FAQ

Does it run on Linux?

Yes, as a first-class platform: it is developed on Linux. Each release has an AppImage (any distribution), a .deb (Debian, Ubuntu, Mint) and an .rpm (Fedora, RHEL, openSUSE). See Getting started.

What does it cost?

Nothing. Dioptra is free and open source under the MIT licence. There is no account, no licence server, no trial period and no tier. Every analysis, effect size and export format is in the one version there is.

Can I use it at work, in a company, or in a clinical setting?

The MIT licence allows any use, commercial included, without asking. It also comes with no warranty, as all open-source licences do. For regulated work, validate it as you would any software: the correctness record and the test suite are there to make that easier.

Can I import my Excel files?

Yes. File → Import reads .xlsx, .xls and .ods directly, with no Office installation, the same way on every system. It reads the stored values at full precision, not the rounded values the sheet displays. Dates become ISO dates. You can also paste straight from Excel; then the clipboard carries what is displayed, so show enough decimals first.

Can I open my Prism files?

Prism’s XML format, .pzfx, and the Prism 10 format, .prism, can be imported: the data tables come across. Prism’s analyses and graphs are not converted; re-run the analyses in Dioptra. The old binary .pzf format is not read; if you have only that, open it in Prism and save it as .pzfx or .prism. Dioptra does not write Prism formats; it exports CSV, TSV and XLSX for anyone who needs the data elsewhere.

Where are my data? Does anything leave my computer?

Your data live in the .dioptra files you save, wherever you save them, and nowhere else. Dioptra makes no network connections: no telemetry, no analytics, no update check, no cloud. It works with the network cable unplugged.

How do I know an old analysis will give the same result next year?

The project file stores the data, every formula as text, every analysis as a specification, every graph as a specification, and the version of Dioptra that wrote it. Opening it recomputes everything from the data. The file format is versioned and newer versions read older files. And because the file is documented JSON, the data and the recipe can be read without Dioptra at all, by unzip and a text editor. See File format.

Why is Welch’s t test the default instead of Student’s?

Student’s t test assumes the two groups have the same variance. When they do, Welch’s test gives nearly the same answer. When they do not, especially with unequal group sizes, Student’s test can give a p value that is far too small or far too large. Welch costs almost nothing when the assumption holds and protects you when it does not. Student’s test is one option away. The longer argument is in Analyses.

Can I run a one-tailed test?

Yes; every test with a direction has the option. It is not the default because a one-tailed test is valid only when the direction was decided before the data were collected and an effect in the other direction would be treated as no effect. When you choose it, the methods sentence says so, so a reader knows.

Why are there no asterisks on my graphs?

Because the default p-value style is APA: brackets show p = .012, not *. Asterisks reduce a continuous measure of evidence to a grade, and readers stop at the grade. If your journal or lab needs them, set the project’s p-value style to GP (inspector, Project, P values); every sheet and bracket switches at once, and switching back costs nothing.

How large a data set can it handle?

A table of a million cells pastes in about 0.13 seconds and scrolls without lag, because the grid fetches only the cells on screen. A column formula over a million rows computes in under a tenth of a second. Graphs with more than 20,000 points are thinned for drawing (one point per 0.75 pt cell, invisible at print size) but never for analysis. The measurements are in Performance.

Are the statistics right?

They are checked against the strongest references available: the NIST Statistical Reference Datasets, whose answers are certified to 15 digits, and the established implementations in SciPy, statsmodels, lifelines and scikit-learn. All 58 NIST data sets pass, and 7,841 comparisons in 300 oracle cases agree within their stated tolerances. The whole record, including the places where a reference library turned out to be the less accurate one, is in Correctness. If you find a disagreement, please open a numerical discrepancy issue with the data and the reference value.

What is missing compared with Prism?

Mixed-effects models, three-way ANOVA, two-way ANOVA with repeated measures on both factors, multiple logistic and Cox regression, and a few smaller analyses. They are listed, with the reason each waits, in the roadmap.

How do I cite Dioptra?

The repository has a CITATION.cff file; GitHub’s Cite this repository button turns it into APA or BibTeX. Cite the version you used (it is in every methods sentence), for example:

ZahakJ. Dioptra: data, statistics and publication graphs without the spreadsheet (version 0.4.0) [Computer software]. 2026. https://github.com/ZahakJ/dioptra

How can I help?

Report bugs and numerical discrepancies as issues, with a small file that shows the problem. Contributions are welcome; read CONTRIBUTING.md in the repository first, because numerical code has rules: a named reference and a test against a known value for every change.