init ref data

ana_func.py

@@ -12,10 +12,14 @@ class dataAnalyticFunc():
             return None
         self._raw_data = pd.DataFrame({'x_data':x_data,'y_data':y_data})
         if ref_data:
+            print(ref_data[:10])
             if len(ref_data) == len(self._raw_data):
                 self._raw_data['ref_data'] = ref_data
         # print(self._raw_data['y_data'].tolist())
 
+    # def find_peak(self):
+    #     pass
+
     def trigger_point(self, value_data, key_data, trigger, order = 1, drop = 1):
         if value_data not in list(self._raw_data) or key_data not in list(self._raw_data):
             print( 'There is no '+ str(value_data) + 'in datafram. ')
@@ -90,6 +94,7 @@ class dataAnalyticFunc():
 
     def guess_func(self,value_name='y_data', window = 10):
         win = window
+        print('guess_func')
         X = np.array([[math.pow(i,j) for j in range(4)] for i in np.linspace(-1*win,win,2*win+1)])
         J = np.linalg.inv(X.T.dot(X)).dot(X.T)
         slop_list = []

main.py

@@ -44,9 +44,7 @@ class Main():
           
           dict_writer.writerow(csv_data)
       elif input_data['mode'] == 3:
-        print('mode333')
         raw_data = CVmode_run()
-        print('mode3')
       else:
         for i in search_id:
           raw_data = slop_run(i, input_data['data_channel'], input_data['data']['window'])

test.py

@@ -38,17 +38,21 @@ def read_data(id,channel_list):
 
 def read_data_csv(file_name=0, start_row=0):
     df = pd.read_excel("read_file/2021-8-9-15-42-46-0_CV discussion.xlsx",skiprows = 63, usecols="B,D,F,H")
-    data = [list(df['Current[nA]']),list(df['Voltage[uV]'])]
+    data = [list(df['Current[nA]']),list(df['Voltage[uV]']),list(df['Unnamed: 7'])]
     # print(df)
     return data
 # read_data_csv()
 
 def CVmode_run():
-    df = read_data_csv()
+    df = read_data_csv() 
     print(df[0][:10])
-    CVmode = ana_func.dataAnalyticFunc(df[0], df[1])
+    data = [[df[0][i] for i in range(len(df[0])) if df[2][i] == 5], [df[1][i] for i in range(len(df[1])) if df[2][i] == 5]]
+    print(data[0][:10])
+    CVmode = ana_func.dataAnalyticFunc(data[1], data[0])
     cal_slop_data = CVmode.guess_func()
-    return [[i for i in range(len(df[0]))],cal_slop_data]
+
+    return [data[0],data[1]]
+    # return [[i for i in range(len(data[0]))],cal_slop_data]
     # return [[i for i in range(len(df[0]))],[i/50 for i in df[0]]]
 # CVmode()