def process(self, datasetdscr, dataset):
removekeys = []
for sid, info in datasetdscr.sensor_desc.iterrows():
last = {}
last['value'] = -1000
if (info.Nominal | info.OnChange):
continue
xs = dataset.s_events.loc[dataset.s_events.SID == sid]
min = xs.value.min()
max = xs.value.max()
#print(min, max, max-min)
invalid_changes = (max - min) * 0.1
for key, event in xs.iterrows():
invalid_changes = event['value'] * .1
if abs(last['value'] - event['value']) < invalid_changes:
#print (event)
removekeys.append(key)
continue
last = event
# print(removekeys)
d = Data(dataset.name)
d.s_events = dataset.s_events.drop(removekeys)
d.a_events = dataset.a_events
d.s_event_list = d.s_events.values
d.acts = dataset.acts
d.act_map = dataset.act_map
return d
def justifySet(self, acts, Train, add_other_action=False):
inp = [Train]
out = []
if (acts[0] != 0):
acts.insert(0, 0)
act_map = {a: i for i, a in enumerate(acts)}
for dtype in inp:
ndtype = Data(dtype.name)
ndtype.s_events = dtype.s_events
ndtype.a_events = dtype.a_events.copy()
ndtype.a_events.Activity = dtype.a_events.Activity.apply(
lambda x: act_map[x]
if x in act_map else (len(acts) if add_other_action else 0))
out.append(ndtype)
ndtype.act_map = act_map
ndtype.acts = acts
return out[0] #Train