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/* ----------------------------------------------------------------------
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 * Project:      CMSIS DSP Library
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 * Title:        arm_std_f32.c
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 * Description:  Standard deviation 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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 *
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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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 *
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 * SPDX-License-Identifier: Apache-2.0
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 *
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 * Licensed under the Apache License, Version 2.0 (the License); you may
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 * not use this file except in compliance with the License.
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 * You may obtain a copy of the License at
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 *
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 * www.apache.org/licenses/LICENSE-2.0
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 *
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 * Unless required by applicable law or agreed to in writing, software
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 * distributed under the License is distributed on an AS IS BASIS, WITHOUT
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 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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 * See the License for the specific language governing permissions and
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 * limitations under the License.
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 */
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#include "arm_math.h"
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/**
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 * @ingroup groupStats
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 */
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/**
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 * @defgroup STD Standard deviation
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 *
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 * Calculates the standard deviation of the elements in the input vector.
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 * The underlying algorithm is used:
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 *
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 * <pre>
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 *   Result = sqrt((sumOfSquares - sum<sup>2</sup> / blockSize) / (blockSize - 1))
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 *
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 *     where, sumOfSquares = pSrc[0] * pSrc[0] + pSrc[1] * pSrc[1] + ... + pSrc[blockSize-1] * pSrc[blockSize-1]
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 *
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 *                     sum = pSrc[0] + pSrc[1] + pSrc[2] + ... + pSrc[blockSize-1]
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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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 */
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/**
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 * @addtogroup STD
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 * @{
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 */
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/**
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 * @brief Standard deviation 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 standard deviation value returned here
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 * @return none.
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 */
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void arm_std_f32(
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  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 sum = 0.0f;                          /* Temporary result storage */
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  float32_t sumOfSquares = 0.0f;                 /* Sum of squares */
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  float32_t in;                                  /* input value */
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  uint32_t blkCnt;                               /* loop counter */
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#if defined (ARM_MATH_DSP)
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  float32_t meanOfSquares, mean, squareOfMean;   /* Temporary variables */
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#else
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  float32_t squareOfSum;                         /* Square of Sum */
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  float32_t var;                                 /* Temporary varaince storage */
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#endif
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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_DSP)
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  /* Run the below code for Cortex-M4 and Cortex-M3 */
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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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    /* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1])  */
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    /* Compute Sum of squares of the input samples
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     * and then store the result in a temporary variable, sum. */
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    in = *pSrc++;
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    sum += in;
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    sumOfSquares += in * in;
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    in = *pSrc++;
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    sum += in;
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    sumOfSquares += in * in;
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    in = *pSrc++;
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    sum += in;
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    sumOfSquares += in * in;
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    in = *pSrc++;
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    sum += in;
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    sumOfSquares += in * in;
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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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  while (blkCnt > 0U)
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  {
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    /* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */
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    /* Compute Sum of squares of the input samples
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     * and then store the result in a temporary variable, sum. */
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    in = *pSrc++;
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    sum += in;
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    sumOfSquares += in * in;
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    /* Decrement the loop counter */
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    blkCnt--;
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  }
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  /* Compute Mean of squares of the input samples
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   * and then store the result in a temporary variable, meanOfSquares. */
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  meanOfSquares = sumOfSquares / ((float32_t) blockSize - 1.0f);
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  /* Compute mean of all input values */
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  mean = sum / (float32_t) blockSize;
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  /* Compute square of mean */
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  squareOfMean = (mean * mean) * (((float32_t) blockSize) /
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                                  ((float32_t) blockSize - 1.0f));
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  /* Compute standard deviation and then store the result to the destination */
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  arm_sqrt_f32((meanOfSquares - squareOfMean), pResult);
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#else
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  /* Run the below code for Cortex-M0 */
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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[blockSize-1] * A[blockSize-1]) */
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    /* Compute Sum of squares of the input samples
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     * and then store the result in a temporary variable, sumOfSquares. */
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    in = *pSrc++;
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    sumOfSquares += in * in;
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    /* C = (A[0] + A[1] + ... + A[blockSize-1]) */
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    /* Compute Sum of the input samples
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     * and then store the result in a temporary variable, sum. */
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    sum += in;
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    /* Decrement the loop counter */
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    blkCnt--;
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  }
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  /* Compute the square of sum */
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  squareOfSum = ((sum * sum) / (float32_t) blockSize);
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  /* Compute the variance */
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  var = ((sumOfSquares - squareOfSum) / (float32_t) (blockSize - 1.0f));
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  /* Compute standard deviation and then store the result to the destination */
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  arm_sqrt_f32(var, pResult);
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#endif /* #if defined (ARM_MATH_DSP) */
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}
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/**
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 * @} end of STD group
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 */