def _set_optimizer_type(self, new_optimizer_type: type):
"""
changes the current type of Optimizer and creates and applies a Optimizer of that type.
@Warnings Should only be called via set_action_type which handles type checking.
Parameters
----------
new_optimizer_type : t.Type[Filter]
type of the new Filter
Returns
-------
NoReturn
"""
if new_optimizer_type == None:
self.current_optimizer_type = None
self.my_optimizer = None
return
if not new_optimizer_type in self.available_optimizer_types + [None]:
raise TypeError(str(new_optimizer_type) + ' is not an available type of Optimizer')
self.my_optimizer = new_optimizer_type(self.selected_atoms)
# SWITCHTABLE FOR input function
input_functions = u.do_nothing()
if isinstance(self.my_optimizer, Optimizer.GreedyGraphOptimizer):
input_function = qt_dialogs.create_multi_dialog(
title='Parameters for GreedyGraphOptimizer', \
inputs=['number of restraints', 'maximal distance of restraints',
'tree-algorithm', 'optimize molecules pairs by'], \
options={'tree-algorithm': ['minmax', 'cog', 'prim', "biased_avg"],
'optimize molecules pairs by': ['None', 'convex_hull',
'pca_2d']}, \
default={'number of restraints': '4',
'maximal distance of restraints': '1.0',
'algorithm': 'minmax',
'optimize molecules pairs by': 'convex_hull'})
elif isinstance(self.my_optimizer, Optimizer.BruteForceRingOptimzer):
input_function = qt_dialogs.create_multi_dialog(
title='Parameters for BruteForceOptimizer', \
inputs=['number of restraints', 'maximal distance of restraints',
'algorithm', 'optimize molecules pairs by'], \
options={'algorithm': ['convex_hull', 'pca'],
'optimize molecules pairs by': ['None', 'convex_hull',
'pca_2d']}, \
default={'number of restraints': '4',
'maximal distance of restraints': '1.2', 'algorithm': 'pca',
'optimize molecules pairs by': 'pca_2d'})
elif isinstance(self.my_optimizer, Optimizer.MetaMoleculeRingOptimizer):
input_function = qt_dialogs.create_multi_dialog(
title='Parameters for BestMoleculeRingOptimizer', \
inputs=['number of restraints', 'maximal distance of restraints',
'algorithm', 'optimize molecules pairs by'], \
options={'algorithm': ['convex_hull', 'pca'],
'optimize molecules pairs by': ['convex_hull',
'pca_2d']}, \
default={'number of restraints': '4',
'maximal distance of restraints': '1.2', 'algorithm': 'pca',
'optimize molecules pairs by': 'pca_2d'})
if try_to_get_args(self.my_optimizer, input_function):
time_start = time.time()
try:
self.selected_restraints = self.my_optimizer.make_restraints()
time_stop = time.time()
print('Optimized in ' + '{:0.1f}'.format(time_stop - time_start) + ' s', mv=3)
except u.NoOptimalSolutionException as ex:
print('Failed to find a optimal solution under the given conditions:', ex, mv=4)
else:
self.my_optimizer = None
self.current_optimizer_type = None
def _set_optimizer_type(self, new_optimizer_type: type):
'''
_set_optimizer_type changes the current type of Optimizer and creates and applies a Optimizer of that type.
:warning: Should only be called via set_action_type which handles type checking.
:param new_optimizer_type: type of the new Filter
:type new_optimizer_type: t.Type[Filter]
:return: None
:rtype: None
'''
if new_optimizer_type == None:
self.current_optimizer_type = None
self.my_optimizer = None
return
if not new_optimizer_type in self.available_optimizer_types + [None]:
raise TypeError(str(new_optimizer_type) + ' is not an available type of Optimizer')
self.my_optimizer = new_optimizer_type(self.selected_atoms)
# TODO: See TODO in u.creat_multi_dialog
# SWITCHTABLE FOR input function
input_functions = u.do_nothing()
# TODO: More elegant than these hardcoded input functions: Give each Optimizer etc. an attribute specifzing which args it needs, which we can than pass to create_multi_dialog
# TODO: Generate new field in pyqt win to select if you want a chain, ring, or all to all connection
if isinstance(self.my_optimizer, Optimizer.TreeHeuristicOptimizer):
input_function = u.create_multi_dialog(title='Parameters for TreeHeuristicOptimizer', \
inputs=['number of restraints', 'maximal distance of restraints',
'tree-algorithm', 'optimize molecules pairs by'], \
options={'tree-algorithm': ['shortest', 'cog', 'prim', "biased_avg"],
'optimize molecules pairs by': ['None', 'convex_hull',
'pca_2d']}, \
default={'number of restraints': '4',
'maximal distance of restraints': '1.2',
'algorithm': 'shortest',
'optimize molecules pairs by': 'pca_2d'})
elif isinstance(self.my_optimizer, Optimizer.BruteForceRingOptimzer):
input_function = u.create_multi_dialog(title='Parameters for BruteForceOptimizer', \
inputs=['number of restraints', 'maximal distance of restraints',
'algorithm', 'optimize molecules pairs by'], \
options={'algorithm': ['convex_hull', 'pca'],
'optimize molecules pairs by': ['None', 'convex_hull',
'pca_2d']}, \
default={'number of restraints': '4',
'maximal distance of restraints': '1.2', 'algorithm': 'pca',
'optimize molecules pairs by': 'pca_2d'})
elif isinstance(self.my_optimizer, Optimizer.MetaMoleculeRingOptimizer):
input_function = u.create_multi_dialog(title='Parameters for BestMoleculeRingOptimizer', \
inputs=['number of restraints', 'maximal distance of restraints',
'algorithm', 'optimize molecules pairs by'], \
options={'algorithm': ['convex_hull', 'pca'],
'optimize molecules pairs by': ['convex_hull',
'pca_2d']}, \
default={'number of restraints': '4',
'maximal distance of restraints': '1.2', 'algorithm': 'pca',
'optimize molecules pairs by': 'pca_2d'})
if try_to_get_args(self.my_optimizer, input_function):
time_start = time.time()
try:
self.selected_restraints = self.my_optimizer.make_restraints()
time_stop = time.time()
print('Optimized in ' + '{:0.1f}'.format(time_stop - time_start) + ' s', mv=3)
except u.NoOptimalSolutionException as ex:
print('Failed to find a optimal solution under the given conditions:', ex, mv=4)
else:
self.my_optimizer = None
self.current_optimizer_type = None
