Diagrama de herencias de vsm.viewer.tfviewer.TfViewer

Diagrama de colaboración para vsm.viewer.tfviewer.TfViewer:

Métodos públicos
def	__init__

def	sim_word_word

def	dist_word_word

def	sim_doc_doc

def	dist_doc_doc

def	sim_word_doc

def	dist_word_doc

def	simmat_words

def	dismat_word

def	simmat_docs

def	dismat_doc

def	coll_freq

def	coll_freqs

Atributos públicos
	corpus

	model

Descripción detallada

A class for viewing Term-Frequency model.

Documentación del constructor y destructor

def vsm.viewer.tfviewer.TfViewer.__init__	(	self,
		corpus,
		model
	)

Initialize TfViewer. 
    
:param corpus: Source of observed data.
:type corpus: :class:`Corpus`

:param model: A Term-Frequency model.
:type model: TfSeq or TfMulti object.

Documentación de las funciones miembro

def vsm.viewer.tfviewer.TfViewer.coll_freq	(	self,
		word
	)

Returns the frequency of `word` in all documents.

:param word: Word to which its frequency is retrieved.
:type word: string or integer

:returns: freqency as integer

def vsm.viewer.tfviewer.TfViewer.coll_freqs	(	self,
		print_len = `20`,
		as_strings = `True`
	)

Returns the frequency of all words in all documents.

:param print_len: Length of words to display. Default is 20.
:type print_len: integer, optional

:param as_strings: If `True`, words are represented as strings
    rather than their integer representation.
:type as_strings: boolean, optional

:returns: an instance of :class:`LabeledColumn`.
    A table with words and their frequencies.

def vsm.viewer.tfviewer.TfViewer.dismat_doc	(	self,
		doc_list,
		dist_fn = `angle_sparse`
	)

Calculates a distance matrix for a given list of documents.

:param doc_list: A list of documents whose distance matrix is to be
    computed.
:type docs: list of strings/integers.

:param dist_fn: A distance function from functions in vsm.spatial.
    Default is :meth:`angle_sparse`.
:type dist_fn: string, optional

:returns: an instance of :class:`IndexedSymmArray`.
    n x n matrix containing floats where n is the number of
    documents in `doc_list`.

:See Also: :meth:`vsm.viewer.wrappers.dismat_doc`

def vsm.viewer.tfviewer.TfViewer.dismat_word	(	self,
		word_list,
		dist_fn = `angle_sparse`
	)

Calculates a distance matrix for a given list of words.

:param word_list: A list of words whose distance matrix is to be
    computed.
:type word_list: list strings/integers.
 
:param dist_fn: A distance function from functions in vsm.spatial.
    Default is :meth:`angle_sparse`.
:type dist_fn: string, optional

:returns: an instance of :class:`IndexedSymmArray`.
    n x n matrix containing floats where n is the number of words
    in `word_list`.

:See Also: :meth:`vsm.viewer.wrappers.dismat_word`

def vsm.viewer.tfviewer.TfViewer.dist_doc_doc	(	self,
		doc_or_docs,
		weights = `[]`,
		print_len = `10`,
		filter_nan = `True`,
		label_fn = `def_label_fn`,
		as_strings = `True`,
		dist_fn = `angle_sparse`,
		order = `'i'`
	)

Computes and sorts the distances between a document or list of documents
and every document.

:param doc_or_docs: Query document(s) to which distances are calculated.
:type doc_or_docs: string/integer or list of strings/integers

:param weights: Specify weights for each query doc in `doc_or_docs`. 
    Default uses equal weights (i.e. arithmetic mean)
:type weights: list of floating point, optional

:param print_len: Number of documents to be displayed. Default is 10.
:type print_len: int, optional

:param filter_nan: If `True` not a number entries are filtered.
    Default is `True`.
:type filter_nan: boolean, optional
 
:param label_fn: A function that defines how documents are represented.
    Default is :meth:`def_label_fn` which retrieves the labels 
    from corpus metadata.
:type label_fn: string, optional

:param as_strings: If `True`, returns a list of documents as strings
    rather than indices. Default is `True`.
:type as_strings: boolean, optional

:param dist_fn: A distance function from functions in vsm.spatial.
    Default is :meth:`angle_sparse`.
:type dist_fn: string, optional

:param order: Order of sorting. 'i' for increasing and 'd' for
    decreasing order. Default is 'i'.
:type order: string, optional

:returns: an instance of :class:`LabeledColumn`.
    A 2-dim array containing documents and their distances to 
    `doc_or_docs`. 

:See Also: :meth:`vsm.viewer.wrappers.dist_doc_doc`

def vsm.viewer.tfviewer.TfViewer.dist_word_doc	(	self,
		word_or_words,
		weights = `[]`,
		label_fn = `def_label_fn`,
		filter_nan = `True`,
		print_len = `10`,
		as_strings = `True`,
		dist_fn = `angle_sparse`,
		order = `'i'`
	)

Computes and sorts distances between a word or a list of words to
every document.

:param word_or_words: Query word(s) to which a pseudo-document is
    created for computation of distances.
:type word_or_words: string/integer or list of strings/integers

:param weights: Specify weights for each query doc in `word_or_words`. 
    Default uses equal weights (i.e. arithmetic mean)
:type weights: list of floating point, optional

:param print_len: Number of documents to be displayed. Default is 10.
:type print_len: int, optional

:param filter_nan: If `True` not a number entries are filtered.
    Default is `True`.
:type filter_nan: boolean, optional
 
:param label_fn: A function that defines how documents are represented.
    Default is :meth:`def_label_fn` which retrieves the labels 
    from corpus metadata.
:type label_fn: string, optional

:param as_strings: If `True`, returns a list of documents as strings
    rather than indices. Default is `True`.
:type as_strings: boolean, optional

:param dist_fn: A distance function from functions in vsm.spatial.
    Default is :meth:`angle_sparse`.
:type dist_fn: string, optional

:param order: Order of sorting. 'i' for increasing and 'd' for decreasing
    order. Default is 'i'.
:type order: string, optional

:returns: an instance of :class:`LabeledColumn`.
    A 2-dim array containing documents and their distances to 
    `word_or_words`. 

:See Also: :meth:`vsm.viewer.wrappers.dist_word_doc`

def vsm.viewer.tfviewer.TfViewer.dist_word_word	(	self,
		word_or_words,
		weights = `[]`,
		filter_nan = `True`,
		print_len = `10`,
		as_strings = `True`,
		dist_fn = `angle_sparse`,
		order = `'i'`
	)

Returns words sorted by the distances between word(s) and every word.

:param word_or_words: Query word(s) to which distances are calculated.
:type word_or_words: string or list of strings

:param weights: Specify weights for each query word in `word_or_words`. 
    Default uses equal weights (i.e. arithmetic mean)
:type weights: list of floating point, optional

:param filter_nan: If `True` not a number entries are filtered.
    Default is `True`.
:type filter_nan: boolean, optional

:param print_len: Number of words to be displayed. Default is 10.
:type print_len: int, optional

:param as_strings: If `True`, returns a list of words as strings rather
    than their integer representations. Default is `True`.
:type as_strings: boolean, optional

:param dist_fn: A distance function from functions in vsm.spatial. 
    Default is :meth:`angle_sparse`.
:type dist_fn: string, optional

:param order: Order of sorting. 'i' for increasing and 'd' for
    decreasing order. Default is 'i'.
:type order: string, optional

:returns: an instance of :class:`LabeledColumn`.
    A 2-dim array containing words and their distances to 
    `word_or_words`. 

:See Also: :meth:`vsm.viewer.wrappers.dist_word_word`

La documentación para esta clase fue generada a partir del siguiente fichero:

vsm/vsm/viewer/tfviewer.py

Métodos públicos

Atributos públicos

Descripción detallada

Documentación del constructor y destructor

Documentación de las funciones miembro