Dioptra v0.4.0

See the README for install lines per platform.

Dioptra v0.3.0

See the README for install lines per platform.

Dioptra v0.2.1

See the README for install lines per platform.

Dioptra v0.2.0

See the README for install lines per platform.

Dioptra 0.1.0

Dioptra 0.1.0 is the first public release: a cross-platform desktop program for scientific data that replaces GraphPad Prism and the spreadsheet before it.

Install: the README has a copy-paste line per platform; the assets below are Linux (AppImage, deb, rpm), Windows (msi, exe) and macOS (Apple silicon and Intel dmg). Builds are unsigned, so Windows and macOS ask once before the first launch.

Website: https://zahakj.github.io/dioptra/ · Manual: https://zahakj.github.io/dioptra/manual/

The first public release.

Data tables

• Eight table kinds: XY, Column, Grouped, Contingency, Survival, Parts of whole, Multiple
  variables and Nested, each explained with a sketch when a table is created.
• Subcolumn formats: replicate values, mean/SD/N, mean/SEM/N, mean/CI/N, mean/SD,
  mean/SEM, median/IQR, lower/upper and single values.
• A virtualised grid that holds a million cells, with the full spreadsheet keyboard set,
  fill down, undo and redo across every action, and a status line with n, mean, SD and sum.
• Text cells kept as text, never coerced; excluded values struck through and kept.
• Cell provenance: typed, pasted (with time), imported (file, sheet, column), formula or
  derived, plus a per-cell edit log.

Getting data in and out

• Paste with automatic separator, decimal-comma and header detection, and a report of what
  was decided; ambiguous values such as 1,234 are kept as text and reported.
• Paste as a new table with a suggested table kind.
• Import of CSV, TSV, text, XLSX, XLS, ODS (built-in reader, stored values at full
  precision) and Prism .pzfx data tables.
• Export of tables to CSV, TSV and XLSX.

Formulas and transforms

• Column formulas and cell formulas with fill-down, a dependency graph, pull-based
  recomputation and circular-reference detection.
• Arithmetic, logic, row functions, summaries, series functions (lag, lead, diff,
  cumsum, rank, zscore, baseline), slices, and unit conversion including
  mass-to-molar conversion for glucose, cholesterol, triglycerides, creatinine and urea.
• Derived tables with stored recipes: transpose, pivot long to wide and wide to long, stack,
  filter, sort, select rows and columns, remove baseline, fraction of total, normalise,
  average replicates and prune.

Command line

• dioptra info, run, import, analyze, render, export, bench and equations drive
  the same engine from scripts and continuous integration.

Analyses

• Twenty analyses: descriptive statistics; t tests (one-sample, Welch, Student, paired,
  ratio paired); Mann–Whitney; Wilcoxon signed-rank; one-way ANOVA with Welch and
  Brown–Forsythe; repeated-measures one-way ANOVA with Greenhouse–Geisser and Huynh–Feldt;
  two-way ANOVA (types I, II, III; one repeated factor); Kruskal–Wallis; Friedman;
  chi-square; Fisher's exact test (2 × 2 and r × c); correlation (Pearson, Spearman,
  Kendall); simple linear regression with bands and diagnostics; nonlinear regression;
  normality tests; outlier identification (Grubbs, ROUT); survival (Kaplan–Meier,
  log-rank, Gehan–Breslow–Wilcoxon, hazard ratios); ROC curves; Bland–Altman; principal
  component analysis.
• Multiple comparisons: Tukey–Kramer, Dunnett, Šidák, Holm, Bonferroni, Dunn and
  Benjamini–Hochberg.
• Nonlinear regression with the equation library (4PL, 5PL, exponential, Michaelis–Menten,
  Hill, binding, Gaussian, polynomials and more), custom equations, weighting, robust
  fitting, constraints, shared parameters, profile-likelihood intervals, model comparison
  by extra sum of squares and AICc, and ROUT.
• Results sheets with assumption checks shown first, APA-style summary sentences, a
  methods sentence, effect sizes with confidence intervals, and a reporting checklist.
• P-value styles APA (default), NEJM, GP and exact, applied project-wide.
• Analyses listed by fit to the table, with the reason for each that does not fit.

Graphs

• Twenty-three families: scatter, line, column, box, violin, strip, raincloud,
  before–after, estimation, SuperPlot, histogram, density, heatmap, correlation matrix,
  Kaplan–Meier with at-risk table, ROC, Bland–Altman, volcano, forest, pie, donut, QQ and
  residual plots; column graphs can be grouped, stacked or percent-stacked.
• An interactive editor: click any element to edit it in the inspector, drag the legend
  and annotations, edit text in place; significance brackets, reference lines and labels.
• Themes Instrument, Night and Journal; palettes Okabe–Ito (default), Tol bright, muted
  and light, viridis, cividis, Tol sunset and grey.
• Sizes in millimetres, type and lines in points, journal presets; multi-panel layouts
  with panel letters.
• Export to SVG (real text), PDF (embedded subset fonts) and PNG at any resolution;
  identical bytes on every platform.

Files and reproducibility

• The .dioptra project file: a zip of documented, pretty-printed JSON with the data,
  formulas, analysis and graph specifications, and the command history.

Correctness and performance

• All 58 NIST StRD data sets used (univariate, linear regression, ANOVA, nonlinear
  regression) pass; 8,327 comparisons against SciPy, statsmodels, lifelines and
  scikit-learn agree within tolerance.
• A million-cell paste in about 0.13 s; a column formula over a million rows in under
  0.11 s.

Platforms

• Linux (AppImage, deb, rpm), Windows (msi, setup exe) and macOS (Apple silicon and Intel
  dmg), built from one codebase.