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Restructuring add-on.

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+                    GNU GENERAL PUBLIC LICENSE
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+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+  If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
+
+    <program>  Copyright (C) <year>  <name of author>
+    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+    This is free software, and you are welcome to redistribute it
+    under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License.  Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+  You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+<http://www.gnu.org/licenses/>.
+
+  The GNU General Public License does not permit incorporating your program
+into proprietary programs.  If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library.  If this is what you want to do, use the GNU Lesser General
+Public License instead of this License.  But first, please read
+<http://www.gnu.org/philosophy/why-not-lgpl.html>.

LICENSE.txt

-                    GNU GENERAL PUBLIC LICENSE
-                       Version 3, 29 June 2007
-
- Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
- Everyone is permitted to copy and distribute verbatim copies
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_text/orngText.py

+"""
+This module is used for text mining in Orange.
+
+The following languages are supported:
+bg - Bulgarian
+cs - Czech
+en - English
+es - Spanish
+et - Estonian
+fr - French
+ge - German
+hr - Croatian
+hu - Hungarian
+it - Italian
+ro - Romanian
+sl - Slovenian
+sr - Serbian
+"""
+
+"""
+list(string) = tokenize(string)
+
+>>> tokenize("Mico Mrkaic je isao po dlekom putu.")
+["Mico", " ", "Mrkaic", " ", "je", " ", "isao" ," ", "po",  " ", "dlekom", " ", "putu", "."]
+
+token = lemmatize(token)
+text = lemmatize(text, lemmatizer=None)
+list(token) = lemmatize(list(token), lemmatizer=None)
+
+p = preprocess() # default english
+p = preprocess(language="hrvatski")
+print p.stopwords
+p.stopwords = ['a', 'the']
+
+p.lemmatize('idemo')
+ici
+
+p.lemmatize('idemo kuci')
+'ici kuca'
+
+p.lemmatize(['idemo','kuci'])
+['ici','kuca']
+
+p.removeStopwords(text)
+p.removeStopwords(list(token))
+p.removeStopwords(token) # returns token or None
+
+print p.tokenize('I am the best.')
+I am best.
+
+table[0]['rijeci7']
+
+encoding - tmt uvijek prima i vraca UTF8 string
+da li je string ili lista je sugavo napravljeno
+dokumentacija
+dodati nove jezike
+text je zadnji string atribut
+from orngText import orngText - jel moze to bolje (proucit python pakete)
+
+##supportedLangs = [('bg', 'Bulgarian'), ('cs', 'Czech'), ('en', 'English'), ('es', 'Spanish')\
+##('et', 'Estonian'), ('fr', 'French'), ('ge', 'German'), ('hr', 'Croatian'),\
+##('hu', 'Hungarian'), ('it', 'Italian'), ('ro', 'Romanian'), ('sl', 'Slovenian'),\
+##('sr', 'Serbian')]
+
+"""
+
+import sys
+if sys.version < "2.4":
+   from sets import Set
+   set = Set
+from xml.sax import handler, make_parser
+import os.path
+import re
+import orange
+import orngTextWrapper
+import types
+import warnings
+from math import log,exp
+
+TEXTMETAID = 7
+
+def getTextAttributePos(data, textAttribute=None, issueWarning=True):
+    """return a position of a last string attribute,
+    if textAttribute not None checks if this is string,
+    return None if no string attribute found"""
+    if textAttribute not in data.domain:
+        textAttribute = None
+    if textAttribute != None and data.domain[textAttribute].varType == orange.VarTypes.String:
+        return data.domain.attributes.index(data.domain[textAttribute])
+    else:
+        atts = list(data.domain.attributes)
+        atts.reverse()
+        for a in atts:
+            if a.varType == orange.VarTypes.String:
+                return data.domain.attributes.index(data.domain[a])
+    if issueWarning:
+        warnings.warn("Data file includes no text attribute")
+    return None
+
+
+def loadWordSet(f):
+    try:
+       f = open(f, 'r')
+    except:
+       return set([])
+    setW = set([])
+    lines = f.readlines()
+    f.close()
+    for line in lines:
+        line = line.lower()
+        if line.find(';') != -1:
+            line = line[:line.find(';')]
+        line = line.strip(' \t\r\n')
+        if len(line):
+            setW.add(line)
+    return setW
+
+
+def boundary_split(s, removePunctuation = True):
+    if removePunctuation:
+        p = re.compile('[\.,!?()\[\]{}:;"\'<>/ \n\r\t]')
+        return [el for el in p.split(s) if el]
+    else:
+        t = []
+        s = re.split('\s', s)
+        p = re.compile('(\W)')
+        for phrase in s:
+            words = p.split(phrase)
+            for word in words:
+                t.append(word)
+        return [el for el in t if el]
+
+class Preprocess(object):
+
+    def __init__(self, language=None, inputEncoding='utf-8', outputEncoding='utf-8', normType = 'lemmatize'):
+        language = language or 'en'
+        self.inputEncoding = inputEncoding
+        self.outputEncoding = outputEncoding
+        self.tokenize = boundary_split
+        self.removedWords = []
+        if normType == 'stem' and len(self.langData[language]) == 3:
+            self.lemmatizer, self.stopwords = (self.langData[language][2], self.langData[language][1])
+        else:
+            self.lemmatizer, self.stopwords = self.langData[language][:2]
+
+    def _in2utf(self, s):
+       return s.decode(self.inputEncoding, 'replace').encode('utf-8', 'ignore')
+
+    def _utf2out(self, s):
+       return s.decode('utf-8', 'ignore').encode(self.outputEncoding, 'ignore')
+        
+    def doOnExampleTable(self, data, textAttribute=None, meth=None, callback=None):
+        newData = orange.ExampleTable(data)
+        textAttributePos = getTextAttributePos(data, textAttribute)
+        for ex in newData:
+            ex[textAttributePos] = meth(ex[textAttributePos].value)
+            if callback:
+                callback()
+        return newData
+        
+    def lemmatizeExampleTable(self, data, textAttribute, callback = None):
+        return self.doOnExampleTable(data, textAttribute, self.lemmatize, callback)
+        
+    def lemmatize(self, token):
+        if isinstance(token, types.StringTypes):
+            return self._utf2out(self.lemmatizer(self._in2utf(token)))
+        elif isinstance(token, types.ListType):
+            return [self._utf2out(self.lemmatizer(self._in2utf(t))) for t in token]
+        else:
+            raise TypeError
+
+    def lowercaseExampleTable(self, data, textAttribute=None, callback=None):
+        """return a data set whith a text of a text attribute in lowercase"""
+        textAttributePos = getTextAttributePos(data, textAttribute)
+        return self.doOnExampleTable(data, textAttributePos, self.lowercase, callback)
+
+    def lowercase(self, text, textAttribute=None):
+        """return a string in lowercase"""
+        text = text.decode(self.inputEncoding, "ignore")
+        return text.lower().encode(self.inputEncoding)
+
+
+    def removeStopwordsFromExampleTable(self, data, textAttribute=None, callback = None):
+        textAttributePos = getTextAttributePos(data, textAttribute)
+        return self.doOnExampleTable(data, textAttributePos, self.removeStopwords, callback)
+    
+    def removeStopwords(self, text):
+        if isinstance(text, types.StringTypes):
+            tokens = self.tokenize(text)
+            tokens = [token for token in tokens if self.lowercase(token) not in self.stopwords]
+            text = ' '.join(tokens)
+            return text
+            #return self._utf2out(tmt.removeWords(self._in2utf(text), list(self.stopwords)))
+        elif isinstance(text, types.ListType):
+            return [t for t in text if self.lowercase(t) not in self.stopwords] or None
+            #return [self._utf2out(t) for t in text if t not in self.stopwords] or None
+        else:
+            raise TypeError
+
+    def removeWordsFromExampleTable(self, data, textAttribute=None, callback = None):
+        textAttributePos = getTextAttributePos(data, textAttribute)
+        return self.doOnExampleTable(data, textAttributePos, self.removeWords, callback)
+   
+    # function filters text for words in removeWords
+    def removeWords(self, text):
+        if isinstance(text, types.StringTypes):
+            tokens = self.tokenize(text)
+            tokens = [token for token in tokens if (self.lowercase(token) not in self.removedWords and len(token) > 2)]
+            text = ' '.join(tokens)
+            return text
+        elif isinstance(text, types.ListType):
+            return [t for t in text if (self.lowercase(t) not in self.removedWords and len(t) > 2)] or None
+        else:
+            raise TypeError        
+
+    import textConfiguration
+    __languageDataPath = textConfiguration.datasetsPath
+    langData = {
+#            'en' : (lambda x: x, [], lambda x: re.split(r'\b', x, re.DOTALL)),
+            'en' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-en.bin')).lemmatizeText,
+                    loadWordSet(os.path.join(__languageDataPath,'stopwords_en.txt')),
+                    orngTextWrapper.porter().lemmatizeText),
+            'hr' : (orngTextWrapper.lemmatizer(os.path.join(__languageDataPath,'lem-hr.fsa')).lemmatizeText,
+                    loadWordSet(os.path.join(__languageDataPath,'stopwords_hr.txt'))),
+            'fr' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-fr.bin')).lemmatizeText,
+                    loadWordSet(os.path.join(__languageDataPath,'stopwords_fr.txt'))),
+            'bg' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-bg.bin')).lemmatizeText, set()),
+            'cs' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-cs.bin')).lemmatizeText, set()),
+            'et' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-et.bin')).lemmatizeText, set()),
+            'ge' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-ge.bin')).lemmatizeText, set()),
+            'hu' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-hu.bin')).lemmatizeText, set()),
+            'it' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-it.bin')).lemmatizeText, set()),
+            'ro' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-ro.bin')).lemmatizeText, set()),
+            'sl' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-sl.bin')).lemmatizeText, set()),
+            'es' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-es.bin')).lemmatizeText, set()),
+            'sr' : (orngTextWrapper.lemmagen(os.path.join(__languageDataPath,'lem-sr.bin')).lemmatizeText, set()),
+            }
+
+def loadReuters(dirName):
+    """Load all .sgm files from the directory dirName."""
+    from xml.sax import make_parser, handler   
+    import os, copy 
+
+    cat = orange.StringVariable("category")
+    name = orange.StringVariable("name")
+    meta = orange.StringVariable("text")
+    lewis = orange.StringVariable("lewissplit")
+    date = orange.StringVariable("date")
+    topics = orange.StringVariable("topics")
+    addCat = [cat, name, meta, lewis, date, topics]
+    dom = orange.Domain(addCat, 0)
+
+    data = orange.ExampleTable(dom)
+    cat = orange.StringVariable("category")
+    name = orange.StringVariable("name")
+    meta = orange.StringVariable("text")
+    lewis = orange.StringVariable("lewissplit")
+    date = orange.StringVariable("date")
+    topics = orange.StringVariable("topics")
+    addCat = [cat, name, meta, lewis, date, topics]
+    dom = orange.Domain(addCat, 0)
+
+    data = orange.ExampleTable(dom)
+
+
+    class ReutersHandler(handler.ContentHandler):
+        def __init__(self):
+            self.chars = []
+            self.parse = True                        
+            self.ignoreTags = set(['places','people','orgs','exchanges','companies','unknown'])
+            self.normalTags = set(['date','topics','title','dateline','body','text'])
+            self.document = {'dateline':'','title':'','body':''}
+            self.f = None
+            self.ex = orange.Example(dom)
+                        
+        def startElement(self, name, attrs):
+            if name.lower() == 'reuters':
+                for attName in attrs.keys():
+                    if attName.lower() == 'newid':
+                        self.ex['name'] = attrs.getValue(attName).encode('utf8','ignore')
+                    elif attName.lower() == 'topics':
+                       self.ex['topics'] = attrs[attName].encode('utf8','ignore')
+                    elif attName.lower() == 'lewissplit':
+                       self.ex['lewissplit'] = attrs.getValue(attName).encode('utf8','ignore')
+            elif name.lower() in self.ignoreTags:
+                self.parse = False
+            elif name.lower() in self.normalTags:
+                self.parse = True
+            else:
+                pass
+
+        def endElement(self, name):
+            if name.lower() in self.ignoreTags:
+                self.parse = True
+            elif name.lower() in self.normalTags:
+                if name.lower() == 'date':
+                   self.ex['date'] = ' '.join(self.chars).encode('utf8','ignore')
+                elif name.lower() == 'topics':
+                   for i in self.chars:
+                      if i in set(['',' ','\n','\r','\t']):
+                         self.chars.remove(i)
+                   self.ex['category']= '+'.join(self.chars).encode('utf8','ignore')
+                self.document[name.lower()] = ' '.join(self.chars).encode('utf8','ignore')
+                self.chars = []
+            elif name.lower() == 'reuters':
+                self.ex['text'] = self.document['title'] + '\n' + self.document['dateline'] + '\n' + self.document['body']
+                data.append(self.ex)
+                self.ex = orange.Example(dom)
+                self.chars = []
+            else:
+                pass
+
+
+        def characters(self, chrs):
+            if self.parse:
+                self.chars.append(chrs)
+
+    files = os.listdir(dirName)
+    files.sort()
+    for fileName in files:
+      fileName = os.path.join(dirName, fileName)
+      if fileName[-4:] == '.sgm':
+          p = make_parser()
+          p.setContentHandler(ReutersHandler())
+          f = open(fileName)
+          forbidden = set(['&#5;','&#22;','&#1;','&#31;','&#2;','&#3;','&#27;[B','&#30;','&#127;','\xFC'])
+          tmp = '_tmpsgmFile'
+          g = open(tmp, 'w')
+          g.write('<?xml version=\"1.0\" ?>\n')
+          g.write('<docset>')
+          f.readline()
+          for line in f:
+              for c in forbidden:
+                  line = line.replace(c, '')
+              g.write(line)
+          f.close()
+          g.write('</docset>')
+          g.close()
+          f = open(tmp)
+          try:
+             p.parse(f)
+          except:
+             print 'Error loading file %s\n' % fileName
+          f.close()
+          os.remove(tmp)         
+
+    return data
+
+def loadFromXML(fileName, tags={}, doNotParse=[]):
+    """returns ExampleTable, as already implemented by Mladen"""
+    cat = orange.StringVariable("category")
+    sel = orange.StringVariable("selection")
+    name = orange.StringVariable("name")
+    meta = orange.StringVariable("text")
+    addCat = [cat, sel, name, meta]
+    dom = orange.Domain(addCat, 0)    
+    data = orange.ExampleTable(dom)
+    
+    f = open(fileName, "r")
+    t = DocumentSetRetriever(f, tags = tags, doNotParse = doNotParse)
+    
+    while 1:
+        # load document
+        ex = orange.Example(dom)
+        doc = t.getNextDocument()
+        
+        if not len(doc): break
+        ex['category'] = ".".join([d.strip().encode('utf-8','ignore') for d in doc['categories']])
+        ex['selection'] = ''
+        ex['name'] = " ".join([("%s" % meta[1]).encode('utf-8','ignore') for meta in doc['meta']])
+        ex['text'] = doc['content'].strip().encode('utf-8','ignore')
+        
+        
+        data.append(ex)
+    return data
+        
+def loadFromListWithCategories(fileName):
+    """
+    File has two lines for each document:
+       *  first line contains the path to the document
+       *  second line contains space separated categories
+    
+    ExampleTable is returned whose domain contains category, name and text
+    """
+    cat = orange.StringVariable("category")
+    name = orange.StringVariable("name")
+    meta = orange.StringVariable("text")
+    addCat = [cat, name, meta]
+    dom = orange.Domain(addCat, 0)    
+    data = orange.ExampleTable(dom)
+    
+    
+    f = open(fileName)
+    while 1:
+        path = f.readline().strip()
+        if not path: break
+        categories = f.readline().strip().split(" ")
+        
+        tmpFile = open(path)
+               
+        ex = orange.Example(dom)
+        ex["name"] = path
+        ex["category"] = ".".join(categories)
+        ex["text"] = "".join(tmpFile.readlines())
+        data.append(ex) 
+            
+    f.close()
+    return data
+
+def bagOfWords(exampleTable, preprocessor=None, textAttribute=None, stopwords=None, callback=None):
+    """given the data return a bag-of-words representation for one of its string attributes"""
+    p = preprocessor
+    domaincopy = orange.Domain(exampleTable.domain)
+    # create new ExampleTable
+    data = orange.ExampleTable(exampleTable)
+    textAttributePos = getTextAttributePos(data, textAttribute)
+    #data.domain = orange.Domain(exampleTable.domain)
+
+    # for ex in exampleTable:
+    #       kreiraj newEx koji ima attribut category i name
+    #       tokeniziraj ex["text"]
+    #       svaki token koji nije interpunkcija dodaj u newex kao metaattribut koristeci incFreqWord
+    #       dodaj newex u newexampletable
+
+    allWords = {}
+    for ex in data:
+        if not preprocessor:
+           if stopwords:
+              tokens = boundary_split(ex[textAttributePos].value.decode('utf-8','ignore').encode('cp1250','ignore'))
+              tokens = [w for w in tokens if w.lower() not in stopwords]
+           else:
+              tokens = boundary_split(ex[textAttributePos].value.decode('utf-8','ignore').encode('cp1250','ignore'))
+        else:
+            tokens = preprocessor.removeStopwords(preprocessor.tokenize(preprocessor.lemmatize(preprocessor.lowercase(ex[textAttributePos].value))))
+        wordList = dict.fromkeys(tokens, 0)
+        for token in tokens:
+            wordList[token] += 1.0
+
+        for k in wordList.keys():
+           id = allWords.get(k, 0)
+           if not id:
+              id = orange.newmetaid()
+              allWords[k] = id
+           ex[id] = wordList[k]
+        if callback:
+            callback()
+
+    data.domain.addmetas(dict([(id, orange.FloatVariable(k)) for k, id in allWords.items()]), TEXTMETAID)
+
+    #exampleTable.domain = orange.Domain(data.domain.attributes)
+    exampleTable.changeDomain(domaincopy)
+    # vrati newexampletable
+    return data
+
+#selectFeaturesByFrequency(bof, min=1, max=None)
+#selectFeaturesByChiSquare(bof, min=4.0)
+
+
+#########data = loadFromListWithCategories('list.txt')
+#p = Preprocess()
+################print p.tokenize(data[0]['text'].value)
+######################bow = bagOfWords(data)
+
+############################################
+##
+## Parse document
+## It could be better to use exsting lib for parsing XML (Beautiful Soup)
+
+class DocumentSetHandler(handler.ContentHandler):            
+    def __init__(self, tags = None, doNotParse = []):
+        self.tagsToHandle = ["content", "category", "document", "categories"]
+        # set default XML tags
+        self.name2tag = {}
+        if not tags:
+            self.tags = {}
+            for tag in self.tagsToHandle:
+                self.tags[tag] = tag
+                self.name2tag[tag] = tag
+        else:
+            self.tags = {}
+            for tag in self.tagsToHandle:
+                if not tags.has_key(tag):
+                    self.tags[tag] = tag
+                    self.name2tag[tag] = tag
+                else:
+                    self.tags[tag] = tags[tag]
+                    self.name2tag[tags[tag]] = tag
+            
+
+                
+            
+        # for current document being parsed
+        self.curDoc = {}
+        self.documents = []
+        self.level = []
+            
+        # other settings
+        self.doNotParse = doNotParse[:]
+        self.doNotParseFlag = 0
+    def startElement(self, name, attrs):
+        if self.name2tag.has_key(name):
+            name = self.name2tag[name]
+##        if name == "document": 
+##            globals()['countdoc'] =globals()['countdoc'] + 1
+        if name in self.doNotParse:
+            self.doNotParseFlag += 1
+        else:
+            try:
+                func = getattr(self, 'do' + name.capitalize())
+                self.level.append(name)
+                func(attrs)
+            except:
+                if name in self.tags:
+                    self.level.append(name)
+                    self.curDoc[name] = []
+    def endElement(self, name):
+        if self.name2tag.has_key(name):
+            name = self.name2tag[name]        
+        if name in self.tags:
+            self.level.pop()
+            if name == "document":
+                self.curDoc["category"] = []
+                self.curDoc["content"] = "".join(self.curDoc["content"])
+                self.documents.append(self.curDoc)
+                self.curDoc = {}
+            elif name == "category":
+                self.curDoc["categories"].append("".join(self.curDoc["category"]))
+            elif name != "categories":
+                self.curDoc[name] = "".join(self.curDoc[name])
+        elif name in self.doNotParse:
+            self.doNotParseFlag -= 1
+    def characters(self, chrs):
+        if not self.doNotParseFlag:
+            try:
+                # check in which tag are the characters
+                # only tagsToHandle are parsed, others will raise exception that is ignored
+                name = self.level[-1]
+                if name not in ["document", "categories"]:
+                    self.curDoc[name].append(chrs)
+            except:
+                pass
+    def doDocument(self, attrs):
+        self.curDoc["meta"] = attrs.items()[:]
+        self.curDoc["content"] = []
+        self.curDoc["category"] = []
+        self.curDoc["categories"] = [] 
+    def doContent(self, attrs):
+        self.curDoc["content"] = []
+    def doCategory(self, attrs):
+        self.curDoc["category"] = []
+    def doCategories(self, attrs):
+        self.curDoc["categories"] = []
+
+class DocumentSetRetriever:
+
+    def __init__(self, source, tags = None, doNotParse = []):
+        self.source = source
+        self.handler = DocumentSetHandler(tags, doNotParse)
+        self.parser = make_parser()
+        self.parser.reset()
+        self.parser.setContentHandler(self.handler)
+
+    def getNextDocument(self):
+        while 1:
+            if len(self.handler.documents):
+                curDoc = self.handler.documents.pop(0)
+                return curDoc
+            if self.source.closed:
+                return {}
+            chunk = self.source.read(10000)
+            if not chunk:
+                self.parser.close()
+                return {}
+            else:
+                self.parser.feed(chunk)
+
+def saveExampleTable(table, fileName):
+   from pickle import dump
+
+   f = open(fileName, 'w')
+   dump(table, f)
+   f.close()
+
+def loadExampleTable(fileName):
+   from pickle import load
+
+   f = open(fileName)
+   table = load(f)
+   f.close()
+   return table
+
+class Preprocessor_norm:
+   def __call__(self, data, LNorm = 2, callback = None):
+      """Normalizes the ExampleTable table using the given L-Norm. The default norm is L2."""
+      from math import sqrt
+      newtable = orange.ExampleTable(data)
+      if LNorm == 2:
+         for example in newtable:
+            sum = 0         
+            for v in example.getmetas(TEXTMETAID).values():
+               #val = example[word].value
+               sum += v*v
+            sum = sqrt(sum)
+            for word in example.getmetas(TEXTMETAID).keys():
+               example[word] = example[word] / sum
+            if callback: callback()
+         return newtable
+      elif LNorm == 1:
+         for example in newtable:
+            sum = 0         
+            for v in example.getmetas(TEXTMETAID).values():
+               #val = example[word].value
+               sum += v
+            for word in example.getmetas(TEXTMETAID).keys():
+               example[word] = example[word] / sum
+            if callback: callback()
+         return newtable      
+      elif LNorm > 2:
+         from math import pow
+         for example in newtable:
+            sum = 0         
+            for v in example.getmetas(TEXTMETAID).values():
+               #val = example[word].value
+               sum += pow(v, LNorm)
+            sum = pow(sum, 1 / LNorm)
+            for word in example.getmetas(TEXTMETAID).keys():
+               example[word] = example[word] / sum
+            if callback: callback()
+         return newtable
+      elif LNorm == 0:
+         for example in newtable:
+            sum = 0         
+            for v in example.getmetas(TEXTMETAID).values():
+                  #val = example[word].value
+                  if v > sum:
+                     sum = v
+            for word in example.getmetas(TEXTMETAID).keys():
+               example[word] = example[word] / sum
+            if callback: callback()
+         return newtable
+      #return data
+      
+import math
+
+class Preprocessor_tfidf:
+    def __init__(self, termNormalizers):
+        self.termNormalizers = termNormalizers
+
+    def __call__(self, data, callback = None):
+        if type(data) == orange.ExampleTable:
+            newData = orange.ExampleTable(data)
+            for ex in newData:
+                for id, val in ex.getmetas(TEXTMETAID).items():
+                    ex[id] *= self.termNormalizers.get(id, 0)
+                if callback: callback()
+            return newData
+        else:
+            ex = orange.Example(data)
+            for id, val in ex.getmetas(TEXTMETAID).items():
+                ex[id] *= self.termNormalizers.get(id, 0)
+            return ex
+
+
+class PreprocessorConstructor_tfidf:
+    def __call__(self, data):
+        frequencies = {}
+        for ex in data:
+            for id in ex.getmetas(TEXTMETAID):
+                frequencies[id] = frequencies.get(id, 0) + 1
+
+        N = float(len(data))
+        normalizers = dict([(id, math.log(N/f)) for id, f in frequencies.items()])
+        return Preprocessor_tfidf(normalizers)
+
+
+def cos(bow, normalize = True, distance = 0, callback = None, metaClass=TEXTMETAID):
+   """returns distance matrix for bag-of-words measured as cosine of a angle btw feature vectors"""
+   from math import sqrt
+   c = orange.SymMatrix(len(bow))
+   metas = {}
+   for i, ex in enumerate(bow):
+      metas[i] = ex.getmetas(metaClass)
+   for i, ex1 in enumerate(bow):
+      for j in range(i):
+         if not distance:
+            c[i, j] = float(sum([v1 * metas[j].get(id, 0) for id, v1 in metas[i].items()]))
+         else:
+            try:
+               c[i, j] = 1. / float(sum([v1 * metas[j].get(id, 0) for id, v1 in metas[i].items()]))
+            except:
+               c[i, j] = 10000000
+         if normalize and c[i, j]:
+            c[i, j] /= sqrt(sum([k**2 for k in metas[j].values()])) * sqrt(sum([p**2 for p in metas[i].values()]))
+         if callback: callback()
+   return c
+
+def FSMRandom(table, perc = True):
+   from random import random
+   words = {}
+   for ex in table:
+      for v in ex.getmetas(TEXTMETAID).values():
+         varname = v.variable.name
+         if not words.has_key(varname):
+            words[varname] = random()
+   t = [(k, v) for k, v in words.items()]