I am attempting to build a small program that will help forecast future demand based on some inputs. Three key pieces of input are demand, on-hand, in-transit. The demand is passed as a list of 52 elements and the in-transit array would need to match it's length The problem I'm running into is initializing the in-transit data.
Demand data looks like this:
d = [100, 221, 470, 100, 250,...]
For the program to properly forecast, I need to pass the in-transit data in over a 52 week period. If I only have inbound inventory in week 3 for example, my data would look like this:
transit = [0, 0, 378,...]
Is there a way that I can pass this data into a numpy array and feed this to the program? Currently I'm using np.zero to initialize but that would only work if I didn't have inventory scheduled to arrive.
Code Snippet
# Determine the starting on hand and transit arrays
hand = np.zeros(time, dtype=int)
transit = np.zeros((time,L+1), dtype=int)
What the beginning array outputs when initialized with np.zero:
[[ 0 0 0 0 0 0 0 0 0]
[ 0 0 0 0 0 0 0 0 6429]
[ 0 0 0 0 0 0 0 0 0]
[ 0 0 0 0 0 0 0 0 0]
[ 0 0 0 0 0 0 0 0 0]
[ 0 0 0 0 0 0 0 0 0]]