本文整理汇总了Python中Orange.data.Table._init_ids方法的典型用法代码示例。如果您正苦于以下问题：Python Table._init_ids方法的具体用法？Python Table._init_ids怎么用？Python Table._init_ids使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Orange.data.Table的用法示例。
在下文中一共展示了Table._init_ids方法的8个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: extend_corpus
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import _init_ids [as 别名]
def extend_corpus(self, metadata, Y):
"""
Append documents to corpus.
Args:
metadata (numpy.ndarray): Meta data
Y (numpy.ndarray): Class variables
"""
if np.prod(self.X.shape) != 0:
raise ValueError("Extending corpus only works when X is empty"
"while the shape of X is {}".format(self.X.shape))
self.metas = np.vstack((self.metas, metadata))
cv = self.domain.class_var
for val in set(filter(None, Y)):
if val not in cv.values:
cv.add_value(val)
new_Y = np.array([cv.to_val(i) for i in Y])[:, None]
self._Y = np.vstack((self._Y, new_Y))
self.X = self.W = np.zeros((self.metas.shape[0], 0))
Table._init_ids(self)
self._tokens = None # invalidate tokens示例2: __init__
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import _init_ids [as 别名]
def __init__(self, X=None, Y=None, metas=None, domain=None, text_features=None):
"""
Args:
X (numpy.ndarray): attributes
Y (numpy.ndarray): class variables
metas (numpy.ndarray): meta attributes; e.g. text
domain (Orange.data.domain): the domain for this Corpus
text_features (list): meta attributes that are used for
text mining. Infer them if None.
"""
n_doc = _check_arrays(X, Y, metas)
self.X = X if X is not None else np.zeros((n_doc, 0))
self.Y = Y if Y is not None else np.zeros((n_doc, 0))
self.metas = metas if metas is not None else np.zeros((n_doc, 0))
self.W = np.zeros((n_doc, 0))
self.domain = domain
self.text_features = None # list of text features for mining
if domain is not None and text_features is None:
self._infer_text_features()
elif domain is not None:
self.set_text_features(text_features)
Table._init_ids(self)示例3: __init__
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import _init_ids [as 别名]
def __init__(self, domain=None, X=None, Y=None, metas=None, W=None, text_features=None):
"""
Args:
domain (Orange.data.Domain): the domain for this Corpus
X (numpy.ndarray): attributes
Y (numpy.ndarray): class variables
metas (numpy.ndarray): meta attributes; e.g. text
W (numpy.ndarray): instance weights
text_features (list): meta attributes that are used for
text mining. Infer them if None.
"""
n_doc = _check_arrays(X, Y, metas)
self.X = X if X is not None and X.size else sp.csr_matrix((n_doc, 0)) # prefer sparse (BoW compute values)
self.Y = Y if Y is not None else np.zeros((n_doc, 0))
self.metas = metas if metas is not None else np.zeros((n_doc, 0))
self.W = W if W is not None else np.zeros((n_doc, 0))
self.domain = domain
self.text_features = None # list of text features for mining
self._tokens = None
self._dictionary = None
self._ngrams_corpus = None
self.ngram_range = (1, 1)
self.attributes = {}
self.pos_tags = None
self.used_preprocessor = None # required for compute values
if domain is not None and text_features is None:
self._infer_text_features()
elif domain is not None:
self.set_text_features(text_features)
Table._init_ids(self)示例4: extend_corpus
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import _init_ids [as 别名]
def extend_corpus(self, metadata, Y):
self.metas = np.vstack((self.metas, metadata))
cv = self.domain.class_var
for val in set(Y):
if val not in cv.values:
cv.add_value(val)
new_Y = np.array([cv.to_val(i) for i in Y])[:, None]
self._Y = np.vstack((self._Y, new_Y))
self.X = self.W = np.zeros((len(self), 0))
Table._init_ids(self)示例5: extend_corpus
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import _init_ids [as 别名]
def extend_corpus(self, documents, metadata, class_values):
# TODO check if Domains match!
self.metas = np.vstack((self.metas, metadata))
self.documents += documents
for val in set(class_values):
if val not in self.domain.class_var.values:
self.domain.class_var.add_value(val)
new_Y = np.array([self.domain.class_var.to_val(cv) for cv in class_values])[:, None]
self._Y = np.vstack((self._Y, new_Y))
self.X = self.W = np.zeros((len(self.documents), 0))
Table._init_ids(self)示例6: __init__
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import _init_ids [as 别名]
def __init__(self, documents, X, Y, metas, domain):
self.documents = documents
if X is not None:
self.X = X
else:
self.X = np.zeros((len(documents), 0))
if Y is not None:
self.Y = Y
else:
self.Y = np.zeros((len(documents), 0))
self.metas = metas
self.W = np.zeros((len(documents), 0))
self.domain = domain
Table._init_ids(self)示例7: __init__
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import _init_ids [as 别名]
def __init__(self, relation):
"""Create a wrapper for fusion.Relation.
Parameters:
-----------
relation: An instance of `skfusion.fusion.Relation`
"""
self.relation = relation
meta_vars, self.metas = self._create_metas(relation)
self._Y = self.W = np.zeros((len(relation.data), 0))
if relation.col_names is not None:
attr_names = relation.col_names
else:
attr_names = range(relation.data.shape[1])
self.domain = Domain([ContinuousVariable(name)
for name in map(str, attr_names)],
metas=meta_vars)
Table._init_ids(self)示例8: extend_corpus
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import _init_ids [as 别名]
def extend_corpus(self, metadata, Y):
"""
Append documents to corpus.
Args:
metadata (numpy.ndarray): Meta data
Y (numpy.ndarray): Class variables
"""
self.metas = np.vstack((self.metas, metadata))
cv = self.domain.class_var
for val in set(Y):
if val not in cv.values:
cv.add_value(val)
new_Y = np.array([cv.to_val(i) for i in Y])[:, None]
self._Y = np.vstack((self._Y, new_Y))
self.X = self.W = np.zeros((len(self), 0))
Table._init_ids(self)
self._tokens = None # invalidate tokens