pywatershed.base.ConservativeProcess

class pywatershed.base.ConservativeProcess(control, discretization, parameters, budget_type=None, metadata_patches=None, metadata_patch_conflicts='error')

Base class for representation of conservative physical processes.

ConservativeProcess is a base class for mass and energy conservation which extends the Process() class with a budget on mass (energy in the future). Please see Process() for many details on the design of this parent class. In ConservativeProcess only mass conservation is currently implemented. Budgets can optionally be established for mass (and eventually energ) and these can be enforced or simply diagnosed with the model run.

Conventions are adopted through the use of the following properties/methods:

mass_budget_terms/get_mass_budget_terms():

These terms must all in in the same units across all components of the budget (inputs, outputs, storage_changes). Diagnostic variables should not appear in the budget terms, only prognostic variables should.

_calculate():

This method is to be overridden by the subclass. Near the end of the method, the subclass should calculate its changes in mass and energy storage in an obvious way. As commented for mass_budget_terms, storage changes should only be tracked for prognostic variables. (For example is snow_water_equiv = snow_ice + snow_liquid, then storage changes for snow_ice and snow_liquid should be tracked and not for snow_water_equiv).

See also

pywatershed.base.Process, pywatershed.base.Budget

Parameters:

• control (Control) – A Control object

• discretization (Parameters) – A discretization object

• parameters (Parameters) – The parameters for this object

• budget_type (Optional[Literal[None, 'warn', 'error']]) – Use a budget and what action to take on budget imbalance.

• metadata_patches (Optional[dict[dict]]) – Override static metadata for any public parameter or variable – experimental.

• metadata_patch_conflicts (Literal['ignore', 'warn', 'error']) – How to handle metadata_patches conflicts. Experimental.

__init__(control, discretization, parameters, budget_type=None, metadata_patches=None, metadata_patch_conflicts='error')

Methods

__init__(control, discretization, parameters)
advance()	Advance the Process in time.
calculate(time_length, **kwargs)	Calculate Process terms for a time step
description()	A dictionary description of this Process.
finalize()	Finalizes the Process, including output methods.
get_dimensions()	Get a tuple of dimension names for this Process.
get_init_values()	Get a dictionary of initialization values for each public variable.
get_inputs()	Get a tuple of input variable names for this Process.
get_mass_budget_terms()	Get a dictionary of variable names for mass budget terms.
get_parameters()	Get a tuple of parameter names for this Process.
get_restart_variables()	Get a list of restart varible names.
get_variables()	Get a tuple of (public) variable names for this Process.
initialize_netcdf([output_dir, ...])	Initialize NetCDF output.
output()	Output data to previously initialized output types.
output_to_csv(pth)	Save each output variable to separate csv file in specified path
set_input_to_adapter(input_variable_name, ...)

Attributes

dimensions	A tuple of parameter names.
init_values	A dictionary of initial values for each public variable.
inputs	A tuple of input variable names.
mass_budget_terms	A dictionary of variable names for the mass budget terms.
parameters	A tuple of parameter names.
restart_variables	A tuple of restart variable names.
variables	A tuple of public variable names.

advance()

Advance the Process in time.

Returns:

None

calculate(time_length, **kwargs)

Calculate Process terms for a time step

Parameters:

simulation_time – current simulation time

Return type:

None

Returns:

None

classmethod description()

A dictionary description of this Process.

Return type:

dict

Returns:

All metadata for all variables in inputs, variables,parameters, and mass_budget_terms for this Process.

property dimensions: tuple

A tuple of parameter names.

finalize()

Finalizes the Process, including output methods. :rtype: None :returns: None

static get_dimensions()

Get a tuple of dimension names for this Process.

Return type:

tuple

static get_init_values()

Get a dictionary of initialization values for each public variable.

Return type:

dict

static get_inputs()

Get a tuple of input variable names for this Process.

Return type:

tuple

classmethod get_mass_budget_terms()

Get a dictionary of variable names for mass budget terms.

Return type:

dict

static get_parameters()

Get a tuple of parameter names for this Process.

Return type:

tuple

static get_restart_variables()

Get a list of restart varible names.

Return type:

list

classmethod get_variables()

Get a tuple of (public) variable names for this Process.

Return type:

tuple

property init_values: dict

A dictionary of initial values for each public variable.

initialize_netcdf(output_dir=None, separate_files=None, budget_args=None, output_vars=None)

Initialize NetCDF output.

Parameters:

• output_dir – base directory path or NetCDF file path if separate_files is True

• separate_files – boolean indicating if storage component output variables should be written to a separate file for each variable

• output_vars – list of variable names to outuput.

Returns:

None

property inputs: tuple

A tuple of input variable names.

property mass_budget_terms: dict

A dictionary of variable names for the mass budget terms.

output()

Output data to previously initialized output types. :rtype: None :returns: None

output_to_csv(pth)

Save each output variable to separate csv file in specified path

property parameters: tuple

A tuple of parameter names.

property restart_variables: tuple

A tuple of restart variable names.

set_input_to_adapter(input_variable_name, adapter)

property variables: tuple

A tuple of public variable names.