本文整理匯總了Python中nltk.compat.integer_types方法的典型用法代碼示例。如果您正苦於以下問題：Python compat.integer_types方法的具體用法？Python compat.integer_types怎麽用？Python compat.integer_types使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類nltk.compat的用法示例。
在下文中一共展示了compat.integer_types方法的4個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: describe
# 需要導入模塊: from nltk import compat [as 別名]
# 或者: from nltk.compat import integer_types [as 別名]
def describe(self, f_id):
# Inherit docs.
if not isinstance(f_id, compat.integer_types):
raise TypeError('describe() expected an int')
try:
self._inv_mapping
except AttributeError:
self._inv_mapping = [-1]*len(self._mapping)
for (info, i) in self._mapping.items():
self._inv_mapping[i] = info
if f_id < len(self._mapping):
(fname, fval, label) = self._inv_mapping[f_id]
return '%s==%r and label is %r' % (fname, fval, label)
elif self._alwayson and f_id in self._alwayson.values():
for (label, f_id2) in self._alwayson.items():
if f_id == f_id2:
return 'label is %r' % label
elif self._unseen and f_id in self._unseen.values():
for (fname, f_id2) in self._unseen.items():
if f_id == f_id2:
return '%s is unseen' % fname
else:
raise ValueError('Bad feature id') 示例2: encode
# 需要導入模塊: from nltk import compat [as 別名]
# 或者: from nltk.compat import integer_types [as 別名]
def encode(self, featureset, label):
# Inherit docs.
encoding = []
# Convert input-features to joint-features:
for fname, fval in featureset.items():
if isinstance(fval, (compat.integer_types, float)):
# Known feature name & value:
if (fname, type(fval), label) in self._mapping:
encoding.append((self._mapping[fname, type(fval),
label], fval))
else:
# Known feature name & value:
if (fname, fval, label) in self._mapping:
encoding.append((self._mapping[fname, fval, label], 1))
# Otherwise, we might want to fire an "unseen-value feature".
elif self._unseen:
# Have we seen this fname/fval combination with any label?
for label2 in self._labels:
if (fname, fval, label2) in self._mapping:
break # we've seen this fname/fval combo
# We haven't -- fire the unseen-value feature
else:
if fname in self._unseen:
encoding.append((self._unseen[fname], 1))
# Add always-on features:
if self._alwayson and label in self._alwayson:
encoding.append((self._alwayson[label], 1))
return encoding 示例3: from_train
# 需要導入模塊: from nltk import compat [as 別名]
# 或者: from nltk.compat import integer_types [as 別名]
def from_train(tokens):
"""
Constructs an ARFF_Formatter instance with class labels and feature
types determined from the given data. Handles boolean, numeric and
string (note: not nominal) types.
"""
# Find the set of all attested labels.
labels = set(label for (tok, label) in tokens)
# Determine the types of all features.
features = {}
for tok, label in tokens:
for (fname, fval) in tok.items():
if issubclass(type(fval), bool):
ftype = '{True, False}'
elif issubclass(type(fval), (compat.integer_types, float, bool)):
ftype = 'NUMERIC'
elif issubclass(type(fval), compat.string_types):
ftype = 'STRING'
elif fval is None:
continue # can't tell the type.
else:
raise ValueError('Unsupported value type %r' % ftype)
if features.get(fname, ftype) != ftype:
raise ValueError('Inconsistent type for %s' % fname)
features[fname] = ftype
features = sorted(features.items())
return ARFF_Formatter(labels, features) 示例4: _fmt_arff_val
# 需要導入模塊: from nltk import compat [as 別名]
# 或者: from nltk.compat import integer_types [as 別名]
def _fmt_arff_val(self, fval):
if fval is None:
return '?'
elif isinstance(fval, (bool, compat.integer_types)):
return '%s' % fval
elif isinstance(fval, float):
return '%r' % fval
else:
return '%r' % fval