CMSIS-DSP: Added scalar float64 entropy and kullback leibler
ClaudioMartino
6 years ago
committed by
Christophe Favergeon
parent
3446683ed3
commit
fb1f6b04a7
@ -0,0 +1,71 @@
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/* ----------------------------------------------------------------------
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* Project: CMSIS DSP Library
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* Title: arm_logsumexp_f64.c
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* Description: LogSumExp
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*
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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) 2010-2020 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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#include <limits.h>
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#include <math.h>
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/**
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* @addtogroup groupStats
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* @{
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*/
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/**
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* @brief Entropy
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*
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* @param[in] pSrcA Array of input values.
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* @param[in] blockSize Number of samples in the input array.
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* @return Entropy -Sum(p ln p)
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*
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*/
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float64_t arm_entropy_f64(const float64_t * pSrcA, uint32_t blockSize)
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{
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const float64_t *pIn;
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uint32_t blkCnt;
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float64_t accum, p;
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pIn = pSrcA;
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blkCnt = blockSize;
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accum = 0.0f;
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while(blkCnt > 0)
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{
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p = *pIn++;
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accum += p * log(p);
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blkCnt--;
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}
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return(-accum);
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}
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/**
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* @} end of groupStats group
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*/
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@ -0,0 +1,73 @@
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/* ----------------------------------------------------------------------
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* Project: CMSIS DSP Library
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* Title: arm_logsumexp_f64.c
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* Description: LogSumExp
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*
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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) 2010-2020 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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#include <limits.h>
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#include <math.h>
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/**
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* @addtogroup groupStats
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* @{
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*/
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/**
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* @brief Kullback-Leibler
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*
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* @param[in] *pSrcA points to an array of input values for probaility distribution A.
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* @param[in] *pSrcB points to an array of input values for probaility distribution B.
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* @param[in] blockSize number of samples in the input array.
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* @return Kullback-Leibler divergence D(A || B)
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*
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*/
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float64_t arm_kullback_leibler_f64(const float64_t * pSrcA, const float64_t * pSrcB, uint32_t blockSize)
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{
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const float64_t *pInA, *pInB;
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uint32_t blkCnt;
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float64_t accum, pA,pB;
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pInA = pSrcA;
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pInB = pSrcB;
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blkCnt = blockSize;
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accum = 0.0f;
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while(blkCnt > 0)
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{
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pA = *pInA++;
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pB = *pInB++;
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accum += pA * log(pB / pA);
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blkCnt--;
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}
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return(-accum);
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}
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/**
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* @} end of groupStats group
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*/
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@ -0,0 +1,32 @@
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#include "Test.h"
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#include "Pattern.h"
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class StatsTestsF64:public Client::Suite
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{
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public:
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StatsTestsF64(Testing::testID_t id);
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virtual void setUp(Testing::testID_t,std::vector<Testing::param_t>& paramsArgs,Client::PatternMgr *mgr);
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virtual void tearDown(Testing::testID_t,Client::PatternMgr *mgr);
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private:
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#include "StatsTestsF64_decl.h"
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Client::Pattern<float64_t> inputA;
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Client::Pattern<float64_t> inputB;
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Client::Pattern<int16_t> dims;
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Client::LocalPattern<float64_t> output;
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Client::LocalPattern<int16_t> index;
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Client::LocalPattern<float64_t> tmp;
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// Reference patterns are not loaded when we are in dump mode
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Client::RefPattern<float64_t> ref;
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Client::Pattern<int16_t> maxIndexes;
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Client::Pattern<int16_t> minIndexes;
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int nbPatterns;
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int vecDim;
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int refOffset;
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};
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@ -0,0 +1,24 @@
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H
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11
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// 10
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0x000A
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// 3
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0x0003
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// 8
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0x0008
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// 9
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0x0009
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// 12
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0x000C
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// 3
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0x0003
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// 8
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0x0008
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// 9
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0x0009
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// 12
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0x000C
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// 3
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0x0003
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// 8
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0x0008
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@ -0,0 +1,24 @@
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H
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11
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// 10
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0x000A
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// 3
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0x0003
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// 8
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0x0008
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// 9
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0x0009
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// 12
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0x000C
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// 3
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0x0003
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// 8
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0x0008
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// 9
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0x0009
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// 12
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0x000C
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// 3
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0x0003
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// 8
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0x0008
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@ -0,0 +1,152 @@
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D
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75
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// 0.505280
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0x3fe02b417ebce314
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// 0.454144
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0x3fdd10b048f98340
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// 0.040576
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0x3fa4c665cc65b4da
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// 0.228813
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0x3fcd49bc24996ead
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// 0.111427
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0x3fbc8677ddbcf163
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// 0.184665
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0x3fc7a31bcac2bf14
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// 0.102689
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0x3fba49d5259ee3fc
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// 0.061293
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0x3faf61d601affcb1
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// 0.149838
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0x3fc32de527c03dd6
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// 0.068132
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0x3fb1711893b7b7bb
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// 0.093143
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0x3fb7d83539db9d64
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// 0.183439
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0x3fc77af068192567
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// 0.135121
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0x3fc14ba61cff9e4a
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// 0.254422
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0x3fd04874bc8b246c
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// 0.083904
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0x3fb57ab816eaf2d4
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// 0.019128
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0x3f93965f819fb27d
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// 0.133743
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0x3fc11e7adb462d9e
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// 0.031570
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0x3fa029f293959c58
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// 0.155015
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0x3fc3d78a1d28ff68
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// 0.003657
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0x3f6df59a34bbe7fc
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// 0.098729
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0x3fb94647dfe164c2
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// 0.188947
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0x3fc82f6c20029e4c
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// 0.047608
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0x3fa8600f36933cc7
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// 0.141847
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0x3fc22808a330e919
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// 0.120154
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0x3fbec26dff4e4a07
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// 0.090980
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0x3fb74a7dd8ae1dc6
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// 0.160669
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0x3fc490cda4dc1fba
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// 0.044310
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0x3fa6afdd8f890bed
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// 0.014223
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0x3f8d212b593bb5d5
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// 0.017826
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0x3f9240db8931faf8
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// 0.046638
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0x3fa7e0dfc0893a18
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// 0.028069
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0x3f9cbe139cf0b961
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// 0.034885
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0x3fa1dc81ecf1e55c
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// 0.555134
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0x3fe1c3a8c3665c97
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// 0.409980
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0x3fda3d1e3b950a27
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// 0.147303
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0x3fc2dad28b75bdbb
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// 0.064279
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0x3fb0749b57b09f6c
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// 0.090849
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0x3fb741e98925ac09
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// 0.096415
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0x3fb8aea8dd2d9f60
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// 0.229429
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0x3fcd5ded0f16ce39
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// 0.278635
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0x3fd1d5267e1ff701
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// 0.078974
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0x3fb437a2f99783fc
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// 0.014116
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0x3f8ce8b0d65cea1e
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// 0.136180
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0x3fc16e5c2448f017
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// 0.113739
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0x3fbd1dfee47d7526
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// 0.014262
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0x3f8d35807b52bb38
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// 0.164832
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0x3fc519385dec9eb0
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// 0.173764
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0x3fc63de6d7b944c8
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// 0.092918
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0x3fb7c97fa6cbdd79
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// 0.163854
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0x3fc4f929fe4ebe2d
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// 0.118066
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0x3fbe398bbcfdf520
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// 0.022384
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0x3f96ebebdf4cf5b5
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// 0.008318
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0x3f8108debf1c188a
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// 0.135012
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0x3fc148117697674d
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// 0.106476
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0x3fbb420b2755099e
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// 0.135063
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0x3fc149bd2923d7a6
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// 0.108069
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0x3fbbaa6936142c3f
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// 0.038218
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0x3fa391498e2c8ec4
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// 0.017892
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0x3f9252517f6a400e
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// 0.050650
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0x3fa9eec84ae68d1c
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// 0.066123
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0x3fb0ed6f2034becb
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// 0.154318
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0x3fc3c0af2f83b20f
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// 0.005330
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0x3f75d54fb82e5b5e
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// 0.174531
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0x3fc65709620cd149
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// 0.434164
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0x3fdbc9575a8675f6
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// 0.062753
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0x3fb0108e60bada3e
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// 0.503083
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0x3fe0194286a569be
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// 0.132317
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0x3fc0efc111f57b42
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// 0.154534
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0x3fc3c7c715d99fde
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// 0.156671
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0x3fc40dcdb6423723
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// 0.061359
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0x3faf6a634a4b379e
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// 0.100333
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0x3fb9af6f5c11a434
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// 0.107005
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0x3fbb64aa0e48ab7f
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// 0.122395
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0x3fbf554c29cc943a
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// 0.165386
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0x3fc52b5e85486ddc
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@ -0,0 +1,152 @@
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D
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75
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// 0.501853
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0x3fe00f2ee978b047
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// 0.177515
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0x3fc6b8d10fd5ee4b
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// 0.320631
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0x3fd48539a523a84e
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// 0.047192
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0x3fa829850436d98b
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// 0.158713
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0x3fc450b4c623ec7d
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// 0.104308
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0x3fbab3f2f656a749
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// 0.205971
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0x3fca5d3e6b075a10
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||||
// 0.218328
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0x3fcbf22b6b1086a3
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// 0.118650
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0x3fbe5fdba7cfa8b1
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// 0.030952
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0x3f9fb1e9d483be94
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// 0.115886
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0x3fbdaab73225b93e
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// 0.113465
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0x3fbd0c04fff053b4
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// 0.148880
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0x3fc30e817da1d640
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// 0.128425
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0x3fc0703748090597
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// 0.122130
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0x3fbf43e6098ab895
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// 0.035091
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0x3fa1f7623e67a84b
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// 0.120082
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0x3fbebdb6179e919d
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// 0.145733
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0x3fc2a762a0f0bacb
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// 0.124931
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0x3fbffb79bbbeee35
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// 0.061264
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0x3faf5dfa6d78e4fd
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// 0.064801
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0x3fb096cf187042e3
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// 0.092918
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0x3fb7c97320f2a3ae
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// 0.118482
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0x3fbe54ceb43c30bc
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// 0.062414
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0x3faff4accb8bd8b0
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// 0.060437
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0x3faef1a8ccd0e611
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// 0.039589
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0x3fa444f8c3c66199
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// 0.105396
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0x3fbafb3f60731313
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// 0.102100
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0x3fba2340353bff17
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// 0.110738
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0x3fbc594c098a19bf
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// 0.080640
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||||
0x3fb4a4cb1be519ee
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// 0.046774
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||||
0x3fa7f2b354bd88a3
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||||
// 0.115713
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||||
0x3fbd9f577ed24e53
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// 0.439571
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0x3fdc21ed1f2ea6d7
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||||
// 0.282044
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||||
0x3fd20d041644dc92
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// 0.278385
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0x3fd1d10eca8c7c97
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||||
// 0.182100
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0x3fc74f10e76157a5
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// 0.043353
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0x3fa63261dc70867f
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// 0.042056
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0x3fa58869987c34b4
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// 0.128218
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0x3fc0697018a334b3
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// 0.136056
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0x3fc16a4920e0b468
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// 0.169850
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0x3fc5bda40485792a
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// 0.136761
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0x3fc181623e3a0bb2
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// 0.161605
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0x3fc4af7cbf200b96
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// 0.080238
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0x3fb48a8204653a41
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// 0.038292
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0x3fa39b0380dedfa9
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// 0.194841
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||||
0x3fc8f08c8462dcd7
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// 0.129271
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0x3fc08bf2ca4780be
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// 0.016048
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0x3f906ec52d80a287
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// 0.228960
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0x3fcd4e8c8faab1fe
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// 0.219449
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0x3fcc16e7c60ce05b
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||||
// 0.062672
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||||
0x3fb00b4bbec4cc77
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||||
// 0.030229
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0x3f9ef45fa10a03d4
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||||
// 0.008741
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||||
0x3f81e6917c79950e
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||||
// 0.121629
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||||
0x3fbf230d5cdc3e8a
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// 0.065855
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||||
0x3fb0dbdfe66a59de
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// 0.141689
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||||
0x3fc222db8d1db5ce
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// 0.137891
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0x3fc1a667b1cd01b9
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||||
// 0.142990
|
||||
0x3fc24d8303bfe315
|
||||
// 0.079355
|
||||
0x3fb450a30d958f82
|
||||
// 0.093264
|
||||
0x3fb7e027cf1d49b7
|
||||
// 0.058599
|
||||
0x3fae00a190b6bd75
|
||||
// 0.096343
|
||||
0x3fb8a9ec7a0837a1
|
||||
// 0.020144
|
||||
0x3f94a0841a8a6bf2
|
||||
// 0.033501
|
||||
0x3fa12715c437ea4d
|
||||
// 0.347819
|
||||
0x3fd642a9e74cc4eb
|
||||
// 0.305751
|
||||
0x3fd3916ca11c18f1
|
||||
// 0.346430
|
||||
0x3fd62be977972226
|
||||
// 0.115685
|
||||
0x3fbd9d8931dc83cd
|
||||
// 0.128242
|
||||
0x3fc06a3d21eb0ba8
|
||||
// 0.013092
|
||||
0x3f8acfc715554a30
|
||||
// 0.146638
|
||||
0x3fc2c505ae582974
|
||||
// 0.153318
|
||||
0x3fc39feddba73197
|
||||
// 0.197917
|
||||
0x3fc955581b9af273
|
||||
// 0.079896
|
||||
0x3fb47410ece8debb
|
||||
// 0.165212
|
||||
0x3fc525adb7c2a0ef
|
||||
@ -0,0 +1,152 @@
|
||||
D
|
||||
75
|
||||
// 0.263522
|
||||
0x3fd0dd8afff76385
|
||||
// 0.289325
|
||||
0x3fd2844bcd035f61
|
||||
// 0.447153
|
||||
0x3fdc9e2933053d19
|
||||
// 0.000025
|
||||
0x3efa6f4e7228bd15
|
||||
// 0.040059
|
||||
0x3fa4829304814b70
|
||||
// 0.053628
|
||||
0x3fab7524ae359534
|
||||
// 0.199652
|
||||
0x3fc98e32f2965e45
|
||||
// 0.205763
|
||||
0x3fca56733f1a01f7
|
||||
// 0.171010
|
||||
0x3fc5e3a89f0d1329
|
||||
// 0.134326
|
||||
0x3fc131988682ed56
|
||||
// 0.195537
|
||||
0x3fc90757419e55d9
|
||||
// 0.182694
|
||||
0x3fc7628782f84ace
|
||||
// 0.103593
|
||||
0x3fba850baa401081
|
||||
// 0.073549
|
||||
0x3fb2d41fc7af6949
|
||||
// 0.083657
|
||||
0x3fb56a8d4ff5c4ce
|
||||
// 0.109701
|
||||
0x3fbc15655565f88a
|
||||
// 0.177554
|
||||
0x3fc6ba14992cfb13
|
||||
// 0.143951
|
||||
0x3fc26cff04aaadfd
|
||||
// 0.081353
|
||||
0x3fb4d38ee714820e
|
||||
// 0.043947
|
||||
0x3fa680398000be22
|
||||
// 0.083992
|
||||
0x3fb58078d86368d7
|
||||
// 0.199730
|
||||
0x3fc990bdeb084e53
|
||||
// 0.062036
|
||||
0x3fafc3360baac4e8
|
||||
// 0.158378
|
||||
0x3fc445bb623c4b7f
|
||||
// 0.036417
|
||||
0x3fa2a53693e22a16
|
||||
// 0.018402
|
||||
0x3f92d7febc6e387b
|
||||
// 0.118342
|
||||
0x3fbe4ba21ce4600c
|
||||
// 0.002168
|
||||
0x3f61c378ef5efebb
|
||||
// 0.058332
|
||||
0x3fadddbafac042e0
|
||||
// 0.048660
|
||||
0x3fa8e9f397ef93b3
|
||||
// 0.067851
|
||||
0x3fb15ea6b21d3082
|
||||
// 0.145693
|
||||
0x3fc2a611572e750e
|
||||
// 0.048427
|
||||
0x3fa8cb76f97dc0ef
|
||||
// 0.295198
|
||||
0x3fd2e48464ca679e
|
||||
// 0.656375
|
||||
0x3fe501065e02f021
|
||||
// 0.088473
|
||||
0x3fb6a628682a7e83
|
||||
// 0.087547
|
||||
0x3fb6698255fbb263
|
||||
// 0.157099
|
||||
0x3fc41bd5965c12f9
|
||||
// 0.047299
|
||||
0x3fa83789c29247a8
|
||||
// 0.237495
|
||||
0x3fce663ac81f0c6c
|
||||
// 0.055216
|
||||
0x3fac454f2e4c27cd
|
||||
// 0.250528
|
||||
0x3fd008a5bf2917e8
|
||||
// 0.076343
|
||||
0x3fb38b310fcff8fd
|
||||
// 0.021593
|
||||
0x3f961c645b41c08a
|
||||
// 0.262684
|
||||
0x3fd0cfceb390413d
|
||||
// 0.112116
|
||||
0x3fbcb3a7b22f6ea7
|
||||
// 0.156858
|
||||
0x3fc413edec26286a
|
||||
// 0.044288
|
||||
0x3fa6ace2e1806ead
|
||||
// 0.230852
|
||||
0x3fcd8c91bb460a8c
|
||||
// 0.028178
|
||||
0x3f9cdacdb11e83ac
|
||||
// 0.001985
|
||||
0x3f6043dcf2bc61d6
|
||||
// 0.141445
|
||||
0x3fc21ae0aaa47d82
|
||||
// 0.219547
|
||||
0x3fcc1a19934b1be0
|
||||
// 0.009410
|
||||
0x3f83459cd302a689
|
||||
// 0.096667
|
||||
0x3fb8bf26175eeef3
|
||||
// 0.031591
|
||||
0x3fa02cb3fab03e31
|
||||
// 0.053311
|
||||
0x3fab4b880d02a953
|
||||
// 0.158655
|
||||
0x3fc44ecf8e8c9f7d
|
||||
// 0.004074
|
||||
0x3f70afd3e9975d43
|
||||
// 0.060421
|
||||
0x3faeef83359c9e67
|
||||
// 0.150100
|
||||
0x3fc336781ccb2f6b
|
||||
// 0.033587
|
||||
0x3fa132555bab6b42
|
||||
// 0.111738
|
||||
0x3fbc9ae433badb47
|
||||
// 0.070899
|
||||
0x3fb2267812291cf3
|
||||
// 0.094328
|
||||
0x3fb825da8e1fce34
|
||||
// 0.465077
|
||||
0x3fddc3d0b5d6209e
|
||||
// 0.440596
|
||||
0x3fdc32b8a6a1ebd4
|
||||
// 0.116737
|
||||
0x3fbde27eae730478
|
||||
// 0.145569
|
||||
0x3fc2a204aea21edf
|
||||
// 0.139047
|
||||
0x3fc1cc47a26356f2
|
||||
// 0.052558
|
||||
0x3faae8e3995a3677
|
||||
// 0.203339
|
||||
0x3fca07013a914739
|
||||
// 0.083542
|
||||
0x3fb5630a011891fd
|
||||
// 0.113459
|
||||
0x3fbd0bad4b66be46
|
||||
// 0.145748
|
||||
0x3fc2a7de90998afd
|
||||
@ -0,0 +1,22 @@
|
||||
D
|
||||
10
|
||||
// 0.833429
|
||||
0x3feaab74254fab33
|
||||
// 1.987310
|
||||
0x3fffcc05dcd7cd66
|
||||
// 1.901057
|
||||
0x3ffe6abb2f676934
|
||||
// 2.245504
|
||||
0x4001f6cae58c45f0
|
||||
// 0.809344
|
||||
0x3fe9e624b250b86c
|
||||
// 1.856407
|
||||
0x3ffdb3d806503032
|
||||
// 2.035090
|
||||
0x400047dd80fc17ed
|
||||
// 2.207907
|
||||
0x4001a9caffce45d4
|
||||
// 0.881589
|
||||
0x3fec35fae331ee22
|
||||
// 2.042380
|
||||
0x400056cb168cbab7
|
||||
@ -0,0 +1,22 @@
|
||||
D
|
||||
10
|
||||
// 0.129920
|
||||
0x3fc0a13512307c18
|
||||
// 0.513409
|
||||
0x3fe06dd851efeff6
|
||||
// 0.106515
|
||||
0x3fbb4490892ca6fc
|
||||
// 0.440309
|
||||
0x3fdc2e04ff890360
|
||||
// 0.717942
|
||||
0x3fe6f961d81600b0
|
||||
// 0.326888
|
||||
0x3fd4ebba22a3aa24
|
||||
// 0.716218
|
||||
0x3fe6eb41f5a1e15a
|
||||
// 0.849533
|
||||
0x3feb2f5f66c7e669
|
||||
// 0.242332
|
||||
0x3fcf04bcf8c08388
|
||||
// 0.222324
|
||||
0x3fcc751ae4b0f2e7
|
||||
@ -0,0 +1,96 @@
|
||||
#include "StatsTestsF64.h"
|
||||
#include <stdio.h>
|
||||
#include "Error.h"
|
||||
#include "arm_math.h"
|
||||
#include "Test.h"
|
||||
|
||||
|
||||
#define SNR_THRESHOLD 300
|
||||
/*
|
||||
|
||||
Reference patterns are generated with
|
||||
a double precision computation.
|
||||
|
||||
*/
|
||||
#define REL_ERROR (1.0e-14)
|
||||
|
||||
void StatsTestsF64::test_entropy_f64()
|
||||
{
|
||||
const float64_t *inp = inputA.ptr();
|
||||
const int16_t *dimsp = dims.ptr();
|
||||
|
||||
float64_t *refp = ref.ptr();
|
||||
float64_t *outp = output.ptr();
|
||||
|
||||
for(int i=0;i < this->nbPatterns; i++)
|
||||
{
|
||||
*outp = arm_entropy_f64(inp,dimsp[i+1]);
|
||||
outp++;
|
||||
inp += dimsp[i+1];
|
||||
}
|
||||
|
||||
ASSERT_SNR(ref,output,(float64_t)SNR_THRESHOLD);
|
||||
|
||||
ASSERT_REL_ERROR(ref,output,REL_ERROR);
|
||||
|
||||
}
|
||||
|
||||
void StatsTestsF64::test_kullback_leibler_f64()
|
||||
{
|
||||
const float64_t *inpA = inputA.ptr();
|
||||
const float64_t *inpB = inputB.ptr();
|
||||
const int16_t *dimsp = dims.ptr();
|
||||
|
||||
float64_t *refp = ref.ptr();
|
||||
float64_t *outp = output.ptr();
|
||||
|
||||
for(int i=0;i < this->nbPatterns; i++)
|
||||
{
|
||||
*outp = arm_kullback_leibler_f64(inpA,inpB,dimsp[i+1]);
|
||||
outp++;
|
||||
inpA += dimsp[i+1];
|
||||
inpB += dimsp[i+1];
|
||||
}
|
||||
|
||||
ASSERT_SNR(ref,output,(float64_t)SNR_THRESHOLD);
|
||||
|
||||
ASSERT_REL_ERROR(ref,output,REL_ERROR);
|
||||
}
|
||||
|
||||
|
||||
void StatsTestsF64::setUp(Testing::testID_t id,std::vector<Testing::param_t>& paramsArgs,Client::PatternMgr *mgr)
|
||||
{
|
||||
switch(id)
|
||||
{
|
||||
case StatsTestsF64::TEST_ENTROPY_F64_1:
|
||||
{
|
||||
inputA.reload(StatsTestsF64::INPUT22_F64_ID,mgr);
|
||||
dims.reload(StatsTestsF64::DIM22_S16_ID,mgr);
|
||||
ref.reload(StatsTestsF64::REF22_ENTROPY_F64_ID,mgr);
|
||||
output.create(ref.nbSamples(),StatsTestsF64::OUT_F64_ID,mgr);
|
||||
|
||||
const int16_t *dimsp = dims.ptr();
|
||||
this->nbPatterns=dimsp[0];
|
||||
}
|
||||
break;
|
||||
|
||||
case StatsTestsF64::TEST_KULLBACK_LEIBLER_F64_2:
|
||||
{
|
||||
inputA.reload(StatsTestsF64::INPUTA24_F64_ID,mgr);
|
||||
inputB.reload(StatsTestsF64::INPUTB24_F64_ID,mgr);
|
||||
dims.reload(StatsTestsF64::DIM24_S16_ID,mgr);
|
||||
ref.reload(StatsTestsF64::REF24_KL_F64_ID,mgr);
|
||||
output.create(ref.nbSamples(),StatsTestsF64::OUT_F64_ID,mgr);
|
||||
|
||||
const int16_t *dimsp = dims.ptr();
|
||||
this->nbPatterns=dimsp[0];
|
||||
}
|
||||
break;
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
void StatsTestsF64::tearDown(Testing::testID_t id,Client::PatternMgr *mgr)
|
||||
{
|
||||
output.dump(mgr);
|
||||
}
|
||||
Loading…
Reference in New Issue