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# coding: UTF-8
# Copyright 2009, 2010 Thomas Jourdan
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
from gettext import gettext as _
import random
import ka_debug
import model_random
import ka_factory
import model_locus
import model_layer
import model_constraintpool
SIZE_CONSTRAINT = 'sizeconstraint'
STATES_CONSTRAINT = 'statesconstraint'
COLORGAMUTTYPE_CONSTRAINT = 'colorgamuttypeconstraint'
LEFT_NEIGHBORS_CONSTRAINT = 'leftneighborsconstraint'
RIGHT_NEIGHBORS_CONSTRAINT = 'rightneighborsconstraint'
class LcaLayer(model_layer.Layer):
"""LcaLayer
inv: len(self.cell_colors) > 0
inv: self.size >= 1
inv: self.states >= 1
inv: self.left_neighbors >= 0
inv: self.right_neighbors >= 0
"""
cdef = [{'bind' : SIZE_CONSTRAINT,
'name' : 'Number of cells.',
'domain': model_constraintpool.INT_RANGE,
'min' : 2, 'max': 32},
{'bind' : STATES_CONSTRAINT,
'name' : 'Number of states.',
'domain': model_constraintpool.INT_RANGE,
'min' : 2, 'max': 6},
{'bind' : LEFT_NEIGHBORS_CONSTRAINT,
'name' : 'Number of left neighbors.',
'domain': model_constraintpool.INT_RANGE,
'min' : 0, 'max': 2},
{'bind' : RIGHT_NEIGHBORS_CONSTRAINT,
'name' : 'Number of right neighbors.',
'domain': model_constraintpool.INT_RANGE,
'min' : 0, 'max': 2},
{'bind' : COLORGAMUTTYPE_CONSTRAINT,
'name' : 'Permitted color gamut',
'domain': model_constraintpool.STRING_M_OF_N,
'enum' : ka_factory.get_factory('colorgamut').keys()},
]
def __init__(self, trunk):
"""linear cellular automata layer constructor
post: len(self.cell_colors) == self.states
"""
super(LcaLayer, self).__init__(trunk)
self.size = 2
self.states = 2
self.left_neighbors = 1
self.right_neighbors = 1
rsize = self.states ** (self.left_neighbors + 1 + self.right_neighbors)
self.rules = [0 for dummy in xrange(rsize)]
self.sequence_ordering = 0.25
colorgamut_factory = ka_factory.get_factory('colorgamut')
colorgamut_key = colorgamut_factory.keys()[0]
self.colorgamut = colorgamut_factory.create(colorgamut_key, self.path)
self.cell_colors = [self.colorgamut.get_randomized_color(self.path),
self.colorgamut.get_randomized_color(self.path), ]
def dot(self):
result = ""
anchor = ka_debug.dot_id(self) + ' -> '
for ref in [self.colorgamut, ]:
result += ka_debug.dot_ref(anchor, ref)
for ref in self.cell_colors:
result += ka_debug.dot_ref(anchor, ref)
return result
def __eq__(self, other):
"""Equality """
equal = isinstance(other, LcaLayer) \
and model_layer.Layer.__eq__(self, other) \
and self.size == other.size \
and self.states == other.states \
and self.left_neighbors == other.left_neighbors \
and self.right_neighbors == other.right_neighbors \
and self.sequence_ordering == other.sequence_ordering \
and len(self.cell_colors) == len(other.cell_colors)
if equal:
for index, rule in enumerate(self.rules):
equal = equal and rule == other.rules[index]
if equal:
for index, site_color in enumerate(self.cell_colors):
equal = equal and site_color == other.cell_colors[index]
return equal
def randomize(self):
"""Randomize the layers components.
post: len(self.cell_colors) == self.states
post: forall(self.rules, lambda f: 0 <= f < self.states)
"""
super(LcaLayer, self).randomize()
cpool = model_constraintpool.ConstraintPool.get_pool()
size_constraint = cpool.get(self, SIZE_CONSTRAINT)
self.size = model_random.randint_constrained(size_constraint)
states_constraint = cpool.get(self, STATES_CONSTRAINT)
self.states = model_random.randint_constrained(states_constraint)
left_neighbors_constraint = cpool.get(self, LEFT_NEIGHBORS_CONSTRAINT)
self.left_neighbors = model_random.randint_constrained(left_neighbors_constraint)
right_neighbors_constraint = cpool.get(self, RIGHT_NEIGHBORS_CONSTRAINT)
self.right_neighbors = model_random.randint_constrained(right_neighbors_constraint)
self.rules = [random.randrange(0, self.states) \
for dummy in xrange(self.get_numberof_rules())]
self.sequence_ordering = random.uniform(0.0, 1.0)
colorgamut_factory = ka_factory.get_factory('colorgamut')
colorgamuttype_constraint = cpool.get(self, COLORGAMUTTYPE_CONSTRAINT)
self.colorgamut = colorgamut_factory.create_random(colorgamuttype_constraint,
self.path)
self.colorgamut.randomize()
self.cell_colors = []
for dummy in range(self.states):
site_color = self.colorgamut.get_randomized_color(self.path)
self.cell_colors.append(site_color)
def fill_sequence(self, lca_state):
"""
post: forall(lca_state, lambda f: 0 <= f < self.states)
"""
seq_random = random.Random()
seq_random.seed(self.random_seed)
state = lca_state[0] = seq_random.randrange(0, self.states)
for index in xrange(1, len(lca_state)):
if seq_random.uniform(0.0, 1.0) < self.sequence_ordering:
state = seq_random.randrange(0, self.states)
lca_state[index] = state
def patch_rulesize(self):
rsize = self.get_numberof_rules()
if len(self.rules) > rsize:
self.rules = self.rules[:rsize]
while len(self.rules) < rsize:
self.rules.append(random.randrange(0, self.states))
self.rules = [x % self.states for x in self.rules]
def patch_colorsize(self):
if len(self.cell_colors) > self.states:
self.cell_colors = self.cell_colors[:self.states]
while len(self.cell_colors) < self.states:
site_color = self.colorgamut.get_randomized_color(self.path)
self.cell_colors.append(site_color)
def mutate(self):
"""Make small random changes to the layers components.
post: len(self.cell_colors) == self.states
post: forall(self.rules, lambda f: 0 <= f < self.states)
"""
super(LcaLayer, self).mutate()
cpool = model_constraintpool.ConstraintPool.get_pool()
size_constraint = cpool.get(self, SIZE_CONSTRAINT)
self.size = model_random.jitter_discret_constrained(
self.size, size_constraint)
states_constraint = cpool.get(self, STATES_CONSTRAINT)
self.states = model_random.jitter_discret_constrained(
self.states, states_constraint)
left_neighbors_constraint = cpool.get(self, LEFT_NEIGHBORS_CONSTRAINT)
self.left_neighbors = model_random.randint_constrained(left_neighbors_constraint)
self.left_neighbors = model_random.jitter_discret_constrained(
self.left_neighbors, left_neighbors_constraint)
right_neighbors_constraint = cpool.get(self, RIGHT_NEIGHBORS_CONSTRAINT)
self.right_neighbors = model_random.jitter_discret_constrained(
self.right_neighbors, right_neighbors_constraint)
self.patch_rulesize()
self.patch_colorsize()
self.colorgamut.mutate()
for cix in range(len(self.cell_colors)):
self.colorgamut.adjust_color(self.cell_colors[cix])
def swap_places(self):
"""Shuffle similar components."""
model_random.swap_places(self.cell_colors)
model_random.swap_places(self.rules)
def crossingover(self, other):
"""
pre: isinstance(other, LcaLayer)
pre: isinstance(self, LcaLayer)
# check for distinct references, needs to copy content, not references
post: __return__ is not self
post: __return__ is not other
post: model_locus.unique_check(__return__, self, other) == ''
post: len(__return__.cell_colors) == __return__.states
post: len(__return__.rules) == __return__.get_numberof_rules()
post: forall(__return__.rules, lambda f: 0 <= f < __return__.states)
"""
new_one = LcaLayer(self.get_trunk())
cross_sequence = self.crossingover_base(new_one, other, 6)
new_one.size = self.size if cross_sequence[0] \
else other.size
new_one.states = self.states if cross_sequence[1] \
else other.states
#TODO rules an die geƤnderten states anpassen.
new_one.left_neighbors = self.left_neighbors if cross_sequence[2] \
else other.left_neighbors
new_one.right_neighbors = self.right_neighbors if cross_sequence[3] \
else other.right_neighbors
new_one.colorgamut = other.colorgamut.copy() if cross_sequence[4] \
else self.colorgamut.copy()
new_one.sequence_ordering = self.sequence_ordering if cross_sequence[5] \
else other.sequence_ordering
new_one.rules = model_random.crossingover_nativeelement_list(self.rules, \
other.rules)
new_one.patch_rulesize()
new_one.cell_colors = model_random.crossingover_list(self.cell_colors,
other.cell_colors)
new_one.patch_colorsize()
for cix in range(len(new_one.cell_colors)):
new_one.colorgamut.adjust_color(new_one.cell_colors[cix])
return new_one
def render(self, task, ctx, width, height):
"""
pre: ctx is not None
pre: width > 0
pre: height > 0
pre: width == height
"""
self.begin_render(ctx, width, height)
lca_state = [0 for dummy in xrange(self.size)]
lca_nextstate = [0 for dummy in xrange(self.size)]
self.fill_sequence(lca_state)
delta = 1.0 / self.size
next_state = 0
x_pos = -0.5
for dummy in xrange(self.size):
y_pos = -0.5
for col in xrange(self.size):
ruleNumber = self.get_rule_index(lca_state, col)
next_state = lca_nextstate[col] = self.rules[ruleNumber]
rgba = self.cell_colors[next_state % len(self.cell_colors)].rgba
ctx.set_source_rgba(rgba[0], rgba[1], rgba[2], rgba[3])
ctx.rectangle(x_pos, y_pos, delta, delta)
ctx.fill()
y_pos += delta
x_pos += delta
# copy temporary cell array to actual cell array
lca_state = lca_nextstate[:]
def get_numberof_rules(self):
"""
post: __return__ >= 1
"""
return self.states ** (self.left_neighbors + 1 + self.right_neighbors)
def get_rule_index(self, lca_state, index):
"""
pre: len(lca_state) == self.size
pre: 0 <= index < self.size
post: 0 <= __return__ < len(self.rules)
"""
ruleNumber = 0
for nx in xrange(index - self.left_neighbors,
index + self.right_neighbors + 1):
ruleNumber *= self.states
ruleNumber += lca_state[nx % len(lca_state)]
return ruleNumber
def explain(self, formater):
formater.begin_list(_('Layer ') + self.__class__.__name__)
super(LcaLayer, self).explain(formater)
formater.text_item(_('Number of states: ') + str(self.states))
formater.text_item(_('Number of left neighbors: ') + str(self.left_neighbors))
formater.text_item(_('Number of right neighbors: ') + str(self.right_neighbors))
formater.text_item(_('Number of cells: ') + str(self.size))
formater.text_item(_('Stability of sequence ordering: ') + str(self.size))
self.colorgamut.explain(formater)
formater.color_array(self.cell_colors, _('Cell colors:'))
formater.end_list()
def copy(self):
"""The linear cellular automata layers copy constructor.
# check for distinct references, needs to copy content, not references
post: __return__ is not self
pre: len(self.cell_colors) == self.states
post: len(__return__.cell_colors) == __return__.states
"""
new_one = LcaLayer(self.get_trunk())
self.copy_base(new_one)
new_one.cell_colors = model_random.copy_list(self.cell_colors)
new_one.states = self.states
new_one.rules = self.rules[:]
new_one.size = self.size
new_one.left_neighbors = self.left_neighbors
new_one.right_neighbors = self.right_neighbors
new_one.sequence_ordering = self.sequence_ordering
new_one.colorgamut = self.colorgamut.copy()
return new_one
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