WITio: A MATLAB data evaluation toolbox to script broader insights into big data from WITec microscopes
WITio is intended for the users of WITec microscopes, who work with WITec Project/Data (*.wip/*.wid) files (v0–v7) and wish to enrich their data evaluation by customized automation scripts within MATLAB environment. Thanks to its fast bidirectional read/write capabilities, WITio bridges the best of both WITec software and MATLAB software. The toolbox is a great script-based automation platform for big data analysis and post-processing, which reduces a lot of slow error-prone manual work. This includes file batch processing, easily accessible customized tools and more systematic data evaluation. When combined with the WITec software's Autosaving feature, they can together even achieve powerful real-time during-measurement task automation for industrial applications. To summarize, WITio aims to constantly open up new research and commercial possibilities to the WITec community by jointly keeping up with the ever-increasing big data for broader insights.
WITio (or formerly wit_io for v1 or wip_reader for v0) project began in 2016 as a by-product of on-going MATLAB data evaluation of large Raman spectroscopic datasets obtained by a confocal Raman microscope, WITec alpha300 RA. The initial purpose was to reduce time spent at manual data exporting from WITec software, and benefit from MATLAB's many libraries, scripting language and improved suitability to big data evaluation. However, its original scope grew much larger after it was completely rewritten by object-oriented programming and gained ability to import data back to WITec software. During its development (up to v2.0.1) author has worked for prof. Harri Lipsanen's group in Department of Electronics and Nanoengineering, Aalto University, Finland.
This is published under free and permissive BSD 3-Clause License. Only exceptions to this license can be found in the third party-folder.
Download the toolbox installer and double-click it to install it.
Download the latest production zip archive
and extract it. For the first time, run MATLAB as administrator, go to the
extracted folder and execute WITio in Command Window to permanently add
the toolbox folder to the MATLAB path.
Run MATLAB as administrator and execute WITio.tbx.wip_wid_context_menus
to add the WITio option to the *.wip and *.wid file right-click context
menus to enable a quick external call to [O_wid, O_wip, O_wit] = WITio.read(file, '-ifall');.
Execute WITio.demo in Command Window to list all available demo cases and
left-mouse click to run WITio.demo.A1_import_file_to_get_started and so on.
Consider using semi-automated batch scripts under batch-package on your WITec Project/Data files. They will read the given file, interact with the user, process the relevant file contents and finally write back to the original file.
Transition from v1.4.0.1 to v2.0.0 involved major and minor breaking changes, all described in CHANGELOG.md. It is highly recommended to go through all renewed demo cases and inspect WITio.tbx.backward_compatible.m as well. Pass on any questions to jtholmi@gmail.com
- Requires MATLAB on Windows, macOS and Linux operating systems.
- Compatible with MATLAB R2011a (or newer), but in the future may be limited MATLAB R2014b to ensure improved OOP performance.
WITio can also read and write arbitrary WIT-tag formatted files
by O_wit = WITio.obj.wit.read(file); and O_wit.write();, respectively. They
can then be viewed interactively by executing O_wit in Command Window. Any WIT-tag
tree content can also be modified using S_DT = WITio.obj.wit.DataTree_get(O_wit);
and WITio.obj.wit.DataTree_set(O_wit, S_DT);.
See detailed information at README on WIT-tag format.txt,
which reveals the general file format and its *.wip and *.wid special cases
with their special wip Project and wid Data object tree structures.
You can begin contributing by reporting bugs and requesting features at the Issues page. You are also most welcome to share some idea or code that has potential to add value to everyone using the toolbox. For example, maybe some of your scripts could be transformed into a new demo or a new batch case.
Each contribution should aim to continually improve the capacity of WITio to script even broader insights into ever-growing big data from WITec microscopes. In fact, the main goal is to jointly impact the world by constantly creating new research and commercial opportunities for the WITec community.
J. T. Holmi (2019). WITio: A MATLAB toolbox for WITec Project/Data (*.wip/*.wid) files (https://gitlab.com/jtholmi/wit_io), GitLab. Version <x.y.z>. Retrieved <Month> <Day>, <Year>.
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[*] Academic supervisor of jtholmi:
Prof. Harri Lipsanen, Aalto University,
Finland
[1] clever_statistics_and_outliers.m:
G. Buzzi-Ferraris and F. Manenti (2011) "Outlier detection in large data sets"
[2] myinpolygon.m: J. Hao et al. (2018)
"Optimal Reliable Point-in-Polygon Test and Differential Coding Boolean Operations on Polygons"
[3] Unpublished predecessor wip_reader and apply_MRLCM.m
(pp. 27–28,35): J. T. Holmi (2016) "Determining the number of graphene layers by Raman-based Si-peak analysis"