本文整理汇总了Python中al_lib.ArchiLib.ArchiLib.getTypeNodes方法的典型用法代码示例。如果您正苦于以下问题：Python ArchiLib.getTypeNodes方法的具体用法？Python ArchiLib.getTypeNodes怎么用？Python ArchiLib.getTypeNodes使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类al_lib.ArchiLib.ArchiLib的用法示例。
在下文中一共展示了ArchiLib.getTypeNodes方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: requirementAnalysis
# 需要导入模块: from al_lib.ArchiLib import ArchiLib [as 别名]
# 或者: from al_lib.ArchiLib.ArchiLib import getTypeNodes [as 别名]
def requirementAnalysis(fileArchimate=None):
if fileArchimate is None:
fileArchimate = u"/Users/morrj140/Documents/SolutionEngineering/Archimate Models/DVC v38.archimate"
al = ArchiLib(fileArchimate)
conceptsFile = fileConceptsRequirements
searchTypes = list()
searchTypes.append(u"archimate:Requirement")
nl = al.getTypeNodes(searchTypes)
logger.info(u"Find Words in Requirements...")
concepts = Concepts(u"Requirement", u"Requirements")
n = 0
for sentence in nl:
n += 1
logger.debug(u"%s" % sentence)
c = concepts.addConceptKeyType(u"Document" + str(n), u"Document")
d = c.addConceptKeyType(sentence, u"Sentence" + str(n))
if True and sentence is not None:
cleanSentence = ' '.join([word for word in sentence.split(u" ") if word not in stop])
for word, pos in nltk.pos_tag(nltk.wordpunct_tokenize(cleanSentence)):
if len(word) > 1 and pos[0] == u"N":
e = d.addConceptKeyType(word, u"Word")
f = e.addConceptKeyType(pos, u"POS")
Concepts.saveConcepts(concepts, conceptsFile)
logger.info(u"Saved : %s" % conceptsFile)
chunks = Chunks(concepts)
chunks.createChunks()示例2: test_RequirementAnalysis
# 需要导入模块: from al_lib.ArchiLib import ArchiLib [as 别名]
# 或者: from al_lib.ArchiLib.ArchiLib import getTypeNodes [as 别名]
def test_RequirementAnalysis(cleandir, fileArchimate):
assert (os.path.isfile(filePPTXIn) is True)
al = ArchiLib(fileArchimate)
conceptsFile = fileConceptsRequirements
searchTypes = list()
searchTypes.append(u"archimate:Requirement")
nl = al.getTypeNodes(searchTypes)
logger.info(u"Find Words in Requirements...")
concepts = Concepts(u"Requirement", u"Requirements")
n = 0
for sentence in nl:
n += 1
logger.debug(u"%s" % sentence)
c = concepts.addConceptKeyType(u"Document" + unicode(n), u"Document")
d = c.addConceptKeyType(sentence, u"Sentence" + unicode(n))
if True and sentence is not None:
cleanSentence = ' '.join([word for word in sentence.split(" ") if word not in stop])
for word, pos in nltk.pos_tag(nltk.wordpunct_tokenize(cleanSentence)):
if len(word) > 1 and pos[0] == u"N":
e = d.addConceptKeyType(word, u"Word")
f = e.addConceptKeyType(pos, u"POS")
Concepts.saveConcepts(concepts, conceptsFile)
logger.info(u"Saved : %s" % conceptsFile)
assert (os.path.isfile(conceptsFile) is True)
chunks = Chunks(concepts)
chunks.createChunks()
assert (os.path.isfile(fileConceptsChunks) is True)示例3: gapSimilarity
# 需要导入模块: from al_lib.ArchiLib import ArchiLib [as 别名]
# 或者: from al_lib.ArchiLib.ArchiLib import getTypeNodes [as 别名]
def gapSimilarity(fileArchimate, searchTypes):
lemmatizer = WordNetLemmatizer()
logger.info(u"Using : %s" % fileArchimate)
al = ArchiLib(fileArchimate)
nl = al.getTypeNodes(searchTypes)
logger.info(u"Find Words...")
concepts = Concepts(u"Word", u"Topic")
n = 0
for sentence in nl:
n += 1
if sentence is None:
continue
logger.info(u"%s" % sentence)
c = concepts.addConceptKeyType(u"Document" + str(n), nl[sentence][ARCHI_TYPE])
d = c.addConceptKeyType(sentence, nl[sentence][ARCHI_TYPE])
cleanSentence = u' '.join([word for word in sentence.split(u" ") if word not in stop])
for word, pos in nltk.pos_tag(nltk.wordpunct_tokenize(cleanSentence)):
if len(word) > 1 and pos[0] == u"N":
lemmaWord =lemmatizer.lemmatize(word.lower())
e = d.addConceptKeyType(lemmaWord, u"LemmaWord")
f = e.addConceptKeyType(pos, u"POS")
if False:
concepts.logConcepts()
if True:
logger.info(u"Find Collocations...")
fc = Collocations()
fc.find_collocations(concepts)
if True:
npbt = DocumentsSimilarity(al)
logger.info(u"Create Topics")
npbt.createTopics(concepts)
if True:
logger.info(u"Find Similarities")
nc = npbt.findSimilarties()
logger.debug(u"Topics")
listTopics = list()
ncg = npbt.topicConcepts.getConcepts().values()
for x in ncg:
logger.info(u"%s[%d]" % (x.name, x.count))
lt = (x.name, x.count)
listTopics.append(lt)
logger.info(u"Topics Sorted")
with open(u"topic_sort.txt", "wb") as f:
for x in sorted(listTopics, key=lambda c: abs(c[1]), reverse=False):
output = "Topic : %s[%d]" % (x[0], x[1])
logger.info(output)
f.write(output + os.linesep)