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
forward turn turnLeft setHeading doFaceTowards gotoXY doGotoObject doGlide changeXPosition setXPosition changeYPosition setYPosition bounceOffEdge xPosition yPosition direction1
data
mapmany1
data lists
1
1
140,-140
1,0,0,0,0,0,0,0
1,1,0,0,0,0,0,0
0,1,0,0,0,0,0,0
0,1,1,0,0,0,0,0
0,0,1,1,0,0,0,0
0,0,0,1,1,0,0,0
0,0,0,0,1,1,0,0
0,0,0,0,0,1,1,1