LVAE Tiled Patching

Functions to reimplement the tiling in the Disentangle repository.

`compute_padding(data_shape, tile_size, overlaps)`

Calculate padding to ensure stitched data comes from the center of a tile.

Padding is added to an array with shape data_shape so that when tiles are stitched together, the data used always comes from the center of a tile, even for tiles at the boundaries of the array.

Parameters:

Name	Type	Description	Default
`data_shape`	`1D numpy.array of int`	The shape of the data to be tiled and stitched together, (S, C, (Z), Y, X).	required
`tile_size`	`1D numpy.array of int`	The tile size in each dimension, ((Z), Y, X).	required
`overlaps`	`1D numpy.array of int`	The tile overlap in each dimension, ((Z), Y, X).	required

Returns:

Type	Description
`tuple of (int, int)`	A tuple specifying the padding to add in each dimension, each element is a two element tuple specifying the padding to add before and after the data. This can be used as the `pad_width` argument to `numpy.pad`.

`compute_tile_grid_shape(data_shape, tile_size, overlaps)`

Calculate the number of tiles in each dimension.

This can be thought of as a grid of tiles.

Parameters:

Name	Type	Description	Default
`data_shape`	`1D numpy.array of int`	The shape of the data to be tiled and stitched together, (S, C, (Z), Y, X).	required
`tile_size`	`1D numpy.array of int`	The tile size in each dimension, ((Z), Y, X).	required
`overlaps`	`1D numpy.array of int`	The tile overlap in each dimension, ((Z), Y, X).	required

Returns:

Type	Description
`tuple of int`	The number of tiles in each direction, ((Z, Y, X)).

`compute_tile_info(tile_grid_indices, data_shape, tile_size, overlaps, sample_id=0)`

Compute the tile information for a tile with the coordinates tile_grid_indices.

Parameters:

Name	Type	Description	Default
`tile_grid_indices`	`1D np.array of int`	The coordinates of the tile within the tile grid, ((Z), Y, X), i.e. for 2D tiling the coordinates for the second tile in the first row of tiles would be (0, 1).	required
`data_shape`	`1D np.array of int`	The shape of the data, should be (C, (Z), Y, X) where Z is optional.	required
`tile_size`	`1D np.array of int`	Tile sizes in each dimension, of length 2 or 3.	required
`overlaps`	`1D np.array of int`	Overlap values in each dimension, of length 2 or 3.	required
`sample_id`	`int`	An ID to identify which sample a tile belongs to.	`0`

Returns:

Type	Description
`TileInformation`	Information that describes how to crop and stitch a tile to create a full image.

`compute_tile_info_legacy(grid_index_manager, index)`

Compute the tile information for a tile at a given dataset index.

Parameters:

Name	Type	Description	Default
`grid_index_manager`	`GridIndexManager`	The grid index manager that keeps track of tile locations.	required
`index`	`int`	The dataset index.	required

Returns:

Type	Description
`TileInformation`	Information that describes how to crop and stitch a tile to create a full image.

Raises:

Type	Description
`ValueError`	If `grid_index_manager.data_shape` does not have 4 or 5 dimensions.

`extract_tiles(arr, tile_size, overlaps, padding_kwargs=None)`

Generate tiles from the input array with specified overlap.

The tiles cover the whole array; which will be additionally padded, to ensure that the section of the tile that contributes to the final image comes from the center of the tile.

The method returns a generator that yields tuples of array and tile information, the latter includes whether the tile is the last one, the coordinates of the overlap crop, and the coordinates of the stitched tile.

Input array should have shape SC(Z)YX, while the returned tiles have shape C(Z)YX, where C can be a singleton.

Parameters:

Name	Type	Description	Default
`arr`	`ndarray`	Array of shape (S, C, (Z), Y, X).	required
`tile_size`	`1D numpy.ndarray of tuple`	Tile sizes in each dimension, of length 2 or 3.	required
`overlaps`	`1D numpy.ndarray of tuple`	Overlap values in each dimension, of length 2 or 3.	required
`padding_kwargs`	`dict`	The arguments of `np.pad` after the first two arguments, `array` and `pad_width`. If not specified the default will be `{"mode": "reflect"}`. See `numpy.pad` docs: https://numpy.org/doc/stable/reference/generated/numpy.pad.html.	`None`

Yields:

Type	Description
`Generator[Tuple[ndarray, TileInformation], None, None]`	Tile generator, yields the tile and additional information.

`n_tiles_1d(axis_size, tile_size, overlap)`

Calculate the number of tiles in a specific dimension.

Parameters:

Name	Type	Description	Default
`axis_size`	`int`	The length of the data for in a specific dimension.	required
`tile_size`	`int`	The length of the tiles in a specific dimension.	required
`overlap`	`int`	The tile overlap in a specific dimension.	required

Returns:

Type	Description
`int`	The number of tiles that fit in one dimension given the arguments.

`total_n_tiles(data_shape, tile_size, overlaps)`

Calculate The total number of tiles over all dimensions.

Parameters:

Name	Type	Description	Default
`data_shape`	`1D numpy.array of int`	The shape of the data to be tiled and stitched together, (S, C, (Z), Y, X).	required
`tile_size`	`1D numpy.array of int`	The tile size in each dimension, ((Z), Y, X).	required
`overlaps`	`1D numpy.array of int`	The tile overlap in each dimension, ((Z), Y, X).	required

Returns:

Type	Description
`int`	The total number of tiles over all dimensions.