Analysis you can defend in review.

Log-binned distributions, CCDF tail fits, x_min diagnostics, FSS, and scaling relations (x ∼ yᵅ) are first-class tools, not notebooks to reassemble - and every result carries the exact Python that produced it.

  • Heavy-tail toolkit built in
  • Every result keeps its Python trace
  • Compose boards for paper panels
Download for Mac

Apple silicon · macOS 15 or later · Free plan · Plus free for 30 days

Send to my Mac

Autoplot runs on a Mac. Send the link to yourself, or open it in the Mac App Store.

In the workspace

Named tools, not notebook archaeology

Log-binned distributions, power-law fits, CCDF tail fits from the powerlaw library, x_min selection by KS distance, scaling relations (x ∼ yᵅ), heat maps, and correlation matrices - built in, not assembled by hand from a Python package each time.

Project files preserve variables, cards, workspaces, annotations, and appearance, so a result you found last month reopens exactly as you left it.

Three workflows

From a tail on a log axis to a paper panel

Heavy-tail workflow

Build X&Y and CCDF cards, inspect tails on log axes, add Xmin diagnostics, compare candidate fits, and export the figure - or copy the Python the assistant generated.

Many-variable workflow

Move from selected variables into correlation matrices or heat maps when the problem is inherently 2D or many-variable, without flattening it into one generic chart.

Figure workflow

Use Compose to assemble X&Y, histogram, CCDF, heat-map, scaling-relation, chart, and correlation sources into paper-backed multi-panel boards, exported as a single figure.

FAQ

Questions from people who plot their own data

Can my collaborators reproduce this?

Yes, in two practical ways:

  • The project file reopens the same workspace state in any copy of Autoplot - same variables, cards, fits, and appearance.
  • Or copy the Python and Matplotlib execution trace the assistant generated and hand over an inspectable script, not a black box.
Which analysis surfaces are included?

Free covers the core; Plus opens the advanced surfaces.

  • In the workspace: X&Y, Histogram, Custom Fit, PDF, AUC, CCDF, Xmin, FSS, and scaling relations (x ∼ yᵅ).
  • As specialized tabs: Heat Map with 2D fits and contours, 3D Plot, Correlations, Charts, and Compose.
How do the power-law and heavy-tail fits work?

Transparently. The log-space PDF fit is a least-squares slope on the log-binned distribution - deliberately simple, and stated as such rather than dressed up as a maximum-likelihood estimate. The CCDF tail fit uses the Python powerlaw library, and a separate x_min diagnostic scans candidate cutoffs by Kolmogorov-Smirnov distance.

It is the analysis you would otherwise assemble from the powerlaw package and Matplotlib - here it is a card that stays part of the saved project, with the generated Python available to inspect.

What does the assistant actually see?

Your intent and your dataset's schema - column names, types, and sizes - never the raw values. It proposes a structured operation; nothing mutates the project until you confirm. The operation then runs locally and leaves a Python execution trace, so you can see exactly what produced the result. Data privacy

Which model powers the assistant?

Open-weights models from a curated set, served through a hosted infrastructure provider chosen for your data privacy. The app's model selector shows what is currently available. It is a narrow analysis assistant gated behind your confirmation, not a frontier chatbot you paste data into.

Coming from Igor Pro?

WaveMetrics' Igor Pro 10 is Windows-only. Igor Pro 9.05 is the last Mac release, and on Apple silicon it runs only through Rosetta.

Autoplot is honestly not at feature parity - Igor's macro language and waveform model have no like-for-like replacement here. What it is: a native Mac scientific workstation built around modern fitting, plotting, reproducibility, and a conversational assistant Igor does not have. CSV and text imports work today; .ibw and .pxp import remain roadmap items.

Is it really native, or a web app in a window?

Native SwiftUI for Apple Silicon, with document-based projects that open and save like any Mac file. Numerical work runs through a persistent in-app Python engine - NumPy, SciPy, Matplotlib, and the surrounding local toolkit - so the stack underneath is the one you already trust.

Do I need Plus?

Most working scientists will.

  • Free: X&Y, histograms with fits, PDF / log-binned / power-law analysis, save and load, and PNG and JPEG export.
  • Plus: CCDF, Xmin diagnostics, FSS, scaling relations (x ∼ yᵅ), heat maps with 2D fits, 3D plots, correlation matrices, charts, Compose, and vector PDF export.
  • Pro: only for heavier assistant volume.

Ready when you are

Download the Mac build and start with the first honest changelog.

Download for Mac

Apple silicon · macOS 15 or later · Free plan · Plus free for 30 days

Send to my Mac

Autoplot runs on a Mac. Send the link to yourself, or open it in the Mac App Store.