est.core package

est.core.io module

simple helper function to link io module and XASObject

class est.core.io.XASReader

Bases: object

Simple reader of a xas file

read_frm_url(spectra_url, channel_url, config_url=None)
read_from_file(file_path)
Parameters

file_path (str) –

Returns

.XASObject

class est.core.io.XASWriter

Bases: object

class to write the output file. In this case we need a class in order to setup the output file before

dump_xas(xas_obj, write_process=True)

write the XASObject into a hdf5 file.

Parameters

  • xas_obj – object to be stored

  • write_process (bool) – if True then store the process flow in the same file.

Type

Union[XASObject,dict]

property output_file
setProperties(properties)
est.core.io.read(spectra_url, channel_url, config_url=None)
Parameters

  • spectra_url (DataUrl) – data url to the spectra

  • channel_url (DataUrl) – data url to the channel / energy

  • config_url (DataUrl) – data url to the process configuration

Returns

Return type

XASObject

est.core.io.read_frm_file(file_path)
Parameters

file_path (str) – path to the file containing the spectra. Must ba a .dat file that pymca can handle or a .h5py with default path

Return type

XASObject

est.core.reprocessing module

some utils function for executing reprocessing

est.core.reprocessing.get_process_instance_frm_h5_desc(desc)
Parameters

desc (dict) – description of the process to instanciate

Returns

instance of the process to execute, configured from the description

est.core.types module

class est.core.types.Sample(name='undefined sample', description=None)

Bases: object

Description of the sample. Needed for writing valid nx file

class est.core.types.Spectra

Bases: object

class est.core.types.Spectrum(energy=None, mu=None)

Bases: larch.symboltable.Group

Core object to be used to store larch and pymca results.

Larch is using ‘Group’ to store the result and add menbers to this group according to the different treatment. Pymca is using a dictionary to store the result.

This class as to adpat to the both behavior and the different naming convention as well.

Parameters

  • (1D) energy (numpy.ndarray) – beam energy

  • (1D) mu (numpy.ndarray) – beam absorption

property chi
copy()
property e0
property energy
extra_keys()
static from_dict(ddict)
property ft
get_missing_keys(keys)

Return missing keys on the spectrum

property k
keys()
load_frm_dict(ddict)
property mu
property norm
property normalized_energy
property normalized_mu
property post_edge
property pre_edge
property shape
to_dict()
update(obj)

Update the contained values from the given obj.

Parameters

obj (Union[XASObject, dict]) –

class est.core.types.XASObject(spectra=None, energy=None, configuration=None, dim1=None, dim2=None, name='scan1', keep_process_flow=True)

Bases: object

Base class of XAS

Parameters

  • spectra – absorbed beam as a list of Spectrum or a numpy.ndarray

  • energy – beam energy

  • configuration (dict) – configuration of the different process

  • dim1 (int) – first dimension of the spectra

  • dim2 (int) – second dimension of the spectra

  • name (str) – name of the object. Will be used for the hdf5 entry

  • keep_process_flow (bool) – if True then will keep the trace of the set of process applied to the XASObject into a hdf5 file.

Type

Union[numpy.ndarray, list]

Type

numpy.ndarray of one dimension

absorbed_beam()
addSpectrum(spectrum)
clean_process_flow()

Remove existing process flow

property configuration
copy(create_h5_file=False)
Parameters

create_h5_file (bool) – True if we want to duplicate the h5 file This is the case for orange widget for example where some reprocessing can append and each process need to keep a clear history of processes, whith no knowledge of next processing.

copy_process_flow_to(h5_file_target)

copy all the recognized process from self.__h5_file to h5_file_target

Parameters

h5_file_target (str) – path to the targeted file. Should be an existing hdf5 file.

property dim1
property dim2
dump(h5_file)

dump the XAS object to a file_path within the Nexus format

property energy
property entry
forceDim1(value)
forceDim2(value)
static from_dict(ddict)
static from_file(h5_file, entry='scan1', spectra_path='data/absorbed_beam', energy_path='data/energy', configuration_path='configuration')
getSpectrum(dim1_idx, dim2_idx)

Util function to access the spectrum at dim1_idx, dim2_idx

get_next_processing_index()
get_process_flow()
Returns

the dict of process information

Return type

dict

has_linked_file()

Associate a .h5 file to the XASObject. This can be used for storing process flow.

Parameters

h5_file –

Returns

property linked_h5_file
load_frm_dict(ddict)

load XAS values from a dict

property n_spectrum

return the number of spectra

register_processing(process, data)

Register one process for the current xas object. This require to having link a h5file to this object

Parameters

  • process – process to be registred

  • data – result of the processing. If there is more than one result then a dictionary with the key under which result should be saved and a numpy.ndarray

Type

Process

Type

Union[numpy.ndarray,dict]

property spectra
static spectra_equal(spectra1, spectra2)
spectra_keys()

keys contained by the spectrum object (energy, mu, normalizedmu…)

to_dict(with_process_details=True)

convert the XAS object to a dict

By default made to simply import raw data.

Parameters

with_process_details – used to embed a list of spectrum with intermediary result instead of only raw mu. This is needed especially for the pushworkflow actors to keep a trace of the processes.

Type

bool