def test_add_season_membership_invalid_spec(self):
season = 'maj' # not a season!
with self.assertRaises(ValueError):
ccat.add_season_membership(self.cube,
'time',
season,
name='maj_season')
def test_add_season_membership(self):
# season membership identifies correct seasons?
season = "djf"
ccat.add_season_membership(self.cube, "time", season, name="in_season")
ccat.add_season(self.cube, "time")
coord_season = self.cube.coord("season")
coord_membership = self.cube.coord("in_season")
season_locations = np.where(coord_season.points == season)[0]
membership_locations = np.where(coord_membership.points)[0]
self.assertArrayEqual(membership_locations, season_locations)
def test_add_season_membership(self):
# season membership identifies correct seasons?
season = 'djf'
ccat.add_season_membership(self.cube, 'time', season, name='in_season')
ccat.add_season(self.cube, 'time')
coord_season = self.cube.coord('season')
coord_membership = self.cube.coord('in_season')
season_locations = np.where(coord_season.points == season)[0]
membership_locations = np.where(coord_membership.points)[0]
self.assertArrayEqual(membership_locations, season_locations)
def test_add_season_membership(self):
# season membership identifies correct seasons?
season = 'djf'
ccat.add_season_membership(self.cube, 'time', season,
name='in_season')
ccat.add_season(self.cube, 'time')
coord_season = self.cube.coord('season')
coord_membership = self.cube.coord('in_season')
season_locations = np.where(coord_season.points == season)[0]
membership_locations = np.where(coord_membership.points)[0]
self.assertArrayEqual(membership_locations, season_locations)
def calc_plot_data(cube_data, season):
'''
Calculate data to plot for given season.
Essentially, extract just what we need and collapse time dimension to mean
:param cube_data: iris cube of source data
:param season: season as string
:return: seasonal mean of data as iris cube
'''
# extract domain
cube_data = cube_data.extract(area_con)
assert not cube_data is None
# extract season
# the season membership approach is used because iris doens't like adding a season co-ordinate that
# includes single month seasons, or doesn't span the whole year
if type(cube_data) == iris.cube.CubeList:
for c in cube_data:
iccat.add_season_membership(c, 'time', season=season)
else:
iccat.add_season_membership(cube_data, 'time', season=season)
plot_data = cube_data.extract(iris.Constraint(season_membership=True))
# Units conversion if necessary
if VAR == 'MSLP':
plot_data.convert_units('hPa')
elif VAR == 'rainfall':
if(plot_data.units != 'mm month -1'):
# convert_units can't handle mm/month.. but we at least check we are converting what we think we are here
assert plot_data.units == cf_units.Unit('kg m-2 s-1'), 'Expect units kg m-2 s-1, got {}'.format(plot_data.units)
plot_data = plot_data * 86400 * 30
plot_data.units = 'mm month -1'
elif VAR == 'temperature':
# ensure units are kelvin
if plot_data.units == 'degrees Celsius':
plot_data.units = 'celsius'
plot_data.convert_units('K')
# Collapse time dimension to mean
if type(cube_data) == iris.cube.CubeList:
for i in range(len(cube_data)):
plot_data[i] = plot_data[i].collapsed('time', iris.analysis.MEAN)
cube_data[i].remove_coord('season_membership')
else:
plot_data = plot_data.collapsed('time', iris.analysis.MEAN)
cube_data.remove_coord('season_membership')
# return
return plot_data
def test_add_season_membership_invalid_spec(self):
season = 'maj' # not a season!
with self.assertRaises(ValueError):
ccat.add_season_membership(self.cube, 'time', season,
name='maj_season')
def test_add_season_membership_invalid_spec(self):
season = "maj" # not a season!
with self.assertRaises(ValueError):
ccat.add_season_membership(
self.cube, "time", season, name="maj_season"
)