def test_creation(self):
a, b, c = symbols('a b c')
u = VegetationCarbonInputScalar(a)
self.assertEqual(type(u), VegetationCarbonInputScalar)
v = u.subs({a: b})
self.assertEqual(type(v), VegetationCarbonInputScalar)
u = VegetationCarbonInputScalar(1)
self.assertEqual(type(u), VegetationCarbonInputScalar)
def test_vegetation_carbon_input_tuple_1(self):
for name in ("a_L", "a_S", "a_R"):
var(name)
u = VegetationCarbonInputScalar(sympify(1))
b = VegetationCarbonInputPartitioningTuple((a_L, a_S, a_R))
res_1 = u * b
print(type(res_1))
# C_root: , #"g*m^{-2}"
# C_wood: #"g*m^{-2}"
#})
#
#ntimes = NumericSimulationTimes(np.arange(, , ))
mvs=MVarSet({
BibInfo(# Bibliographical Information
name="CABLE",
longName="CSIRO Atmosphere Biosphere Land Exchange",
version="1",
# basedOn = "CASA'" # Fung et al. (2005) -> Need to look it up
entryAuthor="Verónika Ceballos-Núñez",
entryAuthorOrcid="0000-0002-0046-1160",
entryCreationDate="14/3/2016",
doi="10.5194/bg-7-2261-2010",
sym_dict=sym_dict
),
A, # the overall compartmental matrix
Input, # the overall input
t, # time for the complete system
x, # state vector of the complete system
VegetationCarbonInputScalar(u),
# vegetation carbon partitioning.
VegetationCarbonInputPartitioningTuple(b),
VegetationCarbonStateVariableTuple((C_leaf, C_root, C_wood)),
# np1
})
#mvs.graph()
# -
mvs.get_InputTuple()
mvs.computable_mvar_types()
mvs.get_OutFluxesBySymbol()
it = mvs.get_VegetationCarbonInputTuple()
#mvs.get_InFluxesBySymbol()
#VegetationCarbonInputPartitioningTuple([tc/b for tc in it])
# +
VegetationCarbonInputScalar(sum(it))
# -
[t for t in mvs.provided_mvar_types]
# +
#for var in mvs.computable_mvar_types():
# mvs.render(var)
# -
mvs.get_VegetationCarbonInputPartitioningTuple()
importlib.invalidate_caches()
mod2 = importlib.import_module(
'bgc_md2.models.Haverd2016Biogeosciences.source')
mvs2 = mod2.mvs
