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Drivers/CMSIS/DSP/Source/ComplexMathFunctions/arm_cmplx_mag_f16.c Normal file
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/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_cmplx_mag_f16.c
* Description: Floating-point complex magnitude
*
* $Date: 23 April 2021
* $Revision: V1.9.0
*
* Target Processor: Cortex-M and Cortex-A cores
* -------------------------------------------------------------------- */
/*
* Copyright (C) 2010-2021 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 "dsp/complex_math_functions_f16.h"
#if defined(ARM_FLOAT16_SUPPORTED)
/**
@ingroup groupCmplxMath
*/
/**
@defgroup cmplx_mag Complex Magnitude
Computes the magnitude of the elements of a complex data vector.
The <code>pSrc</code> points to the source data and
<code>pDst</code> points to the where the result should be written.
<code>numSamples</code> specifies the number of complex samples
in the input array and the data is stored in an interleaved fashion
(real, imag, real, imag, ...).
The input array has a total of <code>2*numSamples</code> values;
the output array has a total of <code>numSamples</code> values.
The underlying algorithm is used:
<pre>
for (n = 0; n < numSamples; n++) {
pDst[n] = sqrt(pSrc[(2*n)+0]^2 + pSrc[(2*n)+1]^2);
}
</pre>
There are separate functions for floating-point, Q15, and Q31 data types.
*/
/**
@addtogroup cmplx_mag
@{
*/
/**
@brief Floating-point complex magnitude.
@param[in] pSrc points to input vector
@param[out] pDst points to output vector
@param[in] numSamples number of samples in each vector
@return none
*/
#if defined(ARM_MATH_MVE_FLOAT16) && !defined(ARM_MATH_AUTOVECTORIZE)
#include "arm_helium_utils.h"
void arm_cmplx_mag_f16(
const float16_t * pSrc,
float16_t * pDst,
uint32_t numSamples)
{
int32_t blockSize = numSamples; /* loop counters */
uint32_t blkCnt; /* loop counters */
f16x8x2_t vecSrc;
f16x8_t sum;
/* Compute 4 complex samples at a time */
blkCnt = blockSize >> 3;
while (blkCnt > 0U)
{
q15x8_t newtonStartVec;
f16x8_t sumHalf, invSqrt;
vecSrc = vld2q(pSrc);
pSrc += 16;
sum = vmulq(vecSrc.val[0], vecSrc.val[0]);
sum = vfmaq(sum, vecSrc.val[1], vecSrc.val[1]);
/*
* inlined Fast SQRT using inverse SQRT newton-raphson method
*/
/* compute initial value */
newtonStartVec = vdupq_n_s16(INVSQRT_MAGIC_F16) - vshrq((q15x8_t) sum, 1);
sumHalf = sum * 0.5f;
/*
* compute 3 x iterations
*
* The more iterations, the more accuracy.
* If you need to trade a bit of accuracy for more performance,
* you can comment out the 3rd use of the macro.
*/
INVSQRT_NEWTON_MVE_F16(invSqrt, sumHalf, (f16x8_t) newtonStartVec);
INVSQRT_NEWTON_MVE_F16(invSqrt, sumHalf, invSqrt);
INVSQRT_NEWTON_MVE_F16(invSqrt, sumHalf, invSqrt);
/*
* set negative values to 0
*/
invSqrt = vdupq_m(invSqrt, (float16_t)0.0f, vcmpltq(invSqrt, (float16_t)0.0f));
/*
* sqrt(x) = x * invSqrt(x)
*/
sum = vmulq(sum, invSqrt);
vstrhq_f16(pDst, sum);
pDst += 8;
/*
* Decrement the blockSize loop counter
*/
blkCnt--;
}
/*
* tail
*/
blkCnt = blockSize & 7;
if (blkCnt > 0U)
{
mve_pred16_t p0 = vctp16q(blkCnt);
q15x8_t newtonStartVec;
f16x8_t sumHalf, invSqrt;
vecSrc = vld2q((float16_t const *)pSrc);
sum = vmulq(vecSrc.val[0], vecSrc.val[0]);
sum = vfmaq(sum, vecSrc.val[1], vecSrc.val[1]);
/*
* inlined Fast SQRT using inverse SQRT newton-raphson method
*/
/* compute initial value */
newtonStartVec = vdupq_n_s16(INVSQRT_MAGIC_F16) - vshrq((q15x8_t) sum, 1);
sumHalf = vmulq(sum, (float16_t)0.5);
/*
* compute 2 x iterations
*/
INVSQRT_NEWTON_MVE_F16(invSqrt, sumHalf, (f16x8_t) newtonStartVec);
INVSQRT_NEWTON_MVE_F16(invSqrt, sumHalf, invSqrt);
/*
* set negative values to 0
*/
invSqrt = vdupq_m(invSqrt, (float16_t)0.0, vcmpltq(invSqrt, (float16_t)0.0));
/*
* sqrt(x) = x * invSqrt(x)
*/
sum = vmulq(sum, invSqrt);
vstrhq_p_f16(pDst, sum, p0);
}
}
#else
void arm_cmplx_mag_f16(
const float16_t * pSrc,
float16_t * pDst,
uint32_t numSamples)
{
uint32_t blkCnt; /* loop counter */
_Float16 real, imag; /* Temporary variables to hold input values */
#if defined (ARM_MATH_LOOPUNROLL) && !defined(ARM_MATH_AUTOVECTORIZE)
/* Loop unrolling: Compute 4 outputs at a time */
blkCnt = numSamples >> 2U;
while (blkCnt > 0U)
{
/* C[0] = sqrt(A[0] * A[0] + A[1] * A[1]) */
real = *pSrc++;
imag = *pSrc++;
/* store result in destination buffer. */
arm_sqrt_f16((real * real) + (imag * imag), pDst++);
real = *pSrc++;
imag = *pSrc++;
arm_sqrt_f16((real * real) + (imag * imag), pDst++);
real = *pSrc++;
imag = *pSrc++;
arm_sqrt_f16((real * real) + (imag * imag), pDst++);
real = *pSrc++;
imag = *pSrc++;
arm_sqrt_f16((real * real) + (imag * imag), pDst++);
/* Decrement loop counter */
blkCnt--;
}
/* Loop unrolling: Compute remaining outputs */
blkCnt = numSamples % 0x4U;
#else
/* Initialize blkCnt with number of samples */
blkCnt = numSamples;
#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
while (blkCnt > 0U)
{
/* C[0] = sqrt(A[0] * A[0] + A[1] * A[1]) */
real = *pSrc++;
imag = *pSrc++;
/* store result in destination buffer. */
arm_sqrt_f16((real * real) + (imag * imag), pDst++);
/* Decrement loop counter */
blkCnt--;
}
}
#endif /* defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE) */
/**
@} end of cmplx_mag group
*/
#endif /* #if defined(ARM_FLOAT16_SUPPORTED) */