From 6097198d9b87e859bee8cecda314b9b0183e1fcd Mon Sep 17 00:00:00 2001 From: kponder Date: Tue, 8 Nov 2016 09:40:59 -0500 Subject: [PATCH] Complete function to generate mock data sets --- Generate_Mock_Lightcurves.ipynb | 643 +++++++++++++++++--------------- 1 file changed, 334 insertions(+), 309 deletions(-) diff --git a/Generate_Mock_Lightcurves.ipynb b/Generate_Mock_Lightcurves.ipynb index 3291302..a24cbae 100644 --- a/Generate_Mock_Lightcurves.ipynb +++ b/Generate_Mock_Lightcurves.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 95, "metadata": { "collapsed": false }, @@ -11,7 +11,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "Neural networks not available in this version of scikit-learn. Neural networks are available from development version 0.18.\n" + "The autoreload extension is already loaded. To reload it, use:\n", + " %reload_ext autoreload\n" ] } ], @@ -62,7 +63,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 96, "metadata": { "collapsed": true }, @@ -73,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 97, "metadata": { "collapsed": false }, @@ -84,7 +85,7 @@ "1" ] }, - "execution_count": 36, + "execution_count": 97, "metadata": {}, "output_type": "execute_result" } @@ -108,7 +109,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 98, "metadata": { "collapsed": true }, @@ -120,7 +121,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 99, "metadata": { "collapsed": false }, @@ -140,7 +141,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 100, "metadata": { "collapsed": true }, @@ -152,7 +153,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 101, "metadata": { "collapsed": false }, @@ -166,7 +167,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 102, "metadata": { "collapsed": false, "scrolled": false @@ -952,7 +953,7 @@ "data": { "text/html": [ "<Table length=103>\n", - "\n", + "
\n", "\n", "\n", "\n", @@ -1006,7 +1007,7 @@ " 133.879 desz 19.26 5.441 27.5 ab" ] }, - "execution_count": 8, + "execution_count": 102, "metadata": {}, "output_type": "execute_result" } @@ -1033,7 +1034,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 103, "metadata": { "collapsed": false }, @@ -1046,7 +1047,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 104, "metadata": { "collapsed": true }, @@ -1059,7 +1060,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 105, "metadata": { "collapsed": false }, @@ -1072,7 +1073,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 106, "metadata": { "collapsed": false }, @@ -1083,7 +1084,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 107, "metadata": { "collapsed": false }, @@ -1094,7 +1095,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 108, "metadata": { "collapsed": false }, @@ 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+1375,7 @@ "True" ] }, - "execution_count": 16, + "execution_count": 109, "metadata": {}, "output_type": "execute_result" } @@ -1385,7 +1386,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 110, "metadata": { "collapsed": false }, @@ -1396,7 +1397,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 111, "metadata": { "collapsed": false }, @@ -1404,7 +1405,8 @@ { "data": { "text/plain": [ - "['_Dataset__on_press',\n", + "['_Dataset__ind',\n", + " '_Dataset__on_press',\n", " '_Dataset__plot_this',\n", " '__doc__',\n", " '__init__',\n", @@ -1420,6 +1422,7 @@ " 'object_names',\n", " 'plot_all',\n", " 'plot_lc',\n", + " 'plot_model',\n", " 'reduced_chi_squared',\n", " 'rootdir',\n", " 'set_model',\n", @@ -1427,7 +1430,7 @@ " 'survey_name']" ] }, - "execution_count": 44, + "execution_count": 111, "metadata": {}, "output_type": "execute_result" } @@ -1438,7 +1441,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 112, "metadata": { "collapsed": false }, @@ -1478,7 +1481,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 113, "metadata": { "collapsed": false }, @@ -1491,7 +1494,21 @@ }, { "cell_type": "code", - "execution_count": 93, + "execution_count": 139, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "#for i in range(0,len(data)):\n", + "# print i, np.where(data[i].split()[0]==\"FLUXCALERR:\")\n", + "# MJD FLT FIELD FLUXCAL FLUXCALERR SNR MAG MAGERR SIM_MAG\n", + "test_table_II.rename_column( 'MJD','mjd')" + ] + }, + { + "cell_type": "code", + "execution_count": 122, "metadata": { "collapsed": false }, @@ -1500,7 +1517,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "['FILTERS:', 'griz']\n" + " ['FILTERS:', 'griz']\n" ] } ], @@ -1514,13 +1531,21 @@ " survey = data[0].split()\n", " stuffRA = data[6].split()\n", " stuffDec = data[7].split()\n", - " table.meta = {survey[0][:-1]: survey[1], stuffRA[0][:-1]: stuffRA[1], stuffDec[0][:-1]: stuffDec[1],filters[0][:-1]: filters[1]}\n", + " MWEBV = data[11].split()\n", + " table.meta = {survey[0][:-1]: survey[1], stuffRA[0][:-1]: stuffRA[1], stuffDec[0][:-1]: stuffDec[1],filters[0][:-1]: filters[1],\n", + " MWEBV[0][:-1]: MWEBV[1]}\n", + " table.rename_column('mjd', 'MJD')\n", + " table.rename_column('filter ', 'MJD')\n", + " table.rename_column('flux', 'MJD')\n", + " table.rename_column('flux_error', 'MJD')\n", + " table.rename_column('zp', 'MJD')\n", + " table.rename_column('zpsys', 'MJD')\n", " sncosmo.write_lc(table, 'name.txt', format = 'snana')" ] }, { "cell_type": "code", - "execution_count": 94, + "execution_count": 123, "metadata": { "collapsed": false }, @@ -1529,45 +1554,45 @@ "name": "stdout", "output_type": "stream", "text": [ - " mjd filter flux flux_error zp zpsys\n", - "--------------- ------ ------- ---------- ---- -----\n", - " 0.0 desg -1.628 10.48 27.5 ab\n", - "0.0160000000033 desr -12.65 7.845 27.5 ab\n", - "0.0320000000065 desi -10.86 9.314 27.5 ab\n", - " 0.977000000006 desz -4.156 5.328 27.5 ab\n", - " 1.985 desg -2.024 3.205 27.5 ab\n", - " 2.0 desr 0.0281 2.425 27.5 ab\n", - " 2.016 desi 0.3376 4.31 27.5 ab\n", - " 9.957 desz -6.591 27.32 27.5 ab\n", - " 10.106 desg 3.678 25.57 27.5 ab\n", - " 10.121 desr -1.047 4.152 27.5 ab\n", - " ... ... ... ... ... ...\n", - " 113.868 desr 1.241 4.828 27.5 ab\n", - " 113.957 desi 14.87 5.61 27.5 ab\n", - " 113.965 desz 13.31 5.166 27.5 ab\n", - " 125.817 desg -0.2672 2.48 27.5 ab\n", - " 125.821 desr 2.634 1.659 27.5 ab\n", - " 125.836 desi 5.357 2.513 27.5 ab\n", - " 125.852 desz 9.238 3.94 27.5 ab\n", - " 133.821 desg -0.5652 7.568 27.5 ab\n", - " 133.832 desr 1.952 2.963 27.5 ab\n", - " 133.856 desi 0.3662 5.022 27.5 ab\n", - " 133.879 desz 19.26 5.441 27.5 ab\n", + " mjd filter flux flux_error zp zpsys\n", + "--------------- ------ --------------- ---------- ---- -----\n", + " 0.0 desg -14.720074909 10.48 27.5 ab\n", + "0.0160000000033 desr -10.0200738069 7.845 27.5 ab\n", + "0.0320000000065 desi 15.8283821719 9.314 27.5 ab\n", + " 0.977000000006 desz -1.54473523767 5.328 27.5 ab\n", + " 1.985 desg -2.07808996718 3.205 27.5 ab\n", + " 2.0 desr -2.68677401212 2.425 27.5 ab\n", + " 2.016 desi -3.0445893869 4.31 27.5 ab\n", + " 9.957 desz 14.1105912517 27.32 27.5 ab\n", + " 10.106 desg -17.7926700123 25.57 27.5 ab\n", + " 10.121 desr 3.18628290331 4.152 27.5 ab\n", + " ... ... ... ... ... ...\n", + " 113.868 desr -2.87035155679 4.828 27.5 ab\n", + " 113.957 desi 12.558242454 5.61 27.5 ab\n", + " 113.965 desz 11.8116159538 5.166 27.5 ab\n", + " 125.817 desg 1.54318656796 2.48 27.5 ab\n", + " 125.821 desr 2.98782795663 1.659 27.5 ab\n", + " 125.836 desi 4.47720426145 2.513 27.5 ab\n", + " 125.852 desz 11.0274173635 3.94 27.5 ab\n", + " 133.821 desg -17.7641729991 7.568 27.5 ab\n", + " 133.832 desr -0.163720929295 2.963 27.5 ab\n", + " 133.856 desi 2.35875326448 5.022 27.5 ab\n", + " 133.879 desz 25.5197080048 5.441 27.5 ab\n", "Length = 103 rows\n" ] }, { "ename": "ValueError", - "evalue": "Missing required metadata kw: MWEBV", + "evalue": "Missing required column name: FLUXCALERR", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest_table_II\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0mtest_table_II\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mmake_new_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m \u001b[0;34m,\u001b[0m \u001b[0mtest_table_II\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m\u001b[0m in \u001b[0;36mmake_new_data\u001b[0;34m(filename, table)\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0mstuffDec\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m7\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mtable\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmeta\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0msurvey\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0msurvey\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstuffRA\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstuffRA\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstuffDec\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstuffDec\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mfilters\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mfilters\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0msncosmo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite_lc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'name.txt'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mformat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'snana'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest_table_II\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0mtest_table_II\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mmake_new_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m \u001b[0;34m,\u001b[0m \u001b[0mtest_table_II\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m\u001b[0m in \u001b[0;36mmake_new_data\u001b[0;34m(filename, table)\u001b[0m\n\u001b[1;32m 11\u001b[0m table.meta = {survey[0][:-1]: survey[1], stuffRA[0][:-1]: stuffRA[1], stuffDec[0][:-1]: stuffDec[1],filters[0][:-1]: filters[1],\n\u001b[1;32m 12\u001b[0m MWEBV[0][:-1]: MWEBV[1]}\n\u001b[0;32m---> 13\u001b[0;31m \u001b[0msncosmo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite_lc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'name.txt'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mformat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'snana'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m//anaconda/lib/python2.7/site-packages/sncosmo/io.pyc\u001b[0m in \u001b[0;36mwrite_lc\u001b[0;34m(data, fname, format, **kwargs)\u001b[0m\n\u001b[1;32m 715\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict_to_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 716\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'w'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 717\u001b[0;31m \u001b[0mWRITERS\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmeta\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 718\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 719\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m//anaconda/lib/python2.7/site-packages/sncosmo/io.pyc\u001b[0m in \u001b[0;36m_write_snana\u001b[0;34m(f, data, meta, **kwargs)\u001b[0m\n\u001b[1;32m 617\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mSNANA_REQUIRED_META\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 618\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mkeys_as_written\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 619\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Missing required metadata kw: '\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 620\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 621\u001b[0m \u001b[0;31m# Get column names and data length\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mValueError\u001b[0m: Missing required metadata kw: MWEBV" + "\u001b[0;32m//anaconda/lib/python2.7/site-packages/sncosmo/io.pyc\u001b[0m in \u001b[0;36m_write_snana\u001b[0;34m(f, data, meta, **kwargs)\u001b[0m\n\u001b[1;32m 635\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mSNANA_REQUIRED_COLUMN\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 636\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mkeys_to_write\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 637\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Missing required column name: '\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 638\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 639\u001b[0m \u001b[0;31m# Write the header\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: Missing required column name: FLUXCALERR" ] } ],
mjdfilterfluxflux_errorzpzpsys
float64str4float64float64float64str2
0.0desg-1.62810.4827.5ab