MayaFlux 0.2.0
Digital-First Multimedia Processing Framework
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◆ IO() [4/7]

template<ComputeData T = std::vector<Kakshya::DataVariant>>
MayaFlux::Yantra::IO< T >::IO ( T &&  d)
inline

Construct from data by move with automatic structure inference.

Parameters
dData to move into the container

Automatically infers dimensions and modality before moving the data. More efficient for large data structures.

Definition at line 75 of file DataIO.hpp.

76 : data(std::move(d))
77 {
78 // Note: We infer from data after it's moved, which should be fine
79 // since inference typically only needs type info and basic properties
80 auto [dims, mod] = infer_structure(data);
81 dimensions = std::move(dims);
82 modality = mod;
83 }
static std::pair< std::vector< Kakshya::DataDimension >, Kakshya::DataModality > infer_structure(const T &data, const std::shared_ptr< Kakshya::SignalSourceContainer > &container=nullptr)
Infer dimensions and modality from any ComputeData type.
T data
The actual computation data.
Definition DataIO.hpp:25
std::vector< Kakshya::DataDimension > dimensions
Data dimensional structure.
Definition DataIO.hpp:26
Kakshya::DataModality modality
Data modality (audio, image, spectral, etc.)
Definition DataIO.hpp:27