'''some definitions'''
area_def = load_area('areas.cfg', 'pc_world')
rlon = np.arange(-180, 180, .1)
rlat = np.arange(90, -90, -.1)
input_iusv_start = int(input("Enter start cruise processing number 0-10: "))
input_iusv_end = int(input("Enter stop cruise processing number 0-10: "))
adir_usv = str(input("Enter directory for USV data: "))
adir_l1r = str(input("Enter directory for L1R data: "))
#intialize grid
for iusv in range(input_iusv_start, input_iusv_end):
file_save = [] #initialize variable for each processing run
ds_usv, name_usv = read_usv(adir_usv, iusv)
fileout = adir_usv + name_usv + 'AMSR2MMDB_filesave2_testing.nc'
#search usv data
minday, maxday = ds_usv.time[0], ds_usv.time[-1]
usv_day = minday
print(minday.data, maxday.data)
while usv_day <= maxday:
#while looping through USV data, look at data +-1 day
ds_day = ds_usv.sel(time=slice(usv_day -
np.timedelta64(1, 'D'), usv_day +
np.timedelta64(1, 'D')))
ilen = ds_day.time.size
if ilen < 1: #don't run on days without any data
continue
#
# - loop through the satellite data
# - calculate the in situ min/max lat/lon on the same day to define a small box of interest
# - use pyresample to map the data onto a predefined 0.1 deg resolution spatial grid
# - subset the gridded map to the area of interest
# - see if there is any valid data in that area
# - if there is any valid data, save the filename into a list
#
#
input_iusv_start = int(input("Enter start cruise processing number 0-10: "))
input_iusv_end = int(input("Enter stop cruise processing number 0-10: "))
adir_usv = str(input("Enter directory for USV data: "))
#intialize grid
for iusv in range(input_iusv_start,input_iusv_end):
ds_usv, usv_name = read_usv(adir_usv,iusv)
print('usv', usv_name)
fileout = adir_usv + 'mmdb_collocation_test/' + usv_name + 'AMSR2MMDB_usv2_testing.nc'
ds_usv = xr.open_dataset(fileout)
# now collocation with orbital data is finished. re-open file and create the mean values for each matchup so there aren't repeates
fileout_norepeat = fileout[:-3]+'_norepeats_testing.nc'
# ds_usv = ds_usv.where(ds_usv.tb<10000,np.nan)
ds_usv = ds_usv.where(ds_usv.amsr2_scan>10000,np.nan) #keep valid scan nmbers, replace rest with nan
ilen,index = ds_usv['insitu.time'].size,0
ds_tem = ds_usv.copy(deep=True)
dsst,dair,dwav,dpres,dsstu,dvwnd,duwnd,dsal,dchl,dgwnd,dlat,dlon,dut = [],[],[],[],[],[],[],[],[],[],[],[],np.empty((),dtype='datetime64')
index=0
while index <= ilen-2:
index += 1
# if np.isnan(ds_usv.tb[index]):
# - loop through the satellite data
# - calculate the in situ min/max lat/lon on the same day to define a small box of interest
# - use pyresample to map the data onto a predefined 0.1 deg resolution spatial grid
# - subset the gridded map to the area of interest
# - see if there is any valid data in that area
# - if there is any valid data, save the filename into a list
#
#
input_iusv_start = int(input("Enter start cruise processing number 0-10: "))
input_iusv_end = int(input("Enter stop cruise processing number 0-10: "))
adir_usv = str(input("Enter directory for USV data: "))
#intialize grid
for iusv in range(input_iusv_start,input_iusv_end):
num_usv = 0
ds_usv, usv_name = read_usv(adir_usv,num_usv)
fileout = adir_usv + usv_name + 'AMSR2MMDB_usv2.nc'
ds_usv = xr.open_dataset(fileout)
# now collocation with orbital data is finished. re-open file and create the mean values for each matchup so there aren't repeates
fileout_norepeat = fileout[:-3]+'_norepeats.nc'
ds_usv = ds_usv.where(ds_usv.tb<10000,np.nan)
ilen,index = ds_usv.dims['time'],0
ds_tem = ds_usv.copy(deep=True)
dsst,dair,dwav,dpres,dsstu,dvwnd,duwnd,dsal,dchl,dgwnd,dlat,dlon, dut = [],[],[],[],[],[],[],[],[],[],[],[],np.empty((),dtype='datetime64')
index=0
while index <= ilen-2:
index += 1
if np.isnan(ds_usv.tb[index]):
continue
if np.isnan(ds_usv.amsr2_scan[index]):