smash.Model#

class smash.Model(setup, mesh)[source]#

Primary data structure of the hydrological model smash.

Parameters:

setupdict: Model initialization setup dictionary (see: setup arguments).
meshdict: Model initialization mesh dictionary. (see: mesh arguments).

See also

save_setup: Save Model initialization setup dictionary.
read_setup: Read Model initialization setup dictionary.
save_mesh: Save Model initialization mesh dictionary.
read_mesh: Read Model initialization mesh dictionary.
generate_mesh: Automatic mesh generation.
save_model: Save Model object.
read_model: Read Model object.
save_model_ddt: Save some derived data types of the Model object to HDF5 file.
read_model_ddt: Read derived data types of the Model object from HDF5 file.

Examples

>>> setup, mesh = smash.load_dataset("cance")
>>> model = smash.Model(setup, mesh)
>>> model
Structure: 'gr-a'
Spatio-Temporal dimension: (x: 28, y: 28, time: 1440)
Last update: Initialization

Attributes:

input_data: The input data of the Model.
mesh: The mesh of the Model.
output: The output of the Model.
parameters: The parameters of the Model.
setup: The setup of the Model.
states: The states of the Model.

Methods

`ann_optimize`([net, optimizer, ...])	Optimize the Model using Artificial Neural Network.
`bayes_estimate`([sample, alpha, n, ...])	Estimate prior Model parameters/states using Bayesian approach.
`bayes_optimize`([sample, alpha, n, ...])	Optimize the Model using Bayesian approach.
`copy`()	Make a deepcopy of the Model.
`event_segmentation`([peak_quant, max_duration])	Compute segmentation information of flood events over all catchments of the Model.
`get_bound_constraints`([states])	Get the boundary constraints of the Model parameters/states.
`multiple_run`(sample[, jobs_fun, wjobs_fun, ...])	Compute Multiple Run of Model.
`optimize`([mapping, algorithm, ...])	Optimize the Model.
`prcp_indices`()	Compute precipitations indices of the Model.
`run`([inplace])	Run the Model.
`signatures`([sign, obs_comp, event_seg])	Compute continuous or/and flood event signatures of the Model.
`signatures_sensitivity`([problem, n, sign, ...])	Compute the first- and total-order variance-based sensitivity (Sobol indices) of spatially uniform hydrological model parameters on the output signatures.