def make_new_mapping(self, old_mapping, locus, features):
new_sr = copy.deepcopy(old_mapping.sr)
new_sr[locus] -= features
for feature in features:
new_sr[locus].add(-feature)
try:
self.feature_dict.get_segment(new_sr[locus])
except IndexError:
return []
new_mapping = Mapping(self.feature_dict, [
False,
copy.deepcopy(old_mapping.ur), new_sr,
copy.deepcopy(old_mapping.changes)
])
new_mapping.stem = copy.copy(old_mapping.stem)
for feature in features:
change = Change(self.feature_dict,
change_type='change',
mapping=new_mapping,
locus=locus,
feature=feature)
change.make_set()
new_mapping.changes.append(change)
new_mapping.add_boundaries()
new_mapping.set_ngrams()
return new_mapping
def change_feature_value(self, mapping):
"""Map a ur to an sr with one segment changed. Prefers fewer feature
changes, but will only map to segments that are in the inventory. Each
feature change is recorded in rule format: 'change
feature-index new-feature-value
major-features-of-original-segment'."""
# decide what to change
locus = numpy.random.randint(0, len(mapping.sr))
segment = mapping.sr[locus]
# decide how many features to change
num_to_change = numpy.random.zipf(2)
if num_to_change > len(segment):
num_to_change = numpy.random.randint(1, len(segment) + 1)
# pick a segment to change to with that many different features
closest_num = None
new_segment = None
changed_features = None
for phone in self.non_boundaries.values():
difference = segment - phone
num_different = len(difference)
if num_different == num_to_change:
new_segment = phone
changed_features = difference
break
else:
if num_different != 0 and (
closest_num == None
or numpy.absolute(num_different - num_to_change) <
numpy.absolute(closest_num - num_to_change)):
closest_num = num_different
new_segment = phone
changed_features = difference
# change the segment
mapping.sr[locus] = new_segment
assert changed_features, 'no change made'
for feature in changed_features:
change = Change(self.feature_dict,
feature=feature,
mapping=mapping,
locus=locus)
change.make_set()
mapping.changes.append(change)
def make_new_mapping(self, old_mapping, locus, features):
new_sr = copy.deepcopy(old_mapping.sr)
new_sr[locus] -= features
for feature in features:
new_sr[locus].add(-feature)
try:
self.feature_dict.get_segment(new_sr[locus])
except IndexError:
return []
new_mapping = Mapping(
self.feature_dict, [False, copy.deepcopy(old_mapping.ur), new_sr, copy.deepcopy(old_mapping.changes)]
)
new_mapping.stem = copy.copy(old_mapping.stem)
for feature in features:
change = Change(self.feature_dict, change_type="change", mapping=new_mapping, locus=locus, feature=feature)
change.make_set()
new_mapping.changes.append(change)
new_mapping.add_boundaries()
new_mapping.set_ngrams()
return new_mapping
def change_feature_value(self, mapping):
"""Map a ur to an sr with one segment changed. Prefers fewer feature
changes, but will only map to segments that are in the inventory. Each
feature change is recorded in rule format: 'change
feature-index new-feature-value
major-features-of-original-segment'."""
# decide what to change
locus = numpy.random.randint(0, len(mapping.sr))
segment = mapping.sr[locus]
# decide how many features to change
num_to_change = numpy.random.zipf(2)
if num_to_change > len(segment):
num_to_change = numpy.random.randint(1, len(segment) + 1)
# pick a segment to change to with that many different features
closest_num = None
new_segment = None
changed_features = None
for phone in self.non_boundaries.values():
difference = segment - phone
num_different = len(difference)
if num_different == num_to_change:
new_segment = phone
changed_features = difference
break
else:
if num_different != 0 and (
closest_num == None
or numpy.absolute(num_different - num_to_change) < numpy.absolute(closest_num - num_to_change)
):
closest_num = num_different
new_segment = phone
changed_features = difference
# change the segment
mapping.sr[locus] = new_segment
assert changed_features, "no change made"
for feature in changed_features:
change = Change(self.feature_dict, feature=feature, mapping=mapping, locus=locus)
change.make_set()
mapping.changes.append(change)
