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Sakura [1] is a data explorer for data generated at the XAS beamline at the Australian Synchrotron.

  • Reads step mode and mapping mode data.
  • Exports columnar ASCII.
  • Cross-platform. Runs on Windows/Mac OSX/Linux
  • Released under the Modified BSD-license
Sakura screenshot

Sakura screenshot.

Contents

Usage

This page describes the usage of Sakura.

On startup

When started, Sakura presents the following empty interface with red overlays identifying the following parts of the user interface:

Sakura GUI areas (Opening view)

Sakura (Windows version) on startup identifying parts of the user interface: 1. Toolbar, 2. File list, 3. Edge list.

  1. Toolbar.

    From left-to-right, the toolbar buttons allow you to 1a) Open a scan dataset, 1b) Export reduced data as ASCII, 1c) Unload all loaded datasets, 1d) Exit the program.

    1a) Open a scan dataset.

    Sakura allows processing of step-mode and mapping-mode datasets. In the case of step-mode data, all data is stored in an individual .mda file. In the case of mapping-mode data, a .mda file contains experiment metadata process variables (PVs), whereas the raw spectral data is stored in accompanying netCDF files. In both cases, the data is loaded by opening the appropriate .mda file in the open file dialog.

    1b) Export reduced data as ASCII.

    When clicked, any processed data in any checked datasets in the File list box are written to ASCII files with the same name as the .mda file, but with a .asc filename extension.

    1c) Unload all loaded datasets.

    All data is unloaded. Equivalent to exiting and restarting Sakura.

    1d) Exit the program.

    Quits Sakura. The same as trying to close the main window.

  2. File list

    Currently loaded files appear here alongside a checkbox that is used to choose datasets for export.

    Step-mode and mapping-mode datasets cannot be simulataneously loaded.

  3. Edge list

    Candidate edges are listed here. Selecting one ???

On file load

Once a file is loaded, the following display areas become active:

Sakura GUI areas 2

Sakura screen areas activated by file load: 4. Average Absorption Edge Spectrum and ??? plots, 5. Absorption Edge Spectrum [mu(E)*d mode], 6. 100-element detector selection widget, 7. 100-element detector selection widget/statistics map, 8. Numerical statistics report.

  1. Average Absorption Edge Spectrum and ??? plots

    Blah ???

  2. Absorption Edge Spectrum [mu(E)*d mode]

    ???

  3. 100-element detector selection widget

  4. 100-element detector selection widget/statistics map

  5. Numerical statistics report

Switching Absorption Edge Spectrum display mode

  1. Absorption Edge Spectrum [Chi(k) mode]
Sakura GUI areas 3

The reciprocal Absorption Edge Spectrum display is accessed via the Chi(k) tab.

Mapping mode dataset spectrum view

  1. Multichannel analyser plot with ROI selection
Sakura GUI areas 4

For netCDF-based mapping-mode datasets, clicking the Spectrum tab in the upper display accesses the MCA spectrum display.

  • The Spectrum display allows the ROI limits to be set.
  • To lock the Spectrum display to show a particular detector element, left-click the mouse on the detector element of interest. The element number changes to Bold Yellow. Repeat this action to unlock the element.
  • After setting the ROI limits using the ROI setters, clicking the Reprocess button will recompute the Absorption edge displays.

TBC

Processing

This page describes the processing that Sakura performs.

TBD

Installation

For MS Windows users, a standalone installer is available from the main site. Download and install this to run Sakura.

Linux and Mac users or Windows users wishing to install from source must install `Python 2.7.x<http://python.org>`_ and the packages listed below. Sakura is written in Python (2.7 at the time of writing). The easiest way to satisfy the Python module dependencies is to install one of the Enthought Canopy Distributions. The older Enthought EPDFree distribution (also available from the main site) also contains all the modules on which Sakura depends. A typical user can just install one of these, then download and unpack the Sakura source code and run the sakura.py file.

Some users might prefer alternatives to EPDFree or Canopy. Other popular Python distributions are Python(x,y) and ActiveState’s ActivePython, both of which will require installation of at least some of the following dependencies:

Python package dependencies

Sakura depends on the following Python modules being installed in the Python environment

Those wishing to build the documentation from source will also need Sphinx. For those familiar with installing Python packages, the dependencies can be found in the central repository of Python modules. For Microsoft Windows users, Christoph Gohlke (C.G.) maintains a useful repository of Windows installers containing the required packages. Linux users can typically find the dependencies using their package manager (e.g. synaptic or yum). Mac users should visit the individual sites linked above for instructions. In all cases, be careful to choose the package versions complied for Python 2.7.x and choose either the 32bit or 64bit package versions to match the version of Python you installed.

Example 2. Windows installation using Python(x,y) (optional)

  1. Visit the Python(x,y) downloads page and install a distribution.
  2. Verify that Python is running correctly (see Example 1. Windows installation using Enthought EPDFree (recommended)).
  3. Visit the Sakura download page and follow the instructions to obtain the Sakura setup file.
  4. Download the Sakura source code bundle and uncompress it.
  5. Double-click sakura.py to run Sakura.

Example 4. Linux installation using synaptic (experienced)

Note: untested.

This description is for Ubuntu Linux. yum packaged names in Fedora Linux flavours should have similar names.

  1. First, verify that Python2.7 is running correctly. e.g. for Ubuntu, open a terminal. At the $ prompt type python -c "import sys; print sys.version". Verify that a string displays identifying a 2.7 branch version of Python.
  2. Using synaptic or apt-get install <package> install the following packages: python-numpy, python-scipy, python-wxgtk2.8
  3. Visit the Sakura download page and follow the instructions to obtain the package.
  4. The main application file is sakura.py in the directory into which Sakura was unpacked.
  5. Start Sakura by running python ./sakura.py.

About Sakura

Please send bug reports and suggestions to sakura _at_ synchrotron.org.au

Software authors:
Peter Kappen peter _dot_ kappen _at_ synchrotron.org.au, Australian Synchrotron
Gary Ruben gary _dot_ ruben _at_ synchrotron.org.au, Victorian eResearch Strategic Initiative (VeRSI)

Software home:
Software source:
Gary Ruben acknowledges funding for Sakura development from NeCTAR.
Recognition of NeCTAR funding:
The Australian Synchrotron is proud to be in partnership with the National eResearch Collaboration Tools and Resources (NeCTAR) project to develop eResearch Tools for the synchrotron research community. This will enable our scientific users to have instant access to the results of data during the course of their experiment which will facilitate better decision making and also provide the opportunity for ongoing data analysis via remote access.

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