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155 lines
4.1 KiB
C
155 lines
4.1 KiB
C
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/* ----------------------------------------------------------------------
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* Project: CMSIS DSP Library
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* Title: arm_braycurtis_distance_f32.c
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* Description: Bray-Curtis distance between two vectors
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*
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* $Date: 23 April 2021
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* $Revision: V1.9.0
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*
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* Target Processor: Cortex-M and Cortex-A cores
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* -------------------------------------------------------------------- */
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/*
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* Copyright (C) 2010-2021 ARM Limited or its affiliates. All rights reserved.
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*
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* SPDX-License-Identifier: Apache-2.0
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*
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* Licensed under the Apache License, Version 2.0 (the License); you may
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* not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an AS IS BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "dsp/distance_functions.h"
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#include "dsp/matrix_utils.h"
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#include <limits.h>
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#include <math.h>
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#define E(MAT,R,C) \
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(*((MAT)->pData + (MAT)->numCols*(R) + (C)))
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#define WIN(R,C) \
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((pWindow == NULL) ? 1 : \
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((*((pWindow)->pData + (pWindow)->numCols*(R) + (C)))==1))
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/**
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@ingroup FloatDist
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*/
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/**
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@defgroup DTW Dynamic Time Warping Distance
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Dynamic Time Warping Distance.
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This is not really a distance since triangular inequality is
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not respected.
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The step pattern used is symmetric2.
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Future versions of this function will provide more customization options.
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*/
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/**
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@addtogroup DTW
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@{
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*/
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/**
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* @brief Dynamic Time Warping distance
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* @param[in] pDistance Distance matrix (Query rows * Template columns)
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* @param[in] pWindow Windowing matrix (can be NULL if no windowing used)
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* @param[out] pDTW Temporary cost buffer (same size)
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* @param[out] distance Distance
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* @return ARM_MATH_ARGUMENT_ERROR in case no path can be found with window constraint
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*
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* @par Windowing matrix
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*
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* The windowing matrix is used to impose some
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* constraints on the search for a path.
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* The algorithm will run faster (smaller search
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* path) but may not be able to find a solution.
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*
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* The distance matrix must be initialized only
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* where the windowing matrix is containing 1.
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* Thus, use of a window also decreases the number
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* of distances which must be computed.
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*/
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arm_status arm_dtw_distance_f32(const arm_matrix_instance_f32 *pDistance,
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const arm_matrix_instance_q7 *pWindow,
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arm_matrix_instance_f32 *pDTW,
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float32_t *distance)
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{
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const uint32_t queryLength = pDistance -> numRows;
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const uint32_t templateLength = pDistance -> numCols;
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float32_t result;
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float32_t *temp = pDTW->pData;
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for(uint32_t q=0 ; q < queryLength; q++)
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{
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for(uint32_t t= 0; t < templateLength; t++)
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{
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*temp++ = F32_MAX;
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}
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}
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pDTW->pData[0] = E(pDistance,0,0);
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for(uint32_t q = 1; q < queryLength; q++)
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{
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if (!WIN(q,0))
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{
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continue;
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}
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E(pDTW,q,0) = E(pDTW,q-1,0) + E(pDistance,q,0);
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}
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for(uint32_t t = 1; t < templateLength; t++)
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{
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if (!WIN(0,t))
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{
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continue;
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}
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E(pDTW,0,t) = E(pDTW,0,t-1) + E(pDistance,0,t);
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}
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for(uint32_t q = 1; q < queryLength; q++)
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{
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for(uint32_t t = 1; t < templateLength; t++)
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{
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if (!WIN(q,t))
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{
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continue;
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}
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E(pDTW,q,t) =
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MIN(E(pDTW,q-1,t-1) + 2.0f * E(pDistance,q,t),
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MIN(E(pDTW,q,t-1) + E(pDistance,q,t),
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E(pDTW,q-1,t) + E(pDistance,q,t)));
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}
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}
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if (E(pDTW,queryLength-1,templateLength-1) == F32_MAX)
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{
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return(ARM_MATH_ARGUMENT_ERROR);
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}
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result = E(pDTW,queryLength-1,templateLength-1);
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result = result / (queryLength + templateLength);
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*distance = result;
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return(ARM_MATH_SUCCESS);
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}
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/**
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* @} end of DTW group
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*/
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