Datasets:
File size: 1,612 Bytes
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import numpy as np
import pickle
import os
import pandas as pd
root="./data/"
data=[]
csi_vaid_subcarrier_index = range(0, 52)
def handle_complex_data(x, valid_indices):
real_parts = []
imag_parts = []
for i in valid_indices:
real_parts.append(x[i * 2])
imag_parts.append(x[i * 2 - 1])
return np.array(real_parts) + 1j * np.array(imag_parts)
for people_num in os.listdir(root):
if len(people_num)>1:
continue
print(people_num)
path=os.path.join(root,people_num)
for file in os.listdir(path):
if file[-3:] != "csv":
continue
print(file)
df = pd.read_csv(os.path.join(path,file))
df.dropna(inplace=True)
df['data'] = df['data'].apply(lambda x: eval(x))
complex_data = df['data'].apply(lambda x: handle_complex_data(x, csi_vaid_subcarrier_index))
magnitude = complex_data.apply(lambda x: np.abs(x))
phase = complex_data.apply(lambda x: np.angle(x, deg=True))
time = np.array(df['timestamp'])
local_time = np.array(df['local_timestamp'])
data.append({
'csi_time':time,
'csi_local_time':local_time,
'people_num': eval(people_num),
'magnitude': np.array([np.array(a) for a in magnitude]),
'phase': np.array([np.array(a) for a in phase]),
'CSI': np.array([np.array(a) for a in complex_data])
})
# 保存全局字典为一个pickle文件
output_file = './csi_data.pkl'
with open(output_file, 'wb') as f:
pickle.dump(data, f) |