def get_free_slots_by_resources(x):
for res in range(resource_intervals[0], resource_intervals[1] + 1):
if intersection(x.allocated_processors, [(res, res)]):
free_resources_gaps[res].append(x.execution_time)
def free_slots(self, begin_time=0, end_time=None):
'''
:returns: a DataFrame (compatible with a JobSet) that contains all
the not overlapping square free slots of this JobSet maximzing the
time. It can be transform to a JobSet to be plot as gantt chart.
'''
# slots_time contains tuple of
# (slot_begin_time,free_resources_intervals)
free_interval_serie = self.free_intervals(begin_time, end_time)
slots_time = [(free_interval_serie.time[0],
[self.res_bounds])]
new_slots_time = slots_time
columns = ['jobID', 'allocated_processors',
'starting_time', 'finish_time', 'execution_time',
'submission_time']
free_slots_df = pd.DataFrame(columns=columns)
prev_free_itvs = [self.res_bounds]
slots = 0
for i, curr_row in free_interval_serie.iterrows():
if i == 0:
continue
new_slots_time = []
curr_time = curr_row.time
taken_resources = difference(prev_free_itvs,
curr_row.free_itvs)
freed_resources = difference(curr_row.free_itvs,
prev_free_itvs)
if i == len(free_interval_serie) - 1:
taken_resources = [self.res_bounds]
if taken_resources:
# slot ends: store it and update free slot
for begin_time, itvs in slots_time:
to_update = intersection(itvs, taken_resources)
if to_update != []:
# store new slots
slots = slots + 1
new_slot = [str(slots),
to_update,
begin_time,
curr_time,
curr_time - begin_time,
begin_time]
free_slots_df.loc[slots] = new_slot
# remove free slots
free_res = difference(itvs, to_update)
if free_res != []:
new_slots_time.append((begin_time, free_res))
else:
new_slots_time.append((begin_time, itvs))
if freed_resources:
# slots begin: udpate free slot
if not new_slots_time:
new_slots_time = slots_time
new_slots_time.append((curr_time, freed_resources))
# update previous
prev_free_itvs = curr_row.free_itvs
# clean slots_free
slots_time = new_slots_time
return free_slots_df
