Description
Generate synthetic radar profiles on supplied integer scales with explicit missing masks, normalized positions and observed axis extrema.
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 synthetic radar profiles on supplied integer scales with explicit missing masks, normalized positions and observed axis extrema.
When to use this tool
Use this generator to create reproducible radar axis comparison 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, profiles, missingProbability 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 values, normalized, axes, profiles. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.
Draw each profile's axis value from its integer range or set it to null under missingProbability. Normalize observed values to (value-minimum)/(maximum-minimum) and return per-axis observed extrema, leaving all-missing extrema null.1
Delegated operations used for this result: minimum; maximum. Their calculation or parsing conventions apply to the corresponding result fields.2, 3
| Input field | Meaning and units | Accepted input |
|---|---|---|
| axes | Axes | Required. Array of Object; no unknown keys.; minimum items 3; maximum items 8. |
| axes[].id | Literal identifier used to match records, independently of their display labels. | Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64. |
| axes[].minimum | Minimum | Required. Safe integer. |
| axes[].maximum | Maximum | Required. Safe integer. |
| profiles | Profiles | Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 8. |
| missingProbability | Missing Probability | Required. Finite number; minimum 0; maximum 1. |
| 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 |
|---|---|---|
| values | Values | Required. Array of Array of Finite number. or Null.; minimum items 3; maximum items 8.; minimum items 1; maximum items 8. |
| normalized | Normalized | Required. Array of Array of Finite number. or Null.; minimum items 3; maximum items 8.; minimum items 1; maximum items 8. |
| axes | Axes | Required. Array of Object; no unknown keys.; minimum items 3; maximum items 8. |
| axes[].id | Literal identifier used to match records, independently of their display labels. | Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64. |
| axes[].minimum | Minimum | Required. Finite number. |
| axes[].maximum | Maximum | Required. Finite number. |
| axes[].observedMinimum | Observed Minimum | Required. Finite number. or Null. |
| axes[].observedMaximum | Observed Maximum | Required. Finite number. or Null. |
| profiles | Profiles | Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 8. |
| 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.
{
"input": {
"axes": [
{
"id": "a",
"minimum": 0,
"maximum": 10
},
{
"id": "b",
"minimum": 0,
"maximum": 20
},
{
"id": "c",
"minimum": 0,
"maximum": 4
}
],
"profiles": [
"p"
],
"missingProbability": 0,
"seed": 42
},
"output": {
"values": [
[
4,
14,
2
]
],
"normalized": [
[
0.4,
0.7,
0.5
]
],
"axes": [
{
"id": "a",
"minimum": 0,
"maximum": 10,
"observedMinimum": 4,
"observedMaximum": 4
},
{
"id": "b",
"minimum": 0,
"maximum": 20,
"observedMinimum": 14,
"observedMaximum": 14
},
{
"id": "c",
"minimum": 0,
"maximum": 4,
"observedMinimum": 2,
"observedMaximum": 2
}
],
"profiles": [
"p"
],
"randomness": {
"seed": 42,
"source": "seed"
}
}
}Limitations and assumptions
- Axis ranges must have positive width and safe inclusive cardinality. Normalization does not reverse desirability, harmonize units, impute missing values, or render a radar chart.
- 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
Similar or alternative tools
- Random Heatmap Block Structure Dataset Generator
Construct labeled heatmap blocks with bounded integer noise and optional mirrored symmetry, retaining the planted block mask.
- Random Histogram Bin Edge Challenge Generator
Generate observations exactly on or one supplied epsilon around explicit bin edges, retaining endpoint-policy membership and outside labels.