cut

cut(X, size|cutPositions)

X is a scalar/vector/matrix/table.

size is a positive integer that must be no greater than the size of X.

cutPositions is a vector with increasing elements, which is used to specify the starting position of each vector in the result.

This function divides X based on the specified size or cutPositions and returns a tuple.

• When X is a scalar, size can only be specified as 1.

• When X is a vector:

  • if size is specified, it divides X into a list of scalars (size=1) or vectors (size>1) of length size.

  • if cutPositions is specified, it divides X into a list of vectors at the specified positions.

• When X is a matrix (table):

  • if size is specified, it divides X into several matrices (tables) with size columns (rows).

  • if cutPositions is specified, it divides X into several matrices (tables) at the specified positions.

Refer to function flatten for the reverse operation.

a=1..10;

cut(a,2);
// output
([1,2],[3,4],[5,6],[7,8],[9,10])

cut(a,3);
// output
([1,2,3],[4,5,6],[7,8,9],[10])

cut(a,9);
// output
([1,2,3,4,5,6,7,8,9],[10])

b = cut(a,2);
b;
// output
([1,2],[3,4],[5,6],[7,8],[9,10])

flatten b;
// output
(1,2,3,4,5,6,7,8,9,10)

cut(a, 0 2 7);
// output
([1,2],[3,4,5,6,7],[8,9,10])

cut(a, 2 7);
// output
([3,4,5,6,7],[8,9,10])

The cut function can be a convenient tool in time-series data analysis. In the example below, we use the cut function to calculate an aggregate measure between two events.

incomes=table(2016.07.31 - 10..1 as date, rand(100,10) as income);
incomes;

eventdates = [2016.07.22, 2016.07.25, 2016.07.29];

x = incomes.date.binsrch(eventdates);
x;
// output
[1,4,8]

incomes.date.cut(x);
// output
([2016.07.22,2016.07.23,2016.07.24],[2016.07.25,2016.07.26,2016.07.27,2016.07.28],[2016.07.29,2016.07.30])

table(eventdates as startDate, each(last,incomes.date.cut(x)) as endDate, each(sum,incomes.income.cut(x)) as incomeSum);