def __init__(self, threshold=1e-2, **kwargs):
"""
Args:
kwargs:
args for SubstitutionProbability class
lambda_table, alpha
"""
self._kwargs = kwargs
self._threshold = threshold
self._substitutor = Substitutor(threshold, **kwargs)
class SubstitutorTest(unittest.TestCase):
def setUp(self):
self.s = Substitutor(threshold=1e-3,
lambda_table=get_table(),
alpha=-5.)
def test_substitutor(self):
s_list = [Specie('O', -2), Specie('Li', 1)]
subs = self.s.pred_from_list(s_list)
self.assertEqual(len(subs), 4, 'incorrect number of substitutions')
c = Composition({'O2-': 1, 'Li1+': 2})
subs = self.s.pred_from_comp(c)
self.assertEqual(len(subs), 4, 'incorrect number of substitutions')
def test_to_dict(self):
Substitutor.from_dict(self.s.to_dict)
class SubstitutionPredictorTransformation(AbstractTransformation):
"""
This transformation takes a structure and uses the structure
prediction module to find likely site substitutions.
"""
def __init__(self, threshold=1e-2, **kwargs):
"""
Args:
kwargs:
args for SubstitutionProbability class
lambda_table, alpha
"""
self._kwargs = kwargs
self._threshold = threshold
self._substitutor = Substitutor(threshold, **kwargs)
def apply_transformation(self, structure, return_ranked_list=False):
if not return_ranked_list:
raise ValueError("SubstitutionPredictorTransformation doesn't"
" support returning 1 structure")
preds = self._substitutor.pred_from_comp(structure.composition)
preds.sort(key=lambda x: x['probability'], reverse=True)
outputs = []
for pred in preds:
st = SubstitutionTransformation(pred['substitutions'])
output = {'structure': st.apply_transformation(structure),
'probability': pred['probability'],
'threshold': self._threshold, 'substitutions': {}}
#dictionary keys have to be converted to strings for JSON
for key, value in pred['substitutions'].items():
output['substitutions'][str(key)] = str(value)
outputs.append(output)
return outputs
def __str__(self):
return "SubstitutionPredictorTransformation"
def __repr__(self):
return self.__str__()
@property
def inverse(self):
return None
@property
def is_one_to_many(self):
return True
@property
def to_dict(self):
d = {"name": self.__class__.__name__, "version": __version__,
"init_args": self._kwargs, "@module": self.__class__.__module__,
"@class": self.__class__.__name__}
d["init_args"]["threshold"] = self._threshold
return d
class SubstitutorTest(unittest.TestCase):
def setUp(self):
self.s = Substitutor(threshold=1e-3, lambda_table=get_table(),
alpha= -5.)
def test_substitutor(self):
s_list = [Specie('O', -2), Specie('Li', 1)]
subs = self.s.pred_from_list(s_list)
self.assertEqual(len(subs), 4
, 'incorrect number of substitutions')
c = Composition({'O2-': 1, 'Li1+': 2})
subs = self.s.pred_from_comp(c)
self.assertEqual(len(subs), 4
, 'incorrect number of substitutions')
def test_as_dict(self):
Substitutor.from_dict(self.s.as_dict())
def __init__(self, threshold=1e-2, **kwargs):
"""
Args:
kwargs:
args for SubstitutionProbability class
lambda_table, alpha
"""
self._kwargs = kwargs
self._threshold = threshold
self._substitutor = Substitutor(threshold, **kwargs)
def test_as_dict(self):
Substitutor.from_dict(self.s.as_dict())
def setUp(self):
self.s = Substitutor(threshold=1e-3, lambda_table=get_table(),
alpha= -5.)
def test_to_dict(self):
Substitutor.from_dict(self.s.to_dict)
def setUp(self):
self.s = Substitutor(threshold=1e-3,
lambda_table=get_table(),
alpha=-5.)
def test_as_dict(self):
Substitutor.from_dict(self.s.as_dict())
class SubstitutionPredictorTransformation(AbstractTransformation):
"""
This transformation takes a structure and uses the structure
prediction module to find likely site substitutions.
"""
def __init__(self, threshold=1e-2, **kwargs):
"""
Args:
kwargs:
args for SubstitutionProbability class
lambda_table, alpha
"""
self._kwargs = kwargs
self._threshold = threshold
self._substitutor = Substitutor(threshold, **kwargs)
def apply_transformation(self, structure, return_ranked_list=False):
if not return_ranked_list:
raise ValueError("SubstitutionPredictorTransformation doesn't"
" support returning 1 structure")
preds = self._substitutor.pred_from_comp(structure.composition)
preds.sort(key=lambda x: x['probability'], reverse=True)
outputs = []
for pred in preds:
st = SubstitutionTransformation(pred['substitutions'])
output = {
'structure': st.apply_transformation(structure),
'probability': pred['probability'],
'threshold': self._threshold,
'substitutions': {}
}
#dictionary keys have to be converted to strings for JSON
for key, value in pred['substitutions'].items():
output['substitutions'][str(key)] = str(value)
outputs.append(output)
return outputs
def __str__(self):
return "SubstitutionPredictorTransformation"
def __repr__(self):
return self.__str__()
@property
def inverse(self):
return None
@property
def is_one_to_many(self):
return True
@property
def to_dict(self):
d = {
"name": self.__class__.__name__,
"version": __version__,
"init_args": self._kwargs,
"@module": self.__class__.__module__,
"@class": self.__class__.__name__
}
d["init_args"]["threshold"] = self._threshold
return d
def test_to_dict(self):
Substitutor.from_dict(self.s.to_dict)
