parseq 0.8.0

ParSeq is a python software library for Parallel execution of Sequential data analysis.

Package ParSeq is a python software library for Parallel execution of Sequential data analysis. It implements a general analysis framework with an adjustable data model (supports grouping, renaming, moving and drag-and-drop), plotters for 1D, 2D and 3D data, cross-data analysis routines and flexible widget work space suitable for single- and multi-screen computers. It also gives a structure to implement particular analysis pipelines as relatively lightweight Python packages.

ParSeq is intended for synchrotron based techniques, first of all spectroscopy.

A screenshot of a scanning XES analysis pipeline as an application example:

Main features

• ParSeq allows creating analysis pipelines as lightweight modules. The above example (scanning XES) is ~1000 lines with ~50% of them defining the four analysis widgets.

• Flexible use of screen area by detachable/dockable transformation nodes (parts of analysis pipeline).

• Two ways of acting from GUI onto multiple data: (a) simultaneous work with multiply selected data and (b) applying a specific parameter or a group of parameters to a later selected subset of data.

• Undo and redo for most of treatment steps.

• Entering into the analysis pipeline at any node, not only at the head of the pipeline.

• Creation of cross-data combinations (e.g. averaging, RMS or PCA) and their propagation downstream the pipeline together with the parental data. The possibility of termination of the parental data at any selected downstream node.

• Parallel execution of data analysis with multiprocessing or multithreading (can be opted by the piplene application).

• Export of the workflow into a project file. Export of data into various data formats (so far unstructured) with accompanied Python scripts that visualize the exported data for the user to tune their publication plots.

• ParSeq understands container files (presently only hdf5) and adds them to the system file tree as subfolders. The file tree, including hdf5 containers, is lazy loaded thus enabling big data collections.

• A web viewer widget near each analysis widget for displaying help pages built from doc strings. The help pages are built by Sphinx at the startup time.

ParSeq creates a data analysis pipeline consisting of nodes and transformations that connect the nodes. The pipeline is fed with data (spectra or images), possibly entering the pipeline at various nodes. The pipeline can be operated via scripts or GUI. The mechanisms for creating nodes and transformations, connecting them together and creating Qt widgets for the transformations are exemplified by separately installed analysis packages:

• ParSeq-XES-scan

• ParSeq-XES-dispersive

Dependencies

• silx – used for plotting and Qt imports.

• sphinx – for building html documentation.

Launch an example

Either install ParSeq and a ParSeq pipeline application by their installers to the standard location or put them to any folder, rename them to their package names (parseq and e.g. parseq_XES_scan) and start the *_start.py file of the pipeline. You can try it with --test to load test data and/or --noGUI to run the pipeline fully in the terminal and plot only the end results but an assumed pattern is to load a project .pspj file from GUI.

Hosting and contact

The ParSeq project is hosted on GitHub. Please use the project’s Issues tab to get help or report an issue.