/* ---------------------------------------------------------------------- * Copyright (C) 2010-2014 ARM Limited. All rights reserved. * * $Date: 12. March 2014 * $Revision: V1.4.4 * * 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: * * 
    
 * 	Result = sqrt((sumOfSquares - sum2 / 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]   
 *
* * 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 */