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AdaptivePrecisionDecoder-Analysis.cpp
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247 lines (199 loc) · 7.97 KB
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#include <iostream>
#include <iomanip>
#include <vector>
#include <string>
#include <fstream>
#include <filesystem>
#include "encoder.hpp"
#include "precision_encoder.hpp"
/*
Adaptive Precision Encoder Analysis Tool
Tool to visualize how the AdaptivePrecisionEncoder makes decisions
about encoding data as compared to the base Encoder.
*/
namespace fs = std::filesystem;
namespace analysis
{
struct EncodingDecision
{
double value;
uint64_t xor_val;
int lzs;
int tzs;
int precision;
bool reused;
int written;
};
void analyze(const std::vector<double> &data)
{
std::cout << "\nAdaptive Precision Encoder Analysis.\n";
comp::PrecisionEncoder baseEncoder(data.size() * 128);
comp::AdaptivePrecisionEncoder apEncoder(data.size() * 128);
for(const auto &d : data)
{
baseEncoder.append(d);
apEncoder.append(d);
}
baseEncoder.fin();
apEncoder.fin();
std::cout << "\nCompression Comparison.\n";
std::cout << std::left << std::setw(30) << "Metric" <<
std::right << std::setw(20) << "Base Precision" <<
std::setw(20) << "Adaptive Precision" <<
std::setw(20) << "Improvement" << '\n';
size_t baseSize = baseEncoder.sizeInBytes();
size_t apSize = apEncoder.sizeInBytes();
size_t originalSize = data.size() * sizeof(double);
double baseRatio = 100 * (baseSize / (double)originalSize);
double apRatio = 100 * (apSize / (double)originalSize);
double improvement = 100 * (double)(baseSize - apSize) / (double)baseSize;
std::cout << std::fixed << std::setprecision(2);
std::cout << std::left << std::setw(30) << "Compressed Size (bytes)"
<< std::right << std::setw(20) << baseSize
<< std::right << std::setw(20) << apSize
<< std::right << std::setw(20) << improvement << "%\n";
std::cout << std::left << std::setw(30) << "Compression Ratio"
<< std::right << std::setw(20) << baseRatio
<< std::right << std::setw(20) << apRatio
<< std::right << std::setw(20) << "-\n";
std::cout << "Stats\n";
std::cout << std::left << std::setw(40) << "Average Precision Ratio"
<< std::right << std::setw(15) << apEncoder.getAvPrecision() << '\n';
std::cout << std::left << std::setw(40) << "Precision Volatility (%)"
<< std::right << std::setw(15) << apEncoder.getPrecisionVol() << '\n';
std::cout << std::left << std::setw(40) << "Precision Reuse Rate (%)"
<< std::right << std::setw(15) << std::setprecision(1)
<< (apEncoder.getPrecisionReuseRate() * 100) << "%\n";
std::cout << "\nDetailed Behavior\n";
std::cout << std::left << std::setw(8) << "Index"
<< std::right << std::setw(15) << "Value"
<< std::setw(12) << "XOR Bits"
<< std::setw(10) << "Leading Zeros"
<< std::setw(10) << "Trailing Zeros"
<< std::setw(12) << "Precision"
<< std::setw(18) << "Base Detection"
<< std::setw(18) << "Adaptive Detection"
<< '\n';
//Re-encode first 50 values
comp::PrecisionEncoder baseTracker(data.size() * 128);
comp::AdaptivePrecisionEncoder apTracker(data.size() * 128);
uint64_t prev_val{0};
bool first{true};
for(size_t i{0}; i < std::min(size_t(50), data.size()); ++i)
{
uint64_t u_val = comp::to_uint64(data[i]);
if(first)
{
std::cout << std::left << std::setw(8) << i
<< std::right << std::fixed << std::setprecision(6)
<< std::setw(15) << data[i]
<< std::setw(12) << '-'
<< std::setw(10) << '-'
<< std::setw(10) << '-'
<< std::setw(12) << "64"
<< std::setw(18) << "FIRST (64 bits)"
<< std::setw(18) << "FIRST (64 bits)"
<< '\n';
prev_val = u_val;
first = false;
continue;
}
uint64_t xor_val = u_val ^ prev_val;
if(xor_val == 0)
{
std::cout << std::left << std::setw(8) << i
<< std::right << std::fixed << std::setprecision(6)
<< std::setw(15) << data[i]
<< std::setw(12) << '0'
<< std::setw(10) << '-'
<< std::setw(10) << '-'
<< std::setw(12) << '0'
<< std::setw(18) << "SAME (1 bit)"
<< std::setw(18) << "SAME (1 bit)"
<< '\n';
}
else
{
int lzs = comp::count_lzs(xor_val);
int tzs = comp::count_tzs(xor_val);
if(lzs >= 32) { lzs = 31; }
int len = 64 - lzs - tzs;
if(len <= 0) { len = 1; }
std::cout << std::left << std::setw(8) << i
<< std::right << std::fixed << std::setprecision(6)
<< std::setw(15) << data[i]
<< std::setw(12) << len
<< std::setw(10) << lzs
<< std::setw(10) << tzs
<< std::setw(12) << len
<< std::setw(18) << "NEW/REUSE"
<< std::setw(18) << "ADAPTIVE"
<< '\n';
}
prev_val = u_val;
}
//Export results to csv
std::string folder = "../results";
std::string filename = folder + "/adaptive_precision_analysis.csv";
try
{
if(!fs::exists(folder))
{
fs::create_directories(folder);
std::cout << "Created director: " << fs::absolute(folder) << '\n';
}
}
catch(const fs::filesystem_error &fe)
{
std::cerr << "Filesystem error: " << fe.what() << '\n';
return;
}
std::ofstream csv(filename);
if(csv.is_open())
{
csv << "Index,Value,XOR_Bits,Leading_Zeros,Trailing_Zeros,Precision\n";
prev_val = 0;
first = true;
for(size_t i{0}; i < data.size(); ++i)
{
uint64_t uval = comp::to_uint64(data[i]);
if(first)
{
csv << i << ',' << data[i] << ",64,0,0,64\n";
prev_val = uval;
first = false;
continue;
}
uint64_t xor_v = uval ^ prev_val;
if(xor_v == 0)
{
csv << i << ',' << data[i] << ",0,0,0,0\n";
}
else
{
int lzs = comp::count_lzs(xor_v);
int tzs = comp::count_tzs(xor_v);
if(lzs >= 32) { lzs = 31; }
int len = 64 - lzs - tzs;
if(len <= 0) { len = 1; }
csv << i << ',' << data[i] << ',' << len << ',' << lzs << ',' << tzs << ',' << len << '\n';
}
prev_val = uval;
}
csv.close();
std::cout << "\nAnalysis exported to: results//adaptive_precision_analysis.csv";
}
}
}
int main()
{
const int TICKS = 10000;
//Perforning Analysis of Generated Test Data
std::vector<double> data(TICKS, 100.25);
for(size_t i{0}; i < data.size(); ++i)
{
if(i % 5 == 0) { data[i] += 0.05; }
}
analysis::analyze(data);
return 0;
}