TheAlgorithms/C-Sharp · error · ArgumentException

Both points should have the same dimensionality

Error message

Both points should have the same dimensionality

What it means

Manhattan.Distance sums |x_i - y_i| across paired coordinates, which requires both arrays to have the same length. On a dimensionality mismatch it throws ArgumentException instead of allowing Zip to silently truncate the shorter point.

Solutions

1. Check point lengths match before calling Distance
2. Normalize data loading so every vector has a fixed width
3. Impute/pad missing coordinates before distance computation
4. Catch ArgumentException to flag malformed records in bulk computations

Example fix

// before
Manhattan.Distance(new double[]{1,2}, new double[]{3}); // throws
// after
Manhattan.Distance(new double[]{1,2}, new double[]{3,0});

bool canCompare = point1 != null && point2 != null && point1.Length == point2.Length;

bool SameDimension(double[] a, double[] b) => a.Length == b.Length;

try { d = Manhattan.Distance(a, b); }
catch (ArgumentException) { markRecordMalformed(recordId); }

When it happens

Trigger: Calling Manhattan.Distance(double[] point1, double[] point2) with arrays of different lengths — e.g., grid positions of differing dimension, or feature vectors built with different numbers of attributes.

Common situations: Pathfinding heuristics over grids where one point omits a coordinate; tabular data with missing columns; concatenating vectors from different encoders.

Related errors

• Both points should have the same dimensionality
• Both points should have the same dimensionality
• Both points should have the same dimensionality
• The order must be greater than or equal to 1.
• The source matrix is not square-shaped.

AI-assisted analysis of TheAlgorithms/C-Sharp@96e2905cab (2026-09-13). Data as JSON: /api/errors/0ccadac83258ce7c. Report an issue: GitHub.

Appendix: source

Thrown at Algorithms/LinearAlgebra/Distances/Manhattan.cs:22

/// Implementation fo Manhattan distance.
/// It is the sum of the lengths of the projections of the line segment between the points onto the coordinate axes.
/// In other words, it is the sum of absolute difference between the measures in all dimensions of two points.
///
/// Its commonly used in regression analysis.
/// </summary>
public static class Manhattan
{
    /// <summary>
    /// Calculate Manhattan distance for two N-Dimensional points.
    /// </summary>
    /// <param name="point1">First N-Dimensional point.</param>
    /// <param name="point2">Second N-Dimensional point.</param>
    /// <returns>Calculated Manhattan distance.</returns>
    public static double Distance(double[] point1, double[] point2)
    {
        if (point1.Length != point2.Length)
        {
            throw new ArgumentException("Both points should have the same dimensionality");
        }

        // distance = |x1-y1| + |x2-y2| + ... + |xn-yn|
        return point1.Zip(point2, (x1, x2) => Math.Abs(x1 - x2)).Sum();
    }
}

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