Grid

class fridom.nonhydro.grid.spectral.grid.Grid(N: list[int], L: list[int], periodic_bounds: list[bool] = [True, True, True], decomposition: str = 'slab')

Bases: Grid

__init__(N: list[int], L: list[int], periodic_bounds: list[bool] = [True, True, True], decomposition: str = 'slab')

Methods

__init__(N, L[, periodic_bounds, decomposition])
create_array([pad, spectral, topo])	Create an array.
create_random_array([seed, pad, spectral, topo])	Create a random array.
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.
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.
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.
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.
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

Compute the dispersion relation of the model.

Parameters

ktuple[float] | tuple[ndarray]

The wave numbers

use_discretebool (default: False)

Whether to include space-discretization effects.

Returns

ndarray

The dispersion relation (omega(k)).

vec_q(s: int, use_discrete=False) → State

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

Parameters

sint

The mode (which eigenvalue / eigenvector to compute).

use_discretebool (default: True)

Whether to include space-discretization effects.

Returns

StateBase

The eigenvector of the linear operator.

vec_p(s: int, use_discrete=False) → State

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

Parameters

sint

The mode (which eigenvalue / eigenvector to compute).

use_discretebool (default: True)

Whether to include space-discretization effects.

Returns

StateBase

The projection vector of the linear operator.