amici.amici.ReturnDataPtr¶
-
class
amici.amici.
ReturnDataPtr
(*args)[source]¶ Swig-Generated class that implements smart pointers to ReturnData as objects.
Attributes
FIM
nplist x nplist, row-major)
J
nx x nx, row-major)
chi2
chi2 value
cpu_time
computation time of forward solve [ms]
cpu_timeB
computation time of backward solve [ms]
llh
loglikelihood value
nJ
dimension of the augmented objective function for 2nd order ASA
ne
number of events
newton_maxsteps
maximal number of newton iterations for steady state calculation
nk
number of fixed parameters
nmaxevent
maximal number of occurring events (for every event type)
np
total number of model parameters
nplist
number of parameter for which sensitivities were requested
nt
number of considered timepoints
numerrtestfails
nt)
numerrtestfailsB
nt)
numnonlinsolvconvfails
number of linear solver convergence failures forward problem (dimension: nt)
numnonlinsolvconvfailsB
number of linear solver convergence failures backward problem (dimension: nt)
numrhsevals
nt)
numrhsevalsB
nt)
numsteps
nt)
numstepsB
nt)
nw
number of columns in w
nx
number of states
nx_solver
number of states with conservation laws applied
nx_solver_reinit
number of solver states to be reinitialized after preequilibration
nxtrue
number of states in the unaugmented system
ny
number of observables
nytrue
number of observables in the unaugmented system
nz
number of event outputs
nztrue
number of event outputs in the unaugmented system
o2mode
flag indicating whether second order sensitivities were requested
order
nt)
posteq_cpu_time
computation time of the steady state solver [ms] (postequilibration)
posteq_cpu_timeB
computation time of the steady state solver of the backward problem [ms] (postequilibration)
posteq_numlinsteps
number of linear steps by Newton step for steady state problem.
posteq_numsteps
number of Newton steps for steady state problem (preequilibration) [newton, simulation, newton] (length = 3) (postequilibration)
posteq_numstepsB
number of simulation steps for adjoint steady state problem (postequilibration) [== 0 if analytical solution worked, > 0 otherwise]
posteq_status
flags indicating success of steady state solver (postequilibration)
posteq_t
time when steadystate was reached via simulation (postequilibration)
posteq_wrms
weighted root-mean-square of the rhs when steadystate was reached (postequilibration)
preeq_cpu_time
computation time of the steady state solver [ms] (preequilibration)
preeq_cpu_timeB
computation time of the steady state solver of the backward problem [ms] (preequilibration)
preeq_numlinsteps
number of linear steps by Newton step for steady state problem.
preeq_numsteps
number of Newton steps for steady state problem (preequilibration) [newton, simulation, newton] (length = 3)
preeq_numstepsB
number of simulation steps for adjoint steady state problem (preequilibration) [== 0 if analytical solution worked, > 0 otherwise]
preeq_status
flags indicating success of steady state solver (preequilibration)
preeq_t
time when steadystate was reached via simulation (preequilibration)
preeq_wrms
weighted root-mean-square of the rhs when steadystate was reached (preequilibration)
pscale
scaling of parameterization (lin,log,log10)
rdata_reporting
reporting mode
res
nt*ny, row-major)
rz
nmaxevent x nz, row-major)
s2llh
(nJ-1) x nplist, row-major)
s2rz
second order parameter derivative of event trigger output (dimension: nmaxevent x nztrue x nplist x nplist, row-major)
sensi
sensitivity order
sensi_meth
sensitivity method
sigmay
nt x ny, row-major)
sigmaz
nmaxevent x nz, row-major)
sllh
nplist)
sres
nt*ny x nplist, row-major)
srz
nmaxevent x nz x nplist, row-major)
ssigmay
nt x nplist x ny, row-major)
ssigmaz
parameter derivative of event output standard deviation (dimension: nmaxevent x nz, row-major)
status
status code
sx
nt x nplist x nx, row-major)
sx0
nplist x nx, row-major)
sx_ss
nplist x nx, row-major)
sy
nt x nplist x ny, row-major)
sz
nmaxevent x nz, row-major)
ts
nt)
w
w data from the model (recurring terms in xdot, for imported SBML models from python, this contains the flux vector) (dimensions: nt x nw, row major)
x
nt x nx, row-major)
x0
nx)
x_ss
nx)
xdot
nx)
y
nt x ny, row-major)
z
nmaxevent x nz, row-major)