hoverboard-firmware-hack-se.../Drivers/CMSIS/DSP_Lib/Source/StatisticsFunctions/arm_std_f32.c

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/* ----------------------------------------------------------------------
* Copyright (C) 2010-2014 ARM Limited. All rights reserved.
*
* $Date: 19. March 2015
* $Revision: V.1.4.5
*
* Project: CMSIS DSP Library
* Title: arm_std_f32.c
*
* Description: Standard deviation of the elements of a floating-point vector.
*
* Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* - Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* - Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in
* the documentation and/or other materials provided with the
* distribution.
* - Neither the name of ARM LIMITED nor the names of its contributors
* may be used to endorse or promote products derived from this
* software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
* ---------------------------------------------------------------------------- */
#include "arm_math.h"
/**
* @ingroup groupStats
*/
/**
* @defgroup STD Standard deviation
*
* Calculates the standard deviation of the elements in the input vector.
* The underlying algorithm is used:
*
* <pre>
* Result = sqrt((sumOfSquares - sum<sup>2</sup> / blockSize) / (blockSize - 1))
*
* where, sumOfSquares = pSrc[0] * pSrc[0] + pSrc[1] * pSrc[1] + ... + pSrc[blockSize-1] * pSrc[blockSize-1]
*
* sum = pSrc[0] + pSrc[1] + pSrc[2] + ... + pSrc[blockSize-1]
* </pre>
*
* There are separate functions for floating point, Q31, and Q15 data types.
*/
/**
* @addtogroup STD
* @{
*/
/**
* @brief Standard deviation of the elements of a floating-point vector.
* @param[in] *pSrc points to the input vector
* @param[in] blockSize length of the input vector
* @param[out] *pResult standard deviation value returned here
* @return none.
*
*/
void arm_std_f32(
float32_t * pSrc,
uint32_t blockSize,
float32_t * pResult)
{
float32_t sum = 0.0f; /* Temporary result storage */
float32_t sumOfSquares = 0.0f; /* Sum of squares */
float32_t in; /* input value */
uint32_t blkCnt; /* loop counter */
#ifndef ARM_MATH_CM0_FAMILY
/* Run the below code for Cortex-M4 and Cortex-M3 */
float32_t meanOfSquares, mean, squareOfMean;
if(blockSize == 1)
{
*pResult = 0;
return;
}
/*loop Unrolling */
blkCnt = blockSize >> 2u;
/* First part of the processing with loop unrolling. Compute 4 outputs at a time.
** a second loop below computes the remaining 1 to 3 samples. */
while(blkCnt > 0u)
{
/* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */
/* Compute Sum of squares of the input samples
* and then store the result in a temporary variable, sum. */
in = *pSrc++;
sum += in;
sumOfSquares += in * in;
in = *pSrc++;
sum += in;
sumOfSquares += in * in;
in = *pSrc++;
sum += in;
sumOfSquares += in * in;
in = *pSrc++;
sum += in;
sumOfSquares += in * in;
/* Decrement the loop counter */
blkCnt--;
}
/* If the blockSize is not a multiple of 4, compute any remaining output samples here.
** No loop unrolling is used. */
blkCnt = blockSize % 0x4u;
while(blkCnt > 0u)
{
/* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */
/* Compute Sum of squares of the input samples
* and then store the result in a temporary variable, sum. */
in = *pSrc++;
sum += in;
sumOfSquares += in * in;
/* Decrement the loop counter */
blkCnt--;
}
/* Compute Mean of squares of the input samples
* and then store the result in a temporary variable, meanOfSquares. */
meanOfSquares = sumOfSquares / ((float32_t) blockSize - 1.0f);
/* Compute mean of all input values */
mean = sum / (float32_t) blockSize;
/* Compute square of mean */
squareOfMean = (mean * mean) * (((float32_t) blockSize) /
((float32_t) blockSize - 1.0f));
/* Compute standard deviation and then store the result to the destination */
arm_sqrt_f32((meanOfSquares - squareOfMean), pResult);
#else
/* Run the below code for Cortex-M0 */
float32_t squareOfSum; /* Square of Sum */
float32_t var; /* Temporary varaince storage */
if(blockSize == 1)
{
*pResult = 0;
return;
}
/* Loop over blockSize number of values */
blkCnt = blockSize;
while(blkCnt > 0u)
{
/* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */
/* Compute Sum of squares of the input samples
* and then store the result in a temporary variable, sumOfSquares. */
in = *pSrc++;
sumOfSquares += in * in;
/* C = (A[0] + A[1] + ... + A[blockSize-1]) */
/* Compute Sum of the input samples
* and then store the result in a temporary variable, sum. */
sum += in;
/* Decrement the loop counter */
blkCnt--;
}
/* Compute the square of sum */
squareOfSum = ((sum * sum) / (float32_t) blockSize);
/* Compute the variance */
var = ((sumOfSquares - squareOfSum) / (float32_t) (blockSize - 1.0f));
/* Compute standard deviation and then store the result to the destination */
arm_sqrt_f32(var, pResult);
#endif /* #ifndef ARM_MATH_CM0_FAMILY */
}
/**
* @} end of STD group
*/