import mod_HYCOM_utils as MHU
import datetime as DTM
from matplotlib import pyplot as plt
from matplotlib import gridspec as GrdSpc
from mpl_toolkits.axes_grid1 import make_axes_locatable
import os, sys
import numpy as np
PLOT_MOD = False
PLOT_OBS = False
year = 2006
# model data
print('Load model daily files...\n')
ddir = '/work/timill/RealTime_Models/TP4a0.12/expt_01.4/data'
fli1 = mr.file_list(ddir, 'DAILY', '.a')
# monthly averaged conc
print('Load OSISAF monthly files...\n')
osidir = '/work/shared/nersc/OSISAF/'
osipat = 'osisaf-nh_aggregated_ice_concentration_nh_polstere-100'
fli2 = mr.file_list(osidir, osipat, '.nc')
# basemap
gs = GrdSpc.GridSpec(1, 1)
bmap = Fplt.start_HYCOM_map('Arctic')
fig = plt.figure()
ax = fig.add_subplot(gs[0, 0])
dto0 = DTM.datetime(year, 1, 1)
dto0_, idx0 = fli2.nearestDate(dto0)
fobj = MR.nc_getinfo(ncfil)
vobj = 'fice'
idx = 2
else:
# file_object_list
pattern = 'archv'
if 1:
# list of binary files
ddir = FCdir + '/bin'
ext = '.a'
elif 1:
# list of netcdf files
ddir = FCdir + '/netcdf'
ext = '.nc'
fobj = MR.file_list(ddir, pattern, ext)
vobj = 'fice'
# 2nd variable to plot: ice velocity as a quiver plot
vobj2 = MR.make_plot_options('uice',\
vec_opt=3,layer=0,conv_fac=1,wave_mask=False,ice_mask=True,dir_from=True)
# =========================================================================
if 0:
# use imshow for a fast plot
fobj.imshow(vobj, time_index=idx, date_label=2)
elif 0:
# use plot_var for a projected plot
fobj.plot_var(vobj, time_index=idx, date_label=2)
elif 0:
# plot pair of variables
dto = DTM.datetime.strptime(cdate + "12", fmt + "%H")
print('\nObservation date')
print(dto)
print('\n')
FCdays = 6 # length of -ice-only FC's
for ndays in range(FCdays):
# 0,...,5 (days which have daily average files)
fcdate = dto - DTM.timedelta(ndays + .5)
fcdir = FCdir + '/' + fcdate.strftime(fmt) + '/bin'
# print(fcdate)
# print(fcdir)
if os.path.exists(fcdir):
hi = mr.file_list(fcdir, 'DAILY', '.a')
# for i,DT in enumerate(hi.datetimes):
# print(i)
# print(DT)
if dto in hi.datetimes:
# ========================================================
# find index corresponding to observation date
idx = hi.datetimes.index(dto)
# call the AOD routine
odir = outdir + '/FC' + str(ndays) + 'days'
if not os.path.exists(odir):
# don't overwrite sub-dirs
hi.areas_of_disagreement(time_index=idx,\
obs_type='OSISAF',obs_path=None,\
def average_area_model(cdate, vertices, fcdir0, outdir='.'):
# average MIZ area for a given date
# use binary files since more likely to be there
# returns None if nothing there
fcdir = fcdir0 + '/' + cdate + '/'
if not os.path.exists(fcdir):
return
lst = os.listdir(fcdir)
if cdate in lst:
# check if need to add another cdate
fcdir += cdate + '/'
lst = os.listdir(fcdir)
if 'bin' in lst:
bindir = fcdir + 'bin'
else:
bindir = fcdir + 'binaries'
# make file_list object from binary files
# - treat in same way as multi-record netcdf
fli = mr.file_list(bindir, 'archv_wav', '.a')
if fli.number_of_time_records == 0:
return
# loop over 6-h intervals:
daily_areas = []
for hr in range(0, 24, 6):
dto = datetime.datetime(int(cdate[:4]), int(cdate[4:6]),
int(cdate[6:8]), hr)
#print(dto)
if dto in fli.datetimes:
idx = fli.datetimes.index(dto)
out = fli.MIZmap(no_width=True,
vertices=vertices,
time_index=idx,
outdir=outdir)
# out = fli.MIZmap(vertices=vertices,time_index=idx,outdir=outdir)
# sys.exit()
#
tfil = out[out.keys()[0]]
pil = mc.single_file(tfil)
tot_area = 0
for pio in pil.poly_info_objects:
#pio.area # approximate area (Euclidean after projection using NP as center)
#pio.ll_coords #list of coords of boundaries
lon, lat = np.array(pio.ll_coords).transpose()
area = GS.area_polygon_ellipsoid(lon, lat)
# print(area)
tot_area += area
print('\nTot area: ' + str(tot_area) + '\n')
daily_areas.append(tot_area)
if len(daily_areas) == 0:
return
else:
# take daily average
TotArea = np.mean(daily_areas)
print('\nAvg tot area: ' + str(TotArea) + '\n')
return TotArea
ODLmap = pyproj.Proj(ODLsrs) #same as srs="+init=EPSG:3413"
bmap = FP.start_HYCOM_map('Arctic')
if 0:
# ease2 projection (North)
# cf https://nsidc.org/data/ease/versions.html
ease2 = pyproj.Proj("+init=EPSG:6931")
# ease1 = pyproj.Proj("+init=EPSG:3408") # works
# directories
if 0:
#hexagon
odir = '/work/shared/nersc/msc/cersat/' # path to observations
mdir = '/work/timill/RealTime_Models/TP4a0.12/expt_01.5/data' # path to model data
flist = mr.file_list(mdir, 'DAILY', '.a')
else:
mdir = '/mnt/sda1/work/Model-outputs/thickness_comp_ifremer/TP4/2015_060'
odir = '/mnt/sda1/work/Model-outputs/thickness_comp_ifremer/cersat'
flist = mr.file_list(mdir, 'DAILY', '.a', gridpath=mdir + '/../topo')
if 1:
olist = ['cs2_smos_ice_thickness_20150302_20150308.nc']
else:
olist = os.listdir(odir)
# mlon,mlat = flist.get_corners()
Mgrid = flist.create_ESMF_grid()
Mfld = create_field(Mgrid, 'hice')
ofil = olist[-1]
ss = str(its) + ' | ' + str(len(wlist))
fid.write(ss)
fid.close()
# place to save results
outdir = mdir2 + '/' + wdir + '/analysis'
if not os.path.exists(outdir):
os.mkdir(outdir)
outdir += '/MIZmap'
if not os.path.exists(outdir):
os.mkdir(outdir)
else:
continue
flist = MR.file_list(mdir2 + '/' + wdir + '/' + subdir, 'archv_wav',
'.a')
step = 0.5
start_date = flist.datetimes[2].strftime('%Y%m%dT%H%M%SZ')
end_date = flist.datetimes[-1].strftime('%Y%m%dT%H%M%SZ')
# end_date = flist.datetimes[4].strftime('%Y%m%dT%H%M%SZ')
regions = ['gre', 'bar', 'lab', 'beau']
out = flist.MIZmap_all(end_date=end_date,start_date=start_date,step=step,\
outdir=outdir,regions=regions,plotting=plotting)
if 1:
# do 1 week at a time (can do all in parallel)
print('\nExit python\n')
sys.exit()
print('\nExit python\n')
ss = str(its) + ' | ' + str(len(wlist))
fid.write(ss)
fid.close()
# place to save results
outdir = mdir2 + '/' + wdir + '/analysis'
if not os.path.exists(outdir):
os.mkdir(outdir)
else:
continue
outdir += '/AODs'
if not os.path.exists(outdir):
os.mkdir(outdir)
flist = MR.file_list(mdir2 + '/' + wdir + '/' + subdir, 'DAILY', '.a')
regions = ['gre', 'bar', 'lab', 'beau']
obs_type = 'OSISAF'
out = flist.AODs_all(outdir=outdir,
regions=regions,
obs_type=obs_type,
plotting=plotting)
# ============================================
# weekly average of conc anomalies
cdates = []
nlist = []
wt = 1. / 7
anom_av = 0.
if len(opts) == 1:
ddir = rootdir + '/' + ddirs[opts[0]]
else:
print('Usage: ' + me + ' run_name')
print('options for run_name')
for s in ddirs:
d_dir = rootdir + '/' + ddir[s]
print(s + ' = ' + d_dir)
print('\n')
raise ValueError('\n\nNot enough inputs to ' + me + '\n')
# ddir = sys.argv[1]
print('sort files in ' + ddir + '...')
fli = mr.file_list(ddir, 'TP4archv_wav', '.a')
# print(fli.datetimes)
if 0:
# just do a few times for testing
start_date = DTM.strptime('20050831', '%Y%m%d') # +TDEL(0.5)
end_date = DTM.strptime('20050901', '%Y%m%d')
plotting = True
show = False
else:
# do all times
start_date = None
end_date = None
plotting = False
show = False
if not os.path.exists(outdir):
os.mkdir(outdir)
hmax = 4
po = FP.plot_object()
shorts = ['BackThick' ,'CS2' ,'SMOS' ,'AnThick' ,'AnThickErr']
clabs = ['Background Thickness, m','Cryosat-2 thickness, m','SMOS thickness, m','Analysis Thickness, m','Analysis Thickness Error, m']
vlist = ['background_thickness' ,'cs2_thickness' ,'smos_thickness' ,'analysis_thickness' ,'analysis_thickness_err']
ts_data = {'RMSE_both_ice':[],'Bias_both_ice':[],\
'RMSE_either_ice':[],'Bias_either_ice':[]}
for i,ofil in enumerate(olist):
# =======================================================================
# get arrays for later
print(mdir+'/'+Mdir[i])
flist = mr.file_list(mdir+'/'+Mdir[i],'DAILY','.a',gridpath=gridpath)
nci = mr.nc_getinfo(odir+'/'+ofil,lonlat_file=odir+'/'+lonlat_file)
# nci.plot_var('analysis_thickness',clim=[0,hmax])
DOCB = False
if i==0:
olon,olat = nci.get_lonlat()
oX,oY = ODLmap(olon,olat)
mlon,mlat = flist.get_lonlat()
mX,mY = ODLmap(mlon,mlat)
DOCB = True
hobs = nci.get_var('analysis_thickness')
# =======================================================================
# =======================================================================
if PLOT_EG: