def training_model_1(train_rot=True):
print("model 1")
fitness_funcs = [
fn.Fitness("polygon overlay", fn.norm_overlap_pc,
fn.Fitness_Relation.pairwise_parent_child, 32,
training_params.fitness_cap,
training_params.fitness_regr_cond)
]
model = tm.model_var_pos()
if train_rot:
sibling_var_names = ["position", "rotation"]
else:
sibling_var_names = ["position"]
parent_var_names = ["shape0"]
return training(model=model,
fitness_funcs=fitness_funcs,
sibling_var_names=sibling_var_names,
parent_var_names=parent_var_names)
def training_model_5(train_pos=True):
print("model 5")
fitness_funcs = [
fn.Fitness("side alignment", fn.rotation_alignment_sb,
fn.Fitness_Relation.pairwise_siblings, 1,
training_params.fitness_cap,
training_params.fitness_regr_cond)
]
model = tm.model_var_rot()
if train_pos:
sibling_var_names = ["rotation", "position"]
else:
sibling_var_names = ["rotation"]
parent_var_names = ["shape0"]
return training(model=model,
fitness_funcs=fitness_funcs,
sibling_var_names=sibling_var_names,
parent_var_names=parent_var_names)
def training_model_3(train_size=True):
print("model 3")
fitness_funcs = [
fn.Fitness("centroid difference", fn.centroid_dist_absolute,
fn.Fitness_Relation.absolute, 1,
training_params.fitness_cap,
training_params.fitness_regr_cond)
]
#hierarchy,var_rot,var_nr_children)
model = tm.model_var_size()
if train_size:
sibling_var_names = ["size", "position"]
else:
sibling_var_names = ["position"]
parent_var_names = ["shape2", "shape4"]
return training(model=model,
fitness_funcs=fitness_funcs,
sibling_var_names=sibling_var_names,
parent_var_names=parent_var_names)
def fitness_order_MO_test():
training_params.title = "test for fitness order, fitness target distance, polgygon overlay"
print_params.verbose_iter = True
print_params.verbose_final_extra = True
for fo0 in range(4, 32, 4):
for fo1 in range(4, 32, 4):
print("fitness orders TD PO:", fo0, fo1)
training_params.extra_info = "TD order: " + str(
fo0) + " PO order: " + str(fo1)
fitness_funcs = [
fn.Targetting_Fitness("Target distances",
fn.min_dist_sb,
fn.Fitness_Relation.pairwise_siblings,
fo0,
0,
1,
target=2),
fn.Fitness("polygon overlay", fn.norm_overlap_pc,
fn.Fitness_Relation.pairwise_parent_child, fo1, 0,
1)
]
#hierarchy,var_rot,var_nr_children)
model = tm.model_var_pos(False)
sibling_var_names = ["position"]
parent_var_names = ["shape0"]
try:
training(model=model,
fitness_funcs=fitness_funcs,
sibling_var_names=sibling_var_names,
parent_var_names=parent_var_names)
except KeyboardInterrupt:
raise
except Exception as e:
print(e)
print_train_parameters()
training_params.reset()