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Random Fictional River Town Network Generator

Construct a connected fictional settlement graph with distinct ordinal elevations and strictly descending river edges, retaining upstream/downstream reachability; not hydrology.

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Description

Construct a connected fictional settlement graph with distinct ordinal elevations and strictly descending river edges, retaining upstream/downstream reachability; not hydrology.

Worldbuilding fixtures describe an invented setting through supplied entities and explicit relations. A reproducible arrangement can support games or writing exercises while keeping constructed history and geography separate from factual claims about the real world.

Construct a connected fictional settlement graph with distinct ordinal elevations and strictly descending river edges, retaining upstream/downstream reachability; not hydrology.

When to use this tool

Use this generator to create reproducible fictional river town network 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

  1. Supply townIds, candidates, edgeCount, minimumElevation, maximumElevation in the field shapes below. Set seed when you need an explicit replay.
  2. 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.
  3. Read towns, rivers, order, componentCount, fictional. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.

Sample a connected candidate-edge network and distinct integer elevations. Orient every river edge from higher to lower elevation, then delegate a topological order and compute each town's upstream and downstream reachability.1

Delegated operations used for this result: topological sort. Their calculation or parsing conventions apply to the corresponding result fields.2

Input fieldMeaning and unitsAccepted input
townIdsTown IdsRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 16.
candidatesCandidatesRequired. Array of Object; no unknown keys.; minimum items 0; maximum items 64.
candidates[].fromFromRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
candidates[].toToRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
edgeCountEdge CountRequired. Safe integer; minimum 0; maximum 64.
minimumElevationMinimum ElevationRequired. Safe integer; minimum -9007199254740991; maximum 9007199254740991.
maximumElevationMaximum ElevationRequired. Safe integer; minimum -9007199254740991; maximum 9007199254740991.
seedOptional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.Optional. Safe integer.
Output fieldInterpretationReturned shape
townsTownsRequired. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
towns[].idLiteral identifier used independently of display labels.Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
towns[].elevationElevationRequired. Safe integer; minimum -9007199254740991; maximum 9007199254740991.
towns[].upstreamUpstreamRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 15.
towns[].downstreamDownstreamRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 15.
riversRiversRequired. Array of Object; no unknown keys.; minimum items 0; maximum items 64.
rivers[].fromFromRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
rivers[].toToRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
orderOrderRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 16.
componentCountComponent CountRequired. Safe integer; minimum 1; maximum 16.
fictionalFictionalRequired. Boolean; exactly true.
randomnessReplay source and normalized 32-bit seed, or null seed for an advancing context source.Required. Object; no unknown keys.
randomness.seedOptional safe-integer replay seed; normalization and precedence are explained below.Required. Safe integer. or Null.
randomness.sourceSourceRequired. 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": {
    "townIds": [
      "a",
      "b",
      "c"
    ],
    "candidates": [
      {
        "from": "a",
        "to": "b"
      },
      {
        "from": "b",
        "to": "c"
      }
    ],
    "edgeCount": 2,
    "minimumElevation": 10,
    "maximumElevation": 12,
    "seed": 42
  },
  "output": {
    "towns": [
      {
        "id": "a",
        "elevation": 11,
        "upstream": [
          "b"
        ],
        "downstream": []
      },
      {
        "id": "b",
        "elevation": 12,
        "upstream": [],
        "downstream": [
          "a",
          "c"
        ]
      },
      {
        "id": "c",
        "elevation": 10,
        "upstream": [
          "b"
        ],
        "downstream": []
      }
    ],
    "rivers": [
      {
        "from": "b",
        "to": "a"
      },
      {
        "from": "b",
        "to": "c"
      }
    ],
    "order": [
      "b",
      "a",
      "c"
    ],
    "componentCount": 1,
    "fictional": true,
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

  • Distinct elevations prevent directed cycles but do not enforce realistic drainage, catchments, river capacity, or confluences. Candidate connectivity and edge count must be feasible; the network is fictional.
  • 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

  1. Tool behavior and example: Random Fictional River Town Network Generator — tool.io

  2. Calculation or validation: graph/topological-sort — tool.io

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