punchbowl.data.io#

Attributes#

Functions#

`write_file_hash`(→ None)	Create a SHA-256 hash for a file.
`get_base_file_name`(→ str)	Determine the base file name without file type extension.
`write_ndcube_to_jp2`(→ None)	Write an NDCube as a JPEG2000 file.
`write_ndcube_to_fits`(→ None)	Write an NDCube as a FITS file.
`_pack_uncertainty`(→ numpy.ndarray)	Compress the uncertainty for writing to file.
`_unpack_uncertainty`(→ numpy.ndarray)	Uncompress the uncertainty when reading from a file.
`_update_statistics`(→ None)	Update image statistics in metadata before writing to file.
`load_ndcube_from_fits`(→ ndcube.NDCube)	Load an NDCube from a FITS file.

Module Contents#

punchbowl.data.io._ROOT = b'.'#

punchbowl.data.io.write_file_hash(path: str) → None#: Create a SHA-256 hash for a file.

punchbowl.data.io.get_base_file_name(cube: ndcube.NDCube) → str#: Determine the base file name without file type extension.

punchbowl.data.io.write_ndcube_to_jp2(cube: ndcube.NDCube, filename: str, layer: int | None = None, vmin: float = 1e-15, vmax: float = 8e-13) → None#: Write an NDCube as a JPEG2000 file.

punchbowl.data.io.write_ndcube_to_fits(cube: ndcube.NDCube, filename: str, overwrite: bool = True, write_hash: bool = True, skip_stats: bool = False, uncertainty_quantize_level: float = 16) → None#: Write an NDCube as a FITS file.

punchbowl.data.io._pack_uncertainty(cube: ndcube.NDCube) → numpy.ndarray#: Compress the uncertainty for writing to file.

punchbowl.data.io._unpack_uncertainty(uncertainty_array: numpy.ndarray, data_array: numpy.ndarray) → numpy.ndarray#: Uncompress the uncertainty when reading from a file.

punchbowl.data.io._update_statistics(cube: ndcube.NDCube) → None#: Update image statistics in metadata before writing to file.

punchbowl.data.io.load_ndcube_from_fits(path: str | pathlib.Path, key: str = ' ', include_provenance: bool = True) → ndcube.NDCube#: Load an NDCube from a FITS file.