4DVAR variational inversions (4dvar
/ std
)¶
Description¶
The variational mode computes the minimum of a function (called simulator
) provided a minimizer
.
It can be applied to the minimization of any function, but in practice,
it is mostly used to compute the minimum of the Bayesian Gaussian cost function.
Yaml arguments¶
The following arguments are used to configure the plugin. pyCIF will return an exception at the initialization if mandatory arguments are not specified, or if any argument does not fit accepted values or type:
Optional arguments¶
save_out_netcdf: (optional): False
Save final posterior vector as NetCDF. This argument overwrites the corresponding argument in the
controlvect
.accepted type: bool
montecarlo: (optional)
Number of perturbed inversions to compute posterior inversions.
- accepted structure:
nsample: (mandatory)
Number of members in the Monte-Carlo. The control run with no perturbation will be computed as the last member of the ensemble.
accepted type: True
perturb_x: (optional): True
Perturb the control vector or not
accepted type: bool
seed_x: (optional)
Seed for the random generator for perturbing x.Useful to run the same perturbationsfor various cases
accepted type: int
perturb_y: (optional): True
Perturb the observation vector or not
accepted type: bool
seed_y: (optional)
Seed for the random generator for perturbing y.Useful to run the same perturbationsfor various cases
accepted type: int
compute_reference: (optional): True
Recompute the unperturbed member
accepted type: bool
aggregate_results: (optional): False
Aggregate ensemble results and re-run prior/posterior cost functions
accepted type: bool
Requirements¶
The current plugin requires the present plugins to run properly:
Requirement name |
Requirement type |
Explicit definition |
Any valid |
Default name |
Default version |
---|---|---|---|---|---|
obsvect |
False |
True |
standard |
std |
|
controlvect |
True |
True |
standard |
std |
|
obsoperator |
True |
True |
standard |
std |
|
minimizer |
True |
True |
M1QN3 |
std |
|
simulator |
True |
True |
gausscost |
std |
|
platform |
True |
True |
None |
None |
Yaml template¶
Please find below a template for a Yaml configuration:
1mode:
2 plugin:
3 name: 4dvar
4 version: std
5 type: mode
6
7 # Optional arguments
8 save_out_netcdf: XXXXX # bool
9 montecarlo:
10 nsample: XXXXX # True
11 perturb_x: XXXXX # bool
12 seed_x: XXXXX # int
13 perturb_y: XXXXX # bool
14 seed_y: XXXXX # int
15 compute_reference: XXXXX # bool
16 aggregate_results: XXXXX # bool