httomo.runner.dataset.DataSetBlock

class httomo.runner.dataset.DataSetBlock(data: ndarray, aux_data: AuxiliaryData, slicing_dim: Literal[0, 1, 2] = 0, block_start: int = 0, chunk_start: int = 0, global_shape: Tuple[int, int, int] | None = None, chunk_shape: Tuple[int, int, int] | None = None, padding: Tuple[int, int] = (0, 0))

Data storage type for block processing in high throughput runs

Methods

__init__(data, aux_data[, slicing_dim, ...])

Constructs a data block for processing in the pipeline in high throughput runs.

Attributes

chunk_index	The index of this block within the chunk handled by the current process
chunk_index_unpadded	The index of the core area of this block within the chunk (padding removed)
chunk_shape	Shape of the full chunk handled by the current process
chunk_shape_unpadded	Shape of the full chunk core area handled by the current process (with padding removed)
data
data_unpadded	Return the data, but with the padding slices removed
global_index	The index of this block within the global data across all processes
global_index_unpadded	The index of the core area of this block within the global data across all processes (with padding removed)
global_shape	Shape of the global data across all processes
is_last_in_chunk	Check if the current dataset is the final one for the chunk handled by the current process
is_padded	Determine if this is a padded block
padding	Get the 'before' and 'after' padding values for this block.
shape_unpadded	Shape of the core date in this block, with padding removed
slicing_dim	Return the slicing dimenions of the block

property chunk_index: Tuple[int, int, int]

The index of this block within the chunk handled by the current process

property chunk_index_unpadded: Tuple[int, int, int]

The index of the core area of this block within the chunk (padding removed)

property chunk_shape: Tuple[int, int, int]

Shape of the full chunk handled by the current process

property chunk_shape_unpadded: Tuple[int, int, int]

Shape of the full chunk core area handled by the current process (with padding removed)

property data: ndarray | cupy.ndarray

property data_unpadded: ndarray | cupy.ndarray

Return the data, but with the padding slices removed

property global_index: Tuple[int, int, int]

The index of this block within the global data across all processes

property global_index_unpadded: Tuple[int, int, int]

The index of the core area of this block within the global data across all processes (with padding removed)

property global_shape: Tuple[int, int, int]

Shape of the global data across all processes

property is_last_in_chunk: bool

Check if the current dataset is the final one for the chunk handled by the current process

property is_padded: bool

Determine if this is a padded block

property padding: Tuple[int, int]

Get the ‘before’ and ‘after’ padding values for this block. This is to be understood as the the number of padding slices in the ‘slicing_dim’ direction that come before and after the core area of the block. If no padding is used, it returns (0, 0).

property shape_unpadded: Tuple[int, int, int]

Shape of the core date in this block, with padding removed

property slicing_dim: Literal[0, 1, 2]

Return the slicing dimenions of the block