API Reference

This page provides an auto-generated summary of multimodemodel’s API

Parameter([g, H, rho_0, a_h, gamma_h, ...])	Class to organise all parameters.
Parameter.f	Getter of the dictionary holding the Coriolis parameter.
Parameter.split(splitter)	Split Parameter's spatially dependent data.
Parameter.merge(others, merger)	Merge Parameter's spatially varying data.
Parameter.__eq__(other)	Return true if other is identical or the same as self.
Variable(data, grid, time)	Variable class consisting of the data, a Grid instance and a time stamp.
Variable.data
Variable.grid
Variable.time
Variable.split(splitter)	Split variable.
Variable.merge(others, merger)	Merge variable.
Variable.copy()	Return a copy.
Variable.as_dataarray	Return variable as xarray.DataArray.
Variable.safe_data	Return data or, if it is None, a zero array of appropriate shape.
Variable.__eq__(other)	Return true if other is identical or the same as self.
Variable.__add__(other)	Add data of to variables.
State(**kwargs)	State class.
State.split(splitter)	Split state.
State.merge(others, merger)	Merge variables.
State.__add__(other)	Add all variables of two states.
StateDeque	Deque of State objects.
StateDeque.split(splitter)	Split StateDeque.
StateDeque.merge(others, merger)	Merge StateDeques.
Domain(state[, history, parameter, id, ...])	Domain classes.
Domain.increment_iteration()	Return incremented iteration from domain.
Domain.split(splitter)	Split domain.
Domain.merge(others, merger)	Merge domains.
Domain.copy()	Return deepcopy of self.
Domain.__eq__(other)	Return true if other is identical or the same as self.
Grid(x, y[, z, mask, dx, dy, dz])	Grid information.
Grid.ndim	Return number of dimensions.
Grid.shape	Return shape tuple of grid.
Grid.dim_x	Return axis of x dimension.
Grid.dim_y	Return axis of x dimension.
Grid.dim_z	Return axis of x dimension.
Grid.cartesian(x, y[, z, mask])	Generate a Cartesian grid.
Grid.regular_lat_lon(lon_start, lon_end, ...)	Generate a regular spherical grid.
Grid.__eq__(other)	Return true if other is identical or the same as self.
StaggeredGrid(eta, u, v, q)	Staggered Grid.
StaggeredGrid.split(splitter)	Split staggered grids.
StaggeredGrid.merge(others, merger)	Merge staggered grids.
StaggeredGrid.cartesian_c_grid([shift])	Generate a Cartesian Arakawa C-Grid.
StaggeredGrid.regular_lat_lon_c_grid([shift])	Generate a Arakawa C-grid for a regular longitude/latitude grid.
GridShift(value[, names, module, qualname, ...])	Direction of shift of staggered grids with respect to the eta-grid.
RegularSplitMerger(parts, dim)	Implements splitting and merging into regular grid.
BorderSplitter(slice, axis)	Implements splitting off stripes along a dimension.
BorderMerger(width, axis)	Merges the borders with a Domain along a dimension.
Border(state, width, dim, iteration[, ...])	Implementation of Border class from API on State class.
Tail()	Implement Tailor class from API.
integrate(initial_state, params, RHS[, ...])	Integrate a system of differential equations.
linearised_SWE(state, params)	Compute RHS of the linearised shallow water equations.
TimeSteppingFunction	alias of TimeSteppingFunctionBase[State, StateDeque]
StateIncrement	alias of State
time_stepping_function(n_rhs, n_state)	Decorate function by adding n_rhs and n_state attributes.
euler_forward	Base class for time stepping function wrapper.
adams_bashforth2	Base class for time stepping function wrapper.
adams_bashforth3	Base class for time stepping function wrapper.
Solver(rhs, ts_schema[, step])	Implement Solver class from API for use with any provided function.
Solver.rhs(state, parameter)	Evaluate right-hand-side function.
Solver.integrate(domain)	Integrate set of PDEs on domain.
Solver.integrate_border(domain, border, ...)	Integrate set of PDEs on a border of a domian.
Solver.get_border_width()	Retuns fixed border width.
coriolis_i(state, params)	Compute the acceleration due to the Coriolis force along the first dimension.
coriolis_j(state, params)	Compute acceleration due to Coriolis force along second dimension.
divergence_j(state, params)	Compute divergence of flow along second dimension with centered differences.
divergence_i(state, params)	Compute divergence of flow along first dimension with centered differences.
pressure_gradient_j(state, params)	Compute the second component of the pressure gradient.
pressure_gradient_i(state, params)	Compute the pressure gradient along the first dimension.
sum_states(states[, keep_time])	Sum states using optimized implementations.
sum_vars(variables[, keep_time])	Sum variables using optimized implementations.
linear_combination(factors, arrays)	Return linear combination of arrays.
CoriolisFunc	alias of Callable[[ndarray], ndarray]
f_constant([f])	Return a closure that returns a constant Coriolis parameter.
beta_plane(f0, beta, y0)	Return a closure that computes the Coriolis parameter on a beta plane.
f_on_sphere([omega])	Return a closure that computes the Coriolis parameter on a sphere.
Workflow(domain, solver)	Run model on a single process.
DaskWorkflow(domain, solver, client, splitter)	Workflow distributed on a Dask cluster.