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emre/storm | storm/__main__.py | web | def web(port, debug=False, theme="modern", ssh_config=None):
"""Starts the web UI."""
from storm import web as _web
_web.run(port, debug, theme, ssh_config) | python | def web(port, debug=False, theme="modern", ssh_config=None):
"""Starts the web UI."""
from storm import web as _web
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diging/tethne | tethne/writers/collection.py | _strip_list_attributes | def _strip_list_attributes(graph_):
"""Converts lists attributes to strings for all nodes and edges in G."""
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"""Converts lists attributes to strings for all nodes and edges in G."""
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if type(v) is list:
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diging/tethne | tethne/writers/collection.py | _safe_type | def _safe_type(value):
"""Converts Python type names to XGMML-safe type names."""
if type(value) is str: dtype = 'string'
if type(value) is unicode: dtype = 'string'
if type(value) is int: dtype = 'integer'
if type(value) is float: dtype = 'real'
return dtype | python | def _safe_type(value):
"""Converts Python type names to XGMML-safe type names."""
if type(value) is str: dtype = 'string'
if type(value) is unicode: dtype = 'string'
if type(value) is int: dtype = 'integer'
if type(value) is float: dtype = 'real'
return dtype | [
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diging/tethne | tethne/readers/wos.py | read | def read(path, corpus=True, index_by='wosid', streaming=False, parse_only=None,
corpus_class=Corpus, **kwargs):
"""
Parse one or more WoS field-tagged data files.
Examples
--------
.. code-block:: python
>>> from tethne.readers import wos
>>> corpus = wos.read("/path/to/some... | python | def read(path, corpus=True, index_by='wosid', streaming=False, parse_only=None,
corpus_class=Corpus, **kwargs):
"""
Parse one or more WoS field-tagged data files.
Examples
--------
.. code-block:: python
>>> from tethne.readers import wos
>>> corpus = wos.read("/path/to/some... | [
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Examples
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.. code-block:: python
>>> from tethne.readers import wos
>>> corpus = wos.read("/path/to/some/wos/data")
>>> corpus
<tethne.classes.corpus.Corpus object at 0x10057c2d0>
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diging/tethne | tethne/readers/wos.py | WoSParser.parse_author | def parse_author(self, value):
"""
Attempts to split an author name into last and first parts.
"""
tokens = tuple([t.upper().strip() for t in value.split(',')])
if len(tokens) == 1:
tokens = value.split(' ')
if len(tokens) > 0:
if len(tokens) > 1:
... | python | def parse_author(self, value):
"""
Attempts to split an author name into last and first parts.
"""
tokens = tuple([t.upper().strip() for t in value.split(',')])
if len(tokens) == 1:
tokens = value.split(' ')
if len(tokens) > 0:
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diging/tethne | tethne/readers/wos.py | WoSParser.handle_CR | def handle_CR(self, value):
"""
Parses cited references.
"""
citation = self.entry_class()
value = strip_tags(value)
# First-author name and publication date.
ptn = '([\w\s\W]+),\s([0-9]{4}),\s([\w\s]+)'
ny_match = re.match(ptn, value, flags=re.U)
... | python | def handle_CR(self, value):
"""
Parses cited references.
"""
citation = self.entry_class()
value = strip_tags(value)
# First-author name and publication date.
ptn = '([\w\s\W]+),\s([0-9]{4}),\s([\w\s]+)'
ny_match = re.match(ptn, value, flags=re.U)
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diging/tethne | tethne/readers/wos.py | WoSParser.postprocess_WC | def postprocess_WC(self, entry):
"""
Parse WC keywords.
Subject keywords are usually semicolon-delimited.
"""
if type(entry.WC) not in [str, unicode]:
WC= u' '.join([unicode(k) for k in entry.WC])
else:
WC= entry.WC
entry.WC= [k.strip().u... | python | def postprocess_WC(self, entry):
"""
Parse WC keywords.
Subject keywords are usually semicolon-delimited.
"""
if type(entry.WC) not in [str, unicode]:
WC= u' '.join([unicode(k) for k in entry.WC])
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WC= entry.WC
entry.WC= [k.strip().u... | [
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diging/tethne | tethne/readers/wos.py | WoSParser.postprocess_subject | def postprocess_subject(self, entry):
"""
Parse subject keywords.
Subject keywords are usually semicolon-delimited.
"""
if type(entry.subject) not in [str, unicode]:
subject = u' '.join([unicode(k) for k in entry.subject])
else:
subject = entry.s... | python | def postprocess_subject(self, entry):
"""
Parse subject keywords.
Subject keywords are usually semicolon-delimited.
"""
if type(entry.subject) not in [str, unicode]:
subject = u' '.join([unicode(k) for k in entry.subject])
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subject = entry.s... | [
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diging/tethne | tethne/readers/wos.py | WoSParser.postprocess_authorKeywords | def postprocess_authorKeywords(self, entry):
"""
Parse author keywords.
Author keywords are usually semicolon-delimited.
"""
if type(entry.authorKeywords) not in [str, unicode]:
aK = u' '.join([unicode(k) for k in entry.authorKeywords])
else:
aK ... | python | def postprocess_authorKeywords(self, entry):
"""
Parse author keywords.
Author keywords are usually semicolon-delimited.
"""
if type(entry.authorKeywords) not in [str, unicode]:
aK = u' '.join([unicode(k) for k in entry.authorKeywords])
else:
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diging/tethne | tethne/readers/wos.py | WoSParser.postprocess_keywordsPlus | def postprocess_keywordsPlus(self, entry):
"""
Parse WoS "Keyword Plus" keywords.
Keyword Plus keywords are usually semicolon-delimited.
"""
if type(entry.keywordsPlus) in [str, unicode]:
entry.keywordsPlus = [k.strip().upper() for k
... | python | def postprocess_keywordsPlus(self, entry):
"""
Parse WoS "Keyword Plus" keywords.
Keyword Plus keywords are usually semicolon-delimited.
"""
if type(entry.keywordsPlus) in [str, unicode]:
entry.keywordsPlus = [k.strip().upper() for k
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diging/tethne | tethne/readers/wos.py | WoSParser.postprocess_funding | def postprocess_funding(self, entry):
"""
Separates funding agency from grant numbers.
"""
if type(entry.funding) not in [str, unicode]:
return
sources = [fu.strip() for fu in entry.funding.split(';')]
sources_processed = []
for source in sources:
... | python | def postprocess_funding(self, entry):
"""
Separates funding agency from grant numbers.
"""
if type(entry.funding) not in [str, unicode]:
return
sources = [fu.strip() for fu in entry.funding.split(';')]
sources_processed = []
for source in sources:
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diging/tethne | tethne/readers/wos.py | WoSParser.postprocess_authors_full | def postprocess_authors_full(self, entry):
"""
If only a single author was found, ensure that ``authors_full`` is
nonetheless a list.
"""
if type(entry.authors_full) is not list:
entry.authors_full = [entry.authors_full] | python | def postprocess_authors_full(self, entry):
"""
If only a single author was found, ensure that ``authors_full`` is
nonetheless a list.
"""
if type(entry.authors_full) is not list:
entry.authors_full = [entry.authors_full] | [
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diging/tethne | tethne/readers/wos.py | WoSParser.postprocess_authors_init | def postprocess_authors_init(self, entry):
"""
If only a single author was found, ensure that ``authors_init`` is
nonetheless a list.
"""
if type(entry.authors_init) is not list:
entry.authors_init = [entry.authors_init] | python | def postprocess_authors_init(self, entry):
"""
If only a single author was found, ensure that ``authors_init`` is
nonetheless a list.
"""
if type(entry.authors_init) is not list:
entry.authors_init = [entry.authors_init] | [
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diging/tethne | tethne/readers/wos.py | WoSParser.postprocess_citedReferences | def postprocess_citedReferences(self, entry):
"""
If only a single cited reference was found, ensure that
``citedReferences`` is nonetheless a list.
"""
if type(entry.citedReferences) is not list:
entry.citedReferences = [entry.citedReferences] | python | def postprocess_citedReferences(self, entry):
"""
If only a single cited reference was found, ensure that
``citedReferences`` is nonetheless a list.
"""
if type(entry.citedReferences) is not list:
entry.citedReferences = [entry.citedReferences] | [
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diging/tethne | tethne/plot/__init__.py | plot_burstness | def plot_burstness(corpus, B, **kwargs):
"""
Generate a figure depicting burstness profiles for ``feature``.
Parameters
----------
B
Returns
-------
fig : :class:`matplotlib.figure.Figure`
Examples
--------
.. code-block:: python
>>> from tethne.analyze.corpus imp... | python | def plot_burstness(corpus, B, **kwargs):
"""
Generate a figure depicting burstness profiles for ``feature``.
Parameters
----------
B
Returns
-------
fig : :class:`matplotlib.figure.Figure`
Examples
--------
.. code-block:: python
>>> from tethne.analyze.corpus imp... | [
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.. code-block:: python
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diging/tethne | tethne/networks/helpers.py | simplify_multigraph | def simplify_multigraph(multigraph, time=False):
"""
Simplifies a graph by condensing multiple edges between the same node pair
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Parameters
----------
graph : networkx.MultiGraph
E.g. a coauthorship graph.
time... | python | def simplify_multigraph(multigraph, time=False):
"""
Simplifies a graph by condensing multiple edges between the same node pair
into a single edge, with a weight attribute equal to the number of edges.
Parameters
----------
graph : networkx.MultiGraph
E.g. a coauthorship graph.
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diging/tethne | tethne/networks/helpers.py | citation_count | def citation_count(papers, key='ayjid', verbose=False):
"""
Generates citation counts for all of the papers cited by papers.
Parameters
----------
papers : list
A list of :class:`.Paper` instances.
key : str
Property to use as node key. Default is 'ayjid' (recommended).
verb... | python | def citation_count(papers, key='ayjid', verbose=False):
"""
Generates citation counts for all of the papers cited by papers.
Parameters
----------
papers : list
A list of :class:`.Paper` instances.
key : str
Property to use as node key. Default is 'ayjid' (recommended).
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diging/tethne | tethne/analyze/collection.py | connected | def connected(G, method_name, **kwargs):
"""
Performs analysis methods from networkx.connected on each graph in the
collection.
Parameters
----------
G : :class:`.GraphCollection`
The :class:`.GraphCollection` to analyze. The specified method will be
applied to each graph in ``G... | python | def connected(G, method_name, **kwargs):
"""
Performs analysis methods from networkx.connected on each graph in the
collection.
Parameters
----------
G : :class:`.GraphCollection`
The :class:`.GraphCollection` to analyze. The specified method will be
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diging/tethne | tethne/analyze/collection.py | attachment_probability | def attachment_probability(G):
"""
Calculates the observed attachment probability for each node at each
time-step.
Attachment probability is calculated based on the observed new edges in the
next time-step. So if a node acquires new edges at time t, this will accrue
to the node's attac... | python | def attachment_probability(G):
"""
Calculates the observed attachment probability for each node at each
time-step.
Attachment probability is calculated based on the observed new edges in the
next time-step. So if a node acquires new edges at time t, this will accrue
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diging/tethne | tethne/analyze/graph.py | global_closeness_centrality | def global_closeness_centrality(g, node=None, normalize=True):
"""
Calculates global closeness centrality for one or all nodes in the network.
See :func:`.node_global_closeness_centrality` for more information.
Parameters
----------
g : networkx.Graph
normalize : boolean
If True, n... | python | def global_closeness_centrality(g, node=None, normalize=True):
"""
Calculates global closeness centrality for one or all nodes in the network.
See :func:`.node_global_closeness_centrality` for more information.
Parameters
----------
g : networkx.Graph
normalize : boolean
If True, n... | [
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diging/tethne | tethne/readers/dfr.py | ngrams | def ngrams(path, elem, ignore_hash=True):
"""
Yields N-grams from a JSTOR DfR dataset.
Parameters
----------
path : string
Path to unzipped JSTOR DfR folder containing N-grams.
elem : string
Name of subdirectory containing N-grams. (e.g. 'bigrams').
ignore_hash : bool
... | python | def ngrams(path, elem, ignore_hash=True):
"""
Yields N-grams from a JSTOR DfR dataset.
Parameters
----------
path : string
Path to unzipped JSTOR DfR folder containing N-grams.
elem : string
Name of subdirectory containing N-grams. (e.g. 'bigrams').
ignore_hash : bool
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diging/tethne | tethne/readers/dfr.py | tokenize | def tokenize(ngrams, min_tf=2, min_df=2, min_len=3, apply_stoplist=False):
"""
Builds a vocabulary, and replaces words with vocab indices.
Parameters
----------
ngrams : dict
Keys are paper DOIs, values are lists of (Ngram, frequency) tuples.
apply_stoplist : bool
If True, will ... | python | def tokenize(ngrams, min_tf=2, min_df=2, min_len=3, apply_stoplist=False):
"""
Builds a vocabulary, and replaces words with vocab indices.
Parameters
----------
ngrams : dict
Keys are paper DOIs, values are lists of (Ngram, frequency) tuples.
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diging/tethne | tethne/readers/dfr.py | _handle_pagerange | def _handle_pagerange(pagerange):
"""
Yields start and end pages from DfR pagerange field.
Parameters
----------
pagerange : str or unicode
DfR-style pagerange, e.g. "pp. 435-444".
Returns
-------
start : str
Start page.
end : str
End page.
"""
try:... | python | def _handle_pagerange(pagerange):
"""
Yields start and end pages from DfR pagerange field.
Parameters
----------
pagerange : str or unicode
DfR-style pagerange, e.g. "pp. 435-444".
Returns
-------
start : str
Start page.
end : str
End page.
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diging/tethne | tethne/readers/dfr.py | _handle_authors | def _handle_authors(authors):
"""
Yields aulast and auinit lists from value of authors node.
Parameters
----------
authors : list, str, or unicode
Value or values of 'author' element in DfR XML.
Returns
-------
aulast : list
A list of author surnames (string).
auini... | python | def _handle_authors(authors):
"""
Yields aulast and auinit lists from value of authors node.
Parameters
----------
authors : list, str, or unicode
Value or values of 'author' element in DfR XML.
Returns
-------
aulast : list
A list of author surnames (string).
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diging/tethne | tethne/readers/dfr.py | _handle_author | def _handle_author(author):
"""
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Parameters
----------
author : str or unicode
Author fullname, e.g. "Richard L. Nixon".
Returns
-------
aulast : str
Author surname.
auinit : str
Author first-initial.
"... | python | def _handle_author(author):
"""
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----------
author : str or unicode
Author fullname, e.g. "Richard L. Nixon".
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-------
aulast : str
Author surname.
auinit : str
Author first-initial.
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diging/tethne | tethne/readers/dfr.py | GramGenerator._get | def _get(self, i):
"""
Retrieve data for the ith file in the dataset.
"""
with open(os.path.join(self.path, self.elem, self.files[i]), 'r') as f:
# JSTOR hasn't always produced valid XML.
contents = re.sub('(&)(?!amp;)', lambda match: '&', f.read())
... | python | def _get(self, i):
"""
Retrieve data for the ith file in the dataset.
"""
with open(os.path.join(self.path, self.elem, self.files[i]), 'r') as f:
# JSTOR hasn't always produced valid XML.
contents = re.sub('(&)(?!amp;)', lambda match: '&', f.read())
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diging/tethne | tethne/model/corpus/mallet.py | LDAModel._generate_corpus | def _generate_corpus(self):
"""
Writes a corpus to disk amenable to MALLET topic modeling.
"""
target = self.temp + 'mallet'
paths = write_documents(self.corpus, target, self.featureset_name,
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self.corpus_path, self.metap... | python | def _generate_corpus(self):
"""
Writes a corpus to disk amenable to MALLET topic modeling.
"""
target = self.temp + 'mallet'
paths = write_documents(self.corpus, target, self.featureset_name,
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diging/tethne | tethne/model/corpus/mallet.py | LDAModel._export_corpus | def _export_corpus(self):
"""
Calls MALLET's `import-file` method.
"""
# bin/mallet import-file --input /Users/erickpeirson/mycorpus_docs.txt
# --output mytopic-input.mallet --keep-sequence --remove-stopwords
if not os.path.exists(self.mallet_bin):
raise ... | python | def _export_corpus(self):
"""
Calls MALLET's `import-file` method.
"""
# bin/mallet import-file --input /Users/erickpeirson/mycorpus_docs.txt
# --output mytopic-input.mallet --keep-sequence --remove-stopwords
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diging/tethne | tethne/model/corpus/mallet.py | LDAModel.run | def run(self, **kwargs):
"""
Calls MALLET's `train-topic` method.
"""
#$ bin/mallet train-topics --input mytopic-input.mallet
#> --num-topics 100
#> --output-doc-topics /Users/erickpeirson/doc_top
#> --word-topic-counts-file /Users/erickpeirson/word_top
#>... | python | def run(self, **kwargs):
"""
Calls MALLET's `train-topic` method.
"""
#$ bin/mallet train-topics --input mytopic-input.mallet
#> --num-topics 100
#> --output-doc-topics /Users/erickpeirson/doc_top
#> --word-topic-counts-file /Users/erickpeirson/word_top
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diging/tethne | tethne/model/corpus/mallet.py | LDAModel.topics_in | def topics_in(self, d, topn=5):
"""
List the top ``topn`` topics in document ``d``.
"""
return self.theta.features[d].top(topn) | python | def topics_in(self, d, topn=5):
"""
List the top ``topn`` topics in document ``d``.
"""
return self.theta.features[d].top(topn) | [
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diging/tethne | tethne/model/corpus/mallet.py | LDAModel.list_topic | def list_topic(self, k, Nwords=10):
"""
List the top ``topn`` words for topic ``k``.
Examples
--------
.. code-block:: python
>>> model.list_topic(1, Nwords=5)
[ 'opposed', 'terminates', 'trichinosis', 'cistus', 'acaule' ]
"""
return [(... | python | def list_topic(self, k, Nwords=10):
"""
List the top ``topn`` words for topic ``k``.
Examples
--------
.. code-block:: python
>>> model.list_topic(1, Nwords=5)
[ 'opposed', 'terminates', 'trichinosis', 'cistus', 'acaule' ]
"""
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diging/tethne | tethne/model/corpus/mallet.py | LDAModel.list_topics | def list_topics(self, Nwords=10):
"""
List the top ``Nwords`` words for each topic.
"""
return [(k, self.list_topic(k, Nwords)) for k in xrange(len(self.phi))] | python | def list_topics(self, Nwords=10):
"""
List the top ``Nwords`` words for each topic.
"""
return [(k, self.list_topic(k, Nwords)) for k in xrange(len(self.phi))] | [
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diging/tethne | tethne/model/corpus/mallet.py | LDAModel.print_topics | def print_topics(self, Nwords=10):
"""
Print the top ``Nwords`` words for each topic.
"""
print('Topic\tTop %i words' % Nwords)
for k, words in self.list_topics(Nwords):
print(unicode(k).ljust(3) + '\t' + ' '.join(list(zip(*words))[0])) | python | def print_topics(self, Nwords=10):
"""
Print the top ``Nwords`` words for each topic.
"""
print('Topic\tTop %i words' % Nwords)
for k, words in self.list_topics(Nwords):
print(unicode(k).ljust(3) + '\t' + ' '.join(list(zip(*words))[0])) | [
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diging/tethne | tethne/model/corpus/mallet.py | LDAModel.topic_over_time | def topic_over_time(self, k, mode='counts', slice_kwargs={}):
"""
Calculate the representation of topic ``k`` in the corpus over time.
"""
return self.corpus.feature_distribution('topics', k, mode=mode,
**slice_kwargs) | python | def topic_over_time(self, k, mode='counts', slice_kwargs={}):
"""
Calculate the representation of topic ``k`` in the corpus over time.
"""
return self.corpus.feature_distribution('topics', k, mode=mode,
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diging/tethne | tethne/classes/corpus.py | Corpus.distribution | def distribution(self, **slice_kwargs):
"""
Calculates the number of papers in each slice, as defined by
``slice_kwargs``.
Examples
--------
.. code-block:: python
>>> corpus.distribution(step_size=1, window_size=1)
[5, 5]
Parameters
... | python | def distribution(self, **slice_kwargs):
"""
Calculates the number of papers in each slice, as defined by
``slice_kwargs``.
Examples
--------
.. code-block:: python
>>> corpus.distribution(step_size=1, window_size=1)
[5, 5]
Parameters
... | [
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.. code-block:: python
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diging/tethne | tethne/classes/corpus.py | Corpus.feature_distribution | def feature_distribution(self, featureset_name, feature, mode='counts',
**slice_kwargs):
"""
Calculates the distribution of a feature across slices of the corpus.
Examples
--------
.. code-block:: python
>>> corpus.feature_distribution(fe... | python | def feature_distribution(self, featureset_name, feature, mode='counts',
**slice_kwargs):
"""
Calculates the distribution of a feature across slices of the corpus.
Examples
--------
.. code-block:: python
>>> corpus.feature_distribution(fe... | [
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.. code-block:: python
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diging/tethne | tethne/classes/corpus.py | Corpus.top_features | def top_features(self, featureset_name, topn=20, by='counts',
perslice=False, slice_kwargs={}):
"""
Retrieves the top ``topn`` most numerous features in the corpus.
Parameters
----------
featureset_name : str
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perslice=False, slice_kwargs={}):
"""
Retrieves the top ``topn`` most numerous features in the corpus.
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----------
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diging/tethne | tethne/analyze/corpus.py | feature_burstness | def feature_burstness(corpus, featureset_name, feature, k=5, normalize=True,
s=1.1, gamma=1., **slice_kwargs):
"""
Estimate burstness profile for a feature over the ``'date'`` axis.
Parameters
----------
corpus : :class:`.Corpus`
feature : str
Name of featureset in... | python | def feature_burstness(corpus, featureset_name, feature, k=5, normalize=True,
s=1.1, gamma=1., **slice_kwargs):
"""
Estimate burstness profile for a feature over the ``'date'`` axis.
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----------
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diging/tethne | tethne/networks/papers.py | cocitation | def cocitation(corpus, min_weight=1, edge_attrs=['ayjid', 'date'], **kwargs):
"""
Generate a cocitation network.
A **cocitation network** is a network in which vertices are papers, and
edges indicate that two papers were cited by the same third paper.
`CiteSpace
<http://cluster.cis.drexel.edu/~... | python | def cocitation(corpus, min_weight=1, edge_attrs=['ayjid', 'date'], **kwargs):
"""
Generate a cocitation network.
A **cocitation network** is a network in which vertices are papers, and
edges indicate that two papers were cited by the same third paper.
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diging/tethne | tethne/classes/feature.py | StructuredFeature.context_chunk | def context_chunk(self, context, j):
"""
Retrieve the tokens in the ``j``th chunk of context ``context``.
Parameters
----------
context : str
Context name.
j : int
Index of a context chunk.
Returns
-------
chunk : list
... | python | def context_chunk(self, context, j):
"""
Retrieve the tokens in the ``j``th chunk of context ``context``.
Parameters
----------
context : str
Context name.
j : int
Index of a context chunk.
Returns
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chunk : list
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diging/tethne | tethne/classes/feature.py | StructuredFeature.add_context | def add_context(self, name, indices, level=None):
"""
Add a new context level to the hierarchy.
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diging/tethne | tethne/classes/graphcollection.py | GraphCollection.index | def index(self, name, graph):
"""
Index any new nodes in `graph`, and relabel the nodes in `graph` using
the index.
Parameters
----------
name : hashable
Unique name used to identify the `graph`.
graph : networkx.Graph
Returns
-------... | python | def index(self, name, graph):
"""
Index any new nodes in `graph`, and relabel the nodes in `graph` using
the index.
Parameters
----------
name : hashable
Unique name used to identify the `graph`.
graph : networkx.Graph
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diging/tethne | tethne/networks/topics.py | terms | def terms(model, threshold=0.01, **kwargs):
"""
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Parameters
----------
model : :class:`.LDAModel`
threshold : float
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kwargs : kwargs
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"""
Two terms are coupled if the posterior probability for both terms is
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diging/tethne | tethne/networks/topics.py | topic_coupling | def topic_coupling(model, threshold=None, **kwargs):
"""
Two papers are coupled if they both contain a shared topic above a
``threshold``.
Parameters
----------
model : :class:`.LDAModel`
threshold : float
Default: ``3./model.Z``
kwargs : kwargs
Passed on to :func:`.coup... | python | def topic_coupling(model, threshold=None, **kwargs):
"""
Two papers are coupled if they both contain a shared topic above a
``threshold``.
Parameters
----------
model : :class:`.LDAModel`
threshold : float
Default: ``3./model.Z``
kwargs : kwargs
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diging/tethne | tethne/analyze/features.py | kl_divergence | def kl_divergence(V_a, V_b):
"""
Calculate Kullback-Leibler distance.
Uses the smoothing method described in `Bigi 2003
<http://lvk.cs.msu.su/~bruzz/articles/classification/Using%20Kullback-Leibler%20Distance%20for%20Text%20Categorization.pdf>`_
to facilitate better comparisons between vectors desc... | python | def kl_divergence(V_a, V_b):
"""
Calculate Kullback-Leibler distance.
Uses the smoothing method described in `Bigi 2003
<http://lvk.cs.msu.su/~bruzz/articles/classification/Using%20Kullback-Leibler%20Distance%20for%20Text%20Categorization.pdf>`_
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diging/tethne | tethne/analyze/features.py | _shared_features | def _shared_features(adense, bdense):
"""
Number of features in ``adense`` that are also in ``bdense``.
"""
a_indices = set(nonzero(adense))
b_indices = set(nonzero(bdense))
shared = list(a_indices & b_indices)
diff = list(a_indices - b_indices)
Ndiff = len(diff)
return Ndiff | python | def _shared_features(adense, bdense):
"""
Number of features in ``adense`` that are also in ``bdense``.
"""
a_indices = set(nonzero(adense))
b_indices = set(nonzero(bdense))
shared = list(a_indices & b_indices)
diff = list(a_indices - b_indices)
Ndiff = len(diff)
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diging/tethne | tethne/networks/base.py | cooccurrence | def cooccurrence(corpus_or_featureset, featureset_name=None, min_weight=1,
edge_attrs=['ayjid', 'date'],
filter=None):
"""
A network of feature elements linked by their joint occurrence in papers.
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"""
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diging/tethne | tethne/networks/base.py | coupling | def coupling(corpus_or_featureset, featureset_name=None,
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node_attrs=[]):
"""
A network of papers linked by their joint posession of features.
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diging/tethne | tethne/networks/base.py | multipartite | def multipartite(corpus, featureset_names, min_weight=1, filters={}):
"""
A network of papers and one or more featuresets.
"""
pairs = Counter()
node_type = {corpus._generate_index(p): {'type': 'paper'}
for p in corpus.papers}
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ft... | python | def multipartite(corpus, featureset_names, min_weight=1, filters={}):
"""
A network of papers and one or more featuresets.
"""
pairs = Counter()
node_type = {corpus._generate_index(p): {'type': 'paper'}
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diging/tethne | tethne/utilities.py | _strip_punctuation | def _strip_punctuation(s):
"""
Removes all punctuation characters from a string.
"""
if type(s) is str and not PYTHON_3: # Bytestring (default in Python 2.x).
return s.translate(string.maketrans("",""), string.punctuation)
else: # Unicode string (default in Python 3.x).
... | python | def _strip_punctuation(s):
"""
Removes all punctuation characters from a string.
"""
if type(s) is str and not PYTHON_3: # Bytestring (default in Python 2.x).
return s.translate(string.maketrans("",""), string.punctuation)
else: # Unicode string (default in Python 3.x).
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diging/tethne | tethne/utilities.py | overlap | def overlap(listA, listB):
"""
Return list of objects shared by listA, listB.
"""
if (listA is None) or (listB is None):
return []
else:
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"""
Return list of objects shared by listA, listB.
"""
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return []
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diging/tethne | tethne/utilities.py | subdict | def subdict(super_dict, keys):
"""
Returns a subset of the super_dict with the specified keys.
"""
sub_dict = {}
valid_keys = super_dict.keys()
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if key in valid_keys:
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"""
Returns a subset of the super_dict with the specified keys.
"""
sub_dict = {}
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diging/tethne | tethne/utilities.py | concat_list | def concat_list(listA, listB, delim=' '):
"""
Concatenate list elements pair-wise with the delim character
Returns the concatenated list
Raises index error if lists are not parallel
"""
# Lists must be of equal length.
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"""
Concatenate list elements pair-wise with the delim character
Returns the concatenated list
Raises index error if lists are not parallel
"""
# Lists must be of equal length.
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diging/tethne | tethne/utilities.py | strip_non_ascii | def strip_non_ascii(s):
"""
Returns the string without non-ASCII characters.
Parameters
----------
string : string
A string that may contain non-ASCII characters.
Returns
-------
clean_string : string
A string that does not contain non-ASCII characters.
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"""
Returns the string without non-ASCII characters.
Parameters
----------
string : string
A string that may contain non-ASCII characters.
Returns
-------
clean_string : string
A string that does not contain non-ASCII characters.
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diging/tethne | tethne/utilities.py | dict_from_node | def dict_from_node(node, recursive=False):
"""
Converts ElementTree node to a dictionary.
Parameters
----------
node : ElementTree node
recursive : boolean
If recursive=False, the value of any field with children will be the
number of children.
Returns
-------
dict ... | python | def dict_from_node(node, recursive=False):
"""
Converts ElementTree node to a dictionary.
Parameters
----------
node : ElementTree node
recursive : boolean
If recursive=False, the value of any field with children will be the
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Returns
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diging/tethne | tethne/utilities.py | MLStripper.feed | def feed(self, data):
"""
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except TypeError:
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"""
added this check as sometimes we are getting the data in integer format instead of string
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diging/tethne | tethne/serialize/paper.py | Serialize.serializePaper | def serializePaper(self):
"""
This method creates a fixture for the "django-tethne_paper" model.
Returns
-------
paper_details in JSON format, which can written to a file.
"""
pid = tethnedao.getMaxPaperID();
papers_details = []
for paper in sel... | python | def serializePaper(self):
"""
This method creates a fixture for the "django-tethne_paper" model.
Returns
-------
paper_details in JSON format, which can written to a file.
"""
pid = tethnedao.getMaxPaperID();
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diging/tethne | tethne/serialize/paper.py | Serialize.serializeCitation | def serializeCitation(self):
"""
This method creates a fixture for the "django-tethne_citation" model.
Returns
-------
citation details which can be written to a file
"""
citation_details = []
citation_id = tethnedao.getMaxCitationID()
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"""
This method creates a fixture for the "django-tethne_citation" model.
Returns
-------
citation details which can be written to a file
"""
citation_details = []
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diging/tethne | tethne/serialize/paper.py | Serialize.serializeInstitution | def serializeInstitution(self):
"""
This method creates a fixture for the "django-tethne_citation_institution" model.
Returns
-------
institution details which can be written to a file
"""
institution_data = []
institution_instance_data = []
affi... | python | def serializeInstitution(self):
"""
This method creates a fixture for the "django-tethne_citation_institution" model.
Returns
-------
institution details which can be written to a file
"""
institution_data = []
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diging/tethne | tethne/serialize/paper.py | Serialize.get_details_from_inst_literal | def get_details_from_inst_literal(self, institute_literal, institution_id, institution_instance_id, paper_key):
"""
This method parses the institute literal to get the following
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2. Country
3. University name
4. ZIP, STATE AND CITY (Only if the country ... | python | def get_details_from_inst_literal(self, institute_literal, institution_id, institution_instance_id, paper_key):
"""
This method parses the institute literal to get the following
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diging/tethne | tethne/serialize/paper.py | Serialize.get_affiliation_details | def get_affiliation_details(self, value, affiliation_id, institute_literal):
"""
This method is used to map the Affiliation between an author and Institution.
Parameters
----------
value - The author name
affiliation_id - Primary key of the affiliation table
inst... | python | def get_affiliation_details(self, value, affiliation_id, institute_literal):
"""
This method is used to map the Affiliation between an author and Institution.
Parameters
----------
value - The author name
affiliation_id - Primary key of the affiliation table
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diging/tethne | tethne/readers/base.py | IterParser.start | def start(self):
"""
Find the first data entry and prepare to parse.
"""
while not self.is_start(self.current_tag):
self.next()
self.new_entry() | python | def start(self):
"""
Find the first data entry and prepare to parse.
"""
while not self.is_start(self.current_tag):
self.next()
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diging/tethne | tethne/readers/base.py | IterParser.handle | def handle(self, tag, data):
"""
Process a single line of data, and store the result.
Parameters
----------
tag : str
data :
"""
if self.is_end(tag):
self.postprocess_entry()
if self.is_start(tag):
self.new_entry()
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"""
Process a single line of data, and store the result.
Parameters
----------
tag : str
data :
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if self.is_end(tag):
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diging/tethne | tethne/readers/base.py | FTParser.open | def open(self):
"""
Open the data file.
"""
if not os.path.exists(self.path):
raise IOError("No such path: {0}".format(self.path))
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"""
Open the data file.
"""
if not os.path.exists(self.path):
raise IOError("No such path: {0}".format(self.path))
with open(self.path, "rb") as f:
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diging/tethne | tethne/readers/base.py | FTParser.next | def next(self):
"""
Get the next line of data.
Returns
-------
tag : str
data :
"""
line = self.buffer.readline()
while line == '\n': # Skip forward to the next line with content.
line = self.buffer.readline()
if line =... | python | def next(self):
"""
Get the next line of data.
Returns
-------
tag : str
data :
"""
line = self.buffer.readline()
while line == '\n': # Skip forward to the next line with content.
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diging/tethne | tethne/networks/authors.py | coauthors | def coauthors(corpus, min_weight=1, edge_attrs=['ayjid', 'date'], **kwargs):
"""
A graph describing joint authorship in ``corpus``.
"""
return cooccurrence(corpus, 'authors', min_weight=min_weight,
edge_attrs=edge_attrs, **kwargs) | python | def coauthors(corpus, min_weight=1, edge_attrs=['ayjid', 'date'], **kwargs):
"""
A graph describing joint authorship in ``corpus``.
"""
return cooccurrence(corpus, 'authors', min_weight=min_weight,
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diging/tethne | tethne/readers/zotero.py | extract_text | def extract_text(fpath):
"""
Extracts structured text content from a plain-text file at ``fpath``.
Parameters
----------
fpath : str
Path to the text file..
Returns
-------
:class:`.StructuredFeature`
A :class:`.StructuredFeature` that contains sentence context.
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"""
Extracts structured text content from a plain-text file at ``fpath``.
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----------
fpath : str
Path to the text file..
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:class:`.StructuredFeature`
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diging/tethne | tethne/readers/zotero.py | extract_pdf | def extract_pdf(fpath):
"""
Extracts structured text content from a PDF at ``fpath``.
Parameters
----------
fpath : str
Path to the PDF.
Returns
-------
:class:`.StructuredFeature`
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"""
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"""
Extracts structured text content from a PDF at ``fpath``.
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----------
fpath : str
Path to the PDF.
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:class:`.StructuredFeature`
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diging/tethne | tethne/readers/zotero.py | read | def read(path, corpus=True, index_by='uri', follow_links=False, **kwargs):
"""
Read bibliographic data from Zotero RDF.
Examples
--------
Assuming that the Zotero collection was exported to the directory
``/my/working/dir`` with the name ``myCollection``, a subdirectory should
have been cre... | python | def read(path, corpus=True, index_by='uri', follow_links=False, **kwargs):
"""
Read bibliographic data from Zotero RDF.
Examples
--------
Assuming that the Zotero collection was exported to the directory
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diging/tethne | tethne/readers/zotero.py | ZoteroParser.handle_date | def handle_date(self, value):
"""
Attempt to coerced date to ISO8601.
"""
try:
return iso8601.parse_date(unicode(value)).year
except iso8601.ParseError:
for datefmt in ("%B %d, %Y", "%Y-%m", "%Y-%m-%d", "%m/%d/%Y"):
try:
... | python | def handle_date(self, value):
"""
Attempt to coerced date to ISO8601.
"""
try:
return iso8601.parse_date(unicode(value)).year
except iso8601.ParseError:
for datefmt in ("%B %d, %Y", "%Y-%m", "%Y-%m-%d", "%m/%d/%Y"):
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diging/tethne | tethne/readers/zotero.py | ZoteroParser.postprocess_link | def postprocess_link(self, entry):
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Attempt to load full-text content from resource.
"""
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if not os.path.exis... | python | def postprocess_link(self, entry):
"""
Attempt to load full-text content from resource.
"""
if not self.follow_links:
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entry.link = [entry.link]
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web-push-libs/pywebpush | pywebpush/__init__.py | webpush | def webpush(subscription_info,
data=None,
vapid_private_key=None,
vapid_claims=None,
content_encoding="aes128gcm",
curl=False,
timeout=None,
ttl=0):
"""
One call solution to endcode and send `data` to the endpoint
co... | python | def webpush(subscription_info,
data=None,
vapid_private_key=None,
vapid_claims=None,
content_encoding="aes128gcm",
curl=False,
timeout=None,
ttl=0):
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web-push-libs/pywebpush | pywebpush/__init__.py | WebPusher.encode | def encode(self, data, content_encoding="aes128gcm"):
"""Encrypt the data.
:param data: A serialized block of byte data (String, JSON, bit array,
etc.) Make sure that whatever you send, your client knows how
to understand it.
:type data: str
:param content_encodi... | python | def encode(self, data, content_encoding="aes128gcm"):
"""Encrypt the data.
:param data: A serialized block of byte data (String, JSON, bit array,
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martijnvermaat/calmap | calmap/__init__.py | calendarplot | def calendarplot(data, how='sum', yearlabels=True, yearascending=True, yearlabel_kws=None,
subplot_kws=None, gridspec_kws=None, fig_kws=None, **kwargs):
"""
Plot a timeseries as a calendar heatmap.
Parameters
----------
data : Series
Data for the plot. Must be indexed by a ... | python | def calendarplot(data, how='sum', yearlabels=True, yearascending=True, yearlabel_kws=None,
subplot_kws=None, gridspec_kws=None, fig_kws=None, **kwargs):
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Plot a timeseries as a calendar heatmap.
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Frojd/wagtail-geo-widget | wagtailgeowidget/helpers.py | geosgeometry_str_to_struct | def geosgeometry_str_to_struct(value):
'''
Parses a geosgeometry string into struct.
Example:
SRID=5432;POINT(12.0 13.0)
Returns:
>> [5432, 12.0, 13.0]
'''
result = geos_ptrn.match(value)
if not result:
return None
return {
'srid': result.group(1),
... | python | def geosgeometry_str_to_struct(value):
'''
Parses a geosgeometry string into struct.
Example:
SRID=5432;POINT(12.0 13.0)
Returns:
>> [5432, 12.0, 13.0]
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Frojd/wagtail-geo-widget | example/examplesite/settings/__init__.py | get_env | def get_env(name, default=None):
"""Get the environment variable or return exception"""
if name in os.environ:
return os.environ[name]
if default is not None:
return default
error_msg = "Set the {} env variable".format(name)
raise ImproperlyConfigured(error_msg) | python | def get_env(name, default=None):
"""Get the environment variable or return exception"""
if name in os.environ:
return os.environ[name]
if default is not None:
return default
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newville/asteval | asteval/asteval.py | Interpreter.user_defined_symbols | def user_defined_symbols(self):
"""Return a set of symbols that have been added to symtable after
construction.
I.e., the symbols from self.symtable that are not in
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Returns
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symbols in symtable that are n... | python | def user_defined_symbols(self):
"""Return a set of symbols that have been added to symtable after
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newville/asteval | asteval/asteval.py | Interpreter.unimplemented | def unimplemented(self, node):
"""Unimplemented nodes."""
self.raise_exception(node, exc=NotImplementedError,
msg="'%s' not supported" %
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newville/asteval | asteval/asteval.py | Interpreter.raise_exception | def raise_exception(self, node, exc=None, msg='', expr=None,
lineno=None):
"""Add an exception."""
if self.error is None:
self.error = []
if expr is None:
expr = self.expr
if len(self.error) > 0 and not isinstance(node, ast.Module):
... | python | def raise_exception(self, node, exc=None, msg='', expr=None,
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"""Add an exception."""
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expr = self.expr
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newville/asteval | asteval/asteval.py | Interpreter.run | def run(self, node, expr=None, lineno=None, with_raise=True):
"""Execute parsed Ast representation for an expression."""
# Note: keep the 'node is None' test: internal code here may run
# run(None) and expect a None in return.
if time.time() - self.start_time > self.max_time:
... | python | def run(self, node, expr=None, lineno=None, with_raise=True):
"""Execute parsed Ast representation for an expression."""
# Note: keep the 'node is None' test: internal code here may run
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newville/asteval | asteval/asteval.py | Interpreter.eval | def eval(self, expr, lineno=0, show_errors=True):
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try:
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if len(self.error) > 0:
... | python | def eval(self, expr, lineno=0, show_errors=True):
"""Evaluate a single statement."""
self.lineno = lineno
self.error = []
self.start_time = time.time()
try:
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newville/asteval | asteval/asteval.py | Interpreter.on_module | def on_module(self, node): # ():('body',)
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newville/asteval | asteval/asteval.py | Interpreter.on_assert | def on_assert(self, node): # ('test', 'msg')
"""Assert statement."""
if not self.run(node.test):
self.raise_exception(node, exc=AssertionError, msg=node.msg)
return True | python | def on_assert(self, node): # ('test', 'msg')
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newville/asteval | asteval/asteval.py | Interpreter.on_name | def on_name(self, node): # ('id', 'ctx')
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newville/asteval | asteval/asteval.py | Interpreter.on_attribute | def on_attribute(self, node): # ('value', 'attr', 'ctx')
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ctx = node.ctx.__class__
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msg = "attribute for storage: shouldn't be here!"
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... | python | def on_attribute(self, node): # ('value', 'attr', 'ctx')
"""Extract attribute."""
ctx = node.ctx.__class__
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newville/asteval | asteval/asteval.py | Interpreter.on_assign | def on_assign(self, node): # ('targets', 'value')
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val = self.run(node.value)
for tnode in node.targets:
self.node_assign(tnode, val)
return | python | def on_assign(self, node): # ('targets', 'value')
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newville/asteval | asteval/asteval.py | Interpreter.on_augassign | def on_augassign(self, node): # ('target', 'op', 'value')
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newville/asteval | asteval/asteval.py | Interpreter.on_slice | def on_slice(self, node): # ():('lower', 'upper', 'step')
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newville/asteval | asteval/asteval.py | Interpreter.on_extslice | def on_extslice(self, node): # ():('dims',)
"""Extended slice."""
return tuple([self.run(tnode) for tnode in node.dims]) | python | def on_extslice(self, node): # ():('dims',)
"""Extended slice."""
return tuple([self.run(tnode) for tnode in node.dims]) | [
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newville/asteval | asteval/asteval.py | Interpreter.on_delete | def on_delete(self, node): # ('targets',)
"""Delete statement."""
for tnode in node.targets:
if tnode.ctx.__class__ != ast.Del:
break
children = []
while tnode.__class__ == ast.Attribute:
children.append(tnode.attr)
t... | python | def on_delete(self, node): # ('targets',)
"""Delete statement."""
for tnode in node.targets:
if tnode.ctx.__class__ != ast.Del:
break
children = []
while tnode.__class__ == ast.Attribute:
children.append(tnode.attr)
t... | [
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newville/asteval | asteval/asteval.py | Interpreter.on_unaryop | def on_unaryop(self, node): # ('op', 'operand')
"""Unary operator."""
return op2func(node.op)(self.run(node.operand)) | python | def on_unaryop(self, node): # ('op', 'operand')
"""Unary operator."""
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newville/asteval | asteval/asteval.py | Interpreter.on_binop | def on_binop(self, node): # ('left', 'op', 'right')
"""Binary operator."""
return op2func(node.op)(self.run(node.left),
self.run(node.right)) | python | def on_binop(self, node): # ('left', 'op', 'right')
"""Binary operator."""
return op2func(node.op)(self.run(node.left),
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newville/asteval | asteval/asteval.py | Interpreter.on_boolop | def on_boolop(self, node): # ('op', 'values')
"""Boolean operator."""
val = self.run(node.values[0])
is_and = ast.And == node.op.__class__
if (is_and and val) or (not is_and and not val):
for n in node.values[1:]:
val = op2func(node.op)(val, self.run(n))
... | python | def on_boolop(self, node): # ('op', 'values')
"""Boolean operator."""
val = self.run(node.values[0])
is_and = ast.And == node.op.__class__
if (is_and and val) or (not is_and and not val):
for n in node.values[1:]:
val = op2func(node.op)(val, self.run(n))
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newville/asteval | asteval/asteval.py | Interpreter._printer | def _printer(self, *out, **kws):
"""Generic print function."""
flush = kws.pop('flush', True)
fileh = kws.pop('file', self.writer)
sep = kws.pop('sep', ' ')
end = kws.pop('sep', '\n')
print(*out, file=fileh, sep=sep, end=end)
if flush:
fileh.flush() | python | def _printer(self, *out, **kws):
"""Generic print function."""
flush = kws.pop('flush', True)
fileh = kws.pop('file', self.writer)
sep = kws.pop('sep', ' ')
end = kws.pop('sep', '\n')
print(*out, file=fileh, sep=sep, end=end)
if flush:
fileh.flush() | [
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newville/asteval | asteval/asteval.py | Interpreter.on_if | def on_if(self, node): # ('test', 'body', 'orelse')
"""Regular if-then-else statement."""
block = node.body
if not self.run(node.test):
block = node.orelse
for tnode in block:
self.run(tnode) | python | def on_if(self, node): # ('test', 'body', 'orelse')
"""Regular if-then-else statement."""
block = node.body
if not self.run(node.test):
block = node.orelse
for tnode in block:
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newville/asteval | asteval/asteval.py | Interpreter.on_ifexp | def on_ifexp(self, node): # ('test', 'body', 'orelse')
"""If expressions."""
expr = node.orelse
if self.run(node.test):
expr = node.body
return self.run(expr) | python | def on_ifexp(self, node): # ('test', 'body', 'orelse')
"""If expressions."""
expr = node.orelse
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expr = node.body
return self.run(expr) | [
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newville/asteval | asteval/asteval.py | Interpreter.on_while | def on_while(self, node): # ('test', 'body', 'orelse')
"""While blocks."""
while self.run(node.test):
self._interrupt = None
for tnode in node.body:
self.run(tnode)
if self._interrupt is not None:
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if isinsta... | python | def on_while(self, node): # ('test', 'body', 'orelse')
"""While blocks."""
while self.run(node.test):
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newville/asteval | asteval/asteval.py | Interpreter.on_for | def on_for(self, node): # ('target', 'iter', 'body', 'orelse')
"""For blocks."""
for val in self.run(node.iter):
self.node_assign(node.target, val)
self._interrupt = None
for tnode in node.body:
self.run(tnode)
if self._interrupt is ... | python | def on_for(self, node): # ('target', 'iter', 'body', 'orelse')
"""For blocks."""
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newville/asteval | asteval/asteval.py | Interpreter.on_listcomp | def on_listcomp(self, node): # ('elt', 'generators')
"""List comprehension."""
out = []
for tnode in node.generators:
if tnode.__class__ == ast.comprehension:
for val in self.run(tnode.iter):
self.node_assign(tnode.target, val)
... | python | def on_listcomp(self, node): # ('elt', 'generators')
"""List comprehension."""
out = []
for tnode in node.generators:
if tnode.__class__ == ast.comprehension:
for val in self.run(tnode.iter):
self.node_assign(tnode.target, val)
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] | bb7d3a95079f96ead75ea55662014bbcc82f9b28 | https://github.com/newville/asteval/blob/bb7d3a95079f96ead75ea55662014bbcc82f9b28/asteval/asteval.py#L683-L695 | train |
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