# cython: embedsignature=True # coding: utf8 from __future__ import unicode_literals, print_function # Compiler crashes on memory view coercion without this. Should report bug. from cython.view cimport array as cvarray cimport numpy as np np.import_array() from libc.string cimport memset import numpy from .typedefs cimport attr_t, flags_t from .attrs cimport IS_ALPHA, IS_ASCII, IS_DIGIT, IS_LOWER, IS_PUNCT, IS_SPACE from .attrs cimport IS_TITLE, IS_UPPER, LIKE_URL, LIKE_NUM, LIKE_EMAIL, IS_STOP from .attrs cimport IS_BRACKET, IS_QUOTE, IS_LEFT_PUNCT, IS_RIGHT_PUNCT, IS_OOV from . import about memset(&EMPTY_LEXEME, 0, sizeof(LexemeC)) cdef class Lexeme: """An entry in the vocabulary. A `Lexeme` has no string context – it's a word-type, as opposed to a word token. It therefore has no part-of-speech tag, dependency parse, or lemma (lemmatization depends on the part-of-speech tag). """ def __init__(self, Vocab vocab, attr_t orth): """Create a Lexeme object. vocab (Vocab): The parent vocabulary orth (uint64): The orth id of the lexeme. Returns (Lexeme): The newly constructd object. """ self.vocab = vocab self.orth = orth self.c = vocab.get_by_orth(vocab.mem, orth) assert self.c.orth == orth def __richcmp__(self, other, int op): if isinstance(other, Lexeme): a = self.orth b = other.orth elif isinstance(other, long): a = self.orth b = other elif isinstance(other, str): a = self.orth_ b = other else: a = 0 b = 1 if op == 2: # == return a == b elif op == 3: # != return a != b elif op == 0: # < return a < b elif op == 1: # <= return a <= b elif op == 4: # > return a > b elif op == 5: # >= return a >= b else: raise NotImplementedError(op) def __hash__(self): return self.c.orth def set_flag(self, attr_id_t flag_id, bint value): """Change the value of a boolean flag. flag_id (int): The attribute ID of the flag to set. value (bool): The new value of the flag. """ Lexeme.c_set_flag(self.c, flag_id, value) def check_flag(self, attr_id_t flag_id): """Check the value of a boolean flag. flag_id (int): The attribute ID of the flag to query. RETURNS (bool): The value of the flag. """ return True if Lexeme.c_check_flag(self.c, flag_id) else False def similarity(self, other): """Compute a semantic similarity estimate. Defaults to cosine over vectors. other (object): The object to compare with. By default, accepts `Doc`, `Span`, `Token` and `Lexeme` objects. RETURNS (float): A scalar similarity score. Higher is more similar. """ if self.vector_norm == 0 or other.vector_norm == 0: return 0.0 return (numpy.dot(self.vector, other.vector) / (self.vector_norm * other.vector_norm)) def to_bytes(self): lex_data = Lexeme.c_to_bytes(self.c) start = &self.c.flags end = &self.c.sentiment + sizeof(self.c.sentiment) assert (end-start) == sizeof(lex_data.data), (end-start, sizeof(lex_data.data)) byte_string = b'\0' * sizeof(lex_data.data) byte_chars = byte_string for i in range(sizeof(lex_data.data)): byte_chars[i] = lex_data.data[i] assert len(byte_string) == sizeof(lex_data.data), (len(byte_string), sizeof(lex_data.data)) return byte_string def from_bytes(self, bytes byte_string): # This method doesn't really have a use-case --- wrote it for testing. # Possibly delete? It puts the Lexeme out of synch with the vocab. cdef SerializedLexemeC lex_data assert len(byte_string) == sizeof(lex_data.data) for i in range(len(byte_string)): lex_data.data[i] = byte_string[i] Lexeme.c_from_bytes(self.c, lex_data) self.orth = self.c.orth property has_vector: """RETURNS (bool): Whether a word vector is associated with the object. """ def __get__(self): return self.vocab.has_vector(self.c.orth) property vector_norm: """RETURNS (float): The L2 norm of the vector representation.""" def __get__(self): vector = self.vector return numpy.sqrt((vector**2).sum()) property vector: """A real-valued meaning representation. RETURNS (numpy.ndarray[ndim=1, dtype='float32']): A 1D numpy array representing the lexeme's semantics. """ def __get__(self): cdef int length = self.vocab.vectors_length if length == 0: raise ValueError( "Word vectors set to length 0. This may be because you " "don't have a model installed or loaded, or because your " "model doesn't include word vectors. For more info, see " "the documentation: \n%s\n" % about.__docs_models__ ) return self.vocab.get_vector(self.c.orth) def __set__(self, vector): assert len(vector) == self.vocab.vectors_length self.vocab.set_vector(self.c.orth, vector) property rank: """RETURNS (unicode): Sequential ID of the lexemes's lexical type, used to index into tables, e.g. for word vectors.""" def __get__(self): return self.c.id def __set__(self, value): self.c.id = value property sentiment: """RETURNS (float): A scalar value indicating the positivity or negativity of the lexeme.""" def __get__(self): return self.c.sentiment def __set__(self, float sentiment): self.c.sentiment = sentiment property orth_: """RETURNS (unicode): The original verbatim text of the lexeme (identical to `Lexeme.text`). Exists mostly for consistency with the other attributes.""" def __get__(self): return self.vocab.strings[self.c.orth] property text: """RETURNS (unicode): The original verbatim text of the lexeme.""" def __get__(self): return self.orth_ property lower: """RETURNS (unicode): Lowercase form of the lexeme.""" def __get__(self): return self.c.lower def __set__(self, attr_t x): self.c.lower = x property norm: """RETURNS (uint64): The lexemes's norm, i.e. a normalised form of the lexeme text. """ def __get__(self): return self.c.norm def __set__(self, attr_t x): self.c.norm = x property shape: """RETURNS (uint64): Transform of the word's string, to show orthographic features. """ def __get__(self): return self.c.shape def __set__(self, attr_t x): self.c.shape = x property prefix: """RETURNS (uint64): Length-N substring from the start of the word. Defaults to `N=1`. """ def __get__(self): return self.c.prefix def __set__(self, attr_t x): self.c.prefix = x property suffix: """RETURNS (uint64): Length-N substring from the end of the word. Defaults to `N=3`. """ def __get__(self): return self.c.suffix def __set__(self, attr_t x): self.c.suffix = x property cluster: """RETURNS (int): Brown cluster ID.""" def __get__(self): return self.c.cluster def __set__(self, attr_t x): self.c.cluster = x property lang: """RETURNS (uint64): Language of the parent vocabulary.""" def __get__(self): return self.c.lang def __set__(self, attr_t x): self.c.lang = x property prob: """RETURNS (float): Smoothed log probability estimate of the lexeme's type.""" def __get__(self): return self.c.prob def __set__(self, float x): self.c.prob = x property lower_: """RETURNS (unicode): Lowercase form of the word.""" def __get__(self): return self.vocab.strings[self.c.lower] def __set__(self, unicode x): self.c.lower = self.vocab.strings.add(x) property norm_: """RETURNS (unicode): The lexemes's norm, i.e. a normalised form of the lexeme text. """ def __get__(self): return self.vocab.strings[self.c.norm] def __set__(self, unicode x): self.c.norm = self.vocab.strings.add(x) property shape_: """RETURNS (unicode): Transform of the word's string, to show orthographic features. """ def __get__(self): return self.vocab.strings[self.c.shape] def __set__(self, unicode x): self.c.shape = self.vocab.strings.add(x) property prefix_: """RETURNS (unicode): Length-N substring from the start of the word. Defaults to `N=1`. """ def __get__(self): return self.vocab.strings[self.c.prefix] def __set__(self, unicode x): self.c.prefix = self.vocab.strings.add(x) property suffix_: """RETURNS (unicode): Length-N substring from the end of the word. Defaults to `N=3`. """ def __get__(self): return self.vocab.strings[self.c.suffix] def __set__(self, unicode x): self.c.suffix = self.vocab.strings.add(x) property lang_: """RETURNS (unicode): Language of the parent vocabulary.""" def __get__(self): return self.vocab.strings[self.c.lang] def __set__(self, unicode x): self.c.lang = self.vocab.strings.add(x) property flags: """RETURNS (uint64): Container of the lexeme's binary flags.""" def __get__(self): return self.c.flags def __set__(self, flags_t x): self.c.flags = x property is_oov: """RETURNS (bool): Whether the lexeme is out-of-vocabulary.""" def __get__(self): return Lexeme.c_check_flag(self.c, IS_OOV) def __set__(self, attr_t x): Lexeme.c_set_flag(self.c, IS_OOV, x) property is_stop: """RETURNS (bool): Whether the lexeme is a stop word.""" def __get__(self): return Lexeme.c_check_flag(self.c, IS_STOP) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_STOP, x) property is_alpha: """RETURNS (bool): Whether the lexeme consists of alphanumeric characters. Equivalent to `lexeme.text.isalpha()`. """ def __get__(self): return Lexeme.c_check_flag(self.c, IS_ALPHA) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_ALPHA, x) property is_ascii: """RETURNS (bool): Whether the lexeme consists of ASCII characters. Equivalent to `[any(ord(c) >= 128 for c in lexeme.text)]`. """ def __get__(self): return Lexeme.c_check_flag(self.c, IS_ASCII) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_ASCII, x) property is_digit: """RETURNS (bool): Whether the lexeme consists of digits. Equivalent to `lexeme.text.isdigit()`. """ def __get__(self): return Lexeme.c_check_flag(self.c, IS_DIGIT) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_DIGIT, x) property is_lower: """RETURNS (bool): Whether the lexeme is in lowercase. Equivalent to `lexeme.text.islower()`. """ def __get__(self): return Lexeme.c_check_flag(self.c, IS_LOWER) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_LOWER, x) property is_upper: """RETURNS (bool): Whether the lexeme is in uppercase. Equivalent to `lexeme.text.isupper()`. """ def __get__(self): return Lexeme.c_check_flag(self.c, IS_UPPER) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_UPPER, x) property is_title: """RETURNS (bool): Whether the lexeme is in titlecase. Equivalent to `lexeme.text.istitle()`. """ def __get__(self): return Lexeme.c_check_flag(self.c, IS_TITLE) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_TITLE, x) property is_punct: """RETURNS (bool): Whether the lexeme is punctuation.""" def __get__(self): return Lexeme.c_check_flag(self.c, IS_PUNCT) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_PUNCT, x) property is_space: """RETURNS (bool): Whether the lexeme consist of whitespace characters. Equivalent to `lexeme.text.isspace()`. """ def __get__(self): return Lexeme.c_check_flag(self.c, IS_SPACE) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_SPACE, x) property is_bracket: """RETURNS (bool): Whether the lexeme is a bracket.""" def __get__(self): return Lexeme.c_check_flag(self.c, IS_BRACKET) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_BRACKET, x) property is_quote: """RETURNS (bool): Whether the lexeme is a quotation mark.""" def __get__(self): return Lexeme.c_check_flag(self.c, IS_QUOTE) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_QUOTE, x) property is_left_punct: """RETURNS (bool): Whether the lexeme is left punctuation, e.g. ).""" def __get__(self): return Lexeme.c_check_flag(self.c, IS_LEFT_PUNCT) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_LEFT_PUNCT, x) property is_right_punct: """RETURNS (bool): Whether the lexeme is right punctuation, e.g. ).""" def __get__(self): return Lexeme.c_check_flag(self.c, IS_RIGHT_PUNCT) def __set__(self, bint x): Lexeme.c_set_flag(self.c, IS_RIGHT_PUNCT, x) property like_url: """RETURNS (bool): Whether the lexeme resembles a URL.""" def __get__(self): return Lexeme.c_check_flag(self.c, LIKE_URL) def __set__(self, bint x): Lexeme.c_set_flag(self.c, LIKE_URL, x) property like_num: """RETURNS (bool): Whether the lexeme represents a number, e.g. "10.9", "10", "ten", etc. """ def __get__(self): return Lexeme.c_check_flag(self.c, LIKE_NUM) def __set__(self, bint x): Lexeme.c_set_flag(self.c, LIKE_NUM, x) property like_email: """RETURNS (bool): Whether the lexeme resembles an email address.""" def __get__(self): return Lexeme.c_check_flag(self.c, LIKE_EMAIL) def __set__(self, bint x): Lexeme.c_set_flag(self.c, LIKE_EMAIL, x)