Introduction

Dioptra is a desktop program for the part of science that happens between the instrument and the paper. You paste the numbers your plate reader, cytometer or notebook produced. You shape them: subtract a blank, convert units, normalise to a control. You test them. You draw the figure the journal will print. One file holds all of it.

It does the job GraphPad Prism does, and the job of the spreadsheet most people open before Prism. It runs on Linux, Windows and macOS, it is free, and the source is open under the MIT licence.

The name comes from the dioptra of Hero of Alexandria, a sighting instrument for measuring angles and levels. The aim is the same as a good instrument’s: read the quantity accurately, show the scale, and do not decorate.

What it is built on

Four ideas run through every chapter of this manual.

Raw data is never changed. An analysis reads your table; it never writes to it. A transform makes a new column or a new table and remembers how. Excluding an outlier strikes the value through; it does not delete it. Every cell can tell you where it came from: typed by hand, pasted at a certain time, imported from a file and column, or computed by a formula.

Every assumption is shown. A t test assumes something about your data. So does an ANOVA, a regression, a chi-square test. Dioptra checks what can be checked, shows the check above the result, and names the alternative when a check fails. The defaults follow current statistical practice (Welch’s t test rather than Student’s, two-sided tests, Tukey–Kramer for all pairs, Holm rather than plain Bonferroni) and the results sheet says which one ran.

The file is the record. A .dioptra file is a zip of readable JSON. It holds the data, each formula as text, each analysis as a specification, each graph as a specification, and the history of commands. Open it in a year and every number comes back the same way.

The figure on screen is the figure you export. The plot engine writes one SVG; the PDF and PNG are made from it, with the fonts bundled, so a figure rendered on Linux is byte-identical on a Mac. Sizes are in millimetres and points, because that is how journals specify them.

How this manual is organised

• Getting started takes you from download to an exported figure in about ten minutes.
• Data tables explains the eight table kinds and how to choose one.
• Entering and shaping data covers paste, missing and excluded values, provenance and transforms. Formulas is the formula reference.
• Analyses explains the guided flow, assumption checks and p-value styles, then documents each analysis.
• Graphs explains the editor, themes, palettes and export, then each graph family.
• File format, Correctness and Performance are the record: what is stored, how the numbers were verified, and how fast it runs.
• Architecture and internals is for people who want to change the code.
• The complaint map lists what scientists dislike about the Prism workflow and what Dioptra does about each item.

The statistics are explained where they are used, briefly, with a reason for each default. If a chapter tells you to do something, it should also tell you why.