Utilities API reference

Utilities API reference#

For dataset discovery, remote exploration, and example downloads, see CyteBase API reference.

Store and computation helpers#

cytearc.load_zarr(zarr_loc, mode, storage_options=None, *, source_storage_options=None)#

Open a Zarr group through the compatibility entry point.

Return type:

Group

cytearc.controlled_compute(arr, nthreads)#

Materialize a deferred array with a bounded thread count.

Return type:

ndarray

cytearc.read_gmt(path)#

Read gene sets from a tab-separated GMT file.

The first field is used as the source name, the second description field is ignored, and each remaining non-empty field becomes one target row.

Parameters:

path (str | PathLike[str]) – Path to a GMT file with at least three fields per non-empty line.

Return type:

DataFrame

Returns:

A DataFrame with source and target columns.

Logging and progress#

CyteArc starts with INFO logs and progress enabled, without timestamps. Notebook sessions do not need an output setup call. For a batch pipeline, configure the independent settings once at startup:

cytearc.configure_output(progress=False, timestamps=True)

Arguments that are omitted retain their current values. configure_output is the primary runtime interface:

  • level controls CyteArc’s log severity.

  • progress controls progress bars, including compute_with_progress.

  • timestamps controls timestamps in CyteArc’s installed log sink.

Progress is independent of log level. Setting a quiet level such as WARNING does not disable progress. Call configure_output(progress=False) to suppress progress bars. Interactive notebooks animate these bars. The documentation shows deterministic completed snapshots from the committed notebook cache instead of replaying an animation.

cytearc.configure_output(*, level=None, progress=None, timestamps=None)#

Configure CyteArc’s logging and progress output.

Unspecified settings retain their current values.

Return type:

None

cytearc.set_verbosity(level=None, filepath=None)#

Set CyteArc’s logging level and optional output file.

Return type:

None

set_verbosity(level=..., filepath=...) remains the interface for selecting a log level and optional file destination. Use it when a durable batch log is needed; use configure_output for ordinary notebook and console behavior.

cytearc.logger#

CyteArc’s loguru logger. Library code logs through this object, so cytearc.configure_output() controls the CyteArc-owned sink while preserving sinks added by callers.

cytearc.tqdmbar(*args, **kwargs)#

Create a progress bar using CyteArc’s display defaults.

Return type:

Any

cytearc.tqdm_params#

Default keyword arguments applied by cytearc.tqdmbar(), including bar format, dynamic width, and colour. Override any of them per call.

cytearc.compute_with_progress(arr, msg=None, nthreads=1)#

Materialize a deferred array while reporting progress.

Return type:

ndarray

Array helpers#

These operate on plain arrays and are used by CyteArc’s own embeddings, graph construction, trajectory dynamics, and merge code.

cytearc.clean_array(x, fill_val=0)#

Replace non-finite and zero values in a numeric array.

Return type:

NDArray[Any]

cytearc.rescale_array(a, frac=0.9)#

Trim extreme values using a fitted normal distribution.

Return type:

ndarray

cytearc.rolling_window(a, w)#

Apply a centered rolling mean along the first axis.

Return type:

ndarray

cytearc.permute_into_chunks(size, chunk_size, seed=42)#

Split sequential indices into independently permuted chunks.

Return type:

list[ndarray]