_images/logo.svg

Documentation for 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:

_images/ixdat_example_figures.png

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.

The documentation

Welcome to the ixdat documentation. We hope that you can find what you are looking for here!

The Introduction has a list of the techniques and file types supported so far.

This documentation, like ixdat itself, is a work in progress and we appreciate any feedback or requests here.

Note, we are currently compiling from the [user_ready] branch, not the master branch.

Indices and tables