def pet(temperature_celsius: np.ndarray, latitude_degrees: float,
data_start_year: int) -> np.ndarray:
"""
This function computes potential evapotranspiration (PET) using
Thornthwaite's equation.
:param temperature_celsius: an array of average temperature values,
in degrees Celsius
:param latitude_degrees: the latitude of the location, in degrees north,
must be within range [-90.0 ... 90.0] (inclusive), otherwise a
ValueError is raised
:param data_start_year: the initial year of the input dataset
:return: an array of PET values, of the same size and shape as the input
temperature values array, in millimeters/time step
:rtype: 1-D numpy.ndarray of floats
"""
# make sure we're not dealing with all NaN values
if np.ma.isMaskedArray(temperature_celsius) and (
temperature_celsius.count() == 0):
# we started with all NaNs for the temperature, so just return the same as PET
return temperature_celsius
else:
# we were passed a vanilla Numpy array, look for indices where the value == NaN
if np.all(np.isnan(temperature_celsius)):
# we started with all NaNs for the temperature, so just return the same
return temperature_celsius
# If we've been passed an array of latitude values then just use
# the first one -- useful when applying this function with xarray.GroupBy
# or numpy.apply_along_axis() where we've had to duplicate values in a 3-D
# array of latitudes in order to correspond with a 3-D array of temperatures.
if isinstance(latitude_degrees,
np.ndarray) and (latitude_degrees.size > 1):
latitude_degrees = latitude_degrees.flat[0]
# make sure we're not dealing with a NaN or out-of-range latitude value
if ((latitude_degrees is not None) and not np.isnan(latitude_degrees)
and (latitude_degrees < 90.0) and (latitude_degrees > -90.0)):
# compute and return the PET values using Thornthwaite's equation
return eto.eto_thornthwaite(
temperature_celsius,
latitude_degrees,
data_start_year,
)
else:
message = ("Invalid latitude value: " + str(latitude_degrees) +
" (must be in degrees north, between -90.0 and " +
"90.0 inclusive)")
_logger.error(message)
raise ValueError(message)
def test_eto_thornthwaite(temps_celsius,
latitude_degrees,
data_year_start_monthly,
pet_thornthwaite_mm):
# compute PET from the monthly temperatures, latitude, and initial years
computed_pet = eto.eto_thornthwaite(temps_celsius, latitude_degrees, data_year_start_monthly
)
# make sure PET is being computed as expected
np.testing.assert_allclose(computed_pet,
pet_thornthwaite_mm.flatten(),
atol=0.001,
equal_nan=True,
err_msg="PET (Thornthwaite) values not computed as expected")
# make sure that a 3-D array raises an error
reshaped_temps = np.reshape(temps_celsius[0:1400], (123, 2, 6))
pytest.raises(ValueError,
eto.eto_thornthwaite,
reshaped_temps,
latitude_degrees,
data_year_start_monthly)
# make sure that an invalid latitude value (lat > 90) raises an error
pytest.raises(ValueError,
eto.eto_thornthwaite,
temps_celsius,
91.0, # latitude > 90 is invalid
data_year_start_monthly)
# make sure that an invalid latitude value (lat < -90) raises an error
pytest.raises(ValueError,
eto.eto_thornthwaite,
temps_celsius,
-91.0, # latitude < -90 is invalid
data_year_start_monthly)
# make sure that an invalid latitude value (None) raises an error
pytest.raises(TypeError,
eto.eto_thornthwaite,
temps_celsius,
None,
data_year_start_monthly)
# make sure that an invalid latitude value (NaN) raises an error
pytest.raises(ValueError,
eto.eto_thornthwaite,
temps_celsius,
np.NaN,
data_year_start_monthly)