Random Parallel Coordinate Profile Dataset Generator

Description

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

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

When to use this tool

Use this generator to create reproducible parallel coordinate profile 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 axes, centers, jitter, count 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 axes, centers, values, means, jitter. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

For every profile and axis, add inclusive integer jitter around that axis's center. Return aligned axes, centers, values, and delegated per-profile means.^[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
axes	Axes	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 2; maximum items 8.
centers	Centers	Required. Array of Safe integer.; minimum items 2; maximum items 8.
jitter	Jitter	Required. Safe integer; minimum 0; maximum 1000000.
count	Requested count; the mechanics explain whether one draw expands into several returned records.	Required. Safe integer; minimum 1; maximum 8.
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
axes	Axes	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 2; maximum items 8.
centers	Centers	Required. Array of Safe integer.; minimum items 2; maximum items 8.
values	Values	Required. Array of Array of Safe integer.; minimum items 2; maximum items 8.; minimum items 1; maximum items 8.
means	Feature means aligned with input columns, in their original units.	Required. Array of Finite number.; minimum items 1; maximum items 8.
jitter	Jitter	Required. Safe integer.
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": {
    "axes": [
      "x",
      "y"
    ],
    "centers": [
      10,
      20
    ],
    "jitter": 1,
    "count": 1,
    "seed": 42
  },
  "output": {
    "axes": [
      "x",
      "y"
    ],
    "centers": [
      10,
      20
    ],
    "values": [
      [
        10,
        20
      ]
    ],
    "means": [
      15
    ],
    "jitter": 1,
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Axes and centers must align one-to-one and all ranges must remain safe integers. The mean combines supplied dimensions literally and has no automatic meaning across incompatible units; no chart is rendered.
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 Parallel Coordinate Profile Dataset Generator — tool.io
Calculation or validation: statistics/mean — tool.io

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