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def accuracy(self, test_set, format=None):
"""Compute the accuracy on a test set. :param test_set: A list of tuples of the form ``(text, label)``, or a filename. :param format: If ``test_set`` is a filename, the file format, e.g. ``"csv"`` or ``"json"``. If ``None``, will attempt to detect the file format. """ |
if isinstance(test_set, basestring): # test_set is a filename
test_data = self._read_data(test_set)
else: # test_set is a list of tuples
test_data = test_set
test_features = [(self.extract_features(d), c) for d, c in test_data]
return nltk.classify.accuracy(self.classifier, test_features) |
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| def update(self, new_data, *args, **kwargs):
'''Update the classifier with new training data and re-trains the
classifier.
:param new_data: New data as a list of tuples of the form
``(text, label)``.
'''
self.train_set += new_data
self.train_features = [(self.extract_features(d), c)
for d, c in self.train_set]
try:
self.classifier = self.nltk_class.train(self.train_features,
*args, **kwargs)
except AttributeError: # Descendant has not defined nltk_class
raise ValueError("NLTKClassifier must have a nltk_class"
" variable that is not None.")
return True |
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def train(self, *args, **kwargs):
"""Train the classifier with a labeled and unlabeled feature sets and return the classifier. Takes the same arguments as the wrapped NLTK class. This method is implicitly called when calling ``classify`` or ``accuracy`` methods and is included only to allow passing in arguments to the ``train`` method of the wrapped NLTK class. :rtype: A classifier """ |
self.classifier = self.nltk_class.train(self.positive_features,
self.unlabeled_features,
self.positive_prob_prior)
return self.classifier |
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| def update(self, new_positive_data=None,
new_unlabeled_data=None, positive_prob_prior=0.5,
*args, **kwargs):
'''Update the classifier with new data and re-trains the
classifier.
:param new_positive_data: List of new, labeled strings.
:param new_unlabeled_data: List of new, unlabeled strings.
'''
self.positive_prob_prior = positive_prob_prior
if new_positive_data:
self.positive_set += new_positive_data
self.positive_features += [self.extract_features(d)
for d in new_positive_data]
if new_unlabeled_data:
self.unlabeled_set += new_unlabeled_data
self.unlabeled_features += [self.extract_features(d)
for d in new_unlabeled_data]
self.classifier = self.nltk_class.train(self.positive_features,
self.unlabeled_features,
self.positive_prob_prior,
*args, **kwargs)
return True |
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def variations(iterable, optional=lambda x: False):
""" Returns all possible variations of a sequence with optional items. """ |
# For example: variations(["A?", "B?", "C"], optional=lambda s: s.endswith("?"))
# defines a sequence where constraint A and B are optional:
# [("A?", "B?", "C"), ("B?", "C"), ("A?", "C"), ("C")]
iterable = tuple(iterable)
# Create a boolean sequence where True means optional:
# ("A?", "B?", "C") => [True, True, False]
o = [optional(x) for x in iterable]
# Find all permutations of the boolean sequence:
# [True, False, True], [True, False, False], [False, False, True], [False, False, False].
# Map to sequences of constraints whose index in the boolean sequence yields True.
a = set()
for p in product([False, True], repeat=sum(o)):
p = list(p)
v = [b and (b and p.pop(0)) for b in o]
v = tuple(iterable[i] for i in xrange(len(v)) if not v[i])
a.add(v)
# Longest-first.
return sorted(a, cmp=lambda x, y: len(y) - len(x)) |
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def parents(self, term, recursive=False, **kwargs):
""" Returns a list of all semantic types for the given term. If recursive=True, traverses parents up to the root. """ |
def dfs(term, recursive=False, visited={}, **kwargs):
if term in visited: # Break on cyclic relations.
return []
visited[term], a = True, []
if dict.__contains__(self, term):
a = self[term][0].keys()
for classifier in self.classifiers:
a.extend(classifier.parents(term, **kwargs) or [])
if recursive:
for w in a: a += dfs(w, recursive, visited, **kwargs)
return a
return unique(dfs(self._normalize(term), recursive, {}, **kwargs)) |
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def constraint(self, word):
""" Returns the constraint that matches the given Word, or None. """ |
if word.index in self._map1:
return self._map1[word.index] |
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def constraints(self, chunk):
""" Returns a list of constraints that match the given Chunk. """ |
a = [self._map1[w.index] for w in chunk.words if w.index in self._map1]
b = []; [b.append(constraint) for constraint in a if constraint not in b]
return b |
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def tree(s, token=[WORD, POS, CHUNK, PNP, REL, LEMMA]):
""" Returns a parsed Text from the given parsed string. """ |
return Text(s, token) |
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def word_tokenize(text, tokenizer=None, include_punc=True, *args, **kwargs):
"""Convenience function for tokenizing text into words. NOTE: NLTK's word tokenizer expects sentences as input, so the text will be tokenized to sentences before being tokenized to words. This function returns an itertools chain object (generator). """ |
_tokenizer = tokenizer if tokenizer is not None else NLTKPunktTokenizer()
words = chain.from_iterable(
WordTokenizer(tokenizer=_tokenizer).itokenize(sentence, include_punc,
*args, **kwargs)
for sentence in sent_tokenize(text, tokenizer=_tokenizer))
return words |
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def word_tokenize(self, text, include_punc=True):
"""The Treebank tokenizer uses regular expressions to tokenize text as in Penn Treebank. It assumes that the text has already been segmented into sentences, e.g. using ``self.sent_tokenize()``. This tokenizer performs the following steps: - split standard contractions, e.g. ``don't`` -> ``do n't`` and ``they'll`` -> ``they 'll`` - treat most punctuation characters as separate tokens - split off commas and single quotes, when followed by whitespace - separate periods that appear at the end of line Source: NLTK's docstring of ``TreebankWordTokenizer`` (accessed: 02/10/2014) """ |
#: Do not process empty strings (Issue #3)
if text.strip() == "":
return []
_tokens = self.word_tok.tokenize(text)
#: Handle strings consisting of a single punctuation mark seperately (Issue #4)
if len(_tokens) == 1:
if _tokens[0] in PUNCTUATION:
if include_punc:
return _tokens
else:
return []
if include_punc:
return _tokens
else:
# Return each word token
# Strips punctuation unless the word comes from a contraction
# e.g. "gibt's" => ["gibt", "'s"] in "Heute gibt's viel zu tun!"
# e.g. "hat's" => ["hat", "'s"]
# e.g. "home." => ['home']
words = [
word if word.startswith("'") else strip_punc(
word,
all=False) for word in _tokens if strip_punc(
word,
all=False)]
return list(words) |
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def sent_tokenize(self, text, **kwargs):
"""Returns a list of sentences. Each sentence is a space-separated string of tokens (words). Punctuation marks are split from other words. Periods (or ?!) mark the end of a sentence. Headings without an ending period are inferred by line breaks. """ |
sentences = find_sentences(text,
punctuation=kwargs.get(
"punctuation",
PUNCTUATION),
abbreviations=kwargs.get(
"abbreviations",
ABBREVIATIONS_DE),
replace=kwargs.get("replace", replacements),
linebreak=r"\n{2,}")
return sentences |
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def parse(self, text):
"""Parses the text. ``pattern.de.parse(**kwargs)`` can be passed to the parser instance and are documented in the main docstring of :class:`PatternParser() <textblob_de.parsers.PatternParser>`. :param str text: A string. """ |
#: Do not process empty strings (Issue #3)
if text.strip() == "":
return ""
#: Do not process strings consisting of a single punctuation mark (Issue #4)
elif text.strip() in PUNCTUATION:
_sym = text.strip()
if _sym in tuple('.?!'):
_tag = "."
else:
_tag = _sym
if self.lemmata:
return "{0}/{1}/O/O/{0}".format(_sym, _tag)
else:
return "{0}/{1}/O/O".format(_sym, _tag)
if self.tokenize:
_tokenized = " ".join(self.tokenizer.tokenize(text))
else:
_tokenized = text
_parsed = pattern_parse(_tokenized,
# text is tokenized before it is passed on to
# pattern.de.parse
tokenize=False,
tags=self.tags, chunks=self.chunks,
relations=self.relations, lemmata=self.lemmata,
encoding=self.encoding, tagset=self.tagset)
if self.pprint:
_parsed = pattern_pprint(_parsed)
return _parsed |
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def _filter_extracted(self, extracted_list):
"""Filter insignificant words for key noun phrase extraction. determiners, relative pronouns, reflexive pronouns In general, pronouns are not useful, as you need context to know what they refer to. Most of the pronouns, however, are filtered out by blob.noun_phrase method's np length (>1) filter :param list extracted_list: A list of noun phrases extracted from parser output. """ |
_filtered = []
for np in extracted_list:
_np = np.split()
if _np[0] in INSIGNIFICANT:
_np.pop(0)
try:
if _np[-1] in INSIGNIFICANT:
_np.pop(-1)
# e.g. 'welcher die ...'
if _np[0] in INSIGNIFICANT:
_np.pop(0)
except IndexError:
_np = []
if len(_np) > 0:
_filtered.append(" ".join(_np))
return _filtered |
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def tag(self, sentence, tokenize=True):
"""Tag a string `sentence`. :param str or list sentence: A string or a list of sentence strings. :param tokenize: (optional) If ``False`` string has to be tokenized before (space separated string). """ |
#: Do not process empty strings (Issue #3)
if sentence.strip() == "":
return []
#: Do not process strings consisting of a single punctuation mark (Issue #4)
elif sentence.strip() in PUNCTUATION:
if self.include_punc:
_sym = sentence.strip()
if _sym in tuple('.?!'):
_tag = "."
else:
_tag = _sym
return [(_sym, _tag)]
else:
return []
if tokenize:
_tokenized = " ".join(self.tokenizer.tokenize(sentence))
sentence = _tokenized
# Sentence is tokenized before it is passed on to pattern.de.tag
# (i.e. it is either submitted tokenized or if )
_tagged = pattern_tag(sentence, tokenize=False,
encoding=self.encoding,
tagset=self.tagset)
if self.include_punc:
return _tagged
else:
_tagged = [
(word, t) for word, t in _tagged if not PUNCTUATION_REGEX.match(
unicode(t))]
return _tagged |
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def _shutil_which(cmd, mode=os.F_OK | os.X_OK, path=None):
"""Given a command, mode, and a PATH string, return the path which conforms to the given mode on the PATH, or None if there is no such file. `mode` defaults to os.F_OK | os.X_OK. `path` defaults to the result of os.environ.get("PATH"), or can be overridden with a custom search path. """ |
# Check that a given file can be accessed with the correct mode.
# Additionally check that `file` is not a directory, as on Windows
# directories pass the os.access check.
def _access_check(fn, mode):
return (os.path.exists(fn) and os.access(fn, mode)
and not os.path.isdir(fn))
# If we're given a path with a directory part, look it up directly rather
# than referring to PATH directories. This includes checking relative to the
# current directory, e.g. ./script
if os.path.dirname(cmd):
if _access_check(cmd, mode):
return cmd
return None
if path is None:
path = os.environ.get("PATH", os.defpath)
if not path:
return None
path = path.split(os.pathsep)
if sys.platform == "win32":
# The current directory takes precedence on Windows.
if not os.curdir in path:
path.insert(0, os.curdir)
# PATHEXT is necessary to check on Windows.
pathext = os.environ.get("PATHEXT", "").split(os.pathsep)
# See if the given file matches any of the expected path extensions.
# This will allow us to short circuit when given "python.exe".
# If it does match, only test that one, otherwise we have to try
# others.
if any([cmd.lower().endswith(ext.lower()) for ext in pathext]):
files = [cmd]
else:
files = [cmd + ext for ext in pathext]
else:
# On other platforms you don't have things like PATHEXT to tell you
# what file suffixes are executable, so just pass on cmd as-is.
files = [cmd]
seen = set()
for dir in path:
normdir = os.path.normcase(dir)
if normdir not in seen:
seen.add(normdir)
for thefile in files:
name = os.path.join(dir, thefile)
if _access_check(name, mode):
return name
return None |
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def translate(self, from_lang=None, to="de"):
"""Translate the word to another language using Google's Translate API. .. versionadded:: 0.5.0 (``textblob``) """ |
if from_lang is None:
from_lang = self.translator.detect(self.string)
return self.translator.translate(self.string,
from_lang=from_lang, to_lang=to) |
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def lemmatize(self):
"""Return the lemma of each word in this WordList. Currently using NLTKPunktTokenizer() for all lemmatization tasks. This might cause slightly different tokenization results compared to the TextBlob.words property. """ |
_lemmatizer = PatternParserLemmatizer(tokenizer=NLTKPunktTokenizer())
# WordList object --> Sentence.string
# add a period (improves parser accuracy)
_raw = " ".join(self) + "."
_lemmas = _lemmatizer.lemmatize(_raw)
return self.__class__([Word(l, t) for l, t in _lemmas]) |
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def tokenize(self, tokenizer=None):
"""Return a list of tokens, using ``tokenizer``. :param tokenizer: (optional) A tokenizer object. If None, defaults to this blob's default tokenizer. """ |
t = tokenizer if tokenizer is not None else self.tokenizer
return WordList(t.tokenize(self.raw)) |
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def noun_phrases(self):
"""Returns a list of noun phrases for this blob.""" |
return WordList([phrase.strip()
for phrase in self.np_extractor.extract(self.raw)
if len(phrase.split()) > 1]) |
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def words(self):
"""Return a list of word tokens. This excludes punctuation characters. If you want to include punctuation characters, access the ``tokens`` property. :returns: A :class:`WordList <WordList>` of word tokens. """ |
return WordList(
word_tokenize(self.raw, self.tokenizer, include_punc=False)) |
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def _read(path, encoding="utf-8", comment=";;;"):
""" Returns an iterator over the lines in the file at the given path, strippping comments and decoding each line to Unicode. """ |
if path:
if isinstance(path, basestring) and os.path.exists(path):
# From file path.
if PY2:
f = codecs.open(path, 'r', encoding='utf-8')
else:
f = open(path, 'r', encoding='utf-8')
elif isinstance(path, basestring):
# From string.
f = path.splitlines()
else:
# From file or buffer.
f = path
for i, line in enumerate(f):
line = line.strip(codecs.BOM_UTF8) if i == 0 and isinstance(line, binary_type) else line
line = line.strip()
line = decode_utf8(line, encoding)
if not line or (comment and line.startswith(comment)):
continue
yield line
return |
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def _suffix_rules(token, tag="NN"):
""" Default morphological tagging rules for English, based on word suffixes. """ |
if isinstance(token, (list, tuple)):
token, tag = token
if token.endswith("ing"):
tag = "VBG"
if token.endswith("ly"):
tag = "RB"
if token.endswith("s") and not token.endswith(("is", "ous", "ss")):
tag = "NNS"
if token.endswith(("able", "al", "ful", "ible", "ient", "ish", "ive", "less", "tic", "ous")) or "-" in token:
tag = "JJ"
if token.endswith("ed"):
tag = "VBN"
if token.endswith(("ate", "ify", "ise", "ize")):
tag = "VBP"
return [token, tag] |
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def _multilingual(function, *args, **kwargs):
""" Returns the value from the function with the given name in the given language module. By default, language="en". """ |
return getattr(_module(kwargs.pop("language", "en")), function)(*args, **kwargs) |
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def find_tokens(self, string, **kwargs):
""" Returns a list of sentences from the given string. Punctuation marks are separated from each word by a space. """ |
# "The cat purs." => ["The cat purs ."]
return find_tokens(string,
punctuation = kwargs.get( "punctuation", PUNCTUATION),
abbreviations = kwargs.get("abbreviations", ABBREVIATIONS),
replace = kwargs.get( "replace", replacements),
linebreak = r"\n{2,}") |
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def find_chunks(self, tokens, **kwargs):
""" Annotates the given list of tokens with chunk tags. Several tags can be added, for example chunk + preposition tags. """ |
# [["The", "DT"], ["cat", "NN"], ["purs", "VB"]] =>
# [["The", "DT", "B-NP"], ["cat", "NN", "I-NP"], ["purs", "VB", "B-VP"]]
return find_prepositions(
find_chunks(tokens,
language = kwargs.get("language", self.language))) |
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def split(self, sep=TOKENS):
""" Returns a list of sentences, where each sentence is a list of tokens, where each token is a list of word + tags. """ |
if sep != TOKENS:
return unicode.split(self, sep)
if len(self) == 0:
return []
return [[[x.replace("&slash;", "/") for x in token.split("/")]
for token in sentence.split(" ")]
for sentence in unicode.split(self, "\n")] |
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def lemma(self, verb, parse=True):
""" Returns the infinitive form of the given verb, or None. """ |
if dict.__len__(self) == 0:
self.load()
if verb.lower() in self._inverse:
return self._inverse[verb.lower()]
if verb in self._inverse:
return self._inverse[verb]
if parse is True: # rule-based
return self.find_lemma(verb) |
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def lexeme(self, verb, parse=True):
""" Returns a list of all possible inflections of the given verb. """ |
a = []
b = self.lemma(verb, parse=parse)
if b in self:
a = [x for x in self[b] if x != ""]
elif parse is True: # rule-based
a = self.find_lexeme(b)
u = []; [u.append(x) for x in a if x not in u]
return u |
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def _edit1(self, w):
""" Returns a set of words with edit distance 1 from the given word. """ |
# Of all spelling errors, 80% is covered by edit distance 1.
# Edit distance 1 = one character deleted, swapped, replaced or inserted.
split = [(w[:i], w[i:]) for i in range(len(w) + 1)]
delete, transpose, replace, insert = (
[a + b[1:] for a, b in split if b],
[a + b[1] + b[0] + b[2:] for a, b in split if len(b) > 1],
[a + c + b[1:] for a, b in split for c in Spelling.ALPHA if b],
[a + c + b[0:] for a, b in split for c in Spelling.ALPHA]
)
return set(delete + transpose + replace + insert) |
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def _edit2(self, w):
""" Returns a set of words with edit distance 2 from the given word """ |
# Of all spelling errors, 99% is covered by edit distance 2.
# Only keep candidates that are actually known words (20% speedup).
return set(e2 for e1 in self._edit1(w) for e2 in self._edit1(e1) if e2 in self) |
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def xml_encode(string):
""" Returns the string with XML-safe special characters. """ |
string = string.replace("&", "&")
string = string.replace("<", "<")
string = string.replace(">", ">")
string = string.replace("\"",""")
string = string.replace(SLASH, "/")
return string |
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def xml_decode(string):
""" Returns the string with special characters decoded. """ |
string = string.replace("&", "&")
string = string.replace("<", "<")
string = string.replace(">", ">")
string = string.replace(""","\"")
string = string.replace("/", SLASH)
return string |
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def nltk_tree(sentence):
""" Returns an NLTK nltk.tree.Tree object from the given Sentence. The NLTK module should be on the search path somewhere. """ |
from nltk import tree
def do_pnp(pnp):
# Returns the PNPChunk (and the contained Chunk objects) in NLTK bracket format.
s = ' '.join([do_chunk(ch) for ch in pnp.chunks])
return '(PNP %s)' % s
def do_chunk(ch):
# Returns the Chunk in NLTK bracket format. Recurse attached PNP's.
s = ' '.join(['(%s %s)' % (w.pos, w.string) for w in ch.words])
s+= ' '.join([do_pnp(pnp) for pnp in ch.attachments])
return '(%s %s)' % (ch.type, s)
T = ['(S']
v = [] # PNP's already visited.
for ch in sentence.chunked():
if not ch.pnp and isinstance(ch, Chink):
T.append('(%s %s)' % (ch.words[0].pos, ch.words[0].string))
elif not ch.pnp:
T.append(do_chunk(ch))
#elif ch.pnp not in v:
elif ch.pnp.anchor is None and ch.pnp not in v:
# The chunk is part of a PNP without an anchor.
T.append(do_pnp(ch.pnp))
v.append(ch.pnp)
T.append(')')
return tree.bracket_parse(' '.join(T)) |
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def graphviz_dot(sentence, font="Arial", colors=BLUE):
""" Returns a dot-formatted string that can be visualized as a graph in GraphViz. """ |
s = 'digraph sentence {\n'
s += '\tranksep=0.75;\n'
s += '\tnodesep=0.15;\n'
s += '\tnode [penwidth=1, fontname="%s", shape=record, margin=0.1, height=0.35];\n' % font
s += '\tedge [penwidth=1];\n'
s += '\t{ rank=same;\n'
# Create node groups for words, chunks and PNP chunks.
for w in sentence.words:
s += '\t\tword%s [label="<f0>%s|<f1>%s"%s];\n' % (w.index, w.string, w.type, _colorize(w, colors))
for w in sentence.words[:-1]:
# Invisible edges forces the words into the right order:
s += '\t\tword%s -> word%s [color=none];\n' % (w.index, w.index+1)
s += '\t}\n'
s += '\t{ rank=same;\n'
for i, ch in enumerate(sentence.chunks):
s += '\t\tchunk%s [label="<f0>%s"%s];\n' % (i+1, "-".join([x for x in (
ch.type, ch.role, str(ch.relation or '')) if x]) or '-', _colorize(ch, colors))
for i, ch in enumerate(sentence.chunks[:-1]):
# Invisible edges forces the chunks into the right order:
s += '\t\tchunk%s -> chunk%s [color=none];\n' % (i+1, i+2)
s += '}\n'
s += '\t{ rank=same;\n'
for i, ch in enumerate(sentence.pnp):
s += '\t\tpnp%s [label="<f0>PNP"%s];\n' % (i+1, _colorize(ch, colors))
s += '\t}\n'
s += '\t{ rank=same;\n S [shape=circle, margin=0.25, penwidth=2]; }\n'
# Connect words to chunks.
# Connect chunks to PNP or S.
for i, ch in enumerate(sentence.chunks):
for w in ch:
s += '\tword%s -> chunk%s;\n' % (w.index, i+1)
if ch.pnp:
s += '\tchunk%s -> pnp%s;\n' % (i+1, sentence.pnp.index(ch.pnp)+1)
else:
s += '\tchunk%s -> S;\n' % (i+1)
if ch.type == 'VP':
# Indicate related chunks with a dotted
for r in ch.related:
s += '\tchunk%s -> chunk%s [style=dotted, arrowhead=none];\n' % (
i+1, sentence.chunks.index(r)+1)
# Connect PNP to anchor chunk or S.
for i, ch in enumerate(sentence.pnp):
if ch.anchor:
s += '\tpnp%s -> chunk%s;\n' % (i+1, sentence.chunks.index(ch.anchor)+1)
s += '\tpnp%s -> S [color=none];\n' % (i+1)
else:
s += '\tpnp%s -> S;\n' % (i+1)
s += "}"
return s |
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def next(self, type=None):
""" Returns the next word in the sentence with the given type. """ |
i = self.index + 1
s = self.sentence
while i < len(s):
if type in (s[i].type, None):
return s[i]
i += 1 |
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def previous(self, type=None):
""" Returns the next previous word in the sentence with the given type. """ |
i = self.index - 1
s = self.sentence
while i > 0:
if type in (s[i].type, None):
return s[i]
i -= 1 |
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def related(self):
""" Yields a list of all chunks in the sentence with the same relation id. """ |
return [ch for ch in self.sentence.chunks
if ch != self and intersects(unzip(0, ch.relations), unzip(0, self.relations))] |
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def next(self, type=None):
""" Returns the next chunk in the sentence with the given type. """ |
i = self.stop
s = self.sentence
while i < len(s):
if s[i].chunk is not None and type in (s[i].chunk.type, None):
return s[i].chunk
i += 1 |
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def previous(self, type=None):
""" Returns the next previous chunk in the sentence with the given type. """ |
i = self.start - 1
s = self.sentence
while i > 0:
if s[i].chunk is not None and type in (s[i].chunk.type, None):
return s[i].chunk
i -= 1 |
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def _do_pnp(self, pnp, anchor=None):
""" Attaches prepositional noun phrases. Identifies PNP's from either the PNP tag or the P-attachment tag. This does not determine the PP-anchor, it only groups words in a PNP chunk. """ |
if anchor or pnp and pnp.endswith("PNP"):
if anchor is not None:
m = find(lambda x: x.startswith("P"), anchor)
else:
m = None
if self.pnp \
and pnp \
and pnp != OUTSIDE \
and pnp.startswith("B-") is False \
and self.words[-2].pnp is not None:
self.pnp[-1].append(self.words[-1])
elif m is not None and m == self._attachment:
self.pnp[-1].append(self.words[-1])
else:
ch = PNPChunk(self, [self.words[-1]], type="PNP")
self.pnp.append(ch)
self._attachment = m |
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def _do_anchor(self, anchor):
""" Collects preposition anchors and attachments in a dictionary. Once the dictionary has an entry for both the anchor and the attachment, they are linked. """ |
if anchor:
for x in anchor.split("-"):
A, P = None, None
if x.startswith("A") and len(self.chunks) > 0: # anchor
A, P = x, x.replace("A","P")
self._anchors[A] = self.chunks[-1]
if x.startswith("P") and len(self.pnp) > 0: # attachment (PNP)
A, P = x.replace("P","A"), x
self._anchors[P] = self.pnp[-1]
if A in self._anchors and P in self._anchors and not self._anchors[P].anchor:
pnp = self._anchors[P]
pnp.anchor = self._anchors[A]
pnp.anchor.attachments.append(pnp) |
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def _do_conjunction(self, _and=("and", "e", "en", "et", "und", "y")):
""" Attach conjunctions. CC-words like "and" and "or" between two chunks indicate a conjunction. """ |
w = self.words
if len(w) > 2 and w[-2].type == "CC" and w[-2].chunk is None:
cc = w[-2].string.lower() in _and and AND or OR
ch1 = w[-3].chunk
ch2 = w[-1].chunk
if ch1 is not None and \
ch2 is not None:
ch1.conjunctions.append(ch2, cc)
ch2.conjunctions.append(ch1, cc) |
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def get(self, index, tag=LEMMA):
""" Returns a tag for the word at the given index. The tag can be WORD, LEMMA, POS, CHUNK, PNP, RELATION, ROLE, ANCHOR or a custom word tag. """ |
if tag == WORD:
return self.words[index]
if tag == LEMMA:
return self.words[index].lemma
if tag == POS:
return self.words[index].type
if tag == CHUNK:
return self.words[index].chunk
if tag == PNP:
return self.words[index].pnp
if tag == REL:
ch = self.words[index].chunk; return ch and ch.relation
if tag == ROLE:
ch = self.words[index].chunk; return ch and ch.role
if tag == ANCHOR:
ch = self.words[index].pnp; return ch and ch.anchor
if tag in self.words[index].custom_tags:
return self.words[index].custom_tags[tag]
return None |
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def slice(self, start, stop):
""" Returns a portion of the sentence from word start index to word stop index. The returned slice is a subclass of Sentence and a deep copy. """ |
s = Slice(token=self.token, language=self.language)
for i, word in enumerate(self.words[start:stop]):
# The easiest way to copy (part of) a sentence
# is by unpacking all of the token tags and passing them to Sentence.append().
p0 = word.string # WORD
p1 = word.lemma # LEMMA
p2 = word.type # POS
p3 = word.chunk is not None and word.chunk.type or None # CHUNK
p4 = word.pnp is not None and "PNP" or None # PNP
p5 = word.chunk is not None and unzip(0, word.chunk.relations) or None # REL
p6 = word.chunk is not None and unzip(1, word.chunk.relations) or None # ROLE
p7 = word.chunk and word.chunk.anchor_id or None # ANCHOR
p8 = word.chunk and word.chunk.start == start+i and BEGIN or None # IOB
p9 = word.custom_tags # User-defined tags.
# If the given range does not contain the chunk head, remove the chunk tags.
if word.chunk is not None and (word.chunk.stop > stop):
p3, p4, p5, p6, p7, p8 = None, None, None, None, None, None
# If the word starts the preposition, add the IOB B-prefix (i.e., B-PNP).
if word.pnp is not None and word.pnp.start == start+i:
p4 = BEGIN+"-"+"PNP"
# If the given range does not contain the entire PNP, remove the PNP tags.
# The range must contain the entire PNP,
# since it starts with the PP and ends with the chunk head (and is meaningless without these).
if word.pnp is not None and (word.pnp.start < start or word.chunk.stop > stop):
p4, p7 = None, None
s.append(word=p0, lemma=p1, type=p2, chunk=p3, pnp=p4, relation=p5, role=p6, anchor=p7, iob=p8, custom=p9)
s.parent = self
s._start = start
return s |
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def constituents(self, pnp=False):
""" Returns an in-order list of mixed Chunk and Word objects. With pnp=True, also contains PNPChunk objects whenever possible. """ |
a = []
for word in self.words:
if pnp and word.pnp is not None:
if len(a) == 0 or a[-1] != word.pnp:
a.append(word.pnp)
elif word.chunk is not None:
if len(a) == 0 or a[-1] != word.chunk:
a.append(word.chunk)
else:
a.append(word)
return a |
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def from_xml(cls, xml):
""" Returns a new Text from the given XML string. """ |
s = parse_string(xml)
return Sentence(s.split("\n")[0], token=s.tags, language=s.language) |
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def get_credits():
"""Extract credits from `AUTHORS.rst`""" |
credits = read(os.path.join(_HERE, "AUTHORS.rst")).split("\n")
from_index = credits.index("Active Contributors")
credits = "\n".join(credits[from_index + 2:])
return credits |
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def solve_series(self, x0, params, varied_data, varied_idx, internal_x0=None, solver=None, propagate=True, **kwargs):
""" Solve system for a set of parameters in which one is varied Parameters x0 : array_like Guess (subject to ``self.post_processors``) params : array_like Parameter values vaired_data : array_like Numerical values of the varied parameter. varied_idx : int or str Index of the varied parameter (indexing starts at 0). If ``self.par_by_name`` this should be the name (str) of the varied parameter. internal_x0 : array_like (default: None) Guess (*not* subject to ``self.post_processors``). Overrides ``x0`` when given. solver : str or callback See :meth:`solve`. propagate : bool (default: True) Use last successful solution as ``x0`` in consecutive solves. \\*\\*kwargs : Keyword arguments pass along to :meth:`solve`. Returns ------- xout : array Of shape ``(varied_data.size, x0.size)``. info_dicts : list of dictionaries Dictionaries each containing keys such as containing 'success', 'nfev', 'njev' etc. """ |
if self.x_by_name and isinstance(x0, dict):
x0 = [x0[k] for k in self.names]
if self.par_by_name:
if isinstance(params, dict):
params = [params[k] for k in self.param_names]
if isinstance(varied_idx, str):
varied_idx = self.param_names.index(varied_idx)
new_params = np.atleast_1d(np.array(params, dtype=np.float64))
xout = np.empty((len(varied_data), len(x0)))
self.internal_xout = np.empty_like(xout)
self.internal_params_out = np.empty((len(varied_data),
len(new_params)))
info_dicts = []
new_x0 = np.array(x0, dtype=np.float64) # copy
conds = kwargs.get('initial_conditions', None) # see ConditionalNeqSys
for idx, value in enumerate(varied_data):
try:
new_params[varied_idx] = value
except TypeError:
new_params = value # e.g. type(new_params) == int
if conds is not None:
kwargs['initial_conditions'] = conds
x, info_dict = self.solve(new_x0, new_params, internal_x0, solver,
**kwargs)
if propagate:
if info_dict['success']:
try:
# See ChainedNeqSys.solve
new_x0 = info_dict['x_vecs'][0]
internal_x0 = info_dict['internal_x_vecs'][0]
conds = info_dict['intermediate_info'][0].get(
'conditions', None)
except:
new_x0 = x
internal_x0 = None
conds = info_dict.get('conditions', None)
xout[idx, :] = x
self.internal_xout[idx, :] = self.internal_x
self.internal_params_out[idx, :] = self.internal_params
info_dicts.append(info_dict)
return xout, info_dicts |
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def solve_and_plot_series(self, x0, params, varied_data, varied_idx, solver=None, plot_kwargs=None, plot_residuals_kwargs=None, **kwargs):
""" Solve and plot for a series of a varied parameter. Convenience method, see :meth:`solve_series`, :meth:`plot_series` & :meth:`plot_series_residuals_internal` for more information. """ |
sol, nfo = self.solve_series(
x0, params, varied_data, varied_idx, solver=solver, **kwargs)
ax_sol = self.plot_series(sol, varied_data, varied_idx, info=nfo,
**(plot_kwargs or {}))
extra = dict(ax_sol=ax_sol, info=nfo)
if plot_residuals_kwargs:
extra['ax_resid'] = self.plot_series_residuals_internal(
varied_data, varied_idx, info=nfo,
**(plot_residuals_kwargs or {})
)
return sol, extra |
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def solve(self, x0, params=(), internal_x0=None, solver=None, attached_solver=None, **kwargs):
""" Solve with user specified ``solver`` choice. Parameters x0: 1D array of floats Guess (subject to ``self.post_processors``) params: 1D array_like of floats Parameters (subject to ``self.post_processors``) internal_x0: 1D array of floats When given it overrides (processed) ``x0``. ``internal_x0`` is not subject to ``self.post_processors``. solver: str or callable or None or iterable of such if str: uses _solve_``solver``(\*args, \*\*kwargs). if ``None``: chooses from PYNEQSYS_SOLVER environment variable. if iterable: chain solving. attached_solver: callable factory Invokes: solver = attached_solver(self). Returns ------- array: solution vector (post-processed by self.post_processors) dict: info dictionary containing 'success', 'nfev', 'njev' etc. Examples -------- [0.841163901914009663684741869855] [0.158836098085990336315258130144] """ |
if not isinstance(solver, (tuple, list)):
solver = [solver]
if not isinstance(attached_solver, (tuple, list)):
attached_solver = [attached_solver] + [None]*(len(solver) - 1)
_x0, self.internal_params = self.pre_process(x0, params)
for solv, attached_solv in zip(solver, attached_solver):
if internal_x0 is not None:
_x0 = internal_x0
elif self.internal_x0_cb is not None:
_x0 = self.internal_x0_cb(x0, params)
nfo = self._get_solver_cb(solv, attached_solv)(_x0, **kwargs)
_x0 = nfo['x'].copy()
self.internal_x = _x0
x0 = self.post_process(self.internal_x, self.internal_params)[0]
return x0, nfo |
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def _solve_scipy(self, intern_x0, tol=1e-8, method=None, **kwargs):
""" Uses ``scipy.optimize.root`` See: http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.root.html Parameters intern_x0: array_like initial guess tol: float Tolerance method: str What method to use. Defaults to ``'lm'`` if ``self.nf > self.nx`` otherwise ``'hybr'``. """ |
from scipy.optimize import root
if method is None:
if self.nf > self.nx:
method = 'lm'
elif self.nf == self.nx:
method = 'hybr'
else:
raise ValueError('Underdetermined problem')
if 'band' in kwargs:
raise ValueError("Set 'band' at initialization instead.")
if 'args' in kwargs:
raise ValueError("Set 'args' as params in initialization instead.")
new_kwargs = kwargs.copy()
if self.band is not None:
warnings.warn("Band argument ignored (see SciPy docs)")
new_kwargs['band'] = self.band
new_kwargs['args'] = self.internal_params
return root(self.f_cb, intern_x0, jac=self.j_cb, method=method, tol=tol, **new_kwargs) |
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def solve(guess_a, guess_b, power, solver='scipy'):
""" Constructs a pyneqsys.symbolic.SymbolicSys instance and returns from its ``solve`` method. """ |
# The problem is 2 dimensional so we need 2 symbols
x = sp.symbols('x:2', real=True)
# There is a user specified parameter ``p`` in this problem:
p = sp.Symbol('p', real=True, negative=False, integer=True)
# Our system consists of 2-non-linear equations:
f = [x[0] + (x[0] - x[1])**p/2 - 1,
(x[1] - x[0])**p/2 + x[1]]
# We construct our ``SymbolicSys`` instance by passing variables, equations and parameters:
neqsys = SymbolicSys(x, f, [p]) # (this will derive the Jacobian symbolically)
# Finally we solve the system using user-specified ``solver`` choice:
return neqsys.solve([guess_a, guess_b], [power], solver=solver) |
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def main(guess_a=1., guess_b=0., power=3, savetxt='None', verbose=False):
""" Example demonstrating how to solve a system of non-linear equations defined as SymPy expressions. The example shows how a non-linear problem can be given a command-line interface which may be preferred by end-users who are not familiar with Python. """ |
x, sol = solve(guess_a, guess_b, power) # see function definition above
assert sol.success
if savetxt != 'None':
np.savetxt(x, savetxt)
else:
if verbose:
print(sol)
else:
print(x) |
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def plot_series(xres, varied_data, indices=None, info=None, fail_vline=None, plot_kwargs_cb=None, ls=('-', '--', ':', '-.'), c=('k', 'r', 'g', 'b', 'c', 'm', 'y'), labels=None, ax=None, names=None, latex_names=None):
""" Plot the values of the solution vector vs the varied parameter. Parameters xres : array Solution vector of shape ``(varied_data.size, x0.size)``. varied_data : array Numerical values of the varied parameter. indices : iterable of integers, optional Indices of variables to be plotted. default: all fail_vline : bool Show vertical lines where the solver failed. plot_kwargs_cb : callable Takes the index as single argument, returns a dict passed to the plotting function ls : iterable of str Linestyles. c : iterable of str Colors. labels : iterable of str ax : matplotlib Axes instance names : iterable of str latex_names : iterable of str """ |
import matplotlib.pyplot as plt
if indices is None:
indices = range(xres.shape[1])
if fail_vline is None:
if info is None:
fail_vline = False
else:
fail_vline = True
if ax is None:
ax = plt.subplot(1, 1, 1)
if labels is None:
labels = names if latex_names is None else ['$%s$' % ln.strip('$') for ln in latex_names]
if plot_kwargs_cb is None:
def plot_kwargs_cb(idx, labels=None):
kwargs = {'ls': ls[idx % len(ls)],
'c': c[idx % len(c)]}
if labels:
kwargs['label'] = labels[idx]
return kwargs
else:
plot_kwargs_cb = plot_kwargs_cb or (lambda idx: {})
for idx in indices:
ax.plot(varied_data, xres[:, idx], **plot_kwargs_cb(idx, labels=labels))
if fail_vline:
for i, nfo in enumerate(info):
if not nfo['success']:
ax.axvline(varied_data[i], c='k', ls='--')
return ax |
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def mpl_outside_legend(ax, **kwargs):
""" Places a legend box outside a matplotlib Axes instance. """ |
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.75, box.height])
# Put a legend to the right of the current axis
ax.legend(loc='upper left', bbox_to_anchor=(1, 1), **kwargs) |
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def linear_rref(A, b, Matrix=None, S=None):
""" Transform a linear system to reduced row-echelon form Transforms both the matrix and right-hand side of a linear system of equations to reduced row echelon form Parameters A : Matrix-like Iterable of rows. b : iterable Returns ------- A', b' - transformed versions """ |
if Matrix is None:
from sympy import Matrix
if S is None:
from sympy import S
mat_rows = [_map2l(S, list(row) + [v]) for row, v in zip(A, b)]
aug = Matrix(mat_rows)
raug, pivot = aug.rref()
nindep = len(pivot)
return raug[:nindep, :-1], raug[:nindep, -1] |
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Description:
def linear_exprs(A, x, b=None, rref=False, Matrix=None):
""" Returns Ax - b Parameters A : matrix_like of numbers Of shape (len(b), len(x)). x : iterable of symbols b : array_like of numbers (default: None) When ``None``, assume zeros of length ``len(x)``. Matrix : class When ``rref == True``: A matrix class which supports slicing, and methods ``__mul__`` and ``rref``. Defaults to ``sympy.Matrix``. rref : bool Calculate the reduced row echelon form of (A | -b). Returns ------- A list of the elements in the resulting column vector. """ |
if b is None:
b = [0]*len(x)
if rref:
rA, rb = linear_rref(A, b, Matrix)
if Matrix is None:
from sympy import Matrix
return [lhs - rhs for lhs, rhs in zip(rA * Matrix(len(x), 1, x), rb)]
else:
return [sum([x0*x1 for x0, x1 in zip(row, x)]) - v
for row, v in zip(A, b)] |
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def from_callback(cls, cb, nx=None, nparams=None, **kwargs):
""" Generate a SymbolicSys instance from a callback. Parameters cb : callable Should have the signature ``cb(x, p, backend) -> list of exprs``. nx : int Number of unknowns, when not given it is deduced from ``kwargs['names']``. nparams : int Number of parameters, when not given it is deduced from ``kwargs['param_names']``. \\*\\*kwargs : Keyword arguments passed on to :class:`SymbolicSys`. See also :class:`pyneqsys.NeqSys`. Examples -------- """ |
if kwargs.get('x_by_name', False):
if 'names' not in kwargs:
raise ValueError("Need ``names`` in kwargs.")
if nx is None:
nx = len(kwargs['names'])
elif nx != len(kwargs['names']):
raise ValueError("Inconsistency between nx and length of ``names``.")
if kwargs.get('par_by_name', False):
if 'param_names' not in kwargs:
raise ValueError("Need ``param_names`` in kwargs.")
if nparams is None:
nparams = len(kwargs['param_names'])
elif nparams != len(kwargs['param_names']):
raise ValueError("Inconsistency between ``nparam`` and length of ``param_names``.")
if nparams is None:
nparams = 0
if nx is None:
raise ValueError("Need ``nx`` of ``names`` together with ``x_by_name==True``.")
be = Backend(kwargs.pop('backend', None))
x = be.real_symarray('x', nx)
p = be.real_symarray('p', nparams)
_x = dict(zip(kwargs['names'], x)) if kwargs.get('x_by_name', False) else x
_p = dict(zip(kwargs['param_names'], p)) if kwargs.get('par_by_name', False) else p
try:
exprs = cb(_x, _p, be)
except TypeError:
exprs = _ensure_3args(cb)(_x, _p, be)
return cls(x, exprs, p, backend=be, **kwargs) |
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def get_jac(self):
""" Return the jacobian of the expressions """ |
if self._jac is True:
if self.band is None:
f = self.be.Matrix(self.nf, 1, self.exprs)
_x = self.be.Matrix(self.nx, 1, self.x)
return f.jacobian(_x)
else:
# Banded
return self.be.Matrix(banded_jacobian(
self.exprs, self.x, *self.band))
elif self._jac is False:
return False
else:
return self._jac |
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Description:
def from_callback(cls, cb, transf_cbs, nx, nparams=0, pre_adj=None, **kwargs):
""" Generate a TransformedSys instance from a callback Parameters cb : callable Should have the signature ``cb(x, p, backend) -> list of exprs``. The callback ``cb`` should return *untransformed* expressions. transf_cbs : pair or iterable of pairs of callables Callables for forward- and backward-transformations. Each callable should take a single parameter (expression) and return a single expression. nx : int Number of unkowns. nparams : int Number of parameters. pre_adj : callable, optional To tweak expression prior to transformation. Takes a sinlge argument (expression) and return a single argument rewritten expression. \\*\\*kwargs : Keyword arguments passed on to :class:`TransformedSys`. See also :class:`SymbolicSys` and :class:`pyneqsys.NeqSys`. Examples -------- """ |
be = Backend(kwargs.pop('backend', None))
x = be.real_symarray('x', nx)
p = be.real_symarray('p', nparams)
try:
transf = [(transf_cbs[idx][0](xi),
transf_cbs[idx][1](xi))
for idx, xi in enumerate(x)]
except TypeError:
transf = zip(_map2(transf_cbs[0], x), _map2(transf_cbs[1], x))
try:
exprs = cb(x, p, be)
except TypeError:
exprs = _ensure_3args(cb)(x, p, be)
return cls(x, _map2l(pre_adj, exprs), transf, p, backend=be, **kwargs) |
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| def write(self, handle):
'''Write binary header data to a file handle.
This method writes exactly 512 bytes to the beginning of the given file
handle.
Parameters
----------
handle : file handle
The given handle will be reset to 0 using `seek` and then 512 bytes
will be written to describe the parameters in this Header. The
handle must be writeable.
'''
handle.seek(0)
handle.write(struct.pack(self.BINARY_FORMAT,
self.parameter_block,
0x50,
self.point_count,
self.analog_count,
self.first_frame,
self.last_frame,
self.max_gap,
self.scale_factor,
self.data_block,
self.analog_per_frame,
self.frame_rate,
b'',
self.long_event_labels and 0x3039 or 0x0,
self.label_block,
b'')) |
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| def read(self, handle):
'''Read and parse binary header data from a file handle.
This method reads exactly 512 bytes from the beginning of the given file
handle.
Parameters
----------
handle : file handle
The given handle will be reset to 0 using `seek` and then 512 bytes
will be read to initialize the attributes in this Header. The handle
must be readable.
Raises
------
AssertionError
If the magic byte from the header is not 80 (the C3D magic value).
'''
handle.seek(0)
(self.parameter_block,
magic,
self.point_count,
self.analog_count,
self.first_frame,
self.last_frame,
self.max_gap,
self.scale_factor,
self.data_block,
self.analog_per_frame,
self.frame_rate,
_,
self.long_event_labels,
self.label_block,
_) = struct.unpack(self.BINARY_FORMAT, handle.read(512))
assert magic == 80, 'C3D magic {} != 80 !'.format(magic) |
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| def binary_size(self):
'''Return the number of bytes needed to store this parameter.'''
return (
1 + # group_id
2 + # next offset marker
1 + len(self.name.encode('utf-8')) + # size of name and name bytes
1 + # data size
1 + len(self.dimensions) + # size of dimensions and dimension bytes
self.total_bytes + # data
1 + len(self.desc.encode('utf-8')) # size of desc and desc bytes
) |
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| def write(self, group_id, handle):
'''Write binary data for this parameter to a file handle.
Parameters
----------
group_id : int
The numerical ID of the group that holds this parameter.
handle : file handle
An open, writable, binary file handle.
'''
name = self.name.encode('utf-8')
handle.write(struct.pack('bb', len(name), group_id))
handle.write(name)
handle.write(struct.pack('<h', self.binary_size() - 2 - len(name)))
handle.write(struct.pack('b', self.bytes_per_element))
handle.write(struct.pack('B', len(self.dimensions)))
handle.write(struct.pack('B' * len(self.dimensions), *self.dimensions))
if self.bytes:
handle.write(self.bytes)
desc = self.desc.encode('utf-8')
handle.write(struct.pack('B', len(desc)))
handle.write(desc) |
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| def read(self, handle):
'''Read binary data for this parameter from a file handle.
This reads exactly enough data from the current position in the file to
initialize the parameter.
'''
self.bytes_per_element, = struct.unpack('b', handle.read(1))
dims, = struct.unpack('B', handle.read(1))
self.dimensions = [struct.unpack('B', handle.read(1))[0] for _ in range(dims)]
self.bytes = b''
if self.total_bytes:
self.bytes = handle.read(self.total_bytes)
size, = struct.unpack('B', handle.read(1))
self.desc = size and handle.read(size).decode('utf-8') or '' |
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| def _as_array(self, fmt):
'''Unpack the raw bytes of this param using the given data format.'''
assert self.dimensions, \
'{}: cannot get value as {} array!'.format(self.name, fmt)
elems = array.array(fmt)
elems.fromstring(self.bytes)
return np.array(elems).reshape(self.dimensions) |
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| def bytes_array(self):
'''Get the param as an array of raw byte strings.'''
assert len(self.dimensions) == 2, \
'{}: cannot get value as bytes array!'.format(self.name)
l, n = self.dimensions
return [self.bytes[i*l:(i+1)*l] for i in range(n)] |
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| def string_array(self):
'''Get the param as a array of unicode strings.'''
assert len(self.dimensions) == 2, \
'{}: cannot get value as string array!'.format(self.name)
l, n = self.dimensions
return [self.bytes[i*l:(i+1)*l].decode('utf-8') for i in range(n)] |
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| def add_param(self, name, **kwargs):
'''Add a parameter to this group.
Parameters
----------
name : str
Name of the parameter to add to this group. The name will
automatically be case-normalized.
Additional keyword arguments will be passed to the `Param` constructor.
'''
self.params[name.upper()] = Param(name.upper(), **kwargs) |
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| def binary_size(self):
'''Return the number of bytes to store this group and its parameters.'''
return (
1 + # group_id
1 + len(self.name.encode('utf-8')) + # size of name and name bytes
2 + # next offset marker
1 + len(self.desc.encode('utf-8')) + # size of desc and desc bytes
sum(p.binary_size() for p in self.params.values())) |
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| def write(self, group_id, handle):
'''Write this parameter group, with parameters, to a file handle.
Parameters
----------
group_id : int
The numerical ID of the group.
handle : file handle
An open, writable, binary file handle.
'''
name = self.name.encode('utf-8')
desc = self.desc.encode('utf-8')
handle.write(struct.pack('bb', len(name), -group_id))
handle.write(name)
handle.write(struct.pack('<h', 3 + len(desc)))
handle.write(struct.pack('B', len(desc)))
handle.write(desc)
for param in self.params.values():
param.write(group_id, handle) |
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| def check_metadata(self):
'''Ensure that the metadata in our file is self-consistent.'''
assert self.header.point_count == self.point_used, (
'inconsistent point count! {} header != {} POINT:USED'.format(
self.header.point_count,
self.point_used,
))
assert self.header.scale_factor == self.point_scale, (
'inconsistent scale factor! {} header != {} POINT:SCALE'.format(
self.header.scale_factor,
self.point_scale,
))
assert self.header.frame_rate == self.point_rate, (
'inconsistent frame rate! {} header != {} POINT:RATE'.format(
self.header.frame_rate,
self.point_rate,
))
ratio = self.analog_rate / self.point_rate
assert True or self.header.analog_per_frame == ratio, (
'inconsistent analog rate! {} header != {} analog-fps / {} point-fps'.format(
self.header.analog_per_frame,
self.analog_rate,
self.point_rate,
))
count = self.analog_used * self.header.analog_per_frame
assert True or self.header.analog_count == count, (
'inconsistent analog count! {} header != {} analog used * {} per-frame'.format(
self.header.analog_count,
self.analog_used,
self.header.analog_per_frame,
))
start = self.get_uint16('POINT:DATA_START')
assert self.header.data_block == start, (
'inconsistent data block! {} header != {} POINT:DATA_START'.format(
self.header.data_block, start))
for name in ('POINT:LABELS', 'POINT:DESCRIPTIONS',
'ANALOG:LABELS', 'ANALOG:DESCRIPTIONS'):
if self.get(name) is None:
warnings.warn('missing parameter {}'.format(name)) |
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| def add_group(self, group_id, name, desc):
'''Add a new parameter group.
Parameters
----------
group_id : int
The numeric ID for a group to check or create.
name : str, optional
If a group is created, assign this name to the group.
desc : str, optional
If a group is created, assign this description to the group.
Returns
-------
group : :class:`Group`
A group with the given ID, name, and description.
Raises
------
KeyError
If a group with a duplicate ID or name already exists.
'''
if group_id in self.groups:
raise KeyError(group_id)
name = name.upper()
if name in self.groups:
raise KeyError(name)
group = self.groups[name] = self.groups[group_id] = Group(name, desc)
return group |
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| def get(self, group, default=None):
'''Get a group or parameter.
Parameters
----------
group : str
If this string contains a period (.), then the part before the
period will be used to retrieve a group, and the part after the
period will be used to retrieve a parameter from that group. If this
string does not contain a period, then just a group will be
returned.
default : any
Return this value if the named group and parameter are not found.
Returns
-------
value : :class:`Group` or :class:`Param`
Either a group or parameter with the specified name(s). If neither
is found, returns the default value.
'''
if isinstance(group, int):
return self.groups.get(group, default)
group = group.upper()
param = None
if '.' in group:
group, param = group.split('.', 1)
if ':' in group:
group, param = group.split(':', 1)
if group not in self.groups:
return default
group = self.groups[group]
if param is not None:
return group.get(param, default)
return group |
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| def _pad_block(self, handle):
'''Pad the file with 0s to the end of the next block boundary.'''
extra = handle.tell() % 512
if extra:
handle.write(b'\x00' * (512 - extra)) |
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| def _write_metadata(self, handle):
'''Write metadata to a file handle.
Parameters
----------
handle : file
Write metadata and C3D motion frames to the given file handle. The
writer does not close the handle.
'''
self.check_metadata()
# header
self.header.write(handle)
self._pad_block(handle)
assert handle.tell() == 512
# groups
handle.write(struct.pack(
'BBBB', 0, 0, self.parameter_blocks(), PROCESSOR_INTEL))
id_groups = sorted(
(i, g) for i, g in self.groups.items() if isinstance(i, int))
for group_id, group in id_groups:
group.write(group_id, handle)
# padding
self._pad_block(handle)
while handle.tell() != 512 * (self.header.data_block - 1):
handle.write(b'\x00' * 512) |
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| def _write_frames(self, handle):
'''Write our frame data to the given file handle.
Parameters
----------
handle : file
Write metadata and C3D motion frames to the given file handle. The
writer does not close the handle.
'''
assert handle.tell() == 512 * (self.header.data_block - 1)
scale = abs(self.point_scale)
is_float = self.point_scale < 0
point_dtype = [np.int16, np.float32][is_float]
point_scale = [scale, 1][is_float]
point_format = 'if'[is_float]
raw = np.empty((self.point_used, 4), point_dtype)
for points, analog in self._frames:
valid = points[:, 3] > -1
raw[~valid, 3] = -1
raw[valid, :3] = points[valid, :3] / self._point_scale
raw[valid, 3] = (
((points[valid, 4]).astype(np.uint8) << 8) |
(points[valid, 3] / scale).astype(np.uint16)
)
point = array.array(point_format)
point.extend(raw.flatten())
point.tofile(handle)
analog = array.array(point_format)
analog.extend(analog)
analog.tofile(handle)
self._pad_block(handle) |
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def _workaround_no_vector_images(project):
"""Replace vector images with fake ones.""" |
RED = (255, 0, 0)
PLACEHOLDER = kurt.Image.new((32, 32), RED)
for scriptable in [project.stage] + project.sprites:
for costume in scriptable.costumes:
if costume.image.format == "SVG":
yield "%s - %s" % (scriptable.name, costume.name)
costume.image = PLACEHOLDER |
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def get_plugin(cls, name=None, **kwargs):
"""Returns the first format plugin whose attributes match kwargs. For example:: get_plugin(extension="scratch14") Will return the :class:`KurtPlugin` whose :attr:`extension <KurtPlugin.extension>` attribute is ``"scratch14"``. The :attr:`name <KurtPlugin.name>` is used as the ``format`` parameter to :attr:`Project.load` and :attr:`Project.save`. :raises: :class:`ValueError` if the format doesn't exist. :returns: :class:`KurtPlugin` """ |
if isinstance(name, KurtPlugin):
return name
if 'extension' in kwargs:
kwargs['extension'] = kwargs['extension'].lower()
if name:
kwargs["name"] = name
if not kwargs:
raise ValueError, "No arguments"
for plugin in cls.plugins.values():
for name in kwargs:
if getattr(plugin, name) != kwargs[name]:
break
else:
return plugin
raise ValueError, "Unknown format %r" % kwargs |
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def clean_up(scripts):
"""Clean up the given list of scripts in-place so none of the scripts overlap. """ |
scripts_with_pos = [s for s in scripts if s.pos]
scripts_with_pos.sort(key=lambda s: (s.pos[1], s.pos[0]))
scripts = scripts_with_pos + [s for s in scripts if not s.pos]
y = 20
for script in scripts:
script.pos = (20, y)
if isinstance(script, kurt.Script):
y += stack_height(script.blocks)
elif isinstance(script, kurt.Comment):
y += 14
y += 15 |
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def obj_classes_from_module(module):
"""Return a list of classes in a module that have a 'classID' attribute.""" |
for name in dir(module):
if not name.startswith('_'):
cls = getattr(module, name)
if getattr(cls, 'classID', None):
yield (name, cls) |
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def decode_network(objects):
"""Return root object from ref-containing obj table entries""" |
def resolve_ref(obj, objects=objects):
if isinstance(obj, Ref):
# first entry is 1
return objects[obj.index - 1]
else:
return obj
# Reading the ObjTable backwards somehow makes more sense.
for i in xrange(len(objects)-1, -1, -1):
obj = objects[i]
if isinstance(obj, Container):
obj.update((k, resolve_ref(v)) for (k, v) in obj.items())
elif isinstance(obj, Dictionary):
obj.value = dict(
(resolve_ref(field), resolve_ref(value))
for (field, value) in obj.value.items()
)
elif isinstance(obj, dict):
obj = dict(
(resolve_ref(field), resolve_ref(value))
for (field, value) in obj.items()
)
elif isinstance(obj, list):
obj = [resolve_ref(field) for field in obj]
elif isinstance(obj, Form):
for field in obj.value:
value = getattr(obj, field)
value = resolve_ref(value)
setattr(obj, field, value)
elif isinstance(obj, ContainsRefs):
obj.value = [resolve_ref(field) for field in obj.value]
objects[i] = obj
for obj in objects:
if isinstance(obj, Form):
obj.built()
root = objects[0]
return root |
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def decode_obj_table(table_entries, plugin):
"""Return root of obj table. Converts user-class objects""" |
entries = []
for entry in table_entries:
if isinstance(entry, Container):
assert not hasattr(entry, '__recursion_lock__')
user_obj_def = plugin.user_objects[entry.classID]
assert entry.version == user_obj_def.version
entry = Container(class_name=entry.classID,
**dict(zip(user_obj_def.defaults.keys(),
entry.values)))
entries.append(entry)
return decode_network(entries) |
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def encode_obj_table(root, plugin):
"""Return list of obj table entries. Converts user-class objects""" |
entries = encode_network(root)
table_entries = []
for entry in entries:
if isinstance(entry, Container):
assert not hasattr(entry, '__recursion_lock__')
user_obj_def = plugin.user_objects[entry.class_name]
attrs = OrderedDict()
for (key, default) in user_obj_def.defaults.items():
attrs[key] = entry.get(key, default)
entry = Container(classID=entry.class_name,
length=len(attrs),
version=user_obj_def.version,
values=attrs.values())
table_entries.append(entry)
return table_entries |
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def _encode(self, obj, context):
"""Encodes a class to a lower-level object using the class' own to_construct function. If no such function is defined, returns the object unchanged. """ |
func = getattr(obj, 'to_construct', None)
if callable(func):
return func(context)
else:
return obj |
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def _decode(self, obj, context):
"""Initialises a new Python class from a construct using the mapping passed to the adapter. """ |
cls = self._get_class(obj.classID)
return cls.from_construct(obj, context) |
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def write_file(self, name, contents):
"""Write file contents string into archive.""" |
# TODO: find a way to make ZipFile accept a file object.
zi = zipfile.ZipInfo(name)
zi.date_time = time.localtime(time.time())[:6]
zi.compress_type = zipfile.ZIP_DEFLATED
zi.external_attr = 0777 << 16L
self.zip_file.writestr(zi, contents) |
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def from_string(cls, width, height, rgba_string):
"""Returns a Form with 32-bit RGBA pixels Accepts string containing raw RGBA color values """ |
# Convert RGBA string to ARGB
raw = ""
for i in range(0, len(rgba_string), 4):
raw += rgba_string[i+3] # alpha
raw += rgba_string[i:i+3] # rgb
assert len(rgba_string) == width * height * 4
return Form(
width = width,
height = height,
depth = 32,
bits = Bitmap(raw),
) |
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def set_file_path(self, path):
"""Update the file_path Entry widget""" |
self.file_path.delete(0, END)
self.file_path.insert(0, path) |
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def load(cls, path, format=None):
"""Load project from file. Use ``format`` to specify the file format to use. Path can be a file-like object, in which case format is required. Otherwise, can guess the appropriate format from the extension. If you pass a file-like object, you're responsible for closing the file. :param path: Path or file pointer. :param format: :attr:`KurtFileFormat.name` eg. ``"scratch14"``. Overrides the extension. :raises: :class:`UnknownFormat` if the extension is unrecognised. :raises: :py:class:`ValueError` if the format doesn't exist. """ |
path_was_string = isinstance(path, basestring)
if path_was_string:
(folder, filename) = os.path.split(path)
(name, extension) = os.path.splitext(filename)
if format is None:
plugin = kurt.plugin.Kurt.get_plugin(extension=extension)
if not plugin:
raise UnknownFormat(extension)
fp = open(path, "rb")
else:
fp = path
assert format, "Format is required"
plugin = kurt.plugin.Kurt.get_plugin(format)
if not plugin:
raise ValueError, "Unknown format %r" % format
project = plugin.load(fp)
if path_was_string:
fp.close()
project.convert(plugin)
if isinstance(path, basestring):
project.path = path
if not project.name:
project.name = name
return project |
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def copy(self):
"""Return a new Project instance, deep-copying all the attributes.""" |
p = Project()
p.name = self.name
p.path = self.path
p._plugin = self._plugin
p.stage = self.stage.copy()
p.stage.project = p
for sprite in self.sprites:
s = sprite.copy()
s.project = p
p.sprites.append(s)
for actor in self.actors:
if isinstance(actor, Sprite):
p.actors.append(p.get_sprite(actor.name))
else:
a = actor.copy()
if isinstance(a, Watcher):
if isinstance(a.target, Project):
a.target = p
elif isinstance(a.target, Stage):
a.target = p.stage
else:
a.target = p.get_sprite(a.target.name)
p.actors.append(a)
p.variables = dict((n, v.copy()) for (n, v) in self.variables.items())
p.lists = dict((n, l.copy()) for (n, l) in self.lists.items())
p.thumbnail = self.thumbnail
p.tempo = self.tempo
p.notes = self.notes
p.author = self.author
return p |
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def convert(self, format):
"""Convert the project in-place to a different file format. Returns a list of :class:`UnsupportedFeature` objects, which may give warnings about the conversion. :param format: :attr:`KurtFileFormat.name` eg. ``"scratch14"``. :raises: :class:`ValueError` if the format doesn't exist. """ |
self._plugin = kurt.plugin.Kurt.get_plugin(format)
return list(self._normalize()) |
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def save(self, path=None, debug=False):
"""Save project to file. :param path: Path or file pointer. If you pass a file pointer, you're responsible for closing it. If path is not given, the :attr:`path` attribute is used, usually the original path given to :attr:`load()`. If `path` has the extension of an existing plugin, the project will be converted using :attr:`convert`. Otherwise, the extension will be replaced with the extension of the current plugin. (Note that log output for the conversion will be printed to stdout. If you want to deal with the output, call :attr:`convert` directly.) If the path ends in a folder instead of a file, the filename is based on the project's :attr:`name`. :param debug: If true, return debugging information from the format plugin instead of the path. :raises: :py:class:`ValueError` if there's no path or name. :returns: path to the saved file. """ |
p = self.copy()
plugin = p._plugin
# require path
p.path = path or self.path
if not p.path:
raise ValueError, "path is required"
if isinstance(p.path, basestring):
# split path
(folder, filename) = os.path.split(p.path)
(name, extension) = os.path.splitext(filename)
# get plugin from extension
if path: # only if not using self.path
try:
plugin = kurt.plugin.Kurt.get_plugin(extension=extension)
except ValueError:
pass
# build output path
if not name:
name = _clean_filename(self.name)
if not name:
raise ValueError, "name is required"
filename = name + plugin.extension
p.path = os.path.join(folder, filename)
# open
fp = open(p.path, "wb")
else:
fp = p.path
path = None
if not plugin:
raise ValueError, "must convert project to a format before saving"
for m in p.convert(plugin):
print m
result = p._save(fp)
if path:
fp.close()
return result if debug else p.path |
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def stringify(self):
"""Returns the color value in hexcode format. eg. ``'#ff1056'`` """ |
hexcode = "#"
for x in self.value:
part = hex(x)[2:]
if len(part) < 2: part = "0" + part
hexcode += part
return hexcode |
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def options(self, scriptable=None):
"""Return a list of valid options to a menu insert, given a Scriptable for context. Mostly complete, excepting 'attribute'. """ |
options = list(Insert.KIND_OPTIONS.get(self.kind, []))
if scriptable:
if self.kind == 'var':
options += scriptable.variables.keys()
options += scriptable.project.variables.keys()
elif self.kind == 'list':
options += scriptable.lists.keys()
options += scriptable.project.lists.keys()
elif self.kind == 'costume':
options += [c.name for c in scriptable.costumes]
elif self.kind == 'backdrop':
options += [c.name for c in scriptable.project.stage.costumes]
elif self.kind == 'sound':
options += [c.name for c in scriptable.sounds]
options += [c.name for c in scriptable.project.stage.sounds]
elif self.kind in ('spriteOnly', 'spriteOrMouse', 'spriteOrStage',
'touching'):
options += [s.name for s in scriptable.project.sprites]
elif self.kind == 'attribute':
pass # TODO
elif self.kind == 'broadcast':
options += list(set(scriptable.project.get_broadcasts()))
return options |
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def text(self):
"""The text displayed on the block. String containing ``"%s"`` in place of inserts. eg. ``'say %s for %s secs'`` """ |
parts = [("%s" if isinstance(p, Insert) else p) for p in self.parts]
parts = [("%%" if p == "%" else p) for p in parts] # escape percent
return "".join(parts) |
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def _strip_text(text):
"""Returns text with spaces and inserts removed.""" |
text = re.sub(r'[ ,?:]|%s', "", text.lower())
for chr in "-%":
new_text = text.replace(chr, "")
if new_text:
text = new_text
return text.lower() |
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def has_insert(self, shape):
"""Returns True if any of the inserts have the given shape.""" |
for insert in self.inserts:
if insert.shape == shape:
return True
return False |
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def _add_conversion(self, plugin, pbt):
"""Add a new PluginBlockType conversion. If the plugin already exists, do nothing. """ |
assert self.shape == pbt.shape
assert len(self.inserts) == len(pbt.inserts)
for (i, o) in zip(self.inserts, pbt.inserts):
assert i.shape == o.shape
assert i.kind == o.kind
assert i.unevaluated == o.unevaluated
if plugin not in self._plugins:
self._plugins[plugin] = pbt |
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