def load():
gt = [(65, 141), (157, 187), (260, 304), (324, 326), (380, 393),
(455, 470), (475, 485), (505, 555), (666, 807), (814, 888),
(903, 929)]
a = [
(66, 73), (78, 126), (135, 147), (175, 186), (225, 236), (274, 318),
(349, 354), (366, 372), (423, 436), (453, 460), (467, 473), (487, 493),
(501, 506), (515, 525), (531, 542), (545, 563), (576, 580), (607, 611),
(641, 646), (665, 673), (678, 898), (907, 933)
]
b = [(63, 136), (166, 188), (257, 310), (451, 473), (519, 546), (663, 916)]
dataset = Data('test')
dataset.activities = ['null', 'Act']
dataset.activities_map = {0: 'null', 1: 'Act'}
dataset.activities_map_inverse = {'null': 0, 'Act': 1}
dataset.activity_events = pd.DataFrame(
columns=["StartTime", "EndTime", "Activity", 'Duration'])
init = pd.to_datetime('1/1/2020')
for k in gt:
actevent = {
"StartTime": init + pd.to_timedelta(str(k[0]) + 's'),
"EndTime": init + pd.to_timedelta(str(k[1]) + 's'),
"Activity": 1,
'Duration': pd.to_timedelta(str(k[1] - k[0]) + 's')
}
dataset.activity_events = dataset.activity_events.append(
actevent, ignore_index=True)
aevents = pd.DataFrame(
columns=["StartTime", "EndTime", "Activity", 'Duration'])
for k in a:
actevent = {
"StartTime": init + pd.to_timedelta(str(k[0]) + 's'),
"EndTime": init + pd.to_timedelta(str(k[1]) + 's'),
"Activity": 1,
'Duration': pd.to_timedelta(str(k[1] - k[0]) + 's')
}
aevents = aevents.append(actevent, ignore_index=True)
bevents = pd.DataFrame(
columns=["StartTime", "EndTime", "Activity", 'Duration'])
for k in b:
actevent = {
"StartTime": init + pd.to_timedelta(str(k[0]) + 's'),
"EndTime": init + pd.to_timedelta(str(k[1]) + 's'),
"Activity": 1,
'Duration': pd.to_timedelta(str(k[1] - k[0]) + 's')
}
bevents = bevents.append(actevent, ignore_index=True)
return dataset, aevents, bevents
def create(real, pred, filename):
evalres = [{}]
evalres[0]['test'] = Data('test res')
evalres[0]['test'].real_events = vs.convert2event(real)
evalres[0]['test'].pred_events = vs.convert2event(pred)
evalres[0]['test'].quality = {}
dataset = Data('MyDataset')
dataset.activities = ['None', 'Act']
dataset.activity_events = evalres[0]['test'].real_events
dataset.activities_map_inverse = {
k: v
for v, k in enumerate(dataset.activities)
}
dataset.activities_map = {v: k for v, k in enumerate(dataset.activities)}
dataset.sensor_events = pd.DataFrame()
runinfo = filename
utils.saveState([runinfo, dataset, evalres], filename)