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added regression test for RS

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Ahmet Inan 2018-09-27 22:33:40 +02:00
commit e660ae8c39
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tests/rs_regression_test.cc Normal file
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/*
Regression Test for the Reed Solomon Encoder and Decoder
Copyright 2018 Ahmet Inan <inan@aicodix.de>
*/
#include <cassert>
#include <random>
#include <iostream>
#include "galois_field.hh"
#include "reed_solomon_decoder.hh"
#include "reed_solomon_encoder.hh"
template <typename GF, typename ENC, typename DEC>
void rs_test(int trials)
{
std::random_device rd;
std::default_random_engine generator(rd());
GF instance;
DEC decode;
ENC encode;
auto rnd_cnt = std::bind(std::uniform_int_distribution<typename ENC::value_type>(0, ENC::NP), generator);
auto rnd_len = std::bind(std::uniform_int_distribution<typename ENC::value_type>(1, ENC::K), generator);
auto rnd_val = std::bind(std::uniform_int_distribution<typename ENC::value_type>(0, ENC::N), generator);
while (--trials) {
int data_len = rnd_len();
auto rnd_pos = std::bind(std::uniform_int_distribution<typename ENC::value_type>(0, data_len + ENC::NP - 1), generator);
typename ENC::value_type data[data_len], orig_data[data_len];
for (int i = 0; i < data_len; ++i)
data[i] = orig_data[i] = rnd_val();
typename ENC::value_type parity[ENC::NP];
encode(data, parity, data_len);
for (int i = 0; i < data_len; ++i)
assert(data[i] == orig_data[i]);
typename ENC::value_type orig_parity[ENC::NP];
for (int i = 0; i < ENC::NP; ++i)
orig_parity[i] = parity[i];
int error_count = rnd_cnt() / 2;
typename ENC::value_type errors[error_count];
for (int i = 0; i < error_count; ++i) {
int pos = rnd_pos();
for (int j = 0; j < i; ++j) {
if (errors[j] == pos) {
pos = rnd_pos();
j = -1;
}
}
errors[i] = pos;
if (pos < data_len)
data[pos] = rnd_val();
else
parity[pos-data_len] = rnd_val();
}
int erasures_count = ENC::NP - 2 * error_count;
typename ENC::value_type erasures[erasures_count];
for (int i = 0; i < erasures_count; ++i) {
int pos = rnd_pos();
for (int j = 0; j < i; ++j) {
if (erasures[j] == pos) {
pos = rnd_pos();
j = -1;
}
}
erasures[i] = pos;
if (pos < data_len)
data[pos] = rnd_val();
else
parity[pos-data_len] = rnd_val();
}
int ret = decode(data, parity, erasures, erasures_count, data_len);
assert(ret >= 0);
for (int i = 0; i < data_len; ++i)
assert(data[i] == orig_data[i]);
for (int i = 0; i < ENC::NP; ++i)
assert(parity[i] == orig_parity[i]);
}
}
int main()
{
if (1) {
// BBC WHP031 RS(15, 11) T=2
typedef CODE::GaloisField<4, 0b10011, uint8_t> GF;
typedef CODE::ReedSolomonDecoder<4, 0, GF> Decoder;
typedef CODE::ReedSolomonEncoder<4, 0, GF> Encoder;
rs_test<GF, Encoder, Decoder>(1000000);
}
if (1) {
// DVB-T RS(255, 239) T=8
typedef CODE::GaloisField<8, 0b100011101, uint8_t> GF;
typedef CODE::ReedSolomonDecoder<16, 0, GF> Decoder;
typedef CODE::ReedSolomonEncoder<16, 0, GF> Encoder;
rs_test<GF, Encoder, Decoder>(100000);
}
if (1) {
// FUN RS(65535, 65471) T=32
typedef CODE::GaloisField<16, 0b10001000000001011, uint16_t> GF;
typedef CODE::ReedSolomonDecoder<64, 1, GF> Decoder;
typedef CODE::ReedSolomonEncoder<64, 1, GF> Encoder;
rs_test<GF, Encoder, Decoder>(100);
}
std::cerr << "Reed Solomon regression test passed!" << std::endl;
return 0;
}