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