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Drivers/CMSIS/DSP/Source/StatisticsFunctions/arm_var_f32.c Normal file
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/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_var_f32.c
* Description: Variance of the elements of a floating-point vector
*
* $Date: 18. March 2019
* $Revision: V1.6.0
*
* Target Processor: Cortex-M cores
* -------------------------------------------------------------------- */
/*
* Copyright (C) 2010-2019 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 variance Variance
Calculates the variance of the elements in the input vector.
The underlying algorithm used is the direct method sometimes referred to as the two-pass method:
<pre>
Result = sum(element - meanOfElements)^2) / numElement - 1
meanOfElements = ( pSrc[0] * pSrc[0] + pSrc[1] * pSrc[1] + ... + pSrc[blockSize-1] ) / blockSize
</pre>
There are separate functions for floating point, Q31, and Q15 data types.
*/
/**
@addtogroup variance
@{
*/
/**
@brief Variance of the elements of a floating-point vector.
@param[in] pSrc points to the input vector
@param[in] blockSize number of samples in input vector
@param[out] pResult variance value returned here
@return none
*/
#if defined(ARM_MATH_NEON_EXPERIMENTAL)
void arm_var_f32(
const float32_t * pSrc,
uint32_t blockSize,
float32_t * pResult)
{
float32_t mean;
float32_t sum = 0.0f; /* accumulator */
float32_t in; /* Temporary variable to store input value */
uint32_t blkCnt; /* loop counter */
float32x4_t sumV = vdupq_n_f32(0.0f); /* Temporary result storage */
float32x2_t sumV2;
float32x4_t inV;
float32x4_t avg;
arm_mean_f32(pSrc,blockSize,&mean);
avg = vdupq_n_f32(mean);
blkCnt = blockSize >> 2U;
/* 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[2] * A[2] + ... + A[blockSize-1] * A[blockSize-1] */
/* Compute Power and then store the result in a temporary variable, sum. */
inV = vld1q_f32(pSrc);
inV = vsubq_f32(inV, avg);
sumV = vmlaq_f32(sumV, inV, inV);
pSrc += 4;
/* Decrement the loop counter */
blkCnt--;
}
sumV2 = vpadd_f32(vget_low_f32(sumV),vget_high_f32(sumV));
sum = sumV2[0] + sumV2[1];
/* 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[2] * A[2] + ... + A[blockSize-1] * A[blockSize-1] */
/* compute power and then store the result in a temporary variable, sum. */
in = *pSrc++;
in = in - mean;
sum += in * in;
/* Decrement the loop counter */
blkCnt--;
}
/* Variance */
*pResult = sum / (float32_t)(blockSize - 1.0f);
}
#else
void arm_var_f32(
const float32_t * pSrc,
uint32_t blockSize,
float32_t * pResult)
{
uint32_t blkCnt; /* Loop counter */
float32_t sum = 0.0f; /* Temporary result storage */
float32_t fSum = 0.0f;
float32_t fMean, fValue;
const float32_t * pInput = pSrc;
if (blockSize <= 1U)
{
*pResult = 0;
return;
}
#if defined (ARM_MATH_LOOPUNROLL)
/* Loop unrolling: Compute 4 outputs at a time */
blkCnt = blockSize >> 2U;
while (blkCnt > 0U)
{
/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
sum += *pInput++;
sum += *pInput++;
sum += *pInput++;
sum += *pInput++;
/* Decrement loop counter */
blkCnt--;
}
/* Loop unrolling: Compute remaining outputs */
blkCnt = blockSize % 0x4U;
#else
/* Initialize blkCnt with number of samples */
blkCnt = blockSize;
#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
while (blkCnt > 0U)
{
/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
sum += *pInput++;
/* Decrement loop counter */
blkCnt--;
}
/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) / blockSize */
fMean = sum / (float32_t) blockSize;
pInput = pSrc;
#if defined (ARM_MATH_LOOPUNROLL)
/* Loop unrolling: Compute 4 outputs at a time */
blkCnt = blockSize >> 2U;
while (blkCnt > 0U)
{
fValue = *pInput++ - fMean;
fSum += fValue * fValue;
fValue = *pInput++ - fMean;
fSum += fValue * fValue;
fValue = *pInput++ - fMean;
fSum += fValue * fValue;
fValue = *pInput++ - fMean;
fSum += fValue * fValue;
/* Decrement loop counter */
blkCnt--;
}
/* Loop unrolling: Compute remaining outputs */
blkCnt = blockSize % 0x4U;
#else
/* Initialize blkCnt with number of samples */
blkCnt = blockSize;
#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
while (blkCnt > 0U)
{
fValue = *pInput++ - fMean;
fSum += fValue * fValue;
/* Decrement loop counter */
blkCnt--;
}
/* Variance */
*pResult = fSum / (float32_t)(blockSize - 1.0f);
}
#endif /* #if defined(ARM_MATH_NEON) */
/**
@} end of variance group
*/