def check_viability(trait_values):
""" check the viability of allocation(a) & residence time(ŧ) combinations"""
rtur = np.array(model.spinup3(0.01, trait_values))
if rtur[0] <= 0.01 or rtur[1] <= 0.01:
return False
return True
def check_viability(trait_values):
""" check the viability of allocation(a) & residence time(ŧ) combinations"""
rtur = np.array(model.spinup3(0.1, trait_values))
if rtur[0] <= 0.001 or rtur[1] <= 0.001:
#print("invalid_combination")
#print(rtur[0], rtur[1])
#print("\n")
return False # aways return true
return True
def check_viability(trait_values, wood):
""" Check the viability of allocation(a) & residence time(ŧ) combinations.
Some PLS combinations of allocation coefficients and residence times
are not 'biomass acumulators' at low npp (< 0.01 kg m⁻² year⁻¹)
do not have enough mass of carbon (< 0.01 kg m⁻²) in all CVEG compartments
trait_values: np.array(shape=(6,), dtype=f64) allocation and residence time combination (possible PLS)
wood: bool Is this a woody PLS?
"""
assert wood is not None
rtur = np.array(model.spinup3(1.0, trait_values))
if wood:
if rtur[0] <= 0.5 or rtur[1] <= 0.5 or rtur[2] <= 0.5:
return False
return True
else:
if rtur[0] <= 0.5 or rtur[1] <= 0.5:
return False
return True