Cross-Temporal Reconciliation Lite

Problem

Reconcile a set of sub-period forecasts with a known aggregate by scaling: adjusted[x] = x * aggregate / sum(series).

Return zero-scaled values when the series sums to zero, so the reconciled values still sum to the aggregate when possible.

Hint

Scaling preserves the relative shape of the sub-period forecasts.

case 1

in: [[1,2,3],12]

expected: [2,4,6]

case 2

in: [[1,1],4]

expected: [2,2]

case 3

in: [[0,0],5]

expected: [0,0]

case 4

in: [[2,3,5],10]

expected: [2,3,5]

Starter codePython

def cross_temporal_reconciliation_lite(series, aggregate):
    # Your code here
    pass

4 test cases · run your code against them in the editor