def compute(cls, precip_rate, wind_direction, criteria):
# Checking input types
if isinstance(precip_rate, netCDF4._netCDF4.Dataset):
pr = NCdata(precip_rate)
elif isinstance(precip_rate, NCdata):
pr = precip_rate
else:
raise TypeError(
'precip_rate of class ', precip_rate.__class__,
' must be either a netCDF4 reader or a '
'NCData object')
if isinstance(wind_direction, netCDF4._netCDF4.Dataset):
wind_dir = NCdata(wind_direction)
elif isinstance(wind_direction, NCdata):
wind_dir = wind_direction
else:
raise TypeError(
'wind_direction of class ', wind_direction.__class__,
' must be either a netCDF4 reader or '
'a NCData object')
# Create new monsoon object
NCmonsoon = MonsoonData.__new__(cls)
# Check that pr and wind_dir have properly aligning grids
# TODO shouldn't need this if statement if align_grids always works properly
if pr.lats != wind_dir.lats or pr.lons != wind_dir.lons:
pr.variable, wind_dir.variable, new_lats, new_lons = cls.align_grids(
pr, wind_dir)
pr.lats = wind_dir.lats = new_lats
pr.lons = wind_dir.lons = new_lons
# Check that pr and wind_dir are compatible; if so assign shared variables to monsoon object
for attr in [
'lats', 'lons', 'time', 'calendar', 'time_units', 'model_id'
]:
if (np.asarray(
getattr(pr, attr) != getattr(wind_dir, attr))).all():
raise TypeError(attr, ' not aligned in pr and wind_dir')
setattr(NCmonsoon, attr, getattr(pr, attr))
# Create boolean monsoon from pr and wind_dir
passing_pr = criteria['precip'](pr.variable)
passing_wd = criteria['wind_dir'](wind_dir.variable)
blank_monsoon = passing_pr & passing_wd
# Add newly calculated data to the monsoon object
NCmonsoon.var_name = 'monsoon'
NCmonsoon.var_units = 'boolean'
NCmonsoon.variable = blank_monsoon.astype(float)
# Created combined global attributes
monsoon_globalattrs = {}
all_keys = list(
set(
list(pr.globalattrs.keys()) +
list(wind_dir.globalattrs.keys())))
for key in all_keys:
if key not in pr.globalattrs.keys():
monsoon_globalattrs[key + '_wd'] = wind_dir.globalattrs[key]
elif key not in wind_dir.globalattrs.keys():
monsoon_globalattrs[key + '_pr'] = pr.globalattrs[key]
elif pr.globalattrs[key] == wind_dir.globalattrs[key]:
monsoon_globalattrs[key] = pr.globalattrs[key]
else:
monsoon_globalattrs[key + '_pr'] = pr.globalattrs[key]
monsoon_globalattrs[key + '_wd'] = wind_dir.globalattrs[key]
# monsoon_globalattrs['monsoon_criteria'] = criteria['summary_dict']
NCmonsoon.globalattrs = monsoon_globalattrs
return NCmonsoon
from wnpmonsoon.ncdata import NCdata
import numpy as np
uas = NCdata(file_, 'uas')
vas = NCdata(file_, 'uas')
wind_sp = np.sqrt(np.square(uas.variable) + np.square(vas.variable))
# TODO decide if this is a good idea / if there is a better way to do this
# Inheriting from another object?
variable = 'ws'
ws = NCdata('notrealfile', variable, create_new=True)
ws.var_name = variable
ws.model = uas.model_id
ws.var_units = uas.var_units
ws.variable = wind_sp
ws.lats = uas.lats
ws.lons = uas.lons
ws.time = uas.time
ws.calendar = uas.calendar
ws.t_units = uas.t_units
ws.write(outfile)