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Run a function on array sublists —Wolfram Documentation

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• See Also
  • ArrayFilter
  • Partition
  • Map
  • SubsetMap
  • MapIndexed
  • ListCorrelate
  • MovingMap
  • CellularAutomaton
• Related Guides
  • Applying Functions to Lists
  • Handling Arrays of Data
  • Functional Programming

BlockMap[f,list,n]

applies f to non-overlapping sublists of length n in list.

BlockMap[f,list,n,d]

applies f to sublists with offset d in list.

BlockMap[f,list,{n₁,n₂,…},…]

applies f to blocks of size n₁×n₂×….

• In BlockMap[f,list,n], all sublists passed to f are of length n. Some elements at the end of list may not be visited.
• In BlockMap[f,list,n,1], all elements of list appear in at least one sublist.
• In BlockMap[f,list,n,d], if d is greater than n, some elements in the middle of list are skipped. »
• BlockMap can be used on SparseArray objects.

Apply a function to all non-overlapping, length-2 sublists:

Apply a function to overlapping sublists of length 2 with offset 1:

Apply a function to a matrix:

Apply a function to all 2x2 sub-matrices:

Apply a function to a ragged array:

Apply a function to blocks of size {2,1,2} of a rank-3 array:

Specify an offset {1,2} with a block size {2,2} to allow overlapping for rows but not for columns:

Multidimensional offsets are effectively coerced to match the block size specification:

Skip elements by using an offset larger than the block size:

Incomplete sublists at the end are dropped:

The head need not be List:

BlockMap works with SparseArray objects:

Compute successive differences of elements:

Compute a moving average with runs of 3 elements:

Compute a moving median of a matrix:

Compute a moving quantile for some data:

Smooth a simulated particle trajectory:

The underlying signal and simulated path with noise:

Smooth the trajectory using a moving TrimmedMean:

Increasing the window size gives a smoother trajectory:

BlockMap is effectively the same as using Map and Partition:

BlockMap need not construct all the sublists and requires less memory:

ListCorrelate[ker,list] effectively combines ker with a sliding block in list:

Use an offset of 1 in BlockMap to apply the function to overlapping segments the length of ker:

ListConvolve is similar except the kernel is reversed:

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