aicsimageio.readers.sldy_reader package

Submodules

aicsimageio.readers.sldy_reader.sldy_image module

class aicsimageio.readers.sldy_reader.sldy_image.SldyImage(fs: AbstractFileSystem, image_directory: Path, data_file_prefix: str, channel_file_prefix: str = '_Ch', timepoint_file_prefix: str = '_TP')[source]

Bases: object

Representation of a single acquisition in a 3i slidebook (SLDY) image.

Parameters

fs (AbstractFileSystem) – The file system to used for reading.
image_directory (types.PathLike) – Path to the image directory this is meant to represent.
data_file_prefix (str, default = “ImageData”) – Prefix to the data files within this image directory to extract.

get_data(timepoint: Optional[int], channel: Optional[int], delayed: bool) → ndarray[source]

Returns the image data for the given timepoint and channel if specified. If delayed, the data will be lazily read in.

Parameters

timepoint (Optional[int]) – Optional timepoint to get data about.
channel (Optional[int]) – Optional channel to get data about.
delayed (bool) – If True, the data will be lazily read in.

Returns

data – Numpy representation of the image data found.

Return type

np.ndarray

property metadata: Dict[str, Optional[dict]]

Returns a dictionary representing the metadata of this acquisition.

Returns: metadata – Simple mapping of metadata file names to the metadata extracted from them. Possibly different than the actual yaml due to mapping the yaml to Python dictionaries, specifically with duplicate keys.
Return type: Dict[str, dict]

Module contents

class aicsimageio.readers.sldy_reader.SldyReader(image: Union[str, Path], fs_kwargs: Dict[str, Any] = {}, data_file_prefix: str = 'ImageData', **kwargs: Any)[source]

Bases: Reader

Read 3i slidebook (SLDY) images

Parameters

image (Path or str) – path to file
fs_kwargs (Dict[str, Any]) – Any specific keyword arguments to pass down to the fsspec created filesystem. Default: {}
data_file_prefix (str, default = “ImageData”) – Prefix to the data files within the image directories to extract. By default this will be set to “ImageData”. However, specifying “HistogramData” would allow you to interact with the image’s histogram data instead.

Raises

exceptions.UnsupportedFileFormatError – If the file is not supported by this reader.

property physical_pixel_sizes: PhysicalPixelSizes

Returns: sizes – Using available metadata, the floats representing physical pixel sizes for dimensions Z, Y, and X.
Return type: PhysicalPixelSizes

Notes

We currently do not handle unit attachment to these values. Please see the file metadata for unit information.

property scenes: Tuple[str, ...]

Returns: scenes – A tuple of valid scene ids in the file.
Return type: Tuple[str, …]

Notes

Scene IDs are strings - not a range of integers.

When iterating over scenes please use:

>>> for id in image.scenes

and not:

>>> for i in range(len(image.scenes))