Random Depth-Layered Starfield Dataset Generator

Description

Generate fictional stars in supplied ordered depth layers with Euclidean parsec distances and extinction-free apparent magnitudes.

A physical-model fixture draws inputs under explicit units and delegates a stated idealized calculation. Computed values follow that model; they are separate from measurements, calibration, and environmental effects omitted by the assumptions.

Generate fictional stars in supplied ordered depth layers with Euclidean parsec distances and extinction-free apparent magnitudes.

When to use this tool

Use this generator to create reproducible depth layered starfield 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 layers, xParsecs, yParsecs, absoluteMagnitude 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 stars. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.

Draw synthetic star positions by depth layer and absolute magnitudes. Calculate Euclidean distance from the origin in parsecs, delegate distance modulus, and add it to absolute magnitude for apparent magnitude.^[1]

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

Input field	Meaning and units	Accepted input
layers	Layers	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
layers[].id	Literal identifier used independently of display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
layers[].count	Count	Required. Safe integer; minimum 1; maximum 64.
layers[].depthParsecs	Depth Parsecs	Required. Object; no unknown keys.
layers[].depthParsecs.minimum	Minimum	Required. Finite number; strictly above 0.
layers[].depthParsecs.maximum	Maximum	Required. Finite number; strictly above 0.
xParsecs	X Parsecs	Required. Object; no unknown keys.
xParsecs.minimum	Minimum	Required. Finite number.
xParsecs.maximum	Maximum	Required. Finite number.
yParsecs	Y Parsecs	Required. Object; no unknown keys.
yParsecs.minimum	Minimum	Required. Finite number.
yParsecs.maximum	Maximum	Required. Finite number.
absoluteMagnitude	Absolute Magnitude	Required. Object; no unknown keys.
absoluteMagnitude.minimum	Minimum	Required. Finite number.
absoluteMagnitude.maximum	Maximum	Required. Finite number.
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
stars	Stars	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 256.
stars[].id	Literal identifier used independently of display labels.	Required. Text; maximum UTF-16 length 80.
stars[].layerId	Layer Id	Required. Text; maximum UTF-16 length 64.
stars[].xParsecs	X Parsecs	Required. Finite number.
stars[].yParsecs	Y Parsecs	Required. Finite number.
stars[].zParsecs	Z Parsecs	Required. Finite number; strictly above 0.
stars[].distanceParsecs	Distance Parsecs	Required. Finite number; strictly above 0.
stars[].absoluteMagnitude	Absolute Magnitude	Required. Finite number.
stars[].distanceModulus	Distance Modulus	Required. Finite number.
stars[].apparentMagnitude	Apparent Magnitude	Required. Finite number.
randomness	Replay source and normalized 32-bit seed, or null seed for an advancing context source.	Required. Object; no unknown keys.
randomness.seed	Optional safe-integer 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": {
    "layers": [
      {
        "id": "near",
        "count": 1,
        "depthParsecs": {
          "minimum": 10,
          "maximum": 10
        }
      },
      {
        "id": "far",
        "count": 1,
        "depthParsecs": {
          "minimum": 100,
          "maximum": 100
        }
      }
    ],
    "xParsecs": {
      "minimum": 0,
      "maximum": 0
    },
    "yParsecs": {
      "minimum": 0,
      "maximum": 0
    },
    "absoluteMagnitude": {
      "minimum": 4,
      "maximum": 6
    },
    "seed": 42
  },
  "output": {
    "stars": [
      {
        "id": "near-0",
        "layerId": "near",
        "xParsecs": 0,
        "yParsecs": 0,
        "zParsecs": 10,
        "distanceParsecs": 10,
        "absoluteMagnitude": 5.339468082878739,
        "distanceModulus": 0,
        "apparentMagnitude": 5.339468082878739
      },
      {
        "id": "far-0",
        "layerId": "far",
        "xParsecs": 0,
        "yParsecs": 0,
        "zParsecs": 100,
        "distanceParsecs": 100,
        "absoluteMagnitude": 5.249489307869226,
        "distanceModulus": 5,
        "apparentMagnitude": 10.249489307869226
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Depth ranges must be supplied in nonoverlapping order, though touching endpoints are allowed. This neglects extinction, motion, and observational selection; it is not an astronomical catalog or sky projection.
A replay requires the same complete input and implementation. The stated sampling convention applies within its eligible space. A finite draw does not exhaust all possible outputs; repeats remain possible unless a distinct-selection rule is explicit.
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 Depth-Layered Starfield Dataset Generator — tool.io
Calculation or validation: astronomy/distance-modulus-parsecs — tool.io

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