ewoksfluo.xrffit.buffers.pymca.PyMcaOutputBuffer#
- class ewoksfluo.xrffit.buffers.pymca.PyMcaOutputBuffer(output_root_uri, diagnostics=False, figuresofmerit=False, **open_options)[source]#
Bases:
OutputBuffer
This is the output buffer of PyMca with an internal output handler.
- Parameters:
output_root_uri (
str
)diagnostics (
bool
)figuresofmerit (
bool
)
- Context(save=True, update=False)#
Either saveContext or bufferContext. By default update=False: try overwriting (exception when not allowed)
- allocateMemory(label, group=None, memtype='ram', **kwargs)#
- Parameters:
label (str)
group (str) – group name of this dataset (in hdf5 this is the nxdata name)
memtype (str) – ram or hdf5
**kwargs –
see _allocateRam or _allocateHdf5
- property already_existed: bool#
- bufferContext(update=True)#
Prepare output buffers (HDF5: create file, NXentry and NXprocess)
- Parameters:
update (bool) – True: update existing NXprocess False: overwrite or raise an exception
- Raises:
RuntimeError – NXprocess exists and overwrite==False
- property cfg#
- clear() None. Remove all items from D. #
- property csv#
- property dat#
- property diagnostics#
- property edf#
- property extensions#
- property fileEntry#
- property fileProcess#
- filename(ext, suffix=None)#
- filenames(ext)#
- flush()#
- get(k[, d]) D[k] if k in D, else d. d defaults to None. #
- hasAllocatedMemory()#
- items() a set-like object providing a view on D's items #
- keys() a set-like object providing a view on D's keys #
- labelFormat(group, prefix)#
For single-page edf/tif file names
- labels(group, labeltype=None)#
- Parameters:
group (str)
labeltype (str) – ‘hdf5’: dataset names used in h5 ‘filename’: file names ‘title’: titles used in edf/dat/csv/tif else: join with space-separator
- Returns list:
strings or tuples
- markDefault(group)#
- property nosave#
- property outputDirLegacy#
- property outputRoot#
- property overwrite#
- pop(k[, d]) v, remove specified key and return the corresponding value. #
If key is not found, d is returned if given, otherwise KeyError is raised.
- popitem() (k, v), remove and return some (key, value) pair #
as a 2-tuple; but raise KeyError if D is empty.
- save()#
Save result of XRF batch fitting. Preferrable use saveContext instead. HDF5 NXprocess will be updated, not overwritten.
- saveContext(**kw)[source]#
Same as bufferContext but with save when leaving the context. By default update=False: try overwriting (exception when not allowed)
- property saveData#
- property saveDataDiagnostics#
- property saveFOM#
- property saveFit#
- property saveResiduals#
- setdefault(k[, d]) D.get(k,d), also set D[k]=d if k not in D #
- property tif#
- update([E, ]**F) None. Update D from mapping/iterable E and F. #
If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
- values() an object providing a view on D's values #
- property xrf_results_uri: str | None#