InterWENO

class fridom.framework.grid.cartesian.weno_interpolation.InterWENO(order: int = 5, eps: float = 1e-10)

Bases: InterENO

WENO interpolation module.

Description

TODO

Parameters

orderint

Order of the WENO interpolation (must be odd), default is 5.

epsfloat

Small value to avoid division by zero, default is 1e-10.

__init__(order: int = 5, eps: float = 1e-10) → None

Methods

__init__([order, eps])
compute_beta_coeffs(stencil_size)	Coefficients that are used to compute the smoothness indicators.
compute_d_coeffs(stencil_size)	Compute the coefficients d_i for the WENO reconstruction.
compute_polynomial_coefficients_cell_average(...)	Polynomial coefficients for the ENO interpolation for cell averages.
compute_polynomial_coefficients_pointwise(...)	Polynomial coefficients for the ENO interpolation for pointwise values.
compute_smoothness_indicators(f, axis)	Compute the smoothness indicators for each stencil.
compute_start_of_stencil(f, axis, destination)	Compute the start of the stencil for the ENO interpolation.
disable()	Disable the module.
enable()	Enable the module.
interpolate(f, destination)	Interpolate the field to the destination position.
is_enabled()	Whether the module is enabled or not.
reconstruct(f, destination)	Reconstruct the field at the destination points using WENO interpolation.
reset()	Stop and start the module.
setup(mset[, setup_mode])	Set the module up.
start()	Start the module.
stop()	Stop the module.
update(mz)	Update the model state.

Attributes

diff_module	The differentiation module to be used by this module.
grid	The grid of the model settings.
info	Return a dictionary with information about the time stepper.
interp_module	The interpolation module to be used by this module.
is_setup	Whether the module is set up.
max_implementation_order
mset	The model settings.
name
required_halo	The required halo points for this module.

name = 'WENO Interpolation'

max_implementation_order = 5

compute_d_coeffs(stencil_size: int) → np.ndarray

Compute the coefficients d_i for the WENO reconstruction.

compute_beta_coeffs(stencil_size: int) → tuple[np.ndarray]

Coefficients that are used to compute the smoothness indicators.

reconstruct(f: ScalarField, destination: Position) → tuple[ScalarField]

Reconstruct the field at the destination points using WENO interpolation.

Parameters

ffr.ScalarField

The field to be reconstructed.

destinationfr.grid.Position

The position where the field is to be reconstructed. (Can only reconstuct in one dimension at a time)

Returns

tuple[fr.ScalarField]

Left and right biased reconstructed fields. (Should be combined with a flux limiter to get the final reconstructed field)

compute_smoothness_indicators(f: fr.ScalarField, axis: int) → list[np.ndarray]

Compute the smoothness indicators for each stencil.