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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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