#!/usr/bin/env python import sys sys.path.append('../../') import os import numpy as np import string import datetime as dt import logging import re import da.tools.io4 as io fontsize = 10 def nice_lat(cls): # # Convert latitude from decimal to cardinal # if cls > 0: h = 'N' else: h = 'S' dec, deg = np.math.modf(cls) return string.strip('%2d %2d\'%s' % (abs(deg), round(abs(60 * dec), 0), h)) def nice_lon(cls): # # Convert longitude from decimal to cardinal # if cls > 0: h = 'E' else: h = 'W' dec, deg = np.math.modf(cls) return string.strip('%3d %2d\'%s' % (abs(deg), round(abs(60 * dec), 0), h)) def nice_alt(cls): # # Reformat elevation or altitude # return string.strip('%10.1f masl' % round(cls, -1)) def summarize_obs(dacycle, printfmt='html'): """*************************************************************************************** Call example: python summarize_obs.py Option printfmt : [tex,scr,html] print summary table in latex, terminal, or html format Other options are all those needed to create a dacycle object OR: call directly from a python script as: q=summarize_obs(dacycle,printfmt='html') ***************************************************************************************""" sumdir = os.path.join(dacycle['dir.analysis'], 'summary') if not os.path.exists(sumdir): logging.info("Creating new directory " + sumdir) os.makedirs(sumdir) mrdir = os.path.join(dacycle['dir.analysis'], 'data_molefractions') if not os.path.exists(mrdir): logging.error("Input directory does not exist (%s), exiting... " % mrdir) return None mrfiles = os.listdir(mrdir) infiles = [os.path.join(mrdir, f) for f in mrfiles if f.endswith('.nc')] if printfmt == 'tex': print '\\begin{tabular*}{\\textheight}{l l l l r r r r}' print 'Code & Name & Lat, Lon, Elev & Lab & N (flagged) & $\\sqrt{R}$ &Inn \\XS &Bias\\\\' print '\hline\\\\ \n\multicolumn{8}{ c }{Semi-Continuous Surface Samples}\\\\[3pt] ' fmt = '%8s & ' + ' %55s & ' + '%20s &' + '%6s &' + ' %4d (%d) & ' + ' %5.2f & ' + ' %5.2f & ' + '%+5.2f \\\\' elif printfmt == 'html': tablehead = \ "<TR>\n <TH> Site code </TH> \ <TH> Sampling Type </TH> \ <TH> Lab. </TH> \ <TH> Country </TH> \ <TH> Lat, Lon, Elev. (m ASL) </TH> \ <TH> No. Obs. Avail. </TH> \ <TH> √R (μmol mol<sup>-1</sup>) </TH> \ <TH> √HPH (μmol mol<sup>-1</sup>) </TH> \ <TH> H(x)-y (μmol mol<sup>-1</sup>) </TH> \ <TH> H(x)-y (JJAS) (μmol mol<sup>-1</sup>) </TH> \ <TH> H(x)-y (NDJFMA) (μmol mol<sup>-1</sup>) </TH> \n \ </TR>\n" fmt = """<TR> \n \ <TD><a href='javascript:LoadCO2Tseries("%s")'>%s </a></TD>\ <TD>%s</TD>\ <TD>%s</TD>\ <TD>%40s</TD>\ <TD>%s</TD>\ <TD>%d</TD>\ <TD>%+5.2f</TD>\ <TD>%+5.2f</TD>\ <TD>%+5.2f±%5.2f</TD>\ <TD>%+5.2f±%5.2f</TD>\ <TD>%+5.2f±%5.2f</TD>\n \ </TR>\n""" elif printfmt == 'scr': print 'Code Site NObs flagged R Inn X2' fmt = '%8s ' + ' %55s %s %s' + ' %4d ' + ' %4d ' + ' %5.2f ' + ' %5.2f' table = [] for infile in infiles: #logging.debug( infile ) f = io.CT_CDF(infile, 'read') date = f.get_variable('time') obs = f.get_variable('value') * 1e6 mdm = f.get_variable('modeldatamismatch') * 1e6 simulated = f.get_variable('modelsamplesmean_forecast') * 1e6 simulated_std = f.get_variable('modelsamplesstandarddeviation_forecast') * 1e6 pydates = [dt.datetime(1970, 1, 1) + dt.timedelta(seconds=int(d)) for d in date] summer = [i for i, d in enumerate(pydates) if d.month in [6, 7, 8, 9] ] winter = [i for i, d in enumerate(pydates) if d.month in [11, 12, 1, 2, 3, 4] ] diff = ((simulated - obs).mean()) diffsummer = ((simulated - obs).take(summer).mean()) diffwinter = ((simulated - obs).take(winter).mean()) diffstd = ((simulated - obs).std()) diffsummerstd = ((simulated - obs).take(summer).std()) diffwinterstd = ((simulated - obs).take(winter).std()) location = nice_lat(f.site_latitude) + ', ' + nice_lon(f.site_longitude) + ', ' + nice_alt(f.site_elevation) if printfmt == 'html': ss = (f.site_code.upper(), f.site_code.upper(), f.dataset_project, f.lab_abbr, f.site_country, location, len(np.ma.compressed(mdm)), mdm.mean(), np.sqrt((simulated_std ** 2).mean()), diff, diffstd, diffsummer, diffsummerstd, diffwinter, diffwinterstd) table.append(ss) f.close() if printfmt == 'tex': saveas = os.path.join(sumdir, 'site_table.tex') f = open(saveas, 'w') elif printfmt == 'html': saveas = os.path.join(sumdir, 'site_table.html') f = open(saveas, 'w') txt = "<meta http-equiv='content-type' content='text/html;charset=utf-8' />\n" f.write(txt) txt = "<table border=1 cellpadding=2 cellspacing=2 width='100%' bgcolor='#EEEEEE'>\n" f.write(txt) f.write(tablehead) for i, ss in enumerate(table): f.write(fmt % ss) if (i + 1) % 15 == 0: f.write(tablehead) if printfmt == 'tex': f.write('\cline{2-8}\\\\') f.write('\hline \\\\') f.write('\end{tabular*}') else: txt = "\n</table>" f.write(txt) f.close() logging.info("File written with summary: %s" % saveas) def summarize_stats(dacycle): """ Summarize the statistics of the observations for this cycle This includes X2 statistics, RMSD, and others for both forecast and final fluxes """ sumdir = os.path.join(dacycle['dir.analysis'], 'summary') if not os.path.exists(sumdir): logging.info("Creating new directory " + sumdir) os.makedirs(sumdir) # get forecast data from optimizer.ddddd.nc startdate = dacycle['time.start'] dacycle['time.sample.stamp'] = "%s" % (startdate.strftime("%Y%m%d"),) infile = os.path.join(dacycle['dir.output'], 'optimizer.%s.nc' % dacycle['time.sample.stamp']) if not os.path.exists(infile): logging.error("File not found: %s" % infile) raise IOError f = io.CT_CDF(infile, 'read') sites = f.get_variable('sitecode') y0 = f.get_variable('observed') * 1e6 hx = f.get_variable('modelsamplesmean_prior') * 1e6 dF = f.get_variable('modelsamplesdeviations_prior') * 1e6 HPHTR = f.get_variable('totalmolefractionvariance').diagonal() * 1e6 * 1e6 R = f.get_variable('modeldatamismatchvariance').diagonal() * 1e6 * 1e6 flags = f.get_variable('flag') f.close() HPHT = dF.dot(np.transpose(dF)).diagonal() / (dF.shape[1] - 1.0) rejected = (flags == 2.0) sitecodes = [string.join(s.compressed(), '').strip() for s in sites] # calculate X2 per observation for this time step x2 = [] for i, site in enumerate(sitecodes): x2.append((y0[i] - hx[i]) ** 2 / HPHTR[i]) x2 = np.ma.masked_where(HPHTR == 0.0, x2) # calculate X2 per site saveas = os.path.join(sumdir, 'x2_table_%s.html' % dacycle['time.sample.stamp']) logging.info("Writing HTML tables for this cycle (%s)" % saveas) f = open(saveas, 'w') txt = "<meta http-equiv='content-type' content='text/html;charset=utf-8' />\n" f.write(txt) txt = "<table border=1 cellpadding=2 cellspacing=2 width='100%' bgcolor='#EEEEEE'>\n" f.write(txt) tablehead = \ "<TR>\n <TH> Site code </TH> \ <TH> N<sub>obs</sub> </TH> \ <TH> N<sub>rejected</sub> </TH> \ <TH> √R (μmol mol<sup>-1</sup>) </TH> \ <TH> √HPH<sup>T</sup> (μmol mol<sup>-1</sup>) </TH> \ <TH> H(x)-y (μmol mol<sup>-1</sup>) </TH> \n \ <TH> X2 </TH> \n \ </TR>\n" fmt = """<TR> \n \ <TD>%s</TD>\ <TD>%d</TD>\ <TD>%d</TD>\ <TD>%+5.2f</TD>\ <TD>%+5.2f</TD>\ <TD>%+5.2f±%5.2f</TD>\ <TD>%5.2f</TD>\n \ </TR>\n""" f.write(tablehead) set_sites = set(sitecodes) set_sites = np.sort(list(set_sites)) for i, site in enumerate(set_sites): sel = [i for i, s in enumerate(sitecodes) if s == site] ss = (site, len(sel), rejected.take(sel).sum(), np.sqrt(R.take(sel)[0]), np.sqrt(HPHT.take(sel).mean()), (hx - y0).take(sel).mean(), (hx - y0).take(sel).std(), x2.take(sel).mean(),) #print site,sel,x2.take(sel) f.write(fmt % ss) if (i + 1) % 15 == 0: f.write(tablehead) txt = "\n</table>" f.write(txt) f.close() # Now summarize for each site across time steps if not dacycle['time.start'] >= dt.datetime(2008, 12, 29): return logging.info("Writing HTML tables for each site") for site in set_sites: saveas = os.path.join(sumdir, '%s_x2.html' % site) f = open(saveas, 'w') logging.debug(saveas) txt = "<meta http-equiv='content-type' content='text/html;charset=utf-8' />\n" f.write(txt) txt = "<table border=1 cellpadding=2 cellspacing=2 width='100%' bgcolor='#EEEEEE'>\n" f.write(txt) tablehead = \ "<TR>\n <TH> From File </TH> \ <TH> Site </TH> \ <TH> N<sub>obs</sub> </TH> \ <TH> N<sub>rejected</sub> </TH> \ <TH> √R (μmol mol<sup>-1</sup>) </TH> \ <TH> √HPH<sup>T</sup> (μmol mol<sup>-1</sup>) </TH> \ <TH> H(x)-y (μmol mol<sup>-1</sup>) </TH> \n \ <TH> X2 </TH> \n \ </TR>\n" f.write(tablehead) files = os.listdir(sumdir) x2_files = [fil for fil in files if fil.startswith('x2')] for htmlfile in x2_files: lines = grep(site, os.path.join(sumdir, htmlfile)) for line in lines: f.write('<TR>\n') f.write('<TD>' + htmlfile + '</TD>') f.write(line + '\n') f.write('</TR>\n') txt = "\n</table>" f.write(txt) f.close() def grep(pattern, fil): fileObj = open(fil, 'r') r = [] for line in fileObj: if re.search(pattern, line): r.append(line) return r # main body if called as script if __name__ == '__main__': # started as script from da.tools.initexit import CycleControl from da.carbondioxide.dasystem import CO2DaSystem sys.path.append('../../') logging.root.setLevel(logging.DEBUG) dacycle = CycleControl(args={'rc':'../../ctdas-od-gfed2-glb6x4-obspack-full.rc'}) dacycle.initialize() dacycle.parse_times() dasystem = CO2DaSystem('../rc/carbontracker_ct09_opf.rc') dasystem.initialize() dacycle.dasystem = dasystem q = summarize_obs(dacycle) while dacycle['time.start'] < dacycle['time.finish']: q = summarize_stats(dacycle) dacycle.advance_cycle_times() sys.exit(0)