Text viewer for call tree data from method tracing.

Renders call trees as ASCII trees with box-drawing characters,
showing call counts and call count percentages.

Chart specifications for ACF (Autocorrelation Function) plots.

Provides:
- Vega-Lite point charts for graphical viewers (:portal, :kindly)
- ASCII bar chart rendering for text viewers (:print, :pprint)

Both chart types show autocorrelation coefficients for all lags,
with severity-based coloring and threshold visualization.

Comparison chart functions for Vega-Lite charts.

Provides single-point bar/box charts and multi-point line charts for
comparing implementations across benchmarks. Used by both domain extracts
and comparison data structures.

Distribution overlay functions for Vega-Lite charts.

Provides KDE, PDF, and CDF visualization layers and complete chart specs
for displaying distribution fits and comparing empirical vs theoretical
distributions.

ASCII chart rendering for distribution analysis visualization.

Provides ASCII chart functions for:
- PDF (probability density function) line charts
- CDF (cumulative distribution function) step charts
- Q-Q (quantile-quantile) scatter plots

These functions are used by :print and :pprint viewers for terminal-based
visualization of distribution fit results.

Profile visualization for call trees, treemaps, and most-called methods.

Provides Vega and Vega-Lite specs for: - Allocation treemaps showing memory
usage by type - Call tree visualizations (hierarchical tree and flame chart) -
Most-called method bar charts

Q-Q plot visualization functions for Vega-Lite charts.

Provides Q-Q (quantile-quantile) plot generation for comparing sample
distributions against fitted theoretical distributions. Q-Q plots show
sample quantiles vs theoretical quantiles - points lying on the y=x
diagonal indicate good fit.

Regression chart functions for Vega-Lite visualizations.

Provides scatter plots with fit lines, residual plots, and log-log regression
charts for complexity analysis. Supports both single-implementation and
multi-implementation comparison modes.

Sample visualization functions for Vega-Lite charts.

Provides scatter plots, histograms, event markers, and sample difference
visualizations for criterium benchmark data.

Tail analysis visualization functions for Vega-Lite charts.

Provides chart generation for extreme value analysis including:
- Tail ratios table showing percentile ratios
- Hill plot showing tail index estimates across k values
- Mean residual life plot for threshold selection
- Zipf plot (complementary CDF on log-log scale)
- Q-Q plots comparing exceedances to exponential and GPD distributions

ASCII chart rendering for tail analysis visualization.

Provides ASCII chart functions for:
- Tail ratios bar chart
- Hill plot (tail index estimates vs k)
- MRL plot (mean residual life vs threshold)
- Zipf plot (complementary CDF on log-log scale)
- Exponential Q-Q plot
- GPD Q-Q plot

These functions are used by :print and :pprint viewers for terminal-based
visualization of tail analysis results.

Shared helpers for common-charts sub-namespaces.

Provides utility functions used across multiple chart generation namespaces
to avoid circular dependencies.

Allocation view helpers for formatting and rendering allocation data.

Provides functions for formatting call sites and object types, as well as
ASCII treemap rendering for allocation visualization.

ASCII chart rendering for terminal-based visualization.

Provides LTTB (Largest Triangle Three Buckets) downsampling and
ASCII line/scatter plot rendering for use in :print and :pprint viewers.

Main entry points:
- `lttb-downsample` - reduce points while preserving visual shape
- `render-chart` - render points as ASCII chart, returns vector of strings

Autocorrelation view helpers.

Provides functions for formatting autocorrelation data and iterating over
metrics for display. Used by print and pprint viewers.

Bootstrap statistics view helpers.

Provides functions for formatting bootstrap estimates and building
bootstrap statistics table rows.

Core utility functions for viewer data preparation.

This namespace provides foundational functions used across multiple viewer
namespaces for formatting metrics, computing SI scaling, and preparing
basic statistical data for display.

Common distribution formatting utilities for viewer implementations.

This namespace provides shared functions used by all viewers
for formatting distribution fit results in tables and text output.

Domain comparison data preparation functions.

Provides functions to prepare domain-comparison data for various chart types
including box plots, bar charts, and line charts, as well as table rendering.

Domain shape detection predicates for visualization strategy selection.

Provides functions to analyze the structure of domain extract and
comparison data to determine the appropriate visualization
strategy (box plot, line chart, or table).

Domain extract table preparation functions.

Provides functions to prepare domain-extract data for table rendering,
including transposed tables for single-point multi-impl scenarios and
grouped data tables.

Modal analysis view helpers.

Provides functions for formatting mode locations and iterating over
multimodal metrics for display.

Domain regression data preparation functions.

Provides functions to prepare regression model data for table and chart
rendering, including model fit data, log-log analysis, and an orchestration
function for rendering regression views.

Shape statistics view helpers.

Provides functions for formatting and classifying shape statistics
(skewness, kurtosis, CV) from bootstrap results.

Common tail analysis context extraction for portal and kindly viewers.

Provides shared data extraction that both graphical viewers need for
tail analysis views including samples access for charts.

A viewer that outputs Kindly-annotated data structures for Clay notebooks.

Uses an accumulator pattern where view functions append Kindly-annotated
values to an atom. The `flush-viewer` multimethod returns a `kind/fragment`
combining all accumulated values.

No runtime dependency on scicloj/kindly - produces plain maps with
appropriate `:kindly/kind` metadata.

Kindly viewer implementations for allocation profiling views.

Provides allocation-summary, allocation-hotspots, allocation-by-type,
and allocation-treemap views that output Kindly-annotated tables and charts.

Kindly viewer for autocorrelation analysis results.

Provides view/* multimethod implementations for displaying autocorrelation
diagnostics in Kindly notebooks, including ACF plots, classification tables,
and effective sample size statistics.

Kindly viewer core functions for basic metrics display.

Provides Kindly-annotated output for:
- metrics, stats, extremes
- bootstrap statistics
- samples, histograms, KDE
- outlier counts and significance
- event stats (class loader, JIT, GC)
- quantiles, sample percentiles, sample diffs
- collect plan, OS, and runtime info

Uses an accumulator pattern where view functions append Kindly-annotated
values to an atom. The `flush-viewer` multimethod returns a `kind/fragment`
combining all accumulated values.

No runtime dependency on scicloj/kindly - produces plain maps with
appropriate `:kindly/kind` metadata.

Distribution fit views for kindly viewer.

Contains views for:
- Distribution model comparison (AIC, BIC, goodness-of-fit tests)
- Parameter confidence intervals for best-fit models
- Distribution PDF, CDF, and Q-Q plot charts

Domain analysis views for Kindly viewer.

Provides views for:
- Domain extract tables and charts
- Domain grouped tables
- Domain comparison tables and charts
- Domain regression analysis with tables and charts

Modal analysis views for kindly viewer.

Contains multimodal distribution warning display.

Kindly viewer for shape statistics.

Displays skewness, kurtosis, and coefficient of variation (CV) for
bootstrap results in a Kindly table.

Tail analysis views for kindly viewer.

Contains views for:
- Tail summary (GPD/Hill parameters)
- Tail ratios (p99/p95, p999/p99, p999/p95)
- High quantile estimates (GPD extrapolation)
- Chart views (tail ratio charts, Hill/MRL/Zipf plots, Q-Q plots)

A viewer that outputs to portal using tap>.

Core functionality (tap infrastructure, metrics, stats, extremes, bootstrap,
samples, outliers, events, KDE) is in criterium.viewer.portal.core.

Domain analysis views (grouped, extract, comparison, regression, apply)
are in criterium.viewer.portal.domain.

Allocation profiling views (summary, hotspots, by-type, treemap)
are in criterium.viewer.portal.allocation.

Distribution fit views (models, parameter CIs, PDF, CDF, Q-Q charts)
are in criterium.viewer.portal.distribution.

Tail analysis views (summary, ratios, high quantiles, charts)
are in criterium.viewer.portal.tail.

Shape statistics views (skewness, kurtosis, CV)
are in criterium.viewer.portal.shape.

Modal analysis views (multimodal warnings)
are in criterium.viewer.portal.modal.

Autocorrelation analysis views (ACF plots, classification, ESS)
are in criterium.viewer.portal.autocorrelation.

Portal viewer functions for allocation profiling display.

Provides Portal output for:
- allocation summary (totals, counts, freed ratio)
- allocation hotspots (call sites with highest allocations)
- allocations by type (aggregated by object type)
- allocation treemap (Vega treemap visualization)

Portal viewer for autocorrelation analysis results.

Provides view/* multimethod implementations for displaying autocorrelation
diagnostics in Portal, including ACF plots, classification tables, and
effective sample size statistics.

Portal viewer core functions for basic metrics display.

Provides Portal output for:
- tap infrastructure (submit, flush)
- metrics, stats, extremes
- bootstrap statistics
- samples with outliers
- outlier counts and significance
- event stats (class loader, JIT, GC)
- histograms, KDE, quantiles

Distribution fit views for portal viewer.

Contains views for:
- Distribution model comparison (AIC, BIC, goodness-of-fit tests)
- Parameter confidence intervals for best-fit models
- Distribution PDF, CDF, and Q-Q plot charts

Portal viewer domain analysis views.

Provides Portal output for:
- domain-grouped views
- domain-extract tables and charts
- domain-comparison tables and charts
- domain-regression results
- domain-apply iteration

Modal analysis views for portal viewer.

Contains multimodal distribution warning display.

Portal viewer for shape statistics.

Displays skewness, kurtosis, and coefficient of variation (CV) for
bootstrap results in a Portal table.

Tail analysis views for portal viewer.

Contains views for:
- Tail summary (GPD/Hill parameters)
- Tail ratios (p99/p95, p999/p99, p999/p95)
- High quantile estimates (GPD extrapolation)
- Chart views (tail ratio charts, Hill/MRL/Zipf plots, Q-Q plots)

A pretty print viewer

A print viewer

Core functionality (metrics, stats, extremes, bootstrap, samples, outliers,
events, GC, OS, runtime) is in criterium.viewer.print.core.

Domain analysis (grouped, extract, comparison, regression, apply) is in
criterium.viewer.print.domain.

Allocation profiling (summary, hotspots, by-type, treemap) is in
criterium.viewer.print.allocation.

Distribution fit (models, parameter CIs) is in
criterium.viewer.print.distribution.

Tail analysis (summary, ratios, high quantiles) is in
criterium.viewer.print.tail.

Shape statistics (skewness, kurtosis, CV) is in
criterium.viewer.print.shape.

Modal analysis (multimodal warnings) is in criterium.viewer.print.modal.

Autocorrelation analysis (lag analysis, effective sample size, classification)
is in criterium.viewer.print.autocorrelation.

Print viewer functions for allocation profiling display.

Provides text output for:
- allocation summary (totals, counts, freed ratio)
- allocation hotspots (call sites with highest allocations)
- allocations by type (aggregated by object type)
- allocation treemap (ASCII tree visualization)

Print viewer for autocorrelation analysis.

Provides views for lag analysis, effective sample size,
CI inflation factors, pattern classification, and ACF plots.

Print viewer core functions for basic metrics display.

Provides text output for:
- metrics, stats, extremes
- bootstrap statistics
- samples with outliers
- outlier counts and significance
- event stats (class loader, JIT, GC)
- final GC warnings
- OS and runtime info
- histograms, KDE, quantiles

Distribution fit views for print viewer.

Contains views for:
- Distribution model comparison (AIC, BIC, goodness-of-fit tests)
- Parameter confidence intervals for best-fit models
- ASCII chart views (PDF, CDF, Q-Q plots)

Print viewer domain analysis views.

Provides text output for:
- domain-grouped views
- domain-extract tables
- domain-comparison tables
- domain-regression results
- domain-apply iteration

Modal analysis views for print viewer.

Contains multimodal distribution warning display.

Print viewer for shape statistics.

Displays skewness, kurtosis, and coefficient of variation (CV) for
bootstrap results.

Print viewer table formatting.

Provides generic table printing with box-drawing separators.

Tail analysis views for print viewer.

Contains views for:
- Tail summary (GPD/Hill parameters)
- Tail ratios (p99/p95, p999/p99, p999/p95)
- High quantile estimates (GPD extrapolation)
- ASCII chart views (tail ratio charts, Hill/MRL/Zipf plots, Q-Q plots)