Renishaw#
Reader for spectroscopy data saved using Renishaw’s WiRE software.
Currently, RosettaSciIO can only read the .wdf
format from Renishaw.
If LumiSpy is installed, Luminescence
will be
used as the signal_type
.
Note
There are many different options for the axes according to the format specifications. However, only a limited subset is tested: Spectral (Wavelength and Raman Shift) for the signal axes and X, Y, Z, FocusTrackZ and Time for navigation axes. Reading maps obtained in a serpentine path is not implemented.
This reader is based on the py-wdf-reader, which is inspired by the matlab reader from Alex Henderson. Moreover, inspiration is taken from gwyddion’s reader.
API functions#
- rsciio.renishaw.file_reader(filename, lazy=False, use_uniform_signal_axis=True, load_unmatched_metadata=False)#
Read Renishaw’s
.wdf
file.- Parameters:
- filename
str
,pathlib.Path
Filename of the file to read or corresponding pathlib.Path.
- lazybool, default=False
Whether to open the file lazily or not.
- use_uniform_signal_axisbool, default=False
Can be specified to choose between non-uniform or uniform signal axes. If True, the
scale
attribute is calculated from the average delta along the signal axis and a warning is raised in case the delta varies by more than 1%.- load_unmatched_metadatabool, default=False
Some of the original_metadata cannot be matched (no key, just value). Part of this is a VisualBasic-Script used for data acquisition (~230kB), which blows up the size of
original_metadata
. If this option is set to True, this metadata will be included and can be accessed bys.original_metadata.UNMATCHED
, otherwise theUNMATCHED
tag will not exist.
- filename
- Returns:
list
ofdict
List of dictionaries containing the following fields:
‘data’ – multidimensional
numpy.ndarray
ordask.array.Array
‘axes’ – list of dictionaries describing the axes containing the fields ‘name’, ‘units’, ‘index_in_array’, and either ‘size’, ‘offset’, and ‘scale’ or a numpy array ‘axis’ containing the full axes vector
‘metadata’ – dictionary containing the parsed metadata
‘original_metadata’ – dictionary containing the full metadata tree from the input file