repelem — Repeat each element of an array by per-dimension replication factors, matching MATLAB repelem semantics.

repelem(A, r1, r2, ..., rN) repeats each element of A along the requested dimensions. Unlike repmat, which tiles whole arrays, repelem expands individual elements into repeated runs or blocks.

Syntax

B = repelem(A, R)
B = repelem(A, R1, R2, ...)

Inputs

Returns

Errors

How repelem works

• repelem(v, n) repeats each element of a row or column vector v n times and preserves vector orientation.
• repelem(v, counts) accepts a count vector with one non-negative integer count per element of v.
• repelem(A, r1, r2, ..., rN) repeats matrix or N-D array elements along each dimension; scalar factors create element blocks and vector factors provide per-index counts for that dimension.
• Numeric, logical, complex, string, char, and cell inputs are supported. Numeric, logical, complex, string, and cell arrays support N-D replication; char arrays are represented as 2-D character matrices.
• All eight integer data classes are replicated from authoritative native storage and returned in the same class; typed integer replication counts are decoded structurally without a floating round trip.
• Zero counts are allowed and remove the corresponding element or dimension slice from the output.
• Replication counts must be finite, non-negative integers. Count vectors must match the size of the dimension they apply to.
• The builtin checks shape and size overflow before materializing output arrays.

Extended capabilities

• repelem preserves the input value class for numeric dtype metadata, logical arrays, complex tensors, string arrays, char arrays, and cell arrays.
• N-D numeric, logical, complex, string, and cell replication uses the runtime's native storage order for each value kind.

Does RunMat run repelem on the GPU?

RunMat does not yet expose a provider hook for element-wise replication. Backends can add one later without changing the MATLAB-facing behavior.

GPU memory and residency

repelem currently uses an exact owner-aware gather-and-restore fallback for GPU tensors, so automatic gathering remains transparent and explicit resident outputs preserve their source owner.

Examples

Repeating every element of a row vector

u = repelem([1 2 3], 2)

Expected output:

u =
     1     1     2     2     3     3

Using a per-element count vector

u = repelem([1 2 3], [1 2 3])

Expected output:

u =
     1     2     2     3     3     3

Expanding a matrix into element blocks

A = [1 2; 3 4];
B = repelem(A, 2, 3)

Expected output:

B =
     1     1     1     2     2     2
     1     1     1     2     2     2
     3     3     3     4     4     4
     3     3     3     4     4     4

Dropping elements with zero counts

u = repelem([1 2 3 4 5], [0 1 0 2 1])

Expected output:

u =
     2     4     4     5

Repeating along a higher dimension

C = {1; 2};
D = repelem(reshape(C, [1 1 2]), 1, 1, 2);
size(D)

Expected output:

ans =
     1     1     4

Using repelem with coding agents

Open a RunMat example with live inputs, then ask the agent to explain how repelem changes the result.

FAQ

Related Array functions

Open-source implementation

Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how repelem is executed, line by line, in Rust.

• View the source for repelem in Rust on GitHub
• Learn how the RunMat runtime works
• Found a bug? Open an issue with a minimal reproduction.

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