StatisticalGenerated from the public API

CorrelationMatrix

See the distribution, the agreement or the uncertainty in the values you supply.

@luc/ui/charts

What it shows

Reveal clusters and signs of pairwise linear relationships across several variables.

Live preview

Symmetric coefficients in −1…1 with a unit diagonal; the matrix arrives already computed.

<CorrelationMatrix
  labels={["Equity", "Credit", "Rates", "Gold", "Oil"]}
  values={[
    [1, 0.72, -0.34, 0.11, 0.46],
    [0.72, 1, -0.18, 0.05, 0.38],
    [-0.34, -0.18, 1, 0.29, -0.22],
    [0.11, 0.05, 0.29, 1, 0.17],
    [0.46, 0.38, -0.22, 0.17, 1],
  ]}
  height={340}
  ariaLabel="Correlation across assets"
/>

Controls

Height

340px

A chart measures its container, so it always needs a definite height.

State

The surface the chart is in — loading, empty and error are drawn by the component.

Accessible name

A drawing is not readable by a screen reader, so it needs a name that states what it shows.

The same fixture as the live preview above; the controls change how it is drawn, not what it measures.

Code

import { CorrelationMatrix } from "@luc/ui/charts";

<CorrelationMatrix
  labels={["Equity", "Credit", "Rates", "Gold", "Oil"]}
  values={[
    [1, 0.72, -0.34, 0.11, 0.46],
    [0.72, 1, -0.18, 0.05, 0.38],
    [-0.34, -0.18, 1, 0.29, -0.22],
    [0.11, 0.05, 0.29, 1, 0.17],
    [0.46, 0.38, -0.22, 0.17, 1],
  ]}
  height={340}
  ariaLabel="Correlation across assets"
  state="ready"
/>

Not controllable here

series / rows — The numbers are the caller's; the fixture above is the example.

Copy for an AI agentA specification an agent can act on: the import, the setup, the chosen props, the data contract and the accessibility expectation.

Implement `CorrelationMatrix` from Luc UI. It is: See the distribution, the agreement or the uncertainty in the values you supply.

Import it with: import { CorrelationMatrix } from "@luc/ui/charts";
Requires: react ^19.0.0; react-dom ^19.0.0; react-hook-form ^7.0.0 (optional, for @luc/ui/forms/react-hook-form); tailwindcss ^4.0.0; node >= 22 (repository tools). Import the stylesheet once at the app root and wrap the tree in `LucProvider`. Both come from the package that publishes @luc.

Chosen configuration: `height={340}`, `state="ready"`, `ariaLabel="Correlation across assets"`.

Accessibility: keep the component's own semantics. Do not re-implement its ARIA wiring, do not add roles it does not declare, and make sure every interactive element is reachable and operable from the keyboard with a visible focus state.
Styling: use Luc UI design tokens and the component's own props. Do not restyle with raw colour literals and do not override the component's internal structure with page CSS.
Motion: respect `prefers-reduced-motion`. The component already does, so do not disable it.

Reproduce this state:
```tsx
<CorrelationMatrix
  labels={["Equity", "Credit", "Rates", "Gold", "Oil"]}
  values={[
    [1, 0.72, -0.34, 0.11, 0.46],
    [0.72, 1, -0.18, 0.05, 0.38],
    [-0.34, -0.18, 1, 0.29, -0.22],
    [0.11, 0.05, 0.29, 1, 0.17],
    [0.46, 0.38, -0.22, 0.17, 1],
  ]}
  height={340}
  ariaLabel="Correlation across assets"
  state="ready"
/>
```

Usage

The values are prepared by the caller: this component draws the points it is given and computes no statistic of its own, so units, scaling and any summary have to be settled before the data reaches it.

It is drawn by the ECharts engine.

Worked examples with real data are on the family overview: Statistical

import { CorrelationMatrix } from "@luc/ui/charts";

<CorrelationMatrix
  labels={["Equity", "Credit", "Rates", "Gold", "Oil"]}
  values={[
    [1, 0.72, -0.34, 0.11, 0.46],
    [0.72, 1, -0.18, 0.05, 0.38],
    [-0.34, -0.18, 1, 0.29, -0.22],
    [0.11, 0.05, 0.29, 1, 0.17],
    [0.46, 0.38, -0.22, 0.17, 1],
  ]}
  height={340}
  ariaLabel="Correlation across assets"
/>

Data contract

`labels` names the variables; `values` is a square symmetric matrix with a unit diagonal. Coefficients must already be computed and lie in the supported −1…1 domain.

Important configuration

Use `labelMode` to control coefficient labels on dense grids, and `formatValue` when the caller needs a different coefficient precision.

Guidelines

When not to use

Do not present correlation as causation, and do not feed a non-symmetric matrix into a chart whose cells imply an unordered pair.

Configuration

Exported symbols
Export	Kind	Signature
`CorrelationMatrix`	15 documented props	`({ labels, values, title, description, labelMode, showValues, formatValue, state, height, className, ariaLabel, ariaDescription, onReady, onEvent, eager, }: CorrelationMatrixProps) => import("@types/…`