figdir = 'time_series/figs/FC'
DO_DATA_COMP = 0
data_comp_str = [psubdirs[1],psubdirs[-1]]
# data_comp_str = [psubdirs[1],psubdirs[2]]
# continue
else:
# compare the persistence FCs too
psubdirs = ['FC0days','FC2days','PFC1days','PFC2days']
figdir = 'time_series/figs/PFC'
DO_DATA_COMP = 0
data_comp_str = [psubdirs[1],psubdirs[-1]]
# continue
for sdir in subdirs:
tsU = mr.read_time_series('time_series/Model_Underest_'+sdir+'.txt')
tsO = mr.read_time_series('time_series/Model_Overest_'+sdir+'.txt')
tsB = 'time_series/Model_Bias_'+sdir+'.txt'
# ============================================================
# get last time series (bias) from over & under time series
dates = tsU.dates
areaU = tsU.data[akey]
areaO = tsO.data[akey]
areaT = areaU+areaO
data = {akey:areaT}
for wkey in Bfields:
# get weighted avg for 2 mean widths
widU = tsU.data[wkey]
widO = tsO.data[wkey]
print('\n')
# =============================================================
for wdir in wlist:
# loop over weeks
its += 1
# place to get results
outdir = mdir2 + '/' + wdir + '/analysis/MIZmap/time_series/'
if not os.path.exists(outdir):
continue
olist = os.listdir(outdir)
for ofil in olist:
if (reg in ofil):
O_ts = MR.read_time_series(outdir + ofil)
continue
W_miz = O_ts.data['Mean_intersecting_width']
W_miz[np.isnan(W_miz)] = 0. # should change some nans to 0?
tdays = []
for i, date in enumerate(O_ts.dates):
dt = date - refdate
ti = dt.total_seconds() * tfac
tdays.append(ti)
Tmin = min(Tmin, ti)
Tmax = max(Tmax, ti)
# =================================================================
# write to file:
"""
srs='+proj=stere +lat_0=90 +lat_ts=70 +lon_0=-45'+\
' +k=1 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs'
"""
# directories
compname = os.getenv('HOSTNAME')
if 'hexagon' in compname:
#hexagon
HEX = True
mdir = '/work/timill/RealTime_Models/results_hindcasts/TP4a0.12/wavesice_erai2/'
gridpath = None
# make time series plots
figdir = 'out/'
tso1 = mr.read_time_series(figdir + '/thickness_error_winter1.txt')
tso2 = mr.read_time_series(figdir + '/thickness_error_winter2.txt')
vlist = ['Bias_either_ice', 'RMSE_either_ice']
figs = ['thickness_error_winter1.png', 'thickness_error_winter2.png']
legs = ['Bias', 'RMSE']
refdate = dtm.datetime(2015, 1, 1)
tfac = 1. / (24 * 3600) # seconds to days
xticks = []
xtlabs = []
for i in range(1, 13):
xticks.append((dtm.datetime(2015, i, 1) - refdate).total_seconds() * tfac)
xtlabs.append(dtm.datetime(2015, i, 1).strftime('%Y%m%d'))
xticks.append((dtm.datetime(2015, i, 15) - refdate).total_seconds() * tfac)
xtlabs.append(dtm.datetime(2015, i, 15).strftime('%Y%m%d'))
for i in range(1, 3):
def convert_datetime(dto, info):
if info['time_units'] == 'days':
xfac = 24 * 3600. # seconds in 1 day
elif info['time_units'] == 'hours':
xfac = 3600. # seconds in 1h
elif info['time_units'] == 'minutes':
xfac = 60. # seconds in 1min
else:
xfac = 1. # seconds in 1min
return (dto - info['refdate']).total_seconds() / xfac
ts = mr.read_time_series(TSfil)
yscaling = 1.e-6 # m^2 -> km^2
lines = []
po, lin, info = ts.plot('model_area', time_units='days', yscaling=yscaling)
lines.append(lin)
po, lin, info = ts.plot('chart_area',
time_units='days',
yscaling=yscaling,
pobj=po)
lines.append(lin)
# po.ax.set_xlabel('Date')
po.ax.set_ylabel('MIZ area, km$^2$')
po.ax.legend(lines, ['Model', 'Chart'])
import os, sys
import mod_reading as mr
from datetime import datetime as DTM
from datetime import timedelta as TDEL
from matplotlib import pyplot as plt
rootdir = '/work/timill/DANY_PAUL_tests'
# DMI ice charts
# - 1st need to merge DMI time-series 2005,2006 manually
# - yearly time series are in /work/shared/nersc/msc/DMI_ice_charts/MIZ_FA/MIZ_polys_classified/[YEAR]/time_series
TS = {}
ts = mr.read_time_series(rootdir + '/time_series_DMI_2005_2006.txt')
TS.update({'DMI': ts})
# print(ts.variables)
SETOPT = 1
VBLOPT = 1
if len(sys.argv) >= 2:
SETOPT = int(sys.argv[1])
if len(sys.argv) >= 3:
VBLOPT = int(sys.argv[2])
# model results
ddirs = {'M1' :'CONST_REFR_1days_2005_242_730',\
'M2' :'CONST_REFR_2days_2005_242_730',\
'M3' :'CONST_REFR_3days_2005_242_730',\
'M4' :'CONST_REFR_4days_2005_242_730',\
'M2L':'CONST_REFR_INIT_LARGE_2days_2005_242_730',\
'M2D':'CONST_REFR_2days_adv_dfloe_2005_242_730/'}