// Uses `nalgebra` crate to invoke `np_linalg` and `sp_linalg` functions // When converting between `nalgebra::Matrix` and `NDArray` following considerations are necessary // // * Both `nalgebra::Matrix` and `NDArray` require their content to be stored in row-major order // * `NDArray` data pointer can be directly read and converted to `nalgebra::Matrix` (row and column number must be known) // * `nalgebra::Matrix::as_slice` returns the content of matrix in column-major order and initial data needs to be transposed before storing it in `NDArray` data pointer use core::slice; use nalgebra::DMatrix; fn report_error( error_name: &str, fn_name: &str, file_name: &str, line_num: u32, col_num: u32, err_msg: &str, ) -> ! { panic!( "Exception {} from {} in {}:{}:{}, message: {}", error_name, fn_name, file_name, line_num, col_num, err_msg ); } pub struct InputMatrix { pub ndims: usize, pub dims: *const usize, pub data: *mut f64, } impl InputMatrix { fn get_dims(&mut self) -> Vec { let dims = unsafe { slice::from_raw_parts(self.dims, self.ndims) }; dims.to_vec() } } /// # Safety /// /// `mat1` and `mat2` should point to a valid 2DArray of `f64` floats in row-major order #[no_mangle] pub unsafe extern "C" fn np_linalg_matmul( mat1: *mut InputMatrix, mat2: *mut InputMatrix, out: *mut InputMatrix, ) { let mat1 = mat1.as_mut().unwrap(); let mat2 = mat2.as_mut().unwrap(); let out = out.as_mut().unwrap(); if !(mat1.ndims == 2 && mat2.ndims == 2) { let err_msg = format!( "expected 2D Vector Input, but received {}D and {}D input", mat1.ndims, mat2.ndims ); report_error("ValueError", "np_matmul", file!(), line!(), column!(), &err_msg); } let dim1 = (*mat1).get_dims(); let dim2 = (*mat2).get_dims(); if dim1[1] != dim2[0] { let err_msg = format!( "shapes ({},{}) and ({},{}) not aligned: {} (dim 1) != {} (dim 0)", dim1[0], dim1[1], dim2[0], dim2[1], dim1[1], dim2[0] ); report_error("ValueError", "np_matmul", file!(), line!(), column!(), &err_msg); } let outdim = out.get_dims(); let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) }; let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) }; let data_slice2 = unsafe { slice::from_raw_parts_mut(mat2.data, dim2[0] * dim2[1]) }; let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1); let matrix2 = DMatrix::from_row_slice(dim2[0], dim2[1], data_slice2); let mut result = DMatrix::::zeros(outdim[0], outdim[1]); matrix1.mul_to(&matrix2, &mut result); out_slice.copy_from_slice(result.transpose().as_slice()); } /// # Safety /// /// `mat1` should point to a valid 2DArray of `f64` floats in row-major order #[no_mangle] pub unsafe extern "C" fn np_linalg_cholesky(mat1: *mut InputMatrix, out: *mut InputMatrix) { let mat1 = mat1.as_mut().unwrap(); let out = out.as_mut().unwrap(); if mat1.ndims != 2 { let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims); report_error("ValueError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg); } let dim1 = (*mat1).get_dims(); if dim1[0] != dim1[1] { let err_msg = format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]); report_error("LinAlgError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg); } let outdim = out.get_dims(); let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) }; let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) }; let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1); let result = matrix1.cholesky(); match result { Some(res) => { out_slice.copy_from_slice(res.unpack().transpose().as_slice()); } None => { report_error( "LinAlgError", "np_linalg_cholesky", file!(), line!(), column!(), "Matrix is not positive definite", ); } }; } /// # Safety /// /// `mat1` should point to a valid 2DArray of `f64` floats in row-major order #[no_mangle] pub unsafe extern "C" fn np_linalg_qr( mat1: *mut InputMatrix, out_q: *mut InputMatrix, out_r: *mut InputMatrix, ) { let mat1 = mat1.as_mut().unwrap(); let out_q = out_q.as_mut().unwrap(); let out_r = out_r.as_mut().unwrap(); if mat1.ndims != 2 { let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims); report_error("ValueError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg); } let dim1 = (*mat1).get_dims(); let outq_dim = (*out_q).get_dims(); let outr_dim = (*out_r).get_dims(); let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) }; let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, outq_dim[0] * outq_dim[1]) }; let out_r_slice = unsafe { slice::from_raw_parts_mut(out_r.data, outr_dim[0] * outr_dim[1]) }; // Refer to https://github.com/dimforge/nalgebra/issues/735 let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1); let res = matrix1.qr(); let (q, r) = res.unpack(); // Uses different algo need to match numpy out_q_slice.copy_from_slice(q.transpose().as_slice()); out_r_slice.copy_from_slice(r.transpose().as_slice()); } /// # Safety /// /// `mat1` should point to a valid 2DArray of `f64` floats in row-major order #[no_mangle] pub unsafe extern "C" fn np_linalg_svd( mat1: *mut InputMatrix, outu: *mut InputMatrix, outs: *mut InputMatrix, outvh: *mut InputMatrix, ) { let mat1 = mat1.as_mut().unwrap(); let outu = outu.as_mut().unwrap(); let outs = outs.as_mut().unwrap(); let outvh = outvh.as_mut().unwrap(); if mat1.ndims != 2 { let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims); report_error("ValueError", "np_linalg_svd", file!(), line!(), column!(), &err_msg); } let dim1 = (*mat1).get_dims(); let outu_dim = (*outu).get_dims(); let outs_dim = (*outs).get_dims(); let outvh_dim = (*outvh).get_dims(); let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) }; let out_u_slice = unsafe { slice::from_raw_parts_mut(outu.data, outu_dim[0] * outu_dim[1]) }; let out_s_slice = unsafe { slice::from_raw_parts_mut(outs.data, outs_dim[0]) }; let out_vh_slice = unsafe { slice::from_raw_parts_mut(outvh.data, outvh_dim[0] * outvh_dim[1]) }; let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1); let result = matrix.svd(true, true); out_u_slice.copy_from_slice(result.u.unwrap().transpose().as_slice()); out_s_slice.copy_from_slice(result.singular_values.as_slice()); out_vh_slice.copy_from_slice(result.v_t.unwrap().transpose().as_slice()); } /// # Safety /// /// `mat1` should point to a valid 2DArray of `f64` floats in row-major order #[no_mangle] pub unsafe extern "C" fn np_linalg_inv(mat1: *mut InputMatrix, out: *mut InputMatrix) { let mat1 = mat1.as_mut().unwrap(); let out = out.as_mut().unwrap(); if mat1.ndims != 2 { let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims); report_error("ValueError", "np_linalg_inv", file!(), line!(), column!(), &err_msg); } let dim1 = (*mat1).get_dims(); if dim1[0] != dim1[1] { let err_msg = format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]); report_error("LinAlgError", "np_linalg_inv", file!(), line!(), column!(), &err_msg); } let outdim = out.get_dims(); let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) }; let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) }; let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1); if !matrix.is_invertible() { report_error( "LinAlgError", "np_linalg_inv", file!(), line!(), column!(), "no inverse for Singular Matrix", ); } let inv = matrix.try_inverse().unwrap(); out_slice.copy_from_slice(inv.transpose().as_slice()); } /// # Safety /// /// `mat1` should point to a valid 2DArray of `f64` floats in row-major order #[no_mangle] pub unsafe extern "C" fn np_linalg_pinv(mat1: *mut InputMatrix, out: *mut InputMatrix) { let mat1 = mat1.as_mut().unwrap(); let out = out.as_mut().unwrap(); if mat1.ndims != 2 { let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims); report_error("ValueError", "np_linalg_pinv", file!(), line!(), column!(), &err_msg); } let dim1 = (*mat1).get_dims(); let outdim = out.get_dims(); let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) }; let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) }; let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1); let svd = matrix.svd(true, true); let inv = svd.pseudo_inverse(1e-15); match inv { Ok(m) => { out_slice.copy_from_slice(m.transpose().as_slice()); } Err(err_msg) => { report_error("LinAlgError", "np_linalg_pinv", file!(), line!(), column!(), err_msg); } } } /// # Safety /// /// `mat1` should point to a valid 2DArray of `f64` floats in row-major order #[no_mangle] pub unsafe extern "C" fn sp_linalg_lu( mat1: *mut InputMatrix, out_l: *mut InputMatrix, out_u: *mut InputMatrix, ) { let mat1 = mat1.as_mut().unwrap(); let out_l = out_l.as_mut().unwrap(); let out_u = out_u.as_mut().unwrap(); if mat1.ndims != 2 { let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims); report_error("ValueError", "sp_linalg_lu", file!(), line!(), column!(), &err_msg); } let dim1 = (*mat1).get_dims(); let outl_dim = (*out_l).get_dims(); let outu_dim = (*out_u).get_dims(); let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) }; let out_l_slice = unsafe { slice::from_raw_parts_mut(out_l.data, outl_dim[0] * outl_dim[1]) }; let out_u_slice = unsafe { slice::from_raw_parts_mut(out_u.data, outu_dim[0] * outu_dim[1]) }; let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1); let (_, l, u) = matrix.lu().unpack(); out_l_slice.copy_from_slice(l.transpose().as_slice()); out_u_slice.copy_from_slice(u.transpose().as_slice()); } /// # Safety /// /// `mat1` should point to a valid 2DArray of `f64` floats in row-major order #[no_mangle] pub unsafe extern "C" fn sp_linalg_schur( mat1: *mut InputMatrix, out_t: *mut InputMatrix, out_z: *mut InputMatrix, ) { let mat1 = mat1.as_mut().unwrap(); let out_t = out_t.as_mut().unwrap(); let out_z = out_z.as_mut().unwrap(); if mat1.ndims != 2 { let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims); report_error("ValueError", "sp_linalg_schur", file!(), line!(), column!(), &err_msg); } let dim1 = (*mat1).get_dims(); if dim1[0] != dim1[1] { let err_msg = format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]); report_error("LinAlgError", "np_linalg_schur", file!(), line!(), column!(), &err_msg); } let out_t_dim = (*out_t).get_dims(); let out_z_dim = (*out_z).get_dims(); let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) }; let out_t_slice = unsafe { slice::from_raw_parts_mut(out_t.data, out_t_dim[0] * out_t_dim[1]) }; let out_z_slice = unsafe { slice::from_raw_parts_mut(out_z.data, out_z_dim[0] * out_z_dim[1]) }; let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1); let (z, t) = matrix.schur().unpack(); out_t_slice.copy_from_slice(t.transpose().as_slice()); out_z_slice.copy_from_slice(z.transpose().as_slice()); } /// # Safety /// /// `mat1` should point to a valid 2DArray of `f64` floats in row-major order #[no_mangle] pub unsafe extern "C" fn sp_linalg_hessenberg( mat1: *mut InputMatrix, out_h: *mut InputMatrix, out_q: *mut InputMatrix, ) { let mat1 = mat1.as_mut().unwrap(); let out_h = out_h.as_mut().unwrap(); let out_q = out_q.as_mut().unwrap(); if mat1.ndims != 2 { let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims); report_error("ValueError", "sp_linalg_hessenberg", file!(), line!(), column!(), &err_msg); } let dim1 = (*mat1).get_dims(); if dim1[0] != dim1[1] { let err_msg = format!("last 2 dimensions of the array must be square: {} != {}", dim1[0], dim1[1]); report_error("LinAlgError", "sp_linalg_hessenberg", file!(), line!(), column!(), &err_msg); } let out_h_dim = (*out_h).get_dims(); let out_q_dim = (*out_q).get_dims(); let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) }; let out_h_slice = unsafe { slice::from_raw_parts_mut(out_h.data, out_h_dim[0] * out_h_dim[1]) }; let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, out_q_dim[0] * out_q_dim[1]) }; let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1); let (q, h) = matrix.hessenberg().unpack(); out_h_slice.copy_from_slice(h.transpose().as_slice()); out_q_slice.copy_from_slice(q.transpose().as_slice()); }