simple_models⚓︎
A collection of trivial toy models.
lin_1d
⚓︎
linear 1x150 model (or whatever), just make observations of the state at given positions.
__init__(input_dict=None, m=None)
⚓︎
Two inputs here. A dictionary of keys, or parameter directly.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
input_dict
|
dict
|
Dictionary containing all information required to run the simulator. It may come from, for example, an init file. |
None
|
m
|
int
|
Parameter to make predicted data. |
None
|
Changelog
- ST 7/9-15
nonlin_onedimmodel
⚓︎
Class of simple 1D forward model for testing purposes.
__init__(input_dict=None)
⚓︎
Two inputs here. A dictionary of keys, or parameter directly.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
input_dict
|
contains all information the run the simulator (may come from, e.g., an init file) |
None
|
sevenmountains
⚓︎
The objective function is the elevations of the seven mountains around bergen, to test optimization algorithm
__init__(input_dict=None, state=None)
⚓︎
call_sim(path=None)
⚓︎
check_sim_end(current_run)
⚓︎
Check if a simulation that has run in the background is finished. For ensemble-based methods, there can possibly be several folders with simulations, and each folder must be checked for finished runs. To check if simulation is done we search for .resp file which is the output in a successful run.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
current_run
|
list
|
List of ensemble members currently running simulation. |
required |
Returns:
| Name | Type | Description |
|---|---|---|
member |
int
|
Ensemble member that is finished. |
Changelog
- ST 9/5-18
get_sim_results(which_resp, ext_data_info=None, member=None)
⚓︎
Get forward simulation results. Simply load the numpy array...
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
which_resp
|
str
|
Specifies which of the responses is to be outputted (just one data type in this case). |
required |
member
|
int
|
Ensemble member that is finished. |
None
|
Returns:
| Name | Type | Description |
|---|---|---|
y |
ndarray
|
Array containing the predicted data (response). |
Changelog
- ST 3/6-16
run_fwd_sim(en_member=None, folder=os.getcwd(), wait_for_proc=False)
⚓︎
Set up and run a forward simulation in an fwd_sim. The parameters for the forward simulation is set in setup_fwd_run. All the steps to set up and run a forward simulation is done in this object.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
en_member
|
int
|
Index of the ensemble member to be run. |
None
|
folder
|
str
|
Folder where the forward simulation is run. |
getcwd()
|
Changelog
- ST 3/6-16
setup_fwd_run(state, assim_ind=None, true_ind=None)
⚓︎
Set input parameters from an fwd_sim in the simulation to get predicted data. Parameters can be an ensemble or a single array.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
state
|
dict
|
Dictionary of input parameter. It can be either a single 'state' or an ensemble of 'state'. |
required |
Other Parameters:
| Name | Type | Description |
|---|---|---|
true_ind |
list
|
The list of observed data assimilation indices. |
assim_ind |
list
|
List with information on assimilation order for ensemble-based methods. |
Changelog
- ST 3/6-16