This is the optimizer-function that is minimized for the inverse, production based model. It takes as input a vector of the influx, as well as the values of the production to be optimized.
This function is embedded in pro_flux()
and is not intended to be
used manually.
Usage
prod_optim(
X,
height,
DS,
D0 = NA,
C0,
pmap,
cmap,
conc,
dstor = 0,
zero_flux = TRUE,
F0 = 0,
known_flux = NA,
known_flux_factor = 0,
DSD0_optim = FALSE,
layer_couple,
wmap,
evenness_factor
)
Arguments
- X
(numeric vector) specifying the production rates to be optimized
- height
(numeric vector) giving the height of each step
- DS
(numeric vector) giving the DS of each step
- D0
RESERVED FOR FUTURE EXPANSION
- C0
(numeric) The concentration at the bottom of the lowermost step.
- pmap
(integer vector) assigning a production from X to each step
- cmap
(integer vector) assigning the modeled concentrations to the observed concentrations as there can be multiple observations per depth
- conc
(numeric) the observed concentrations (in the same unit as the modelled concentrations).
- dstor
RESERVED FOR FUTURE EXPANSION
- zero_flux
(logical) Applies the zero-flux boundary condition(
TRUE
)? IfFALSE
, the first value inX
. represents the incoming flux to the lowest layer.- F0
(numeric) flux into lowest layer.
- known_flux
RESERVED FOR FUTURE EXPANSION
- known_flux_factor
RESERVED FOR FUTURE EXPANSION
- DSD0_optim
RESERVED FOR FUTURE EXPANSION
- layer_couple
(numeric vector) A vector defining the weights that bind the different layers together. If all is zero, no penalisation for stark differences between the optimized production rates of adjacent layers takes place
- wmap
(numeric) A vector defining the weights of the different concentration measurements in the RMSE calculation.
- evenness_factor
(numeric) Defines strong should stark differences between the production rates and very small production rates be penalized.
See also
Other proflux:
prod_mod_conc()