Source code for romtools.composite_vector_space

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from typing import List
import numpy as np
from romtools.vector_space import VectorSpace




class CompositeVectorSpace:
    '''
    Constructs a composite vector space out of a list of vector spaces
    Different vector spaces need to have the same number of spatial DOFs
    '''

    def __init__(self, list_of_vector_spaces: List[VectorSpace]):
        '''
        Inputs: list_of_vector_spaces: list[VectorSpace] containing the list of vector spaces to combine
        '''
        # Computed dimensions and ensure vector spaces are compatable
        self.__get_extent_and_check_compatability(list_of_vector_spaces)

        # Construct basis as a list of local bases
        self.__construct_compact_basis(list_of_vector_spaces)

    def extents(self) -> np.ndarray:
        return self.__extent

    def get_shift_vector(self) -> np.ndarray:
        return self.__construct_global_shift_vector()

    def get_basis(self) -> np.ndarray:
        return self.__construct_full_basis()

    def get_compact_basis(self) -> List[np.ndarray]:
        return self.__compact_basis

    def get_compact_shift_vector(self) -> List[np.ndarray]:
        return self.__compact_shift_vector

    def __get_extent_and_check_compatability(self, list_of_vector_spaces):
        # Checks that dimensions of the vector spaces match
        # and assigns self.__extent
        dims = np.zeros(len(list_of_vector_spaces))
        n_vector_spaces = len(list_of_vector_spaces)
        n_vars = 0
        total_number_of_bases = 0
        for i in range(0, n_vector_spaces):
            local_vector_space = list_of_vector_spaces[i]
            local_vector_space_dimensions = local_vector_space.get_basis().shape
            n_vars += local_vector_space_dimensions[0]
            dims[i] = local_vector_space_dimensions[1]
            total_number_of_bases += local_vector_space_dimensions[2]

        nx = int(dims[0])
        n_vars = int(n_vars)
        total_number_of_bases = int(total_number_of_bases)
        self.__extent = np.array([n_vars, nx, total_number_of_bases], dtype='int')
        assert np.allclose(np.diff(dims),
                           np.zeros(dims.size-1)
               ), "Error constructing composite vector space, not all spaces have the same spatial dimension"

    def __construct_global_shift_vector(self):
        # Constructs the shift vector for the composite vector space
        shift_vector = self.__compact_shift_vector[0]
        for local_shift_vector in self.__compact_shift_vector[1:]:
            shift_vector = np.append(shift_vector, local_shift_vector, axis=0)
        return shift_vector

    def __construct_full_basis(self):
        # Constructs a dense basis for the composite vector space
        basis = np.zeros((self.__extent[0], self.__extent[1], self.__extent[2]))
        start_var_index = 0
        start_basis_index = 0
        for local_basis in self.__compact_basis:
            dim = local_basis.shape
            basis[start_var_index:start_var_index+dim[0], :, start_basis_index:start_basis_index+dim[2]] = local_basis
            start_var_index += dim[0]
            start_basis_index += dim[2]
        return basis

    def __construct_compact_basis(self, list_of_vector_spaces):
        # Constructs a list of bases.
        # This is much more efficient in terms of memory
        self.__compact_basis = [space.get_basis() for space in list_of_vector_spaces]
        self.__compact_shift_vector = [space.get_shift_vector() for space in list_of_vector_spaces]