def produce_monthly_climatology(months, year_start, year_end):
import calendar
from utils import get_netCDF_filepath
year_range = str(year_start) + '-' + str(year_end)
for month in months:
label = calendar.month_abbr[month] + '_' + year_range + '_average'
month_days = []
for year in range(year_start, year_end + 1):
n_days = calendar.monthrange(year, month)[1]
month_days = month_days + date_range(
datetime.date(year, month, 1),
datetime.date(year, month, n_days))
avg_period = str(month).zfill(2)
tau_fp = get_netCDF_filepath(field_type='monthly_climo',
date=datetime.date(year, month, 1),
year_start=year_start,
year_end=year_end)
surface_stress_dataset = SurfaceStressDataWriter(
field_type='monthly_climo',
date=month_days[-1],
year_start=year_start,
year_end=year_end)
surface_stress_dataset.date = month_days[-1]
surface_stress_dataset.compute_mean_fields(
month_days, avg_method='partial_data_ok')
surface_stress_dataset.plot_diagnostic_fields(plot_type='custom',
custom_label=label)
surface_stress_dataset.write_fields_to_netcdf()
def process_and_plot_day(date):
""" Process and plot fields for only one day. """
from SurfaceStressDataWriter import SurfaceStressDataWriter
surface_stress_dataset = SurfaceStressDataWriter(field_type='daily', date=date)
surface_stress_dataset.compute_daily_surface_stress_field(u_geo_source='CS2')
surface_stress_dataset.compute_daily_auxillary_fields()
surface_stress_dataset.write_fields_to_netcdf()
surface_stress_dataset.plot_diagnostic_fields(plot_type='daily', custom_label='no_custom_label_')
def produce_annual_mean(year):
dates = date_range(datetime.date(year, 1, 1), datetime.date(year, 12, 31))
surface_stress_dataset = SurfaceStressDataWriter(field_type='annual',
date=dates[0])
surface_stress_dataset.compute_mean_fields(dates,
avg_method='partial_data_ok')
surface_stress_dataset.plot_diagnostic_fields(plot_type='annual')
surface_stress_dataset.write_fields_to_netcdf()
def process_day(date):
""" Process for only one day. """
from SurfaceStressDataWriter import SurfaceStressDataWriter
try:
surface_stress_dataset = SurfaceStressDataWriter(field_type='daily', date=date)
surface_stress_dataset.compute_daily_surface_stress_field(u_geo_source='CS2')
surface_stress_dataset.compute_daily_auxillary_fields()
surface_stress_dataset.write_fields_to_netcdf()
except Exception as e:
logger.error('Failed to process day {}. Returning.'.format(date))
logger.error('{}'.format(e), exc_info=True)
return
def produce_monthly_mean(date_in_month):
month = date_in_month.month
year = date_in_month.year
date1 = datetime.date(year, month, 1)
n_days = calendar.monthrange(date1.year, date1.month)[1]
date2 = datetime.date(year, month, n_days)
dates = date_range(date1, date2)
surface_stress_dataset = SurfaceStressDataWriter(field_type='monthly',
date=dates[0])
surface_stress_dataset.compute_mean_fields(dates,
avg_method='partial_data_ok')
surface_stress_dataset.plot_diagnostic_fields(plot_type='monthly')
surface_stress_dataset.write_fields_to_netcdf()
def produce_climatology(year_start, year_end):
from utils import get_netCDF_filepath
climo_label = str(year_start) + '-' + str(year_end) + '_average'
dates = date_range(datetime.date(year_start, 1, 1),
datetime.date(year_end, 12, 31))
surface_stress_dataset = SurfaceStressDataWriter(field_type='climo',
year_start=year_start,
year_end=year_end)
surface_stress_dataset.date = dates[0]
surface_stress_dataset.compute_mean_fields(dates,
avg_method='partial_data_ok')
surface_stress_dataset.plot_diagnostic_fields(plot_type='custom',
custom_label=climo_label)
surface_stress_dataset.write_fields_to_netcdf()
def produce_seasonal_mean(seasons_to_compute, year):
seasons = {
'JFM': {
'date1': datetime.date(year, 1, 1),
'date2': datetime.date(year, 3, 31),
'label': 'Summer_JFM_' + str(year) + '_average'
},
'AMJ': {
'date1': datetime.date(year, 4, 1),
'date2': datetime.date(year, 6, 30),
'label': 'Fall_AMJ_' + str(year) + '_average'
},
'JAS': {
'date1': datetime.date(year, 7, 1),
'date2': datetime.date(year, 9, 30),
'label': 'Winter_JAS_' + str(year) + '_average'
},
'OND': {
'date1': datetime.date(year, 10, 1),
'date2': datetime.date(year, 12, 31),
'label': 'Spring_JFM_' + str(year) + '_average'
}
}
for s in seasons_to_compute:
logger.info('s={:s}'.format(s))
dates = date_range(seasons[s]['date1'], seasons[s]['date2'])
surface_stress_dataset = SurfaceStressDataWriter(None)
surface_stress_dataset.date = dates[0]
surface_stress_dataset.compute_mean_fields(
dates, avg_method='partial_data_ok')
surface_stress_dataset.plot_diagnostic_fields(
plot_type='custom', custom_label=seasons[s]['label'])
surface_stress_dataset.write_fields_to_netcdf(field_type='seasonal',
season_str=s)
def plot_day(date):
from SurfaceStressDataWriter import SurfaceStressDataWriter
surface_stress_dataset = SurfaceStressDataWriter(None)
surface_stress_dataset.date = date
surface_stress_dataset.compute_mean_fields([date], avg_method='full_data_only')
surface_stress_dataset.plot_diagnostic_fields(plot_type='daily')
def produce_seasonal_climatology(seasons, year_start, year_end):
year_range = str(year_start) + '-' + str(year_end)
labels = {
'DJF': 'Summer_DJF_' + year_range + '_average',
'MAM': 'Fall_MAM_' + year_range + '_average',
'JJA': 'Winter_JJA_' + year_range + '_average',
'SON': 'Spring_SON_' + year_range + '_average',
'JFM': 'Summer_JFM_' + year_range + '_average',
'AMJ': 'Fall_AMJ_' + year_range + '_average',
'JAS': 'Winter_JAS_' + year_range + '_average',
'OND': 'Spring_OND_' + year_range + '_average'
}
season_start_month = {
'DJF': 12,
'MAM': 3,
'JJA': 6,
'SON': 9,
'JFM': 1,
'AMJ': 4,
'JAS': 7,
'OND': 10
}
season_end_month = {
'DJF': 2,
'MAM': 5,
'JJA': 8,
'SON': 11,
'JFM': 3,
'AMJ': 6,
'JAS': 9,
'OND': 12
}
for season in seasons:
season_days = []
for year in range(year_start, year_end + 1):
start_date = datetime.date(year, season_start_month[season], 1)
end_month_days = calendar.monthrange(year,
season_end_month[season])[1]
end_date = datetime.date(year, season_end_month[season],
end_month_days)
season_days = season_days + date_range(start_date, end_date)
surface_stress_dataset = SurfaceStressDataWriter(
field_type='seasonal_climo',
season_str=season,
year_start=year_start,
year_end=year_end)
surface_stress_dataset.date = season_days[0]
surface_stress_dataset.compute_mean_fields(
season_days, avg_method='partial_data_ok')
surface_stress_dataset.plot_diagnostic_fields(
plot_type='custom', custom_label=labels[season])
surface_stress_dataset.write_fields_to_netcdf()