Converted by Snapinator
it works but it takes alot of time to generate the map.
Original project made by guilhermeA2018 : https://scratch.mit.edu/projects/1164298057/data:image/png;base64,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Converted by Snapinator
it works but it takes alot of time to generate the map.
Original project made by guilhermeA2018 : https://scratch.mit.edu/projects/1164298057/
0
mX22mY22Distance260Actual heighthighest wall-180cellXcellZDir offset0.1130
Data400
CalculatedY180
d1
d2
cellX
cellZ180
Distance2-3-1808130
PlayerYDir20
500
PlayerXDir5
Xpos0.2
400
1
400
0
399
Zpos-0.2
400
1
400
0
399
Xpos-0.2
400
1
400
0
399
Zpos-0.2
400
1
400
0
399
fps1
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