def __init__(self, df, resource_bounds=None, float_precision=6):
# set float round precision
self.float_precision = float_precision
self.df = np.round(df, float_precision)
if resource_bounds:
self.res_bounds = resource_bounds
else:
self.res_bounds = (
min([b for x in self.df.allocated_processors
for (b, e) in x]),
max([e for x in self.df.allocated_processors
for (b, e) in x]))
self.MaxProcs = total([self.res_bounds])
self.df['proc_alloc'] = self.df.allocated_processors.apply(total)
# Add missing columns
if 'starting_time' not in self.df.columns:
self.df['starting_time'] = \
self.df['submission_time'] + self.df['waiting_time']
if 'finish_time' not in self.df.columns:
self.df['finish_time'] = \
self.df['starting_time'] + self.df['execution_time']
# TODO check consistency on calculated columns...
# init cache
self._utilisation = None
self._queue = None
def detailed_utilisation(self):
df = self.free_intervals()
df['total'] = total([self.res_bounds]) - df.free_itvs.apply(total)
df.set_index("time", drop=True, inplace=True)
return df
