Goals of this refactor: * Simplify creating virtual arrays. * Simplify passing virtual arrays around. * Simplify converting between typed and generic virtual arrays. * Reduce memory allocations. As a quick reminder, a virtual arrays is a data structure that behaves like an array (i.e. it can be accessed using an index). However, it may not actually be stored as array internally. The two most important implementations of virtual arrays are those that correspond to an actual plain array and those that have the same value for every index. However, many more implementations exist for various reasons (interfacing with legacy attributes, unified iterator over all points in multiple splines, ...). With this refactor the core types (`VArray`, `GVArray`, `VMutableArray` and `GVMutableArray`) can be used like "normal values". They typically live on the stack. Before, they were usually inside a `std::unique_ptr`. This makes passing them around much easier. Creation of new virtual arrays is also much simpler now due to some constructors. Memory allocations are reduced by making use of small object optimization inside the core types. Previously, `VArray` was a class with virtual methods that had to be overridden to change the behavior of a the virtual array. Now,`VArray` has a fixed size and has no virtual methods. Instead it contains a `VArrayImpl` that is similar to the old `VArray`. `VArrayImpl` should rarely ever be used directly, unless a new virtual array implementation is added. To support the small object optimization for many `VArrayImpl` classes, a new `blender::Any` type is added. It is similar to `std::any` with two additional features. It has an adjustable inline buffer size and alignment. The inline buffer size of `std::any` can't be relied on and is usually too small for our use case here. Furthermore, `blender::Any` can store additional user-defined type information without increasing the stack size. Differential Revision: https://developer.blender.org/D12986
564 lines
17 KiB
C++
564 lines
17 KiB
C++
/*
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* This program is free software; you can redistribute it and/or
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* modify it under the terms of the GNU General Public License
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* as published by the Free Software Foundation; either version 2
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* of the License, or (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software Foundation,
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* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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*/
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#include "BLI_array.hh"
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#include "BLI_span.hh"
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#include "BLI_task.hh"
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#include "BLI_timeit.hh"
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#include "BKE_attribute_access.hh"
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#include "BKE_attribute_math.hh"
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#include "BKE_spline.hh"
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#include "FN_generic_virtual_array.hh"
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using blender::Array;
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using blender::float3;
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using blender::IndexRange;
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using blender::MutableSpan;
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using blender::Span;
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using blender::VArray;
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using blender::attribute_math::convert_to_static_type;
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using blender::bke::AttributeIDRef;
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using blender::fn::GMutableSpan;
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using blender::fn::GSpan;
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using blender::fn::GVArray;
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Spline::Type Spline::type() const
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{
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return type_;
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}
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void Spline::copy_base_settings(const Spline &src, Spline &dst)
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{
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dst.normal_mode = src.normal_mode;
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dst.is_cyclic_ = src.is_cyclic_;
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}
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static SplinePtr create_spline(const Spline::Type type)
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{
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switch (type) {
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case Spline::Type::Poly:
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return std::make_unique<PolySpline>();
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case Spline::Type::Bezier:
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return std::make_unique<BezierSpline>();
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case Spline::Type::NURBS:
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return std::make_unique<NURBSpline>();
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}
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BLI_assert_unreachable();
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return {};
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}
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/**
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* Return a new spline with the same data, settings, and attributes.
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*/
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SplinePtr Spline::copy() const
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{
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SplinePtr dst = this->copy_without_attributes();
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dst->attributes = this->attributes;
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return dst;
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}
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/**
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* Return a new spline with the same type and settings like "cyclic", but without any data.
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*/
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SplinePtr Spline::copy_only_settings() const
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{
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SplinePtr dst = create_spline(type_);
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this->copy_base_settings(*this, *dst);
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this->copy_settings(*dst);
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return dst;
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}
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/**
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* The same as #copy, but skips copying dynamic attributes to the new spline.
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*/
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SplinePtr Spline::copy_without_attributes() const
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{
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SplinePtr dst = this->copy_only_settings();
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this->copy_data(*dst);
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/* Though the attributes storage is empty, it still needs to know the correct size. */
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dst->attributes.reallocate(dst->size());
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return dst;
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}
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void Spline::translate(const blender::float3 &translation)
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{
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for (float3 &position : this->positions()) {
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position += translation;
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}
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this->mark_cache_invalid();
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}
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void Spline::transform(const blender::float4x4 &matrix)
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{
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for (float3 &position : this->positions()) {
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position = matrix * position;
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}
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this->mark_cache_invalid();
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}
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void Spline::reverse()
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{
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this->positions().reverse();
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this->radii().reverse();
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this->tilts().reverse();
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this->attributes.foreach_attribute(
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[&](const AttributeIDRef &id, const AttributeMetaData &meta_data) {
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std::optional<blender::fn::GMutableSpan> attribute = this->attributes.get_for_write(id);
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if (!attribute) {
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BLI_assert_unreachable();
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return false;
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}
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convert_to_static_type(meta_data.data_type, [&](auto dummy) {
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using T = decltype(dummy);
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attribute->typed<T>().reverse();
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});
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return true;
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},
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ATTR_DOMAIN_POINT);
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this->reverse_impl();
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this->mark_cache_invalid();
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}
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int Spline::evaluated_edges_size() const
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{
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const int eval_size = this->evaluated_points_size();
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if (eval_size < 2) {
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/* Two points are required for an edge. */
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return 0;
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}
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return this->is_cyclic_ ? eval_size : eval_size - 1;
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}
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float Spline::length() const
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{
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Span<float> lengths = this->evaluated_lengths();
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return lengths.is_empty() ? 0.0f : this->evaluated_lengths().last();
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}
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int Spline::segments_size() const
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{
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const int size = this->size();
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return is_cyclic_ ? size : size - 1;
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}
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bool Spline::is_cyclic() const
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{
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return is_cyclic_;
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}
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void Spline::set_cyclic(const bool value)
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{
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is_cyclic_ = value;
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}
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static void accumulate_lengths(Span<float3> positions,
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const bool is_cyclic,
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MutableSpan<float> lengths)
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{
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float length = 0.0f;
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for (const int i : IndexRange(positions.size() - 1)) {
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length += float3::distance(positions[i], positions[i + 1]);
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lengths[i] = length;
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}
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if (is_cyclic) {
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lengths.last() = length + float3::distance(positions.last(), positions.first());
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}
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}
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/**
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* Return non-owning access to the cache of accumulated lengths along the spline. Each item is the
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* length of the subsequent segment, i.e. the first value is the length of the first segment rather
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* than 0. This calculation is rather trivial, and only depends on the evaluated positions.
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* However, the results are used often, and it is necessarily single threaded, so it is cached.
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*/
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Span<float> Spline::evaluated_lengths() const
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{
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if (!length_cache_dirty_) {
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return evaluated_lengths_cache_;
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}
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std::lock_guard lock{length_cache_mutex_};
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if (!length_cache_dirty_) {
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return evaluated_lengths_cache_;
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}
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const int total = evaluated_edges_size();
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evaluated_lengths_cache_.resize(total);
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if (total != 0) {
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Span<float3> positions = this->evaluated_positions();
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accumulate_lengths(positions, is_cyclic_, evaluated_lengths_cache_);
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}
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length_cache_dirty_ = false;
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return evaluated_lengths_cache_;
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}
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static float3 direction_bisect(const float3 &prev, const float3 &middle, const float3 &next)
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{
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const float3 dir_prev = (middle - prev).normalized();
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const float3 dir_next = (next - middle).normalized();
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const float3 result = (dir_prev + dir_next).normalized();
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if (UNLIKELY(result.is_zero())) {
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return float3(0.0f, 0.0f, 1.0f);
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}
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return result;
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}
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static void calculate_tangents(Span<float3> positions,
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const bool is_cyclic,
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MutableSpan<float3> tangents)
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{
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if (positions.size() == 1) {
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tangents.first() = float3(0.0f, 0.0f, 1.0f);
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return;
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}
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for (const int i : IndexRange(1, positions.size() - 2)) {
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tangents[i] = direction_bisect(positions[i - 1], positions[i], positions[i + 1]);
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}
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if (is_cyclic) {
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const float3 &second_to_last = positions[positions.size() - 2];
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const float3 &last = positions.last();
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const float3 &first = positions.first();
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const float3 &second = positions[1];
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tangents.first() = direction_bisect(last, first, second);
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tangents.last() = direction_bisect(second_to_last, last, first);
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}
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else {
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tangents.first() = (positions[1] - positions[0]).normalized();
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tangents.last() = (positions.last() - positions[positions.size() - 2]).normalized();
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}
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}
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/**
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* Return non-owning access to the direction of the curve at each evaluated point.
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*/
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Span<float3> Spline::evaluated_tangents() const
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{
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if (!tangent_cache_dirty_) {
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return evaluated_tangents_cache_;
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}
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std::lock_guard lock{tangent_cache_mutex_};
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if (!tangent_cache_dirty_) {
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return evaluated_tangents_cache_;
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}
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const int eval_size = this->evaluated_points_size();
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evaluated_tangents_cache_.resize(eval_size);
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Span<float3> positions = this->evaluated_positions();
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calculate_tangents(positions, is_cyclic_, evaluated_tangents_cache_);
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this->correct_end_tangents();
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tangent_cache_dirty_ = false;
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return evaluated_tangents_cache_;
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}
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static float3 rotate_direction_around_axis(const float3 &direction,
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const float3 &axis,
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const float angle)
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{
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BLI_ASSERT_UNIT_V3(direction);
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BLI_ASSERT_UNIT_V3(axis);
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const float3 axis_scaled = axis * float3::dot(direction, axis);
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const float3 diff = direction - axis_scaled;
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const float3 cross = float3::cross(axis, diff);
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return axis_scaled + diff * std::cos(angle) + cross * std::sin(angle);
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}
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static void calculate_normals_z_up(Span<float3> tangents, MutableSpan<float3> r_normals)
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{
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BLI_assert(r_normals.size() == tangents.size());
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/* Same as in `vec_to_quat`. */
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const float epsilon = 1e-4f;
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for (const int i : r_normals.index_range()) {
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const float3 &tangent = tangents[i];
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if (fabsf(tangent.x) + fabsf(tangent.y) < epsilon) {
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r_normals[i] = {1.0f, 0.0f, 0.0f};
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}
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else {
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r_normals[i] = float3(tangent.y, -tangent.x, 0.0f).normalized();
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}
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}
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}
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/**
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* Rotate the last normal in the same way the tangent has been rotated.
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*/
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static float3 calculate_next_normal(const float3 &last_normal,
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const float3 &last_tangent,
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const float3 ¤t_tangent)
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{
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if (last_tangent.is_zero() || current_tangent.is_zero()) {
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return last_normal;
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}
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const float angle = angle_normalized_v3v3(last_tangent, current_tangent);
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if (angle != 0.0) {
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const float3 axis = float3::cross(last_tangent, current_tangent).normalized();
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return rotate_direction_around_axis(last_normal, axis, angle);
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}
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return last_normal;
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}
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static void calculate_normals_minimum(Span<float3> tangents,
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const bool cyclic,
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MutableSpan<float3> r_normals)
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{
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BLI_assert(r_normals.size() == tangents.size());
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if (r_normals.is_empty()) {
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return;
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}
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const float epsilon = 1e-4f;
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/* Set initial normal. */
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const float3 &first_tangent = tangents[0];
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if (fabs(first_tangent.x) + fabs(first_tangent.y) < epsilon) {
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r_normals[0] = {1.0f, 0.0f, 0.0f};
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}
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else {
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r_normals[0] = float3(first_tangent.y, -first_tangent.x, 0.0f).normalized();
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}
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/* Forward normal with minimum twist along the entire spline. */
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for (const int i : IndexRange(1, r_normals.size() - 1)) {
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r_normals[i] = calculate_next_normal(r_normals[i - 1], tangents[i - 1], tangents[i]);
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}
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if (!cyclic) {
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return;
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}
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/* Compute how much the first normal deviates from the normal that has been forwarded along the
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* entire cyclic spline. */
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const float3 uncorrected_last_normal = calculate_next_normal(
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r_normals.last(), tangents.last(), tangents[0]);
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float correction_angle = angle_signed_on_axis_v3v3_v3(
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r_normals[0], uncorrected_last_normal, tangents[0]);
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if (correction_angle > M_PI) {
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correction_angle = correction_angle - 2 * M_PI;
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}
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/* Gradually apply correction by rotating all normals slightly. */
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const float angle_step = correction_angle / r_normals.size();
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for (const int i : r_normals.index_range()) {
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const float angle = angle_step * i;
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r_normals[i] = rotate_direction_around_axis(r_normals[i], tangents[i], angle);
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}
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}
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/**
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* Return non-owning access to the direction vectors perpendicular to the tangents at every
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* evaluated point. The method used to generate the normal vectors depends on Spline.normal_mode.
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*/
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Span<float3> Spline::evaluated_normals() const
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{
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if (!normal_cache_dirty_) {
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return evaluated_normals_cache_;
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}
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std::lock_guard lock{normal_cache_mutex_};
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if (!normal_cache_dirty_) {
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return evaluated_normals_cache_;
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}
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const int eval_size = this->evaluated_points_size();
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evaluated_normals_cache_.resize(eval_size);
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Span<float3> tangents = this->evaluated_tangents();
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MutableSpan<float3> normals = evaluated_normals_cache_;
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/* Only Z up normals are supported at the moment. */
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switch (this->normal_mode) {
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case ZUp: {
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calculate_normals_z_up(tangents, normals);
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break;
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}
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case Minimum: {
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calculate_normals_minimum(tangents, is_cyclic_, normals);
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break;
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}
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case Tangent: {
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/* Tangent mode is not yet supported. */
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calculate_normals_z_up(tangents, normals);
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break;
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}
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}
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/* Rotate the generated normals with the interpolated tilt data. */
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VArray<float> tilts = this->interpolate_to_evaluated(this->tilts());
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for (const int i : normals.index_range()) {
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normals[i] = rotate_direction_around_axis(normals[i], tangents[i], tilts[i]);
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}
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normal_cache_dirty_ = false;
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return evaluated_normals_cache_;
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}
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Spline::LookupResult Spline::lookup_evaluated_factor(const float factor) const
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{
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return this->lookup_evaluated_length(this->length() * factor);
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}
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/**
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* \note This does not support extrapolation currently.
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*/
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Spline::LookupResult Spline::lookup_evaluated_length(const float length) const
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{
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BLI_assert(length >= 0.0f && length <= this->length());
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Span<float> lengths = this->evaluated_lengths();
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const float *offset = std::lower_bound(lengths.begin(), lengths.end(), length);
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const int index = offset - lengths.begin();
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const int next_index = (index == this->evaluated_points_size() - 1) ? 0 : index + 1;
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const float previous_length = (index == 0) ? 0.0f : lengths[index - 1];
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const float factor = (length - previous_length) / (lengths[index] - previous_length);
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return LookupResult{index, next_index, factor};
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}
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/**
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* Return an array of evenly spaced samples along the length of the spline. The samples are indices
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* and factors to the next index encoded in floats. The logic for converting from the float values
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* to interpolation data is in #lookup_data_from_index_factor.
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*/
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Array<float> Spline::sample_uniform_index_factors(const int samples_size) const
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{
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const Span<float> lengths = this->evaluated_lengths();
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BLI_assert(samples_size > 0);
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Array<float> samples(samples_size);
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samples[0] = 0.0f;
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if (samples_size == 1) {
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return samples;
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}
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const float total_length = this->length();
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const float sample_length = total_length / (samples_size - (is_cyclic_ ? 0 : 1));
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/* Store the length at the previous evaluated point in a variable so it can
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* start out at zero (the lengths array doesn't contain 0 for the first point). */
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float prev_length = 0.0f;
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int i_sample = 1;
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for (const int i_evaluated : IndexRange(this->evaluated_edges_size())) {
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const float length = lengths[i_evaluated];
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/* Add every sample that fits in this evaluated edge. */
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while ((sample_length * i_sample) < length && i_sample < samples_size) {
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const float factor = (sample_length * i_sample - prev_length) / (length - prev_length);
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samples[i_sample] = i_evaluated + factor;
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i_sample++;
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}
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prev_length = length;
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}
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/* Zero lengths or float inaccuracies can cause invalid values, or simply
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* skip some, so set the values that weren't completed in the main loop. */
|
|
for (const int i : IndexRange(i_sample, samples_size - i_sample)) {
|
|
samples[i] = float(samples_size);
|
|
}
|
|
|
|
if (!is_cyclic_) {
|
|
/* In rare cases this can prevent overflow of the stored index. */
|
|
samples.last() = lengths.size();
|
|
}
|
|
|
|
return samples;
|
|
}
|
|
|
|
Spline::LookupResult Spline::lookup_data_from_index_factor(const float index_factor) const
|
|
{
|
|
const int eval_size = this->evaluated_points_size();
|
|
|
|
if (is_cyclic_) {
|
|
if (index_factor < eval_size) {
|
|
const int index = std::floor(index_factor);
|
|
const int next_index = (index < eval_size - 1) ? index + 1 : 0;
|
|
return LookupResult{index, next_index, index_factor - index};
|
|
}
|
|
return LookupResult{eval_size - 1, 0, 1.0f};
|
|
}
|
|
|
|
if (index_factor < eval_size - 1) {
|
|
const int index = std::floor(index_factor);
|
|
const int next_index = index + 1;
|
|
return LookupResult{index, next_index, index_factor - index};
|
|
}
|
|
return LookupResult{eval_size - 2, eval_size - 1, 1.0f};
|
|
}
|
|
|
|
void Spline::bounds_min_max(float3 &min, float3 &max, const bool use_evaluated) const
|
|
{
|
|
Span<float3> positions = use_evaluated ? this->evaluated_positions() : this->positions();
|
|
for (const float3 &position : positions) {
|
|
minmax_v3v3_v3(min, max, position);
|
|
}
|
|
}
|
|
|
|
GVArray Spline::interpolate_to_evaluated(GSpan data) const
|
|
{
|
|
return this->interpolate_to_evaluated(GVArray::ForSpan(data));
|
|
}
|
|
|
|
/**
|
|
* Sample any input data with a value for each evaluated point (already interpolated to evaluated
|
|
* points) to arbitrary parameters in between the evaluated points. The interpolation is quite
|
|
* simple, but this handles the cyclic and end point special cases.
|
|
*/
|
|
void Spline::sample_with_index_factors(const GVArray &src,
|
|
Span<float> index_factors,
|
|
GMutableSpan dst) const
|
|
{
|
|
BLI_assert(src.size() == this->evaluated_points_size());
|
|
|
|
blender::attribute_math::convert_to_static_type(src.type(), [&](auto dummy) {
|
|
using T = decltype(dummy);
|
|
const VArray<T> src_typed = src.typed<T>();
|
|
MutableSpan<T> dst_typed = dst.typed<T>();
|
|
if (src.size() == 1) {
|
|
dst_typed.fill(src_typed[0]);
|
|
return;
|
|
}
|
|
blender::threading::parallel_for(dst_typed.index_range(), 1024, [&](IndexRange range) {
|
|
for (const int i : range) {
|
|
const LookupResult interp = this->lookup_data_from_index_factor(index_factors[i]);
|
|
dst_typed[i] = blender::attribute_math::mix2(interp.factor,
|
|
src_typed[interp.evaluated_index],
|
|
src_typed[interp.next_evaluated_index]);
|
|
}
|
|
});
|
|
});
|
|
}
|