The regrid operator selects non-overlapping subarrays and performs aggregation on them.

Synopsis

regrid(array,grid_1 [, grid_2,...,grid_N],
aggregate_call_1 [, aggregate_call_2,...,aggregate_call_N])

Summary

The regrid operator partitions the cells in the input array into blocks. For each block, regrid applies a specific aggregate operation over the value(s) of some attribute in each block.

Note that the chunk size does not have to be a multiple of the grid size, and the grids may span array chunks. However, processing is most efficient if chunk size is a multiple of the grid size, and grids do not span array chunks.

Inputs

The regrid operator takes the following arguments:

array: A source array with one or more attributes and one or more dimensions.
grid_n: A list of block sizes, one per dimension.
aggregate_call_n: One or more aggregate calls.

Example

To divide a 4×4 array into 4 equal partitions and calculates the average of each one, do the following. This process is known as spatial averaging.

Create an array m4x4:

AFL% CREATE ARRAY m4x4 <val:double>[i=0:3; j=0:3];

The output is:

Query was executed successfully

Run this command, which increments val from 0 to 15:

AFL% store(build (m4x4, i*4+j), m4x4);

The output is:

{i,j} val
{0,0} 0
{0,1} 1
{0,2} 2
{0,3} 3
{1,0} 4
{1,1} 5
{1,2} 6
{1,3} 7
{2,0} 8
{2,1} 9
{2,2} 10
{2,3} 11
{3,0} 12
{3,1} 13
{3,2} 14
{3,3} 15

Regrid m4x4 into four (2*2) partitions and find the average of each partition.

AFL% regrid(m4x4, 2,2, avg(val) as Average);

The output is:

{i,j} Average
{0,0} 2.5
{0,1} 4.5
{1,0} 10.5
{1,1} 12.5

The regrid of 2x2 causes the following shape:
0 1 2 3
4 5 6 7
8 9 10 11
12 13 14 15
and the averages are computed as:
(0 + 1 + 4 + 5) / 4 = 2.5
(2 + 3 + 6 + 7) / 4 = 4.5
(8 + 9 + 12 + 13) / 4 = 10.5
(10 + 11 + 14 + 15) / 4 = 12.5
which results in:
2.5 4.5
10.5 12.5

Remove the m4x4 array

AFL% remove(m4x4);

The output is:

Query was executed successfully

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