capytaine.green_functions.abstract_green_function module

Abstract structure of a class used to compute the Green function

class capytaine.green_functions.abstract_green_function.AbstractGreenFunction[source]

Bases: ABC

Abstract method to evaluate the Green function.

abstractmethod evaluate(mesh1, mesh2, free_surface, water_depth, wavenumber, adjoint_double_layer=True, early_dot_product=True, diagonal_term_in_double_layer=True)[source]

Assemble the influence matrices between mesh1 and mesh2.

Parameters:

  • mesh1 (MeshLike or array of shape (n, 3)) – mesh of the receiving body (where the potential is measured), or an array of points (only supported if only S is wanted or early_dot_product is False).

  • mesh2 (MeshLike) – mesh of the source body (over which the source distribution is integrated)

  • free_surface (float) – position of the free surface

  • water_depth (float) – constant depth of water

  • wavenumber (float) – wavenumber

  • adjoint_double_layer (bool, optional) – compute double layer for direct method (D) or adjoint double layer for indirect method (K) matrices (default: True)

  • early_dot_product (bool, optional) – if True, K is the matrix of ∫∇G·n, if False it is the gradient ∫∇G (default: True)

  • diagonal_term_in_double_layer (bool, optional) – if True, add the I/2 term in the double layer operator (default: True)

Returns:

the matrices S and K, with shapes (n, m) for S and (n, m) for K if early_dot_product is True or (3, n, m) otherwise, where n is the number of receiving points of mesh1 and m the number of faces of mesh2.

Return type:

tuple of arrays

exportable_settings: dict
floating_point_precision: str
matrices_array_backend = <module 'array_api_compat.numpy' from '/home/runner/work/_temp/setup-uv-cache/archive-v0/0Rudd_diFPWAFKR-/lib/python3.12/site-packages/array_api_compat/numpy/__init__.py'>
matrices_device = 'cpu'
exception capytaine.green_functions.abstract_green_function.GreenFunctionEvaluationError[source]

Bases: Exception