def __init__(self, image_1d, noise_map_1d, convolver, mapper, regularization):
self.mapper = mapper<EOL>self.regularization = regularization<EOL>self.blurred_mapping_matrix = convolver.convolve_mapping_matrix(mapping_matrix=mapper.mapping_matrix)<EOL>self.data_vector = inversion_util.data_vector_from_blurred_mapping_matrix_and_data(<EOL>blurred_mapping_matrix=self.blurred_mapping_matrix, image_1d=image_1d, noise_map_1d=noise_map_1d)<EOL>self.curvature_matrix = inversion_util.curvature_matrix_from_blurred_mapping_matrix(<EOL>blurred_mapping_matrix=self.blurred_mapping_matrix, noise_map_1d=noise_map_1d)<EOL>self.regularization_matrix =regularization.regularization_matrix_from_pixel_neighbors(pixel_neighbors=mapper.geometry.pixel_neighbors,<EOL>pixel_neighbors_size=mapper.geometry.pixel_neighbors_size)<EOL>self.curvature_reg_matrix = np.add(self.curvature_matrix, self.regularization_matrix)<EOL>self.solution_vector = np.linalg.solve(self.curvature_reg_matrix, self.data_vector)<EOL>
An inversion, which given an input image and noise-map reconstructs the image using a linear inversion, \
        including a convolution that accounts for blurring.

        The inversion uses a 2D pixelization to perform the reconstruction by mapping each pixelization pixel to a \
        set of image pixels via a mapper. The reconstructed pixelization is smoothed via a regularization scheme to \
        prevent over-fitting noise.

        Parameters
        -----------
        image_1d : ndarray
            Flattened 1D array of the observed image the inversion is fitting.
        noise_map_1d : ndarray
            Flattened 1D array of the noise-map used by the inversion during the fit.   
        convolver : ccd.convolution.Convolver
            The convolver used to blur the mapping matrix with the PSF.
        mapper : inversion.mappers.Mapper
            The mapping between the image-pixels (via its regular / sub-grid) and pixelization pixels.
        regularization : inversion.regularization.Regularization
            The regularization scheme applied to smooth the pixelization used to reconstruct the image for the \
            inversion

        Attributes
        -----------
        blurred_mapping_matrix : ndarray
            The matrix representing the blurred mappings between the image's sub-grid of pixels and the pixelization \
            pixels.
        regularization_matrix : ndarray
            The matrix defining how the pixelization's pixels are regularized with one another for smoothing (H).
        curvature_matrix : ndarray
            The curvature_matrix between each pixelization pixel and all other pixelization pixels (F).
        curvature_reg_matrix : ndarray
            The curvature_matrix + regularization matrix.
        solution_vector : ndarray
            The vector containing the reconstructed fit to the hyper.