510 lines
12 KiB
C
510 lines
12 KiB
C
/* ----------------------------------------------------------------------
|
|
* Project: CMSIS DSP Library
|
|
* Title: arm_mat_ldl_f32.c
|
|
* Description: Floating-point LDL decomposition
|
|
*
|
|
* $Date: 23 April 2021
|
|
* $Revision: V1.9.0
|
|
*
|
|
* Target Processor: Cortex-M and Cortex-A cores
|
|
* -------------------------------------------------------------------- */
|
|
/*
|
|
* Copyright (C) 2010-2021 ARM Limited or its affiliates. All rights reserved.
|
|
*
|
|
* SPDX-License-Identifier: Apache-2.0
|
|
*
|
|
* Licensed under the Apache License, Version 2.0 (the License); you may
|
|
* not use this file except in compliance with the License.
|
|
* You may obtain a copy of the License at
|
|
*
|
|
* www.apache.org/licenses/LICENSE-2.0
|
|
*
|
|
* Unless required by applicable law or agreed to in writing, software
|
|
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
|
|
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
* See the License for the specific language governing permissions and
|
|
* limitations under the License.
|
|
*/
|
|
|
|
#include "dsp/matrix_functions.h"
|
|
|
|
|
|
|
|
|
|
|
|
#if defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE)
|
|
|
|
|
|
/// @private
|
|
#define SWAP_ROWS_F32(A,i,j) \
|
|
{ \
|
|
int cnt = n; \
|
|
\
|
|
for(int w=0;w < n; w+=4) \
|
|
{ \
|
|
f32x4_t tmpa,tmpb; \
|
|
mve_pred16_t p0 = vctp32q(cnt); \
|
|
\
|
|
tmpa=vldrwq_z_f32(&A[i*n + w],p0);\
|
|
tmpb=vldrwq_z_f32(&A[j*n + w],p0);\
|
|
\
|
|
vstrwq_p(&A[i*n + w], tmpb, p0); \
|
|
vstrwq_p(&A[j*n + w], tmpa, p0); \
|
|
\
|
|
cnt -= 4; \
|
|
} \
|
|
}
|
|
|
|
/// @private
|
|
#define SWAP_COLS_F32(A,i,j) \
|
|
for(int w=0;w < n; w++) \
|
|
{ \
|
|
float32_t tmp; \
|
|
tmp = A[w*n + i]; \
|
|
A[w*n + i] = A[w*n + j];\
|
|
A[w*n + j] = tmp; \
|
|
}
|
|
|
|
/**
|
|
@ingroup groupMatrix
|
|
*/
|
|
|
|
/**
|
|
@addtogroup MatrixChol
|
|
@{
|
|
*/
|
|
|
|
/**
|
|
* @brief Floating-point LDL^t decomposition of positive semi-definite matrix.
|
|
* @param[in] pSrc points to the instance of the input floating-point matrix structure.
|
|
* @param[out] pl points to the instance of the output floating-point triangular matrix structure.
|
|
* @param[out] pd points to the instance of the output floating-point diagonal matrix structure.
|
|
* @param[out] pp points to the instance of the output floating-point permutation vector.
|
|
* @return The function returns ARM_MATH_SIZE_MISMATCH, if the dimensions do not match.
|
|
* @return execution status
|
|
- \ref ARM_MATH_SUCCESS : Operation successful
|
|
- \ref ARM_MATH_SIZE_MISMATCH : Matrix size check failed
|
|
- \ref ARM_MATH_DECOMPOSITION_FAILURE : Input matrix cannot be decomposed
|
|
* @par
|
|
* Computes the LDL^t decomposition of a matrix A such that P A P^t = L D L^t.
|
|
*/
|
|
arm_status arm_mat_ldlt_f32(
|
|
const arm_matrix_instance_f32 * pSrc,
|
|
arm_matrix_instance_f32 * pl,
|
|
arm_matrix_instance_f32 * pd,
|
|
uint16_t * pp)
|
|
{
|
|
|
|
arm_status status; /* status of matrix inverse */
|
|
|
|
|
|
#ifdef ARM_MATH_MATRIX_CHECK
|
|
|
|
/* Check for matrix mismatch condition */
|
|
if ((pSrc->numRows != pSrc->numCols) ||
|
|
(pl->numRows != pl->numCols) ||
|
|
(pd->numRows != pd->numCols) ||
|
|
(pl->numRows != pd->numRows) )
|
|
{
|
|
/* Set status as ARM_MATH_SIZE_MISMATCH */
|
|
status = ARM_MATH_SIZE_MISMATCH;
|
|
}
|
|
else
|
|
|
|
#endif /* #ifdef ARM_MATH_MATRIX_CHECK */
|
|
|
|
{
|
|
|
|
const int n=pSrc->numRows;
|
|
int fullRank = 1, diag,k;
|
|
float32_t *pA;
|
|
|
|
memset(pd->pData,0,sizeof(float32_t)*n*n);
|
|
memcpy(pl->pData,pSrc->pData,n*n*sizeof(float32_t));
|
|
pA = pl->pData;
|
|
|
|
int cnt = n;
|
|
uint16x8_t vecP;
|
|
|
|
for(int k=0;k < n; k+=8)
|
|
{
|
|
mve_pred16_t p0;
|
|
p0 = vctp16q(cnt);
|
|
|
|
vecP = vidupq_u16((uint16_t)k, 1);
|
|
|
|
vstrhq_p(&pp[k], vecP, p0);
|
|
|
|
cnt -= 8;
|
|
}
|
|
|
|
|
|
for(k=0;k < n; k++)
|
|
{
|
|
/* Find pivot */
|
|
float32_t m=F32_MIN,a;
|
|
int j=k;
|
|
|
|
|
|
for(int r=k;r<n;r++)
|
|
{
|
|
if (pA[r*n+r] > m)
|
|
{
|
|
m = pA[r*n+r];
|
|
j = r;
|
|
}
|
|
}
|
|
|
|
if(j != k)
|
|
{
|
|
SWAP_ROWS_F32(pA,k,j);
|
|
SWAP_COLS_F32(pA,k,j);
|
|
}
|
|
|
|
|
|
pp[k] = j;
|
|
|
|
a = pA[k*n+k];
|
|
|
|
if (fabsf(a) < 1.0e-8f)
|
|
{
|
|
|
|
fullRank = 0;
|
|
break;
|
|
}
|
|
|
|
float32_t invA;
|
|
|
|
invA = 1.0f / a;
|
|
|
|
int32x4_t vecOffs;
|
|
int w;
|
|
vecOffs = vidupq_u32((uint32_t)0, 1);
|
|
vecOffs = vmulq_n_s32(vecOffs,n);
|
|
|
|
for(w=k+1; w<n; w+=4)
|
|
{
|
|
int cnt = n - k - 1;
|
|
|
|
f32x4_t vecX;
|
|
|
|
f32x4_t vecA;
|
|
f32x4_t vecW0,vecW1, vecW2, vecW3;
|
|
|
|
mve_pred16_t p0;
|
|
|
|
vecW0 = vdupq_n_f32(pA[(w + 0)*n+k]);
|
|
vecW1 = vdupq_n_f32(pA[(w + 1)*n+k]);
|
|
vecW2 = vdupq_n_f32(pA[(w + 2)*n+k]);
|
|
vecW3 = vdupq_n_f32(pA[(w + 3)*n+k]);
|
|
|
|
for(int x=k+1;x<n;x += 4)
|
|
{
|
|
p0 = vctp32q(cnt);
|
|
|
|
//pA[w*n+x] = pA[w*n+x] - pA[w*n+k] * (pA[x*n+k] * invA);
|
|
|
|
|
|
vecX = vldrwq_gather_shifted_offset_z_f32(&pA[x*n+k], (uint32x4_t)vecOffs, p0);
|
|
vecX = vmulq_m_n_f32(vuninitializedq_f32(),vecX,invA,p0);
|
|
|
|
|
|
vecA = vldrwq_z_f32(&pA[(w + 0)*n+x],p0);
|
|
vecA = vfmsq_m(vecA, vecW0, vecX, p0);
|
|
vstrwq_p(&pA[(w + 0)*n+x], vecA, p0);
|
|
|
|
vecA = vldrwq_z_f32(&pA[(w + 1)*n+x],p0);
|
|
vecA = vfmsq_m(vecA, vecW1, vecX, p0);
|
|
vstrwq_p(&pA[(w + 1)*n+x], vecA, p0);
|
|
|
|
vecA = vldrwq_z_f32(&pA[(w + 2)*n+x],p0);
|
|
vecA = vfmsq_m(vecA, vecW2, vecX, p0);
|
|
vstrwq_p(&pA[(w + 2)*n+x], vecA, p0);
|
|
|
|
vecA = vldrwq_z_f32(&pA[(w + 3)*n+x],p0);
|
|
vecA = vfmsq_m(vecA, vecW3, vecX, p0);
|
|
vstrwq_p(&pA[(w + 3)*n+x], vecA, p0);
|
|
|
|
cnt -= 4;
|
|
}
|
|
}
|
|
|
|
for(; w<n; w++)
|
|
{
|
|
int cnt = n - k - 1;
|
|
|
|
f32x4_t vecA,vecX,vecW;
|
|
|
|
|
|
mve_pred16_t p0;
|
|
|
|
vecW = vdupq_n_f32(pA[w*n+k]);
|
|
|
|
for(int x=k+1;x<n;x += 4)
|
|
{
|
|
p0 = vctp32q(cnt);
|
|
|
|
//pA[w*n+x] = pA[w*n+x] - pA[w*n+k] * (pA[x*n+k] * invA);
|
|
|
|
vecA = vldrwq_z_f32(&pA[w*n+x],p0);
|
|
|
|
vecX = vldrwq_gather_shifted_offset_z_f32(&pA[x*n+k], (uint32x4_t)vecOffs, p0);
|
|
vecX = vmulq_m_n_f32(vuninitializedq_f32(),vecX,invA,p0);
|
|
|
|
vecA = vfmsq_m(vecA, vecW, vecX, p0);
|
|
|
|
vstrwq_p(&pA[w*n+x], vecA, p0);
|
|
|
|
cnt -= 4;
|
|
}
|
|
}
|
|
|
|
for(int w=k+1;w<n;w++)
|
|
{
|
|
pA[w*n+k] = pA[w*n+k] * invA;
|
|
}
|
|
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
diag=k;
|
|
if (!fullRank)
|
|
{
|
|
diag--;
|
|
for(int row=0; row < n;row++)
|
|
{
|
|
mve_pred16_t p0;
|
|
int cnt= n-k;
|
|
f32x4_t zero=vdupq_n_f32(0.0f);
|
|
|
|
for(int col=k; col < n;col += 4)
|
|
{
|
|
p0 = vctp32q(cnt);
|
|
|
|
vstrwq_p(&pl->pData[row*n+col], zero, p0);
|
|
|
|
cnt -= 4;
|
|
}
|
|
}
|
|
}
|
|
|
|
for(int row=0; row < n;row++)
|
|
{
|
|
mve_pred16_t p0;
|
|
int cnt= n-row-1;
|
|
f32x4_t zero=vdupq_n_f32(0.0f);
|
|
|
|
for(int col=row+1; col < n;col+=4)
|
|
{
|
|
p0 = vctp32q(cnt);
|
|
|
|
vstrwq_p(&pl->pData[row*n+col], zero, p0);
|
|
|
|
cnt -= 4;
|
|
}
|
|
}
|
|
|
|
for(int d=0; d < diag;d++)
|
|
{
|
|
pd->pData[d*n+d] = pl->pData[d*n+d];
|
|
pl->pData[d*n+d] = 1.0;
|
|
}
|
|
|
|
status = ARM_MATH_SUCCESS;
|
|
|
|
}
|
|
|
|
|
|
/* Return to application */
|
|
return (status);
|
|
}
|
|
#else
|
|
|
|
/// @private
|
|
#define SWAP_ROWS_F32(A,i,j) \
|
|
for(w=0;w < n; w++) \
|
|
{ \
|
|
float32_t tmp; \
|
|
tmp = A[i*n + w]; \
|
|
A[i*n + w] = A[j*n + w];\
|
|
A[j*n + w] = tmp; \
|
|
}
|
|
|
|
/// @private
|
|
#define SWAP_COLS_F32(A,i,j) \
|
|
for(w=0;w < n; w++) \
|
|
{ \
|
|
float32_t tmp; \
|
|
tmp = A[w*n + i]; \
|
|
A[w*n + i] = A[w*n + j];\
|
|
A[w*n + j] = tmp; \
|
|
}
|
|
|
|
/**
|
|
@ingroup groupMatrix
|
|
*/
|
|
|
|
/**
|
|
@addtogroup MatrixChol
|
|
@{
|
|
*/
|
|
|
|
/**
|
|
* @brief Floating-point LDL^t decomposition of positive semi-definite matrix.
|
|
* @param[in] pSrc points to the instance of the input floating-point matrix structure.
|
|
* @param[out] pl points to the instance of the output floating-point triangular matrix structure.
|
|
* @param[out] pd points to the instance of the output floating-point diagonal matrix structure.
|
|
* @param[out] pp points to the instance of the output floating-point permutation vector.
|
|
* @return The function returns ARM_MATH_SIZE_MISMATCH, if the dimensions do not match.
|
|
* @return execution status
|
|
- \ref ARM_MATH_SUCCESS : Operation successful
|
|
- \ref ARM_MATH_SIZE_MISMATCH : Matrix size check failed
|
|
- \ref ARM_MATH_DECOMPOSITION_FAILURE : Input matrix cannot be decomposed
|
|
* @par
|
|
* Computes the LDL^t decomposition of a matrix A such that P A P^t = L D L^t.
|
|
*/
|
|
arm_status arm_mat_ldlt_f32(
|
|
const arm_matrix_instance_f32 * pSrc,
|
|
arm_matrix_instance_f32 * pl,
|
|
arm_matrix_instance_f32 * pd,
|
|
uint16_t * pp)
|
|
{
|
|
|
|
arm_status status; /* status of matrix inverse */
|
|
|
|
|
|
#ifdef ARM_MATH_MATRIX_CHECK
|
|
|
|
/* Check for matrix mismatch condition */
|
|
if ((pSrc->numRows != pSrc->numCols) ||
|
|
(pl->numRows != pl->numCols) ||
|
|
(pd->numRows != pd->numCols) ||
|
|
(pl->numRows != pd->numRows) )
|
|
{
|
|
/* Set status as ARM_MATH_SIZE_MISMATCH */
|
|
status = ARM_MATH_SIZE_MISMATCH;
|
|
}
|
|
else
|
|
|
|
#endif /* #ifdef ARM_MATH_MATRIX_CHECK */
|
|
|
|
{
|
|
|
|
const int n=pSrc->numRows;
|
|
int fullRank = 1, diag,k;
|
|
float32_t *pA;
|
|
int row,d;
|
|
|
|
memset(pd->pData,0,sizeof(float32_t)*n*n);
|
|
memcpy(pl->pData,pSrc->pData,n*n*sizeof(float32_t));
|
|
pA = pl->pData;
|
|
|
|
for(k=0;k < n; k++)
|
|
{
|
|
pp[k] = k;
|
|
}
|
|
|
|
|
|
for(k=0;k < n; k++)
|
|
{
|
|
/* Find pivot */
|
|
float32_t m=F32_MIN,a;
|
|
int j=k;
|
|
|
|
|
|
int r;
|
|
int w;
|
|
|
|
for(r=k;r<n;r++)
|
|
{
|
|
if (pA[r*n+r] > m)
|
|
{
|
|
m = pA[r*n+r];
|
|
j = r;
|
|
}
|
|
}
|
|
|
|
if(j != k)
|
|
{
|
|
SWAP_ROWS_F32(pA,k,j);
|
|
SWAP_COLS_F32(pA,k,j);
|
|
}
|
|
|
|
|
|
pp[k] = j;
|
|
|
|
a = pA[k*n+k];
|
|
|
|
if (fabsf(a) < 1.0e-8f)
|
|
{
|
|
|
|
fullRank = 0;
|
|
break;
|
|
}
|
|
|
|
for(w=k+1;w<n;w++)
|
|
{
|
|
int x;
|
|
for(x=k+1;x<n;x++)
|
|
{
|
|
pA[w*n+x] = pA[w*n+x] - pA[w*n+k] * pA[x*n+k] / a;
|
|
}
|
|
}
|
|
|
|
for(w=k+1;w<n;w++)
|
|
{
|
|
pA[w*n+k] = pA[w*n+k] / a;
|
|
}
|
|
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
diag=k;
|
|
if (!fullRank)
|
|
{
|
|
diag--;
|
|
for(row=0; row < n;row++)
|
|
{
|
|
int col;
|
|
for(col=k; col < n;col++)
|
|
{
|
|
pl->pData[row*n+col]=0.0;
|
|
}
|
|
}
|
|
}
|
|
|
|
for(row=0; row < n;row++)
|
|
{
|
|
int col;
|
|
for(col=row+1; col < n;col++)
|
|
{
|
|
pl->pData[row*n+col] = 0.0;
|
|
}
|
|
}
|
|
|
|
for(d=0; d < diag;d++)
|
|
{
|
|
pd->pData[d*n+d] = pl->pData[d*n+d];
|
|
pl->pData[d*n+d] = 1.0;
|
|
}
|
|
|
|
status = ARM_MATH_SUCCESS;
|
|
|
|
}
|
|
|
|
|
|
/* Return to application */
|
|
return (status);
|
|
}
|
|
#endif /* defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE) */
|
|
|
|
/**
|
|
@} end of MatrixChol group
|
|
*/
|