Grid Mask Neighbor Count Table

Count set neighbors for every mask cell under an explicit four/eight-neighbor convention; outside cells contribute zero.

Description

Count set neighbors for every mask cell under an explicit four/eight-neighbor convention; outside cells contribute zero.

Neighbor counts measure adjacent set cells independently of whether the center is set.

When to use this tool

Count set neighbors for every mask cell under an explicit four/eight-neighbor convention; outside cells contribute zero.

  • Prepare the supplied mask, diagonal 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 mask, diagonal. 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.counts. Interpret false, null and empty lists using the distinctions below; they can be valid outputs.

Validate a binary mask and count in-bounds one-valued neighbors for every cell, using four orthogonal or eight surrounding positions according to diagonal.1

Input fieldMeaning and representationAccepted input
maskmask.Numeric rows; at most 128 rows and 128 values per row
diagonalExplicit choice for diagonal; supply a boolean rather than a text label.true or false
Output fieldInterpretation
resultObject containing the named outputs below.
result.countsThe counts list in the ordering and representation described above.
json
{
  "input": {
    "mask": [
      [
        1,
        0
      ],
      [
        0,
        1
      ]
    ],
    "diagonal": true
  },
  "output": {
    "result": {
      "counts": [
        [
          1,
          2
        ],
        [
          2,
          1
        ]
      ]
    }
  }
}

Limitations and assumptions

  • The center is excluded and outside positions contribute zero. Counts are not connectivity labels or a growth simulation.
  • Coordinate pairs use [row,column] where stated. Masks are nonempty rectangular zero/one matrices of at most 128 rows, 128 columns and 16,384 cells; outside-mask values are unset for the neighborhood operations.
  • 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.
  • String lists have at most 128 entries of at most 128 code units; matrices have at most 128 rows and columns. Larger numeric lists and parsed JSON have separate bounded budgets. 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

Keep row/column coordinates distinct from x/y pairs and byte offsets. Select the neighborhood metric, outside-mask rule and storage-order convention explicitly; these operations do not infer an image format.

References

  1. Tool behavior and example: Grid Mask Neighbor Count Table — tool.io

Similar or alternative tools

  • Grid Mask Boolean Combination

    Combine identically shaped binary masks by explicit AND, OR, XOR or left difference; no resampling or alignment inference.

  • Grid Mask Border Cells

    List set binary mask cells adjacent to a four-neighbor unset/outside position in stable row-major order.

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