|
|
import numpy as np
|
|
|
import pickle
|
|
|
|
|
|
|
|
|
result=[]
|
|
|
|
|
|
pad=[-1000]*52
|
|
|
loacl_gap=10000
|
|
|
|
|
|
|
|
|
with open("./csi_data.pkl", 'rb') as f:
|
|
|
csi = pickle.load(f)
|
|
|
|
|
|
for data in csi:
|
|
|
csi_time=data['csi_time']
|
|
|
local_time=data['csi_local_time']
|
|
|
magnitude=data['magnitude']
|
|
|
phase=data['phase']
|
|
|
people=data['volunteer_id']
|
|
|
action=data['action_id']
|
|
|
|
|
|
last_local=None
|
|
|
current_magnitude=[]
|
|
|
current_phase=[]
|
|
|
current_timestamp=[]
|
|
|
for i in range(len(csi_time)):
|
|
|
if last_local is None:
|
|
|
last_local=local_time[i]
|
|
|
current_magnitude.append(magnitude[i])
|
|
|
current_phase.append(phase[i])
|
|
|
current_timestamp.append(local_time[i])
|
|
|
else:
|
|
|
local = local_time[i]
|
|
|
num=round((local-last_local-loacl_gap)/loacl_gap)
|
|
|
if num>0:
|
|
|
delta=(local-last_local)/(num+1)
|
|
|
for j in range(num):
|
|
|
current_magnitude.append(pad)
|
|
|
current_phase.append(pad)
|
|
|
current_timestamp.append(current_timestamp[-1] + delta)
|
|
|
current_magnitude.append(magnitude[i])
|
|
|
current_phase.append(phase[i])
|
|
|
current_timestamp.append(local_time[i])
|
|
|
last_local=local
|
|
|
|
|
|
|
|
|
result.append({
|
|
|
'time': np.array(current_timestamp),
|
|
|
'people': people,
|
|
|
'action': action,
|
|
|
'magnitude': np.array(current_magnitude),
|
|
|
'phase': np.array(current_phase)
|
|
|
})
|
|
|
|
|
|
output_file = './data_sequence.pkl'
|
|
|
with open(output_file, 'wb') as f:
|
|
|
pickle.dump(result, f)
|
|
|
|
|
|
|
