Official ARM version: v5.6.0
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rihab kouki
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2939 changed files with 339304 additions and 113320 deletions
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@ -3,13 +3,13 @@
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* Title: arm_var_f32.c
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* Description: Variance of the elements of a floating-point vector
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*
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* $Date: 27. January 2017
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* $Revision: V.1.5.1
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* $Date: 18. March 2019
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* $Revision: V1.6.0
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*
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* Target Processor: Cortex-M cores
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* -------------------------------------------------------------------- */
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/*
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* Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
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* Copyright (C) 2010-2019 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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@ -29,153 +29,206 @@
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#include "arm_math.h"
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/**
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* @ingroup groupStats
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@ingroup groupStats
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*/
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/**
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* @defgroup variance Variance
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*
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* Calculates the variance of the elements in the input vector.
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* The underlying algorithm used is the direct method sometimes referred to as the two-pass method:
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*
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* <pre>
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* Result = sum(element - meanOfElements)^2) / numElement - 1
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*
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* where, meanOfElements = ( pSrc[0] * pSrc[0] + pSrc[1] * pSrc[1] + ... + pSrc[blockSize-1] ) / blockSize
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*
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* </pre>
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*
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* There are separate functions for floating point, Q31, and Q15 data types.
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@defgroup variance Variance
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Calculates the variance of the elements in the input vector.
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The underlying algorithm used is the direct method sometimes referred to as the two-pass method:
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<pre>
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Result = sum(element - meanOfElements)^2) / numElement - 1
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meanOfElements = ( pSrc[0] * pSrc[0] + pSrc[1] * pSrc[1] + ... + pSrc[blockSize-1] ) / blockSize
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</pre>
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There are separate functions for floating point, Q31, and Q15 data types.
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*/
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/**
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* @addtogroup variance
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* @{
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@addtogroup variance
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@{
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*/
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/**
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* @brief Variance of the elements of a floating-point vector.
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* @param[in] *pSrc points to the input vector
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* @param[in] blockSize length of the input vector
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* @param[out] *pResult variance value returned here
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* @return none.
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@brief Variance of the elements of a floating-point vector.
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@param[in] pSrc points to the input vector
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@param[in] blockSize number of samples in input vector
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@param[out] pResult variance value returned here
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@return none
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*/
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#if defined(ARM_MATH_NEON_EXPERIMENTAL)
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void arm_var_f32(
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float32_t * pSrc,
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const float32_t * pSrc,
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uint32_t blockSize,
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float32_t * pResult)
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{
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float32_t fMean, fValue;
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uint32_t blkCnt; /* loop counter */
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float32_t * pInput = pSrc;
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float32_t sum = 0.0f;
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float32_t fSum = 0.0f;
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#if defined(ARM_MATH_DSP)
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float32_t in1, in2, in3, in4;
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#endif
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float32_t mean;
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if (blockSize <= 1U)
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{
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*pResult = 0;
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return;
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}
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float32_t sum = 0.0f; /* accumulator */
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float32_t in; /* Temporary variable to store input value */
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uint32_t blkCnt; /* loop counter */
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#if defined(ARM_MATH_DSP)
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/* Run the below code for Cortex-M4 and Cortex-M7 */
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float32x4_t sumV = vdupq_n_f32(0.0f); /* Temporary result storage */
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float32x2_t sumV2;
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float32x4_t inV;
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float32x4_t avg;
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/*loop Unrolling */
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blkCnt = blockSize >> 2U;
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arm_mean_f32(pSrc,blockSize,&mean);
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avg = vdupq_n_f32(mean);
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/* First part of the processing with loop unrolling. Compute 4 outputs at a time.
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** a second loop below computes the remaining 1 to 3 samples. */
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while (blkCnt > 0U)
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{
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/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
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in1 = *pInput++;
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in2 = *pInput++;
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in3 = *pInput++;
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in4 = *pInput++;
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blkCnt = blockSize >> 2U;
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sum += in1;
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sum += in2;
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sum += in3;
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sum += in4;
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/* Compute 4 outputs at a time.
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** a second loop below computes the remaining 1 to 3 samples. */
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while (blkCnt > 0U)
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{
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/* C = A[0] * A[0] + A[1] * A[1] + A[2] * A[2] + ... + A[blockSize-1] * A[blockSize-1] */
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/* Compute Power and then store the result in a temporary variable, sum. */
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inV = vld1q_f32(pSrc);
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inV = vsubq_f32(inV, avg);
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sumV = vmlaq_f32(sumV, inV, inV);
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pSrc += 4;
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/* Decrement the loop counter */
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blkCnt--;
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}
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/* Decrement the loop counter */
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blkCnt--;
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}
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/* If the blockSize is not a multiple of 4, compute any remaining output samples here.
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** No loop unrolling is used. */
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blkCnt = blockSize % 0x4U;
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sumV2 = vpadd_f32(vget_low_f32(sumV),vget_high_f32(sumV));
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sum = sumV2[0] + sumV2[1];
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#else
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/* Run the below code for Cortex-M0 or Cortex-M3 */
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/* If the blockSize is not a multiple of 4, compute any remaining output samples here.
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** No loop unrolling is used. */
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blkCnt = blockSize % 0x4U;
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/* Loop over blockSize number of values */
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blkCnt = blockSize;
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while (blkCnt > 0U)
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{
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/* C = A[0] * A[0] + A[1] * A[1] + A[2] * A[2] + ... + A[blockSize-1] * A[blockSize-1] */
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/* compute power and then store the result in a temporary variable, sum. */
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in = *pSrc++;
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in = in - mean;
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sum += in * in;
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#endif
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/* Decrement the loop counter */
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blkCnt--;
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}
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while (blkCnt > 0U)
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{
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/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
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sum += *pInput++;
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/* Variance */
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*pResult = sum / (float32_t)(blockSize - 1.0f);
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/* Decrement the loop counter */
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blkCnt--;
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}
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/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) / blockSize */
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fMean = sum / (float32_t) blockSize;
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pInput = pSrc;
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#if defined(ARM_MATH_DSP)
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/*loop Unrolling */
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blkCnt = blockSize >> 2U;
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/* First part of the processing with loop unrolling. Compute 4 outputs at a time.
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** a second loop below computes the remaining 1 to 3 samples. */
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while (blkCnt > 0U)
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{
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fValue = *pInput++ - fMean;
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fSum += fValue * fValue;
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fValue = *pInput++ - fMean;
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fSum += fValue * fValue;
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fValue = *pInput++ - fMean;
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fSum += fValue * fValue;
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fValue = *pInput++ - fMean;
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fSum += fValue * fValue;
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/* Decrement the loop counter */
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blkCnt--;
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}
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blkCnt = blockSize % 0x4U;
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#else
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/* Run the below code for Cortex-M0 or Cortex-M3 */
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/* Loop over blockSize number of values */
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blkCnt = blockSize;
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#endif
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while (blkCnt > 0U)
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{
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fValue = *pInput++ - fMean;
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fSum += fValue * fValue;
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/* Decrement the loop counter */
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blkCnt--;
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}
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/* Variance */
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*pResult = fSum / (float32_t)(blockSize - 1.0f);
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}
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#else
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void arm_var_f32(
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const float32_t * pSrc,
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uint32_t blockSize,
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float32_t * pResult)
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{
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uint32_t blkCnt; /* Loop counter */
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float32_t sum = 0.0f; /* Temporary result storage */
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float32_t fSum = 0.0f;
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float32_t fMean, fValue;
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const float32_t * pInput = pSrc;
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if (blockSize <= 1U)
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{
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*pResult = 0;
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return;
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}
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#if defined (ARM_MATH_LOOPUNROLL)
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/* Loop unrolling: Compute 4 outputs at a time */
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blkCnt = blockSize >> 2U;
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while (blkCnt > 0U)
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{
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/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
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sum += *pInput++;
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sum += *pInput++;
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sum += *pInput++;
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sum += *pInput++;
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/* Decrement loop counter */
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blkCnt--;
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}
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/* Loop unrolling: Compute remaining outputs */
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blkCnt = blockSize % 0x4U;
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#else
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/* Initialize blkCnt with number of samples */
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blkCnt = blockSize;
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#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
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while (blkCnt > 0U)
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{
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/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
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sum += *pInput++;
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/* Decrement loop counter */
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blkCnt--;
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}
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/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) / blockSize */
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fMean = sum / (float32_t) blockSize;
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pInput = pSrc;
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#if defined (ARM_MATH_LOOPUNROLL)
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/* Loop unrolling: Compute 4 outputs at a time */
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blkCnt = blockSize >> 2U;
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while (blkCnt > 0U)
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{
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fValue = *pInput++ - fMean;
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fSum += fValue * fValue;
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fValue = *pInput++ - fMean;
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fSum += fValue * fValue;
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fValue = *pInput++ - fMean;
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fSum += fValue * fValue;
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fValue = *pInput++ - fMean;
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fSum += fValue * fValue;
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/* Decrement loop counter */
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blkCnt--;
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}
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/* Loop unrolling: Compute remaining outputs */
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blkCnt = blockSize % 0x4U;
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#else
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/* Initialize blkCnt with number of samples */
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blkCnt = blockSize;
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#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
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while (blkCnt > 0U)
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{
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fValue = *pInput++ - fMean;
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fSum += fValue * fValue;
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/* Decrement loop counter */
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blkCnt--;
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}
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/* Variance */
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*pResult = fSum / (float32_t)(blockSize - 1.0f);
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}
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#endif /* #if defined(ARM_MATH_NEON) */
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/**
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* @} end of variance group
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@} end of variance group
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*/
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