diff --git a/read_data.py b/read_data.py
index afda2db..4ae2fd1 100644
--- a/read_data.py
+++ b/read_data.py
@@ -1,3 +1,4 @@
+<<<<<<< HEAD
 import mne
 import scipy.io as scio
 import numpy as np
@@ -68,3 +69,75 @@ def read_data(data_path,i):
     data =np.array(data).reshape((48*22,751))
     label = EEG_label.repeat(22)
     return data,label
+=======
+import mne
+import scipy.io as scio
+import numpy as np
+
+def read_data(data_path,i):
+    data_path = data_path
+    DATA = scio.loadmat(data_path)
+    DATA = DATA["data"][0]
+    DATA = DATA[i] #第i次实验，从3到8
+    EEG_DATA = DATA["X"][0][0].transpose(1,0)
+    EEG_label = DATA['y'][0][0][:,0]
+
+    ch_names = ['Fz','Fp1','Fp2','AF3','AF4','AF7','AF8','C3','POz','Cz','PO3','C4','PO4','PO5','PO6','PO7','PO8','Oz','O1','Pz','P6','P7','EOG-left','EOG-central','EOG-right']
+    ch_types = ['eeg','eeg','eeg','eeg','eeg','eeg','eeg','eeg','eeg','eeg',
+                'eeg','eeg','eeg','eeg','eeg','eeg','eeg','eeg','eeg','eeg',
+                'eeg','eeg','eog','eog','eog']
+
+    info = mne.create_info(ch_names = ch_names,
+                            ch_types=ch_types,
+                            sfreq=250)
+    info.set_montage('standard_1020')
+    raw = mne.io.RawArray(EEG_DATA,info)
+
+    n_times = DATA["trial"][0][0][:,0] #时间戳
+    event = np.zeros((4,12),int)
+    v,b,n,m=0,0,0,0
+    for i in range (0,n_times.shape[0]):
+        if EEG_label[i]==1:
+            event[0,v]=n_times[i]
+            v+=1
+        if EEG_label[i]==2:
+            event[1,b]=n_times[i]
+            b+=1
+        if EEG_label[i]==3:
+            event[2,n]=n_times[i]
+            n+=1
+        if EEG_label[i]==4:
+            event[3,m]=n_times[i]
+            m+=1
+
+
+    events = np.zeros((48,3),int)
+    j=0
+    for i in range(events.shape[0]):
+        if i<12:
+            events[i][0]=event[0][j]
+            events[i][2]=1
+        elif i<24:
+            events[i][0]=event[1][j]
+            events[i][2]=2
+        elif i<36:
+            events[i][0]=event[2][j]
+            events[i][2]=3
+        elif i<48:
+            events[i][0]=event[3][j]
+            events[i][2]=4
+        j+=1
+        if j>=12:
+            j=0
+    events = sorted(events, key = lambda events: events[0])
+    event_id = dict(lefthand=1,righthand=2,feet=3,tongue=4)
+    picks = mne.pick_types(raw.info, meg=False, eeg=True, stim=False, eog=False, ecg=False,
+                    exclude='bads')
+    epochs = mne.Epochs(raw, events, event_id, tmin=3, tmax=6, proj=True,baseline=(None, None), picks=picks,preload=True)
+
+
+    data = epochs.get_data()
+    data =np.array(data).reshape((48*22,751))
+    label = EEG_label.repeat(22)
+    return data,label
+>>>>>>> 01d5a4b6f6a345f8700056939e9080b3b1b1a0e5