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/* SPDX-License-Identifier: GPL-2.0-or-later */
#pragma once
/** \file
* \ingroup bli
*
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
* A`GVectorArray` is a container for a fixed amount of dynamically growing vectors with a generic
* data type. Its main use case is to store many small vectors with few separate allocations. Using
* this structure is generally more efficient than allocating each vector separately.
*/
#include "BLI_array.hh"
#include "BLI_generic_virtual_vector_array.hh"
#include "BLI_linear_allocator.hh"
namespace blender {
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
/* An array of vectors containing elements of a generic type. */
class GVectorArray : NonCopyable, NonMovable {
private:
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
struct Item {
void *start = nullptr;
int64_t length = 0;
int64_t capacity = 0;
};
/* Use a linear allocator to pack many small vectors together. Currently, memory from reallocated
* vectors is not reused. This can be improved in the future. */
LinearAllocator<> allocator_;
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
/* The data type of individual elements. */
const CPPType &type_;
/* The size of an individual element. This is inlined from `type_.size()` for easier access. */
const int64_t element_size_;
/* The individual vectors. */
Array<Item> items_;
public:
GVectorArray() = delete;
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
GVectorArray(const CPPType &type, int64_t array_size);
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
~GVectorArray();
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
int64_t size() const
{
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
return items_.size();
}
bool is_empty() const
{
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
return items_.is_empty();
}
const CPPType &type() const
{
return type_;
}
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
void append(int64_t index, const void *value);
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
/* Add multiple elements to a single vector. */
void extend(int64_t index, const GVArray &values);
void extend(int64_t index, GSpan values);
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
/* Add multiple elements to multiple vectors. */
void extend(IndexMask mask, const GVVectorArray &values);
void extend(IndexMask mask, const GVectorArray &values);
void clear(IndexMask mask);
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
GMutableSpan operator[](int64_t index);
GSpan operator[](int64_t index) const;
private:
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
void realloc_to_at_least(Item &item, int64_t min_capacity);
};
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
/* A non-owning typed mutable reference to an `GVectorArray`. It simplifies access when the type of
* the data is known at compile time. */
template<typename T> class GVectorArray_TypedMutableRef {
private:
GVectorArray *vector_array_;
public:
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
GVectorArray_TypedMutableRef(GVectorArray &vector_array) : vector_array_(&vector_array)
{
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
BLI_assert(vector_array_->type().is<T>());
}
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
int64_t size() const
{
return vector_array_->size();
}
bool is_empty() const
{
return vector_array_->is_empty();
}
void append(const int64_t index, const T &value)
{
vector_array_->append(index, &value);
}
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
void extend(const int64_t index, const Span<T> values)
{
vector_array_->extend(index, values);
}
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
void extend(const int64_t index, const VArray<T> &values)
{
Geometry Nodes: refactor virtual array system 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
2021-11-16 10:15:51 +01:00
vector_array_->extend(index, values);
}
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
MutableSpan<T> operator[](const int64_t index)
{
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
return (*vector_array_)[index].typed<T>();
}
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
};
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
/* A generic virtual vector array implementation for a `GVectorArray`. */
class GVVectorArray_For_GVectorArray : public GVVectorArray {
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
private:
const GVectorArray &vector_array_;
public:
GVVectorArray_For_GVectorArray(const GVectorArray &vector_array)
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
: GVVectorArray(vector_array.type(), vector_array.size()), vector_array_(vector_array)
{
}
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
protected:
int64_t get_vector_size_impl(const int64_t index) const override
{
Functions: refactor virtual array data structures When a function is executed for many elements (e.g. per point) it is often the case that some parameters are different for every element and other parameters are the same (there are some more less common cases). To simplify writing such functions one can use a "virtual array". This is a data structure that has a value for every index, but might not be stored as an actual array internally. Instead, it might be just a single value or is computed on the fly. There are various tradeoffs involved when using this data structure which are mentioned in `BLI_virtual_array.hh`. It is called "virtual", because it uses inheritance and virtual methods. Furthermore, there is a new virtual vector array data structure, which is an array of vectors. Both these types have corresponding generic variants, which can be used when the data type is not known at compile time. This is typically the case when building a somewhat generic execution system. The function system used these virtual data structures before, but now they are more versatile. I've done this refactor in preparation for the attribute processor and other features of geometry nodes. I moved the typed virtual arrays to blenlib, so that they can be used independent of the function system. One open question for me is whether all the generic data structures (and `CPPType`) should be moved to blenlib as well. They are well isolated and don't really contain any business logic. That can be done later if necessary.
2021-03-21 19:31:24 +01:00
return vector_array_[index].size();
}
void get_vector_element_impl(const int64_t index,
const int64_t index_in_vector,
void *r_value) const override
{
type_->copy_assign(vector_array_[index][index_in_vector], r_value);
}
};
} // namespace blender