def get_boxes(self, sentence):
"""
Get all the boxes corresponding the given sentence
Arguments:
sentence --- can be string (will be splited), or an array of strings
Returns:
an array of boxes (see pyocr boxes)
"""
if isinstance(sentence, unicode):
keywords = split_words(sentence)
else:
assert(isinstance(sentence, list))
keywords = sentence
output = []
for keyword in keywords:
for box in self.boxes:
# unfold generator output
words = []
for word in split_words(box.content):
words.append(word)
if keyword in words:
output.append(box)
return output
def get_boxes(self, sentence):
"""
Get all the boxes corresponding the given sentence
Arguments:
sentence --- can be string (will be splited), or an array of strings
Returns:
an array of boxes (see pyocr boxes)
"""
if isinstance(sentence, unicode):
keywords = split_words(sentence)
else:
assert (isinstance(sentence, list))
keywords = sentence
output = []
for keyword in keywords:
for line in self.boxes:
for box in line.word_boxes:
if keyword in box.content:
output.append(box)
continue
# unfold generator output
words = [x for x in split_words(box.content)]
if keyword in words:
output.append(box)
continue
return output
def find_documents(self, sentence):
"""
Returns all the documents matching the given keywords
Arguments:
keywords --- keywords (single string)
Returns:
An array of document id (strings)
"""
if sentence.strip() == "":
return self.docs[:]
positive_keywords = []
negative_keywords = []
print ("Looking for documents containing %s"
% (sentence.encode('ascii', 'replace')))
for keyword in split_words(sentence):
if keyword[:1] != "!":
positive_keywords.append(keyword)
else:
negative_keywords.append(keyword[1:])
if (len(positive_keywords) == 0 and len(negative_keywords) == 0):
return []
documents = None
if len(positive_keywords) <= 0:
positive_keywords = ["*"]
for keyword in positive_keywords:
docs = self.__find_documents(keyword)
if documents == None:
documents = docs
else:
# intersection of both arrays
documents = [val for val in documents if val in docs]
if documents == None:
return []
print "Found %d documents" % (len(documents))
for keyword in negative_keywords:
docs = self.__find_documents(keyword)
print "Found %d documents to remove" % (len(documents))
for doc in docs:
try:
documents.remove(doc)
except ValueError:
pass
documents.sort()
return documents
def __contains__(self, sentence):
words = split_words(sentence)
words = [word.lower() for word in words]
txt = self.text
for line in txt:
line = line.lower()
for word in words:
if word in line:
return True
return False
def __get_keywords(self):
"""
Get all the keywords related of this page
Returns:
An array of strings
"""
for line in self.text:
for word in split_words(line):
yield (word)
def __contains__(self, sentence):
words = split_words(sentence)
words = [word.lower() for word in words]
txt = self.text
for line in txt:
line = line.lower()
for word in words:
if word in line:
return True
return False
def __get_keywords(self):
"""
Get all the keywords related of this page
Returns:
An array of strings
"""
for line in self.text:
for word in split_words(line):
yield(word)
def find_documents(self, sentence):
"""
Returns all the documents matching the given keywords
Arguments:
keywords --- keywords (single string)
Returns:
An array of document id (strings)
"""
if sentence.strip() == "":
return self.docs[:]
positive_keywords = []
negative_keywords = []
print("Looking for documents containing %s" %
(sentence.encode('ascii', 'replace')))
for keyword in split_words(sentence):
if keyword[:1] != "!":
positive_keywords.append(keyword)
else:
negative_keywords.append(keyword[1:])
if (len(positive_keywords) == 0 and len(negative_keywords) == 0):
return []
documents = None
if len(positive_keywords) <= 0:
positive_keywords = ["*"]
for keyword in positive_keywords:
docs = self.__find_documents(keyword)
if documents == None:
documents = docs
else:
documents.intersection_update(docs)
if documents == None:
return []
print "Found %d documents" % (len(documents))
for keyword in negative_keywords:
docs = self.__find_documents(keyword)
print "Found %d documents to remove" % (len(documents))
documents.symmetric_difference_update(docs)
documents = list(documents)
documents.sort()
return documents
def find_documents(self, sentence):
"""
Returns all the documents matching the given keywords
Arguments:
keywords --- keywords (single string)
Returns:
An array of document id (strings)
"""
if sentence.strip() == "":
return self.docs[:]
positive_keywords = []
negative_keywords = []
print ("Looking for documents containing %s"
% (sentence.encode('ascii', 'replace')))
for keyword in split_words(sentence):
if keyword[:1] != "!":
positive_keywords.append(keyword)
else:
negative_keywords.append(keyword[1:])
if (len(positive_keywords) == 0 and len(negative_keywords) == 0):
return []
documents = None
if len(positive_keywords) <= 0:
positive_keywords = ["*"]
for keyword in positive_keywords:
docs = self.__find_documents(keyword)
if documents == None:
documents = docs
else:
documents.intersection_update(docs)
if documents == None:
return []
print "Found %d documents" % (len(documents))
for keyword in negative_keywords:
docs = self.__find_documents(keyword)
print "Found %d documents to remove" % (len(documents))
documents.symmetric_difference_update(docs)
documents = list(documents)
documents.sort()
return documents
def add_label(self, label, doc):
"""
Add a new label to the list of known labels.
Arguments:
label --- The new label (see labels.Label)
doc --- The first document on which this label has been added
"""
label_words = split_words(label.name)
for word in label_words:
self.__index_keyword(doc, word)
if not word in self.__keywords:
self.__keywords.append(word)
self.__keywords.sort()
if not label in self.label_list:
self.label_list.append(label)
self.label_list.sort()
def add_label(self, label, doc):
"""
Add a new label to the list of known labels.
Arguments:
label --- The new label (see labels.Label)
doc --- The first document on which this label has been added
"""
label_words = split_words(label.name)
for word in label_words:
if not word in self.__keyword_to_docs:
self.__keywords.append(word)
self.__keywords.sort()
self.__keyword_to_docs[word] = set([doc])
else:
self.__keyword_to_docs[word].add(doc)
if not label in self.label_list:
self.label_list.append(label)
self.label_list.sort()
def find_suggestions(self, sentence):
"""
Search all possible suggestions. Suggestions returned always have at
least one document matching.
Arguments:
sentence --- keywords (single strings) for which we want
suggestions
Return:
An array of sets of keywords. Each set of keywords (-> one string)
is a suggestion.
"""
keywords = split_words(sentence)
results = self.__find_suggestions(self.__unfold_generator(keywords))
try:
results.remove(sentence) # remove strict match if it is here
except ValueError:
pass
results.sort()
return results
def find_suggestions(self, sentence):
"""
Search all possible suggestions. Suggestions returned always have at
least one document matching.
Arguments:
sentence --- keywords (single strings) for which we want
suggestions
Return:
An array of sets of keywords. Each set of keywords (-> one string)
is a suggestion.
"""
keywords = split_words(sentence)
results = self.__find_suggestions([x for x in keywords])
try:
results.remove(sentence) # remove strict match if it is here
except ValueError:
pass
results.sort()
return results
logger.error("Unable to get boxes for '%s': %s"
% (self.doc.docid, exc))
# will fall back on pdf boxes
except OSError, exc: # os.stat() failed
pass
# fall back on what libpoppler tells us
# TODO: Line support !
txt = self.pdf_page.get_text()
pdf_size = self.pdf_page.get_size()
words = set()
self.__boxes = []
for line in txt.split("\n"):
for word in split_words(unicode(line, encoding='utf-8')):
words.add(word)
for word in words:
for rect in self.pdf_page.find_text(word):
word_box = PdfWordBox(word, rect, pdf_size)
line_box = PdfLineBox([word_box], rect, pdf_size)
self.__boxes.append(line_box)
return self.__boxes
boxes = property(__get_boxes)
def __render_img(self, factor):
# TODO(Jflesch): In a perfect world, we shouldn't use ImageSurface.
# we should draw directly on the GtkImage.window.cairo_create()
# context. It would be much more efficient.
def main():
pconfig = config.PaperworkConfig()
pconfig.read()
print("Opening docs (%s)" % pconfig.workdir)
print("====================")
dsearch = docsearch.DocSearch(pconfig.workdir)
nb_words = 0
nb_docs = (len(dsearch.docs))
nb_pages = 0
max_pages = 0
total_word_len = 0
max_word_len = 0
words = set()
total_nb_unique_words = 0
total_nb_unique_words_per_doc = 0
print("")
print("Analysis")
print("========")
for doc in dsearch.docs:
sys.stdout.write(str(doc) + ": ")
sys.stdout.flush()
doc_words = set()
if doc.nb_pages > max_pages:
max_pages = doc.nb_pages
for page in doc.pages:
sys.stdout.write("%d " % (page.page_nb + 1))
sys.stdout.flush()
nb_pages += 1
for line in page.text:
for word in util.split_words(line):
# ignore words too short to be useful
if (len(word) < 4):
continue
if not word in words:
words.add(word)
total_nb_unique_words += 1
if not word in doc_words:
doc_words.add(word)
total_nb_unique_words_per_doc += 1
nb_words += 1
total_word_len += len(word)
if max_word_len < len(word):
max_word_len = len(word)
sys.stdout.write("\n")
print("")
print("Statistics")
print("==========")
print("Total number of documents: %d" % nb_docs)
print("Total number of pages: %d" % nb_pages)
print("Total number of words: %d" % nb_words)
print("Total words len: %d" % total_word_len)
print("Total number of unique words: %d" % total_nb_unique_words)
print("===")
print("Maximum number of pages in one document: %d" % max_pages)
print("Maximum word length: %d" % max_word_len)
print("Average word length: %f" % (float(total_word_len) / float(nb_words)))
print ("Average number of words per page: %f"
% (float(nb_words) / float(nb_pages)))
print ("Average number of words per document: %f"
% (float(nb_words) / float(nb_docs)))
print ("Average number of pages per document: %f"
% (float(nb_pages) / float(nb_docs)))
print ("Average number of unique words per document: %f"
% (float(total_nb_unique_words_per_doc) / float(nb_docs)))
except IOError, exc:
print "Unable to get boxes for '%s': %s" % (self.doc.docid, exc)
# will fall back on pdf boxes
except OSError, exc: # os.stat() failed
pass
# fall back on what libpoppler tells us
# TODO: Line support !
txt = self.pdf_page.get_text()
pdf_size = self.pdf_page.get_size()
words = set()
self.__boxes = []
for line in txt.split("\n"):
for word in split_words(unicode(line, encoding="utf-8")):
words.add(word)
for word in words:
for rect in self.pdf_page.find_text(word):
word_box = PdfWordBox(word, rect, pdf_size)
line_box = PdfLineBox([word_box], rect, pdf_size)
self.__boxes.append(line_box)
return self.__boxes
boxes = property(__get_boxes)
def __render_img(self, factor):
# TODO(Jflesch): In a perfect world, we shouldn't use ImageSurface.
# we should draw directly on the GtkImage.window.cairo_create() context.
# It would be much more efficient.
def main():
print "Opening index"
print "============="
pconfig = config.PaperworkConfig()
dsearch = docsearch.DocSearch(pconfig.workdir)
nb_words = 0
nb_docs = (len(dsearch.docs))
nb_pages = 0
total_word_len = 0
max_word_len = 0
words = set()
total_nb_unique_words = 0
total_nb_unique_words_per_doc = 0
print ""
print "Analysis"
print "========"
for doc in dsearch.docs:
sys.stdout.write(str(doc) + ": ")
sys.stdout.flush()
doc_words = set()
for page in doc.pages:
sys.stdout.write("%d " % (page.page_nb + 1))
sys.stdout.flush()
nb_pages += 1
for line in page.text:
for word in util.split_words(line):
# ignore words too short to be useful
if (len(word) < 4):
continue
if not word in words:
words.add(word)
total_nb_unique_words += 1
if not word in doc_words:
doc_words.add(word)
total_nb_unique_words_per_doc += 1
nb_words += 1
total_word_len += len(word)
if max_word_len < len(word):
max_word_len = len(word)
sys.stdout.write("\n")
print ""
print "Statistics"
print "=========="
print "Total number of documents: %d" % nb_docs
print "Total number of pages: %d" % nb_pages
print "Total number of words: %d" % total_word_len
print "Total number of unique words: %d" % total_nb_unique_words
print "==="
print "Maximum word length: %d" % max_word_len
print "Average word length: %f" % (float(total_word_len) / float(nb_words))
print("Average number of words per page: %f" %
(float(nb_words) / float(nb_pages)))
print("Average number of words per document: %f" %
(float(nb_words) / float(nb_docs)))
print("Average number of pages per document: %f" %
(float(nb_pages) / float(nb_docs)))
print("Average number of unique words per document: %f" %
(float(total_nb_unique_words_per_doc) / float(nb_docs)))