def _solve_gapfill(job: Job) -> List[List[int]]:
# 1. Sort by magnitude (largest first)
# 2. stack until limit is reached
# 3. try smaller as long as possible
# 4. create new bar
# TODO: rewrite to use native map instead
# we are writing around in target sizes, prevent leaking changes to job
mutable_sizes = copy.deepcopy(job.sizes_as_list())
targets = sorted(mutable_sizes, reverse=True)
stocks = []
current_size = 0
current_stock = []
i_target = 0
while len(targets) > 0:
# nothing fit, next stock
if i_target >= len(targets):
# add local result
stocks.append(current_stock)
# reset
current_stock = []
current_size = 0
i_target = 0
current_target = targets[i_target]
# target fits inside current stock, transfer to results
if (current_size + current_target.length +
job.cut_width) < job.max_length:
current_stock.append(current_target.length)
current_size += current_target.length + job.cut_width
# remove empty entries
if current_target.quantity <= 1:
targets.remove(current_target)
else:
current_target.quantity -= 1
# try smaller
else:
i_target += 1
# apply last "forgotten" stock
if current_stock:
stocks.append(current_stock)
# trimming could be calculated from len(stocks) * length - sum(stocks)
return stocks
def _solve_FFD(job: Job) -> List[List[int]]:
# iterate over list of stocks
# put into first stock that it fits into
# 1. Sort by magnitude (largest first)
# 2. stack until limit is reached
# 3. try smaller as long as possible
# 4. create new bar
# TODO: rewrite to use native map instead
mutable_sizes = copy.deepcopy(job.sizes_as_list())
sizes = sorted(mutable_sizes, reverse=True)
stocks: List[List[int]] = [[]]
stock_lengths: List[int] = [0]
i_target = 0
while i_target < len(sizes):
current_size = sizes[i_target]
for i, stock in enumerate(stocks):
# step through existing stocks until current size fits
if (job.max_length - stock_lengths[i]) > current_size.length:
# add size
stock.append(current_size.length)
stock_lengths[i] += job.cut_width + current_size.length
break
else: # nothing fit, opening next bin
stocks.append([current_size.length])
stock_lengths.append(0)
# decrease/get next
if current_size.quantity <= 1:
i_target += 1
else:
current_size.quantity -= 1
return stocks