Hackage :: [Package]

hanalyze-cli: hanalyze command-line interface for the hanalyze toolkit

[ bsd3, machine-learning, math, numeric, program, statistics ] [ Propose Tags ] [ Report a vulnerability ]

The hanalyze command-line executable of the hanalyze toolkit. Its 15 subcommands cover regression (regress for LM GLM GLMM GP HBM, plus ridge, kernel, spline, quantile, gam, rf and multireg), data inspection and plotting (info, hist), design of experiments (doe, taguchi) and reshaping (clean, melt, regrid), with HTML PNG SVG output and optional HTML analysis reports. . It was split out of the hanalyze package so that library work does not trigger the CLI compile+link by default, and so that its dependency on the umbrella public API alone (no internal module access) is guaranteed structurally. See README.md for the subcommand map and examples.

[Skip to Readme]

Downloads

Maintainer's Corner

Package maintainers

For package maintainers and hackage trustees

Candidates

  • No Candidates
Versions [RSS] 0.2.0.1
Dependencies base (>=4.14 && <5), containers (>=0.6 && <0.8), dataframe-core (>=1.1 && <1.2), dataframe-csv (>=1.0.2 && <1.1), dataframe-operations (>=1.1.1 && <1.2), filepath (>=1.4 && <1.6), hanalyze (==0.2.0.1), hmatrix (>=0.20 && <0.22), hvega (>=0.12 && <0.13), mwc-random (>=0.15 && <0.16), text (>=1.2 && <2.2), time (>=1.11 && <1.13), vector (>=0.12 && <0.14) [details]
Tested with ghc ==9.6.7
License BSD-3-Clause
Copyright 2026 Aelysce Project (Toshiaki Honda)
Author Toshiaki Honda
Maintainer frenzieddoll@gmail.com
Uploaded by frenzieddoll at 2026-08-13T05:54:49Z
Category Math, Statistics, Numeric, Machine Learning
Distributions
Executables hanalyze
Downloads 1 total (1 in the last 30 days)
Rating (no votes yet) [estimated by Bayesian average]
Your Rating
  • λ
  • λ
  • λ
Status Docs not available [build log]
Last success reported on 2026-08-13 [all 1 reports]

Readme for hanalyze-cli-0.2.0.1

[back to package description]

hanalyze-cli

The command-line front end of hanalyze. This package ships a single executable, hanalyze, and no library.

It was split out of the umbrella package in Phase 106 for two reasons:

  • so that working on the library does not trigger a CLI compile + link every time, and
  • so that the CLI depends only on the umbrella's public API — the fact that it never reaches into internal modules is guaranteed structurally (build-depends names only hanalyze). 
cabal build hanalyze          # included in the default cabal.project
cabal run   hanalyze -- --help

Subcommands (15 in total)

Regression

Command What it does
regress Classical / Bayesian regression (LM / GLM / GLMM / GP / HBM). The default — omitting the subcommand name lands here
ridge Regularized regression (Ridge / Lasso / Elastic Net)
kernel Kernel regression / RFF approximation
spline B-spline / natural cubic regression
quantile Quantile regression (τ-quantile, MM-IRLS)
gam Generalized additive model (additive B-splines + Ridge)
rf Random forest regression (CART + bagging + feature subsets)
multireg Multi-output regression (wide CSV; linear / kernel-rbf)

Inspecting and plotting data

Command What it does
info Print per-column type and basic statistics
hist Histogram, optionally with a theoretical density overlaid

Design of experiments

Command What it does
doe Generate orthogonal arrays (L_n)
taguchi Taguchi method (S/N ratio + factor effects + inner/outer arrays)

Reshaping data

Command What it does
clean Apply per-column cleaning rules (StripUnits, ParseCurrency, ParseDecimalEU, …)
melt Wide → long reshaping
regrid Align sparse long-form data [id, z, y] onto a common grid

⚠ clean, melt and regrid are implemented but missing from the hanalyze --help listing. Run any of them with no arguments to see its usage (e.g. hanalyze melt).

Usage

# inspect column types and basic statistics
hanalyze info data.csv

# simple regression (subcommand omitted = regress)
hanalyze data.csv x y

# polynomial degrees with a 90% confidence interval
hanalyze data.tsv "x1 x2" y LM --degree -1 2 -2 3 --ci 0.90

# Poisson regression with a log link
hanalyze data.csv x y GLM -d poisson -l log

# random effects (LM + --group → LME, GLM + --group → GLMM)
hanalyze data.csv x y LM --group school

# write an HTML report
hanalyze data.csv x y --report report.html --waic

Main options of regress:

Option Meaning
-d, --dist DIST Distribution: gaussian / binomial / poisson (default gaussian)
-l, --link LINK Link: identity / log / logit / sqrt (default: canonical)
--degree SPEC Polynomial degree specification (default 1)
--ci [LEVEL] Confidence interval (default 0.95)
--pi [LEVEL] Prediction interval (Gaussian only; default 0.95)
--group COL Grouping column → LME / GLMM
--format FORMAT Output format: html / png / svg (default html)
--report [FILE] Generate an HTML analysis report (default report.html)
--waic Add WAIC and LOO-CV to the report (requires --report)

Options specific to the other subcommands are printed when you run them with no arguments (e.g. hanalyze ridge).

There is no CLI-specific page yet; hanalyze <sub> examples appear inside the per-feature docs.

← repository README