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------\n", " 24.188\n", " 25.002\n", " 24.715\n", " 24.49\n", " 23.121\n", " 25.202\n", " 22.186\n", " 23.98\n", " 20.002\n", " ...\n", " 21.279\n", " 23.285\n", " 22.511\n", " 21.457\n", " 23.503\n", " 23.251\n", " 22.525\n", " 23.116\n", " 22.813\n", " 23.244, 'ELAIS-S1':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'GAMA-09':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'GAMA-12':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'GAMA-15':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'HDF-N':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'Herschel-Stripe-82':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'Lockman-SWIRE':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'HATLAS-NGP':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'SA13':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'HATLAS-SGP':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'SPIRE-NEP':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'SSDF':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'xFLS':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------\n", " 18.621\n", " 23.041\n", " 23.288\n", " 23.722\n", " 24.15\n", " 24.179\n", " 22.707\n", " 24.031\n", " 19.815\n", " ...\n", " 24.229\n", " 23.131\n", " 23.283\n", " 23.606\n", " 22.295\n", " 23.149\n", " 23.039\n", " 21.135\n", " 23.495\n", " 20.356, 'XMM-13hr':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------, 'XMM-LSS':
\n", " m_wfc_g\n", " mag \n", " float64\n", " -------}, 'gpc1_g': {'AKARI-NEP':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 22.8649997711182\n", " 21.6070003509521\n", " 20.7877006530762\n", " 23.6667995452881\n", " 21.6905002593994\n", " 22.8159008026123\n", " 23.5333995819092\n", " 22.300500869751\n", " 16.4899005889893\n", " ...\n", " 21.5778007507324\n", " 20.3281002044678\n", " 21.4724006652832\n", " 22.8048000335693\n", " 21.24880027771\n", " 25.016300201416\n", " 22.8286991119385\n", " 22.8638000488281\n", " 22.7234992980957\n", " 21.8864002227783, 'AKARI-SEP':
\n", " m_gpc1_g\n", " mag \n", " float64 \n", " --------, 'Bootes':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 22.2868995666504\n", " 19.8700008392334\n", " 23.3344993591309\n", " 21.4396991729736\n", " 24.1117000579834\n", " 22.5146007537842\n", " 19.1180992126465\n", " 23.3360996246338\n", " 21.3780994415283\n", " ...\n", " 22.0450992584229\n", " 22.2285995483398\n", " 20.9731998443604\n", " 23.1324005126953\n", " 23.2915992736816\n", " 23.2012996673584\n", " 22.8125991821289\n", " 25.9708003997803\n", " 23.0874996185303\n", " 22.657600402832, 'CDFS-SWIRE':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 21.8311996459961\n", " 22.3866996765137\n", " 22.5380992889404\n", " 22.6912002563477\n", " 21.9339008331299\n", " 21.8612995147705\n", " 21.8673992156982\n", " 19.0193004608154\n", " 21.7845993041992\n", " ...\n", " 22.2220001220703\n", " 21.5769996643066\n", " 22.992000579834\n", " 21.24880027771\n", " 22.4845008850098\n", " 15.8690996170044\n", " 15.5569000244141\n", " 21.8540992736816\n", " 21.8243007659912\n", " 18.3808994293213, 'COSMOS':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 23.7957000732422\n", " 23.1375999450684\n", " 23.7546997070312\n", " 21.964599609375\n", " 22.1091995239258\n", " 19.7198009490967\n", " 23.2399005889893\n", " 24.4703006744385\n", " 22.8148994445801\n", " ...\n", " 22.2336006164551\n", " 21.9748992919922\n", " 23.2691993713379\n", " 21.0109996795654\n", " 20.3694000244141\n", " 22.9570999145508\n", " 22.7579002380371\n", " 21.5221004486084\n", " 22.5911998748779\n", " 23.0673007965088, 'EGS':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 20.5914001464844\n", " 22.1373996734619\n", " 22.7896995544434\n", " 18.8700008392334\n", " 22.3467998504639\n", " 22.5049991607666\n", " 22.0659008026123\n", " 22.7924995422363\n", " 22.9277992248535\n", " ...\n", " 22.777099609375\n", " 21.7201995849609\n", " 22.8733005523682\n", " 21.7052993774414\n", " 22.9941005706787\n", " 22.5727996826172\n", " 22.4876003265381\n", " 22.4185009002686\n", " 21.9552993774414\n", " 25.4839992523193, 'ELAIS-N1':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 22.2413997650146\n", " 22.6944999694824\n", " 23.4081001281738\n", " 22.8169994354248\n", " 23.1438007354736\n", " 17.3600006103516\n", " 22.3696994781494\n", " 21.0042991638184\n", " 22.1865005493164\n", " ...\n", " 22.0986995697021\n", " 21.9923992156982\n", " 17.3743991851807\n", " 17.5870990753174\n", " 21.6602993011475\n", " 19.8092994689941\n", " 16.9519004821777\n", " 22.4237003326416\n", " 20.2423992156982\n", " 22.5391998291016, 'ELAIS-N2':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 17.2089004516602\n", " 16.4733009338379\n", " 17.4743003845215\n", " 22.0153007507324\n", " 24.0596008300781\n", " 22.9041004180908\n", " 23.5671997070312\n", " 23.5032005310059\n", " 21.9776992797852\n", " ...\n", " 23.984899520874\n", " 17.6336002349854\n", " 22.5214996337891\n", " 13.6819000244141\n", " 22.0701999664307\n", " 18.7593002319336\n", " 23.0459995269775\n", " 23.3572006225586\n", " 23.4004001617432\n", " 23.3633995056152, 'ELAIS-S1':
\n", " m_gpc1_g\n", " mag \n", " float64 \n", " --------, 'GAMA-09':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 22.6879005432129\n", " 23.3381004333496\n", " 17.3330993652344\n", " 22.2751007080078\n", " 22.3533000946045\n", " 24.3076992034912\n", " 21.8495006561279\n", " 21.8782005310059\n", " 21.7947998046875\n", " ...\n", " 22.6128997802734\n", " 23.077600479126\n", " 22.5909996032715\n", " 14.8218002319336\n", " 22.7796993255615\n", " 24.6714992523193\n", " 22.0851001739502\n", " 23.2464008331299\n", " 21.5202007293701\n", " 18.99049949646, 'GAMA-12':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 19.8019008636475\n", " 21.68630027771\n", " 20.2816009521484\n", " 21.4503002166748\n", " 22.1392993927002\n", " 22.1068000793457\n", " 21.2047004699707\n", " 20.6511001586914\n", " 19.8106994628906\n", " ...\n", " 22.0499992370605\n", " 22.7427005767822\n", " 22.6287994384766\n", " 22.5797004699707\n", " 22.7786998748779\n", " 20.7432994842529\n", " 22.940299987793\n", " 19.0631999969482\n", " 20.6133003234863\n", " 22.9636001586914, 'GAMA-15':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 21.4190006256104\n", " 22.6042995452881\n", " 21.3883991241455\n", " 22.2625007629395\n", " 22.827299118042\n", " 21.8418998718262\n", " 20.8306999206543\n", " 20.1054000854492\n", " 22.9549999237061\n", " ...\n", " 17.6812992095947\n", " 17.781400680542\n", " 19.0401000976562\n", " 22.4741992950439\n", " 21.763599395752\n", " 20.2984008789062\n", " 20.0300006866455\n", " 21.0930004119873\n", " 22.3241004943848\n", " 21.869800567627, 'HDF-N':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 16.5387001037598\n", " 21.1261005401611\n", " 18.5067005157471\n", " 15.6749000549316\n", " 20.235200881958\n", " 25.8118000030518\n", " 22.2534999847412\n", " 24.7397003173828\n", " 22.5746002197266\n", " ...\n", " 22.6786003112793\n", " 24.8558006286621\n", " 21.3955001831055\n", " 21.9015007019043\n", " 22.1219005584717\n", " 22.4493007659912\n", " 21.6681995391846\n", " 20.2231006622314\n", " 22.3323001861572\n", " 23.3097991943359, 'Herschel-Stripe-82':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 23.3834991455078\n", " 21.8160991668701\n", " 22.0368995666504\n", " 23.2115993499756\n", " 22.8463001251221\n", " 22.9740009307861\n", " 22.7401008605957\n", " 22.7639999389648\n", " 21.6527996063232\n", " ...\n", " 20.5382995605469\n", " 23.3495998382568\n", " 23.7084007263184\n", " 22.5245990753174\n", " 20.065299987793\n", " 22.7129001617432\n", " 22.6247997283936\n", " 21.7886009216309\n", " 22.4141006469727\n", " 22.1658992767334, 'Lockman-SWIRE':
\n", " m_gpc1_g\n", " mag \n", " float64 \n", " --------, 'HATLAS-NGP':
\n", " m_gpc1_g\n", " mag \n", " float64 \n", " --------, 'SA13':
\n", " m_gpc1_g\n", " mag \n", " float64 \n", " --------, 'HATLAS-SGP':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 21.5146007537842\n", " 19.0013008117676\n", " 21.6774997711182\n", " 19.2994995117188\n", " 23.1616992950439\n", " 21.8278007507324\n", " 22.861400604248\n", " 22.7250995635986\n", " 21.1432991027832\n", " ...\n", " 22.5783996582031\n", " 21.8215007781982\n", " 23.3593997955322\n", " 22.3071002960205\n", " 22.1923999786377\n", " 22.5473003387451\n", " 23.0538005828857\n", " 22.1117992401123\n", " 23.7287998199463\n", " 22.2413997650146, 'SPIRE-NEP':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 22.4862003326416\n", " 22.3337993621826\n", " 22.5650005340576\n", " 23.0660991668701\n", " 22.2840995788574\n", " 22.9237995147705\n", " 20.2338008880615\n", " 25.693000793457\n", " 22.0270004272461\n", " ...\n", " 22.577299118042\n", " 22.2938995361328\n", " 24.0580997467041\n", " 22.8253002166748\n", " 22.6525001525879\n", " 18.0412998199463\n", " 22.4899997711182\n", " 21.5841999053955\n", " 21.3006000518799\n", " 20.8605003356934, 'SSDF':
\n", " m_gpc1_g\n", " mag \n", " float64 \n", " --------, 'xFLS':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 23.3285007476807\n", " 21.202600479126\n", " 22.9729995727539\n", " 22.7787990570068\n", " 21.5414009094238\n", " 22.6984996795654\n", " 22.7399997711182\n", " 16.8605003356934\n", " 22.1984004974365\n", " ...\n", " 21.1720008850098\n", " 20.7681999206543\n", " 13.5818004608154\n", " 22.341100692749\n", " 23.2667999267578\n", " 23.0617008209229\n", " 21.5890998840332\n", " 23.4477996826172\n", " 21.9594993591309\n", " 21.2789993286133, 'XMM-13hr':
\n", " m_gpc1_g\n", " mag \n", " float64 \n", " --------, 'XMM-LSS':
\n", " m_gpc1_g \n", " mag \n", " float64 \n", " ----------------\n", " 21.5193004608154\n", " 20.6208992004395\n", " 22.2556991577148\n", " 21.3889999389648\n", " 23.6215000152588\n", " 22.0414009094238\n", " 21.8929004669189\n", " 23.2422008514404\n", " 22.2688999176025\n", " ...\n", " 24.0275993347168\n", " 21.756799697876\n", " 22.3411998748779\n", " 22.3376007080078\n", " 22.25950050354\n", " 23.1229000091553\n", " 22.2933006286621\n", " 22.0750999450684\n", " 20.4755001068115\n", " 22.4934005737305}, 'decam_g': {'AKARI-NEP':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'AKARI-SEP':
\n", " m_decam_g \n", " mag \n", " float64 \n", " ----------------\n", " 27.3512096405029\n", " 24.5801277160645\n", " 24.6603202819824\n", " 23.1829700469971\n", " 23.7280540466309\n", " 26.0909633636475\n", " 23.7979316711426\n", " 24.6847190856934\n", " 26.5824584960938\n", " ...\n", " 24.9742374420166\n", " 24.3166160583496\n", " 25.3336391448975\n", " 21.4737300872803\n", " 22.8091640472412\n", " 24.8032913208008\n", " 21.6819305419922\n", " 25.5231151580811\n", " 30.3473205566406\n", " 23.9725875854492, 'Bootes':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'CDFS-SWIRE':
\n", " m_decam_g \n", " mag \n", " float64 \n", " ----------------\n", " 24.5385513305664\n", " 23.742654800415\n", " 24.5208549499512\n", " 25.4372940063477\n", " 23.4483757019043\n", " 24.7072830200195\n", " 23.0938282012939\n", " 25.2747173309326\n", " 23.5594463348389\n", " ...\n", " 24.9751396179199\n", " 23.9331378936768\n", " 24.4740428924561\n", " 21.5098533630371\n", " 23.600399017334\n", " 17.5894088745117\n", " 22.2627029418945\n", " 24.9402542114258\n", " 24.2005043029785\n", " 23.1619682312012, 'COSMOS':
\n", " m_decam_g \n", " mag \n", " float64 \n", " ----------------\n", " 23.4527816772461\n", " 23.3915100097656\n", " 24.5924453735352\n", " 24.9649124145508\n", " 23.7100448608398\n", " 28.1928787231445\n", " 24.2065963745117\n", " 24.0358123779297\n", " 21.552848815918\n", " ...\n", " 23.1455917358398\n", " 24.2173233032227\n", " 22.6914978027344\n", " 23.3310928344727\n", " 24.1130065917969\n", " 23.0324172973633\n", " 20.6477432250977\n", " 23.0264205932617\n", " 22.1510848999023\n", " 24.3920364379883, 'EGS':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'ELAIS-N1':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'ELAIS-N2':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'ELAIS-S1':
\n", " m_decam_g \n", " mag \n", " float64 \n", " ----------------\n", " 23.3754482269287\n", " 23.8095512390137\n", " 25.0937023162842\n", " 23.7320346832275\n", " 24.4684028625488\n", " 24.1777305603027\n", " 23.1053256988525\n", " 23.80930519104\n", " 23.5428142547607\n", " ...\n", " 26.2275562286377\n", " 24.0611553192139\n", " 24.7075710296631\n", " 24.6456413269043\n", " 23.4614601135254\n", " 21.692699432373\n", " 23.167797088623\n", " 23.814697265625\n", " 26.7337036132812\n", " 25.0903663635254, 'GAMA-09':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------\n", " 22.783173\n", " 19.621422\n", " 23.68222\n", " 24.33355\n", " 22.01043\n", " 19.29216\n", " 21.302322\n", " 17.019653\n", " 23.159203\n", " ...\n", " 24.715576\n", " 24.845428\n", " 24.432495\n", " 23.582787\n", " 23.89518\n", " 25.481636\n", " 25.14\n", " 23.844902\n", " 23.309692\n", " 26.603195, 'GAMA-12':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------\n", " 23.378922\n", " 26.057716\n", " 23.03965\n", " 19.447945\n", " 24.8843\n", " 21.797874\n", " 24.450722\n", " 24.419266\n", " 25.37165\n", " ...\n", " 24.423103\n", " 24.310799\n", " 14.925484\n", " 23.991241\n", " 23.883743\n", " 23.999496\n", " 24.937973\n", " 22.917068\n", " 22.25013\n", " 22.92585, 'GAMA-15':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------\n", " 21.979904\n", " 17.631279\n", " 23.445961\n", " 26.308334\n", " 26.146217\n", " 24.151085\n", " 23.66726\n", " 24.083115\n", " 24.671684\n", " ...\n", " 24.797539\n", " 22.589272\n", " 25.171486\n", " 25.49636\n", " 25.890678\n", " 23.851662\n", " 21.960571\n", " 25.073616\n", " 23.39428\n", " 24.167847, 'HDF-N':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'Herschel-Stripe-82':
\n", " m_decam_g \n", " mag \n", " float64 \n", " ----------------\n", " 21.3846435546875\n", " 23.9071578979492\n", " 22.9767532348633\n", " 21.8534336090088\n", " 23.8555526733398\n", " 22.4241561889648\n", " 23.0489673614502\n", " 23.284538269043\n", " 23.5089263916016\n", " ...\n", " 26.5016498565674\n", " 25.4025859832764\n", " 26.4302463531494\n", " 25.9039783477783\n", " 25.8085021972656\n", " 25.2978267669678\n", " 25.6075134277344\n", " 25.8375282287598\n", " 25.5507488250732\n", " 25.1108779907227, 'Lockman-SWIRE':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'HATLAS-NGP':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'SA13':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'HATLAS-SGP':
\n", " m_decam_g \n", " mag \n", " float64 \n", " ----------------\n", " 25.0321254730225\n", " 22.8353252410889\n", " 24.0421733856201\n", " 19.8806667327881\n", " 22.7583446502686\n", " 24.5900936126709\n", " 20.8870735168457\n", " 23.3070468902588\n", " 20.6925315856934\n", " ...\n", " 25.6934108734131\n", " 24.3497409820557\n", " 23.5132999420166\n", " 24.3166732788086\n", " 23.9729537963867\n", " 22.2633895874023\n", " 24.2156600952148\n", " 23.5673027038574\n", " 25.8179340362549\n", " 24.4324798583984, 'SPIRE-NEP':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'SSDF':
\n", " m_decam_g \n", " mag \n", " float64 \n", " ----------------\n", " 23.9452495574951\n", " 24.4626560211182\n", " 25.0428695678711\n", " 23.3441066741943\n", " 21.8964519500732\n", " 24.3941268920898\n", " 25.2548542022705\n", " 26.1766815185547\n", " 25.4190235137939\n", " ...\n", " 22.6061363220215\n", " 24.969747543335\n", " 22.432861328125\n", " 24.8445625305176\n", " 25.1429061889648\n", " 24.2463226318359\n", " 23.559061050415\n", " 23.8377838134766\n", " 25.0702610015869\n", " 25.7485866546631, 'xFLS':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'XMM-13hr':
\n", " m_decam_g\n", " mag \n", " float64 \n", " ---------, 'XMM-LSS':
\n", " m_decam_g \n", " mag \n", " float64 \n", " ----------------\n", " 23.5760135650635\n", " 26.1797370910645\n", " 23.4090728759766\n", " 23.099292755127\n", " 24.2937278747559\n", " 22.658130645752\n", " 25.1774024963379\n", " 24.6821365356445\n", " 24.3993511199951\n", " ...\n", " 24.8712902069092\n", " 23.6233711242676\n", " 22.6166439056396\n", " 20.6127376556396\n", " 24.468900680542\n", " 23.2015132904053\n", " 24.0908870697021\n", " 24.9753189086914\n", " 24.115743637085\n", " 23.9049415588379}, '90prime_g': {'AKARI-NEP':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'AKARI-SEP':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'Bootes':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------\n", " 22.076622\n", " 19.918587\n", " 24.224792\n", " 23.893051\n", " 23.432716\n", " 21.360893\n", " 21.97628\n", " 23.385864\n", " 23.027489\n", " ...\n", " 22.823097\n", " 21.758217\n", " 23.625046\n", " 22.531982\n", " 23.872704\n", " 20.224457\n", " 24.814034\n", " 23.616829\n", " 23.366081\n", " 23.419716, 'CDFS-SWIRE':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'COSMOS':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'EGS':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------\n", " 22.658989\n", " 24.633652\n", " 23.497688\n", " 23.075027\n", " 24.82843\n", " 23.298302\n", " 23.323265\n", " 20.488777\n", " 22.216797\n", " ...\n", " 24.465294\n", " 23.691032\n", " 23.47091\n", " 23.387947\n", " 24.283089\n", " 23.026352\n", " 22.143875\n", " 20.288483\n", " 24.844711\n", " 22.594215, 'ELAIS-N1':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'ELAIS-N2':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'ELAIS-S1':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'GAMA-09':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'GAMA-12':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'GAMA-15':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'HDF-N':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'Herschel-Stripe-82':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'Lockman-SWIRE':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'HATLAS-NGP':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'SA13':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------\n", " 24.041458\n", " 23.265419\n", " 22.846642\n", " 23.346596\n", " 25.245735\n", " 24.542877\n", " 23.443626\n", " 22.090523\n", " 23.396736\n", " ...\n", " 24.113869\n", " 22.68348\n", " 25.46096\n", " 20.393593\n", " 22.369354\n", " 26.206345\n", " 25.539833\n", " 24.586884\n", " 24.785149\n", " 29.147835, 'HATLAS-SGP':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'SPIRE-NEP':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'SSDF':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------, 'xFLS':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------\n", " 23.13749\n", " 23.123108\n", " 21.256508\n", " 24.97158\n", " 19.753319\n", " 25.755714\n", " 17.884766\n", " 23.11554\n", " 23.162514\n", " ...\n", " 20.667229\n", " 21.345978\n", " 22.862648\n", " 21.28495\n", " 21.210976\n", " 18.902908\n", " 20.424858\n", " 22.164627\n", " 21.553513\n", " 19.896294, 'XMM-13hr':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------\n", " 24.004356\n", " 22.30812\n", " 24.47647\n", " 23.475487\n", " 24.30481\n", " 24.071045\n", " 23.931213\n", " 23.167854\n", " 21.188126\n", " ...\n", " 24.133095\n", " 22.93222\n", " 24.375519\n", " 24.46167\n", " 24.418732\n", " 24.2565\n", " 24.21328\n", " 23.092415\n", " 23.708305\n", " 23.821045, 'XMM-LSS':
\n", " m_90prime_g\n", " mag \n", " float64 \n", " -----------}, 'sdss_g': {'AKARI-NEP':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'AKARI-SEP':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'Bootes':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'CDFS-SWIRE':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'COSMOS':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'EGS':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'ELAIS-N1':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'ELAIS-N2':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'ELAIS-S1':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'GAMA-09':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'GAMA-12':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'GAMA-15':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'HDF-N':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'Herschel-Stripe-82':
\n", " m_sdss_g \n", " mag \n", " float64 \n", " ----------------\n", " 23.16748046875\n", " 18.8512840270996\n", " 23.613245010376\n", " 23.2207622528076\n", " 24.4240894317627\n", " 23.470531463623\n", " 21.610164642334\n", " 24.5126247406006\n", " 22.1481285095215\n", " ...\n", " 22.342041015625\n", " 23.2707061767578\n", " 23.580078125\n", " 23.2221603393555\n", " 18.076976776123\n", " 23.0668792724609\n", " 23.8846740722656\n", " 24.8808422088623\n", " 24.2330493927002\n", " 24.0838832855225, 'Lockman-SWIRE':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'HATLAS-NGP':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'SA13':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'HATLAS-SGP':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'SPIRE-NEP':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'SSDF':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'xFLS':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'XMM-13hr':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------, 'XMM-LSS':
\n", " m_sdss_g\n", " mag \n", " float64 \n", " --------}, 'isaac_k': {'AKARI-NEP':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'AKARI-SEP':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'Bootes':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'CDFS-SWIRE':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------\n", " 24.765022\n", " 26.504532\n", " 24.804184\n", " 25.373993\n", " 21.928139\n", " 25.663422\n", " 20.02967\n", " 25.187302\n", " 26.64943\n", " ...\n", " 25.270325\n", " 22.909714\n", " 24.23893\n", " 24.855461\n", " 24.38089\n", " 22.644485\n", " 24.270187\n", " 21.597527\n", " 23.401512\n", " 24.355072, 'COSMOS':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'EGS':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'ELAIS-N1':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'ELAIS-N2':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'ELAIS-S1':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'GAMA-09':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'GAMA-12':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'GAMA-15':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'HDF-N':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'Herschel-Stripe-82':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'Lockman-SWIRE':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'HATLAS-NGP':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'SA13':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'HATLAS-SGP':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'SPIRE-NEP':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'SSDF':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'xFLS':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'XMM-13hr':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------, 'XMM-LSS':
\n", " m_isaac_k\n", " mag \n", " float64 \n", " ---------}, 'moircs_k': {'AKARI-NEP':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'AKARI-SEP':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'Bootes':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'CDFS-SWIRE':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'COSMOS':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'EGS':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'ELAIS-N1':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'ELAIS-N2':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'ELAIS-S1':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'GAMA-09':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'GAMA-12':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'GAMA-15':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'HDF-N':
\n", " m_moircs_k \n", " mag \n", " float64 \n", " ----------------\n", " 28.912009271007\n", " 29.0802914741732\n", " 28.792577316517\n", " 28.1463398171417\n", " 28.8094261397843\n", " 28.7586906898022\n", " 28.6252103424405\n", " 25.3920270527308\n", " 25.5235562704568\n", " ...\n", " 28.2140280111241\n", " 29.3761007134118\n", " 28.7673038912914\n", " 28.8668533367912\n", " 28.6533906854574\n", " 28.9614204787268\n", " 28.673473230429\n", " 28.6109737208143\n", " 28.7955317025706\n", " 28.7548844240118, 'Herschel-Stripe-82':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'Lockman-SWIRE':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'HATLAS-NGP':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'SA13':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'HATLAS-SGP':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'SPIRE-NEP':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'SSDF':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'xFLS':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'XMM-13hr':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------, 'XMM-LSS':
\n", " m_moircs_k\n", " mag \n", " float64 \n", " ----------}, 'ukidss_k': {'AKARI-NEP':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'AKARI-SEP':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'Bootes':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'CDFS-SWIRE':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'COSMOS':
\n", " m_ukidss_k \n", " mag \n", " float64 \n", " ----------------\n", " 20.0260467529297\n", " 20.19677734375\n", " 20.0113315582275\n", " 20.0561199188232\n", " 18.9145488739014\n", " 19.2261714935303\n", " 19.5165367126465\n", " 17.9017391204834\n", " 19.5410404205322\n", " ...\n", " 17.7640228271484\n", " 19.7852954864502\n", " 19.6420021057129\n", " 18.9899673461914\n", " 19.5373554229736\n", " 20.949592590332\n", " 20.4988174438477\n", " 20.3787631988525\n", " 19.2813758850098\n", " 19.1197509765625, 'EGS':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'ELAIS-N1':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------\n", " 19.701931\n", " 21.189533\n", " 20.847317\n", " 21.994812\n", " 22.657696\n", " 19.81652\n", " 22.60165\n", " 21.6941\n", " 19.661238\n", " ...\n", " 21.528645\n", " 21.953152\n", " 22.893547\n", " 21.391829\n", " 20.525274\n", " 20.959604\n", " 21.433565\n", " 21.534248\n", " 21.076912\n", " 21.20223, 'ELAIS-N2':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'ELAIS-S1':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'GAMA-09':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------\n", " 19.395937\n", " 18.980877\n", " 17.298445\n", " 18.681791\n", " 21.447458\n", " 19.63707\n", " 20.597944\n", " 17.07453\n", " 19.729206\n", " ...\n", " 19.506132\n", " 13.111143\n", " 19.549725\n", " 19.919981\n", " 19.427109\n", " 19.221918\n", " 14.883772\n", " 20.21664\n", " 20.176655\n", " 18.206116, 'GAMA-12':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------\n", " 16.423344\n", " 17.35732\n", " 19.625473\n", " 19.205694\n", " 17.36816\n", " 19.495749\n", " 18.923994\n", " 18.71121\n", " 19.219046\n", " ...\n", " 20.243753\n", " 19.672113\n", " 16.329351\n", " 19.905546\n", " 19.579607\n", " 19.589952\n", " 19.988745\n", " 19.182821\n", " 18.219841\n", " 18.568428, 'GAMA-15':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------\n", " 19.448742\n", " 19.841217\n", " 18.638638\n", " 19.815258\n", " 20.261177\n", " 14.120284\n", " 18.541542\n", " 19.656948\n", " 17.911352\n", " ...\n", " 12.5918\n", " 18.563559\n", " 18.256813\n", " 16.903442\n", " 19.350267\n", " 19.68805\n", " 19.648895\n", " 19.605808\n", " 16.67435\n", " 19.034664, 'HDF-N':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'Herschel-Stripe-82':
\n", " m_ukidss_k \n", " mag \n", " float64 \n", " ----------------\n", " 18.3379421234131\n", " 18.9946784973145\n", " 20.390682220459\n", " 19.7265663146973\n", " 11.0139026641846\n", " 17.6093730926514\n", " 17.638557434082\n", " 19.6064453125\n", " 18.1318016052246\n", " ...\n", " 18.4959583282471\n", " 19.1209030151367\n", " 19.1820774078369\n", " 19.1677932739258\n", " 19.0021209716797\n", " 18.3564529418945\n", " 19.2596073150635\n", " 19.2279300689697\n", " 19.988582611084\n", " 19.5486717224121, 'Lockman-SWIRE':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'HATLAS-NGP':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'SA13':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'HATLAS-SGP':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'SPIRE-NEP':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'SSDF':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'xFLS':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'XMM-13hr':
\n", " m_ukidss_k\n", " mag \n", " float64 \n", " ----------, 'XMM-LSS':
\n", " m_ukidss_k \n", " mag \n", " float64 \n", " ----------------\n", " 22.3576602935791\n", " 21.0176658630371\n", " 22.5098495483398\n", " 23.2631072998047\n", " 20.6812191009521\n", " 18.3378047943115\n", " 22.7616119384766\n", " 24.1179351806641\n", " 24.2526893615723\n", " ...\n", " 21.6618404388428\n", " 20.6086502075195\n", " 19.0851707458496\n", " 17.5050754547119\n", " 20.3228931427002\n", " 19.6364402770996\n", " 21.8223743438721\n", " 22.0456008911133\n", " 20.0125293731689\n", " 19.9001197814941}, 'newfirm_k': {'AKARI-NEP':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'AKARI-SEP':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'Bootes':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------\n", " 20.326792\n", " 17.099434\n", " 23.90909\n", " 22.164291\n", " 22.216393\n", " 24.171091\n", " 22.67859\n", " 22.36589\n", " 21.473892\n", " ...\n", " 25.69249\n", " 20.140991\n", " 21.70679\n", " 19.60869\n", " 19.78639\n", " 20.96799\n", " 20.36599\n", " 20.66769\n", " 25.47099\n", " 25.91649, 'CDFS-SWIRE':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'COSMOS':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'EGS':
\n", " m_newfirm_k \n", " mag \n", " float64 \n", " ----------------\n", " 32.657197555883\n", " 28.5485659366201\n", " 22.8275363390587\n", " 32.3448507895354\n", " 30.7738783867968\n", " 33.8500007652631\n", " 28.3329360327426\n", " 27.6215965510804\n", " 29.8448507143623\n", " ...\n", " 24.6830039984434\n", " 23.2353557290478\n", " 25.4499379665768\n", " 25.4729275386983\n", " 23.2432124316702\n", " 23.8585027012832\n", " 24.6278393455188\n", " 25.7374535766109\n", " 25.7841454870382\n", " 29.2372555926465, 'ELAIS-N1':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'ELAIS-N2':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'ELAIS-S1':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'GAMA-09':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'GAMA-12':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'GAMA-15':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'HDF-N':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'Herschel-Stripe-82':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'Lockman-SWIRE':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'HATLAS-NGP':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'SA13':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'HATLAS-SGP':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'SPIRE-NEP':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'SSDF':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'xFLS':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'XMM-13hr':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------, 'XMM-LSS':
\n", " m_newfirm_k\n", " mag \n", " float64 \n", " -----------}, 'wircs_k': {'AKARI-NEP':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'AKARI-SEP':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'Bootes':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'CDFS-SWIRE':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'COSMOS':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'EGS':
\n", " m_wircs_k \n", " mag \n", " float64 \n", " ----------------\n", " 19.0342235565186\n", " 17.4222221374512\n", " 20.3126220703125\n", " 14.3728218078613\n", " 19.9368228912354\n", " 20.6986236572266\n", " 22.0270233154297\n", " 21.5342235565186\n", " 21.2824230194092\n", " ...\n", " 21.9013233184814\n", " 22.4373226165771\n", " 21.5765228271484\n", " 19.3450222015381\n", " 20.8131237030029\n", " 21.1296234130859\n", " 22.7596225738525\n", " 19.5745220184326\n", " 22.5939235687256\n", " 20.9025230407715, 'ELAIS-N1':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'ELAIS-N2':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'ELAIS-S1':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'GAMA-09':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'GAMA-12':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'GAMA-15':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'HDF-N':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'Herschel-Stripe-82':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'Lockman-SWIRE':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'HATLAS-NGP':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'SA13':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'HATLAS-SGP':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'SPIRE-NEP':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'SSDF':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'xFLS':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'XMM-13hr':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------, 'XMM-LSS':
\n", " m_wircs_k\n", " mag \n", " float64 \n", " ---------}, 'hawki_k': {'AKARI-NEP':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'AKARI-SEP':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'Bootes':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'CDFS-SWIRE':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------\n", " 23.67846\n", " 20.692284\n", " 25.743866\n", " 25.32122\n", " 23.596481\n", " 19.702393\n", " 25.508156\n", " 22.58522\n", " 22.859192\n", " ...\n", " 23.589363\n", " 20.745255\n", " 25.958572\n", " 20.757355\n", " 25.354149\n", " 28.571274\n", " 24.309975\n", " 25.72548\n", " 24.428246\n", " 24.82283, 'COSMOS':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'EGS':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'ELAIS-N1':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'ELAIS-N2':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'ELAIS-S1':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'GAMA-09':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'GAMA-12':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'GAMA-15':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'HDF-N':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'Herschel-Stripe-82':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'Lockman-SWIRE':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'HATLAS-NGP':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'SA13':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'HATLAS-SGP':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'SPIRE-NEP':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'SSDF':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'xFLS':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'XMM-13hr':
\n", " m_hawki_k\n", " mag \n", " float64 \n", " ---------, 'XMM-LSS':
\n", " m_hawki_k \n", " mag \n", " float64 \n", " ----------------\n", " 23.8377395949919\n", " 26.4229046511233\n", " 25.5035545180658\n", " 25.431948241629\n", " 25.8460471455404\n", " 25.8320964535204\n", " 22.1280047798669\n", " 25.5262768014757\n", " 25.469787619208\n", " ...\n", " 25.8353382001983\n", " 25.4543051157703\n", " 22.4541642632768\n", " 27.6254888248011\n", " 25.6346024806377\n", " 26.1455550107197\n", " 25.3860365327388\n", " 24.9951218905389\n", " 24.1028961985053\n", " 24.1228855901054}, 'wircam_ks': {'AKARI-NEP':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------\n", " 17.739\n", " 18.882\n", " 20.202\n", " 19.221\n", " 20.665\n", " 19.194\n", " 20.764\n", " 15.93\n", " 17.343\n", " ...\n", " 20.179\n", " 19.554\n", " 20.748\n", " 19.381\n", " 19.517\n", " 19.581\n", " 19.134\n", " 17.707\n", " 19.904\n", " 17.083,\n", " 'AKARI-SEP':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'Bootes':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'CDFS-SWIRE':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'COSMOS':
\n", " m_wircam_ks \n", " mag \n", " float64 \n", " ----------------\n", " 25.7185001373291\n", " 22.9505004882812\n", " 30.6084003448486\n", " 23.0813007354736\n", " 22.9529991149902\n", " 23.7966003417969\n", " 24.5226993560791\n", " 21.5995006561279\n", " 24.097900390625\n", " ...\n", " 22.7313995361328\n", " 22.983699798584\n", " 28.7376003265381\n", " 25.4920997619629\n", " 24.4703998565674\n", " 24.2238006591797\n", " 23.455099105835\n", " 23.3649997711182\n", " 23.2740993499756\n", " 23.8379001617432,\n", " 'EGS':
\n", " m_wircam_ks \n", " mag \n", " float64 \n", " ----------------\n", " 22.5240001678467\n", " 24.0421009063721\n", " 25.4629993438721\n", " 23.9318008422852\n", " 22.3313999176025\n", " 22.2590999603271\n", " 21.7490997314453\n", " 16.7161998748779\n", " 20.8568000793457\n", " ...\n", " 23.0032997131348\n", " 22.9444999694824\n", " 20.2516994476318\n", " 23.1926002502441\n", " 23.3784008026123\n", " 23.7896003723145\n", " 19.3125991821289\n", " 22.8803005218506\n", " 21.9671993255615\n", " 22.1025009155273,\n", " 'ELAIS-N1':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'ELAIS-N2':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'ELAIS-S1':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'GAMA-09':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'GAMA-12':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'GAMA-15':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'HDF-N':
\n", " m_wircam_ks \n", " mag \n", " float64 \n", " ----------------\n", " 19.9531728201181\n", " 19.1257756999575\n", " 20.9147552860526\n", " 19.8943344194287\n", " 22.8052274111513\n", " 19.3897366451285\n", " 22.4442732932025\n", " 22.8638201259267\n", " 22.9008156962974\n", " ...\n", " 22.8751671916718\n", " 22.0842009697231\n", " 22.1987079765469\n", " 22.6949610588732\n", " 22.6999826426071\n", " 20.6362453963399\n", " 20.168727609731\n", " 20.9027390013582\n", " 20.5401498558857\n", " 19.7270333357526,\n", " 'Herschel-Stripe-82':
\n", " m_wircam_ks \n", " mag \n", " float64 \n", " ----------------\n", " 19.1181316375732\n", " 19.164363861084\n", " 19.8148975372314\n", " 21.7369842529297\n", " 20.9506893157959\n", " 18.8417644500732\n", " 20.8506603240967\n", " 20.549243927002\n", " 17.9875183105469\n", " ...\n", " 21.348747253418\n", " 21.4952507019043\n", " 22.9669075012207\n", " 21.969352722168\n", " 23.0437030792236\n", " 22.8046360015869\n", " 22.1338195800781\n", " 21.5482845306396\n", " 23.0613231658936\n", " 21.9243793487549,\n", " 'Lockman-SWIRE':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'HATLAS-NGP':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'SA13':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'HATLAS-SGP':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'SPIRE-NEP':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'SSDF':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'xFLS':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'XMM-13hr':
\n", " m_wircam_ks\n", " mag \n", " float64 \n", " -----------,\n", " 'XMM-LSS':
\n", " m_wircam_ks \n", " mag \n", " float64 \n", " ----------------\n", " 22.2600002288818\n", " 21.7299995422363\n", " 20.4209995269775\n", " 22.7099990844727\n", " 22.617000579834\n", " 22.701000213623\n", " 21.44700050354\n", " 22.6669998168945\n", " 19.9610004425049\n", " ...\n", " 20.7189998626709\n", " 22.3169994354248\n", " 24.0879993438721\n", " 20.4290008544922\n", " 22.1660003662109\n", " 23.2859992980957\n", " 19.4290008544922\n", " 20.4669990539551\n", " 18.8430004119873\n", " 22.8950004577637}, 'vista_ks': {'AKARI-NEP':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'AKARI-SEP':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------\n", " 20.831287\n", " 19.159641\n", " 20.695368\n", " 14.220743\n", " 16.79507\n", " 20.085579\n", " 17.238113\n", " 17.928457\n", " 20.531004\n", " ...\n", " 20.234035\n", " 21.083328\n", " 17.141233\n", " 20.386019\n", " 18.506254\n", " 18.203592\n", " 20.10307\n", " 19.573156\n", " 20.227282\n", " 17.893667, 'Bootes':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'CDFS-SWIRE':
\n", " m_vista_ks \n", " mag \n", " float64 \n", " ----------------\n", " 18.6178874969482\n", " 19.5172348022461\n", " 17.1389579772949\n", " 17.2088088989258\n", " 20.148681640625\n", " 19.7504005432129\n", " 19.3097038269043\n", " 19.6083755493164\n", " 18.944242477417\n", " ...\n", " 20.7035675048828\n", " 20.1316299438477\n", " 18.5201454162598\n", " 19.389741897583\n", " 15.4449710845947\n", " 19.8296642303467\n", " 21.1155166625977\n", " 17.2220764160156\n", " 15.0654134750366\n", " 17.9207744598389, 'COSMOS':
\n", " m_vista_ks \n", " mag \n", " float64 \n", " ----------------\n", " 24.8808002471924\n", " 25.487699508667\n", " 25.2493000030518\n", " 24.023099899292\n", " 22.7728996276855\n", " 23.7716007232666\n", " 25.9022998809814\n", " 25.0153007507324\n", " 20.2637996673584\n", " ...\n", " 24.0445003509521\n", " 22.1921997070312\n", " 21.8409004211426\n", " 21.5049991607666\n", " 23.0321998596191\n", " 19.7040996551514\n", " 23.9545993804932\n", " 22.5846996307373\n", " 18.9270992279053\n", " 25.8593006134033, 'EGS':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'ELAIS-N1':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'ELAIS-N2':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'ELAIS-S1':
\n", " m_vista_ks \n", " mag \n", " float64 \n", " ----------------\n", " 19.8604164123535\n", " 20.111722946167\n", " 21.0714588165283\n", " 18.2745513916016\n", " 17.6266822814941\n", " 17.0745716094971\n", " 19.2031631469727\n", " 19.3426303863525\n", " 19.2458038330078\n", " ...\n", " 20.0083332061768\n", " 19.8163223266602\n", " 15.6504764556885\n", " 20.1930389404297\n", " 21.4311065673828\n", " 20.9327354431152\n", " 19.768856048584\n", " 21.1845664978027\n", " 18.7114238739014\n", " 20.4641418457031, 'GAMA-09':
\n", " m_vista_ks \n", " mag \n", " float64 \n", " ----------------\n", " 19.2147407531738\n", " 18.8226413726807\n", " 17.2319984436035\n", " 18.7666549682617\n", " 20.5431785583496\n", " 19.8179779052734\n", " 17.0064640045166\n", " 20.3026218414307\n", " 20.0470104217529\n", " ...\n", " 20.8750305175781\n", " 20.5886344909668\n", " 19.6568870544434\n", " 17.6658592224121\n", " 20.9046497344971\n", " 19.949592590332\n", " 20.8194236755371\n", " 20.1874752044678\n", " 20.0991706848145\n", " 17.7134208679199, 'GAMA-12':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------\n", " 20.1357\n", " 16.185911\n", " 20.70952\n", " 17.364332\n", " 20.027357\n", " 21.029842\n", " 19.34515\n", " 17.207623\n", " 20.414938\n", " ...\n", " 19.864428\n", " 18.7765\n", " 19.917963\n", " 20.148384\n", " 19.257713\n", " 20.255478\n", " 18.14916\n", " 18.578833\n", " 20.183006\n", " 20.288399, 'GAMA-15':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------\n", " 20.450727\n", " 19.089176\n", " 20.402971\n", " 20.840242\n", " 20.595377\n", " 21.374731\n", " 19.685452\n", " 18.967585\n", " 20.6188\n", " ...\n", " 19.231497\n", " 18.786829\n", " 20.180864\n", " 19.902061\n", " 20.216635\n", " 20.489332\n", " 20.175209\n", " 20.598812\n", " 20.630007\n", " 19.406937, 'HDF-N':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'Herschel-Stripe-82':
\n", " m_vista_ks \n", " mag \n", " float64 \n", " ----------------\n", " 19.798397064209\n", " 20.1150722503662\n", " 19.1442070007324\n", " 19.2423248291016\n", " 17.7896251678467\n", " 18.980281829834\n", " 19.6375370025635\n", " 18.7165813446045\n", " 19.0437984466553\n", " ...\n", " 20.8796615600586\n", " 20.7459831237793\n", " 19.2829418182373\n", " 18.9516201019287\n", " 20.0597629547119\n", " 18.498161315918\n", " 19.3270168304443\n", " 19.5052547454834\n", " 15.7080125808716\n", " 19.391674041748, 'Lockman-SWIRE':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'HATLAS-NGP':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'SA13':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'HATLAS-SGP':
\n", " m_vista_ks \n", " mag \n", " float64 \n", " ----------------\n", " 21.6547317504883\n", " 14.7025499343872\n", " 13.8523597717285\n", " 20.0415382385254\n", " 18.3635387420654\n", " 20.5660743713379\n", " 20.9032211303711\n", " 17.9320888519287\n", " 20.9609527587891\n", " ...\n", " 20.5288982391357\n", " 20.7577362060547\n", " 19.6695442199707\n", " 18.2212066650391\n", " 18.7157020568848\n", " 18.7333011627197\n", " 19.0281372070312\n", " 16.7950439453125\n", " 19.4042377471924\n", " 18.4999027252197, 'SPIRE-NEP':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'SSDF':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------\n", " 20.126722\n", " 20.019072\n", " 18.602434\n", " 20.451097\n", " 20.009731\n", " 20.221542\n", " 20.679173\n", " 19.634726\n", " 20.51425\n", " ...\n", " 19.029783\n", " 16.265606\n", " 19.878534\n", " 20.108107\n", " 19.13922\n", " 18.733795\n", " 20.540003\n", " 20.624159\n", " 19.578531\n", " 21.159245, 'xFLS':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'XMM-13hr':
\n", " m_vista_ks\n", " mag \n", " float64 \n", " ----------, 'XMM-LSS':
\n", " m_vista_ks \n", " mag \n", " float64 \n", " ----------------\n", " 20.8328266143799\n", " 17.6308460235596\n", " 19.4814128875732\n", " 19.0339012145996\n", " 20.380744934082\n", " 20.1647357940674\n", " 19.994592666626\n", " 19.4205532073975\n", " 20.8467559814453\n", " ...\n", " 19.0932846069336\n", " 19.5815830230713\n", " 19.2015228271484\n", " 18.9479007720947\n", " 19.3612613677979\n", " 20.7076091766357\n", " 19.4265594482422\n", " 17.5071392059326\n", " 20.1998825073242\n", " 19.5586242675781}, 'moircs_ks': {'AKARI-NEP':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'AKARI-SEP':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'Bootes':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'CDFS-SWIRE':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'COSMOS':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'EGS':
\n", " m_moircs_ks \n", " mag \n", " float64 \n", " ----------------\n", " 14.1986519640643\n", " 21.8875399525856\n", " 22.0123910809143\n", " 21.6921102915378\n", " 21.5464450484417\n", " 21.6802959450894\n", " 24.313789286663\n", " 23.1500339096638\n", " 22.2098671883703\n", " ...\n", " 21.0170640515712\n", " 19.4390274201383\n", " 24.3946056170326\n", " 20.8160503583025\n", " 23.7660555321868\n", " 23.2162814757571\n", " 24.3282375025965\n", " 24.3144729546063\n", " 22.4251259966857\n", " 23.3611704537718, 'ELAIS-N1':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'ELAIS-N2':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'ELAIS-S1':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'GAMA-09':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'GAMA-12':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'GAMA-15':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'HDF-N':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'Herschel-Stripe-82':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'Lockman-SWIRE':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'HATLAS-NGP':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'SA13':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'HATLAS-SGP':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'SPIRE-NEP':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'SSDF':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'xFLS':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'XMM-13hr':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------, 'XMM-LSS':
\n", " m_moircs_ks\n", " mag \n", " float64 \n", " -----------}, 'omega2000_ks': {'AKARI-NEP':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'AKARI-SEP':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'Bootes':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'CDFS-SWIRE':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'COSMOS':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'EGS':
\n", " m_omega2000_ks \n", " mag \n", " float64 \n", " ----------------\n", " 22.4814047416075\n", " 21.9843211757868\n", " 22.6205254736152\n", " 20.9617279385355\n", " 22.3051255053395\n", " 24.2702191095774\n", " 24.6038288201053\n", " 22.863652909508\n", " 20.4271291057566\n", " ...\n", " 22.2106915894766\n", " 22.0073644272826\n", " 20.8984208629747\n", " 20.4732547685611\n", " 20.513576519708\n", " 21.1422018661357\n", " 21.1947427891823\n", " 21.4440957459171\n", " 20.8394445347884\n", " 21.1479540106711, 'ELAIS-N1':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'ELAIS-N2':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'ELAIS-S1':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'GAMA-09':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'GAMA-12':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'GAMA-15':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'HDF-N':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'Herschel-Stripe-82':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'Lockman-SWIRE':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'HATLAS-NGP':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'SA13':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'HATLAS-SGP':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'SPIRE-NEP':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'SSDF':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'xFLS':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'XMM-13hr':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------, 'XMM-LSS':
\n", " m_omega2000_ks\n", " mag \n", " float64 \n", " --------------}, 'tifkam_ks': {'AKARI-NEP':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'AKARI-SEP':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'Bootes':
\n", " m_tifkam_ks \n", " mag \n", " float64 \n", " ----------------\n", " 22.9318312545316\n", " 20.0982316822277\n", " 23.0577317330182\n", " 21.9547322948974\n", " 22.3656328311972\n", " 20.8653325295026\n", " 20.116731199499\n", " 20.6151329611231\n", " 20.6182322530431\n", " ...\n", " 19.4994324629665\n", " 20.5298329534448\n", " 21.5794330749759\n", " 16.3085326063985\n", " 16.889131725958\n", " 16.6284316756451\n", " 17.7897322013221\n", " 14.7940331800036\n", " 17.6007322013221\n", " 18.2051337477882, 'CDFS-SWIRE':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'COSMOS':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'EGS':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'ELAIS-N1':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'ELAIS-N2':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'ELAIS-S1':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'GAMA-09':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'GAMA-12':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'GAMA-15':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'HDF-N':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'Herschel-Stripe-82':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'Lockman-SWIRE':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'HATLAS-NGP':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'SA13':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'HATLAS-SGP':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'SPIRE-NEP':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'SSDF':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'xFLS':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'XMM-13hr':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------, 'XMM-LSS':
\n", " m_tifkam_ks\n", " mag \n", " float64 \n", " -----------}}" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mag_tables" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20000000\n" ] } ], "source": [ "#service.maxrec=100000000\n", "print(service.hardlimit)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Herschel Stripe 82 hits the hard limit on rows so we must get it from two queries" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "COMPLETED\n" ] } ], "source": [ "\n", "query = \"\"\"\n", " SELECT \n", " m_{}\n", " FROM herschelhelp.main\n", " WHERE herschelhelp.main.m_{} IS NOT NULL\n", " AND herschelhelp.main.field='{}'\n", " AND herschelhelp.main.m_decam_g<25\n", " \"\"\".format('decam_g', 'decam_g', 'Herschel-Stripe-82')\n", "\n", "job = service.submit_job(query)\n", "job.run()\n", "job_url = job.url\n", "job_result = vo.dal.tap.AsyncTAPJob(job_url)\n", "start_time = time.time()\n", "wait = 10.\n", "while job.phase == 'EXECUTING':\n", " #print('Job still running after {} seconds.'.format(round(time.time() - start_time)))\n", " time.sleep(wait) \n", " #wait *=2\n", "\n", "print(job.phase)\n", "result = job_result.fetch_result()" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "16912119" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(result.table)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "COMPLETED\n" ] } ], "source": [ "query = \"\"\"\n", " SELECT \n", " m_{}\n", " FROM herschelhelp.main\n", " WHERE herschelhelp.main.m_{} IS NOT NULL\n", " AND herschelhelp.main.field='{}'\n", " AND herschelhelp.main.m_decam_g>25\n", " \"\"\".format('decam_g', 'decam_g', 'Herschel-Stripe-82')\n", "\n", "job = service.submit_job(query)\n", "job.run()\n", "job_url = job.url\n", "job_result = vo.dal.tap.AsyncTAPJob(job_url)\n", "start_time = time.time()\n", "wait = 10.\n", "while job.phase == 'EXECUTING':\n", " #print('Job still running after {} seconds.'.format(round(time.time() - start_time)))\n", " time.sleep(wait) \n", " #wait *=2\n", "\n", "print(job.phase)\n", "result2 = job_result.fetch_result()" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "7068890" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(result2.table)" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "hs82 = vstack([clean_table(result.table), clean_table(result2.table)])" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "23981009" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(hs82)" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "mag_tables['decam_g'].update({ 'Herschel-Stripe-82': hs82})" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "write = False\n", "read = True\n", "for band in bands:\n", " for f in fields:\n", " if write and (len(mag_tables[band][f['name']]) != 0):\n", " clean_table(mag_tables[band][f['name']]).write(\n", " './data/{}_{}.fits'.format(band, f['name']), overwrite = True\n", " )\n", " print('Table cleaned and written to ./data/{}_{}.fits'.format(band, f['name']))\n", " elif read:\n", " mag_tables[band].update( \n", " {f['name'] : Table.read('./data/{}_{}.fits'.format(band, f['name']))} \n", " ) \n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Get depth tables to calculate area" ] }, { "cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Job still running after 0 seconds.\n", "Job still running after 13 seconds.\n", "Job still running after 33 seconds.\n", "COMPLETED\n" ] } ], "source": [ "depth_query = \"\"\"\n", "SELECT \n", "DISTINCT\n", "hp_idx_o_10,\"\"\"\n", "for band in bands:\n", " depth_query += \" ferr_{}_mean,\".format(band)\n", "\n", "depth_query = depth_query.strip(',')\n", "depth_query +=\"\"\" FROM depth.main\"\"\"\n", "\n", "job = service.submit_job(depth_query, maxrec=100000000)\n", "job.run()\n", "job_url = job.url\n", "job_result = vo.dal.tap.AsyncTAPJob(job_url)\n", "start_time = time.time()\n", "wait = 10.\n", "while job.phase == 'EXECUTING':\n", " #print('Job still running after {} seconds.'.format(round(time.time() - start_time)))\n", " time.sleep(wait) \n", " #wait *=2\n", "\n", "print('Job {} after {} seconds.'.format(print(job.phase), round(time.time() - start_time))) \n", "\n", "result = job_result.fetch_result()\n", "depth_result = result.table\n", " " ] }, { "cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [], "source": [ "depth_result = clean_table(depth_result)\n", "depth_result.write('./data/depth_result.fits', overwrite = True)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "depth_result = Table.read('./data/depth_result.fits')" ] }, { "cell_type": "code", "execution_count": 105, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=394298\n", "
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hp_idx_o_10ferr_mmt_g_meanferr_omegacam_g_meanferr_suprime_g_meanferr_megacam_g_meanferr_wfc_g_meanferr_gpc1_g_meanferr_decam_g_meanferr_90prime_g_meanferr_sdss_g_meanferr_isaac_k_meanferr_moircs_k_meanferr_ukidss_k_meanferr_newfirm_k_meanferr_wircs_k_meanferr_hawki_k_meanferr_wircam_ks_meanferr_vista_ks_meanferr_moircs_ks_meanferr_omega2000_ks_meanferr_tifkam_ks_mean
uJyuJyuJyuJyuJyuJyuJyuJyuJyuJyuJyuJyuJyuJyuJyuJyuJyuJyuJyuJy
int64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64
1048576nan0.125900130.034778833nannan1.412937710463480.23891595nannannannan12.952429nannannannannannannannan
1048577nan0.128495290.037005715nannan2.585537187556430.26041004nannannannan11.078862nannannannan5.14322257041931nannannan
1048578nan0.131991740.037534576nannan12.12188152045080.5586686nannannannan11.872732nannannannan8.65422657208565nannannan
1048579nan0.126742480.03794215nannan1.564003369041180.23023675nannannannan10.076924nannannannan6.18435804410414nannannan
1048580nan0.142063330.04043122nannan1.395442554979380.22086646nannannannan8.667696nannannannan6.11608852039684nannannan
1048581nan0.263065040.04343463nannan56.28295551786242.3186026nannannannan11.104447nannannannan6.84368888158647nannannan
1048582nan0.1169917960.03961132nannan3.784595150986510.26216686nannannannan9.996422nannannannan6.07616801972085nannannan
1048583nan0.115538430.038907822nannan0.9113893770629180.1591954nannannannan8.795542nannannannan6.55130145814684nannannan
1048584nan0.1222919450.03996328nannan1.816467034829760.19182965nannannannan9.125632nannannannan6.00280002447275nannannan
...............................................................
12042983nan0.930249975880756nannannannannannannannannannannannannannannannannannan
12042985nan0.468560519334635nannannannannannannannannannannannannannannannannannan
12043008nan1.2922718398981nannannannannannannannannannannannannannannannannannan
12043009nan0.968513775613246nannannannannannannannannannannannannannannannannannan
12043010nan0.999256698665766nannannannannannannannannannannannannannannannannannan
12043011nan0.996619003703517nannannannannannannannannannannannannannannannannannan
12043012nan0.456915067791621nannannannannannannannannannannannannannannannannannan
12043016nan1.0629012014192nannannannannannannannannannannannannannannannannannan
12043017nan1.16795881142515nannannannannannannannannannannannannannannannannannan
12043018nan1.22905076556922nannannannannannannannannannannannannannannannannannan
" ], "text/plain": [ "\n", "hp_idx_o_10 ferr_mmt_g_mean ... ferr_omega2000_ks_mean ferr_tifkam_ks_mean\n", " uJy ... uJy uJy \n", " int64 float64 ... float64 float64 \n", "----------- --------------- ... ---------------------- -------------------\n", " 1048576 nan ... nan nan\n", " 1048577 nan ... nan nan\n", " 1048578 nan ... nan nan\n", " 1048579 nan ... nan nan\n", " 1048580 nan ... nan nan\n", " 1048581 nan ... nan nan\n", " 1048582 nan ... nan nan\n", " 1048583 nan ... nan nan\n", " 1048584 nan ... nan nan\n", " ... ... ... ... ...\n", " 12042983 nan ... nan nan\n", " 12042985 nan ... nan nan\n", " 12043008 nan ... nan nan\n", " 12043009 nan ... nan nan\n", " 12043010 nan ... nan nan\n", " 12043011 nan ... nan nan\n", " 12043012 nan ... nan nan\n", " 12043016 nan ... nan nan\n", " 12043017 nan ... nan nan\n", " 12043018 nan ... nan nan" ] }, "execution_count": 105, "metadata": {}, "output_type": "execute_result" } ], "source": [ "depth_result" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plot the histograms" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "bands_plotting = {\n", " 'mmt_g':['MMT $g$','b'], \n", " 'omegacam_g':['Omegacam $g$','g'], \n", " 'suprime_g':['HSC $g$','r'], \n", " 'megacam_g':['Megacam $g$','c'], \n", " 'wfc_g':['WFC $g$','m'], \n", " 'gpc1_g':['GPC1 $g$','y'], \n", " 'decam_g':['DECam $g$','k'], \n", " '90prime_g':['90Prime $g$','darkcyan'], \n", " 'sdss_g':['SDSS $g$','olive'], \n", " 'isaac_k':['ISAAC $K$','hotpink'], \n", " 'moircs_k':['MOIRCS $K$','indigo'], \n", " 'ukidss_k':['UKIDSS $K$','midnightblue'], \n", " 'newfirm_k':['Newfirm $K$','violet'], \n", " 'wircs_k':['WIRKS $K$','darkorchid'], \n", " 'hawki_k':['HAWKI $K$','royalblue'], \n", " 'wircam_ks':['WIRCam $Ks$','chartreuse'], \n", " 'vista_ks':['VISTA $Ks$','rebeccapurple'], \n", " 'moircs_ks':['MOIRCS $Ks$','gold'], \n", " 'omega2000_ks':['Omega2000 $Ks$','coral'], \n", " 'tifkam_ks':['TIFKAM $Ks$','gray']\n", "}" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "h = np.histogram(mag_tables['decam_g']['Herschel-Stripe-82']['m_decam_g'], bins = 100)\n", "bin_width = (np.abs(h[1][5] - h[1][4]) )\n", "area = 100\n", "vals = plt.fill_between( h[1][:-1], h[0]/(bin_width*area), alpha=0.5)\n", "plt.xlim(20.,27.)\n", "plt.yscale('log')\n", "#plt.ylim(1.e5,1.e7)" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['mmt_g',\n", " 'omegacam_g',\n", " 'suprime_g',\n", " 'megacam_g',\n", " 'wfc_g',\n", " 'gpc1_g',\n", " 'decam_g',\n", " '90prime_g',\n", " 'sdss_g']" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "[b for b in mag_tables if b.endswith('g')]" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "data": { "image/png": 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1NhFqbiLS0Xnb+jAYsMStDNvq1ZhzpHjc2kzp6WimhfqVt/RYqD9pF3B3xs8Y4AYQQhwCDj3KQKpwpeJxiOpRanprONh8kMPth/FGvCTbkvna8q/x4rIXWZe6bsaWSERUJ9w+TvCGFJNItxcEaHYTtuWJ2JYnYV2etKTE5H7oPj/6WCtGWyMmVzuRXiuBC8sIXhkiNtZJpPkIkd46rPnZ2FavIeHlfVhLirEUF2MpLMRgUY3PFgoLVVy8gOeucx5gYroDqTbHikdFCMHFwYscbD7Ir1t/zVBwCJfZxfP5z/PishfZlLkJk+HJ/2Um/Q03RwneGCHUPIoI62AAS74Hz5cKsK1IwpzjWhIhu/dCDwYJNTURunmTcGMjoZuNhG7eJNLdPfkazWrFsmwZlpIVmFIqMLiyMSb8Lnb7t3FtzsS5JfupENzFykIVlxuASdO05UKIm/Fz5dxOmnxklOWieBiNI40cbDnIwZaDdHm7sBgs7MjbwYtFL7I9dztW45N/genhmBST68MEb4wQGw0B0m/i2JCBbbkMzZ2pcOCFRHRggEB9PYHLl6WINN4k0t4hM/sBzGasRUXYKypIfON1rCUlWJcvx5ybe0duhxCCcMs43lNdTBzrZOJ4J/a1qbi252DNv/teVDHfzHcosgkpcH8J5AJvAVEhRFTTtH9BFpf4DjJa7CCwVQgxbYEBFYqsuJNbocMHWw5yc+QmRs3Ilqwt7C3ay678Xbgt7ie+RnQkSLBhmMC1YULNoxAVaFYj1uJEbCvkcpcp5e4gycWNHgoRvHpVikl9PcH6i7etEaMRS2HhpHjIfQmW/PxpO9KjI0G8n/Xgq+lFBKJYijy4d+ZhW5GkIrpmmMd16M+3uHwPKSxT+SshxPfieS5/D+wGhoDv3spzmeY1blkub928efOhr1csXQb8A3zS/skXQof3Fu1lT+EeUu2pTzS+0AXhjgmC14YJNgwR6fUDYEyxYV+VjG11MtbChCVTCkUIQaSjIy4kF6WYNDRARCZtmrKzsJeXy21dObY1qzHYZjaiTQ/F8J3txXuii9hYCHOmE/fOXOxlafOWz7PUWJTiMpcoy+XppGWshSPtRzjScYSLA7Lq8K3Q4b1Fe8lx5TzR+HogSvDmiBSU68My58QA1sIEbHFBMaXal8TdtIjFCDY04K85i7+mhsCFC8RGRgDQHA7spaXYy9dhLy/Htm4d5vT0uZtbVIYyTxzrJNrvx5hkxV2di6My44nzZZ52lLjcB2W5PF3oQufy4OVJQbnVW35tylp25e9iV96uJyoSKYQg2uefFJRQ6zjoAoPDhG1lshSUFUkY7Ivfd3K3mPjPnUOfkDE1loIC7Bs2YK+owF6+DmtJyYII8xW6INgwzMTRDsLtExicJlxbc3A9k4XBoXJYHgclLg9BWS5Ll0gswtnesxzpOMKn7Z/SH+jHpJmoyqxiV/6uJ+4tHx0NEWocIdQo62TpXrnsY850SDFZlYwl37PoI7tELEbwWoMUkpoa/LW1d4iJY9Om+LYRc0bGPM/2wQghCLeOM3Gsk2DDMJrFiHNTJq7tOZgSVITZdFhqSZQKxQPxhr2c7D7JkfYjnOg8gTfixW6ysy1nG8/lPUd1bvVjN9rS/RFCzWOy4GLjKNHBAAAGl3myjLx1eSKmxMWbEX+LcEcH3qPH8J069QUx8bzwwqIRk7vRNE1WLihKINLrY+JYJ97TXXjPdOOoSMe9Ixdz+tKrA7aQWPKWi1oWWzoMBgb5tONTjrQf4fOez4noEZJtyezM28muvF1sztr8WK2ARUQn1DY2aZlEuuJJjBYD1mWycq+tJBFThmPR+05EJIK/7jzeY8fwHjtGuKkJAHN+Ps7NmxetmDwK0eEg3pNd+M72IiI69rUpuHflY8lxzffUFjRqWewhqGWxxUnbeJv0n7QfoX6gHoEg15XL8/nPsyt/F+Vp5RgND3fYCiHQY1Fi0SjRcIRIt5dw0xixjiDRTj9EddnkKt+NrUQKiiV3aTS5ig4P4z1+HO+xY/hOnpLWidmMc2MVrh07cO3YgaWwcL6nOWfEvGG8p7vxnu5GBGPYVibhfi4Pa6FqKX0vlLg8BCUuiwMhBFeGrkwKStOYvLNenbSKXanbqXKtIylsxzsyxMTQEN7hISaGBwmMjxGLRtGjUkBi0ciU4yh2zUmmvZAMeyHptgKsRplfMhoeoC/Yxpg2QMAZwJrgwpGQKDdPAs7EpMljR6LcG00L2zEshCB07RreY8eYOHqU4MVLIATGtFRc1dW4duzAufVZjC7n/EwwGoLACIR9EA1CJAgRf/w4cHt/69hoAbMdLE4wO8DiALMzvnfcPmdxwSPcaNxCD0bxnunBe7IT3RfFuiwB9668OS37vxhQ4vIQlLgsXPwRP591nubklY9puFlHdNyHK2gmlzRSY26sfgiMjhKLRO54n2Yw4ExKxp2cgiMhEaPZgtFkwmgyYdGsOIMJOIMuHD4n5rAUhJglRjgpSjRVJ5YKYYL4x8bwj43gGxslMDaGb2wU/9go0XDonvO1uT1kFBWTu2otOavXklmyArNlfp3EsbExfGfO4D1xAt+Jk0T7++Vcy8pw7dyBa8dObGtWz16DKj0GQ43QdwX8Q/FtWO4D8b1/RB6HvbMzB4gLjQusrvjefXt/65wzDZIKIKkQEgvQjR58Z/uYON6JPh7GkufGvSsP26pkJTIocbkvyueysIhGIoz2dNHYdJGLDWfobmskNjiO22vCKG7/IxtMJtwpqbiTU3Elp+BKTrn9OCUFd3IqjsREDPE7VRGJEWodn3TCTxZ/vJURvzze9fARc06EEERCQfyjo/jHR6XgxI8nhgbpudHAYIds4WA0mchYtpyc1WvJXb2W7BWrsTlndx1f6DrBK1cmxSRQXw+6jsHjwfnMM3K5q3o7ptQnSwy9J7oOIy3Qff721lP/RdGwJoAjWW72ZHCkTHmcJK0Ps11uJlvcCrGByT7lvBViEWnZhP0Q8cX3/i+eC/sgPAGhCQh55XxCXgiNTzmegGjgrnl6ILEAkVCEL/gsE53LifktmNNMuHeXYC9NXfSRgE+CEpeHoCyXuSUaDjPc3clQZztDnR0MdrbR09aIf2BosqaUQBBwgT0jlbzClaxesZH03AI86RnY3Z4HioAejBJqGyfcOi6bZnVOQFSAUcOS75F+k+WJWHLcs5apHfBO0H39Kp3XrtDVcIW+5kb0WAw0jbT8QnJWSbHJWbUWV9KTNw6LDg7iO3UK74mT+E6dkgmMmoattBTX9m04t23Hvq5sZvNNoiEYbob+a9BzIS4m9RCKFy032SCzDLLXyy2zDFyZUjyMCzQYNTgGI20w2nbPvYiE8es7mIi+TlTkYbIM417ei2NDDlreBvBkz/cnmFOUuDwEJS6zS8jvp/vGNboartB57TK9jTeIRWVTK6GB1xljyBlk3B0jKSeXspWb2bHuBUrSVj7S+LGxEKHWcUKtY4Rbx4n0+mTlOQOYs11YCxOwLpd9TuYrIzsSDNLTeH1SbLpvNhANyaW1xIws8svKqdjzEmkFRY80nhCC4OXLTHxyGN+JEwSvXgXAmJKCa9uzOLdtx/nsVkzJTyhcug7jnXJZa6gJBm/GjxthrANEvF+K0QIZpXEhqZD7tFVgXNg+qGkhBHj7YbQN0XeNwMU+JloKiUSyMGq9uI0/x5lwGS23HHLWQ/YG+XNwzHzX0YWCEpeHoMRlZvGPj8WFRH6R9rc0I4SOZjRgzEykLznEFVMHw64gJDvYlredHbk72JqzFY/lwRVshRBEBwJSSFrGCbWNExsOAjI82JLvwVrowVKYgCXfvWDLe8SiUfpbm+i6doXOhqu0XTpPNBQib00Z6198heLKTZPLelMJt7cztn8/4/s/INzaCkYj9vUVuLZtx7l9G7bVT+A7iQSh9xJ01UJ3HfRehuEm6Ti/hcUFKSV3bqnLIX0NmJ6+filS5HsZ/7iJSL/AYAritJ3EGX4Hk6FPvighT1ptU7fEAlgCPhslLvdB+VxmhvHBAbquXaYzLijDXR0AGM0WXIXZjKYK6q1tXLa0EzUJShJL2JG7gx15O1iXuu6B4cKTfeGb4n3hW2/3hTc4zZNCYi3yYM5yohkXZ3hw0Ovl0pFfc/7XHzAxOEBCegYVX36Zsl17MAaCjB88xNgH+wnWXwRNw7FxI559L+PZswdjwmOEyeoxGLwhheTW1ncFdPmzxZUJWeVSOG4JSEoJuDKWxJfiTCOEINQ0hvdMN8GrQyDAlidwZjZi00+j9V2EoZu3LT1rAmSW3habrArIWLvofrZKXB6CslweHSEEY/19dFy9SOfVy3Reu8L4gLxDs9gdpK9YTjDTRoOjh2PR80zEvJgNZjZlbqI6t5rq3OoH9pK/1Rc+1DRGqGmUUMttMTGm2OQSV6EHS6FnyRR9nIoei9F47jPqPvgVXTeuYUQjd2iMgv5RUoqWkbDvZTwvvYQ5K2t6AwshrZKGA9B6UvpIbjnZrR65fJNTCTkb5P4p8x3MJNHREL6aHnxne9EnIhiTrDg3Z+Es92D0NULvRfm76L0EfZdl8AGAOxtW7oWVL0LRdhmwsMBR4vIQlLjcHyEEo73ddFy9TOfVS3Rcu4x3aBAAu9tDzuq1mPJTafWMcDp8kUvDlxEIUmwp7MjbQXVuNc9kPYPDfO9yGkIIokNBKSRNo4SaxybrcxkTrbInfHEC1mWJS76zoIhG8Z0+zdj+D5g4fJhREaUtL4tuhxldCIoqKtmw9xUKyjc8mqjGotB+WgpKw0EYawfNIO+Sc6ukTyCnUloksxWG/BQjYjqBK0P4Push1DwGRg1HWSrOZ7Kx5Lvl71CPwXALdHwG1w9B0xEpNhYXlDwPK1+C5bsXrN9GictDUOJyGyEEw92dcavkMh1XL+EbGQbAkZBI7poyUpYvoy85xNnIFU71nGY4OIyGRmlqKdtztrM9dztrUtZg0O79hRUdDhJqHp20TmLjYQAMHgu2ZQlxQUnElLz463M9DCEEwfp6xj44wPihQ8SGhjB4PHheeIGEfS9jr6zEPz7GxU8+pP7jg/hGR0jOzmX93ldYW70L8909UMI++QXVcABufCgTEo1WKN4Fq16CFS+AK21+PuxTTKTPh+/zXny1fYhQDHOWE+eWLBwV6RisU5aFIwFoOX779+ftA80IBVtvWzXJjxb0MRcocXkIT7u4jPX30XKhlo6rl+i8egn/2CgAzqRkcleXkrumlFC2nfOR65zsPsmlwUvoQifBmsCz2c+yLWcbz+Y8S7Lt3ndXsbEQweaxSeskNiKjpAxO86RVYi1OWJLLXPcj1NzM+AcfMPbBASLt7WgWC66dO0l4ZR/O6moMli86x2PRCNfPnKTu4Pv0Nd/E6nSy4YVX2Li9EnP3Z3Dj11JYokGwJUohWfWSFBarqpG1ENBDMfwX+vF91kOkx4dmNeLYkI5rcxbmzLuqIui6DKy4flBaNf0yIpDMMljzGqz9CqQUz/2HmIISl4fwtIlLLBqhq+EaLRfO0Vx3dtIB70pJJS8uJoklRVzRmznZdZJTXacYCg4BsvfJ9tztbMvZRmlK6T2d8bGJ8G3LpHlssnKwZjdhXZYwaZ0shWKP0yHS18f4wUOM798vQ4cNBpxbNuN5eR/u3V/C6H609slirJvuE7+g9tMT3Oz04zKF2JbWypo8C9rql6SgFGxdWmHASwwhBOH2CXyf9eC/OAAxgSXPjXNjJvbyVAzWe+QBDTfL5c2rv4LOs/LcPAuNEpeH8DSIi3dkmJYL52g5f462i+cJBwIYjCZy15SybP1GCis20G/zcrLrJCe7TlI/UE9MxPBYPNI6yd3G1uyt92z3G/PJMvS3BCXaLx2UmtUoS5vHrRNzlvOpy2aOjY8z8dFHjH1wAP/nn4MQ2EpLSdj3Mu69ex+tI6N/GFpPyOWSluMyygvAlkiX5xmOXjfR2ztKxrISdv7eW+SuWju7H0oxo8R8Efx1/fjO9hLt96NZDNjXpeHclIklz33vG7DRDrj2PlyxL4Z7AAAgAElEQVT5FXTWyHMZZbD2VVjzFUh9/KZ302FWxUXTtOOPOF5QCLFnupOYTZZyKLKux+htvDlpnfS3yCKPruQUitZXsWz9RpJXFnNu+PykoAwEBgBYnbyabTnbqM6tpjS1FJPhzruo2HiYcLvMfg81jxHp8QHxPJPCBGmdFCdiznY9lb3K9XAY79GjjO//AO+xY4hwGHNBPgkv78Pz8ktYix5hzdw/DJfehfp/kZnvCOnkLdgKRdVyyygFgxGh61w7dYwTP/sx3uEhVmzZRvU33yQh/fGboCnmnklr5mwvgYsDiLCOKcOBsyoTx4Z0jM77WKJjnXD1fWnRdHwuz2WUQuWbUPFbsqjnLDHb4hIA/uBhLwP+qxBiQdatXiqWi398jLZLF2g5f47WC7UEJsbRNANZK1axbH0VBRUbGHAF+Lz3c052neRC/wViIobb7OaZ7Gcml7umWiciphPp8RFuGyfUPkG4fXzSZ4LJgLXQgzW+zGXJdS3aPJMnRQhBoK6OsffeZ/zDD9HHxzGmpuJ5cS8J+/ZhKy19+BJgLApNh+H8P8k1dj0ic01WvQxFO2SY8AOWuiLBIGf3/xtn3/8FQuhUvvQam197HYtdNb5abOihKIH6QXxnewl3TIBRw742BefGTFmZ+X4rAGNd0qK5+K/ypsSWCFXfgk1vz0p4+WyLy2EhxPOP8LqPFprlcovFKi63rJPW+lpaLtTS23RTLru4PRRVVFK0vpJofgIXJi5T01tDbW8tExHZTXBl0spJMSlPK5+0TmLeMOG2CULt44Tbxol0eRERmfhlTLBgyffIrcCNJdu1JHqaPAmh5hbG9r/P+Pv7iXR1odntuHd/iYRXXsW5ZfOj1fIauC4F5eK/yuggRwqs+02o+KZMtJsmE0ODnHznJ1w98SmOhES2ff13Wbvz+Xtm/CsWPpFeH76zvfjP96P7ozJvpioTR2XG/cPzhYCOGjjz/0LDBzIEvfRrsOWPZHmeGUL5XB7CYhIX78gwrfV1tF6ope3ieYI+L5pmIHP5CgrLN2AtyeKmpZea/rOc6z3HSGgEgDx3HpsyN8ktaxOp9lREVCfS6yPcMTFpmdwqpYJRw5LtwpLvxlIgBWWp55k8KtGhIZkx//77BC9dko75Z54h4dVXcD//PAbnIyxDBEbh8i/gwj/L7HjNCCu+LAVl+Z4ZKaXS03idoz/5O7pvXCOtcBk7f+c75Jeue+JxFfODiOgErg7iO9tHqHEUNLCWJOKoSMdemnLvIACAkVb4/G+h7qcycbZgGzzzP8powifMb1Li8hAWsrjEohG6bzTQekFaJwNtLQA4E5MoLK8kYVUhXSkBzo3XU9NTM+k3yXBksDlr86SgZDoyiQ4FCHd6iXRMEO6cINztldWCAYPbgvWWkBR4pFVifrqtkqnowSAThw8z/v5+vCdPQiyGdc1qEva9guelFx/umI+GoeucdMg3H5PRPnpE1uSq+CasewNcj+DcnyZCCK6fOcGJn/2Y8YF+SjZuofq3v01SpsrAX8xEhwL4avvwn+8nNhJCMxuwrUnBUZGGbUXSvZeng2NQ94/w+X+TRUeTl0lLZt0bYHs8j8Wcioumab8rhPjptN84w2ia9g3gr4UQD80YW2jiMtrXS9vFOlrr62i/XB+P7DKSvXI1aWtWMZwNF0UTNX1n6fJ2AZBsS2Zz5mY2Zm1kc+ZmskUGkU6vFJHOCcIdXkRQllHRzAbMuS4seW4suW4seW6MidanKiz4UYj09sqeKMdP4Dt9Gt3nw5SZScK+l0l45RWsy5ff/826Lst8tByTgtJ2RvYWQZN+lGU7ZAhp9vo5qScVCYeoO/Aen//yvxOLRqna9xW2fPU3MVuXfqLqUkYIQbhtHP/5fgKXBtH9UQwOE/Z1aTgq0rAU3KM9RSwq/TJn/kbe8BjMMkBkVTyM3f3ogSCzIi6apq2512ngB0KIZ6d7sZlE0zQD8C5QJITY8LDXz7e4hAN+2q9cmhSU0d4eANypaWSXlRLIs3Pd1c/nw7W0jrcC4LF42Ji5UVomnipy/GlEum5bJbExmfWOAcyZzjuExJTmeCqjuB6GCIfx153He+I4vuMnCMUjCE2Zmbiqq/G8+CKOTRvvX3V4rFNmVTcflfW7AnJJktQV0iG/bAcUbpP9TOYJ78gwJ372Y64eP4InLZ1d3/ofKK7cPG/zUcwcIqoTvDGC/0I/wWvDiIiOMcmKoyIdR0Ua5ox7LNd21soos4YPZB4NQO7GuNDse2hI82yJyzjwc6SgTGW3EOL+lQnnAE3TfhuIAX/2KB98rsVF6Dp9LU20XTxPa30d3TeuocdimKxWMletQi9Moj15gprQJW6Myi84h8lBZXolO93Psl5fS9pEAtEeP5Fu72T5FABTig1zXEQseW7MWc4FW3Z+IRDp7sZ7/ATeEyfwnzmD7veD2YyjshLX9u24qrdjKSm5t1UnhGyU1XBA/nP2XJDnPblSSIp2yDtCzzSLTM4BnVcv88mP/j+GOtsprtrMc7/3NgnpGfM9LcUMoYeiBC4P4b/QL/0zAszZTik05WkYE+7ynwoBAw1w7YM7/5ZTV0qhWf2yrEV31//BbInL58CLQoihu84fEEK8NN2L3WP8PwbeBMqAd4QQb055Lhn4EbAHGAT+XAjxs/hzRuCXwGtAzUIRF+/wEK0Xz9MW3wIT4wAk5OVCYTJdqX7OmRpp9cn2uE7NwW7nTrYaKikJF+AZsRLt8SNCMTmgAUxpDizZLsxZTszZTsxZrvvHwiuAuHVSW4v32HG8J04QbpL5P+bsbJzV23FVV+PYtBmj6z5OeT0mo3AaPpCiMiJ9YJN3eytfkuXpF8ESYywape7ge5z++c9AwJav/iZV+76C0aT+hpYSsYkw/voB/Bf6iXR6ZSDAsoR4IEAqBvs9AgFGO2TZmYYPoPUUiBgkF8Omt2TuTNxHM1vi4gF8QojYdAd+pItr2lcBHfgyYL9LXN4BDMDvAxXAAWCrEOKKpmm/B8SEEP+kadq5+RCXaDjMQHsLfU2N9DbfpLfxBkOd7QBY3C60ohS6UgPU2prpQfZ+WEUxu43VlAdXkjGWiGlYgC5//prFOCkgliyXFJIMB5pZWSSPQnRoSIrJ0aP4Tp1C9/nQzGYcGzfivGWdLFt2f59TyCuXuRo+kPkn/kG5Tr1sR1xQXpzWOvVCY3xwgKM/+SE3a06TnJ3L87//h+SXls/3tBSzQGTAj//CAIEL/USHgmDUsK1KlkKzKvneQTz+Yfl3X/tjWQ3A7ITyr8Omt9Ay1sy+Q1/TtHQhRP90L/II434fyL0lLpqmOYERoFQIcSN+7h+BLiHEdzVN+z+B9Uhhegb4iRDif3rQNZ5EXKKRCEMdbfQ23aSv+Sa9zY0MdbTJfumAyWknlu6gJyXIeUcbfU4fJoxsNVSxQ2xmlb+QpAEHml/mkhgcJrmcFbdILNkujMm2p65sypMghCDU0ID36FEmjh4lePESCIEpPR3Xzp24du7AuWULBsd9kgsjAZnp3HJCll3pqpVNtCxuWLFHCkrJbrA9uGvmYqP5/FmO/MPfMtbXy+ptO9nxO7+PM3H+/EOK2UMIQaTTi/9CP/6LA+gTETSrEXtpKo6KtPsnanafh5ofwqWfQyyE9lfjcyIuR4QQu6Z7kUcY925xWQ+cFkLYp7zmfwZ2CCH23fXe+1oumqa9DbwNkJ+fX9nW1vbQucSiUYY62yeFpK+5kYG2VvSYjMKyOJ2Ys5MZTYzRbBvgkqkVry2KR7jYbdzOllgFRRM5OPuNkyHAxhQb1gIP1sIE2QAr7empDDyT6IEAvs8+w3v0GN6jR4n2yQZmtnXrcO3cgXvnTqyrV9/7ZxsNydDgW2LSeRZiYZl7kr1eNm4qqoaCZxdFA6cnIRIOUfOrn3P2vXcxmi1s+/rvUL7nRZWAuYQRuiDUNCotmsuDiFAMg9uMY10ajop0zLmuL/7f+Iag7ido1X82J+LyqRDiuele5BHGvVtctgPvCiEyp7zmLeCbQoid0xz7vrXFIuEQg22t9Lc20dfSRH9LE4PtrcSiUkisTifu3GyCaRa6nGPUG5tpFj1oaJTE8nnO/Czrw6vJGU3FPCRAICO3sl1YC+KteQs9GN1PX9/xmSLS34/3yKdMfHoE/2efI0IhDA4HzmeflRZK9XZMafeJRB/tgKvvwc1fSx9KNBhvpFUOhdvllr9lyVknj8pITxeH//6/0XbxPOmFxXzpO39E1vKV8z0txSwjIjECDfGIs4ZhiAlMqXbs5TK02Zx2p7U/J3kuc2y5nBJCOKa85s+AnXdbLo9K5YYN4r1/+mlcRBrpb21mqKsDoculKpvLTXpRMe7cLAY9Ia6Y2jnpq2U0NEpWJI3KWClbtPUU+3NJGLGjhW/7SiwF7kkxseS572wMpJgWQgjCjY1MHD7CxJEjBC9eBMCcl4fruZ24d+7EXlV1z14oAIy0SUG5+iu51AWywF/RDmmd5D8D9sQ5+jQLHyEENz47xdGf/ADv6Ahlu/aw9fVv4kpamF0RFTOLHogSuDwoI86ax2TEWY4LR3ka9vI0TAnWJScut3wua4UQN+Pnfgp0CyG+O82x9wH7cpMS3vqT3dsAcCUlk15UTHpRMcn5BfS7/ZwLXOZ012lG+wdZESxgXWQl6/U1ZI4nYwrHHWAmTTrbc11YctxYcl0qn2QGELEYgbq6SUGJtMvACFtZGe7nd+HatQvr8uX3X0ocbrktKN3n5bmsClj7Gqx+Zd6bLS0GwgE/p9/9Gec/3I/BZKLyxVfZ+MrXsDpmr9quYmERGw/JiLP6gcmIM0uhh4w/qFh8y2KappkAE/CXQC7wFhAVQkQ1TfsX5ELTd5DRYgeJR4s9zrVWlxSLg+/+K+lFxQwZJjjZdZKz7TVMtA6wYiKflcEiVoWKcEbi2cxGTSYmxoXEnOuS0VtPaUXgmUb3+/GdPs3E4SN4jx4lNjIio7u2bJGC8txzmDPuk5Oh6zJe/8aHUlB66uX57A2w5lW5LaA2sYuJ0d4eTv33f6Lh1DFsLjebX3udii+/jOl+lqJiSRIZDBCoH8Bf30/Wn22cE3HJEEL0TfciDxjve0hhmcpfCSG+F89z+XtgNzAEfPdWnss0r7EP2JezLOetf/8Pf8zQjW6yhpMo9ZdQEszHiAGhCUzpDqx5HpnhnuvCnOl86qsBzyRCCMLNzfhOncZ3+jS+M2ek/8TjwVVdjfv5XTi3b8foukerXl2X7V9bT0LbSRmTHxiWz+VUyhIra16FpIK5/VBLmL6WJk6+8xNa6+twp6Sx9fXfYs2OXcrp/5QhhMBgMMxNbTFN06qFEF9oHqZp2jeEEO9MdwJzxarsZeKT3/0JALpBoOXY8JSkYy1KwJLvxmB7hLLpimkRHRrCd/qMFJPTpyeju8z5+ZOC4qiqQjPfldCn69B3OS4mp+R2q8xKQr4sr1L4rPSjJObN8ad6umi/fJET7/yY3sYbpOTms+3rv0tx1WYV7fgUMWeFKzVNG0BaFP9RCBHRNC0R+FtgvRBixXQnMFeUFawSx390CEdxMpZct6oGPAvogQD+c7WTYhK6fh0AQ0ICzi1bcG7divPZrVhy76ocFIvKApBtp6DttNyCo/K5xIJ4ZNezMkxYWSdzjhCCmzWnOfnOTxnp6SJrxSqqv/EmuWum34dGsfiYS3HJBv4ByAD+H+B7SH/InwohfNOdwGyzlNsczzd6MEjw6tVJQQnU1SHCYVm3a/36STGxrVmDZpyynBINS8f7Lauk/XMIywZnJC+TInJLUBLmtYSdYgp6LMblox9z5t2f4R0ZZtmGjWz7+u+SVqD8W0uZuS65bwc+B9YCPxJCvD3tQeaY+a6KvNgRuk64uZnAxUsELtYTvHiJ4I0bcCsnaMWKSTFxVFbemRkf9suw4LbTUkw6aiAakM+lrZJiUrBV7hdgAUjFnURCQc5/+AE1771LyO9n9badbH39myRmLN7yOIr7M5eWSwXwz8BN4O+A/xs4C/yhEGJ0uhOYbZTl8nhEBwYIXLxIoP4igUsXCV66jO71AmBwubCVlWIvW4e9fB32devuTGSc6IOOz6RF0vGZjObSo4AmW/oWPHtbUJyp8/MBFU9M0Oul5r13OX9oP7FolJVbt7PptddJyy+c76kpZpC5FJch4H8VQvxd/LET+GtgjxBiwXpXleXyYGJeL95Pj+L99Aj+8xeI9sh+M5hM2FaswFa+blJMLEVFt/ud6DoM3oiLSXy7VUXYZJPRXHmbZSZ83qZ57XOimB28w0PUHnyP+o8PEQkGWLZhI5tee4Oclavne2qKGWAuxWWZEKL5HudfEUK8P90JzBVKXL5IdGQE75EjjH/0Ef7TZxCRCKa0NBwbN2IvX4etbB22Nasx2KZ0MoxFoe+SXOJqPQXtp29HcjlS4yKyWWbCZ5XPSJ94xeIg4J3gwq8/oO7QfoIT4+SuLmXTa69TWL5BRZctYuba57Ib+AaQJoTYp2laFeARQhyZ9mBzhBIXSXRggIlPPpGCUnMWYjHM2dm49+zBvWcP9oryO7swxiK3ne+tp6Rlcsv5nlQUX956BvK2yEx49SXy1BMJBrl05Nec/eCXeIcGSS8sZtNrv8HyzVtVnswiZC4tl38H/Hukv+XPhRAJmqatBX4ohNg63QnMNsrnApGuLsY//piJjz8hUFcHQmApKooLym4ZzXVLFISQYcE3PrpdPTjil8+lrpR+ksJt0jJJyJm/D6VY8MSiEa6dOErN+79gpLuTxMwsNr7yNdZUP4/p7twmxYJlLsWlCXheCNGqadqIECIp3hmyXwiRMt0JzBVPk+US8/oI1F8gUFuH9/hxgpcvA2BdtQr3nt14du++s61vNCSF5PohuY13ARpkrL0zkst1n+rDCsUD0PUYjWc/o+ZX79LX3IgrKZnKl15j3e69WGz2hw+gmFfmUlz6gSwhREzTtGEhRLKmaTagRQixYONIl7K4RPr7CdTV4a+tI1BbS7ChQTraDQZsZaV4du/GvXs3loIpCYj+Ybj5kWxz2ngYwl4wO6B4F6zcC8u/rMREMaMIIWi7dIGaX71Lx5WL2Jwu1u99hfV792F3ued7eor7MJfi8nPgvBDif58iLv8LUCGE+K3pTmCuWCricqtGl7+2lkBtHf66OiIdHQBodjv28nIcGzZgr9yAvbwCo90Kvn6Y6JEhwkM35ZJX+xnZM9uVCStfkG18i6rBrO4kFbNP940Gat57l6Zzn2O22anY8yKVL72mumIuQOZSXLKA/UAqkAM0A+PAPiFE73QnMNssZp+LHgoRbmkhdLORUFMjoes3CJw/T2xUphMZU1JwrK/AXpKJI0vDliLQ/H1SRCZ6YKIXfAPI4tJTyCiV1snKvZC1HgyqFI5ifhhoa+HzX73LjTMnMZpMlO7aw8ZXvoonNX2+p6aIM9fRYhqwESgAOoAaIYQ+7YHmkIVsuejh8G0RabxJuKmJ0M1Gwu3tcnkLwGTCUlCAvWwNjgIPjqRxzIEraF21t7Pd0cCZBu5McGeBOyO+z5QWijtTllNxqX9cxcJipKeLmvd+ztXjRwCNNdXPsenV3yApSwWNzDdzKi6LkYUiLrrfT+DiRfx1dYSuNRBqjItILCZfYDRiyc/HWlKCdXkJ1uxkLPYxrNEmtJ4a6LsCQpftejPXybyS/C0yWdGdDUZV3VmxeBkf6Ofs/l9w6chH6NEYK7duZ/Nrr5Oqsv7njVkVF03T/sujDCaE+M/TncBcMV/iEunrJ3Be+kYCtXXS2R6LgaZhKSjAurwES0mJFJOiQiy2cQx956GzBjrOwninHMjshNwqGQKcv0UeW5UTVLE08Y2OcO6DX05m/RdXbWHLV94gs2TBFl5fssy2uPzDlIc24GvIemJtQD6wCfiFEOIb053AXDEX4iJ0ndDNxjvEJNLVBYBms2Fftw77hvXS4V5RgRFfXERqZD5J9wWIheRgnlzI2wi5m6SYZJaBUeUGKJ4uAt4Jzh96n/OH9hP0eSlYt55Nr/4GeWvXqaz/OWIuHfr/ArwrhPjFlHNfBV5/GsUlOjTExMcfM/HppwTOX0AfHwfAmJqKY/167JUbcGzYgG15MdpQw51iMiajvDBaZM/3vE2Qu1HuPdkzPleFYrESDvi58NFBag/8Cv/YKImZWZTu3M2aHbtwJ6vip7PJXIrLGJAshIhNOWcEhoUQCdOdwFwxk+JyS1DGD32I/+xZ0HUsBQU4Nm2aFBNzogWt6+wUq+Q8RINyAE/ObRHJ3QRZ68BknZG5KRRLmUg4xI0zJ7l89GM6r15G0wwUVmyg9LndFFduwmhS1v1MM5fiUgv8RAjx11PO/TvgW0KIDdOdwGwzU6HI9xSUoiI8e1/AvWcP1sQoWvsZ6PhcCspom3yj0SILOOZuur3MpcqmKBRPzEhvN1eOHubKsU/wDg9hd3tYvf05Sp/brcr+zyBzKS7rgV8CJqALmesSBb4qhKib7gTmisexXO4rKF/eg7uyEKuhA639rra87qy7rJJyMNsefCGFQvHY6HqMtvrzXP70YxrPfY4ei5KxbDllu3azcms1Nqdrvqe4qJnrPBczsAXIBnqAM0KIyLQHmkMeRVxEJEKw4TqB8+eZOHx4iqAU4n6mFE+JGWv0GlpnjSyXAvG2vFtv1+BKLFCVgRWKecI/PkbDyaNc+vRjBttbMZktLN+8ldLndpO3puzOit+KR2K2o8X+NyHEf3qE1/2VEOIvpzuJueBe4hLp6ydw4QKB+noC9fUEL19GhGS0lqWoCPe29Xgy+rH2f4gWlo560tfExWQr5G9VbXkVigWIEIK+5kYuf/oxDaeOEfL7cKeksXLrdlZtrSa9qFhFmz0isy0uE8A64GG/jVohxIIsDlRVWSmO/93fSSG5IMXkVrdFzWzGtnYt9vJy7GtXYrd2YGr9N7Se87Kb4tqvwKqXpaA4kuf5kygUiukQCYdorDlDw6ljtNbXocdiJGXlsHJrNau2VpOSu2Ab6C4IZltcdGSBqoeJS1AI4ZjuJKaLpmkZSL9PBIgB3xRC9DzoPaV2h3g3XhXYnJ2NvaICe0U59vJyrKtXYxi8CrU/hkvvyiWvtNVQ9S1Y94ZqzatQLBECE+PcrDnN9dPHab9yCYQgraBoUmgS0jPme4oLjqeq/Es89FkIIXRN094EcoUQ33/QeyrSE8WJ//xtbOXrMOevlMtZVg9cfU+KSs8FMNmh9KtQ+aZ0yiuzWaFYsnhHhrnx2UkaTh+n50YDAFnLV7JqazUrntmOK0mtUsBTJi5TiYdBdwohfvmg11XlmMW5t+5jVKWvlYKy7g2wJ878JBUKxYJmrL+P62dO0HDqGANtLaBp5K0pY9XWaoqrNj/VrQAWpbhomvbHwJtAGfCOEOLNKc8lAz8C9gCDyJbKP5vyfAXwt0AisEcI0faga1VVVYlzJz6G8R6Y6JZ73wAUbpd1upSVolAogKHODq6fOU7DqeOM9HSBppFVsoLiys0UV20mJTf/qQoGWKzi8lVAB74M2O8Sl3cAA/D7QAVwANgqhLhy1xhvALuEEH/woGstlKrICoVicSCEYKCthabaz2k6V0Nfs0zCTsjIlEJTuZmcVWswmpZ2JfK5TKI0zHTvFk3Tvo/0m7wZf+wERoBSIcSN+Ll/BLqEEN/VNM0ihAjHz38Z+LIQ4k8fdA0lLgqF4kmYGB6kufYsTbWf0365nlgkgtXppKiiiuKqzRRVVGJ1OOd7mjPO44rLtCQ37kj3apqWKIQITfdi02AFELslLHHqgR3x4wpN0/4vZKRYEPj2feb7NvA2QH5+/uzNVqFQLHncyamU795L+e69hIMB2i6ep+lcDc11NTScOobBaCR3TRnFlZsp2bgFT2rafE95XpmWuAghYpqm3QBSgO7ZmRIALmDsrnNjgDs+jxqg+mGDCCF+oGlaD7DPYrFUzvgsFQrFU4nFZmf5pq0s37QVXY/Rc+O6XD6rreHTH/8tR3/6Q1ZtrWbTq7/x1DY6e5zFwn8GPtA07b8CnUxp0C6EODJD8/ICnrvOeYCJ6Q4khNgP7K+qqnprJiamUCgUUzEYjOSsWkPOqjVUf/NbjPR0Uf/Jh1z8+BDXTh6luGoLm197nazlK+d7qnPK4/hcWu7zlBBCLHusSdzf57JWCHEzfu6nQLcQ4rvTHHtGqiIrFArFdAhMjHP+w/2Tjc7yS9ex6bU3yC8tX1TRZos1WsyEtJ7+EsgF3gKiQohovCmZAL6DjBY7yD2ixR4V5dBXKBTzQTjg5+InH3LuwK/wjQyTWbycTV95g5LKzYuikOZiFZfvIYVlKn8lhPhePM/l74HdwBDw3al5LtO4hrJcFArFvBMNh7ly7DBn3/85Y/19pOTms+m111m1tRqD0Tjf07svc11yfzfwDSBNCLFP07QqwDODPpcZR1kuCoViIaDHYlw/c4KaX73LYEcbnrQMNr7yNf7/9u49So6yTuP494EQQjJkQkIIECHhAEEuCmIQEbwsxHhFcMEbAsIKuIDirufowgoLRHF1L2ePy8K6UUQI18CCBxZckTUI7II6oICROyQkkpAJuZArgcxv/3hrtOnM9HR3aqp6Os/nnD6ZqeqpetLp6V/e96163wPeN41hw4eXHW8TRd7n8iXgy8APSHfNd0raH/h+RLyr0QBFcXExs1YSPT08+/Cv+dWts1n0zJOM7BzD5AMPZtQOY+nIHqPGjKVjbPqzrMJTZHF5FjgqIuZJWh4RO2T3vyyJiHGNBhhs7hYzs1YWESyY+xgP3XEr3S/MY83y5fRsfH2T540Y1ZEKz9hxjBqzQyo+O4xj9Pid2OOgtw/aTAFFFpclwC7ZPS/LImKspBHA8xHRsitnueViZkNB9PSwbvUq1ixfxurly1i9/GXWLF/O6uXLWFP59Ypl9GzcCMCOu01i2mlnM/HN++Wep934l0sAABHSSURBVJA79DP3AucCl1RsOweY08SxzMysgrbaipGjOxk5upPxk/bo93m9RWjh47/jnqt+wA0Xfo23HDmdd3/2VLbr2L7AxH1rpuWyC3A7sCMwEXgOeAU4OiIW555wM7lbzMza3Yb163jg5ut56I4fM2JUB+896fPs954jc7mfpuirxQQcAuwOLAB+nfdklnlzt5iZtbvu+c/zsx9cxqKnnuBN+x3AtM+fvdnLOBc55jIcOJ90KfKupDnGbgAuiYj1jQYoiouLmW0JoqeHx+bcxX3X/ogN69dzyMeO49A//yTbDN+2qeMVWVyuAPYhjbnMByYB5wHPRESfsxOXyd1iZrYlWrtyBb+45of8/t6f0zlhZ476izPZ46DG5+8tsri8DOwZESsqto0lFZeWXXTaLRcz2xK98LtHufuKy1n+4kKmHPZu/uzk0+gYW/9dI80Wl2YmtlkMVC9Gvx2wqIljmZnZINr9gLdy8j9cyuGfPJHnun7JlV/5Sx7+ye309Gwc1PPW1XKRdGTFt+8ATgAuJU25vxtwNnBdRHxnMELmwS0XM9vSrVi8iLuvuJz5j/6Gzp0msPOeUxg/aQ923H0y4ydNZvtx4ze5wmxQu8VqTLNfqekp94vg4mJmlmYEeOrB/+Xx++ew9IV5rFzy0h/3bTty1B8LzfjdU9GZuM++g3cTZUT0fydPi6sY0C87iplZ6SSxz2FHsM9hRwDw6tq1LF0wn6UvPE/3/Hl0vzCP39/7czasW7d55ylzyv0iueViZlafiOCV7iV0vzCPvQ95ZzHTv0jqJE338jbSWveVgaY3ejwzM2stkujcaQKdO01o+hjNzC12E7A1cCuwee0mMzNrS80Ul3cC4yLitbzDmJlZe2jmPpf7gX3zDmJmZu2jmZbLKcCdkn4JvFS5IyJm5BEqT75azMyseM20XC4h3Tg5Adi74tGSn94RcXtEnNHZ2Vl2FDOzLUYzLZdPA1MiwtO9mJlZn5ppuTwHeDDfzMz61UzLZRZwm6RL2XTM5ee5pDIzsyGtmeJydvbnt6q2B1DI3GKS3gF8l9SC+gNwsi+NNjNrHQ0XlxaZZ2wBcGRErJP098AxwM0lZzIzs0wzLZfSVV1MsAHoKSuLmZltqpm5xfq9lyUi/q7BY32RdN/MW4DrI+KUin1jgSuA6cBS4LyIuK7q5ydl+7/ZyHnNzGxwNdNy2a3q+52B95LmGmvUi6TC8AHSapaVLiO1SiYABwF3SHokIuYCSBpNurjgFI+3mJm1lmbGXE6t3ibpg8BnmjjWLdnPTwXeVHG8UcBxwAERsRq4X9JtwEnAuZKGATcAF0fEk42e18zMBlcz97n05S7g2JyOBTAF2BgRT1VsewTYP/v6M8ChwAWS7pH0qb4OIukMSV2Surq7u3OMZ2ZmtTQz5lJ9ufFI4ATSFVx56QBWVm1bCWwPEBGzSF1iNUXETGAmpMXCcsxnZmY1NDPm8kzV92uB3wKf2/w4f7QaGF21bTSwqtEDeeJKM7PiNTPmkldXWi1PAcMk7R0RT2fbDgTmFnBuMzPbTHUXF0lzSHfh9yci4qhGTp4NzA8jrWy5taQRwOsRsUbSLcAMSaeRrhY7BnhXI8fPQt0O3D516tTTG/1ZMzNrTiMtl2v62T4ROIc09tKo84ELK74/EbgYuAg4C/ghsAR4GTiz9zJkMzNrbYpobpxb0jjgPOB04EZgRkQszDFbLirGXE5/+umnB3y+mZn9iaSHImJqoz/X8PiJpNGSvkEa2J8AHBwRZ7RiYQEvFmZmVoa6i4uk7SSdR1rPZV/giIg4KSKeHbR0OZB0tKSZK1dWX9lsZmaDpe5uMUmLSQPv/wh09fWcVl7PZerUqdHV1WdsMzPrR7PdYo0M6K8nXS12Zj/7C1vPxczMWlvdxSUiJg9ijkHjmyjNzIpXxA2RpfKAvplZ8dq+uJiZWfHavrj4ajEzs+K1fXFxt5iZWfHavriYmVnxXFzMzCx3Li5mZpa7ti8uHtA3Myte2xcXD+ibmRWv7YuLmZkVz8XFzMxy5+JiZma5c3ExM7PctX1x8dViZmbFa/vi4qvFzMyK1/bFxczMiufiYmZmuXNxMTOz3A3J4iKpU9KvJK2WdEDZeczM7I2GZHEB1gIfAW4uO4iZmW1qSBaXiHgtIrrLzmFmZn0rtbhI+qKkLkmvSvpR1b6xkm6VtEbSfEknlBTTzMwaNKzk878IfBP4ALBd1b7LgA3ABOAg4A5Jj0TE3GIjmplZo0ptuUTELRHxY+Dlyu2SRgHHARdExOqIuB+4DTiphJhmZtagVh1zmQJsjIinKrY9Auzf+42kO4HpwPclndLXQSSdkXW7dXV3e4jGzKwoZXeL9acDqJ4MbCWwfe83EfHhgQ4SETOBmQBTp06NPAOamVn/WrXlshoYXbVtNLCq0QN54kozs+K1anF5Chgmae+KbQcCDQ/me+JKM7PilX0p8jBJI4Ctga0ljZA0LCLWALcAMySNknQ4cAwwq4lzuOViZlawslsu5wPrgHOBE7Ovz8/2nUW6PHkJcD1wZjOXIbvlYmZWPEW09zi3pKOBo/faa6/Tn3766bLjmJkNKZIeioipjf5c2S2XQeeWi5lZ8dq+uHjMxcyseG1fXNxyMTMrXtsXFzMzK17bFxd3i5mZFa/ti4u7xczMitf2xcXMzIrX9sXF3WJmZsVr++LibjEzs+K1fXExM7PiubiYmVnuXFzMzCx3bV9cPKBvZla8ti8uHtA3Myte2xcXMzMrnouLmZnlzsXFzMxy5+JiZma5a/vi4qvFzMyK1/bFxVeLmZkVr+2Li5mZFc/FxczMcufiYmZmuXNxMTOz3Lm4mJlZ7lxczMwsdy4uZmaWOxcXMzPLnSKi7AyFkLQKeLLsHJthR2Bp2SE2w1DOP5Szg/OXbajn3ycitm/0h4YNRpIW9WRETC07RLMkdTl/OYZydnD+srVD/mZ+zt1iZmaWOxcXMzPL3ZZUXGaWHWAzOX95hnJ2cP6ybZH5t5gBfTMzK86W1HIxM7OCuLiYmVnuXFzMzCx3bVVcJG0r6QpJ8yWtkvQbSR+q2H+UpCckrZU0R9KkMvNWq5Vf0nBJN0uaJykkva/kuJsYIP87Jf1M0jJJ3ZJukrRL2ZkrDZB/P0ldkpZnj7sl7Vd25koDvf8rnndh9h6aVkbOvgzw2k/O8q6ueFxQduZKdXz2jJR0uaSlklZKurfMvNUGeP0/W/Xar83+Pd5e65htVVxIN4UuAN4LdAIXALOzN+eOwC3ZtrFAF3BjWUH70W/+bP/9wInA4jLC1aFW/h1IV51MBiYBq4ArywhZQ638LwLHk947OwK3ATeUkrJ/A71/kLQn6e+xqIR8tQyYHRgTER3Z4xvFR6xpoPwzSe+dfbM//7r4iDX1mz8irq143TuAs4DngIdrHjEi2voBPAocB5wB/F/F9lHAOuDNZWesJ3/VtoXA+8rO1mz+bPvBwKqy8zX5+g8DzgbWlp2v0fzAT4APA/OAaWXnqyc76T8kAQwrO1OT+fcBXgFGl51pc947FdvnABcO9PPt1nJ5A0kTgCnAXGB/4JHefRGxBng2296SqvIPOQPkf08/21tGX/klrQDWA5cC3yopWl2q80v6BLAhIu4sNVgd+nnvzJe0UNKVWU9Ey6rKfygwH7g46xZ7TNJxpQYcQH+/u9lQwnuAqwc6RtsWF0nbANcCV0XEE0AHsLLqaSuBhidkK0If+YeUWvklvRX4O+CrZWSrR3/5I2IMqdvgi8BvSoo3oOr8kjpIxfCvyk02sD5e+6XAIaTu1LeTfmevLS9hbX3kfxNwAOnzZlfSe+cqSfuWl7J/A3z2nAzcFxHPD3SctiwukrYCZgEbSP+QAKuB0VVPHU3q+28p/eQfMmrll7QXqWvmyxFxXwnxBjTQ65+1er8HXC1pp4LjDaif/BcDs+r5UChTX9kjYnVEdEXE6xHxUrZ9uqTq3+fS9fParwNeA74ZERsi4hekrqXp5aTsXx2fPScDV9VzrLYrLpIEXAFMIPUXvpbtmgscWPG8UcCetFjXTI38Q0Kt/FmT+m7gGxExq6SINTXw+m8FjAQmFpWtHjXyHwWcI2mxpMXAbqQB278pKeomGnjte6cVUSHB6lQj/6PlparfQK+/pMNJLa+b6zpg2YNGgzAI9T3gQaCjavt4UrP0OGAE8B3gwbLz1ps/27dtln0h6X89I8im8GmVR43XfyJpjOurZWdsMv/7gbcBW5NavP9KuoJsRNmZ68w/Dti54rEA+ERf77MWzH4oaVB8q+zvcSMwp+y8DeTfBniGdAXWMOBwUo9JS11MVOuzJ9s/E7i67uOV/RfK+cWZRPpfzXpSN1jv47PZ/mnAE6Rm6j3A5LIzN5h/Xra/8tEyf4da+YELs32V21eXnbmB/J/I3jurgW7gTuCtZWdu5P1T9dx5tNDVYgO89p8BngfWkC6hvhrYuezMjbz2pAuHHsj+Dr8HPl525gbzjwBWAEfVe0xPXGlmZrlruzEXMzMrn4uLmZnlzsXFzMxy5+JiZma5c3ExM7PcubiYmVnuXFzMmiRprnJcV0dprZ6G11iRdIqkjdlaG4XPVyXpYklrsjU+hhV9fmtNLi42JGUfxBuqZ8eV9NvsQ27yYGeIiP0j4p7svBdJumawz1nDA5HW23i86BNHxIW08OziVg4XFxvKnifdvQ2ApLcA25UXx8x6ubjYUDaLNEtrr89Rtc6EpI9kS7a+ImmBpIuq9p+cLe36sqQLKrumstbIbElXZ0u/zpU0teJn50maJumDwN8Cn8q6ph6p3F/x/De0biSdVHHur1fl2krSuZKezfbPljS23hcmO9dNkq7Jsj8maYqk8yQtyV6L6RXPP1XS49lzn5P0harjfU3SIkkvSjotax3uVW8e2/K4uNhQ9iAwWtK+krYGPgVUd02tIRWgMcBHgDMlHQsgaT/gctL8VbuQ1mmpnuX4Y6TljMeQljb+t+oQEfHfpLVSbsy6pg6sfk617Nz/DpxEmml2HGndj17nAMeSlp3dFVgOXDbQcascTSrAO5DWnvkp6Xd+IjAD+I+K5y4BPkqalPNU4F8kHZxl/SDwFdLcfHtlmcxqcnGxoa639fJ+0sSSf6jcGRH3RMRjEdETEY8C1/OnD8fjgdsj4v6I2EBawKx6sr37I+LOiNiYnWvAwlGn44H/ioh7I+JV0oy5PRX7vwB8PSIWZvsvAo5vcMD8voj4aUS8DtxEmhn825GmUr8BmCxpDEBE3BERz0byC+Au4N3ZcT4JXBkRcyNiLWltGLOafGWHDXWzgHuBPehj6VVJhwLfJq0EOJy0bMFN2e5dSVPPAxARayW9XHWIxRVfrwVGSBqWfWBvjupzr6k69yTgVkmVBWcjaa2NNxTQGl6q+HodsDQrkr3fQ1qhdYWkD5Fmrp7Cn9aqeawia1fFsRZgNgC3XGxIi4j5pIH9DwO39PGU60jdWbtFRCdpzYreRaYWUdEVJWk7UvdUU1H62LaG9CHda+eKrxeRFuzqPffIqnMvAD4UEWMqHiMiot7CUjdJ2wL/CfwTMCHSUs530s/rVJnbrD8uLtYOPg8cGWn54WrbA8siYr2kdwAnVOy7GTha0rskDSd19zS7uuFLpG6myt+p3wKflrRNdiHA8VXn/qikI7Jzz+CNv4/fAy7JVu9E0nhJxzSZbSC9Lbpu4PWsFVO5BO9s4NRsbGskqfvQrCYXFxvysrGCrn52nwXMkLSK9KE4u+Ln5gJfIo0/LCKtDrgEeLWJGL1dbS9Lejj7+gLSUtrLSYXruqpzn51tW5Q9Z2HF8b5LanHdlWV/kLQiY+4iYhXpAoLZWY4TsnP37v8JaeXNOaQVFR/IdjXzOtkWwouFmWUkdZBW29s7Ip4vO0+9JJ1EuvJrA3DYYN9Imc0C8Dtg24h4XdKFpKvJtgVGVYzr2BbMxcW2aJKOBv6H1B32z6TWwcHhX4w3kPRx4A5gFHAV0BMRx5abylqZu8VsS3cM8GL22Bv4tAtLn75AGpN5lnTV2pnlxrFW55aLmZnlzi0XMzPLnYuLmZnlzsXFzMxy5+JiZma5c3ExM7Pc/T9U/QA85tWU9wAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "\n", "f = 'COSMOS'\n", "area = 5\n", "for band in [b for b in mag_tables if b.endswith('g')]:\n", " mask = np.isfinite(mag_tables[band][f]['m_'+band])\n", " mags = mag_tables[band][f][mask]['m_'+band]\n", " if not np.sum(mask)==0:\n", " #vz.hist(table[name][mask], bins='scott', label=label, alpha=.5)\n", " h = np.histogram(mags, bins = 100)\n", " bin_width = (np.abs(h[1][5] - h[1][4]) )\n", " #ax.fill_between( h[1][:-1], h[0]/bin_width)#, alpha=0.4)\n", " ax.plot( h[1][:-1], h[0]/bin_width , c=bands_plotting[band])#, alpha=0.4)\n", "\n", "\n", "ax.legend(loc=1, fontsize=8)\n", "\n", "plt.xlim(20.,27.)\n", "plt.xlabel(\"Magnitude [mag]\")\n", "plt.yscale('log')\n", "\n", "#plt.ylim(0.,0.4)\n", "plt.ylabel('Number [dex$^{-1}$]')\n", "\n", "plt.rc('font', family='serif', serif='Times')\n", "plt.rc('text') #, usetex=True)\n", "plt.rc('xtick', labelsize=12)\n", "plt.rc('ytick', labelsize=12)\n", "plt.rc('axes', labelsize=12)\n", "\n", "\n", "#plt.savefig('./figs/numbers_g_en1.pdf', bbox_inches='tight')\n", "#plt.savefig('./figs/numbers_g_en1.png', bbox_inches='tight')" ] }, { "cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "AKARI-NEP\n", "AKARI-SEP\n", "Bootes\n", "CDFS-SWIRE\n", "COSMOS\n", "EGS\n", "ELAIS-N1\n", "ELAIS-N2\n", "ELAIS-S1\n", "GAMA-09\n", "GAMA-12\n", "GAMA-15\n", "HDF-N\n", "Herschel-Stripe-82\n", "Lockman-SWIRE\n", "HATLAS-NGP\n", "SA13\n", "HATLAS-SGP\n", "SPIRE-NEP\n", "SSDF\n", "xFLS\n", "XMM-13hr\n", "XMM-LSS\n" ] } ], "source": [ "for n, f in enumerate(fields):\n", " print(f['name'])" ] }, { "cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [], "source": [ "areas = {}\n", "for band in bands:\n", " areas.update({band: {}})\n", " for n, f in enumerate(fields):\n", " f = f['name']\n", " f_moc = MOC(filename='../../../dmu2/dmu2_field_coverages/{}_MOC.fits'.format(f))\n", " \n", " band_moc = MOC(10,\n", " depth_result[~np.isnan(depth_result['ferr_{}_mean'.format(band)])]['hp_idx_o_10']\n", " )\n", " area = band_moc.intersection( f_moc).area_sq_deg #.flattened(order=10)\n", " areas[band].update({f: area})\n", " \n", "np.save('./data/areas.npy', areas) " ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "\n", "areas = np.load('./data/areas.npy').item()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'mmt_g': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 0.0,\n", " 'EGS': 0.6655336327260426,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 0.0},\n", " 'omegacam_g': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 12.969709611153812,\n", " 'COSMOS': 1.2425480138087197,\n", " 'EGS': 0.0,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 57.80578632331259,\n", " 'GAMA-12': 61.070087406918006,\n", " 'GAMA-15': 60.8652329582364,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 284.82237178600843,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 0.0},\n", " 'suprime_g': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 5.080892346207861,\n", " 'EGS': 1.3302988691704583,\n", " 'ELAIS-N1': 7.9372262306884185,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 19.200839964537668,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 17.710099951763613,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 7.973904346531386,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 14.397850940184703},\n", " 'megacam_g': {'AKARI-NEP': 1.1736997069749913,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 1.1769781977765972,\n", " 'EGS': 3.5654099731654307,\n", " 'ELAIS-N1': 11.312586190198246,\n", " 'ELAIS-N2': 7.911664247719644,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 4.451217206624386,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 133.15283032210607,\n", " 'Lockman-SWIRE': 21.793050433813832,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 18.499038027318857},\n", " 'wfc_g': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 0.0,\n", " 'EGS': 0.0,\n", " 'ELAIS-N1': 12.706354592231047,\n", " 'ELAIS-N2': 7.872732169450572,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 10.851394741966057,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 5.388506990952311,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 0.0},\n", " 'gpc1_g': {'AKARI-NEP': 9.194322547429266,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 11.424874500153253,\n", " 'CDFS-SWIRE': 12.804555637022904,\n", " 'COSMOS': 5.083453667146616,\n", " 'EGS': 3.453070436791646,\n", " 'ELAIS-N1': 13.40385351027275,\n", " 'ELAIS-N2': 9.149704336676157,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 61.99569756776522,\n", " 'GAMA-12': 62.69089129696204,\n", " 'GAMA-15': 61.69679141421254,\n", " 'HDF-N': 0.6714758973039536,\n", " 'Herschel-Stripe-82': 361.8871400591684,\n", " 'Lockman-SWIRE': 21.52949050921597,\n", " 'HATLAS-NGP': 177.69537965468356,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 75.37404032148797,\n", " 'SPIRE-NEP': 0.1280660469377391,\n", " 'SSDF': 0.0,\n", " 'xFLS': 7.439561572288363,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 21.752837695075385},\n", " 'decam_g': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 8.713152795874791,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 12.971246403717068,\n", " 'COSMOS': 4.997137151510578,\n", " 'EGS': 0.0,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 8.998586401289625,\n", " 'GAMA-09': 58.85818187062816,\n", " 'GAMA-12': 41.56383553364322,\n", " 'GAMA-15': 24.088864844057298,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 288.883141228729,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 150.76093847408842,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 111.11589090850397,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 21.75437448763864},\n", " '90prime_g': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 10.841712948817566,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 0.0,\n", " 'EGS': 3.455734210567951,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 39.79324559510081,\n", " 'SA13': 0.2387663379107207,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 6.074582417607165,\n", " 'XMM-13hr': 0.7434490156829628,\n", " 'XMM-LSS': 0.0},\n", " 'sdss_g': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 0.0,\n", " 'EGS': 0.0,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 115.59400198498533,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 0.0},\n", " 'isaac_k': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 0.07540528843694078,\n", " 'COSMOS': 0.0,\n", " 'EGS': 0.0,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 0.0},\n", " 'moircs_k': {'AKARI-NEP': 0.0,\n", " 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176.65543212713033,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 7.080669282350043},\n", " 'newfirm_k': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 9.500963890216987,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 0.0,\n", " 'EGS': 0.04262038042087957,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 0.0},\n", " 'wircs_k': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 0.0,\n", " 'EGS': 0.872078553227228,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 0.0},\n", " 'hawki_k': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 0.052455852825697924,\n", " 'COSMOS': 0.0,\n", " 'EGS': 0.0,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 0.09835472404818361},\n", " 'wircam_ks': {'AKARI-NEP': 0.7835593015838627,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 2.1867533646712825,\n", " 'EGS': 0.5525281529081816,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.46211352377013776,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 10.01041062493531},\n", " 'vista_ks': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 6.897176250297651,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 9.674262864933135,\n", " 'COSMOS': 1.7867774868753359,\n", " 'EGS': 0.0,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 8.514650423121296,\n", " 'GAMA-09': 53.92697312008112,\n", " 'GAMA-12': 56.84626427323628,\n", " 'GAMA-15': 56.599865198928065,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 220.22662610689446,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 211.04700554165365,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 95.05517918846093,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 20.28443240088727},\n", " 'moircs_ks': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 0.0,\n", " 'EGS': 0.14425359527066933,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 0.0},\n", " 'omega2000_ks': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 0.0,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 0.0,\n", " 'EGS': 0.27867171813652025,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 0.0},\n", " 'tifkam_ks': {'AKARI-NEP': 0.0,\n", " 'AKARI-SEP': 0.0,\n", " 'Bootes': 5.208753487470498,\n", " 'CDFS-SWIRE': 0.0,\n", " 'COSMOS': 0.0,\n", " 'EGS': 0.0,\n", " 'ELAIS-N1': 0.0,\n", " 'ELAIS-N2': 0.0,\n", " 'ELAIS-S1': 0.0,\n", " 'GAMA-09': 0.0,\n", " 'GAMA-12': 0.0,\n", " 'GAMA-15': 0.0,\n", " 'HDF-N': 0.0,\n", " 'Herschel-Stripe-82': 0.0,\n", " 'Lockman-SWIRE': 0.0,\n", " 'HATLAS-NGP': 0.0,\n", " 'SA13': 0.0,\n", " 'HATLAS-SGP': 0.0,\n", " 'SPIRE-NEP': 0.0,\n", " 'SSDF': 0.0,\n", " 'xFLS': 0.0,\n", " 'XMM-13hr': 0.0,\n", " 'XMM-LSS': 0.0}}" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "areas" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dim = [4,6]\n", "fig, axes = plt.subplots(dim[1], dim[0], sharex=True, sharey=True)\n", "plt.rcParams.update({'font.size': 12})\n", "\n", "#area_per_pixel = MOC(10, (1234)).area_sq_degrees\n", "for n, f in enumerate(fields):\n", " f = f['name']\n", " \n", " x, y = np.floor_divide(n, dim[0]), np.remainder(n, dim[0])\n", " \n", " \n", " \n", " \n", " for band in [b for b in mag_tables if b.endswith('g')]:\n", " mask = np.isfinite(mag_tables[band][f]['m_'+band])\n", " #mask &= (bands[band][0]['field'] == f)\n", "\n", " \n", " area = areas[band][f]\n", " #area=f_moc.area_sq_deg\n", " mags = mag_tables[band][f][mask]['m_'+band]\n", " if not np.sum(mask)==0:\n", " #vz.hist(table[name][mask], bins='scott', label=label, alpha=.5)\n", " h = np.histogram(mags, bins = 100)\n", " bin_width = (np.abs(h[1][5] - h[1][4]) )\n", " #ax.fill_between( h[1][:-1], h[0]/bin_width)#, alpha=0.4)\n", " axes[x,y].plot( h[1][:-1], h[0]/(bin_width*area), c=bands_plotting[band][1])#, alpha=0.4)\n", "\n", "\n", " \n", " \n", "\n", "\n", " axes[x,y].get_xaxis().set_tick_params(direction='out')\n", " axes[x,y].xaxis.set_ticks_position('bottom')\n", " axes[x,y].tick_params(axis='x', labelsize=8)\n", " axes[x,y].set_xlim(18, 29)\n", " axes[x,y].set_xticks([18,20,22,24,26,28])\n", " axes[x,y].set_ylim(1.e2, 0.5e6)\n", " axes[x,y].set_yscale('log')\n", " \n", " axes[x,y].scatter([-99],[-99], \n", " label=f, \n", " c='w', s=0.0001)\n", " axes[x,y].legend(frameon=False, loc=(-0.2, 0.8)) #, bbox_to_anchor=(0.1, 0.7, 0.2, 0.2)\n", "\n", "\n", "\n", "\n", "for band in [b for b in mag_tables if b.endswith('g')]:\n", " axes[dim[1]-1,dim[0]-1].scatter([-99],[-99], \n", " label=bands_plotting[band][0], \n", " c=bands_plotting[band][1], s=5.)\n", "axes[dim[1]-1,dim[0]-1].legend( prop={'size': 6},ncol=2) \n", " \n", "axes[dim[1]-1,dim[0]-1].tick_params(axis='x', labelsize=8)\n", "#axes[dim[1]-1,dim[0]-1].set_xlabel('band')\n", " \n", "fig.text(0.5, 0.07, '$g$ magnitude [mag]', ha='center')\n", "fig.text(0.04, 0.5, 'Differential $g$ number counts [deg.$^{-2}$ dex$^{-1}$]', va='center', rotation='vertical')\n", "\n", "fig.set_size_inches(10, 12)\n", "fig.subplots_adjust(hspace=0, wspace=0)\n", "\n", "plt.rc('axes', labelsize=12)\n", "plt.savefig('./figs/numbers_g_allfields.pdf', bbox_inches='tight')\n", "plt.savefig('./figs/numbers_g_allfields.png', bbox_inches='tight')" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dim = [4,6]\n", "fig, axes = plt.subplots(dim[1], dim[0], sharex=True, sharey=True)\n", "plt.rcParams.update({'font.size': 12})\n", "\n", "#area_per_pixel = MOC(10, (1234)).area_sq_degrees\n", "for n, f in enumerate(fields):\n", " f = f['name']\n", " \n", " x, y = np.floor_divide(n, dim[0]), np.remainder(n, dim[0])\n", " \n", " f_moc = MOC(filename='../../../dmu2/dmu2_field_coverages/{}_MOC.fits'.format(f))\n", " \n", " \n", " for band in [b for b in mag_tables if not b.endswith('g')]:\n", " mask = np.isfinite(mag_tables[band][f]['m_'+band])\n", " #mask &= (bands[band][0]['field'] == f)\n", " #band_moc = MOC(10,\n", " # depth_result[~np.isnan(depth_result['ferr_{}_mean'.format(band)])]['hp_idx_o_10']\n", " #)\n", " \n", " #area = band_moc.intersection( f_moc) * area_per_pixel #.flattened(order=10)\n", " #area=f_moc.area_sq_deg\n", " area = areas[band][f]\n", " mags = mag_tables[band][f][mask]['m_'+band]\n", " if not np.sum(mask)==0:\n", " #vz.hist(table[name][mask], bins='scott', label=label, alpha=.5)\n", " h = np.histogram(mags, bins = 100)\n", " bin_width = (np.abs(h[1][5] - h[1][4]) )\n", " #ax.fill_between( h[1][:-1], h[0]/bin_width)#, alpha=0.4)\n", " axes[x,y].plot( h[1][:-1], h[0]/(bin_width*area), c=bands_plotting[band][1])#, alpha=0.4)\n", "\n", "\n", " \n", " \n", "\n", "\n", " axes[x,y].get_xaxis().set_tick_params(direction='out')\n", " axes[x,y].xaxis.set_ticks_position('bottom')\n", " axes[x,y].tick_params(axis='x', labelsize=8)\n", " axes[x,y].set_xlim(15, 28)\n", " axes[x,y].set_xticks([16,18,20,22,24,26, 28])\n", " axes[x,y].set_ylim(1.e1, 0.5e6)\n", " axes[x,y].set_yscale('log')\n", " \n", " axes[x,y].scatter([-99],[-99], \n", " label=f, \n", " c='w', s=0.0001)\n", " axes[x,y].legend(frameon=False, loc=(-0.2, 0.8))\n", "\n", "\n", "\n", "\n", "for band in [b for b in mag_tables if not b.endswith('g')]:\n", " axes[dim[1]-1,dim[0]-1].scatter([-99],[-99], \n", " label=bands_plotting[band][0], \n", " c=bands_plotting[band][1], s=5.)\n", "axes[dim[1]-1,dim[0]-1].legend( prop={'size': 6},ncol=2) \n", " \n", "axes[dim[1]-1,dim[0]-1].tick_params(axis='x', labelsize=8)\n", "#axes[dim[1]-1,dim[0]-1].set_xlabel('band')\n", " \n", "fig.text(0.5, 0.07, '$K$ or $Ks$ magnitude [mag]', ha='center')\n", "fig.text(0.04, 0.5, 'Differential $K$ or $Ks$ number counts [deg.$^{-2}$ dex$^{-1}$]', va='center', rotation='vertical')\n", "\n", "fig.set_size_inches(10, 12)\n", "fig.subplots_adjust(hspace=0, wspace=0)\n", "\n", "plt.rc('axes', labelsize=12)\n", "plt.savefig('./figs/numbers_K_allfields.pdf', bbox_inches='tight')\n", "plt.savefig('./figs/numbers_K_allfields.png', bbox_inches='tight')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "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": "3.6.8" } }, "nbformat": 4, "nbformat_minor": 2 }