afmformats.formats.fmt_hdf5
¶
Functions¶
load_hdf5()
: Loads HDF5 files as exported by afmformats
- afmformats.formats.fmt_hdf5.load_hdf5(path_or_h5, callback=None, meta_override=None)[source]¶
Loads HDF5 files as exported by afmformats
The HDF5 format is self explanatory. The root attributes contain the version of afmformats used to create it. For each curve, one group is created, named according to “0”, “1”, … “9”, “10”, “11”, etc. The attributes of each group are key-value pairs defined in
afmformats.meta.KEYS_VALID
. The group contains datasets named according toafmformats.afm_data.known_columns
and have the attribute “unit” with the corresponding value inafmformats.afm_data.column_units
.- Parameters
path_or_h5 (str or pathlib.Path or h5py.Group) – path to HDF5 file or an HDF5 group
callback (callable) – function for progress tracking; must accept a float in [0, 1] as an argument.
meta_override (dict) – if specified, contains key-value pairs of metadata that are used when loading the files (see
afmformats.meta.META_FIELDS
)
Notes
In case path_or_h5 is a h5py.Group object, the “path” metadata variable will always be set to the path of the original HDF5 file. Keep this in mind if you think about storing multiple datasets (each containing multiple curves) in one HDF5 file (bad idea).
Classes¶
H5DictReader
: Undocumented.
- class afmformats.formats.fmt_hdf5.H5DictReader(path_or_h5, enum_key)[source]¶
Read-only HDF5-based dictionary for arrays
- Parameters
path_or_h5 (str or pathlib.Path or h5py.Group) – Path to HDF5 file or an HDF5 group
enum_key (str) – Name of the subgroup in path_or_h5 that contains the data of the dictionary
Inheritance