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https://github.com/IcedRooibos/py32f0-template.git
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153 lines
3.8 KiB
C
153 lines
3.8 KiB
C
/* ----------------------------------------------------------------------
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* Project: CMSIS DSP Library
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* Title: arm_mean_f16.c
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* Description: Mean value of a floating-point vector
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*
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* $Date: 23 April 2021
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* $Revision: V1.9.0
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*
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* Target Processor: Cortex-M and Cortex-A cores
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* -------------------------------------------------------------------- */
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/*
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* Copyright (C) 2010-2021 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 "dsp/statistics_functions_f16.h"
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#if defined(ARM_FLOAT16_SUPPORTED)
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/**
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@ingroup groupStats
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*/
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/**
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@defgroup mean Mean
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Calculates the mean of the input vector. Mean is defined as the average of the elements in the vector.
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The underlying algorithm is used:
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<pre>
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Result = (pSrc[0] + pSrc[1] + pSrc[2] + ... + pSrc[blockSize-1]) / blockSize;
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</pre>
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There are separate functions for floating-point, Q31, Q15, and Q7 data types.
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*/
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/**
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@addtogroup mean
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@{
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*/
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/**
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@brief Mean value of a floating-point vector.
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@param[in] pSrc points to the input vector.
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@param[in] blockSize number of samples in input vector.
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@param[out] pResult mean value returned here.
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@return none
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*/
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#if defined(ARM_MATH_MVE_FLOAT16) && !defined(ARM_MATH_AUTOVECTORIZE)
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#include "arm_helium_utils.h"
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void arm_mean_f16(
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const float16_t * pSrc,
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uint32_t blockSize,
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float16_t * pResult)
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{
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int32_t blkCnt; /* loop counters */
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f16x8_t vecSrc;
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f16x8_t sumVec = vdupq_n_f16(0.0f16);
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blkCnt = blockSize;
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do {
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mve_pred16_t p = vctp16q(blkCnt);
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vecSrc = vldrhq_z_f16((float16_t const *) pSrc, p);
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sumVec = vaddq_m_f16(sumVec, sumVec, vecSrc, p);
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blkCnt -= 8;
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pSrc += 8;
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}
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while (blkCnt > 0);
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*pResult = (_Float16)vecAddAcrossF16Mve(sumVec) / (_Float16) blockSize;
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}
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#else
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void arm_mean_f16(
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const float16_t * pSrc,
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uint32_t blockSize,
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float16_t * pResult)
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{
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uint32_t blkCnt; /* Loop counter */
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float16_t sum = 0.0f; /* Temporary result storage */
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#if defined (ARM_MATH_LOOPUNROLL) && !defined(ARM_MATH_AUTOVECTORIZE)
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/* Loop unrolling: Compute 4 outputs at a time */
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blkCnt = blockSize >> 2U;
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while (blkCnt > 0U)
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{
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/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
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sum += (_Float16)*pSrc++;
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sum += (_Float16)*pSrc++;
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sum += (_Float16)*pSrc++;
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sum += (_Float16)*pSrc++;
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/* Decrement the loop counter */
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blkCnt--;
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}
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/* Loop unrolling: Compute remaining outputs */
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blkCnt = blockSize % 0x4U;
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#else
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/* Initialize blkCnt with number of samples */
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blkCnt = blockSize;
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#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
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while (blkCnt > 0U)
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{
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/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
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sum += (_Float16)*pSrc++;
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/* Decrement loop counter */
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blkCnt--;
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}
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/* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) / blockSize */
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/* Store result to destination */
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*pResult = ((_Float16)sum / (_Float16)blockSize);
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}
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#endif /* defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE) */
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/**
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@} end of mean group
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*/
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#endif /* #if defined(ARM_FLOAT16_SUPPORTED) */
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