T = ImmutableMatrix([[-1, 0], [h, -1]]) #transition operator
N = diag(k_1, k_2) #decomposition operator
t = TimeSymbol("t") # unit: "year"
x = StateVariableTuple((Y, O))
u = InputTuple((i, 0))
B = CompartmentalMatrix(xi * T * N)
# - "Bare fallow":
np1 = NumericParameterization(par_dict={
k_1: 0.8,
k_2: 0.00605,
i: 0,
h: 0.13,
r: 1.32
},
func_dict=frozendict({}))
nsv1 = NumericStartValueDict({Y: 0.3, O: 3.96})
# - "+N +straw":
np2 = NumericParameterization(par_dict={
k_1: 0.8,
k_2: 0.00605,
i: 0.285,
h: 0.125,
r: 1.00
},
func_dict=frozendict({}))
nsv2 = NumericStartValueDict({Y: 0.3, O: 4.11})
# - "-N +straw":
np3 = NumericParameterization(par_dict={
k_1: 0.8,
Q_10: 1,
W: 4.2,
T: 25,
GPP: 3370, #"gC*day^{-1}"
eta_f: 0.14,
eta_r: 0.26,
eta_w: 0.14,
gamma_f: 0.00258,
gamma_w: 0.0000586,
gamma_r: 0.00239
},
func_dict=frozendict({})
# state_var_units=gram/kilometer**2,
# time_unit=day
)
nsv1 = NumericStartValueDict({C_f: 250, C_w: 4145, C_r: 192})
ntimes = NumericSimulationTimes(np.arange(0, 150, 2.5))
mvs = MVarSet({
BibInfo( # Bibliographical Information
name="",
longName="",
version="",
entryAuthor="Verónika Ceballos-Núñez",
entryAuthorOrcid="0000-0002-0046-1160",
entryCreationDate="24/3/2016",
doi="",
# further_references=BibInfo(doi=""),
# modApproach: process based,
# partitioningScheme: fixed,
f_cs: 0.45,
f_np: 0.16,
f_nr: 0.03,
f_ns: 0.005,
h_max: 0.0003,
h_half: 200,
kappa: 300,
rho: '5*10**5',
C_i: 240
},
func_dict=frozendict({}))
nsv1 = NumericStartValueDict({
N: 0.01,
C: 0.15,
W_p: 100,
W_s: 100,
W_r: 100,
W_C: 45,
W_N: 30
})
ntimes = NumericSimulationTimes(np.arange(0, 150, 25))
#ntimes = NumericSimulationTimes(np.arange(0, 1, 0.001)) #Fixme: There were 2 in the yaml file, not sure which one works best
mvs = MVarSet({
BibInfo( # Bibliographical Information
name="",
longName="",
version="1",
entryAuthor="Verónika Ceballos-Núñez",
entryAuthorOrcid="0000-0002-0046-1160",
entryCreationDate="29/7/2015",
cr_foliage: 0.00258,
cr_wood: 0.0000586,
cr_root: 0.002390,
cr_metlit: 0.0109,
cr_stlit: 0.00095,
cr_fastsom: 0.0105,
cr_slowsom: 0.0000995,
cr_passsom: 0.0000115
},
func_dict=frozendict({}))
# "Initial values as in Wang and Luo"
nsv1 = NumericStartValueDict({
C_foliage: 250,
C_roots: 4145,
C_wood: 192,
C_metlit: 93,
C_stlit: 545,
C_fastsom: 146,
C_slowsom: 1585,
C_passsom: 300
})
ntimes = NumericSimulationTimes(np.arange(0, 200, 1))
mvs = CMTVS(
{
BibInfo( # Bibliographical Information
name="TECO",
longName="Terrestrial Ecosystem Model",
version="",
entryAuthor="Carlos A. Sierra",
entryAuthorOrcid="0000-0003-0009-4169",
entryCreationDate="12/4/2018",
[[-gamma_f, 0 , 0 , (l_p*eta_f) ,(s_p*eta_f)],
[ 0 ,-gamma_r, 0 , (l_p*eta_r) ,(s_p*eta_r)],
[ 0 , 0 ,-gamma_w, (l_p*eta_w) ,(s_p*eta_w)],
[ gamma_f, gamma_r, gamma_w, -(l_p+l_s+l_dr), 0 ],
[ 0 , 0 , 0 , l_s ,-(s_p+s_dr)]
])
## The following are default values suggested by this entry's creator only to be able to run the model:
np1 = NumericParameterization(
par_dict={u: 1400, eta_f: 0.48, eta_r: 0.44, eta_w: 0.49, gamma_r: 3.03, gamma_f: 23.32, gamma_w: 0.04},
func_dict=frozendict({})
)
nsv1 = NumericStartValueDict({
C_f: 200,
C_w: 5000,
C_r: 300
})
ntimes = NumericSimulationTimes(np.arange(0, 20000, 0.01))
# doi: 10.1016/0304-3800(88)90112-3
np2 = NumericParameterization(
par_dict={
eta_f: Rational(25,100), eta_r: Rational(40,100), eta_w: Rational(35,100), gamma_r: Rational(40,100), gamma_f: Rational(33,100), gamma_w: Rational(0,100)},
func_dict=frozendict({})
)
# doi: 10.1093/treephys/9.1-2.161 # Hunt1991TreePhysiol
np3 = NumericParameterization(
par_dict={
#
# Althouhg p10 is considered to have unit 1/Kelvin
# inspection of the T_rate expression connects it
# to Temperature DIFFERENCE from the triple point
p_10: 0.0693, # /kelvin
p_14: 0.45,
p_15: 0.001, # 1/day
p_16: 0.251,
},
func_dict=frozendict({})
# state_var_units=kilogram/meter**2,
# time_unit=day
)
nsv1 = NumericStartValueDict({
C_f: 58,
C_lab: 60,
C_w: 770,
C_r: 102
})
## We create the parameterized model explicitly , although the framework would find the ingredients
nsrm = NumericParameterizedSmoothReservoirModel(srm,np1)
ntimes = NumericSimulationTimes(np.arange(0, 1096, 1))
## We create the model run explicitly again, although the framework would find the ingredients
nsmr= numeric_model_run_1(
nsrm,
numeric_start_value_array_1(nsv1,x),
ntimes
c_1: 0.00258,
c_2: 0.0000586,
c_3: 0.002390,
c_4: 0.0109,
c_5: 0.00095,
c_6: 0.0105,
c_7: 0.0000995,
c_8: 0.0000115
},
func_dict=frozendict({}))
# "Initial values as in Wang and Luo"
nsv1 = NumericStartValueDict({
x_1: 250,
x_2: 4145,
x_3: 192,
x_4: 93,
x_5: 545,
x_6: 146,
x_7: 1585,
x_8: 300
})
ntimes = NumericSimulationTimes(np.arange(0, 200, 1))
mvs = CMTVS(
{
BibInfo( # Bibliographical Information
name="TECO",
longName="Terrestrial Ecosystem Model",
version="",
entryAuthor="Carlos A. Sierra",
entryAuthorOrcid="0000-0003-0009-4169",
entryCreationDate="12/4/2018",
def test_numeric_input_tuple(self):
# setup the paths to the testdata
cable_out_path = Path(
'/home/data/cable-data/example_runs/parallel_1901_2004_with_spinup/output/new4'
)
# cable_data_set = cH.cable_ds(cable_out_path)
time_slice = slice(0, None)
landpoint_slice = slice(1590, 1637) # cheated
# landpoint_slice = slice(None,None)
# time_slice=slice(None,None,None)
zarr_cache_path = cP.slice_dir_path(
cable_out_path,
sub_dir_trunk="zarr_mm11",
time_slice=time_slice,
landpoint_slice=landpoint_slice,
)
if "cable_data_set" not in dir():
cable_data_set = cH.cable_ds(cable_out_path)
args = {
"cable_data_set": cable_data_set,
"zarr_cache_path": zarr_cache_path,
"landpoint_slice": landpoint_slice,
"time_slice": time_slice,
#'batch_size': 128,
"batch_size": 12,
#'rm': True
}
x_org_iveg = cH.cacheWrapper(cC.x_org_iveg, **args)
time = cH.cacheWrapper(cC.time, **args)
patches, landpoints = cC.all_pools_vary_cond_nz(**args)
pcs = patches.compute()
lpcs = landpoints.compute()
pcs, lpcs
p = Path('plots')
p.mkdir(exist_ok=True)
ind = 0 # first pair that has a nonconstant solution for
lp = lpcs[ind]
patch = lpcs[ind]
# get the symbolic represantation from the database
mvs = self.mvs
# define some stuff to extend it with
def default(t):
return 1
leaf = Symbol('leaf')
fine_root = Symbol('fine_root')
Npp = Function("Npp")
bvec_leaf = Function("bvec_leaf")
bvec_fine_root = Function("bvec_fine_root")
xk_leaf_cold = Function("xk_leaf_cold")
xk_leaf_dry = Function("xk_leaf_dry")
kleaf = Function("kleaf")
kfroot = Function("kfroot")
# bvec_wood = Function("bvec_wood")
np1 = NumericParameterization(
par_dict={},
func_dict=frozendict({
Npp: default,
bvec_fine_root: default,
bvec_leaf: default,
xk_leaf_cold: default,
kleaf: default,
kfroot: default,
xk_leaf_dry: default,
}),
)
nsv1 = NumericStartValueDict({leaf: 0.3, fine_root: 3.96})
ntimes1 = NumericSimulationTimes(np.linspace(0, 1, 11))
# extend the symbolice version with the new stuff
pvs = mvs.provided_mvar_values
#from IPython import embed; embed()
pvs1 = pvs.union(frozenset({np1, nsv1, ntimes1}))
mvs1 = MVarSet(pvs1)
x = mvs1.get_StateVariableTuple()
Input = mvs1.get_InputTuple()
#B = mvs1.get_CompartmentalMatrix()
sym_times = mvs1.get_NumericSimulationTimes()
sol_smooth = mvs1.get_NumericSolutionArray()
comp_slice = slice(0, 100)
n = sol_smooth.shape[1]
fig = plt.figure()
for pool in range(n):
ax = fig.add_subplot(n + 1, 1, 2 + pool)
title = "\$" + latex(x[pool]) + "\$"
#ax.plot(
# sym_times[comp_slice],
# sol_smooth[comp_slice, pool],
# color='r'
#)
ax.plot(time[comp_slice],
x_org_iveg[comp_slice, pool, patch, lp],
color='b')
fontsize = 10
ax.set_title(title, fontsize=fontsize)
fig.savefig('solution.pdf')
np1 = NumericParameterization(par_dict={
K_1: 0.076,
K_2: 0.28,
K_3: 0.094,
K_4: 0.35,
K_5: 0.14,
K_6: 0.0038,
K_7: 0.00013,
xi: 1
},
func_dict=frozendict({}))
nsv1 = NumericStartValueDict({
C_1: 100,
C_2: 200,
C_3: 00,
C_4: 0,
C_5: 0,
C_6: 0,
C_7: 0
}) #faked values by Markus to make it run
#ntimes = NumericSimulationTimes(np.arange())
mvs = CMTVS(
{
BibInfo( # Bibliographical Information
name="Century",
longName="",
version="1",
entryAuthor="Holger Metzler",
entryAuthorOrcid="0000-0002-8239-1601",
entryCreationDate="10/03/2016",
np1 = NumericParameterization(par_dict={
D_max: 0.26,
Y: 0.44,
K_s: 3.0,
theta: 0.23,
ExuT: 0.8,
BGF: 0.15,
K_d: 14.5,
K_r: 0.4,
ExuM: 8.0,
mu_max: 0.063
},
func_dict=frozendict({}))
# Standard version of BACWAVE, optimized to simulate bacterial biomass along wheat roots:
nsv1 = NumericStartValueDict({X: 0.5, S: 1.5}) # "Low"
nsv2 = NumericStartValueDict({X: 1.0, S: 2.5}) # "Medium"
nsv3 = NumericStartValueDict({X: 1.5, S: 4.0}) # "High"
ntimes = NumericSimulationTimes(np.arange(0, 2000, 0.1))
mvs = CMTVS(
{
BibInfo( # Bibliographical Information
name="BACWAVE",
longName="",
version="",
entryAuthor="Holger Metzler",
entryAuthorOrcid="0000-0002-8239-1601",
entryCreationDate="15/03/2016",
doi="10.2307/4251775",
sym_dict=sym_dict),
F_1: 2.081,
F_2: 0.0686,
F_3: 0.5217,
F_4: 0.5926,
F_5: 9.813e-3,
F_21: 0.8378,
F_41: 0.5676,
F_42: 0.0322,
F_52: 4.425e-3,
F_43: 0.1739,
F_53: 0.0870,
F_54: 0.0370
},
func_dict=frozendict({}))
nsv1 = NumericStartValueDict({x_1: 37, x_2: 452, x_3: 69, x_4: 81, x_5: 1121})
ntimes = NumericSimulationTimes(np.arange(0, 200, 0.1))
mvs = CMTVS(
{
BibInfo( # Bibliographical Information
name="",
longName="",
version="",
entryAuthor="Carlos A. Sierra",
entryAuthorOrcid="0000-0003-0009-4169",
entryCreationDate="12/9/2016",
doi="",
# bibtex= "@incollection{Emanuel1981,
# author = {W. R. Emanuel and G. G. Killough and J. S. Olson},
# booktitle = {Carbon Cycle Modelling},