| | 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)
|
| |
|
| |
|
