102 lines
4.0 KiB
Python
102 lines
4.0 KiB
Python
from copy import deepcopy
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from fn.op import foldr, call
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from SimCAD.engine.utils import engine_exception
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id_exception = engine_exception(KeyError, KeyError, None)
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class Executor:
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def __init__(self, policy_ops, policy_update_exception=id_exception, state_update_exception=id_exception):
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self.policy_ops = policy_ops # behavior_ops
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self.state_update_exception = state_update_exception
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self.policy_update_exception = policy_update_exception # behavior_update_exception
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# get_behavior_input
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def get_policy_input(self, var_dict, sub_step, sL, s, funcs):
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ops = self.policy_ops[::-1]
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def get_col_results(var_dict, sub_step, sL, s, funcs):
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return list(map(lambda f: f(var_dict, sub_step, sL, s), funcs))
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return foldr(call, get_col_results(var_dict, sub_step, sL, s, funcs))(ops)
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def apply_env_proc(self, env_processes, state_dict, sub_step):
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for state in state_dict.keys():
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if state in list(env_processes.keys()):
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env_state = env_processes[state]
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if (env_state.__name__ == '_curried') or (env_state.__name__ == 'proc_trigger'):
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state_dict[state] = env_state(sub_step)(state_dict[state])
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else:
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state_dict[state] = env_state(state_dict[state])
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# mech_step
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def partial_state_update(self, var_dict, sub_step, sL, state_funcs, policy_funcs, env_processes, time_step, run):
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last_in_obj = sL[-1]
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_input = self.policy_update_exception(self.get_policy_input(var_dict, sub_step, sL, last_in_obj, policy_funcs))
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# ToDo: add env_proc generator to `last_in_copy` iterator as wrapper function
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last_in_copy = dict(
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[
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self.state_update_exception(f(var_dict, sub_step, sL, last_in_obj, _input)) for f in state_funcs
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]
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)
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for k in last_in_obj:
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if k not in last_in_copy:
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last_in_copy[k] = last_in_obj[k]
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del last_in_obj
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self.apply_env_proc(env_processes, last_in_copy, last_in_copy['timestamp'])
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last_in_copy["mech_step"], last_in_copy["time_step"], last_in_copy['run'] = sub_step, time_step, run
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sL.append(last_in_copy)
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del last_in_copy
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return sL
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# mech_pipeline
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def state_update_pipeline(self, var_dict, states_list, configs, env_processes, time_step, run):
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sub_step = 0
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states_list_copy = deepcopy(states_list)
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genesis_states = states_list_copy[-1]
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genesis_states['mech_step'], genesis_states['time_step'] = sub_step, time_step
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states_list = [genesis_states]
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sub_step += 1
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for config in configs:
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s_conf, p_conf = config[0], config[1]
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states_list = self.partial_state_update(var_dict, sub_step, states_list, s_conf, p_conf, env_processes, time_step, run)
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sub_step += 1
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time_step += 1
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return states_list
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def run_pipeline(self, var_dict, states_list, configs, env_processes, time_seq, run):
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time_seq = [x + 1 for x in time_seq]
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simulation_list = [states_list]
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for time_step in time_seq:
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pipe_run = self.state_update_pipeline(var_dict, simulation_list[-1], configs, env_processes, time_step, run)
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_, *pipe_run = pipe_run
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simulation_list.append(pipe_run)
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return simulation_list
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# ToDo: Muiltithreaded Runs
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def simulation(self, var_dict, states_list, configs, env_processes, time_seq, runs):
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pipe_run = []
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for run in range(runs):
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run += 1
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states_list_copy = deepcopy(states_list)
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head, *tail = self.run_pipeline(var_dict, states_list_copy, configs, env_processes, time_seq, run)
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genesis = head.pop()
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genesis['mech_step'], genesis['time_step'], genesis['run'] = 0, 0, run
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first_timestep_per_run = [genesis] + tail.pop(0)
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pipe_run += [first_timestep_per_run] + tail
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del states_list_copy
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return pipe_run
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