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/******************************************************************************
* @file distance_functions.h
* @brief Public header file for CMSIS DSP Library
* @version V1.10.0
* @date 08 July 2021
* Target Processor: Cortex-M and Cortex-A cores
******************************************************************************/
/*
* Copyright (c) 2010-2020 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.
*/
#ifndef _DISTANCE_FUNCTIONS_H_
#define _DISTANCE_FUNCTIONS_H_
#include "arm_math_types.h"
#include "arm_math_memory.h"
#include "dsp/none.h"
#include "dsp/utils.h"
#include "dsp/statistics_functions.h"
#include "dsp/basic_math_functions.h"
#include "dsp/fast_math_functions.h"
#ifdef __cplusplus
extern "C"
{
#endif
/**
* @defgroup groupDistance Distance functions
*
* Distance functions for use with clustering algorithms.
* There are distance functions for float vectors and boolean vectors.
*
*/
/* 6.14 bug */
#if defined (__ARMCC_VERSION) && (__ARMCC_VERSION >= 6100100) && (__ARMCC_VERSION < 6150001)
__attribute__((weak)) float __powisf2(float a, int b);
#endif
/**
* @brief Euclidean distance between two vectors
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float32_t arm_euclidean_distance_f32(const float32_t *pA,const float32_t *pB, uint32_t blockSize);
/**
* @brief Euclidean distance between two vectors
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float64_t arm_euclidean_distance_f64(const float64_t *pA,const float64_t *pB, uint32_t blockSize);
/**
* @brief Bray-Curtis distance between two vectors
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float32_t arm_braycurtis_distance_f32(const float32_t *pA,const float32_t *pB, uint32_t blockSize);
/**
* @brief Canberra distance between two vectors
*
* This function may divide by zero when samples pA[i] and pB[i] are both zero.
* The result of the computation will be correct. So the division per zero may be
* ignored.
*
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float32_t arm_canberra_distance_f32(const float32_t *pA,const float32_t *pB, uint32_t blockSize);
/**
* @brief Chebyshev distance between two vectors
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float32_t arm_chebyshev_distance_f32(const float32_t *pA,const float32_t *pB, uint32_t blockSize);
/**
* @brief Chebyshev distance between two vectors
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float64_t arm_chebyshev_distance_f64(const float64_t *pA,const float64_t *pB, uint32_t blockSize);
/**
* @brief Cityblock (Manhattan) distance between two vectors
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float32_t arm_cityblock_distance_f32(const float32_t *pA,const float32_t *pB, uint32_t blockSize);
/**
* @brief Cityblock (Manhattan) distance between two vectors
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float64_t arm_cityblock_distance_f64(const float64_t *pA,const float64_t *pB, uint32_t blockSize);
/**
* @brief Correlation distance between two vectors
*
* The input vectors are modified in place !
*
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float32_t arm_correlation_distance_f32(float32_t *pA,float32_t *pB, uint32_t blockSize);
/**
* @brief Cosine distance between two vectors
*
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float32_t arm_cosine_distance_f32(const float32_t *pA,const float32_t *pB, uint32_t blockSize);
/**
* @brief Cosine distance between two vectors
*
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float64_t arm_cosine_distance_f64(const float64_t *pA,const float64_t *pB, uint32_t blockSize);
/**
* @brief Jensen-Shannon distance between two vectors
*
* This function is assuming that elements of second vector are > 0
* and 0 only when the corresponding element of first vector is 0.
* Otherwise the result of the computation does not make sense
* and for speed reasons, the cases returning NaN or Infinity are not
* managed.
*
* When the function is computing x log (x / y) with x 0 and y 0,
* it will compute the right value (0) but a division per zero will occur
* and shoudl be ignored in client code.
*
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float32_t arm_jensenshannon_distance_f32(const float32_t *pA,const float32_t *pB,uint32_t blockSize);
/**
* @brief Minkowski distance between two vectors
*
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] n Norm order (>= 2)
* @param[in] blockSize vector length
* @return distance
*
*/
float32_t arm_minkowski_distance_f32(const float32_t *pA,const float32_t *pB, int32_t order, uint32_t blockSize);
/**
* @brief Dice distance between two vectors
*
* @param[in] pA First vector of packed booleans
* @param[in] pB Second vector of packed booleans
* @param[in] order Distance order
* @param[in] blockSize Number of samples
* @return distance
*
*/
float32_t arm_dice_distance(const uint32_t *pA, const uint32_t *pB, uint32_t numberOfBools);
/**
* @brief Hamming distance between two vectors
*
* @param[in] pA First vector of packed booleans
* @param[in] pB Second vector of packed booleans
* @param[in] numberOfBools Number of booleans
* @return distance
*
*/
float32_t arm_hamming_distance(const uint32_t *pA, const uint32_t *pB, uint32_t numberOfBools);
/**
* @brief Jaccard distance between two vectors
*
* @param[in] pA First vector of packed booleans
* @param[in] pB Second vector of packed booleans
* @param[in] numberOfBools Number of booleans
* @return distance
*
*/
float32_t arm_jaccard_distance(const uint32_t *pA, const uint32_t *pB, uint32_t numberOfBools);
/**
* @brief Kulsinski distance between two vectors
*
* @param[in] pA First vector of packed booleans
* @param[in] pB Second vector of packed booleans
* @param[in] numberOfBools Number of booleans
* @return distance
*
*/
float32_t arm_kulsinski_distance(const uint32_t *pA, const uint32_t *pB, uint32_t numberOfBools);
/**
* @brief Roger Stanimoto distance between two vectors
*
* @param[in] pA First vector of packed booleans
* @param[in] pB Second vector of packed booleans
* @param[in] numberOfBools Number of booleans
* @return distance
*
*/
float32_t arm_rogerstanimoto_distance(const uint32_t *pA, const uint32_t *pB, uint32_t numberOfBools);
/**
* @brief Russell-Rao distance between two vectors
*
* @param[in] pA First vector of packed booleans
* @param[in] pB Second vector of packed booleans
* @param[in] numberOfBools Number of booleans
* @return distance
*
*/
float32_t arm_russellrao_distance(const uint32_t *pA, const uint32_t *pB, uint32_t numberOfBools);
/**
* @brief Sokal-Michener distance between two vectors
*
* @param[in] pA First vector of packed booleans
* @param[in] pB Second vector of packed booleans
* @param[in] numberOfBools Number of booleans
* @return distance
*
*/
float32_t arm_sokalmichener_distance(const uint32_t *pA, const uint32_t *pB, uint32_t numberOfBools);
/**
* @brief Sokal-Sneath distance between two vectors
*
* @param[in] pA First vector of packed booleans
* @param[in] pB Second vector of packed booleans
* @param[in] numberOfBools Number of booleans
* @return distance
*
*/
float32_t arm_sokalsneath_distance(const uint32_t *pA, const uint32_t *pB, uint32_t numberOfBools);
/**
* @brief Yule distance between two vectors
*
* @param[in] pA First vector of packed booleans
* @param[in] pB Second vector of packed booleans
* @param[in] numberOfBools Number of booleans
* @return distance
*
*/
float32_t arm_yule_distance(const uint32_t *pA, const uint32_t *pB, uint32_t numberOfBools);
#ifdef __cplusplus
}
#endif
#endif /* ifndef _DISTANCE_FUNCTIONS_H_ */
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