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News About Lisp-Stat

Getting Started

An easy way to start with Lisp-Stat

It’s never been easy for a developer to get started in Common Lisp. Emacs, though a powerful editor, isn’t considered an IDE by modern standards. Setting up a compiler, quicklisp, slime, swank, and then learning an entirely new programming paradigm has scared off many would-be entrants to the Common Lisp community.

Given the size of the Common Lisp community this is understandable. Making the new user experience smooth and frictionless as possible is hard work. It’s the kind of work that no one volunteers for; it’s the kind of work you have to be paid for.

Still, it’s a pre-requisite for new users, so I’ve created ls-dev-image, a ‘batteries included’ OCI image for Lisp-Stat or just plain Common Lisp development. Assuming you have an OCI (e.g Docker) runtime installed. Here’s how to get started.

Shell

docker run --rm -it --user vscode -w /home/vscode ghcr.io/lisp-stat/ls-dev:latest bash

Now you’re in the container with a bash shell and can configure the machine as you like.

Common Lisp REPL

If you want a Common Lisp REPL:

docker run --rm -it --user vscode -w /home/vscode ghcr.io/lisp-stat/ls-dev:latest ls-repl

and you should see:

Linedit version 0.17.6, smart mode, ESC-h for help.
CL-USER(1):

You could also have gotten here from the shell with the sbcl command. This is a bare common lisp image, with nothing loaded. Now you load lisp-stat from the Quicklisp repositories with:

(ql:quickload :lisp-stat)
... lot's of compilation output ...
[package ls-user]
(:LISP-STAT)
CL-USER(2):

and to start working with Lisp-Stat:

(in-package :ls-user

This REPL has been configured with a few packages to make it easier to work with.

  • linedit, provides customizable line-editing. You can use emacs key bindings to edit the REPL commands.
  • Acl-repl is a SBCL extension that gives you command history (via up/down arrows) and some short command codes such as :cs for compile-system, :ts for test-system, etc.

Generally you won’t be doing development with the REPL, you’ll be doing it in emacs.

Emacs/Slime

Now you can use Common Lisp with emacs, quicklisp and slime. From the shell you can type ’emacs’ followed by ‘M-x slime’ and start hacking Common Lisp.

image

Lisp-Stat

The upstream repositories are often out of date. To get the latest and to keep them synced you can use the init.sh script with ls-init.sh --mode experimenter. Experimenter will download the repos so you can try out the source code, but you won’t be able to push your changes or make pull requests. For that you want to be a ‘contributor’: ls-init.sh --mode contributor.

Now when you start ls-repl you should see the lisp-stat REPL prompt, indicating you’re in the LS-USER package:

ls-init.sh --mode experimenter
# ... output from repo checkouts, linking, configuration

ls-repl

lot’s of recompilation because you’re now using local source repos and then:

...
To load "ls-server":
  Load 1 ASDF system:
    ls-server
; Loading "ls-server"
.....

Linedit version 0.17.6, smart mode, ESC-h for help.
LS-USER(1):

From here emacs and M-x slime (from the shell) will load Lisp-Stat.

LS-Server

A ls-server is also configured to start automatically on port 20202. If you open your browser and point it to https://localhost:20202 (or other port, depending on your OCI container configuration) you’ll see the web interface for displaying plots and viewing/editing data-frames.

image

You can also run this OCI image in GitHub codespaces.

Staying up-to-date

You will want to run docker pull occasionally to get the latest ls-dev-image. This should stabilize in a month or so and after that it won’t need to be updated frequently. To keep lisp-stat source in sync, run ls-init.sh --refresh. If you want help with ls-init.sh, run ls-init.sh --help.

Contributions and bug reports are welcome and encouraged.

2023 End of Year Summary

Year end wrap-up

We started the year by working through the examples from the first chapter of the Introduction to the Practice of Statistics. Whilst this is an excellent test for Lisp-Stat, Chapter 2 presented some major challanges to the plotting system, so the highlight for this year is Plot 2.0. This is a breaking change, however the fix for plots is relatively simple.

The updates for 2023 include:

Introduction to the Practice of Statistics

The first chapter from The Introduction to the Practice of Statistics completed

The examples from the first chapter of the book are now completed. This chapter focuses mostly on graphics, and the examples here supplement those in the plotting examples.

Statistical Analysis with Lisp-Stat

Version 1.0-beta
By Steve Nunez |

Lisp-Stat is the culmination of many months work to pull together the best-in-class statistical analysis packages available in Common Lisp, under a commercially friendly license, usable ‘out of the box’. It is an environment for statistical computing, conceptually similar to R, that is also suitable for front-line production deployments. It grew out of a desire to have an environment for rapidly prototyping analytical and A.I. solutions, and move directly to production environments with minimal friction. Typically there is a gap between the modeling environment, perhaps R or Python, and the delivery environment. Lisp-Stat closes that gap.

Lisp-Stat is in daily use for statistical analysis and is now considered ready for a broader audience.

Why Lisp?

We had a few requirements when evaluating options. Specifically the system had to:

  • Work well in the kind of exploratory environment conducive to analytics and AI
  • Be robust enough to be deployed in an enterprise-level production environment
  • Be available under a license without source code restrictions

Common Lisp was the only framework that met all these requirements. And, it is not the first time lisp has been used in a statistical setting. XLISP-STAT, our spiritual predecessor, was a contemporary of R in the early days of development. Wikipedia says about it: “XLispStat was historically influential in the field of statistical visualization” and its author, Luke Tierney, was a member of the original R core team.

What does Lisp-Stat do?

Lisp-Stat provides support for vectorized mathematical operations, a super-set of common lisp array operations, and a comprehensive set of statistical methods that are implemented using the latest numerical algorithms. In addition, Common Lisp provides a dynamic programming environment that includes a REPL for interactive evaluation of code, CLOS, an excellent object oriented environment and a meta-object protocol (MOP).

We have also compiled an archive of XLISP-STAT libraries that can be ported with the aid of a compatibility package (XLS). This gives Lisp-Stat a leg up on ecosystem development; there are many useful statistical routines in the archive.

Getting Started

If you are familiar with R, and want to understand how to do similar things with Lisp-Stat, the basic tutorial is the place to begin. If you have a Common Lisp installation and want give Lisp-Stat a quick try, start with Install to Plot in 5 minutes. For newcomers to lisp, see the Installation section for how to get going from ground zero.

What’s in the box?

All the basics for descriptive statistical analysis.

Data Frames

Load the classic R mtcars data set into a data frame:

(data :mtcars)

Plotting

The plotting examples show how to plot the horsepower vs. miles-per-gallon of the similar Vega-Lite data set:

(plot:plot
  (vega:defplot hp-mpg
  `(:title "Horsepower vs. MPG"
    :data (:values ,vgcars)
    :mark :point
	:encoding (:x (:field :horsepower :type :quantitative)
	           :y (:field :miles-per-gallon :type :quantitative)))))

Jupyter notebooks

For reproducible research and sharing.

Lisp-Stat running in a Jupyter-Lab notebook

Examples & Tutorials

The examples show how to create commonly used statistical plots and the analytic examples work through the examples of the book Introduction to the Practice of Statistics using Lisp-Stat.

Example data sets

About 1500 R data sets can be loaded using the rdata package.

Where do I get help?

The community page page describes how the project is structured. Help can be obtained from:

Where did it come from?

Several of these libraries are based on the work of Tamas K Papp, who was working as a practicing econometrician using Common Lisp before leaving the community for Julia. One of the design goals for Lisp-Stat was to avoid the Lisp Curse that plagues so many common lisp niches, including statistics. So, rather than reinvent the wheel, we took some existing wheels, greased and polished them, added documentation and filed off the rough edges to make them work smoothly together in an integrated environment. The greenfield work includes special functions and plot.

Haven’t I seen this before?

You may have. In late March 2021 existence of Lisp-Stat was leaked to Hacker News and Reddit. At that time, we were still getting Lisp-Stat ready for general release, and things were not quite where we wanted them to be. If you saw the original leaked version, here are the changes:

  • Documentation:
    • Reorganized getting started, tutorials, reference
    • Added plotting and data-frame examples
    • Added “Install to plot in 5 minutes” getting started guide
    • Expanded analytic examples
    • Expanded basic tutorial
    • QA: spelling, grammar, typos, examples
    • Added resources section
    • Added search
  • Data Frame
    • Added pretty printing
    • Added markdown printing
    • Added variable shortcuts, you can now refer to a variable by name in all contexts
    • Added head, tail, summary, column-name functions
    • Added define-data-frame macro
    • Miscellaneous bug fixes
  • Plot
    • Added box plot
    • Added histogram