# if strongestwind: # for en in ensnames: # for ex in experiments: # outdir, ncdir = get_folders(en,ex) # p.plot_strongest_wind(iwind,fwind,2000,ncdir,outdir,clvs=windlvs) if accum_rain: for en in ensnames: for ex in experiments: for t in times: outdir, ncdir = get_folders(en, ex) p.plot_accum_rain(t, 6, ncdir, outdir, Nlim=42.7, Elim=-94.9, Slim=37.0, Wlim=-101.8) if compute_dte or plot_3D_dte or plot_1D_dte: pfname = 'DTE_' + enstype ofname = enstype pickledir, outdir = get_pickle_dirs(ensnames[0]) path_to_wrfouts = [] for en in ensnames: for ex in experiments: od, fpath = get_folders(en, ex) # print fpath path_to_wrfouts.append(utils.netcdf_files_in(fpath))
import sys import numpy as N #import matplotlib as M #M.use('gtkagg') sys.path.append('/home/jrlawson/gitprojects/WEM') from WEM.postWRF.postWRF import WRFEnviron p = WRFEnviron() outdir = '/home/jrlawson/public_html/bowecho' datadir = '/chinook2/jrlawson/bowecho/20130815/VERIF' reportday = (2013,8,15,23,0,0) # utc = [(2013,8,16,3,m,0) for m in range(0,60,5)] utc = (2013,8,16,3,0,0) ncdir = '/chinook2/jrlawson/bowecho/20130815/GEFSR2/c00/ICBC' # p.plot2D(t,utc=utc,level=2000) p.plot_accum_rain(utc,6,ncdir,outdir,clvs=N.arange(5,85,1)) for t in utc: # R = Radar(t,datadir) # R.plot_radar(outdir,Nlim=42.0,Elim=-92.0,Slim=32.0,Wlim=-102.0) p.plot_radar(t,datadir,outdir,ncdir=ncdir,nct=nct) # SPC = SPCReports(reportday,datadir,torn=False,hail=False)
import sys import numpy as N sys.path.append('/home/jrlawson/gitprojects/WEM') from WEM.postWRF.postWRF import WRFEnviron # Initialise the environment p = WRFEnviron() # output directory outdir = '/home/jrlawson/public_html/bowecho' # netcdf directory. ncdir = '/chinook2/jrlawson/bowecho/20130815/GEFSR2/c00/ICBC' # initial and final times. itime = (2013, 8, 15, 3, 0, 0) ftime = (2013, 8, 15, 3, 0, 0) hourly = 6 times = p.generate_times(itime, ftime, hourly * 60 * 60) # Loop over all times. # clvs lets you change the contour values # The second argument is accumulation time, in hours for t in times: p.plot_accum_rain(t, hourly, ncdir, outdir, clvs=N.arange(5, 85, 1))
windlvs = N.arange(10,31,1) if strongestwind: for en in ensnames: for ex in experiments: outdir, ncdir = get_folders(en,ex) # p.plot_strongest_wind(iwind,fwind,2000,ncdir,outdir,clvs=windlvs) p.plot_strongest_wind(iwind,fwind,2000,ncdir=ncdir,nct=nct,outdir=outdir,clvs=windlvs,dom=1, cmap='jet',cb=True) if accum_rain: for en in ensnames: for ex in experiments: for t in times: outdir, ncdir = get_folders(en,ex) p.plot_accum_rain(t,6,ncdir,outdir, Nlim=42.7,Elim=-94.9,Slim=37.0,Wlim=-101.8 ) if compute_dte or plot_3D_dte or plot_1D_dte or powerspectrum: pfname = 'DTE_' + enstype ofname = enstype pickledir,outdir = get_pickle_dirs(ensnames[0]) path_to_wrfouts = [] for en in ensnames: for ex in experiments: od,fpath = get_folders(en,ex) print fpath path_to_wrfouts.append(utils.netcdf_files_in(fpath)) if compute_dte: p.compute_diff_energy('1D','DTE',path_to_wrfouts,dtetimes,
import sys import numpy as N #import matplotlib as M #M.use('gtkagg') sys.path.append('/home/jrlawson/gitprojects/WEM') from WEM.postWRF.postWRF import WRFEnviron p = WRFEnviron() outdir = '/home/jrlawson/public_html/bowecho' datadir = '/chinook2/jrlawson/bowecho/20130815/VERIF' reportday = (2013, 8, 15, 23, 0, 0) # utc = [(2013,8,16,3,m,0) for m in range(0,60,5)] utc = (2013, 8, 16, 3, 0, 0) ncdir = '/chinook2/jrlawson/bowecho/20130815/GEFSR2/c00/ICBC' # p.plot2D(t,utc=utc,level=2000) p.plot_accum_rain(utc, 6, ncdir, outdir, clvs=N.arange(5, 85, 1)) for t in utc: # R = Radar(t,datadir) # R.plot_radar(outdir,Nlim=42.0,Elim=-92.0,Slim=32.0,Wlim=-102.0) p.plot_radar(t, datadir, outdir, ncdir=ncdir, nct=nct) # SPC = SPCReports(reportday,datadir,torn=False,hail=False)
import sys import numpy as N sys.path.append('/home/jrlawson/gitprojects/WEM') from WEM.postWRF.postWRF import WRFEnviron # Initialise the environment p = WRFEnviron() # output directory outdir = '/home/jrlawson/public_html/bowecho' # netcdf directory. ncdir = '/chinook2/jrlawson/bowecho/20130815/GEFSR2/c00/ICBC' # initial and final times. itime = (2013,8,15,3,0,0) ftime = (2013,8,15,3,0,0) hourly = 6 times = p.generate_times(itime,ftime,hourly*60*60) # Loop over all times. # clvs lets you change the contour values # The second argument is accumulation time, in hours for t in times: p.plot_accum_rain(t,hourly,ncdir,outdir,clvs=N.arange(5,85,1))