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ContiguousAccessProcessor Class Reference
Data Processor for efficient, sequential access to N-dimensional data containers. More...
#include <ContiguousAccessProcessor.hpp>
Collaboration diagram for ContiguousAccessProcessor:
Detailed Description
Data Processor for efficient, sequential access to N-dimensional data containers.
ContiguousAccessProcessor is the default processor for streaming, reading, and processing N-dimensional data in a linear, memory-efficient manner. It is designed for digital-first, data-driven workflows and supports:
- Efficient sequential access to multi-dimensional data (audio, images, tensors, etc.)
- Both row-major and column-major memory layouts
- Automatic or manual advancement of read position for streaming or block-based processing
- Looping and region-based access for playback, streaming, or repeated analysis
- Flexible output buffer sizing and dimension selection for custom workflows
This processor is foundational for scenarios such as:
- Real-time audio or signal streaming
- Batch or block-based data processing
- Efficient extraction of contiguous regions for machine learning or DSP
- Integration with digital-first nodes, routines, and buffer systems
Unlike analog-inspired processors, ContiguousAccessProcessor is unconstrained by legacy metaphors and is optimized for modern, data-centric applications.
The documentation for this class was generated from the following file:
