from dascore.io.dasdae.core import DASDAEV1
from dascore.utils.downloader import fetch
path = fetch("example_dasdae_event_1.h5")
array = DASDAEV1().read_array(path, {"time": (0, 50)})
array.shape(601, 50)
| method of dascore.io.core.FiberIO | source |
read_array(
self ,
resource ,
windows: dict[str, tuple[int, int]] ,
**kwargs ,
)-> ‘np.ndarray’
Return the raw data array for absolute sample windows.
A data-only fast path for callers which already know a resource’s structure (from an index) and need no Patch, attrs, or coordinates back. This default reads the whole resource through read and trims — a Patch is still built internally, just not returned — so every format is correct without overriding; formats override it to slice storage directly and skip the Patch work.
| Parameter | Description |
|---|---|
| resource |
The resource to read, as read takes it.
|
| windows |
Maps dimension name to (start, stop) half-open pythonindices on the resource’s own sample grid. Dimensions absent from the mapping are returned whole. |
| **kwargs |
Reader-specific options. Multi-patch resources takesource_patch_key (as read and scan spell it)naming the one patch the windows index; without it an ambiguous resource raises rather than guesses. |
The array in the resource’s stated dimension order (the order scan reports), untransposed and uncast.