def test_orbital_interpolation():
# check to see if we get smooth results when we interpolate
# orbital parameters at high temporal frequency
kyears = np.linspace(-11, 0, 1001)
orb = OrbitalTable.interp(kyear=kyears)
S30 = daily_insolation(lat=30, day=172, orb=orb)
# there should be no abrupt changes
# test if insolation varies by more than 0.1 W/m2 per year
assert S30.diff(dim='kyear').max() < 0.1
def test_daily_insolation():
lat = np.linspace(-90., 90., 500.)
days = np.linspace(0, const.days_per_year, 365.)
Q = daily_insolation(lat, days)
# check the range of Q
np.testing.assert_almost_equal(Q.max(), 562.0333475)
np.testing.assert_almost_equal(Q.min(), 0.0)
# check the area integral
Q_area_int = (np.sum(np.mean(Q, axis=1) * np.cos(np.deg2rad(lat))) /
np.sum(np.cos(np.deg2rad(lat))))
np.testing.assert_almost_equal(Q_area_int, 341.384184481)
def test_daily_insolation():
lat = np.linspace( -90., 90., 500. )
days = np.linspace(0, const.days_per_year, 365. )
Q = daily_insolation(lat, days)
# check the range of Q
np.testing.assert_almost_equal(Q.max(), 562.0333475)
np.testing.assert_almost_equal(Q.min(), 0.0)
# check the area integral
Q_area_int = (np.sum(np.mean(Q, axis=1) * np.cos(np.deg2rad(lat))) /
np.sum(np.cos(np.deg2rad(lat))) )
np.testing.assert_almost_equal(Q_area_int, 341.384184481)
def add_monthly_insolation(ds):
month_days = [31,28,31,30,31,30,31,31,30,31,30,31] #list of the number of days in a month
day_of_month = [
np.cumsum(month_days) - np.array(month_days),
np.cumsum(month_days)
] #list of first and last day of each month
day_num = np.arange(1,366) #number of days in a year
month_num = np.arange(0,12) #number of months in a year
insolation = np.zeros(len(day_num)) #insolation for each day
monthly_insol = np.zeros(len(month_num)) #insolation for each month
for day in day_num: #calculate daily insolation
insolation[day-1] = daily_insolation(lat = -90, day = day)
for month in month_num: #calculate monthly mean insolation
monthly_insol[month] = insolation[day_of_month[0][month]:day_of_month[1][month]].mean()
ds['monthly_insolation'] = xr.DataArray(data = monthly_insol, dims = 'month') #add into our dataset
def _daily_insolation_array(self):
lat = self.lat
days_of_year = self.time['days_of_year']
orb = self.orb
S0 = self.S0
return daily_insolation(lat, days_of_year, orb=orb, S0=S0)
def _daily_insolation_array(self):
lat = self.lat
days_of_year = self.time['days_of_year']
orb = self.orb
S0 = self.S0
return daily_insolation(lat, days_of_year, orb=orb, S0=S0)
def _daily_insolation(self, day):
years = np.linspace(-self.num_years, 0, self.num_years)
orb = OrbitalTable.interp(kyear=years)
return daily_insolation(lat=self.lat, day=day, orb=orb)
def _daily_insolation(self, day):
years = np.linspace(-YEARS_IN_SIMULATION, 0, YEARS_IN_SIMULATION)
orb = OrbitalTable.interp(kyear=years)
i = daily_insolation(lat=self.latitude, day=day, orb=orb)
return i.to_dict()['data']