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// ----------------------------------------------------------------------------
// - Open3D: www.open3d.org -
// ----------------------------------------------------------------------------
// Copyright (c) 2018-2024 www.open3d.org
// SPDX-License-Identifier: MIT
// ----------------------------------------------------------------------------
#include "open3d/core/nns/NanoFlannIndex.h"
#include <cmath>
#include <limits>
#include "core/CoreTest.h"
#include "open3d/core/Device.h"
#include "open3d/core/Dtype.h"
#include "open3d/core/SizeVector.h"
#include "open3d/core/Tensor.h"
#include "open3d/utility/Helper.h"
#include "tests/Tests.h"
#include "tests/core/CoreTest.h"
using namespace open3d;
using namespace std;
namespace open3d {
namespace tests {
TEST(NanoFlannIndex, SearchKnn) {
// Define test data.
core::Device device = core::Device("CPU:0");
core::Tensor dataset_points = core::Tensor::Init<double>({{0.0, 0.0, 0.0},
{0.0, 0.0, 0.1},
{0.0, 0.0, 0.2},
{0.0, 0.1, 0.0},
{0.0, 0.1, 0.1},
{0.0, 0.1, 0.2},
{0.0, 0.2, 0.0},
{0.0, 0.2, 0.1},
{0.0, 0.2, 0.2},
{0.1, 0.0, 0.0}},
device);
core::Tensor query_points = core::Tensor::Init<double>(
{{0.064705, 0.043921, 0.087843}}, device);
core::Tensor gt_indices, gt_distances;
// int32
// Set up index.
core::nns::NanoFlannIndex index32(dataset_points, core::Int32);
// if k <= 0.
EXPECT_THROW(index32.SearchKnn(query_points, -1), std::runtime_error);
EXPECT_THROW(index32.SearchKnn(query_points, 0), std::runtime_error);
// if k == 3
core::Tensor indices, distances;
core::SizeVector shape{1, 3};
gt_indices = core::Tensor::Init<int32_t>({{1, 4, 9}}, device);
gt_distances = core::Tensor::Init<double>(
{{0.00626358, 0.00747938, 0.0108912}}, device);
std::tie(indices, distances) = index32.SearchKnn(query_points, 3);
EXPECT_EQ(indices.GetShape(), shape);
EXPECT_EQ(distances.GetShape(), shape);
EXPECT_TRUE(indices.AllClose(gt_indices));
EXPECT_TRUE(distances.AllClose(gt_distances));
// if k > size.
shape = core::SizeVector{1, 10};
gt_indices = core::Tensor::Init<int32_t>({{1, 4, 9, 0, 3, 2, 5, 7, 6, 8}},
device);
gt_distances = core::Tensor::Init<double>(
{{0.00626358, 0.00747938, 0.0108912, 0.0138322, 0.015048, 0.018695,
0.0199108, 0.0286952, 0.0362638, 0.0411266}},
device);
std::tie(indices, distances) = index32.SearchKnn(query_points, 12);
EXPECT_EQ(indices.GetShape(), shape);
EXPECT_EQ(distances.GetShape(), shape);
EXPECT_TRUE(indices.AllClose(gt_indices));
EXPECT_TRUE(distances.AllClose(gt_distances));
// int64
// Set up index.
core::nns::NanoFlannIndex index64(dataset_points, core::Int64);
// if k <= 0.
EXPECT_THROW(index64.SearchKnn(query_points, -1), std::runtime_error);
EXPECT_THROW(index64.SearchKnn(query_points, 0), std::runtime_error);
// if k == 3
shape = core::SizeVector{1, 3};
gt_indices = core::Tensor::Init<int64_t>({{1, 4, 9}}, device);
gt_distances = core::Tensor::Init<double>(
{{0.00626358, 0.00747938, 0.0108912}}, device);
std::tie(indices, distances) = index64.SearchKnn(query_points, 3);
EXPECT_EQ(indices.GetShape(), shape);
EXPECT_EQ(distances.GetShape(), shape);
EXPECT_TRUE(indices.AllClose(gt_indices));
EXPECT_TRUE(distances.AllClose(gt_distances));
// if k > size.
shape = core::SizeVector{1, 10};
gt_indices = core::Tensor::Init<int64_t>({{1, 4, 9, 0, 3, 2, 5, 7, 6, 8}},
device);
gt_distances = core::Tensor::Init<double>(
{{0.00626358, 0.00747938, 0.0108912, 0.0138322, 0.015048, 0.018695,
0.0199108, 0.0286952, 0.0362638, 0.0411266}},
device);
std::tie(indices, distances) = index64.SearchKnn(query_points, 12);
EXPECT_EQ(indices.GetShape(), shape);
EXPECT_EQ(distances.GetShape(), shape);
EXPECT_TRUE(indices.AllClose(gt_indices));
EXPECT_TRUE(distances.AllClose(gt_distances));
}
TEST(NanoFlannIndex, SearchRadius) {
// Define test data.
core::Device device = core::Device("CPU:0");
core::Tensor dataset_points = core::Tensor::Init<double>({{0.0, 0.0, 0.0},
{0.0, 0.0, 0.1},
{0.0, 0.0, 0.2},
{0.0, 0.1, 0.0},
{0.0, 0.1, 0.1},
{0.0, 0.1, 0.2},
{0.0, 0.2, 0.0},
{0.0, 0.2, 0.1},
{0.0, 0.2, 0.2},
{0.1, 0.0, 0.0}},
device);
core::Tensor query_points = core::Tensor::Init<double>(
{{0.064705, 0.043921, 0.087843}}, device);
core::Tensor gt_indices, gt_distances, gt_neighbors_row_splits;
// int32
// Set up index.
core::nns::NanoFlannIndex index32(dataset_points, core::Int32);
// if radius <= 0
EXPECT_THROW(index32.SearchRadius(query_points, -1.0), std::runtime_error);
EXPECT_THROW(index32.SearchRadius(query_points, 0.0), std::runtime_error);
// if radius == 0.1
core::Tensor indices, distances, neighbors_row_splits;
core::SizeVector shape{2};
gt_indices = core::Tensor::Init<int32_t>({1, 4}, device);
gt_distances = core::Tensor::Init<double>({0.00626358, 0.00747938}, device);
gt_neighbors_row_splits = core::Tensor::Init<int32_t>({0, 2}, device);
core::Tensor radii = core::Tensor::Init<double>({0.1});
std::tie(indices, distances, neighbors_row_splits) =
index32.SearchRadius(query_points, radii, false);
EXPECT_EQ(indices.GetShape(), shape);
EXPECT_EQ(distances.GetShape(), shape);
EXPECT_EQ(neighbors_row_splits.GetShape(), shape);
EXPECT_TRUE(indices.AllClose(gt_indices));
EXPECT_TRUE(distances.AllClose(gt_distances));
EXPECT_TRUE(neighbors_row_splits.AllClose(gt_neighbors_row_splits));
// int64
// Set up index.
core::nns::NanoFlannIndex index64(dataset_points, core::Int64);
// if radius <= 0
EXPECT_THROW(index64.SearchRadius(query_points, -1.0), std::runtime_error);
EXPECT_THROW(index64.SearchRadius(query_points, 0.0), std::runtime_error);
// if radius == 0.1
shape = core::SizeVector{2};
gt_indices = core::Tensor::Init<int64_t>({1, 4}, device);
gt_distances = core::Tensor::Init<double>({0.00626358, 0.00747938}, device);
gt_neighbors_row_splits = core::Tensor::Init<int64_t>({0, 2}, device);
std::tie(indices, distances, neighbors_row_splits) =
index64.SearchRadius(query_points, radii, false);
EXPECT_EQ(indices.GetShape(), shape);
EXPECT_EQ(distances.GetShape(), shape);
EXPECT_EQ(neighbors_row_splits.GetShape(), shape);
EXPECT_TRUE(indices.AllClose(gt_indices));
EXPECT_TRUE(distances.AllClose(gt_distances));
EXPECT_TRUE(neighbors_row_splits.AllClose(gt_neighbors_row_splits));
}
} // namespace tests
} // namespace open3d
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