import numpy as np
import dascore as dc
from dascore.utils.downloader import fetch
file_path = fetch("terra15_das_1_trimmed.hdf5")
patch = dc.read(file_path)read
read(
path: str | pathlib._local.Path | upath.core.UPath | dascore.utils.io.IOResourceManager[str, Path, UPath, IOResourceManager] ,
file_format: str | None[str, None] = None,
file_version: str | None[str, None] = None,
time: tuple[tuple[None | int | float | str | numpy.datetime64 | pandas.Timestamp | ellipsis[None, int, float, str, datetime64, Timestamp, <class ’ellipsis], None | int | float | str | numpy.datetime64 | pandas.Timestamp | ellipsis[None, int, float, str, datetime64, Timestamp, <class ’ellipsis]], None] = None,
distance: tuple[tuple[float | ellipsis | None[float, <class ’ellipsis, None], float | ellipsis | None[float, <class ’ellipsis, None]], None] = None,
**kwargs ,
)-> ‘dc.Spool’
Read a fiber file.
For most cases, dascore.spool is preferable to this function.
Parameters
| Parameter | Description |
|---|---|
| path | A path to the file to read. |
| file_format |
A string indicating the file format. If not provided dascore will try to estimate the format. |
| file_version | An optional string indicating the format version. |
| time | An optional tuple of time ranges. |
| distance | An optional tuple of distances. |
| *kwargs | All kwargs are passed to the format-specific read functions. |
Note
Unlike spool this function reads the entire file into memory.