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Wolfram Language & System Documentation Center
ArrayFlatten
  • See Also
    • Flatten
    • Join
    • Band
    • ArrayQ
    • ArrayDepth
    • ArrayPad
    • ImageApply
    • SubstitutionSystem
    • ArrayReduce
  • Related Guides
    • Rearranging & Restructuring Lists
    • Constructing Matrices
    • Structure Matrices & Convolution Kernels
    • Computational Systems
    • Image Filtering & Neighborhood Processing
    • Handling Arrays of Data
    • Basic Image Manipulation
    • Iterated Maps & Fractals
  • Tech Notes
    • Rearranging Nested Lists
    • Combining Lists
    • Structural Operations
    • Vectors and Matrices
    • Tensors
    • See Also
      • Flatten
      • Join
      • Band
      • ArrayQ
      • ArrayDepth
      • ArrayPad
      • ImageApply
      • SubstitutionSystem
      • ArrayReduce
    • Related Guides
      • Rearranging & Restructuring Lists
      • Constructing Matrices
      • Structure Matrices & Convolution Kernels
      • Computational Systems
      • Image Filtering & Neighborhood Processing
      • Handling Arrays of Data
      • Basic Image Manipulation
      • Iterated Maps & Fractals
    • Tech Notes
      • Rearranging Nested Lists
      • Combining Lists
      • Structural Operations
      • Vectors and Matrices
      • Tensors

ArrayFlatten[{{m11,m12,…},{m21,m22,…},…}]

creates a single flattened matrix from a matrix of matrices mi j.

ArrayFlatten[a,r]

flattens out r pairs of levels in the array a.

Details
Details and Options Details and Options
Examples  
Basic Examples  
Scope  
Applications  
Properties & Relations  
See Also
Tech Notes
Related Guides
Related Links
History
Cite this Page
BUILT-IN SYMBOL
  • See Also
    • Flatten
    • Join
    • Band
    • ArrayQ
    • ArrayDepth
    • ArrayPad
    • ImageApply
    • SubstitutionSystem
    • ArrayReduce
  • Related Guides
    • Rearranging & Restructuring Lists
    • Constructing Matrices
    • Structure Matrices & Convolution Kernels
    • Computational Systems
    • Image Filtering & Neighborhood Processing
    • Handling Arrays of Data
    • Basic Image Manipulation
    • Iterated Maps & Fractals
  • Tech Notes
    • Rearranging Nested Lists
    • Combining Lists
    • Structural Operations
    • Vectors and Matrices
    • Tensors
    • See Also
      • Flatten
      • Join
      • Band
      • ArrayQ
      • ArrayDepth
      • ArrayPad
      • ImageApply
      • SubstitutionSystem
      • ArrayReduce
    • Related Guides
      • Rearranging & Restructuring Lists
      • Constructing Matrices
      • Structure Matrices & Convolution Kernels
      • Computational Systems
      • Image Filtering & Neighborhood Processing
      • Handling Arrays of Data
      • Basic Image Manipulation
      • Iterated Maps & Fractals
    • Tech Notes
      • Rearranging Nested Lists
      • Combining Lists
      • Structural Operations
      • Vectors and Matrices
      • Tensors

ArrayFlatten

ArrayFlatten[{{m11,m12,…},{m21,m22,…},…}]

creates a single flattened matrix from a matrix of matrices mi j.

ArrayFlatten[a,r]

flattens out r pairs of levels in the array a.

Details

  • ArrayFlatten requires that the blocks it flattens have dimensions that fit together.
  • ArrayFlatten can be used to form block matrices from arrays of blocks.
  • For a matrix of matrices, ArrayFlatten[a] yields a matrix whose elements are in the same order as in MatrixForm[a].
  • ArrayFlatten[a] is normally equivalent to Flatten[a,{{1,3},{2,4}}]. »
  • ArrayFlatten[a,r] is normally equivalent to Flatten[a,{{1,r+1},{2,r+2},…,{r,2r}}].
  • For a tensor with rank 2r, ArrayFlatten[a,r] gives a tensor with rank r.
  • In ArrayFlatten[{{m11,m12,…},{m21,m22,…},…}], all the matrices mi j in the same row must have the same first dimension, and matrices mi j in the same column must have the same second dimension.
  • In general, in ArrayFlatten[a,r], all the k^(th) dimensions of a[[i1,i2,…,i_r]] must be equal for each possible value of ik .
  • Elements at level r whose array depth is less than r are treated as scalars, and are replicated to fill out a rank-r array of the appropriate dimensions.
  • ArrayFlatten works with SparseArray objects. »

Examples

open all close all

Basic Examples  (2)

Create a block matrix by flattening out a matrix of matrices:

Use 0s to represent zero matrices:

Scope  (4)

Flatten a rank-4 array to rank 2:

Flatten only the first four levels of a rank-6 array:

Flatten a rank 6 array to rank 3:

ArrayFlatten works with SparseArray objects:

Make a sparse matrix from a block matrix of SparseArray objects:

Applications  (5)

Put together many copies of a "tile":

Iterate a 2D substitution system:

Iterate a 3D substitution system:

Form an involutory matrix , such that :

Check that the resulting matrix is involutory:

Form a block matrix semidiscretization of the wave equation with n spatial points:

Differentiation matrix for second-order approximation of with periodic boundary conditions:

Identity matrix of size n:

Form block matrix a for system where :

Identity matrix of size 2 n:

Set up an initial condition vector for :

Approximate the solution at using the backward Euler method with time step k:

Show and at :

Properties & Relations  (3)

MatrixForm displays matrices of matrices in the same order as ArrayFlatten:

ArrayFlatten is a special case of Flatten:

KroneckerProduct is defined as ArrayFlatten of an Outer product:

See Also

Flatten  Join  Band  ArrayQ  ArrayDepth  ArrayPad  ImageApply  SubstitutionSystem  ArrayReduce

Function Repository: BlockDiagonalMatrix

Tech Notes

    ▪
  • Rearranging Nested Lists
  • ▪
  • Combining Lists
  • ▪
  • Structural Operations
  • ▪
  • Vectors and Matrices
  • ▪
  • Tensors

Related Guides

    ▪
  • Rearranging & Restructuring Lists
  • ▪
  • Constructing Matrices
  • ▪
  • Structure Matrices & Convolution Kernels
  • ▪
  • Computational Systems
  • ▪
  • Image Filtering & Neighborhood Processing
  • ▪
  • Handling Arrays of Data
  • ▪
  • Basic Image Manipulation
  • ▪
  • Iterated Maps & Fractals

Related Links

  • An Elementary Introduction to the Wolfram Language : Rearranging Lists

History

Introduced in 2007 (6.0)

Wolfram Research (2007), ArrayFlatten, Wolfram Language function, https://reference.wolfram.com/language/ref/ArrayFlatten.html.

Text

Wolfram Research (2007), ArrayFlatten, Wolfram Language function, https://reference.wolfram.com/language/ref/ArrayFlatten.html.

CMS

Wolfram Language. 2007. "ArrayFlatten." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/ArrayFlatten.html.

APA

Wolfram Language. (2007). ArrayFlatten. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ArrayFlatten.html

BibTeX

@misc{reference.wolfram_2025_arrayflatten, author="Wolfram Research", title="{ArrayFlatten}", year="2007", howpublished="\url{https://reference.wolfram.com/language/ref/ArrayFlatten.html}", note=[Accessed: 01-May-2026]}

BibLaTeX

@online{reference.wolfram_2025_arrayflatten, organization={Wolfram Research}, title={ArrayFlatten}, year={2007}, url={https://reference.wolfram.com/language/ref/ArrayFlatten.html}, note=[Accessed: 01-May-2026]}

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