Update README.md

README.md

@@ -40,28 +40,29 @@ Earlier packages may work but are not guaranteed to be supported.
 ```python
 import time
 from pybci import PyBCI
+if __name__ == '__main__':
 bci = PyBCI(createPseudoDevice=True) # set default epoch timing, looks for first available lsl marker stream and all data streams
-bci.TrainMode() # assume both marker and datastreams available to start training on received epochs
-accuracy = 0
-try:
-    while(True): # training based on couple epochs more then min threshold for classifying
-        currentMarkers = bci.ReceivedMarkerCount() # check to see how many received epochs, if markers sent are too close together will be ignored till done processing
-        time.sleep(1) # wait for marker updates
-        print("Markers received: " + str(currentMarkers) +" Class accuracy: " + str(accuracy), end="\r")
-        if len(currentMarkers) > 1:  # check there is more then one marker type received
-            if min([currentMarkers[key][1] for key in currentMarkers]) > bci.minimumEpochsRequired:
-                classInfo = bci.CurrentClassifierInfo() # hangs if called too early
-                accuracy = classInfo["accuracy"]
-            if min([currentMarkers[key][1] for key in currentMarkers]) > bci.minimumEpochsRequired+1:  
-                bci.TestMode()
-                break
-    while True: # now sufficient epochs gathered start testing
-        markerGuess = bci.CurrentClassifierMarkerGuess() # when in test mode only y_pred returned
-        guess = [key for key, value in currentMarkers.items() if value[0] == markerGuess]
-        print("Current marker estimation: " + str(guess), end="\r")
-        time.sleep(0.5)
-except KeyboardInterrupt: # allow user to break while loop
-    pass
+    bci.TrainMode() # assume both marker and datastreams available to start training on received epochs
+    accuracy = 0
+    try:
+        while(True): # training based on couple epochs more then min threshold for classifying
+            currentMarkers = bci.ReceivedMarkerCount() # check to see how many received epochs, if markers sent are too close together will be ignored till done processing
+            time.sleep(1) # wait for marker updates
+            print("Markers received: " + str(currentMarkers) +" Class accuracy: " + str(accuracy), end="\r")
+            if len(currentMarkers) > 1:  # check there is more then one marker type received
+                if min([currentMarkers[key][1] for key in currentMarkers]) > bci.minimumEpochsRequired:
+                    classInfo = bci.CurrentClassifierInfo() # hangs if called too early
+                    accuracy = classInfo["accuracy"]
+                if min([currentMarkers[key][1] for key in currentMarkers]) > bci.minimumEpochsRequired+1:  
+                    bci.TestMode()
+                    break
+        while True: # now sufficient epochs gathered start testing
+            markerGuess = bci.CurrentClassifierMarkerGuess() # when in test mode only y_pred returned
+            guess = [key for key, value in currentMarkers.items() if value[0] == markerGuess]
+            print("Current marker estimation: " + str(guess), end="\r")
+            time.sleep(0.5)
+    except KeyboardInterrupt: # allow user to break while loop
+        pass
 ```
 
 ## Background Information