neuropercolation/cellular_automaton/cell_state.py
2019-02-17 11:11:27 +01:00

122 lines
4.9 KiB
Python

from multiprocessing import RawArray, RawValue
from ctypes import c_float, c_bool
class CellState:
"""
This is the base class for all cell states.
When using the cellular automaton display, inherit this class and implement get_state_draw_color.
"""
_state_save_slot_count = 2
def __init__(self, initial_state=(0., ), draw_first_state=True):
self._state_slots = [list(initial_state) for i in range(self.__class__._state_save_slot_count)]
self._active = [False for i in range(self.__class__._state_save_slot_count)]
self._active[0] = True
self._dirty = draw_first_state
def is_active(self, current_evolution_step):
""" Returns the active status for the requested evolution_step
:param current_evolution_step: The evolution_step of interest.
:return: True if the cell state is set active for this evolution_step.
"""
return self._active[self._calculate_slot(current_evolution_step)]
def set_active_for_next_evolution_step(self, current_evolution_step):
""" Sets the cell active for the next evolution_step, so it will be evolved.
:param current_evolution_step: The current evolution_step index.
:return:
"""
self._active[self._calculate_slot(current_evolution_step + 1)] = True
def is_set_for_redraw(self):
""" States if this state should be redrawn.
:return: True if redraw is needed.
"""
return self._dirty
def was_redrawn(self):
""" Remove the state from redraw cycle until next state change """
self._dirty = False
def get_state_of_last_evolution_step(self, current_evolution_step):
return self.get_state_of_evolution_step(current_evolution_step - 1)
def get_state_of_evolution_step(self, evolution_step):
""" Returns the state of the evolution_step.
:param evolution_step: Uses the evolution_step index, to differ between concurrent states.
:return The state of this evolution_step.
"""
return self._state_slots[self._calculate_slot(evolution_step)]
def set_state_of_evolution_step(self, new_state, evolution_step):
""" Sets the new state for the evolution_step.
:param new_state: The new state to set.
:param evolution_step: The evolution_step index, to differ between concurrent states.
:return True if the state really changed.
"""
changed = self._set_new_state_if_valid(new_state, evolution_step)
self._dirty |= changed
self._active[self._calculate_slot(evolution_step)] = False
return changed
def _set_new_state_if_valid(self, new_state, evolution_step):
current_state = self.get_state_of_evolution_step(evolution_step)
if len(new_state) != len(current_state):
raise IndexError("State length may not change!")
self.__change_current_state_values(current_state, new_state)
return self.__did_state_change(evolution_step)
@staticmethod
def __change_current_state_values(current_state, new_state):
for i, ns in enumerate(new_state):
if current_state[i] != ns:
current_state[i] = ns
def __did_state_change(self, evolution_step):
for a, b in zip(self.get_state_of_evolution_step(evolution_step),
self.get_state_of_last_evolution_step(evolution_step)):
if a != b:
return True
return False
def get_state_draw_color(self, evolution_step):
""" When implemented should return the color representing the requested state.
:param evolution_step: Requested evolution_step.
:return: Color of the state as rgb tuple
"""
raise NotImplementedError
@classmethod
def _calculate_slot(cls, evolution_step):
return evolution_step % cls._state_save_slot_count
class SynchronousCellState(CellState):
"""
CellState version using shared values for multi processing purpose.
"""
def __init__(self, initial_state=(0., ), draw_first_state=True):
super().__init__(initial_state, draw_first_state)
self._state_slots = [RawArray(c_float, initial_state) for i in range(self.__class__._state_save_slot_count)]
self._active = [RawValue(c_bool, False) for i in range(self.__class__._state_save_slot_count)]
self._active[0].value = True
self._dirty = RawValue(c_bool, draw_first_state)
def set_active_for_next_evolution_step(self, current_evolution_step):
self._active[self._calculate_slot(current_evolution_step + 1)].value = True
def is_set_for_redraw(self):
return self._dirty.value
def was_redrawn(self):
self._dirty.value = False
def set_state_of_evolution_step(self, new_state, evolution_step):
changed = self._set_new_state_if_valid(new_state, evolution_step)
self._dirty.value |= changed
self._active[self._calculate_slot(evolution_step)].value = False
return changed