Grid

Grid#

class fridom.shallowwater.grid.spectral.grid.Grid(N: list[int], L: list[int], *args: any, **kwargs: dict)[source]#

Bases: Grid

__init__(N: list[int], L: list[int], *args: any, **kwargs: dict) → None[source]#

Methods

`__init__`(N, L, args, *kwargs)
`create_array`([pad, spectral, topo])	Create an array.
`create_random_array`([seed, pad, spectral, topo])	Create a random array.
`cumulative_integral`(field, axis[, direction])	Compute the cumulative integral of a field along a given axis.
`fft`(arr[, padding, bc_types, positions])	Perform a (fast) fourier transform on the input array.
`get_mesh`([position, spectral])	Get the meshgrid of the grid points.
`ifft`(arr[, padding, bc_types, positions])	Perform an inverse (fast) fourier transform on the input array.
`integrate`(field[, axes])	Integrate a scalar field over a given domain.
`max`(field[, axes])	Compute the maximum of a field over the given axes.
`min`(field[, axes])	Compute the minimum of a field over the given axes.
`omega`(k[, use_discrete])	Compute the dispersion relation of the model.
`pad`(arr)	Add halo padding to an array.
`setup`(mset)	Initialize the grid from the model settings.
`sum`(field[, axes])	Sum a field over the given axes.
`sync`(arr[, flat_axes])	Synchronize the halo (boundary) points of an array across all MPI ranks.
`sync_multi`(arrs)	Synchronize the halo (boundary) points of multiple arrays across all MPI ranks.
`unpad`(arr)	Remove the halo padding from an array.
`vec_p`(s[, use_discrete])	Computes the projection vector of the linear operator of the mode s.
`vec_q`(s[, use_discrete])	Computes the eigenvector of the linear operator of the mode s.

Attributes

`K`	Spectral meshgrid on the local domain.
`L`	Domain size in each direction.
`N`	Grid points in each direction.
`X`	The meshgrid of the grid points.
`cell_center`	The position of the cell centers.
`characteristic_function`	The characteristic function of the grid (1 inside the domain, 0 outside).
`dV`	The volume element of the grid.
`diff_module`	The differential operator module.
`domain_decomp`	The domain decomposition object.
`dx`	The grid spacing in each dimension.
`fourier_transform_available`	Indicates whether the grid supports fast fourier transforms.
`halo`	The halo size of the grid.
`info`	Return a dictionary with information about the grid.
`interp_module`	The interpolation operator module.
`k_global`	Global spectral k-vectors.
`k_local`	Spectral k-vectors on the local domain.
`mpi_available`	Indicates whether the grid supports MPI parallelization.
`mset`	The model settings object.
`n_dims`	The number of dimensions of the grid.
`omega_analytical`	Analytical dispersion relation.
`omega_space_discrete`	Dispersion relation with space-discretization effects.
`omega_time_discrete`	Dispersion relation with space-time-discretization effects.
`periodic_bounds`	A tuple of booleans indicating whether the grid is periodic in each dimension.
`spectral_grid`	Indicates whether the grid is a spectral grid.
`total_grid_points`	The total number of grid points in the grid.
`water_mask`	Get the water mask.
`x_global`	The x-vector of the global grid points.

omega(k: tuple[float] | tuple[ndarray], use_discrete: bool = False) → ndarray[source]#

Compute the dispersion relation of the model.

ktuple[float] | tuple[ndarray]: The wave numbers
use_discretebool (default: False): Whether to include space-discretization effects.

vec_q(s: int, use_discrete=False) → State[source]#

Computes the eigenvector of the linear operator of the mode s.

sint: The mode (which eigenvalue / eigenvector to compute).
use_discretebool (default: True): Whether to include space-discretization effects.

vec_p(s: int, use_discrete=False) → State[source]#

Computes the projection vector of the linear operator of the mode s.

sint: The mode (which eigenvalue / eigenvector to compute).
use_discretebool (default: True): Whether to include space-discretization effects.