Monotonic Run Segmenter

Segment maximal weak-monotonic runs, sharing turning-point samples; flat steps retain the active direction and fully flat runs have direction zero.

Description

Segment maximal weak-monotonic runs, sharing turning-point samples; flat steps retain the active direction and fully flat runs have direction zero.

Monotonic runs group consecutive movement in one direction while allowing flat steps. A turning sample belongs to both neighboring runs so each change remains represented.

When to use this tool

Segment maximal weak-monotonic runs, sharing turning-point samples; flat steps retain the active direction and fully flat runs have direction zero.

  • Prepare the supplied values fields for this operation.
  • Compare the complete example with the representation used by your own input before carrying the result into another step.

How to use the tool and how it works

  1. Enter values. Use the exact text syntax, units and index conventions explained below.
  2. Run the tool. If input validation fails, correct the supplied fields before interpreting any result.
  3. Read result.segments. Interpret false, null and empty lists using the distinctions below; they can be valid outputs.

Track the last nonzero adjacent-difference sign. On a change of sign, close the current half-open segment and start the next at the previous sample. Return direction -1, 0 or 1 for each run.1

Input fieldMeaning and representationAccepted input
valuesvalues.List of finite numbers; bounded by the operation
Output fieldInterpretation
resultObject containing the named outputs below.
result.segmentsThe segments list in the ordering and representation described above.
json
{
  "input": {
    "values": [
      1,
      2,
      3,
      2
    ]
  },
  "output": {
    "result": {
      "segments": [
        {
          "start": 0,
          "end": 3,
          "direction": 1
        },
        {
          "start": 2,
          "end": 4,
          "direction": -1
        }
      ]
    }
  }
}

Limitations and assumptions

  • Adjacent runs can overlap by their turning point. Equal steps retain the current direction, and a fully flat list has direction zero; no noise tolerance is applied.
  • Every declared top-level field is required and unexpected fields are rejected. Numeric inputs must be finite; ordinary text fields are bounded to 8,192 UTF-16 code units, with tighter operation-specific limits where stated.
  • Ordinary string lists have at most 128 entries of at most 128 code units each; numeric lists and matrices have separate bounded size checks. Nonfinite results and excessively large serialized outputs are rejected.
  • Indexes are zero-based and spans have an exclusive end unless explicitly stated otherwise. A valid false, null or empty-list result is distinct from malformed input.

Alternative or Complementary methods

Use explicit source-index maps when rearranging data or planning missing-value fills. Keep row-major coordinates, cyclic indexes and one-based occurrence numbers distinct, and inspect null donor positions before copying values.

References

  1. Tool behavior and example: Monotonic Run Segmenter — tool.io

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