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bot_diffs_4.pyx
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"""
Linear regression using the state and four backward finite differences.
Assumes 4 actions.
"""
from cython import cast, ccall, cclass, locals, returns, sizeof
from libc.stdlib cimport calloc, free
from libc.string cimport memcpy
from bot_base cimport BaseBot
from interface cimport c_do_action, c_get_state
@cclass
class Bot(BaseBot):
@staticmethod
def shapes(steps, actions, features):
return {
'free': (actions,),
'state0l': (actions, features),
'diffs0l': (actions, features),
'diffs1l': (actions, features),
'diffs2l': (actions, features),
'diffs3l': (actions, features)
}
def __cinit__(self, level, *args, **kwargs):
self.state1 = cast('float*', calloc(level['features'], sizeof(float)))
self.state2 = cast('float*', calloc(level['features'], sizeof(float)))
self.state3 = cast('float*', calloc(level['features'], sizeof(float)))
self.state4 = cast('float*', calloc(level['features'], sizeof(float)))
def __dealloc__(self):
free(self.state4)
free(self.state3)
free(self.state2)
free(self.state1)
@ccall
@returns('Bot')
@locals(state='bint', bot='Bot', state_size='int')
def clone(self, state=True):
bot = BaseBot.clone(self, state)
if state:
state_size = self.level['features'] * sizeof(float)
memcpy(bot.state1, self.state1, state_size)
memcpy(bot.state2, self.state2, state_size)
memcpy(bot.state3, self.state3, state_size)
memcpy(bot.state4, self.state4, state_size)
return bot
@ccall
@returns('void')
@locals(steps='int', step='int', action='int',
features='int', feature='int', state_size='int',
free='float[4]', state0l='float[:, ::1]',
diffs0l='float[:, ::1]', diffs1l='float[:, ::1]',
diffs2l='float[:, ::1]', diffs3l='float[:, ::1]',
values='float[4]',
state0='float*', state1='float*', state2='float*',
state3='float*', state4='float*',
state0f='float', state1f='float', state2f='float', state3f='float',
diffs0f='float', diffs1f='float', diffs2f='float', diffs3f='float')
def act(self, steps):
features = self.level['features']
state_size = features * sizeof(float)
free = self.params['free']
state0l = self.params['state0l']
diffs0l = self.params['diffs0l']
diffs1l = self.params['diffs1l']
diffs2l = self.params['diffs2l']
diffs3l = self.params['diffs3l']
state1 = self.state1
state2 = self.state2
state3 = self.state3
state4 = self.state4
action = -1
for step in range(steps):
values = free[:]
state0 = c_get_state()
for feature in range(features):
state0f = state0[feature]
state1f = state1[feature]
state2f = state2[feature]
state3f = state3[feature]
diffs0f = state0f - state1f
diffs1f = diffs0f - state1f + state2f
diffs2f = state0f - 3 * (state1f - state2f) - state3f
diffs3f = (state0f - 4 * (state1f + state3f) +
6 * state2f + state4[feature])
values[0] += (state0l[0, feature] * state0f +
diffs0l[0, feature] * diffs0f +
diffs1l[0, feature] * diffs1f +
diffs2l[0, feature] * diffs2f +
diffs3l[0, feature] * diffs3f)
values[1] += (state0l[1, feature] * state0f +
diffs0l[1, feature] * diffs0f +
diffs1l[1, feature] * diffs1f +
diffs2l[1, feature] * diffs2f +
diffs3l[1, feature] * diffs3f)
values[2] += (state0l[2, feature] * state0f +
diffs0l[2, feature] * diffs0f +
diffs1l[2, feature] * diffs1f +
diffs2l[2, feature] * diffs2f +
diffs3l[2, feature] * diffs3f)
values[3] += (state0l[3, feature] * state0f +
diffs0l[3, feature] * diffs0f +
diffs1l[3, feature] * diffs1f +
diffs2l[3, feature] * diffs2f +
diffs3l[3, feature] * diffs3f)
action = (((0 if values[0] > values[3] else 3)
if values[0] > values[2] else
(2 if values[2] > values[3] else 3))
if values[0] > values[1] else
((1 if values[1] > values[3] else 3)
if values[1] > values[2] else
(2 if values[2] > values[3] else 3)))
c_do_action(action)
state4, state3, state2, state1 = state3, state2, state1, state4
memcpy(state1, state0, state_size)
self.state1 = state1
self.state2 = state2
self.state3 = state3
self.state4 = state4
self.last_action = action