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232 lines
7.3 KiB
C++
232 lines
7.3 KiB
C++
#include "aare/ClusterVector.hpp"
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#include <cstdint>
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#include <catch2/catch_all.hpp>
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#include <catch2/catch_test_macros.hpp>
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#include <catch2/matchers/catch_matchers_floating_point.hpp>
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using aare::Cluster;
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using aare::ClusterVector;
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TEST_CASE("ClusterVector 2x2 int32_t capacity 4, push back then read",
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"[.ClusterVector]") {
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ClusterVector<Cluster<int32_t, 2, 2>> cv(4);
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REQUIRE(cv.capacity() == 4);
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REQUIRE(cv.size() == 0);
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REQUIRE(cv.cluster_size_x() == 2);
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REQUIRE(cv.cluster_size_y() == 2);
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// int16_t, int16_t, 2x2 int32_t = 20 bytes
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REQUIRE(cv.item_size() == 20);
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// Create a cluster and push back into the vector
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Cluster<int32_t, 2, 2> c1 = {1, 2, {3, 4, 5, 6}};
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cv.push_back(c1);
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REQUIRE(cv.size() == 1);
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REQUIRE(cv.capacity() == 4);
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// Read the cluster back out using copy. TODO! Can we improve the API?
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Cluster<int32_t, 2, 2> c2;
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std::byte *ptr = cv.element_ptr(0);
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std::copy(ptr, ptr + cv.item_size(), reinterpret_cast<std::byte *>(&c2));
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// Check that the data is the same
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REQUIRE(c1.x == c2.x);
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REQUIRE(c1.y == c2.y);
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for (size_t i = 0; i < 4; i++) {
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REQUIRE(c1.data[i] == c2.data[i]);
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}
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}
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TEST_CASE("Summing 3x1 clusters of int64", "[.ClusterVector]") {
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ClusterVector<Cluster<int32_t, 3, 1>> cv(2);
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REQUIRE(cv.capacity() == 2);
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REQUIRE(cv.size() == 0);
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REQUIRE(cv.cluster_size_x() == 3);
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REQUIRE(cv.cluster_size_y() == 1);
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// Create a cluster and push back into the vector
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Cluster<int32_t, 3, 1> c1 = {1, 2, {3, 4, 5}};
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cv.push_back(c1);
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REQUIRE(cv.capacity() == 2);
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REQUIRE(cv.size() == 1);
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Cluster<int32_t, 3, 1> c2 = {6, 7, {8, 9, 10}};
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cv.push_back(c2);
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REQUIRE(cv.capacity() == 2);
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REQUIRE(cv.size() == 2);
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Cluster<int32_t, 3, 1> c3 = {11, 12, {13, 14, 15}};
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cv.push_back(c3);
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REQUIRE(cv.capacity() == 4);
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REQUIRE(cv.size() == 3);
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auto sums = cv.sum();
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REQUIRE(sums.size() == 3);
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REQUIRE(sums[0] == 12);
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REQUIRE(sums[1] == 27);
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REQUIRE(sums[2] == 42);
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}
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TEST_CASE("Storing floats", "[.ClusterVector]") {
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ClusterVector<Cluster<float, 2, 4>> cv(10);
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REQUIRE(cv.capacity() == 10);
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REQUIRE(cv.size() == 0);
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REQUIRE(cv.cluster_size_x() == 2);
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REQUIRE(cv.cluster_size_y() == 4);
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// Create a cluster and push back into the vector
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Cluster<float, 2, 4> c1 = {1, 2, {3.0, 4.0, 5.0, 6.0, 3.0, 4.0, 5.0, 6.0}};
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cv.push_back(c1);
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REQUIRE(cv.capacity() == 10);
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REQUIRE(cv.size() == 1);
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Cluster<float, 2, 4> c2 = {
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6, 7, {8.0, 9.0, 10.0, 11.0, 8.0, 9.0, 10.0, 11.0}};
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cv.push_back(c2);
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REQUIRE(cv.capacity() == 10);
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REQUIRE(cv.size() == 2);
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auto sums = cv.sum();
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REQUIRE(sums.size() == 2);
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REQUIRE_THAT(sums[0], Catch::Matchers::WithinAbs(36.0, 1e-6));
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REQUIRE_THAT(sums[1], Catch::Matchers::WithinAbs(76.0, 1e-6));
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}
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TEST_CASE("Push back more than initial capacity", "[.ClusterVector]") {
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ClusterVector<Cluster<int32_t, 2, 2>> cv(2);
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auto initial_data = cv.data();
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Cluster<int32_t, 2, 2> c1 = {1, 2, {3, 4, 5, 6}};
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cv.push_back(c1);
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REQUIRE(cv.size() == 1);
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REQUIRE(cv.capacity() == 2);
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Cluster<int32_t, 2, 2> c2 = {6, 7, {8, 9, 10, 11}};
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cv.push_back(c2);
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REQUIRE(cv.size() == 2);
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REQUIRE(cv.capacity() == 2);
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Cluster<int32_t, 2, 2> c3 = {11, 12, {13, 14, 15, 16}};
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cv.push_back(c3);
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REQUIRE(cv.size() == 3);
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REQUIRE(cv.capacity() == 4);
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Cluster<int32_t, 2, 2> *ptr =
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reinterpret_cast<Cluster<int32_t, 2, 2> *>(cv.data());
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REQUIRE(ptr[0].x == 1);
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REQUIRE(ptr[0].y == 2);
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REQUIRE(ptr[1].x == 6);
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REQUIRE(ptr[1].y == 7);
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REQUIRE(ptr[2].x == 11);
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REQUIRE(ptr[2].y == 12);
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// We should have allocated a new buffer, since we outgrew the initial
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// capacity
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REQUIRE(initial_data != cv.data());
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}
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TEST_CASE("Concatenate two cluster vectors where the first has enough capacity",
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"[.ClusterVector]") {
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ClusterVector<Cluster<int32_t, 2, 2>> cv1(12);
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Cluster<int32_t, 2, 2> c1 = {1, 2, {3, 4, 5, 6}};
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cv1.push_back(c1);
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Cluster<int32_t, 2, 2> c2 = {6, 7, {8, 9, 10, 11}};
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cv1.push_back(c2);
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ClusterVector<Cluster<int32_t, 2, 2>> cv2(2);
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Cluster<int32_t, 2, 2> c3 = {11, 12, {13, 14, 15, 16}};
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cv2.push_back(c3);
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Cluster<int32_t, 2, 2> c4 = {16, 17, {18, 19, 20, 21}};
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cv2.push_back(c4);
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cv1 += cv2;
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REQUIRE(cv1.size() == 4);
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REQUIRE(cv1.capacity() == 12);
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Cluster<int32_t, 2, 2> *ptr =
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reinterpret_cast<Cluster<int32_t, 2, 2> *>(cv1.data());
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REQUIRE(ptr[0].x == 1);
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REQUIRE(ptr[0].y == 2);
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REQUIRE(ptr[1].x == 6);
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REQUIRE(ptr[1].y == 7);
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REQUIRE(ptr[2].x == 11);
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REQUIRE(ptr[2].y == 12);
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REQUIRE(ptr[3].x == 16);
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REQUIRE(ptr[3].y == 17);
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}
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TEST_CASE("Concatenate two cluster vectors where we need to allocate",
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"[.ClusterVector]") {
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ClusterVector<Cluster<int32_t, 2, 2>> cv1(2);
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Cluster<int32_t, 2, 2> c1 = {1, 2, {3, 4, 5, 6}};
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cv1.push_back(c1);
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Cluster<int32_t, 2, 2> c2 = {6, 7, {8, 9, 10, 11}};
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cv1.push_back(c2);
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ClusterVector<Cluster<int32_t, 2, 2>> cv2(2);
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Cluster<int32_t, 2, 2> c3 = {11, 12, {13, 14, 15, 16}};
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cv2.push_back(c3);
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Cluster<int32_t, 2, 2> c4 = {16, 17, {18, 19, 20, 21}};
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cv2.push_back(c4);
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cv1 += cv2;
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REQUIRE(cv1.size() == 4);
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REQUIRE(cv1.capacity() == 4);
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Cluster<int32_t, 2, 2> *ptr =
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reinterpret_cast<Cluster<int32_t, 2, 2> *>(cv1.data());
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REQUIRE(ptr[0].x == 1);
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REQUIRE(ptr[0].y == 2);
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REQUIRE(ptr[1].x == 6);
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REQUIRE(ptr[1].y == 7);
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REQUIRE(ptr[2].x == 11);
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REQUIRE(ptr[2].y == 12);
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REQUIRE(ptr[3].x == 16);
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REQUIRE(ptr[3].y == 17);
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}
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struct ClusterTestData {
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uint8_t ClusterSizeX;
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uint8_t ClusterSizeY;
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std::vector<int64_t> index_map_x;
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std::vector<int64_t> index_map_y;
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};
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TEST_CASE("Gain Map Calculation Index Map", "[.ClusterVector][.gain_map]") {
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auto clustertestdata = GENERATE(
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ClusterTestData{3,
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3,
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{-1, 0, 1, -1, 0, 1, -1, 0, 1},
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{-1, -1, -1, 0, 0, 0, 1, 1, 1}},
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ClusterTestData{
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4,
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4,
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{-2, -1, 0, 1, -2, -1, 0, 1, -2, -1, 0, 1, -2, -1, 0, 1},
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{-2, -2, -2, -2, -1, -1, -1, -1, 0, 0, 0, 0, 1, 1, 1, 1}},
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ClusterTestData{2, 2, {-1, 0, -1, 0}, {-1, -1, 0, 0}},
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ClusterTestData{5,
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5,
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{-2, -1, 0, 1, 2, -2, -1, 0, 1, 2, -2, -1, 0,
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1, 2, -2, -1, 0, 1, 2, -2, -1, 0, 1, 2},
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{-2, -2, -2, -2, -2, -1, -1, -1, -1, -1, 0, 0, 0,
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0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2}});
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uint8_t ClusterSizeX = clustertestdata.ClusterSizeX;
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uint8_t ClusterSizeY = clustertestdata.ClusterSizeY;
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std::vector<int64_t> index_map_x(ClusterSizeX * ClusterSizeY);
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std::vector<int64_t> index_map_y(ClusterSizeX * ClusterSizeY);
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int64_t index_cluster_center_x = ClusterSizeX / 2;
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int64_t index_cluster_center_y = ClusterSizeY / 2;
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for (size_t j = 0; j < ClusterSizeX * ClusterSizeY; j++) {
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index_map_x[j] = j % ClusterSizeX - index_cluster_center_x;
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index_map_y[j] = j / ClusterSizeX - index_cluster_center_y;
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}
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CHECK(index_map_x == clustertestdata.index_map_x);
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CHECK(index_map_y == clustertestdata.index_map_y);
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} |