How to use findWord method in fMBT

Best Python code snippet using fMBT_python

GetTense.py

Source:GetTense.py

...41                        nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1] != "VBG"):42                    a = TypeWord[0][0]43                    lemmatizer = WordNetLemmatizer()44                    x = lemmatizer.lemmatize(a, 'v')45                    WordLevel = FindWord.findWord(x)46                    TenseLevel = FindWord.findWord('Present Perfect')47                    if levels.index(WordLevel) <= levels.index(TenseLevel):48                        Tense.append(TenseLevel)49                    else:50                        Tense.append(WordLevel)51                    PresentPerfect.append(1)5253                # Present Progressive54                elif (TypeWord[0][1] == "VBG") and (words[i - 1] in ["am", "are", "is", "isn't"]) and (55                        words[i + 1] != 'to') or (TypeWord[0][1] == "VBG") and (56                        words[i - 1] in ["am", "are", "is", ] and (words[i - 2] == "not")) and (57                        words[i + 1] != 'to') or (58                        (TypeWord[0][1] == "VBG") and (59                        (nltk.pos_tag(nltk.word_tokenize(words[i - 1]))[0][1]) in ["NN", "PRP"] and (60                        words[i + 1] != "to") and (words[i - 2]) in ["am", "is", "are"] and (61                                words[i - 2] not in ["was", "were"]))):6263                    a = TypeWord[0][0]64                    lemmatizer = WordNetLemmatizer()65                    x = lemmatizer.lemmatize(a, 'v')66                    WordLevel = FindWord.findWord(x)67                    TenseLevel = FindWord.findWord('Present Progressive')68                    if levels.index(WordLevel) <= levels.index(TenseLevel):69                        Tense.append(TenseLevel)70                    else:71                        Tense.append(WordLevel)72                    PresentProgressive.append(1)7374                # S-Present75                elif ((TypeWord[0][1] in ["VBZ", "VBP", "VB"]) and (76                        words[i - 2] not in ["wouldn't", "would", "will", "did", "didn't"]) and (77                              words[i - 1] not in ["to", "will", "won't", "would", "wouldn't"]) and ((78                        (nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1]) not in ["VB", "VBD", "VBG", "VBN", "VBP",79                                                                                       "VBZ"])) and (80                              (nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1])) not in ["PRP", "NN"] and (81                              words[i + 1] != "not") or (82                              (TypeWord[0][1] == "VBZ" or "VBP") and (words[i - 1] in ["doesn't", "don't"]) and (83                              ((nltk.pos_tag(nltk.word_tokenize(words[i - 2]))[0][1])) in ["PRP", "NN"]) and ((84                              (nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1]) not in ["VB", "VBD", "VBG", "VBN",85                                                                                             "VBP", "VBZ"]))) or (86                              (TypeWord[0][1] == "VBZ" or "VBP") and (87                              (nltk.pos_tag(nltk.word_tokenize(words[i - 1]))[0][1]) in ["PRP", "NN"]) and (88                                      words[i - 2] in ["do", "does"]))):89                    a = TypeWord[0][0]90                    lemmatizer = WordNetLemmatizer()91                    x = lemmatizer.lemmatize(a, 'v')92                    WordLevel = FindWord.findWord(x)93                    TenseLevel = FindWord.findWord('Simple Present')94                    if levels.index(WordLevel) <= levels.index(TenseLevel):95                        Tense.append(TenseLevel)96                    else:97                        Tense.append(WordLevel)98                    SimplePresent.append(1)99100                # present perfect progressive101                elif (TypeWord[0][1] == "VBG") and words[i - 1] == 'been' and (102                        words[i - 2] in ['have', 'has', "hasn't", "haven't"]) and (103                        words[i - 3] not in ["will", "won't", "would", "wouldn't"]) and (104                        words[i - 4] not in ["wouldn't", "would", "will", "won't"]) or (105                        (TypeWord[0][1] == "VBG") and (words[i - 1] == 'been') and ((nltk.pos_tag(106                    nltk.word_tokenize(words[i - 2]))[0][1]) == "PRP" or "NN" or "NNS" or "NNP" or "NNPS") and (107                                words[i - 3] in ['has', 'have', "hasn't", "haven't"])):108                    a = TypeWord[0][0]109                    lemmatizer = WordNetLemmatizer()110                    x = lemmatizer.lemmatize(a, 'v')111                    WordLevel = FindWord.findWord(x)112                    TenseLevel = FindWord.findWord('Present perfect progressive')113                    if levels.index(WordLevel) <= levels.index(TenseLevel):114                        Tense.append(TenseLevel)115                    else:116                        Tense.append(WordLevel)117                    presentPerfectProgressive.append(1)118119                    # Past perfect120                elif (TypeWord[0][1] in ["VBN", "VBD"]) and (words[i - 1] in ['had', "hadn't"]) and (121                        (nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1]) != "VBG") or ((122                                                                                                     TypeWord[0][1] in [123                                                                                                 "VBN", "VBD"] and ((124                                                                                                                            nltk.pos_tag(125                                                                                                                                nltk.word_tokenize(126                                                                                                                                    words[127                                                                                                                                        i - 1]))[128                                                                                                                                0][129                                                                                                                                1]) == "PRP" or "NN" or "NNS" or "NNP" or "NNPS")) and (130                                                                                                     (words[i - 2] in [131                                                                                                         'had',132                                                                                                         "hadn't"]) and (133                                                                                                     (134                                                                                                             nltk.pos_tag(135                                                                                                                 nltk.word_tokenize(136                                                                                                                     words[137                                                                                                                         i + 1]))[138                                                                                                                 0][139                                                                                                                 1] != "VBG")))):140                    a = TypeWord[0][0]141                    lemmatizer = WordNetLemmatizer()142                    x = lemmatizer.lemmatize(a, 'v')143                    WordLevel = FindWord.findWord(x)144                    TenseLevel = FindWord.findWord('Past perfect')145                    if levels.index(WordLevel) <= levels.index(TenseLevel):146                        Tense.append(TenseLevel)147                    else:148                        Tense.append(WordLevel)149                    PastPerfect.append(1)150151                # simple past152                elif ((TypeWord[0][1] in ["VBN", "VBD"]) and (153                        (nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1]) not in ["NN", "PRP", "VBN", "VBD", "VB",154                                                                                       "VBG"]) and (155                              (nltk.pos_tag(nltk.word_tokenize(words[i - 1]))[0][1]) not in ["VBN", "VBD", "VB"]) and (156                              (nltk.pos_tag(nltk.word_tokenize(words[i - 1]))[0][1]) in ["NN", "PRP"]) and (157                              (nltk.pos_tag(nltk.word_tokenize(words[i - 1]))[0][1]) not in ["VBN", "VBD"]) or (158                              (TypeWord[0][1] == "VB") and (words[i - 1] == "didn't")) or (159                              (TypeWord[0][1] == "VB") and ((160                                                                    nltk.pos_tag(161                                                                        nltk.word_tokenize(162                                                                            words[163                                                                                i - 1]))[164                                                                        0][165                                                                        1]) == "PRP" or "NN" or "NNS" or "NNP" or "NNPS") and (166                                      words[i - 2] in [167                                  "didn't", 'did']))):168169                    a = TypeWord[0][0]170                    lemmatizer = WordNetLemmatizer()171                    x = lemmatizer.lemmatize(a, 'v')172                    WordLevel = FindWord.findWord(x)173                    TenseLevel = FindWord.findWord('Simple Past')174                    if levels.index(WordLevel) <= levels.index(TenseLevel):175                        Tense.append(TenseLevel)176                    else:177                        Tense.append(WordLevel)178                    simplePast.append(1)179180181                # Past Progressive182                elif (TypeWord[0][1] == "VBG") and ((words[i - 1] in ["was", "were", "wasn't", "weren't"])) or (183                        (TypeWord[0][1] == "VBG") and (((nltk.pos_tag(nltk.word_tokenize(words[i - 1]))[0][184                    1]) == "PRP" or "NN" or "NNS" or "NNP" or "NNPS"))) and (185                        (words[i - 2] in ["was", "were", "wasn't", "weren't"])):186                    a = TypeWord[0][0]187                    lemmatizer = WordNetLemmatizer()188                    x = lemmatizer.lemmatize(a, 'v')189                    WordLevel = FindWord.findWord(x)190                    TenseLevel = FindWord.findWord('past Progressive')191                    if levels.index(WordLevel) <= levels.index(TenseLevel):192                        Tense.append(TenseLevel)193                    else:194                        Tense.append(WordLevel)195                    PastProgressive.append(1)196197198                # Past perfect progressive199                elif (TypeWord[0][1] == "VBG" and ((words[i - 2] in ['had', "hadn't"])) and (200                        words[i - 1] == 'been')) or (201                        (TypeWord[0][1] == 'VBG') and (words[i - 1] == 'been') and ((nltk.pos_tag(202                    nltk.word_tokenize(words[i - 2]))[0][1]) == "PRP" or "NN" or "NNS" or "NNP" or "NNPS") and (203                                words[i - 3] in ['had', "hadn't"])):204                    a = TypeWord[0][0]205                    lemmatizer = WordNetLemmatizer()206                    x = lemmatizer.lemmatize(a, 'v')207                    WordLevel = FindWord.findWord(x)208                    TenseLevel = FindWord.findWord('Past perfect progressive')209                    if levels.index(WordLevel) <= levels.index(TenseLevel):210                        Tense.append(TenseLevel)211                    else:212                        Tense.append(WordLevel)213                    PastPerfectProgressive.append(1)214215216                # will future217                elif ((TypeWord[0][1] in ["VBP", "VB", "VBZ"]) and (words[i - 1] in ['will', "won't"])) or ((218                        (TypeWord[0][1] == 'VB') and (nltk.pos_tag(nltk.word_tokenize(words[i - 1]))[0][219                                                          1] == "PRP" or "NN" or "NNS" or "NNP" or "NNPS") and (220                                words[i - 2] in ['will',221                                                 "won't"]) and (222                                (nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1] not in ["VBG", "VBD", "VBN"])))):223                    a = TypeWord[0][0]224                    lemmatizer = WordNetLemmatizer()225                    x = lemmatizer.lemmatize(a, 'v')226                    WordLevel = FindWord.findWord(x)227                    TenseLevel = FindWord.findWord('will future')228                    if levels.index(WordLevel) <= levels.index(TenseLevel):229                        Tense.append(TenseLevel)230                    else:231                        Tense.append(WordLevel)232                    future.append(1)233234235236                # going to future237                elif ((TypeWord[0][1] == 'VB') and (words[i - 1] == 'to') and (words[i - 2] == 'going') and (238                        words[i - 3] == 'not') and (words[i - 4] in ['am', 'are', 'is'])) or (239                        (TypeWord[0][1] == 'VB') and (words[i - 1] == 'to') and (words[i - 2] == 'going') and (240                        nltk.pos_tag(nltk.word_tokenize(words[i - 3]))[0][1] in ["PRP", "NN", "NNS", "NNP",241                                                                                 "NNPS"]) and (242                                words[i - 4] in ['am', "is", 'are', ])) or (243                        (TypeWord[0][1] == 'VB') and (words[i - 1] == 'to') and (words[i - 2] == 'going') and (244                        words[i - 3] in ['am', 'are', 'is'])):245                    a = TypeWord[0][0]246                    lemmatizer = WordNetLemmatizer()247                    x = lemmatizer.lemmatize(a, 'v')248                    WordLevel = FindWord.findWord(x)249                    TenseLevel = FindWord.findWord('going to future')250                    if levels.index(WordLevel) <= levels.index(TenseLevel):251                        Tense.append(TenseLevel)252                    else:253                        Tense.append(WordLevel)254                    future.append(1)255256257                # futer progressive258                elif ((TypeWord[0][1] == 'VBG') and (words[i - 1] == 'be') and (words[i - 2] in ['will', "won't"])) or (259                        (TypeWord[0][1] == 'VBG') and (words[i - 1] == 'be') and (260                        nltk.pos_tag(nltk.word_tokenize(words[i - 2]))[0][261                            1] == "PRP" or "NN" or "NNS" or "NNP" or "NNPS") and (words[i - 3] in ['will', "won't"])):262                    a = TypeWord[0][0]263                    lemmatizer = WordNetLemmatizer()264                    x = lemmatizer.lemmatize(a, 'v')265                    WordLevel = FindWord.findWord(x)266                    TenseLevel = FindWord.findWord('future progressive')267                    if levels.index(WordLevel) <= levels.index(TenseLevel):268                        Tense.append(TenseLevel)269                    else:270                        Tense.append(WordLevel)271                    futureProgressive.append(1)272273274                # future perfect275                elif ((TypeWord[0][1] in ["VBN", "VBD"]) and (words[i - 1] == 'have') and (276                        words[i - 2] in ['will', "won't"]) and (277                              nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1] != "VBG")) or (278                        (TypeWord[0][1] in ["VBN", "VBD"]) and (words[i - 1] == 'have') and (279                        nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1] != "VBG") and (280                                nltk.pos_tag(nltk.word_tokenize(words[i - 2]))[0][281                                    1] == "PRP" or "NN" or "NNS" or "NNP" or "NNPS") and (282                                words[i - 3] in ['will', "won't"])):283                    a = TypeWord[0][0]284                    lemmatizer = WordNetLemmatizer()285                    x = lemmatizer.lemmatize(a, 'v')286                    WordLevel = FindWord.findWord(x)287                    TenseLevel = FindWord.findWord('future perfect')288                    if levels.index(WordLevel) <= levels.index(TenseLevel):289                        Tense.append(TenseLevel)290                    else:291                        Tense.append(WordLevel)292                    futurePerfect.append(1)293294295                # fututre perfect progressive296                elif ((TypeWord[0][1] == 'VBG') and (words[i - 1] == 'been') and (words[i - 2] == 'have') and (297                        words[i - 3] in ['will', "won't", "'ll", 'will not'])) or (298                        (TypeWord[0][1] == 'VBG') and (words[i - 1] == 'been') and (words[i - 2] == 'have') and (299                        nltk.pos_tag(nltk.word_tokenize(words[i - 3]))[0][300                            1] == "PRP" or "NN" or "NNS" or "NNP" or "NNPS") and (words[i - 4] in ['will', "won't"])):301                    a = TypeWord[0][0]302                    lemmatizer = WordNetLemmatizer()303                    x = lemmatizer.lemmatize(a, 'v')304                    WordLevel = FindWord.findWord(x)305                    TenseLevel = FindWord.findWord('future perfect progressive')306                    if levels.index(WordLevel) <= levels.index(TenseLevel):307                        Tense.append(TenseLevel)308                    else:309                        Tense.append(WordLevel)310                    futurePerfectProgressive.append(1)311312313                # conditional simple314                elif (TypeWord[0][1] == 'VB') and (words[i - 1] in ['would', "wouldn't"]) and (315                        nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1] not in ["VBG", "VBD", "VBN"]) or (316                        (TypeWord[0][1] == 'VB') and (317                        nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1] not in ["VBG", "VBN", "VBD"]) and (318                                nltk.pos_tag(nltk.word_tokenize(words[i - 1]))[0][319                                    1] == "PRP" or "NN" or "NNS" or "NNP" or "NNPS") and (320                                words[i - 2] in ['would', "wouldn't"])):321                    a = TypeWord[0][0]322                    lemmatizer = WordNetLemmatizer()323                    x = lemmatizer.lemmatize(a, 'v')324                    WordLevel = FindWord.findWord(x)325                    TenseLevel = FindWord.findWord('conditional simple')326                    if levels.index(WordLevel) <= levels.index(TenseLevel):327                        Tense.append(TenseLevel)328                    else:329                        Tense.append(WordLevel)330                    conditionalSimple.append(1)331332                # conditional progressive333                elif ((TypeWord[0][1] == 'VBG') and (words[i - 1] == 'be') and (334                        words[i - 2] in ['would', "wouldn't"])) or (335                        (TypeWord[0][1] == 'VBG') and (words[i - 1] == 'be') and (336                        nltk.pos_tag(nltk.word_tokenize(words[i - 2]))[0][337                            1] == "PRP" or "NN" or "NNS" or "NNP" or "NNPS") and (338                                words[i - 3] in ['would', "wouldn't"])):339                    a = TypeWord[0][0]340                    lemmatizer = WordNetLemmatizer()341                    x = lemmatizer.lemmatize(a, 'v')342                    WordLevel = FindWord.findWord(x)343                    TenseLevel = FindWord.findWord('conditional progressive')344                    if levels.index(WordLevel) <= levels.index(TenseLevel):345                        Tense.append(TenseLevel)346                    else:347                        Tense.append(WordLevel)348                    conditionalProgressive.append(1)349350351                # conditional perfect352                elif ((TypeWord[0][1] in ['VBN', "VBD"]) and (words[i - 1] == 'have') and (353                        words[i - 2] in ['would', "wouldn't"]) and (354                              nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1] != "VBG")) or (355                        (TypeWord[0][1] in ["VBN", "VBD"]) and (words[i - 1] == 'have') and (356                        nltk.pos_tag(nltk.word_tokenize(words[i - 2]))[0][357                            1] == "PRP" or "NN" or "NNS" or "NNP" or "NNPS") and (358                                words[i - 3] in ['would', "wouldn't"]) and (359                                nltk.pos_tag(nltk.word_tokenize(words[i + 1]))[0][1] != "VBG")):360                    a = TypeWord[0][0]361                    lemmatizer = WordNetLemmatizer()362                    x = lemmatizer.lemmatize(a, 'v')363                    WordLevel = FindWord.findWord(x)364                    TenseLevel = FindWord.findWord('conditional perfect')365                    if levels.index(WordLevel) <= levels.index(TenseLevel):366                        Tense.append(TenseLevel)367                    else:368                        Tense.append(WordLevel)369                    conditionalPerfect.append(1)370371372                # conditional perfect progressive373                elif ((TypeWord[0][1] == 'VBG') and (words[i - 1] == 'been') and (words[i - 2] == 'have') and (374                        words[i - 3] in ['would', "wouldn't"])) or (375                        (TypeWord[0][1] == 'VBG') and (words[i - 1] == 'been') and (words[i - 2] == 'have') and (376                        nltk.pos_tag(nltk.word_tokenize(words[i - 3]))[0][377                            1] == "PRP" or "NN" or "NNS" or "NNP" or "NNPS") and (378                                words[i - 4] in ['would', "wouldn't"])):379                    a = TypeWord[0][0]380                    lemmatizer = WordNetLemmatizer()381                    x = lemmatizer.lemmatize(a, 'v')382                    WordLevel = FindWord.findWord(x)383                    TenseLevel = FindWord.findWord('conditional perfect progressive')384                    if levels.index(WordLevel) <= levels.index(TenseLevel):385                        Tense.append(TenseLevel)386                    else:387                        Tense.append(WordLevel)388                    conditionalPerfectProgressive.append(1)389390        return Tense391    except :
...

reducer14.py

Source:reducer14.py

1#!/usr/bin/python2## reducer13.py3## Author: Prabhakar Gundugola4## Description: reducer code for HW1.45import sys6import math7def isspam(true_class):8    if true_class == 1:9        return 'SPAM'10    else:11        return 'HAM'12filenames = sys.argv[1:]13spam_email_count = 014ham_email_count = 015spam_word_count = 016ham_word_count = 017spam_findword = {}18ham_findword = {}19total_cases = 020correct_cases = 021for filename in filenames:22    with open(filename, "r") as myfile:23        for line in myfile:24            tokens = line.split('\t')25            doc_id = tokens[0]26            true_class = int(tokens[1])27            #findword = tokens[3]28            #findword_count = int(tokens[4])29            word_count = int(tokens[2])30            31            if true_class == 1:32                spam_email_count += 133                spam_word_count += word_count34            else:35                ham_email_count += 136                ham_word_count += word_count37            38            if len(tokens) > 3:39                for i in range(3, len(tokens), 2):40                    findword = tokens[i]41                    findword_count = int(tokens[i+1])42                    43                    if true_class == 1:44                        if findword not in spam_findword:45                            spam_findword[findword] = findword_count46                        else:47                            spam_findword[findword] += findword_count48                    else:49                        if findword not in ham_findword:50                            ham_findword[findword] = findword_count51                        else:52                            ham_findword[findword] += findword_count53print "spam_email_count: ", spam_email_count54print "ham_email_count: ", ham_email_count55print "spam_word_count: ", spam_word_count56print "ham_word_count: ", ham_word_count57spam_prior = math.log((1.0*spam_email_count)/(spam_email_count + ham_email_count))58ham_prior = math.log((1.0*ham_email_count)/(ham_email_count + spam_email_count))59spam_findword_prob = {}60ham_findword_prob = {}61print "spam_prior: ", spam_prior62print "ham_prior: ", ham_prior63for word in spam_findword:64    if spam_findword[word] > 0:65        spam_findword_prob[word] = math.log((1.0*spam_findword[word]/spam_word_count))66    else:67        spam_findword_prob[word] = float('-inf')68for word in ham_findword:69    if ham_findword[word] > 0:70        ham_findword_prob[word] = math.log((1.0*ham_findword[word]/ham_word_count))71    else:72        ham_findword_prob[word] = float('-inf')73# Naive Bayes classification74for filename in filenames:75    with open(filename, "r") as myfile:76        for line in myfile:77            total_cases += 178            tokens = line.split('\t')79            doc_id = tokens[0]80            true_class = int(tokens[1])81            vocab = {}82            if len(tokens) > 3:83                for i in range(3, len(tokens), 2):84                    findword = tokens[i]85                    findword_count = int(tokens[i+1])86                    vocab[findword] = findword_count87            88            spam_doc_prob, ham_doc_prob = 0.0, 0.089            for key, value in vocab.iteritems():90                if spam_findword_prob[key] == float('-inf'):91                    if value == 0:92                        spam_doc_prob += 093                    else:94                        spam_doc_prob += float('-inf')95                else:96                    spam_doc_prob += spam_findword_prob[key]*value97            for key, value in vocab.iteritems():98                if ham_findword_prob[key] == float('-inf'):99                    if value == 0:100                        ham_doc_prob += 0101                    else:102                        ham_doc_prob += float('-inf')103                else:104                    ham_doc_prob += ham_findword_prob[key]*value105                    106            spam_doc_prob += spam_prior107            ham_doc_prob += ham_prior108            109            result = doc_id.ljust(30) + '\t\t' + isspam(true_class) + '\t\t'110            if spam_doc_prob > ham_doc_prob:111                predicted = 1112            else:113                predicted = 0114            result += isspam(predicted)115            print result116            if true_class == predicted:117                correct_cases += 1118accuracy = 100.0*correct_cases/total_cases119print "-----------------------"120print "Accuracy: " + str(accuracy) + '%'...

binarysearch.py

Source:binarysearch.py

1'''2Binary search operates on a sorted array of size n. It searches for elements3by splitting at the n/2th element, and checks whether the element to find4is larger or smaller than the checked element. It then splits the bottom5(when element is smaller) or top (when element is bigger) in half again,6thereby eliminating the other half. It repeats this process until it finds the7element. runs in O(log n)8'''9import random10alphabet = "abcdefghijklmnopqrstuvwxyz"11words = []12# seed a list of random numbers13for num in range(0, 1000):14    word = ''15    sample = random.sample([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,16                            15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25], 12)17    for nr in sample:18        word += alphabet[nr]19    words.append(word)20findword = "xfdskjfsdhjk"21words.append(findword)22sortedwords = sorted(words)23def algorithms.BinarySearch(array, findword):24    if len(array) <= 0:25        print 'array contains no elements'26        return27    high = len(sortedwords) - 128    low = 029    currentlocation = ((high-low)/2) + low30    numberofsearches = 031    found = False32    while not found:33        numberofsearches += 134        print 'testing at location:', currentlocation35        if sortedwords[currentlocation] == findword:36            print 'found the word: ', findword, ' at location: ', currentlocation, ' in ', numberofsearches, ' searches.'37            break38        elif sortedwords[currentlocation] < findword:39            low = currentlocation40            currentlocation = ((high-low)/2) + low41        elif sortedwords[currentlocation] > findword:42            high = currentlocation43            currentlocation = ((high-low)/2) + low44def recursivebinarysearch(array, findword, upperbound, lowerbound):45    if len(array) <= 0:46        print 'array contains no elements'47        return48    if upperbound <= 0:49        print 'item:', findword, 'not found in array'50        return51    currentlocation = ((upperbound-lowerbound)/2)+lowerbound52    print 'testing at location:', currentlocation, upperbound, lowerbound53    if array[currentlocation] == findword:54        print 'found the word: ', findword, ' at location: ', currentlocation55        return currentlocation56    elif array[currentlocation] < findword:57        return recursivebinarysearch(array, findword, upperbound, currentlocation)58    elif array[currentlocation] > findword:59        return recursivebinarysearch(array, findword, currentlocation, lowerbound)60# passes an array that is constantly split until its search completes61def recursivesplitbinarysearch(array, findword):62    if len(array) <= 0:63        print 'array contains no elements, findword:', findword, 'not in array'64        return -165    location = len(array)/266    print 'array is now size:', len(array),' testing at location: ', location, array[location]67    if findword == array[location]:68        print 'found the word ', findword69        return True70    elif findword > array[location]:71        return recursivesplitbinarysearch(array[location:], findword)72    elif findword < array[location]:73        return recursivesplitbinarysearch(array[:location], findword)74algorithms.BinarySearch(sortedwords, findword)75recursivebinarysearch(sortedwords, findword, len(sortedwords), 0)...

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