use pandas csv reader and use subplots

logdata_visualization/analyze.py

@@ -1,52 +1,47 @@
 import matplotlib.pyplot as plt
-import csv
+#import csv
+import pandas as pd
 
-x=[]
+import numpy as np
-speed_FrontL=[]
-speed_FrontR=[]
-speed_RearL=[]
-speed_RearR=[]
-
-fp = open('LOG00203c_replacedFrontLeftWheel.TXT')
-
-rdr = csv.DictReader(filter(lambda row: row[0]!='#', fp))
-for row in rdr:
-    #print(row)
-    x.append(float(row['cmd_FrontL']))
-
-    speed_FrontL.append(float(row['speed_FrontL']))
-    speed_FrontR.append(float(row['speed_FrontR']))
-    speed_RearL.append(float(row['speed_RearL']))
-    speed_RearR.append(float(row['speed_RearR']))
-fp.close()
 
 
-#plt.plot(x,y, label='Loaded from file!')
+import argparse
-scattersize=5
+
+parser = argparse.ArgumentParser(description='Analyzes fixed csv logs from bobbycar')
+parser.add_argument('-i', '--input', type=argparse.FileType('r'), required=True, help="input csv log file")
+args = parser.parse_args()
+
+df = pd.read_csv(args.input.name)
+
+x = df['timestamp']
+x = [i-x[0] for i in x] #offset time by starttime
+
+
+scattersize=1
 scatteralpha=0.1
-plt.scatter(x,speed_FrontL, s=scattersize, alpha=scatteralpha, label="speed_FrontL")
+
-plt.scatter(x,speed_FrontR, s=scattersize, alpha=scatteralpha, label="speed_FrontR")
+
-plt.scatter(x,speed_RearL, s=scattersize, alpha=scatteralpha, label="speed_RearL")
+fig, ax1 = plt.subplots()
-plt.scatter(x,speed_RearR, s=scattersize, alpha=scatteralpha, label="speed_RearR")
+
-plt.xlabel('cmd')
+ax2 = ax1.twinx()
-plt.ylabel('speed')
+
-plt.title('Interesting Graph\nCheck it out')
+
-plt.legend()
+#plt.scatter(x,df['rpm_FrontL'], s=scattersize, alpha=scatteralpha, label="rpm_FrontL")
+ax1.plot(x,np.array(df['vbat_Front']), c='b', alpha=0.5, label="vbat_Front")
+ax1.plot(x,np.array(df['vbat_Rear']), c='r', alpha=0.5, label="vbat_Rear")
+ax2.plot(x,np.array(df['cmd_FrontL']), c='r', alpha=0.5, label="cmd_FrontL")
+#plt.plot(x,np.array(df['currentConsumed']), c='g', alpha=0.5, label="currentConsumed")
+
+#plt.scatter(x,df['rpm_FrontR'], s=scattersize, alpha=scatteralpha, label="rpm_FrontR")
+
+ax1.set_xlabel('timestamp')
+#plt.ylabel('data')
+ax1.set_ylabel('first axis')
+ax2.set_ylabel('second axis')
+#plt.title('')
+ax1.legend(loc='upper left')
+ax2.legend(loc='upper right')
 plt.show()
 
 
-'''
+exit()
-with open(,'r') as csvfile:
-    plots = csv.reader(filter(lambda row: row[0]!='#', csvfile), delimiter=',')
-    for row in plots:
-        x.append(float(row[0]))
-        y.append(float(row[1]))
-
-plt.plot(x,y, label='Loaded from file!')
-plt.xlabel('x')
-plt.ylabel('y')
-plt.title('Interesting Graph\nCheck it out')
-plt.legend()
-plt.show()
-'''
-

logdata_visualization/logfix.py

@@ -107,8 +107,6 @@ if (args.consecutive):
         
         
 
-    print("")
-    print(inputFilenames)
     
 
 else:
@@ -150,7 +148,7 @@ for inputFilename in inputFilenames:
 
     linesStarttime+=_linesStarttime
     
-    print("Line in file="+str(len(inputlines)))
+    print("Lines in file="+str(len(inputlines)))
 
 assert len(lines)==len(linesStarttime), "Length of lines and linesStarttime does not match"