Miscellaneous tasks#

How to use

These tasks come from ewoksbm32 ewokstxs ewoksxas ewoksxrdct. It can be installed with

pip install ewoksbm32 ewokstxs ewoksxas ewoksxrdct

TxsTask#

txs integration task which saves the results to a HDF5 file

Identifier:
ewokstxs.tasks.txs.TxsTask
Task type:
class
Inputs:
binning*
center*
detector*
distance*
energy*
filename*
output_filename*
scan*
scan_key*
integrate1d_options
pixel
Outputs:
nxdata_url

TxsTaskWithoutSaving#

txs integration task which returns the results

Identifier:
ewokstxs.tasks.txs.TxsTaskWithoutSaving
Task type:
class
Inputs:
binning*
center*
detector*
distance*
energy*
filename*
scan*
scan_key*
integrate1d_options
pixel
Outputs:
intensity
intensity_error
radial
radial_units

LinearCombinationAnalysis#

Task to do linear combination analysis on X-ray absorption spectra.

Identifier:
ewoksxas.tasks.lca.LinearCombinationAnalysis
Task type:
class
Inputs:
Sample_Data* : Orange.data.table.Table
Component_Data* : Orange.data.table.Table
parameters : dict
Outputs:
Transformed_Data : Orange.data.table.Table
Data : Orange.data.table.Table
Components : Orange.data.table.Table

Normalize#

Task to normalize X-ray absorption spectra using Larch.

Identifier:
ewoksxas.tasks.normalize.Normalize
Task type:
class
Inputs:
Data* : Orange.data.table.Table
parameters : dict
Outputs:
Data : Orange.data.table.Table
Groups : list[larch.symboltable.Group]

PeakFitting#

Task to fit one or several peaks of a single shape to each spectrum.

Wraps :class:ewoksxas.fit.peak_fit.PeakModel: every spectrum in the input table is fitted with the configured peak shape and baseline (read from parameters via PeakModel.from_dict), and the fitted model curves are returned with the per-peak descriptors (center, height, area, FWHM and its Gaussian/Lorentzian contributions and the mixing fraction) as metadata.

Each per-peak descriptor base becomes the columns base_0, base_1, … up to the largest peak count fitted across the run, NaN-padded for spectra with fewer peaks; the bare base column aliases the first peak so single-peak consumers keep working. The per-fit quality (r2, rmse) and the integer n_peaks are added once per spectrum. The input table’s metadata (e.g. Scan Name and any acquisition metas) is carried through to the output, with these fit descriptors taking precedence on name collisions.

Identifier:
ewoksxas.tasks.peak_fit.PeakFitting
Task type:
class
Inputs:
Data* : Orange.data.table.Table
parameters : dict
Outputs:
Data : Orange.data.table.Table

ReadScans#

Task to read scan data and metadata from files.

Identifier:
ewoksxas.tasks.read_scans.ReadScans
Task type:
class
Inputs:
Data* : Orange.data.table.Table
x* : str
counters* : list[ewoksxas.tasks.read_scans.CounterInfo]
metadata* : list[ewoksxas.tasks.read_scans.MetadataInfo]
x_interp_grid : list[float] | None= None
Outputs:
Data : Orange.data.table.Table

Xftf#

Task to calculate k-space for X-ray absorption spectra using Larch.

Identifier:
ewoksxas.tasks.xftf.Xftf
Task type:
class
Inputs:
Data* : Orange.data.table.Table
parameters : dict
Outputs:
Data : Orange.data.table.Table
Groups : list[larch.symboltable.Group]

SumTask#

Add two numbers

Identifier:
ewoksxrdct.tasks.sumtask.SumTask
Task type:
class
Inputs:
a*
b
delay
Outputs:
result

SumTask1#

Add two numbers

Identifier:
ewoksxrdct.tasks.sumtask.SumTask1
Task type:
class
Inputs:
a*
b
delay
Outputs:
result

SumTask2#

Add two numbers

Identifier:
ewoksxrdct.tasks.sumtask.SumTask2
Task type:
class
Inputs:
a*
b
delay
Outputs:
result