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fix process1.py #1

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7 changes: 7 additions & 0 deletions .gitignore
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Original file line number Diff line number Diff line change
@@ -0,0 +1,7 @@
.env
*.csv
*.npy
*.pth
*.pkl
*.pyc
*.txt
131 changes: 91 additions & 40 deletions WiGesture/data_process_example/process1.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,8 +3,8 @@
import os
import pandas as pd

root="./data"
data=[]
root = "./data"
data = []
csi_vaid_subcarrier_index = range(0, 52)

def handle_complex_data(x, valid_indices):
Expand All @@ -15,44 +15,95 @@ def handle_complex_data(x, valid_indices):
imag_parts.append(x[i * 2 - 1])
return np.array(real_parts) + 1j * np.array(imag_parts)

people_id = 0
for dataset_dir in os.listdir(root):
print(dataset_dir)
dataset_path = os.path.join(root, dataset_dir)
if not os.path.isdir(dataset_path):
continue

for static_dir in os.listdir(dataset_path):
print(static_dir)
static_path = os.path.join(dataset_path, static_dir)
if not os.path.isdir(static_path):
continue

for id_dir in os.listdir(static_path):
id_path = os.path.join(static_path, id_dir)
if not os.path.isdir(id_path):
continue

print(f"Processing ID: {id_dir}")
action_id = 0

# Verifique se há arquivos CSV diretamente no diretório ID
for item in os.listdir(id_path):
item_path = os.path.join(id_path, item)

# Se for um diretório, considere como um diretório de ação
if os.path.isdir(item_path):
action_dir = item
print(f" Action: {action_dir}")

# Processe os arquivos CSV dentro do diretório de ação
for file in os.listdir(item_path):
if not file.endswith('.csv'):
continue

file_path = os.path.join(item_path, file)
try:
df = pd.read_csv(file_path)
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,
'volunteer_name': id_dir,
'volunteer_id': people_id,
'action': action_dir,
'action_id': action_id,
'magnitude': np.array([np.array(a) for a in magnitude]),
'phase': np.array([np.array(a) for a in phase])
})
except Exception as e:
print(f" Error processing {file_path}: {e}")

action_id += 1

# Se for um arquivo CSV, processe-o diretamente
elif item.endswith('.csv'):
try:
df = pd.read_csv(item_path)
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,
'volunteer_name': id_dir,
'volunteer_id': people_id,
'action': 'unknown',
'action_id': 0,
'magnitude': np.array([np.array(a) for a in magnitude]),
'phase': np.array([np.array(a) for a in phase])
})
except Exception as e:
print(f" Error processing {item_path}: {e}")

people_id += 1


people_id=0
for people in os.listdir(root):
print(people)
action_id=0
path_people=os.path.join(root,people)
for action in os.listdir(path_people):
count=0
print(action)
path_action=os.path.join(path_people,action)
for file in os.listdir(path_action):
count+=1
path=os.path.join(path_action,file)
df = pd.read_csv(path)
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,
'volunteer_name': people,
'volunteer_id': people_id,
'action': action,
'action_id': action_id,
'magnitude': np.array([np.array(a) for a in magnitude]),
'phase': np.array([np.array(a) for a in phase])
})
# if count==4:
# break
action_id+=1
people_id+=1

# 保存全局字典为一个pickle文件
# Salve o dicionário global como um arquivo pickle
output_file = './csi_data.pkl'
with open(output_file, 'wb') as f:
pickle.dump(data, f)
pickle.dump(data, f)