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porestore.image

Local NumPy arrays and their persistent remote image records.

Image

A local array, a remote image, or both. Properties never fetch data implicitly.

array = array instance-attribute

client property

id property

status property

metadata property

metrics: Solution property

Already-returned image metrics as a table; refresh metadata explicitly.

Reading this property never starts a job, downloads an array, or fetches metadata. Values and units are exactly those returned by the API.

from_numpy(array, **kwargs) classmethod

from_id(image_id, *, client=None) classmethod

Recover metadata for an existing image, without downloading its array.

upload(*, client=None) -> Image

Serialize a local array as NPY, upload directly, and start ingestion.

Returns this Image immediately after registration; call wait_until_ready explicitly before submitting calculations. Repeated uploads of the same Image reuse its existing remote record. Construct a new Image to upload edits.

refresh() -> Image

wait_until_ready(*, timeout: float = 300.0, poll_interval: float = 2.0) -> Image

download(*, refresh: bool = False) -> np.ndarray

Download the stored sample as NumPy; retain an in-memory copy until refresh=True.

This retrieves the current ingested image, which may differ from the original upload. Zarr decompression runs in the notebook process.

upload(data: np.ndarray | str | PathLike, *, name: str | None = None, description: str = '', voxel_size: float | None = None, client=None, wait: bool = False, timeout: float = 300.0, poll_interval: float = 2.0, raw_metadata: dict | None = None) -> Image

Upload a NumPy array or local file and return its remote Image.

Uses the configured connection unless client is supplied. Arrays are sent as NPY; the API selects a file decoder from the filename's extension. RAW files also need raw_metadata containing their dimensions and dtype. voxel_size is in micrometres. With wait=True, wait for ingestion to finish before returning; by default, return immediately after registration.