State machine search algorithm in Python
So a few years back I posted the Vanilla Queen algorithm in pseudo code. I was a little bit crazy at the time, and I don't understand it fully anymore, but still asked AI to turn the pseudo code into Python.
Can you turn this pseudo code into runnable Python code please?
// DEFINING WATER
define c+ as up
define c- as down
define level as c(now())
define wave as {
wave(0) as surface,
wave(n, surface) as wave(level, {c+,c-})
};
// SET X, Y
assign x = me
assign y = me
x(me) = me(x)
y(me) = me( x(level(y)) )
// GOT IT
// NOW LETS DIVE TO THE BOTTOM AND COME up
run()
{
define I as me;
I go(diving(wave(0), wave(0)));
return( go( diving(c+)));
}
// DEEP DIVING ALONE
func diving(I) {
I := wave(n)
}
it came up with this:
import datetime
class Entity:
def __init__(self, name="me"):
self.name = name
self.x = self
self.y = self
def get_level(self):
# Representing 'c(now())' as a timestamp-based value
return datetime.datetime.now().second
def wave(self, n, surface="surface"):
"""
Interpreting the wave logic: wave(0) is the surface,
otherwise it fluctuates between up (c+) and down (c-).
"""
if n == 0:
return surface
# Alternating states based on level
return "up" if self.get_level() % 2 == 0 else "down"
def diving(self, current_wave):
"""Sets the entity's state to a new wave depth."""
print(f"Deep diving alone... current depth: {current_wave}")
return self.wave(1) # Moving to wave(n)
def run(self):
print("--- Starting the Dive ---")
# assign x = me, y = me logic
self.x = self
self.y = self
# I go(diving(wave(0), wave(0)))
surface = self.wave(0)
depth_reached = self.diving(surface)
# return( go( diving(c+)))
# Interpreting c+ as 'up'
final_state = "up"
print(f"Returning to the surface: {final_state}")
return final_state
# GOT IT. NOW LETS DIVE.
if __name__ == "__main__":
subject = Entity()
result = subject.run()
print(f"Dive complete. Final status: {result}")
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