The in-situ experimental data tool
Project description
ixdat: The In-situ Experimental Data Tool
With ixdat, you can import, combine, and export complex experimental datasets as simply as:
ec = Measurement.read_set("awesome_EC_data", reader="biologic") ec.plot_measurement() ms = Measurement.read("2021-03-30 16_59_35 MS data.tsv", reader="zilien") ms.plot_measurement() ecms = ec + ms ecms.plot_measurement() ecms.export("my_combined_data.csv")
Output:
In-situ experimental data made easy
Or rather than exporting, you can take advantage of ixdat’s powerful analysis tools and database backends to be a one-stop tool from messy raw data to public repository accompanying your breakthrough publication and advancing our field.
Version
This is the latest version.
For changes up to this version, see CHANGES.rst
For ixdat 0.1.9 see the v0.1.x branch.
About
ixdat provides a powerful object-oriented interface to experimental data, especially in-situ experimental data for which it is of interest to combine data obtained simultaneously from multiple techniques.
Documentation is at https://ixdat.readthedocs.io
In addition to a pluggable parser interface for importing your data format, ixdat also includes pluggable exporters and plotters, as well as a database interface. A relational model of experimental data is designed into every level.
Measurement technique |
Status |
Readers |
---|---|---|
Electrochemistry |
Released |
|
Mass Spectrometry |
Released |
|
Electrochemistry - Mass Spectrometry |
Released |
|
Spectroelectrochemistry |
Released |
|
X-ray photoelectron spectroscopy (XPS) |
Development |
|
X-ray diffraction (XRD) |
Development |
|
In-situ Electrochemistry - X-ray adsorption spectroscopy |
Development |
|
Low-Energy Ion Scattering (LEIS) |
Future |
Tutorials are described at https://ixdat.readthedocs.io/en/latest/tutorials.html
Installation
To use ixdat, you need to have python installed. We recommend Anaconda python.
To install ixdat, just type in your terminal or Anaconda prompt:
$ pip install ixdat
And hit enter.
ixdat is under development, and to make use of the newest features, you may need to upgrade to the latest version. This is also easy. Just type:
$ pip install --upgrade ixdat
Article repositories
ixdat is shown in practice in a growing number of open repositories of data and analysis for academic publications:
Soren B. Scott, et al. Tracking oxygen atoms in electrochemical CO oxidation –Part I: Oxygen exchange via CO2 hydration. Electrochimica Acta, 374, 137842, 2021.
Repository: https://github.com/ScottSoren/pyCOox_public
Soren B. Scott, et al. Tracking oxygen atoms in electrochemical CO oxidation –Part II: Lattice oxygen reactivity in oxides of Pt and Ir. Electrochimica Acta, 374, 137844, 2021.
Repository: https://github.com/ScottSoren/pyCOox_public
Kevin Krempl, et al. Dynamic Interfacial Reaction Rates from Electrochemistry - Mass Spectrometry. Journal of Analytical Chemistry. 93, 7022-7028, 2021
Repository: https://github.com/kkrempl/Dynamic-Interfacial-Reaction-Rates
Junheng Huang, et al. Online Electrochemistry−Mass Spectrometry Evaluation of the Acidic Oxygen Evolution Reaction at Supported Catalysts. ACS Catal. 11, 12745-12753, 2021
Repository: https://github.com/ScottSoren/Huang2021
Join us
ixdat is free and open source software and we welcome input and new collaborators. Please help us improve ixdat!
Contact us (https://github.com/ixdat/ixdat/discussions or sbscott@ic.ac.uk) or just get started developing.
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