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Add an example to demonstrate sampling and point advection using an a…
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…daptive grid

Signed-off-by: Dan Bailey <danbailey@ilm.com>
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@danrbailey
danrbailey committed Mar 12, 2024
1 parent 6145b10 commit ed5046d
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106 changes: 68 additions & 38 deletions openvdb/openvdb/tools/Interpolation.h
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Original file line number Diff line number Diff line change
Expand Up @@ -629,29 +629,35 @@ template<class ValueT, class TreeT, size_t N>
inline void
BoxSampler::getValues(ValueT (&data)[N][N][N], const TreeT& inTree, Coord ijk)
{
data[0][0][0] = inTree.getValue(ijk); // i, j, k
// This algorithm is only defined for sparse grids

ijk[2] += 1;
data[0][0][1] = inTree.getValue(ijk); // i, j, k + 1
if constexpr (TreeTraits<TreeT>::IsSparse) {
data[0][0][0] = inTree.getValue(ijk); // i, j, k

ijk[1] += 1;
data[0][1][1] = inTree.getValue(ijk); // i, j+1, k + 1
ijk[2] += 1;
data[0][0][1] = inTree.getValue(ijk); // i, j, k + 1

ijk[2] -= 1;
data[0][1][0] = inTree.getValue(ijk); // i, j+1, k
ijk[1] += 1;
data[0][1][1] = inTree.getValue(ijk); // i, j+1, k + 1

ijk[0] += 1;
ijk[1] -= 1;
data[1][0][0] = inTree.getValue(ijk); // i+1, j, k
ijk[2] -= 1;
data[0][1][0] = inTree.getValue(ijk); // i, j+1, k

ijk[2] += 1;
data[1][0][1] = inTree.getValue(ijk); // i+1, j, k + 1
ijk[0] += 1;
ijk[1] -= 1;
data[1][0][0] = inTree.getValue(ijk); // i+1, j, k

ijk[1] += 1;
data[1][1][1] = inTree.getValue(ijk); // i+1, j+1, k + 1
ijk[2] += 1;
data[1][0][1] = inTree.getValue(ijk); // i+1, j, k + 1

ijk[2] -= 1;
data[1][1][0] = inTree.getValue(ijk); // i+1, j+1, k
ijk[1] += 1;
data[1][1][1] = inTree.getValue(ijk); // i+1, j+1, k + 1

ijk[2] -= 1;
data[1][1][0] = inTree.getValue(ijk); // i+1, j+1, k
} else {
static_assert(AlwaysFalseValue<TreeT>, "Not Implemented");
}
}

template<class ValueT, class TreeT, size_t N>
Expand Down Expand Up @@ -744,39 +750,63 @@ inline bool
BoxSampler::sample(const TreeT& inTree, const Vec3R& inCoord,
typename TreeT::ValueType& result)
{
using ValueT = typename TreeT::ValueType;

const Vec3i inIdx = local_util::floorVec3(inCoord);
const Vec3R uvw = inCoord - inIdx;

// Retrieve the values of the eight voxels surrounding the
// fractional source coordinates.
ValueT data[2][2][2];

const bool hasActiveValues = BoxSampler::probeValues(data, inTree, Coord(inIdx));

result = BoxSampler::trilinearInterpolation(data, uvw);

return hasActiveValues;
if constexpr (TreeTraits<TreeT>::IsSparse) {
using ValueT = typename TreeT::ValueType;

const Vec3i inIdx = local_util::floorVec3(inCoord);
const Vec3R uvw = inCoord - inIdx;

// Retrieve the values of the eight voxels surrounding the
// fractional source coordinates.
ValueT data[2][2][2];

const bool hasActiveValues = BoxSampler::probeValues(data, inTree, Coord(inIdx));

result = BoxSampler::trilinearInterpolation(data, uvw);

return hasActiveValues;
} else if constexpr (TreeTraits<TreeT>::IsAdaptive) {
// As an example, return the background value.
// This is where the logic that could sample against an adaptive tree would live.
// Extract the tree from the Tree or ValueAccessor
auto& tree = TreeAdapter<TreeT>::tree(inTree);
result = tree.background();
return true;
} else {
static_assert(AlwaysFalseValue<TreeT>, "Not Implemented");
}
std::abort(); // unreachable
}


template<class TreeT>
inline typename TreeT::ValueType
BoxSampler::sample(const TreeT& inTree, const Vec3R& inCoord)
{
using ValueT = typename TreeT::ValueType;
if constexpr (TreeTraits<TreeT>::IsSparse) {

const Vec3i inIdx = local_util::floorVec3(inCoord);
const Vec3R uvw = inCoord - inIdx;
using ValueT = typename TreeT::ValueType;

// Retrieve the values of the eight voxels surrounding the
// fractional source coordinates.
ValueT data[2][2][2];
const Vec3i inIdx = local_util::floorVec3(inCoord);
const Vec3R uvw = inCoord - inIdx;

// Retrieve the values of the eight voxels surrounding the
// fractional source coordinates.
ValueT data[2][2][2];

BoxSampler::getValues(data, inTree, Coord(inIdx));
BoxSampler::getValues(data, inTree, Coord(inIdx));

return BoxSampler::trilinearInterpolation(data, uvw);
return BoxSampler::trilinearInterpolation(data, uvw);
} else if constexpr (TreeTraits<TreeT>::IsAdaptive) {
// As an example, return the background value.
// This is where the logic that could sample against an adaptive tree would live.
// Extract the tree from the Tree or ValueAccessor
auto& tree = TreeAdapter<TreeT>::tree(inTree);
return tree.background();
} else {
static_assert(AlwaysFalseValue<TreeT>, "Not Implemented");
}
std::abort(); // unreachable
}


Expand Down
34 changes: 34 additions & 0 deletions openvdb/openvdb/unittest/TestAdaptive.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,8 @@
// SPDX-License-Identifier: MPL-2.0

#include <openvdb/openvdb.h>
#include <openvdb/tools/Interpolation.h>
#include <openvdb/tools/PointAdvect.h>
#include <openvdb/adaptive/AdaptiveGrid.h>

#include <gtest/gtest.h>
Expand All @@ -23,3 +25,35 @@ TEST_F(TestAdaptive, test)

EXPECT_EQ(adaptiveGrid.background(), 5.0f);
}

TEST_F(TestAdaptive, testSample)
{
const float background = 5.0f;
openvdb::adaptive::AdaptiveGrid<float> adaptiveGrid(background);

float result = openvdb::tools::BoxSampler::sample(adaptiveGrid.tree(), openvdb::Vec3R(1.3, 1.6, 1.8));

EXPECT_EQ(result, background);
}

TEST_F(TestAdaptive, testAdvect)
{
using AdaptiveGridT = openvdb::adaptive::AdaptiveGrid<openvdb::Vec3s>;
using PointAdvectT = openvdb::tools::PointAdvect<AdaptiveGridT>;
using PointListT = PointAdvectT::PointListType;

const openvdb::Vec3s background(0.0f, 1.0f, 0.0f);
AdaptiveGridT adaptiveGrid(background);

openvdb::tools::PointAdvect<AdaptiveGridT> pointAdvect(adaptiveGrid);

PointListT points;
points.push_back(openvdb::Vec3s(0.0f, 0.0f, 0.0f));
points.push_back(openvdb::Vec3s(1.0f, 2.0f, 3.0f));

float dt = 1/24.0f;
pointAdvect.advect(points, dt);

EXPECT_EQ(points[0], openvdb::Vec3s(0.0f, dt, 0.0f));
EXPECT_EQ(points[1], openvdb::Vec3s(1.0f, 2.0f + dt, 3.0f));
}

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