We recently had a question about replacing values below 0 with 0 so I thought I’d write a quick note to demonstrate one way you can do that using iolite’s python functionality.
With Kenneth Ludwig’s Isoplot becoming more and more difficult to use in modern Excel (let alone on a Mac), there is increasing interest in alternatives. One alternative is Pieter Vermeesch’s IsoplotR.
A recent publication by Cogné et al. used a modified iolite 2/3 data reduction scheme to calculate ‘weighted’ U/Ca as part of an apatite fission track dating protocol.
Sometimes we want to examine the relationship between elements (channels) in our datasets to guide us in our data processing. For example, looking for elements whose concentrations correlate strongly can provide us with ideas about what to plot, or whether our data make sense.
Curve fitting plays an import role in iolite’s data reduction pipeline. In order to get accurate results we must have an accurate representation of how our backgrounds and sensitivities are evolving with time.
Using laser logs to help sort out what’s what in your data files is a significant time saver. Now, with iolite 4’s python API (see here and here for more info) you can do even more with your laser data!
iolite comes with many useful python packages, but we cannot anticipate everything our users might want to use python for in iolite. If your great idea depends on additional python packages that we do not include, here is a quick overview of one way you can install those packages.
We recently had an email asking about exporting time series data that had been smoothed by averaging. It turns out this is something very easy to do with iolite 4’s built in python interpreter.