Random Heatmap Block Structure Dataset Generator

Description

Construct labeled heatmap blocks with bounded integer noise and optional mirrored symmetry, retaining the planted block mask.

A chart dataset contains values plus the labels, grouping, totals, or missing-value conventions needed to interpret them. Separating the numeric construction from plotting makes conservation rules and deliberate edge cases visible before a chart is rendered.

Construct labeled heatmap blocks with bounded integer noise and optional mirrored symmetry, retaining the planted block mask.

When to use this tool

Use this generator to create reproducible heatmap block structure dataset cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.

How to use the tool and how it works

Supply rowBlocks, columnBlocks, within, between, noise, symmetric in the field shapes below. Set seed when you need an explicit replay.
Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
Read matrix, sameBlock, symmetric, rowBlocks, columnBlocks. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Choose within- or between-block centers from equality of supplied row/column block labels and add bounded integer noise. Symmetric mode requires matching block sequences and copies the upper triangle; return the same-block mask and verified symmetry flag.^[1]

Delegated operations used for this result: symmetry checker. Their calculation or parsing conventions apply to the corresponding result fields.^[2]

Input field	Meaning and units	Accepted input
rowBlocks	Row Blocks	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 12.
columnBlocks	Column Blocks	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 12.
within	Within	Required. Safe integer.
between	Between	Required. Safe integer.
noise	Noise	Required. Safe integer; minimum 0; maximum 1000000.
symmetric	Symmetric	Required. Boolean.
seed	Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.	Optional. Safe integer.

Output field	Interpretation	Returned shape
matrix	Matrix	Required. Array of Array of Safe integer.; minimum items 1; maximum items 12.; minimum items 1; maximum items 12.
sameBlock	Same Block	Required. Array of Array of Boolean.; minimum items 1; maximum items 12.; minimum items 1; maximum items 12.
symmetric	Symmetric	Required. Boolean.
rowBlocks	Row Blocks	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 12.
columnBlocks	Column Blocks	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 12.
randomness	Replay metadata: source is seed or context; seed is the normalized 32-bit seed or null for a context source.	Required. Object; no unknown keys.
randomness.seed	Optional numeric replay seed; normalization and precedence are explained below.	Required. Safe integer. or Null.
randomness.source	Source	Required. Text; one of "context", "seed".

An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.

json

{
  "input": {
    "rowBlocks": [
      "a",
      "b"
    ],
    "columnBlocks": [
      "a",
      "b"
    ],
    "within": 5,
    "between": 1,
    "noise": 1,
    "symmetric": true,
    "seed": 42
  },
  "output": {
    "matrix": [
      [
        5,
        1
      ],
      [
        1,
        6
      ]
    ],
    "sameBlock": [
      [
        true,
        false
      ],
      [
        false,
        true
      ]
    ],
    "symmetric": true,
    "rowBlocks": [
      "a",
      "b"
    ],
    "columnBlocks": [
      "a",
      "b"
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

The mask is the planted block truth, not inferred clustering. Non-symmetric mode can still happen to produce a symmetric matrix; all jitter endpoints must remain safe integers.
A replay requires the same complete input and implementation. Randomized construction does not guarantee uniform coverage of every feasible output; finite samples can repeat unless a distinct-selection rule is explicitly stated.
The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.

Alternative or Complementary methods

For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.

References

Tool behavior and example: Random Heatmap Block Structure Dataset Generator — tool.io
Calculation or validation: matrix/symmetry-checker — tool.io

Similar or alternative tools

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Generate planted feature profiles with bounded additive integer jitter and explicit shared axes, centers and per-profile means.