diff --git a/tools/easy.py b/tools/easy.py
index 9cf4362b..b2d9dc23 100755
--- a/tools/easy.py
+++ b/tools/easy.py
@@ -5,75 +5,75 @@
 from subprocess import *
 
 if len(sys.argv) <= 1:
-	print('Usage: {0} training_file [testing_file]'.format(sys.argv[0]))
-	raise SystemExit
+    print('Usage: {0} training_file [testing_file]'.format(sys.argv[0]))
+    raise SystemExit
 
 # svm, grid, and gnuplot executable files
-
 is_win32 = (sys.platform == 'win32')
 if not is_win32:
-	svmscale_exe = "../svm-scale"
-	svmtrain_exe = "../svm-train"
-	svmpredict_exe = "../svm-predict"
-	grid_py = "./grid.py"
-	gnuplot_exe = "/usr/bin/gnuplot"
+    svmscale_exe = "../svm-scale"
+    svmtrain_exe = "../svm-train"
+    svmpredict_exe = "../svm-predict"
+    grid_py = "./grid.py"
+    gnuplot_exe = "/usr/bin/gnuplot"
 else:
-        # example for windows
-	svmscale_exe = r"..\windows\svm-scale.exe"
-	svmtrain_exe = r"..\windows\svm-train.exe"
-	svmpredict_exe = r"..\windows\svm-predict.exe"
-	gnuplot_exe = r"c:\tmp\gnuplot\binary\pgnuplot.exe"
-	grid_py = r".\grid.py"
+    # example for windows
+    svmscale_exe = r"..\windows\svm-scale.exe"
+    svmtrain_exe = r"..\windows\svm-train.exe"
+    svmpredict_exe = r"..\windows\svm-predict.exe"
+    gnuplot_exe = r"c:\tmp\gnuplot\binary\pgnuplot.exe"
+    grid_py = r".\grid.py"
 
-assert os.path.exists(svmscale_exe),"svm-scale executable not found"
-assert os.path.exists(svmtrain_exe),"svm-train executable not found"
-assert os.path.exists(svmpredict_exe),"svm-predict executable not found"
-assert os.path.exists(gnuplot_exe),"gnuplot executable not found"
-assert os.path.exists(grid_py),"grid.py not found"
+assert os.path.exists(svmscale_exe), "svm-scale executable not found"
+assert os.path.exists(svmtrain_exe), "svm-train executable not found"
+assert os.path.exists(svmpredict_exe), "svm-predict executable not found"
+assert os.path.exists(gnuplot_exe), "gnuplot executable not found"
+assert os.path.exists(grid_py), "grid.py not found"
 
 train_pathname = sys.argv[1]
-assert os.path.exists(train_pathname),"training file not found"
+assert os.path.exists(train_pathname), "training file not found"
 file_name = os.path.split(train_pathname)[1]
 scaled_file = file_name + ".scale"
 model_file = file_name + ".model"
 range_file = file_name + ".range"
 
 if len(sys.argv) > 2:
-	test_pathname = sys.argv[2]
-	file_name = os.path.split(test_pathname)[1]
-	assert os.path.exists(test_pathname),"testing file not found"
-	scaled_test_file = file_name + ".scale"
-	predict_test_file = file_name + ".predict"
+    test_pathname = sys.argv[2]
+    file_name = os.path.split(test_pathname)[1]
+    assert os.path.exists(test_pathname), "testing file not found"
+    scaled_test_file = file_name + ".scale"
+    predict_test_file = file_name + ".predict"
 
 cmd = '{0} -s "{1}" "{2}" > "{3}"'.format(svmscale_exe, range_file, train_pathname, scaled_file)
 print('Scaling training data...')
-Popen(cmd, shell = True, stdout = PIPE).communicate()	
+Popen(cmd, shell=True, stdout=PIPE).communicate()
 
 cmd = '{0} -svmtrain "{1}" -gnuplot "{2}" "{3}"'.format(grid_py, svmtrain_exe, gnuplot_exe, scaled_file)
 print('Cross validation...')
-f = Popen(cmd, shell = True, stdout = PIPE).stdout
+f = Popen(cmd, shell=True, stdout=PIPE).stdout
 
 line = ''
 while True:
-	last_line = line
-	line = f.readline()
-	if not line: break
-c,g,rate = map(float,last_line.split())
+    last_line = line
+    line = f.readline()
+    if not line:
+        break
+c, g, rate = map(float, last_line.split())
 
-print('Best c={0}, g={1} CV rate={2}'.format(c,g,rate))
+print('Best c={0}, g={1} CV rate={2}'.format(c, g, rate))
 
-cmd = '{0} -c {1} -g {2} "{3}" "{4}"'.format(svmtrain_exe,c,g,scaled_file,model_file)
+cmd = '{0} -c {1} -g {2} "{3}" "{4}"'.format(svmtrain_exe, c, g, scaled_file, model_file)
 print('Training...')
-Popen(cmd, shell = True, stdout = PIPE).communicate()
+Popen(cmd, shell=True, stdout=PIPE).communicate()
 
 print('Output model: {0}'.format(model_file))
 if len(sys.argv) > 2:
-	cmd = '{0} -r "{1}" "{2}" > "{3}"'.format(svmscale_exe, range_file, test_pathname, scaled_test_file)
-	print('Scaling testing data...')
-	Popen(cmd, shell = True, stdout = PIPE).communicate()	
+    cmd = '{0} -r "{1}" "{2}" > "{3}"'.format(svmscale_exe, range_file, test_pathname, scaled_test_file)
+    print('Scaling testing data...')
+    Popen(cmd, shell=True, stdout=PIPE).communicate()
 
-	cmd = '{0} "{1}" "{2}" "{3}"'.format(svmpredict_exe, scaled_test_file, model_file, predict_test_file)
-	print('Testing...')
-	Popen(cmd, shell = True).communicate()	
+    cmd = '{0} "{1}" "{2}" "{3}"'.format(svmpredict_exe, scaled_test_file, model_file, predict_test_file)
+    print('Testing...')
+    Popen(cmd, shell=True).communicate()
 
-	print('Output prediction: {0}'.format(predict_test_file))
+    print('Output prediction: {0}'.format(predict_test_file))