/* vim:set ts=2 sw=2 sts=2 et: */ /** * \author Marcus Holland-Moritz (github@mhxnet.de) * \copyright Copyright (c) Marcus Holland-Moritz * * This file is part of dwarfs. * * dwarfs is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * dwarfs is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with dwarfs. If not, see . */ #include #include #include #include #include #include #include #include #include #include #include #include using namespace dwarfs; namespace { template std::vector generate_random_data(std::mt19937_64& rng, size_t count, unsigned unused_lsb_count = 0, unsigned full_chance = 50) { std::uniform_int_distribution dist(0, full_chance); std::uniform_int_distribution noise(30000, 31000); std::uniform_int_distribution full( 0, std::numeric_limits::max()); std::vector data(count); ValueType mask = static_cast(std::numeric_limits::max() << unused_lsb_count); std::generate(data.begin(), data.end(), [&]() { auto v = dist(rng) == 0 ? full(rng) : noise(rng); return folly::Endian::big(v & mask); }); return data; } template std::vector make_test_data(int components, int pixels, int unused_lsb) { std::mt19937_64 rng(42); std::uniform_int_distribution any_value( 0, std::numeric_limits::max()); std::vector> data(components); auto random_value = [&]() { return folly::Endian::big(any_value(rng) << unused_lsb); }; for (auto& d : data) { auto d1 = generate_random_data(rng, pixels / 3, unused_lsb); auto d2 = std::vector(pixels / 3, random_value()); auto d3 = generate_random_data( rng, pixels - (d1.size() + d2.size()), unused_lsb, 0); d = ranges::views::concat(d1, d2, d3) | ranges::to_vector; } if (data.size() < 1 || data.size() > 2) { throw std::runtime_error("invalid number of components"); } std::vector tmp; tmp.resize(data.size() * data[0].size()); for (size_t i = 0; i < data[0].size(); ++i) { for (size_t j = 0; j < data.size(); ++j) { tmp[i * data.size() + j] = data[j][i]; } } std::vector out; out.resize(tmp.size() * sizeof(ValueType)); std::memcpy(out.data(), tmp.data(), out.size()); return out; } struct data_params { data_params(int components, int pixels, int unused, int block = 0) : num_components{components} , num_pixels{pixels} , unused_lsb{unused} , block_size{block} {} int num_components; int num_pixels; int unused_lsb; int block_size; }; std::ostream& operator<<(std::ostream& os, data_params const& p) { os << "{comp=" << p.num_components << ", pix=" << p.num_pixels << ", lsb=" << p.unused_lsb << ", block=" << p.block_size << "}"; return os; } std::vector const data_parameters{ // clang-format off { 1, 1000, 0, 16 }, { 2, 1000, 2, 32 }, { 1, 1000, 4, 64 }, { 2, 3333, 6, 99 }, // clang-format on }; } // namespace class ricepp_param : public testing::TestWithParam {}; TEST_P(ricepp_param, combinations) { auto param = GetParam(); nlohmann::json meta{ {"endianness", "big"}, {"bytes_per_sample", 2}, {"unused_lsb_count", param.unused_lsb}, {"component_count", param.num_components}, }; auto const data = make_test_data( param.num_components, param.num_pixels, param.unused_lsb); block_compressor comp(fmt::format("ricepp:block_size={}", param.block_size)); auto compressed = comp.compress(data, meta.dump()); EXPECT_LT(compressed.size(), 7 * data.size() / 10); auto decompressed = block_decompressor::decompress( compression_type::RICEPP, compressed.data(), compressed.size()); ASSERT_EQ(data.size(), decompressed.size()); EXPECT_EQ(data, decompressed); } INSTANTIATE_TEST_SUITE_P(dwarfs, ricepp_param, ::testing::ValuesIn(data_parameters));