Random Small Multiples Panel Dataset Generator

Description

Generate related synthetic panels from a shared series with declared units, per-panel offsets, jitter and one common scale.

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.

Generate related synthetic panels from a shared series with declared units, per-panel offsets, jitter and one common scale.

When to use this tool

Use this generator to create reproducible small multiples panel 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 baseline, panels, offsets, jitter, unit 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 panels, minimum, maximum, unit. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

For each panel, add its corresponding offset and independent inclusive integer jitter to each baseline value. Return the panel mean from the existing mean tool, shared global minimum and maximum, and the supplied unit label.^[1]

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

Input field	Meaning and units	Accepted input
baseline	Baseline	Required. Array of Safe integer.; minimum items 1; maximum items 16.
panels	Panels	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 8.
offsets	Offsets	Required. Array of Safe integer.; minimum items 1; maximum items 8.
jitter	Jitter	Required. Safe integer; minimum 0; maximum 1000000.
unit	Unit	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
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
panels	Panels	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 8.
panels[].id	Literal identifier used to match records, independently of their display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
panels[].values	Values	Required. Array of Safe integer.; minimum items 1; maximum items 16.
panels[].mean	Mean	Required. Finite number.
panels[].offset	Offset	Required. Safe integer.
minimum	Minimum	Required. Finite number.
maximum	Maximum	Required. Finite number.
unit	Unit	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
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": {
    "baseline": [
      2,
      4
    ],
    "panels": [
      "a",
      "b"
    ],
    "offsets": [
      0,
      3
    ],
    "jitter": 1,
    "unit": "items",
    "seed": 42
  },
  "output": {
    "panels": [
      {
        "id": "a",
        "values": [
          2,
          4
        ],
        "mean": 3,
        "offset": 0
      },
      {
        "id": "b",
        "values": [
          6,
          8
        ],
        "mean": 7,
        "offset": 3
      }
    ],
    "minimum": 2,
    "maximum": 8,
    "unit": "items",
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Panel IDs are distinct and offsets must align one-to-one with them. Values and range endpoints must remain safe integers. Units are labels supplied by the caller, not conversions or measurements.
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 Small Multiples Panel Dataset Generator — tool.io
Calculation or validation: statistics/mean — tool.io

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