STM32-Custom-Bootloader-and.../App1/Drivers/CMSIS/DSP/Source/StatisticsFunctions/arm_std_f32.c
2023-04-22 10:18:26 +02:00

187 lines
5.4 KiB
C

/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_std_f32.c
* Description: Standard deviation of the elements of a floating-point vector
*
* $Date: 27. January 2017
* $Revision: V.1.5.1
*
* Target Processor: Cortex-M cores
* -------------------------------------------------------------------- */
/*
* Copyright (C) 2010-2017 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.
*/
#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 */
#if defined (ARM_MATH_DSP)
float32_t meanOfSquares, mean, squareOfMean; /* Temporary variables */
#else
float32_t squareOfSum; /* Square of Sum */
float32_t var; /* Temporary varaince storage */
#endif
if (blockSize == 1U)
{
*pResult = 0;
return;
}
#if defined (ARM_MATH_DSP)
/* Run the below code for Cortex-M4 and Cortex-M3 */
/*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 */
/* 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 /* #if defined (ARM_MATH_DSP) */
}
/**
* @} end of STD group
*/