In [1]:

    

%%time
import logging
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
logging.getLogger().setLevel(logging.INFO)

from gensim import corpora, models
from collections import defaultdict
import gensim
import Pyro4
    
class prob:
    slices = 0
    def __init__(self):
        self.twenty = []
        prob.slices += 1
    def __del__(self):
        prob.slices -= 1
class test:
    def __init__(self):
        self.box = []
def filtered(*args):
#removed word list    
    read_words = open('stopwords.txt', 'r')
    r_words = read_words.readline()
    #remove common words and tokenize
    stoplist = set(r_words.split())
    
    texts = [[word for word in document.lower().split() if word not in stoplist]
            for document in args]
    read_words.close()
    return texts
class iterator1:
    n1 = 0 
    def __init__(self):
        iterator1.n1+=1
    def delete(self):
        iterator1.n1 = 0 
class iterator2:
    n = 0 
    def __init__(self):
        iterator2.n+=1
    def delete(self):
        iterator2.n = 0 
#Outputs 20% side of the abstracts\n",
def outputfile(y): 
    num1 = iterator1()
    number1 = iterator1.n1
    file=open("cu_test_doc_"+str(number1)+".txt","w")
    for line in y:
        file.write(line)
    file.close()
    if number1 == 5:
        num1.delete()
#Create a file for each Directorate and Division 
def outputfile2(y): 
    num = iterator2()
    number = iterator2.n
    file=open("cu_test_dir_div_"+str(number)+".txt","w")    
    for line in y:
        file.write(line)
    file.close()
    if number == 5:
        num.delete()                
    
#Directorates and Divisions files
file = open('cu_doc_div.txt', 'r')
dd = file.readlines() 
    
#Download Abstracts\n",
file = open('cu_tigers.txt', 'r')
dictionary = file.readlines()
    
FSIZE = len(dictionary)
    
#split abstract lists length by 5 
t_split = FSIZE / 5
#variable to account for remainder if abstract list length is not evenly divisible by 5 
test_s = FSIZE % 5 
    
#round value to account for decimals 
r = round(t_split)
r1 = r*2
r2 = (r*2)+r
r3 = (r*4)
r4 = FSIZE - r3
    
#Objects that hold the abstract array slices 
L20_1 = prob()
L20_2 = prob()
L20_3 = prob()
L20_4 = prob()
L20_5 = prob()
    
#Objects that hold the Directorate Division 20% groups 
L20_10 = prob()
L20_20 = prob()
L20_30 = prob()
L20_40 = prob()
L20_50 = prob()
    
#Holders for each group 
t80 = test()
t20 = test()
    
#20% abstract group storage (first 4)
l1 = L20_1.twenty = dictionary[:r]
l2 = L20_2.twenty = dictionary[r:r1]
l3 = L20_3.twenty = dictionary[r1:r2]
l4 = L20_4.twenty = dictionary[r2:r3]
    
#make files for 20% abstract groups 
outputfile(l1)
outputfile(l2)
outputfile(l3)
outputfile(l4)
    
#20% Directorate Division group storage
d1 = L20_10.twenty = dd[:r] 
d2 = L20_20.twenty = dd[r:r1] 
d3 = L20_30.twenty = dd[r1:r2]
d4 = L20_40.twenty = dd[r2:r3] 
    
#make files for 20% Directorate Division groups 
outputfile2(d1)
outputfile2(d2)
outputfile2(d3)
outputfile2(d4)
            
# check for last 20% group to account for uneven 5 way split
if test_s == 0:
    l5 = L20_5.twenty = dictionary[r3:FSIZE]
    d5 = L20_50.twenty = dd[r3:FSIZE] 
    outputfile(l5)
    outputfile2(d5)
else: 
    l5 = L20_5.twenty = dictionary[r3:r4]
    d5 = L20_50.twenty = dd[r3:r4] 
    outputfile(l5)
    outputfile2(d5)
    
#********************Model Training*************************************

#t_file = open('topic_count.txt', 'r')
#t_count = t_file.read()
#TOPIC_COUNT = int(t_count)
    
#Comparison 1 arrangement, output test group into file, create: dictionary, corpus, lda model
t8a = t80.box = l2 + l3 + l4 + l5 

#create dictionary and filter abstract 
dictionary1 = corpora.Dictionary(filtered(*t8a))
dictionary1.save('cu_dict1.dict')
   
#create corpus
corpus1 = [dictionary1.doc2bow(text) for text in filtered(*t8a)]#filter stop words and covert from document to bag of words
corpora.MmCorpus.serialize('cu_corpus1.mm', corpus1)

#create model more passes have better results to an extent, but are more time consuming 
ldamodel1 = gensim.models.ldamulticore.LdaMulticore(corpus1, num_topics=TOPIC_COUNT, id2word = dictionary1, passes=40, workers=20, chunksize=1000)
#ldamodel1 = gensim.models.ldamodel.LdaModel(corpus1, num_topics=TOPIC_COUNT, id2word = dictionary1, passes=40)
ldamodel1.save('CuModel_1.lda')


    

    




INFO:gensim.utils:Pattern library is not installed, lemmatization won't be available.
INFO:gensim.corpora.sharded_corpus:Could not import Theano, will use standard float for default ShardedCorpus dtype.
INFO:summa.preprocessing.cleaner:'pattern' package not found; tag filters are not available for English
INFO:gensim.corpora.dictionary:adding document #0 to Dictionary(0 unique tokens: [])
INFO:gensim.corpora.dictionary:adding document #10000 to Dictionary(120683 unique tokens: ['polygenic', '(kinetic)', 'reused.', 'nanodevice', 'transmitting']...)
INFO:gensim.corpora.dictionary:built Dictionary(144742 unique tokens: ['polygenic', '(kinetic)', 'reused.', 'nanodevice', 'transmitting']...) from 13065 documents (total 2839436 corpus positions)
INFO:gensim.utils:saving Dictionary object under cu_dict1.dict, separately None
INFO:gensim.corpora.mmcorpus:storing corpus in Matrix Market format to cu_corpus1.mm
INFO:gensim.matutils:saving sparse matrix to cu_corpus1.mm
INFO:gensim.matutils:PROGRESS: saving document #0
INFO:gensim.matutils:PROGRESS: saving document #1000
INFO:gensim.matutils:PROGRESS: saving document #2000
INFO:gensim.matutils:PROGRESS: saving document #3000
INFO:gensim.matutils:PROGRESS: saving document #4000
INFO:gensim.matutils:PROGRESS: saving document #5000
INFO:gensim.matutils:PROGRESS: saving document #6000
INFO:gensim.matutils:PROGRESS: saving document #7000
INFO:gensim.matutils:PROGRESS: saving document #8000
INFO:gensim.matutils:PROGRESS: saving document #9000
INFO:gensim.matutils:PROGRESS: saving document #10000
INFO:gensim.matutils:PROGRESS: saving document #11000
INFO:gensim.matutils:PROGRESS: saving document #12000
INFO:gensim.matutils:PROGRESS: saving document #13000
INFO:gensim.matutils:saved 13065x144742 matrix, density=0.115% (2166122/1891054230)
INFO:gensim.corpora.indexedcorpus:saving MmCorpus index to cu_corpus1.mm.index
INFO:gensim.models.ldamodel:using symmetric alpha at 0.02127659574468085
INFO:gensim.models.ldamodel:using symmetric eta at 0.02127659574468085
INFO:gensim.models.ldamodel:using serial LDA version on this node
INFO:gensim.models.ldamulticore:running online LDA training, 47 topics, 40 passes over the supplied corpus of 13065 documents, updating every 20000 documents, evaluating every ~13065 documents, iterating 50x with a convergence threshold of 0.001000
INFO:gensim.models.ldamulticore:training LDA model using 20 processes
INFO:gensim.models.ldamulticore:PROGRESS: pass 0, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 0, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
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INFO:gensim.models.ldamulticore:PROGRESS: pass 0, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #3 (0.021): 0.004*students + 0.003*data + 0.003*development + 0.003*program + 0.003*stem + 0.003*engineering + 0.002*undergraduate + 0.002*science + 0.002*study + 0.002*methods
INFO:gensim.models.ldamodel:topic #14 (0.021): 0.006*energy + 0.005*data + 0.004*students + 0.003*model + 0.003*proposed + 0.003*work + 0.002*models + 0.002*systems + 0.002*system + 0.002*develop
INFO:gensim.models.ldamodel:topic #8 (0.021): 0.004*students + 0.004*engineering + 0.003*social + 0.003*stem + 0.003*education + 0.003*program + 0.003*development + 0.003*materials + 0.003*data + 0.002*study
INFO:gensim.models.ldamodel:topic #2 (0.021): 0.004*data + 0.004*systems + 0.004*students + 0.004*design + 0.002*study + 0.002*science + 0.002*social + 0.002*energy + 0.002*methods + 0.002*information
INFO:gensim.models.ldamodel:topic #41 (0.021): 0.004*students + 0.003*science + 0.003*materials + 0.003*important + 0.003*development + 0.003*graduate + 0.003*systems + 0.003*properties + 0.003*work + 0.003*energy
INFO:gensim.models.ldamodel:topic diff=30.798196, rho=1.000000
INFO:gensim.models.ldamodel:-10.784 per-word bound, 1762.7 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 1, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 1, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
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INFO:gensim.models.ldamulticore:PROGRESS: pass 1, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #1 (0.021): 0.004*data + 0.003*students + 0.003*study + 0.003*climate + 0.003*learning + 0.002*water + 0.002*systems + 0.002*work + 0.002*different + 0.002*development
INFO:gensim.models.ldamodel:topic #4 (0.021): 0.006*data + 0.003*learning + 0.002*design + 0.002*field + 0.002*study + 0.002*where + 0.002*students + 0.002*information + 0.002*science + 0.002*results
INFO:gensim.models.ldamodel:topic #19 (0.021): 0.006*students + 0.004*science + 0.003*data + 0.003*community + 0.003*proposed + 0.003*systems + 0.003*program + 0.002*development + 0.002*researchers + 0.002*support
INFO:gensim.models.ldamodel:topic #45 (0.021): 0.003*data + 0.003*model + 0.003*development + 0.003*students + 0.003*study + 0.002*materials + 0.002*time + 0.002*design + 0.002*based + 0.002*proposed
INFO:gensim.models.ldamodel:topic #17 (0.021): 0.006*data + 0.005*science + 0.004*students + 0.003*learning + 0.003*develop + 0.003*stem + 0.003*development + 0.003*computational + 0.003*work + 0.002*important
INFO:gensim.models.ldamodel:topic diff=0.797819, rho=0.257641
INFO:gensim.models.ldamodel:-10.555 per-word bound, 1504.9 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 2, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
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INFO:gensim.models.ldamulticore:PROGRESS: pass 2, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #7 (0.021): 0.013*materials + 0.004*students + 0.004*science + 0.003*development + 0.002*potential + 0.002*study + 0.002*program + 0.002*fundamental + 0.002*energy + 0.002*support
INFO:gensim.models.ldamodel:topic #31 (0.021): 0.007*students + 0.005*science + 0.003*learning + 0.003*data + 0.003*develop + 0.003*program + 0.003*undergraduate + 0.002*graduate + 0.002*cell + 0.002*materials
INFO:gensim.models.ldamodel:topic #37 (0.021): 0.006*materials + 0.003*systems + 0.003*development + 0.003*students + 0.003*study + 0.003*graduate + 0.003*data + 0.002*conference + 0.002*program + 0.002*develop
INFO:gensim.models.ldamodel:topic #18 (0.021): 0.004*students + 0.004*study + 0.003*materials + 0.003*model + 0.003*data + 0.003*chemical + 0.002*proposed + 0.002*engineering + 0.002*important + 0.002*work
INFO:gensim.models.ldamodel:topic #22 (0.021): 0.006*data + 0.005*ice + 0.004*students + 0.004*sea + 0.003*science + 0.003*develop + 0.003*arctic + 0.003*development + 0.003*engineering + 0.002*scientific
INFO:gensim.models.ldamodel:topic diff=0.806025, rho=0.249494
INFO:gensim.models.ldamodel:-10.374 per-word bound, 1327.1 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 3, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
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INFO:gensim.models.ldamulticore:PROGRESS: pass 3, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
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INFO:gensim.models.ldamodel:topic #26 (0.021): 0.020*data + 0.006*learning + 0.005*students + 0.005*science + 0.004*support + 0.003*information + 0.003*scientific + 0.003*network + 0.002*development + 0.002*social
INFO:gensim.models.ldamodel:topic #12 (0.021): 0.004*data + 0.004*develop + 0.004*students + 0.003*study + 0.003*science + 0.002*energy + 0.002*applications + 0.002*development + 0.002*methods + 0.002*design
INFO:gensim.models.ldamodel:topic #7 (0.021): 0.014*materials + 0.004*students + 0.004*science + 0.003*development + 0.002*potential + 0.002*polymer + 0.002*fundamental + 0.002*program + 0.002*study + 0.002*design
INFO:gensim.models.ldamodel:topic #0 (0.021): 0.002*materials + 0.002*students + 0.002*system + 0.002*study + 0.002*human + 0.002*data + 0.002*cells + 0.002*cell + 0.002*development + 0.002*develop
INFO:gensim.models.ldamodel:topic #13 (0.021): 0.013*data + 0.005*design + 0.002*social + 0.002*technology + 0.002*develop + 0.002*information + 0.002*science + 0.002*most + 0.002*field + 0.002*study
INFO:gensim.models.ldamodel:topic diff=0.809247, rho=0.242073
INFO:gensim.models.ldamodel:-10.231 per-word bound, 1201.8 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 4, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
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INFO:gensim.models.ldamulticore:PROGRESS: pass 4, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
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INFO:gensim.models.ldamulticore:PROGRESS: pass 4, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #0 (0.021): 0.002*system + 0.002*students + 0.002*materials + 0.002*study + 0.002*human + 0.002*cells + 0.002*data + 0.002*cell + 0.002*mechanisms + 0.002*microbial
INFO:gensim.models.ldamodel:topic #41 (0.021): 0.004*ocean + 0.003*important + 0.003*students + 0.003*materials + 0.003*science + 0.003*changes + 0.003*study + 0.003*properties + 0.003*graduate + 0.002*systems
INFO:gensim.models.ldamodel:topic #38 (0.021): 0.006*study + 0.006*data + 0.005*theory + 0.004*geometry + 0.004*students + 0.004*geometric + 0.003*mathematical + 0.003*applications + 0.003*information + 0.002*analysis
INFO:gensim.models.ldamodel:topic #4 (0.021): 0.006*data + 0.003*learning + 0.002*information + 0.002*important + 0.002*field + 0.002*community + 0.002*study + 0.002*work + 0.002*results + 0.002*design
INFO:gensim.models.ldamodel:topic #25 (0.021): 0.007*materials + 0.006*properties + 0.004*energy + 0.004*quantum + 0.003*students + 0.003*magnetic + 0.003*control + 0.003*experimental + 0.003*study + 0.003*metal
INFO:gensim.models.ldamodel:topic diff=0.803817, rho=0.235278
INFO:gensim.models.ldamodel:-10.113 per-word bound, 1107.5 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
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INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #20 (0.021): 0.008*data + 0.005*learning + 0.005*models + 0.004*algorithms + 0.004*develop + 0.003*work + 0.003*information + 0.003*machine + 0.003*system + 0.003*students
INFO:gensim.models.ldamodel:topic #4 (0.021): 0.006*data + 0.003*learning + 0.002*information + 0.002*important + 0.002*community + 0.002*work + 0.002*results + 0.002*study + 0.002*field + 0.002*security
INFO:gensim.models.ldamodel:topic #34 (0.021): 0.004*study + 0.003*data + 0.003*students + 0.002*social + 0.002*systems + 0.002*design + 0.002*quantum + 0.002*work + 0.002*test + 0.002*information
INFO:gensim.models.ldamodel:topic #8 (0.021): 0.009*social + 0.008*engineering + 0.006*stem + 0.005*students + 0.005*education + 0.004*study + 0.004*development + 0.003*learning + 0.003*program + 0.003*science
INFO:gensim.models.ldamodel:topic #36 (0.021): 0.013*data + 0.003*study + 0.003*development + 0.003*ice + 0.003*scientific + 0.003*students + 0.002*system + 0.002*applications + 0.002*potential + 0.002*program
INFO:gensim.models.ldamodel:topic diff=0.788218, rho=0.229024
INFO:gensim.models.ldamodel:-10.016 per-word bound, 1035.2 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #45 (0.021): 0.003*data + 0.003*model + 0.003*time + 0.002*study + 0.002*development + 0.002*models + 0.002*systems + 0.002*based + 0.002*results + 0.002*proposed
INFO:gensim.models.ldamodel:topic #42 (0.021): 0.008*species + 0.007*data + 0.004*students + 0.003*models + 0.003*study + 0.003*processes + 0.003*model + 0.002*different + 0.002*develop + 0.002*work
INFO:gensim.models.ldamodel:topic #26 (0.021): 0.027*data + 0.006*learning + 0.005*science + 0.004*support + 0.004*information + 0.004*students + 0.004*scientific + 0.003*network + 0.003*big + 0.003*social
INFO:gensim.models.ldamodel:topic #38 (0.021): 0.008*study + 0.007*theory + 0.005*geometry + 0.005*data + 0.005*geometric + 0.005*mathematical + 0.003*applications + 0.003*students + 0.003*pi + 0.003*theory,
INFO:gensim.models.ldamodel:topic #8 (0.021): 0.009*social + 0.008*engineering + 0.006*stem + 0.005*education + 0.005*students + 0.004*study + 0.004*development + 0.003*learning + 0.003*science + 0.003*program
INFO:gensim.models.ldamodel:topic diff=0.762900, rho=0.223244
INFO:gensim.models.ldamodel:-9.937 per-word bound, 980.4 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #29 (0.021): 0.005*data + 0.003*climate + 0.003*system + 0.002*systems + 0.002*important + 0.002*under + 0.002*spectrum + 0.002*model + 0.002*students + 0.002*understand
INFO:gensim.models.ldamodel:topic #21 (0.021): 0.008*power + 0.007*energy + 0.004*control + 0.004*system + 0.003*students + 0.003*solar + 0.003*systems + 0.002*develop + 0.002*communication + 0.002*grid
INFO:gensim.models.ldamodel:topic #25 (0.021): 0.011*materials + 0.007*properties + 0.005*quantum + 0.004*energy + 0.003*magnetic + 0.003*material + 0.003*students + 0.003*fundamental + 0.003*experimental + 0.003*mechanical
INFO:gensim.models.ldamodel:topic #9 (0.021): 0.006*software + 0.004*system + 0.004*systems + 0.004*design + 0.003*security + 0.003*computational + 0.003*methods + 0.003*development + 0.003*data + 0.003*algorithms
INFO:gensim.models.ldamodel:topic #26 (0.021): 0.028*data + 0.005*science + 0.005*learning + 0.004*information + 0.004*support + 0.004*scientific + 0.004*network + 0.003*students + 0.003*big + 0.003*social
INFO:gensim.models.ldamodel:topic diff=0.729668, rho=0.217881
INFO:gensim.models.ldamodel:-9.868 per-word bound, 934.4 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #28 (0.021): 0.004*chemical + 0.004*materials + 0.004*energy + 0.004*students + 0.004*chemistry + 0.003*training + 0.003*development + 0.003*science + 0.003*including + 0.003*program
INFO:gensim.models.ldamodel:topic #24 (0.021): 0.004*students + 0.003*development + 0.003*science + 0.002*support + 0.002*mechanisms + 0.002*undergraduate + 0.002*chemical + 0.002*potential + 0.002*graduate + 0.002*including
INFO:gensim.models.ldamodel:topic #14 (0.021): 0.011*energy + 0.008*power + 0.005*wireless + 0.005*proposed + 0.005*design + 0.005*systems + 0.004*system + 0.004*technology + 0.004*data + 0.004*performance
INFO:gensim.models.ldamodel:topic #26 (0.021): 0.030*data + 0.005*science + 0.005*learning + 0.005*information + 0.004*support + 0.004*network + 0.004*scientific + 0.003*big + 0.003*social + 0.003*students
INFO:gensim.models.ldamodel:topic #36 (0.021): 0.015*data + 0.003*development + 0.003*study + 0.003*ice + 0.003*scientific + 0.002*system + 0.002*support + 0.002*students + 0.002*information + 0.002*potential
INFO:gensim.models.ldamodel:topic diff=0.690297, rho=0.212886
INFO:gensim.models.ldamodel:-9.809 per-word bound, 897.0 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #39 (0.021): 0.007*data + 0.005*software + 0.004*system + 0.003*develop + 0.003*memory + 0.003*work + 0.003*proposed + 0.002*systems + 0.002*analysis + 0.002*performance
INFO:gensim.models.ldamodel:topic #22 (0.021): 0.015*ice + 0.009*sea + 0.007*arctic + 0.006*ocean + 0.005*data + 0.005*climate + 0.004*antarctic + 0.003*science + 0.003*level + 0.003*changes
INFO:gensim.models.ldamodel:topic #35 (0.021): 0.006*data + 0.004*students + 0.004*collections + 0.003*water + 0.003*specimens + 0.003*science + 0.002*control + 0.002*collection + 0.002*design + 0.002*important
INFO:gensim.models.ldamodel:topic #45 (0.021): 0.003*data + 0.003*model + 0.003*time + 0.002*study + 0.002*models + 0.002*development + 0.002*results + 0.002*based + 0.002*structure + 0.002*proposed
INFO:gensim.models.ldamodel:topic #6 (0.021): 0.007*data + 0.004*students + 0.004*graduate + 0.004*scientific + 0.004*methods + 0.004*science + 0.003*design + 0.003*study + 0.003*education + 0.002*program
INFO:gensim.models.ldamodel:topic diff=0.646542, rho=0.208220
INFO:gensim.models.ldamodel:-9.759 per-word bound, 866.6 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #23 (0.021): 0.004*students + 0.004*data + 0.003*development + 0.003*develop + 0.003*learning + 0.002*science + 0.002*computer + 0.002*process + 0.002*results + 0.002*teaching
INFO:gensim.models.ldamodel:topic #26 (0.021): 0.033*data + 0.006*science + 0.005*information + 0.004*support + 0.004*network + 0.004*learning + 0.004*scientific + 0.004*big + 0.003*social + 0.003*computing
INFO:gensim.models.ldamodel:topic #15 (0.021): 0.015*cell + 0.009*cells + 0.006*gene + 0.005*genes + 0.005*cellular + 0.004*genetic + 0.004*dna + 0.004*during + 0.004*mechanisms + 0.004*molecular
INFO:gensim.models.ldamodel:topic #36 (0.021): 0.016*data + 0.003*development + 0.003*scientific + 0.003*study + 0.003*ice + 0.002*system + 0.002*support + 0.002*access + 0.002*information + 0.002*potential
INFO:gensim.models.ldamodel:topic #45 (0.021): 0.003*data + 0.003*model + 0.003*time + 0.002*study + 0.002*models + 0.002*development + 0.002*results + 0.002*based + 0.002*structure + 0.002*proposed
INFO:gensim.models.ldamodel:topic diff=0.600209, rho=0.203848
INFO:gensim.models.ldamodel:-9.717 per-word bound, 841.4 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #4 (0.021): 0.006*data + 0.003*workers + 0.002*volcanic + 0.002*information + 0.002*important + 0.002*tsunami + 0.002*h-1b + 0.002*learning + 0.002*security + 0.002*work
INFO:gensim.models.ldamodel:topic #36 (0.021): 0.016*data + 0.003*development + 0.003*scientific + 0.003*study + 0.003*ice + 0.002*support + 0.002*system + 0.002*access + 0.002*information + 0.002*potential
INFO:gensim.models.ldamodel:topic #33 (0.021): 0.019*stem + 0.015*learning + 0.011*students + 0.008*education + 0.008*science + 0.008*development + 0.007*teachers + 0.007*mathematics + 0.006*program + 0.006*teaching
INFO:gensim.models.ldamodel:topic #9 (0.021): 0.008*software + 0.005*systems + 0.005*system + 0.005*security + 0.005*design + 0.004*computational + 0.004*algorithms + 0.004*methods + 0.003*computing + 0.003*tools
INFO:gensim.models.ldamodel:topic #22 (0.021): 0.017*ice + 0.011*sea + 0.008*arctic + 0.006*ocean + 0.005*climate + 0.005*data + 0.005*antarctic + 0.004*level + 0.003*science + 0.003*atmospheric
INFO:gensim.models.ldamodel:topic diff=0.552852, rho=0.199741
INFO:gensim.models.ldamodel:-9.681 per-word bound, 820.8 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #24 (0.021): 0.003*students + 0.003*support + 0.003*development + 0.003*mechanisms + 0.002*science + 0.002*potential + 0.002*chemical + 0.002*vessel + 0.002*undergraduate + 0.002*provides
INFO:gensim.models.ldamodel:topic #46 (0.021): 0.030*students + 0.012*program + 0.008*undergraduate + 0.007*stem + 0.007*faculty + 0.007*science + 0.006*engineering + 0.006*community + 0.005*underrepresented + 0.005*graduate
INFO:gensim.models.ldamodel:topic #19 (0.021): 0.005*science + 0.005*arctic + 0.004*social + 0.003*students + 0.003*technology + 0.003*systems + 0.002*development + 0.002*national + 0.002*proposed + 0.002*community
INFO:gensim.models.ldamodel:topic #14 (0.021): 0.011*energy + 0.009*power + 0.006*wireless + 0.006*design + 0.006*technology + 0.006*proposed + 0.005*systems + 0.005*system + 0.004*performance + 0.004*devices
INFO:gensim.models.ldamodel:topic #7 (0.021): 0.018*materials + 0.003*fuel + 0.003*design + 0.003*science + 0.003*students + 0.003*development + 0.002*energy + 0.002*fundamental + 0.002*potential + 0.002*polymer
INFO:gensim.models.ldamodel:topic diff=0.505826, rho=0.195871
INFO:gensim.models.ldamodel:-9.650 per-word bound, 803.5 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #15 (0.021): 0.016*cell + 0.010*cells + 0.006*gene + 0.006*genes + 0.005*cellular + 0.005*genetic + 0.004*mechanisms + 0.004*dna + 0.004*molecular + 0.004*during
INFO:gensim.models.ldamodel:topic #33 (0.021): 0.019*stem + 0.017*learning + 0.012*students + 0.009*education + 0.008*science + 0.008*development + 0.008*teachers + 0.007*mathematics + 0.006*program + 0.006*teaching
INFO:gensim.models.ldamodel:topic #3 (0.021): 0.005*language + 0.004*investigators + 0.004*stars + 0.004*study + 0.003*star + 0.003*formation + 0.003*students + 0.003*different + 0.003*gas + 0.003*galaxies
INFO:gensim.models.ldamodel:topic #29 (0.021): 0.004*data + 0.003*spectrum + 0.003*system + 0.003*coral + 0.002*climate + 0.002*important + 0.002*systems + 0.002*fault + 0.002*under + 0.002*radio
INFO:gensim.models.ldamodel:topic #11 (0.021): 0.014*water + 0.005*environmental + 0.004*carbon + 0.003*food + 0.003*develop + 0.003*organic + 0.003*nitrogen + 0.003*model + 0.002*models + 0.002*microbial
INFO:gensim.models.ldamodel:topic diff=0.460190, rho=0.192219
INFO:gensim.models.ldamodel:-9.624 per-word bound, 789.2 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #40 (0.021): 0.014*earthquake + 0.009*seismic + 0.006*slip + 0.006*earthquakes + 0.005*data + 0.005*fault + 0.004*rupture + 0.004*slow + 0.003*team + 0.003*hazard
INFO:gensim.models.ldamodel:topic #7 (0.021): 0.018*materials + 0.003*fuel + 0.003*design + 0.003*science + 0.003*students + 0.003*development + 0.002*energy + 0.002*potential + 0.002*fundamental + 0.002*cells
INFO:gensim.models.ldamodel:topic #45 (0.021): 0.003*data + 0.003*model + 0.003*time + 0.002*models + 0.002*study + 0.002*structure + 0.002*based + 0.002*results + 0.002*proposed + 0.002*different
INFO:gensim.models.ldamodel:topic #14 (0.021): 0.011*energy + 0.009*power + 0.006*technology + 0.006*wireless + 0.006*design + 0.006*proposed + 0.005*systems + 0.005*system + 0.004*performance + 0.004*devices
INFO:gensim.models.ldamodel:topic #36 (0.021): 0.017*data + 0.004*scientific + 0.003*development + 0.003*ice + 0.003*study + 0.002*support + 0.002*access + 0.002*system + 0.002*information + 0.002*past
INFO:gensim.models.ldamodel:topic diff=0.416723, rho=0.188763
INFO:gensim.models.ldamodel:-9.601 per-word bound, 776.8 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #22 (0.021): 0.019*ice + 0.012*sea + 0.010*arctic + 0.007*ocean + 0.006*climate + 0.006*antarctic + 0.005*data + 0.004*level + 0.004*atmospheric + 0.004*changes
INFO:gensim.models.ldamodel:topic #40 (0.021): 0.015*earthquake + 0.009*seismic + 0.006*slip + 0.006*earthquakes + 0.005*data + 0.005*fault + 0.004*rupture + 0.004*slow + 0.003*team + 0.003*hazard
INFO:gensim.models.ldamodel:topic #23 (0.021): 0.003*develop + 0.003*data + 0.003*students + 0.003*development + 0.002*computer + 0.002*process + 0.002*science + 0.002*results + 0.002*damage + 0.002*cognitive
INFO:gensim.models.ldamodel:topic #5 (0.021): 0.007*data + 0.005*students + 0.005*dark + 0.005*matter + 0.004*group + 0.003*physics + 0.003*work + 0.003*particle + 0.003*study + 0.003*design
INFO:gensim.models.ldamodel:topic #8 (0.021): 0.013*social + 0.007*engineering + 0.006*study + 0.004*what + 0.004*policy + 0.004*education + 0.004*stem + 0.003*political + 0.003*data + 0.003*across
INFO:gensim.models.ldamodel:topic diff=0.375963, rho=0.185488
INFO:gensim.models.ldamodel:-9.581 per-word bound, 766.1 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #10 (0.021): 0.004*data + 0.003*global + 0.003*support + 0.003*science + 0.003*work + 0.003*time + 0.003*methods + 0.003*models + 0.002*development + 0.002*students
INFO:gensim.models.ldamodel:topic #33 (0.021): 0.020*stem + 0.019*learning + 0.012*students + 0.009*education + 0.009*science + 0.008*teachers + 0.008*development + 0.008*mathematics + 0.007*teaching + 0.006*program
INFO:gensim.models.ldamodel:topic #12 (0.021): 0.004*gravitational + 0.004*develop + 0.003*data + 0.003*study + 0.002*students + 0.002*solar + 0.002*techniques + 0.002*results + 0.002*important + 0.002*work
INFO:gensim.models.ldamodel:topic #34 (0.021): 0.003*study + 0.003*data + 0.002*test + 0.002*students + 0.002*work + 0.002*online + 0.002*investigators + 0.002*social + 0.002*design + 0.002*key
INFO:gensim.models.ldamodel:topic #37 (0.021): 0.004*se + 0.004*systems + 0.003*materials + 0.002*theory + 0.002*study + 0.002*development + 0.002*award + 0.002*develop + 0.002*structures + 0.002*pi
INFO:gensim.models.ldamodel:topic diff=0.338240, rho=0.182377
INFO:gensim.models.ldamodel:-9.564 per-word bound, 757.0 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #35 (0.021): 0.007*data + 0.006*collections + 0.004*specimens + 0.004*collection + 0.003*water + 0.003*students + 0.003*specimen + 0.003*control + 0.002*multiple + 0.002*design
INFO:gensim.models.ldamodel:topic #4 (0.021): 0.006*data + 0.004*workers + 0.003*tsunami + 0.003*volcanic + 0.002*h-1b + 0.002*important + 0.002*sr + 0.002*numerical + 0.002*information + 0.002*submarine
INFO:gensim.models.ldamodel:topic #40 (0.021): 0.016*earthquake + 0.009*seismic + 0.006*slip + 0.006*earthquakes + 0.005*fault + 0.005*data + 0.004*rupture + 0.004*slow + 0.004*hazard + 0.003*team
INFO:gensim.models.ldamodel:topic #30 (0.021): 0.005*data + 0.004*pain + 0.004*health + 0.004*system + 0.003*model + 0.003*developed + 0.003*treatment + 0.003*analysis + 0.003*systems + 0.002*computational
INFO:gensim.models.ldamodel:topic #17 (0.021): 0.005*science + 0.005*computational + 0.005*data + 0.004*develop + 0.004*development + 0.003*speech + 0.003*work + 0.003*computer + 0.003*learning + 0.003*models
INFO:gensim.models.ldamodel:topic diff=0.303704, rho=0.179417
INFO:gensim.models.ldamodel:-9.549 per-word bound, 749.3 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #32 (0.021): 0.022*conference + 0.015*workshop + 0.011*researchers + 0.010*students + 0.008*international + 0.007*held + 0.007*support + 0.006*graduate + 0.006*participants + 0.005*award
INFO:gensim.models.ldamodel:topic #10 (0.021): 0.004*data + 0.003*global + 0.003*support + 0.003*science + 0.003*time + 0.003*work + 0.003*models + 0.002*methods + 0.002*development + 0.002*during
INFO:gensim.models.ldamodel:topic #25 (0.021): 0.015*materials + 0.008*properties + 0.005*quantum + 0.005*energy + 0.005*material + 0.004*fundamental + 0.004*students + 0.004*mechanical + 0.004*experimental + 0.004*surface
INFO:gensim.models.ldamodel:topic #31 (0.021): 0.013*protein + 0.009*proteins + 0.007*plant + 0.006*students + 0.006*molecular + 0.004*rna + 0.004*plants + 0.003*biological + 0.003*cellular + 0.003*synthetic
INFO:gensim.models.ldamodel:topic #29 (0.021): 0.004*spectrum + 0.004*data + 0.003*coral + 0.003*system + 0.003*radio + 0.002*fault + 0.002*important + 0.002*systems + 0.002*under + 0.002*climate
INFO:gensim.models.ldamodel:topic diff=0.272376, rho=0.176597
INFO:gensim.models.ldamodel:-9.536 per-word bound, 742.1 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #25 (0.021): 0.015*materials + 0.008*properties + 0.005*quantum + 0.005*energy + 0.005*material + 0.004*fundamental + 0.004*students + 0.004*mechanical + 0.004*experimental + 0.004*surface
INFO:gensim.models.ldamodel:topic #3 (0.021): 0.007*language + 0.005*stars + 0.005*investigators + 0.004*star + 0.004*study + 0.004*formation + 0.004*galaxies + 0.004*gas + 0.003*different + 0.003*observations
INFO:gensim.models.ldamodel:topic #14 (0.021): 0.011*energy + 0.009*power + 0.007*technology + 0.006*design + 0.006*wireless + 0.006*proposed + 0.006*system + 0.005*systems + 0.005*devices + 0.005*performance
INFO:gensim.models.ldamodel:topic #18 (0.021): 0.004*drug + 0.003*potential + 0.003*chemical + 0.003*team + 0.003*model + 0.003*proposed + 0.003*study + 0.003*important + 0.003*work + 0.002*molecular
INFO:gensim.models.ldamodel:topic #2 (0.021): 0.007*systems + 0.004*design + 0.004*building + 0.003*control + 0.003*distributed + 0.002*human + 0.002*information + 0.002*critical + 0.002*sensory + 0.002*develop
INFO:gensim.models.ldamodel:topic diff=0.244152, rho=0.173906
INFO:gensim.models.ldamodel:-9.524 per-word bound, 736.1 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 20, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #11 (0.021): 0.017*water + 0.006*environmental + 0.006*carbon + 0.004*food + 0.004*organic + 0.003*nitrogen + 0.003*production + 0.003*microbial + 0.003*soil + 0.003*develop
INFO:gensim.models.ldamodel:topic #38 (0.021): 0.012*theory + 0.010*study + 0.008*mathematical + 0.006*geometry + 0.006*geometric + 0.006*equations + 0.005*quantum + 0.005*theory, + 0.004*pi + 0.004*number
INFO:gensim.models.ldamodel:topic #46 (0.021): 0.032*students + 0.013*program + 0.009*undergraduate + 0.008*faculty + 0.008*stem + 0.008*engineering + 0.007*science + 0.007*community + 0.006*graduate + 0.006*underrepresented
INFO:gensim.models.ldamodel:topic #44 (0.021): 0.005*control + 0.005*technology + 0.004*design + 0.004*data + 0.003*brain + 0.003*system + 0.003*students + 0.003*potential + 0.003*improve + 0.002*human
INFO:gensim.models.ldamodel:topic #28 (0.021): 0.008*chemical + 0.008*chemistry + 0.004*professor + 0.004*students + 0.004*program + 0.004*instrument + 0.004*molecules + 0.004*energy + 0.004*training + 0.003*development
INFO:gensim.models.ldamodel:topic diff=0.218874, rho=0.171335
INFO:gensim.models.ldamodel:-9.514 per-word bound, 731.1 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 21, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #28 (0.021): 0.008*chemical + 0.008*chemistry + 0.005*professor + 0.004*students + 0.004*program + 0.004*instrument + 0.004*molecules + 0.004*energy + 0.004*training + 0.003*development
INFO:gensim.models.ldamodel:topic #41 (0.021): 0.009*ocean + 0.004*processes + 0.004*data + 0.004*study + 0.004*models + 0.004*flow + 0.004*seismic + 0.004*subduction + 0.004*mantle + 0.003*important
INFO:gensim.models.ldamodel:topic #24 (0.021): 0.003*vessel + 0.003*support + 0.003*mechanisms + 0.002*provides + 0.002*3d + 0.002*potential + 0.002*development + 0.002*science + 0.002*proposal + 0.002*instrumentation
INFO:gensim.models.ldamodel:topic #2 (0.021): 0.008*systems + 0.004*design + 0.004*building + 0.003*control + 0.003*distributed + 0.002*human + 0.002*information + 0.002*critical + 0.002*sensory + 0.002*develop
INFO:gensim.models.ldamodel:topic #34 (0.021): 0.002*data + 0.002*test + 0.002*work + 0.002*study + 0.002*students + 0.002*investigators + 0.002*online + 0.002*social + 0.002*design + 0.002*key
INFO:gensim.models.ldamodel:topic diff=0.196345, rho=0.168874
INFO:gensim.models.ldamodel:-9.504 per-word bound, 726.0 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 22, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #27 (0.021): 0.007*network + 0.005*data + 0.004*cancer + 0.003*species + 0.003*north + 0.003*develop + 0.003*science + 0.003*researchers + 0.002*lepidoptera + 0.002*including
INFO:gensim.models.ldamodel:topic #18 (0.021): 0.005*drug + 0.003*potential + 0.003*team + 0.003*chemical + 0.003*proposed + 0.003*model + 0.003*study + 0.003*important + 0.003*work + 0.002*molecular
INFO:gensim.models.ldamodel:topic #25 (0.021): 0.015*materials + 0.008*properties + 0.005*quantum + 0.005*energy + 0.005*material + 0.004*fundamental + 0.004*mechanical + 0.004*students + 0.004*experimental + 0.004*surface
INFO:gensim.models.ldamodel:topic #12 (0.021): 0.005*gravitational + 0.004*develop + 0.003*study + 0.003*data + 0.003*solar + 0.002*techniques + 0.002*results + 0.002*ligo + 0.002*students + 0.002*scientific
INFO:gensim.models.ldamodel:topic #30 (0.021): 0.005*pain + 0.005*data + 0.004*health + 0.004*system + 0.004*model + 0.003*treatment + 0.003*developed + 0.003*numerical + 0.003*chronic + 0.003*models
INFO:gensim.models.ldamodel:topic diff=0.176351, rho=0.166516
INFO:gensim.models.ldamodel:-9.496 per-word bound, 722.0 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 23, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #13 (0.021): 0.013*data + 0.005*design + 0.003*manufacturing + 0.002*most + 0.002*3d + 0.002*novel + 0.002*technology + 0.002*mass + 0.002*information + 0.002*system
INFO:gensim.models.ldamodel:topic #15 (0.021): 0.016*cell + 0.011*cells + 0.007*gene + 0.006*genes + 0.005*cellular + 0.005*mechanisms + 0.005*genetic + 0.004*molecular + 0.004*dna + 0.004*during
INFO:gensim.models.ldamodel:topic #40 (0.021): 0.017*earthquake + 0.011*seismic + 0.008*earthquakes + 0.007*slip + 0.007*fault + 0.005*data + 0.005*hazard + 0.004*rupture + 0.004*slow + 0.004*japan
INFO:gensim.models.ldamodel:topic #38 (0.021): 0.012*theory + 0.011*study + 0.009*mathematical + 0.006*geometry + 0.006*geometric + 0.006*equations + 0.005*quantum + 0.005*theory, + 0.005*pi + 0.004*number
INFO:gensim.models.ldamodel:topic #11 (0.021): 0.017*water + 0.007*environmental + 0.006*carbon + 0.004*food + 0.004*organic + 0.003*production + 0.003*nitrogen + 0.003*microbial + 0.003*soil + 0.003*develop
INFO:gensim.models.ldamodel:topic diff=0.158637, rho=0.164255
INFO:gensim.models.ldamodel:-9.487 per-word bound, 717.8 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 24, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #28 (0.021): 0.009*chemical + 0.008*chemistry + 0.005*professor + 0.005*program + 0.004*students + 0.004*instrument + 0.004*molecules + 0.004*energy + 0.004*training + 0.003*reactions
INFO:gensim.models.ldamodel:topic #21 (0.021): 0.011*power + 0.009*energy + 0.006*control + 0.005*system + 0.004*solar + 0.004*grid + 0.003*renewable + 0.003*perovskite + 0.003*communication + 0.003*systems
INFO:gensim.models.ldamodel:topic #8 (0.021): 0.014*social + 0.007*study + 0.005*engineering + 0.004*policy + 0.004*what + 0.004*political + 0.004*public + 0.003*people + 0.003*data + 0.003*economic
INFO:gensim.models.ldamodel:topic #29 (0.021): 0.005*spectrum + 0.004*coral + 0.003*data + 0.003*radio + 0.003*system + 0.003*fault + 0.003*reef + 0.002*systems + 0.002*important + 0.002*understand
INFO:gensim.models.ldamodel:topic #26 (0.021): 0.040*data + 0.007*information + 0.006*network + 0.006*science + 0.005*scientific + 0.005*infrastructure + 0.005*support + 0.004*big + 0.004*access + 0.004*software
INFO:gensim.models.ldamodel:topic diff=0.142973, rho=0.162083
INFO:gensim.models.ldamodel:-9.480 per-word bound, 714.0 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 25, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #8 (0.021): 0.014*social + 0.007*study + 0.005*engineering + 0.004*policy + 0.004*what + 0.004*political + 0.004*public + 0.004*people + 0.004*data + 0.003*economic
INFO:gensim.models.ldamodel:topic #3 (0.021): 0.009*language + 0.006*stars + 0.006*investigators + 0.005*star + 0.005*study + 0.004*galaxies + 0.004*formation + 0.004*gas + 0.004*observations + 0.003*different
INFO:gensim.models.ldamodel:topic #38 (0.021): 0.013*theory + 0.011*study + 0.009*mathematical + 0.006*geometry + 0.006*geometric + 0.006*equations + 0.005*quantum + 0.005*theory, + 0.005*pi + 0.004*number
INFO:gensim.models.ldamodel:topic #16 (0.021): 0.011*neural + 0.008*brain + 0.005*visual + 0.005*activity + 0.004*information + 0.003*optical + 0.003*data + 0.003*study + 0.003*physics + 0.003*different
INFO:gensim.models.ldamodel:topic #18 (0.021): 0.005*drug + 0.003*potential + 0.003*team + 0.003*proposed + 0.003*model + 0.003*chemical + 0.003*study + 0.003*important + 0.002*work + 0.002*drugs
INFO:gensim.models.ldamodel:topic diff=0.129125, rho=0.159995
INFO:gensim.models.ldamodel:-9.473 per-word bound, 710.5 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 26, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #46 (0.021): 0.033*students + 0.013*program + 0.009*undergraduate + 0.008*faculty + 0.008*engineering + 0.008*stem + 0.007*science + 0.007*community + 0.006*graduate + 0.006*underrepresented
INFO:gensim.models.ldamodel:topic #41 (0.021): 0.009*ocean + 0.005*data + 0.005*processes + 0.004*study + 0.004*models + 0.004*flow + 0.004*mantle + 0.004*seismic + 0.004*subduction + 0.003*important
INFO:gensim.models.ldamodel:topic #21 (0.021): 0.011*power + 0.009*energy + 0.006*control + 0.005*system + 0.004*solar + 0.004*grid + 0.003*renewable + 0.003*perovskite + 0.003*communication + 0.003*systems
INFO:gensim.models.ldamodel:topic #0 (0.021): 0.007*disease + 0.004*host + 0.004*bacteria + 0.004*microbial + 0.004*bacterial + 0.004*immune + 0.003*pathogen + 0.003*infectious + 0.003*human + 0.002*mechanisms
INFO:gensim.models.ldamodel:topic #4 (0.021): 0.006*workers + 0.005*data + 0.004*tsunami + 0.003*volcanic + 0.003*h-1b + 0.003*sr + 0.002*numerical + 0.002*submarine + 0.002*important + 0.002*einstein
INFO:gensim.models.ldamodel:topic diff=0.116893, rho=0.157986
INFO:gensim.models.ldamodel:-9.467 per-word bound, 707.6 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 27, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #21 (0.021): 0.011*power + 0.009*energy + 0.006*control + 0.005*system + 0.005*solar + 0.004*grid + 0.003*renewable + 0.003*perovskite + 0.003*communication + 0.003*systems
INFO:gensim.models.ldamodel:topic #36 (0.021): 0.020*data + 0.004*scientific + 0.004*development + 0.003*ice + 0.003*study + 0.003*access + 0.003*support + 0.003*subglacial + 0.003*past + 0.002*databases
INFO:gensim.models.ldamodel:topic #6 (0.021): 0.006*graduate + 0.005*data + 0.005*scientific + 0.004*science + 0.003*sleep + 0.003*students + 0.003*design + 0.003*education + 0.003*program + 0.003*local
INFO:gensim.models.ldamodel:topic #14 (0.021): 0.011*energy + 0.009*power + 0.008*technology + 0.007*design + 0.006*proposed + 0.006*wireless + 0.006*system + 0.006*systems + 0.005*devices + 0.005*performance
INFO:gensim.models.ldamodel:topic #1 (0.021): 0.011*climate + 0.007*species + 0.006*changes + 0.005*environmental + 0.005*data + 0.004*effects + 0.004*ecological + 0.004*study + 0.004*ecosystem + 0.003*marine
INFO:gensim.models.ldamodel:topic diff=0.106091, rho=0.156050
INFO:gensim.models.ldamodel:-9.461 per-word bound, 704.9 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 28, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #19 (0.021): 0.007*arctic + 0.006*science + 0.005*social + 0.003*photonics + 0.003*national + 0.003*technology + 0.002*systems + 0.002*development + 0.002*potential + 0.002*impacts
INFO:gensim.models.ldamodel:topic #5 (0.021): 0.008*matter + 0.007*dark + 0.006*physics + 0.006*data + 0.004*group + 0.004*particle + 0.004*students + 0.003*neutrino + 0.003*work + 0.003*cosmic
INFO:gensim.models.ldamodel:topic #25 (0.021): 0.016*materials + 0.008*properties + 0.005*material + 0.005*energy + 0.005*quantum + 0.004*fundamental + 0.004*mechanical + 0.004*experimental + 0.004*students + 0.004*surface
INFO:gensim.models.ldamodel:topic #6 (0.021): 0.006*graduate + 0.005*scientific + 0.005*data + 0.004*science + 0.003*sleep + 0.003*students + 0.003*design + 0.003*education + 0.003*program + 0.003*local
INFO:gensim.models.ldamodel:topic #32 (0.021): 0.022*conference + 0.018*workshop + 0.012*researchers + 0.010*students + 0.008*international + 0.007*support + 0.007*held + 0.006*graduate + 0.006*participants + 0.006*together
INFO:gensim.models.ldamodel:topic diff=0.096540, rho=0.154184
INFO:gensim.models.ldamodel:-9.455 per-word bound, 701.9 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 29, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #3 (0.021): 0.010*language + 0.006*stars + 0.006*investigators + 0.005*star + 0.005*study + 0.005*galaxies + 0.005*gas + 0.004*formation + 0.004*observations + 0.004*team
INFO:gensim.models.ldamodel:topic #25 (0.021): 0.016*materials + 0.008*properties + 0.005*material + 0.005*energy + 0.005*quantum + 0.004*fundamental + 0.004*mechanical + 0.004*experimental + 0.004*surface + 0.004*students
INFO:gensim.models.ldamodel:topic #18 (0.021): 0.006*drug + 0.004*potential + 0.003*team + 0.003*proposed + 0.003*model + 0.003*chemical + 0.003*important + 0.003*drugs + 0.002*work + 0.002*study
INFO:gensim.models.ldamodel:topic #5 (0.021): 0.008*matter + 0.007*dark + 0.007*physics + 0.006*data + 0.004*group + 0.004*particle + 0.004*students + 0.003*neutrino + 0.003*black + 0.003*work
INFO:gensim.models.ldamodel:topic #19 (0.021): 0.007*arctic + 0.006*science + 0.005*social + 0.003*photonics + 0.003*national + 0.003*technology + 0.002*systems + 0.002*development + 0.002*potential + 0.002*impacts
INFO:gensim.models.ldamodel:topic diff=0.088097, rho=0.152383
INFO:gensim.models.ldamodel:-9.450 per-word bound, 699.5 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 30, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #1 (0.021): 0.011*climate + 0.007*species + 0.006*changes + 0.005*environmental + 0.005*data + 0.004*effects + 0.004*ecological + 0.004*ecosystem + 0.004*study + 0.003*marine
INFO:gensim.models.ldamodel:topic #6 (0.021): 0.006*graduate + 0.005*scientific + 0.005*data + 0.005*science + 0.003*sleep + 0.003*students + 0.003*education + 0.003*design + 0.003*program + 0.003*local
INFO:gensim.models.ldamodel:topic #46 (0.021): 0.033*students + 0.013*program + 0.009*undergraduate + 0.008*engineering + 0.008*faculty + 0.008*stem + 0.007*science + 0.007*community + 0.007*graduate + 0.006*underrepresented
INFO:gensim.models.ldamodel:topic #14 (0.021): 0.011*energy + 0.009*power + 0.008*technology + 0.007*design + 0.007*proposed + 0.006*wireless + 0.006*system + 0.005*systems + 0.005*devices + 0.005*performance
INFO:gensim.models.ldamodel:topic #26 (0.021): 0.040*data + 0.007*information + 0.006*network + 0.006*science + 0.005*scientific + 0.005*infrastructure + 0.005*support + 0.004*access + 0.004*users + 0.004*big
INFO:gensim.models.ldamodel:topic diff=0.080615, rho=0.150644
INFO:gensim.models.ldamodel:-9.445 per-word bound, 697.1 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 31, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #28 (0.021): 0.010*chemical + 0.010*chemistry + 0.005*professor + 0.005*program + 0.005*students + 0.005*molecules + 0.004*instrument + 0.004*reactions + 0.004*energy + 0.004*training
INFO:gensim.models.ldamodel:topic #14 (0.021): 0.011*energy + 0.009*power + 0.008*technology + 0.007*design + 0.007*proposed + 0.006*wireless + 0.006*system + 0.005*systems + 0.005*devices + 0.005*performance
INFO:gensim.models.ldamodel:topic #13 (0.021): 0.012*data + 0.005*design + 0.003*manufacturing + 0.003*3d + 0.002*most + 0.002*novel + 0.002*mass + 0.002*deccan + 0.002*system + 0.002*technology
INFO:gensim.models.ldamodel:topic #44 (0.021): 0.007*control + 0.005*technology + 0.004*patients + 0.004*design + 0.003*system + 0.003*brain + 0.003*medical + 0.003*care + 0.003*clinical + 0.003*patient
INFO:gensim.models.ldamodel:topic #22 (0.021): 0.022*ice + 0.014*sea + 0.012*arctic + 0.009*ocean + 0.009*climate + 0.007*antarctic + 0.006*atmospheric + 0.005*level + 0.005*variability + 0.005*changes
INFO:gensim.models.ldamodel:topic diff=0.073968, rho=0.148964
INFO:gensim.models.ldamodel:-9.440 per-word bound, 694.7 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 32, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #43 (0.021): 0.010*fellowship + 0.010*evolutionary + 0.008*biology + 0.008*species + 0.007*biological + 0.007*fellow + 0.007*genetic + 0.006*training + 0.005*host + 0.005*plan
INFO:gensim.models.ldamodel:topic #40 (0.021): 0.017*earthquake + 0.011*seismic + 0.009*earthquakes + 0.008*slip + 0.008*fault + 0.007*summer + 0.006*u.s. + 0.006*japan + 0.006*data + 0.005*asia
INFO:gensim.models.ldamodel:topic #3 (0.021): 0.011*language + 0.007*stars + 0.006*investigators + 0.005*star + 0.005*study + 0.005*galaxies + 0.005*gas + 0.005*formation + 0.004*observations + 0.004*team
INFO:gensim.models.ldamodel:topic #25 (0.021): 0.016*materials + 0.008*properties + 0.005*material + 0.005*energy + 0.005*quantum + 0.004*fundamental + 0.004*mechanical + 0.004*experimental + 0.004*surface + 0.004*optical
INFO:gensim.models.ldamodel:topic #33 (0.021): 0.022*learning + 0.021*stem + 0.013*students + 0.010*education + 0.010*science + 0.009*teachers + 0.008*development + 0.008*mathematics + 0.007*teaching + 0.006*school
INFO:gensim.models.ldamodel:topic diff=0.068049, rho=0.147338
INFO:gensim.models.ldamodel:-9.436 per-word bound, 692.7 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 33, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #35 (0.021): 0.008*collections + 0.008*data + 0.007*specimens + 0.006*collection + 0.004*specimen + 0.003*water + 0.003*control + 0.003*multiple + 0.002*digitization + 0.002*biodiversity
INFO:gensim.models.ldamodel:topic #23 (0.021): 0.003*develop + 0.003*damage + 0.002*computer + 0.002*cognitive + 0.002*development + 0.002*results + 0.002*data + 0.002*novel + 0.002*monarch + 0.002*evolution
INFO:gensim.models.ldamodel:topic #20 (0.021): 0.012*data + 0.010*methods + 0.010*algorithms + 0.009*models + 0.007*develop + 0.006*learning + 0.006*statistical + 0.006*computational + 0.005*information + 0.005*analysis
INFO:gensim.models.ldamodel:topic #26 (0.021): 0.041*data + 0.007*information + 0.007*network + 0.006*science + 0.005*scientific + 0.005*infrastructure + 0.005*support + 0.004*access + 0.004*users + 0.004*big
INFO:gensim.models.ldamodel:topic #46 (0.021): 0.033*students + 0.014*program + 0.009*undergraduate + 0.009*engineering + 0.008*faculty + 0.008*stem + 0.007*science + 0.007*community + 0.007*graduate + 0.006*underrepresented
INFO:gensim.models.ldamodel:topic diff=0.062763, rho=0.145764
INFO:gensim.models.ldamodel:-9.431 per-word bound, 690.4 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 34, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #6 (0.021): 0.007*graduate + 0.005*scientific + 0.005*science + 0.004*data + 0.004*sleep + 0.003*education + 0.003*students + 0.003*design + 0.003*program + 0.003*local
INFO:gensim.models.ldamodel:topic #8 (0.021): 0.015*social + 0.007*study + 0.004*policy + 0.004*what + 0.004*engineering + 0.004*public + 0.004*people + 0.004*political + 0.004*data + 0.004*economic
INFO:gensim.models.ldamodel:topic #14 (0.021): 0.011*energy + 0.008*power + 0.008*technology + 0.007*design + 0.007*proposed + 0.006*wireless + 0.006*system + 0.005*systems + 0.005*devices + 0.005*performance
INFO:gensim.models.ldamodel:topic #16 (0.021): 0.013*neural + 0.012*brain + 0.006*visual + 0.005*activity + 0.004*information + 0.004*neuroscience + 0.003*optical + 0.003*physics + 0.003*imaging + 0.003*study
INFO:gensim.models.ldamodel:topic #32 (0.021): 0.022*conference + 0.019*workshop + 0.012*researchers + 0.011*students + 0.009*international + 0.008*support + 0.007*held + 0.006*graduate + 0.006*participants + 0.006*together
INFO:gensim.models.ldamodel:topic diff=0.058032, rho=0.144240
INFO:gensim.models.ldamodel:-9.428 per-word bound, 688.8 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 35, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #11 (0.021): 0.019*water + 0.008*environmental + 0.008*carbon + 0.005*organic + 0.004*food + 0.004*production + 0.004*microbial + 0.004*nitrogen + 0.004*soil + 0.003*process
INFO:gensim.models.ldamodel:topic #16 (0.021): 0.013*neural + 0.012*brain + 0.006*visual + 0.005*activity + 0.004*information + 0.004*neuroscience + 0.003*optical + 0.003*physics + 0.003*imaging + 0.003*processing
INFO:gensim.models.ldamodel:topic #20 (0.021): 0.012*data + 0.010*methods + 0.010*algorithms + 0.009*models + 0.007*develop + 0.006*learning + 0.006*computational + 0.006*statistical + 0.005*information + 0.005*analysis
INFO:gensim.models.ldamodel:topic #12 (0.021): 0.005*solar + 0.004*gravitational + 0.004*develop + 0.003*study + 0.003*data + 0.002*techniques + 0.002*scientific + 0.002*events + 0.002*results + 0.002*pis
INFO:gensim.models.ldamodel:topic #18 (0.021): 0.007*drug + 0.004*potential + 0.003*proposed + 0.003*team + 0.003*model + 0.003*drugs + 0.002*pharmaceutical + 0.002*blood + 0.002*chemical + 0.002*important
INFO:gensim.models.ldamodel:topic diff=0.053793, rho=0.142762
INFO:gensim.models.ldamodel:-9.424 per-word bound, 687.1 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 36, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #44 (0.021): 0.007*control + 0.006*technology + 0.005*patients + 0.004*medical + 0.004*patient + 0.004*clinical + 0.004*care + 0.004*design + 0.004*robotic + 0.004*human
INFO:gensim.models.ldamodel:topic #40 (0.021): 0.017*earthquake + 0.011*seismic + 0.009*summer + 0.009*earthquakes + 0.009*slip + 0.008*fault + 0.007*u.s. + 0.007*asia + 0.006*east + 0.006*institutes
INFO:gensim.models.ldamodel:topic #41 (0.021): 0.008*ocean + 0.005*data + 0.005*processes + 0.005*study + 0.005*flow + 0.005*models + 0.004*mantle + 0.004*surface + 0.004*earth + 0.004*important
INFO:gensim.models.ldamodel:topic #15 (0.021): 0.016*cell + 0.011*cells + 0.006*gene + 0.006*mechanisms + 0.005*genes + 0.005*cellular + 0.005*genetic + 0.004*molecular + 0.004*brain + 0.004*biological
INFO:gensim.models.ldamodel:topic #25 (0.021): 0.016*materials + 0.008*properties + 0.005*material + 0.005*energy + 0.005*quantum + 0.005*fundamental + 0.004*mechanical + 0.004*experimental + 0.004*optical + 0.004*surface
INFO:gensim.models.ldamodel:topic diff=0.049978, rho=0.141330
INFO:gensim.models.ldamodel:-9.421 per-word bound, 685.4 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 37, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #12 (0.021): 0.005*solar + 0.004*gravitational + 0.004*develop + 0.003*study + 0.003*data + 0.002*events + 0.002*scientific + 0.002*techniques + 0.002*results + 0.002*pis
INFO:gensim.models.ldamodel:topic #36 (0.021): 0.021*data + 0.004*scientific + 0.004*development + 0.003*ice + 0.003*access + 0.003*study + 0.003*support + 0.003*subglacial + 0.003*past + 0.003*databases
INFO:gensim.models.ldamodel:topic #22 (0.021): 0.023*ice + 0.014*sea + 0.012*arctic + 0.010*climate + 0.009*ocean + 0.007*atmospheric + 0.007*antarctic + 0.005*variability + 0.005*level + 0.005*changes
INFO:gensim.models.ldamodel:topic #24 (0.021): 0.004*vessel + 0.004*support + 0.003*instrumentation + 0.003*proposal + 0.003*provides + 0.003*3d + 0.003*oceanographic + 0.003*potential + 0.002*mechanisms + 0.002*r/v
INFO:gensim.models.ldamodel:topic #9 (0.021): 0.013*software + 0.008*security + 0.008*systems + 0.007*design + 0.006*computing + 0.006*system + 0.005*techniques + 0.005*computer + 0.004*hardware + 0.004*performance
INFO:gensim.models.ldamodel:topic diff=0.046547, rho=0.139939
INFO:gensim.models.ldamodel:-9.417 per-word bound, 683.7 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 38, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #8 (0.021): 0.015*social + 0.007*study + 0.005*policy + 0.004*what + 0.004*public + 0.004*people + 0.004*engineering + 0.004*political + 0.004*data + 0.004*economic
INFO:gensim.models.ldamodel:topic #46 (0.021): 0.033*students + 0.014*program + 0.009*undergraduate + 0.009*engineering + 0.009*faculty + 0.008*stem + 0.007*science + 0.007*community + 0.007*graduate + 0.006*underrepresented
INFO:gensim.models.ldamodel:topic #37 (0.021): 0.006*se + 0.004*systems + 0.002*theory + 0.002*structures + 0.002*rigidity + 0.002*oxidation + 0.002*materials + 0.002*award + 0.002*stable + 0.002*spread
INFO:gensim.models.ldamodel:topic #19 (0.021): 0.008*arctic + 0.007*science + 0.006*social + 0.003*photonics + 0.003*national + 0.002*systems + 0.002*development + 0.002*technology + 0.002*construction + 0.002*indigenous
INFO:gensim.models.ldamodel:topic #39 (0.021): 0.006*data + 0.003*software + 0.003*work + 0.003*system + 0.003*support + 0.003*different + 0.002*including + 0.002*proposed + 0.002*during + 0.002*memory
INFO:gensim.models.ldamodel:topic diff=0.043447, rho=0.138588
INFO:gensim.models.ldamodel:-9.414 per-word bound, 682.1 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #0 = documents up to #1000/13065, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #1 = documents up to #2000/13065, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #2 = documents up to #3000/13065, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #3 = documents up to #4000/13065, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #4 = documents up to #5000/13065, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #5 = documents up to #6000/13065, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #6 = documents up to #7000/13065, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #7 = documents up to #8000/13065, outstanding queue size 8
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #8 = documents up to #9000/13065, outstanding queue size 9
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #9 = documents up to #10000/13065, outstanding queue size 10
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #10 = documents up to #11000/13065, outstanding queue size 11
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #11 = documents up to #12000/13065, outstanding queue size 12
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #12 = documents up to #13000/13065, outstanding queue size 13
INFO:gensim.models.ldamulticore:PROGRESS: pass 39, dispatched chunk #13 = documents up to #13065/13065, outstanding queue size 14
INFO:gensim.models.ldamodel:topic #15 (0.021): 0.016*cell + 0.011*cells + 0.006*gene + 0.006*mechanisms + 0.005*genes + 0.005*cellular + 0.005*genetic + 0.004*molecular + 0.004*brain + 0.004*biological
INFO:gensim.models.ldamodel:topic #38 (0.021): 0.013*theory + 0.011*study + 0.010*mathematical + 0.006*geometric + 0.006*geometry + 0.006*equations + 0.006*quantum + 0.005*theory, + 0.005*pi + 0.004*number
INFO:gensim.models.ldamodel:topic #40 (0.021): 0.017*earthquake + 0.011*seismic + 0.011*summer + 0.009*earthquakes + 0.009*slip + 0.008*fault + 0.008*u.s. + 0.007*east + 0.007*asia + 0.007*institutes
INFO:gensim.models.ldamodel:topic #29 (0.021): 0.006*spectrum + 0.004*coral + 0.004*radio + 0.003*system + 0.003*reef + 0.003*data + 0.003*fault + 0.002*reefs + 0.002*nutritional + 0.002*support
INFO:gensim.models.ldamodel:topic #7 (0.021): 0.016*materials + 0.007*fuel + 0.004*design + 0.003*cells + 0.003*membranes + 0.002*energy + 0.002*performance + 0.002*potential + 0.002*sustainable + 0.002*shale
INFO:gensim.models.ldamodel:topic diff=0.040637, rho=0.137276
INFO:gensim.models.ldamodel:-9.410 per-word bound, 680.4 perplexity estimate based on a held-out corpus of 65 documents with 14564 words
INFO:gensim.utils:saving LdaState object under CuModel_1.lda.state, separately None
INFO:gensim.utils:saving LdaMulticore object under CuModel_1.lda, separately None
INFO:gensim.utils:not storing attribute dispatcher
INFO:gensim.utils:not storing attribute state






    




CPU times: user 34min 24s, sys: 13min 55s, total: 48min 19s
Wall time: 57min 3s

In [6]:

    

#All Xml Award IDs 
file2=open("cu_doc_div3.txt","w")    
for lines in gt8:
    file2.write(lines)
file2.close()


    

In [ ]:

    

#Comparison 2 arrangement, output test group into file, create: dictionary, corpus, lda model \n",
t8b = t80.box = l1 + l3 + l4 + l5 
t2b = t20.box = l2
#create test file
outputfile(l2)
#create dictionary and filter abstract 
dictionary2 = corpora.Dictionary(filtered(*t8b))
dictionary2.save('cu_dict2.dict')
#create corpus
corpus2 = [dictionary2.doc2bow(text) for text in filtered(*t8b)]#filter stop words and covert from document to bag of words
corpora.MmCorpus.serialize('cu_corpus2.mm', corpus2)
#create model 
ldamodel2 = gensim.models.ldamodel.LdaModel(corpus2, num_topics=25, id2word = dictionary2, passes=5)
ldamodel2.save('CuModel_2.lda')


#Comparison 3 arrangement, output test group into file, create: dictionary, corpus, lda model 
t8c = t80.box = l1 + l2 + l4 + l5  
t2c = t20.box = l3
#create test file
outputfile(l3)
#create dictionary and filter abstract 
dictionary3 = corpora.Dictionary(filtered(*t8c))\n",dictionary3.save('/tmp/cu_dict3.dict')
#create corpus
corpus3 = [dictionary3.doc2bow(text) for text in filtered(*t8c)]#filter stop words and covert from document to bag of words
corpora.MmCorpus.serialize('/tmp/cu_corpus3.mm', corpus3)
#create model 
ldamodel3 = gensim.models.ldamodel.LdaModel(corpus3, num_topics=25, id2word = dictionary3, passes=5)
ldamodel3.save('/tmp/CuModel_3.lda')
    
    
#Comparison 4 arrangement, output test group into file, create: dictionary, corpus, lda model
t8d = t80.box = l1 + l2 + l3 + l5
t2d = t20.box = l4
#create test file
outputfile(l4)
#create dictionary and filter abstract 
dictionary4 = corpora.Dictionary(filtered(*t8d))
dictionary4.save('/tmp/cu_dict4.dict')
#create corpus
corpus4 = [dictionary4.doc2bow(text) for text in filtered(*t8d)]#filter stop words and covert from document to bag of words
corpora.MmCorpus.serialize('/tmp/cu_corpus4.mm', corpus4)
#create model 
ldamodel4 = gensim.models.ldamodel.LdaModel(corpus4, num_topics=25, id2word = dictionary4, passes=5)
ldamodel4.save('/tmp/CuModel_4.lda')
    
#Comparison 5 arrangement, output test group into file, create: dictionary, corpus, lda model
t8e = t80.box = l1 + l2 + l3 + l4
t2e = t20.box = l5
#create test file
outputfile(l5)
#create dictionary and filter abstract 
dictionary5 = corpora.Dictionary(filtered(*t8e))
dictionary5.save('/tmp/cu_dict5.dict')
#create corpus
corpus5 = [dictionary5.doc2bow(text) for text in filtered(*t8e)]#filter stop words and covert from document to bag of words
corpora.MmCorpus.serialize('/tmp/cu_corpus5.mm', corpus5)
#create model 
ldamodel5 = gensim.models.ldamodel.LdaModel(corpus5, num_topics=25, id2word = dictionary5, passes=5)
ldamodel5.save('/tmp/CuModel_5.lda')


    

In [1]:

    

#****************************Test Version*********************************************************


import logging
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
logging.getLogger().setLevel(logging.INFO)

from gensim import corpora, models
from collections import defaultdict
import gensim
import Pyro4
    
class prob:
    slices = 0
    def __init__(self):
        self.twenty = []
        prob.slices += 1
    def __del__(self):
        prob.slices -= 1
class test:
    def __init__(self):
        self.box = []
def filtered(*args):
#removed word list    
    read_words = open('stopwords.txt', 'r')
    r_words = read_words.readline()
    #remove common words and tokenize
    stoplist = set(r_words.split())
    
    texts = [[word for word in document.lower().split() if word not in stoplist]
            for document in args]
    read_words.close()
    return texts
class iterator1:
    n1 = 0 
    def __init__(self):
        iterator1.n1+=1
    def delete(self):
        iterator1.n1 = 0 
class iterator2:
    n = 0 
    def __init__(self):
        iterator2.n+=1
    def delete(self):
        iterator2.n = 0 
#Outputs 20% side of the abstracts\n",
def outputfile(y): 
    num1 = iterator1()
    number1 = iterator1.n1
    file=open("cu_test_doc_"+str(number1)+".txt","w")
    for line in y:
        file.write(line)
    file.close()
    if number1 == 5:
        num1.delete()
#Create a file for each Directorate and Division 
def outputfile2(y): 
    num = iterator2()
    number = iterator2.n
    file=open("cu_test_dir_div_"+str(number)+".txt","w")    
    for line in y:
        file.write(line)
    file.close()
    if number == 5:
        num.delete()                
    
#Directorates and Divisions files
file = open('cu_doc_div.txt', 'r')
dd = file.readlines() 
    
#Download Abstracts\n",
file = open('cu_tigers.txt', 'r')
dictionary = file.readlines()
    
FSIZE = len(dictionary)
    
#split abstract lists length by 5 
t_split = FSIZE / 5
#variable to account for remainder if abstract list length is not evenly divisible by 5 
test_s = FSIZE % 5 
    
#round value to account for decimals 
r = round(t_split)
r1 = r*2
r2 = (r*2)+r
r3 = (r*4)
r4 = FSIZE
    
#Objects that hold the abstract array slices 
L20_1 = prob()
L20_2 = prob()
L20_3 = prob()
L20_4 = prob()
L20_5 = prob()
    
#Objects that hold the Directorate Division 20% groups 
L20_10 = prob()
L20_20 = prob()
L20_30 = prob()
L20_40 = prob()
L20_50 = prob()
    
#Holders for each group 
t80 = test()
t20 = test()
    
#20% abstract group storage (first 4)
l1 = L20_1.twenty = dictionary[:r]
l2 = L20_2.twenty = dictionary[r:r1]
l3 = L20_3.twenty = dictionary[r1:r2]
l4 = L20_4.twenty = dictionary[r2:r3]
l5 = L20_5.twenty = dictionary[r3:FSIZE]
    
#make files for 20% abstract groups 
outputfile(l1)
outputfile(l2)
outputfile(l3)
outputfile(l4)
outputfile(l5)
    
#20% Directorate Division group storage
d1 = L20_10.twenty = dd[:r] 
d2 = L20_20.twenty = dd[r:r1] 
d3 = L20_30.twenty = dd[r1:r2]
d4 = L20_40.twenty = dd[r2:r3]
d5 = L20_50.twenty = dd[r3:FSIZE]
    
#make files for 20% Directorate Division groups 
outputfile2(d1)
outputfile2(d2)
outputfile2(d3)
outputfile2(d4)
outputfile2(d5)
                
#********************Model Training*************************************

#t_file = open('topic_count.txt', 'r')
#t_count = t_file.read()
#TOPIC_COUNT = int(t_count)
    
#Comparison 1 arrangement, output test group into file, create: dictionary, corpus, lda model
t8a = t80.box = l2 + l3 + l4 + l5 

#80% group non duplicate storage
group_80_Topics = test()
gt8 = group_80_Topics.box

#80% group topic names 
c8 = test()
c8 = d2 + d3 + d4 + d5


#Store the 80% group topics 
for Topic in range(len(c8)):
    if c8[Topic] not in gt8:
        gt8.append(c8[Topic])

#All Directorates and Divisions 
file4=open("cu_doc_div3.txt","w")    
for lines in gt8:
    file4.write(lines)
file4.close()

#Get 80% group topic count 
TOPIC_COUNT = len(gt8)

#Output number of topics for later use 
file1=open("topic_count.txt","w")
file1.write(str(TOPIC_COUNT))
file1.close()

#create dictionary and filter abstract 
dictionary1 = corpora.Dictionary(filtered(*t8a))
dictionary1.save('/tmp/cu_dict1.dict')
   
#create corpus
corpus1 = [dictionary1.doc2bow(text) for text in filtered(*t8a)]#filter stop words and covert from document to bag of words
corpora.MmCorpus.serialize('/tmp/cu_corpus1.mm', corpus1)

#create model more passes have better results to an extent, but are more time consuming 
ldamodel1 = gensim.models.ldamulticore.LdaMulticore(corpus1, num_topics=TOPIC_COUNT, id2word = dictionary1, passes=20, workers=5, chunksize=10)
#ldamodel1 = gensim.models.ldamodel.LdaModel(corpus1, num_topics=TOPIC_COUNT, id2word = dictionary1, passes=40)
ldamodel1.save('/tmp/CuModel_1.lda')


    

    




INFO:gensim.utils:Pattern library is not installed, lemmatization won't be available.
INFO:gensim.corpora.sharded_corpus:Could not import Theano, will use standard float for default ShardedCorpus dtype.
INFO:summa.preprocessing.cleaner:'pattern' package not found; tag filters are not available for English
INFO:gensim.corpora.dictionary:adding document #0 to Dictionary(0 unique tokens: [])
INFO:gensim.corpora.dictionary:built Dictionary(5989 unique tokens: ['instilling', 'based-manufacturing', 'essentially', 'processing.', 'venue']...) from 78 documents (total 16269 corpus positions)
INFO:gensim.utils:saving Dictionary object under /tmp/cu_dict1.dict, separately None
INFO:gensim.corpora.mmcorpus:storing corpus in Matrix Market format to /tmp/cu_corpus1.mm
INFO:gensim.matutils:saving sparse matrix to /tmp/cu_corpus1.mm
INFO:gensim.matutils:PROGRESS: saving document #0
INFO:gensim.matutils:saved 78x5989 matrix, density=2.653% (12394/467142)
INFO:gensim.corpora.indexedcorpus:saving MmCorpus index to /tmp/cu_corpus1.mm.index
INFO:gensim.models.ldamodel:using symmetric alpha at 0.041666666666666664
INFO:gensim.models.ldamodel:using symmetric eta at 0.041666666666666664
INFO:gensim.models.ldamodel:using serial LDA version on this node
INFO:gensim.models.ldamulticore:running online LDA training, 24 topics, 20 passes over the supplied corpus of 78 documents, updating every 50 documents, evaluating every ~78 documents, iterating 50x with a convergence threshold of 0.001000
INFO:gensim.models.ldamulticore:training LDA model using 5 processes
INFO:gensim.models.ldamulticore:PROGRESS: pass 0, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 0, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 0, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 0, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 0, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 0, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 0, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 0, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #21 (0.042): 0.006*water + 0.006*development + 0.005*biological + 0.004*study + 0.004*sustainable + 0.004*environmental + 0.004*determine + 0.004*proposed + 0.004*np + 0.004*nps
INFO:gensim.models.ldamodel:topic #20 (0.042): 0.005*systems + 0.004*power + 0.003*highly + 0.003*data + 0.003*heterogeneous + 0.003*students + 0.003*hpc + 0.003*ice + 0.003*manufacturing + 0.003*nucleation
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.004*develop + 0.004*students + 0.004*engineering + 0.004*recommender + 0.003*development + 0.003*goal + 0.003*support + 0.003*team + 0.003*materials + 0.003*number
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.005*design + 0.005*power + 0.004*energy + 0.004*performance + 0.003*technology + 0.003*function + 0.003*engineering + 0.003*materials + 0.003*unique + 0.003*modeling
INFO:gensim.models.ldamodel:topic #15 (0.042): 0.007*data + 0.006*power + 0.005*students + 0.005*ejected + 0.004*systems + 0.004*ice + 0.004*particle + 0.003*graduate + 0.003*particles + 0.003*tools
INFO:gensim.models.ldamodel:topic diff=15.642468, rho=1.000000
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.004*students + 0.004*technology + 0.004*ambic + 0.003*graduate + 0.003*engineering + 0.003*infrastructure + 0.003*stem + 0.003*performance + 0.003*design + 0.002*data
INFO:gensim.models.ldamodel:topic #11 (0.042): 0.006*science + 0.005*education + 0.005*support + 0.005*students + 0.005*network + 0.005*faculty + 0.004*workshop + 0.004*development + 0.004*develop + 0.004*charging
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.004*students + 0.004*develop + 0.004*engineering + 0.003*materials + 0.003*different + 0.003*activities + 0.003*support + 0.003*team + 0.003*learning + 0.003*existing
INFO:gensim.models.ldamodel:topic #14 (0.042): 0.006*students + 0.004*program + 0.004*stem + 0.004*design + 0.003*development + 0.003*science + 0.003*learning + 0.003*graduate + 0.003*different + 0.003*engineering
INFO:gensim.models.ldamodel:topic #18 (0.042): 0.004*cyberbullying + 0.003*signals + 0.003*spaces + 0.003*mathematical + 0.003*theory, + 0.003*branges + 0.002*visual + 0.002*nature + 0.002*students + 0.002*function
INFO:gensim.models.ldamodel:topic diff=3.739151, rho=0.408248
INFO:gensim.models.ldamodel:-13.206 per-word bound, 9448.2 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 1, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 1, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 1, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 1, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 1, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 1, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 1, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 1, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 60 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.005*recommender + 0.005*develop + 0.004*students + 0.004*team + 0.004*activities + 0.003*systems + 0.003*support + 0.003*engineering + 0.003*existing + 0.003*materials
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.005*develop + 0.004*novel + 0.003*undergraduate + 0.003*graphene + 0.003*cell + 0.003*development + 0.003*graduate + 0.003*ion + 0.003*cells + 0.003*properties
INFO:gensim.models.ldamodel:topic #21 (0.042): 0.005*biological + 0.005*students + 0.005*study + 0.005*development + 0.004*guides + 0.004*environmental + 0.004*learning + 0.004*water + 0.004*determine + 0.004*develop
INFO:gensim.models.ldamodel:topic #5 (0.042): 0.004*students + 0.004*education + 0.004*design + 0.004*stem + 0.004*science + 0.003*process + 0.003*study + 0.003*different + 0.003*data + 0.003*lower
INFO:gensim.models.ldamodel:topic #17 (0.042): 0.005*disposal + 0.005*development + 0.005*graduate + 0.005*students + 0.004*methods + 0.004*infrastructure + 0.003*conference + 0.003*quantify + 0.003*life + 0.003*based
INFO:gensim.models.ldamodel:topic diff=0.973075, rho=0.319438
INFO:gensim.models.ldamodel:merging changes from 18 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.004*recommender + 0.004*develop + 0.003*students + 0.003*team + 0.003*activities + 0.003*systems + 0.003*support + 0.003*engineering + 0.002*existing + 0.002*materials
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.011*privacy + 0.010*origami + 0.008*network + 0.007*latency + 0.006*engineering + 0.006*develop + 0.006*students + 0.005*existing + 0.005*hpc + 0.005*computing
INFO:gensim.models.ldamodel:topic #19 (0.042): 0.008*membrane + 0.004*undergraduate + 0.004*novel + 0.004*develop + 0.004*fouling + 0.004*discovery + 0.003*geometric + 0.003*water + 0.003*surface + 0.003*students
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.010*infrastructure + 0.008*graduate + 0.007*students + 0.006*science + 0.006*training + 0.005*traineeship + 0.005*stem + 0.005*professionals + 0.005*societal + 0.004*award
INFO:gensim.models.ldamodel:topic #0 (0.042): 0.012*water + 0.009*extreme + 0.007*quality + 0.005*mercury + 0.004*urban + 0.004*implant + 0.004*flooding + 0.004*events + 0.004*materials + 0.003*data
INFO:gensim.models.ldamodel:topic diff=1.048357, rho=0.319438
INFO:gensim.models.ldamodel:-11.183 per-word bound, 2324.7 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 2, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 2, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 2, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 2, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 2, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 2, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 2, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 2, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #16 (0.042): 0.015*water + 0.006*distribution + 0.005*sustainability + 0.005*wireless + 0.005*monitoring + 0.005*sensing + 0.005*amulet + 0.004*detect + 0.004*potential + 0.004*schemes
INFO:gensim.models.ldamodel:topic #21 (0.042): 0.007*biological + 0.006*environmental + 0.006*study + 0.005*determine + 0.005*np + 0.005*nps + 0.005*np-protein + 0.005*develop + 0.004*identify + 0.004*water
INFO:gensim.models.ldamodel:topic #20 (0.042): 0.013*field + 0.009*students + 0.008*physical + 0.007*experiences + 0.006*effective + 0.006*learning + 0.006*reality + 0.006*related + 0.005*impact + 0.005*institutional
INFO:gensim.models.ldamodel:topic #2 (0.042): 0.009*heat + 0.008*mtbe + 0.006*microbial + 0.006*materials + 0.005*energy + 0.005*processing + 0.004*power + 0.004*temperature + 0.004*program + 0.004*undergraduate
INFO:gensim.models.ldamodel:topic #17 (0.042): 0.008*disposal + 0.007*development + 0.006*graduate + 0.006*methods + 0.005*students + 0.005*infrastructure + 0.005*quantify + 0.005*life + 0.004*contribute + 0.004*sustainable
INFO:gensim.models.ldamodel:topic diff=0.926823, rho=0.304290
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.011*infrastructure + 0.008*emerging + 0.007*simulation + 0.007*adaptive + 0.007*model + 0.007*preferences + 0.006*critical + 0.006*real-time + 0.006*human + 0.006*cognitive
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.009*infrastructure + 0.008*students + 0.008*ambic + 0.007*graduate + 0.007*science + 0.006*training + 0.006*stem + 0.006*biomanufacturing + 0.005*biopharmaceutical + 0.005*traineeship
INFO:gensim.models.ldamodel:topic #4 (0.042): 0.011*students + 0.011*program + 0.010*learning + 0.010*outcomes + 0.010*geoscience + 0.007*programs + 0.007*conference + 0.006*graduate + 0.005*participants + 0.005*current
INFO:gensim.models.ldamodel:topic #0 (0.042): 0.015*water + 0.013*mercury + 0.013*extreme + 0.009*coastal + 0.009*flooding + 0.008*carbon + 0.007*quality + 0.006*wetlands + 0.006*study + 0.006*events
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.011*privacy + 0.010*origami + 0.008*network + 0.007*latency + 0.007*engineering + 0.006*develop + 0.006*students + 0.006*hpc + 0.005*computing + 0.005*existing
INFO:gensim.models.ldamodel:topic diff=0.882466, rho=0.304290
INFO:gensim.models.ldamodel:-10.692 per-word bound, 1653.8 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 3, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 3, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 3, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 3, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 3, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 3, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 3, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 3, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #22 (0.042): 0.008*technology + 0.006*team + 0.005*cybersecurity + 0.005*data + 0.004*surface + 0.004*studies + 0.004*students + 0.004*homes + 0.004*number + 0.004*national
INFO:gensim.models.ldamodel:topic #4 (0.042): 0.016*students + 0.015*geoscience + 0.011*program + 0.010*conference + 0.009*graduate + 0.009*learning + 0.007*outcomes + 0.006*current + 0.005*programs + 0.005*participants
INFO:gensim.models.ldamodel:topic #10 (0.042): 0.015*grain + 0.015*steel + 0.009*computing + 0.009*size + 0.007*corrosion + 0.005*national + 0.005*concrete + 0.005*reinforcing + 0.005*consortium + 0.004*campuses
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.008*engineering + 0.008*privacy + 0.008*students + 0.007*origami + 0.007*network + 0.007*develop + 0.006*data + 0.005*system + 0.005*latency + 0.005*systems
INFO:gensim.models.ldamodel:topic #16 (0.042): 0.013*water + 0.010*sustainability + 0.008*amulet + 0.007*faculty + 0.006*courses + 0.006*stand-alone + 0.005*distribution + 0.005*engineering + 0.005*different + 0.004*wireless
INFO:gensim.models.ldamodel:topic diff=0.774321, rho=0.291111
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #13 (0.042): 0.011*microwave + 0.009*technology + 0.009*yeast + 0.008*internet + 0.007*design + 0.006*flow + 0.006*properties + 0.005*detection + 0.005*information + 0.005*based
INFO:gensim.models.ldamodel:topic #15 (0.042): 0.007*power + 0.007*ejected + 0.005*particle + 0.005*particles + 0.005*performance + 0.004*energy + 0.004*measurement + 0.004*aspect + 0.004*supports + 0.004*quality
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.009*students + 0.009*infrastructure + 0.009*ambic + 0.007*graduate + 0.007*science + 0.007*biomanufacturing + 0.007*stem + 0.006*training + 0.006*biopharmaceutical + 0.005*cell
INFO:gensim.models.ldamodel:topic #10 (0.042): 0.015*computing + 0.010*grain + 0.010*steel + 0.008*national + 0.008*consortium + 0.008*campuses + 0.006*size + 0.006*capabilities + 0.006*carc + 0.006*campus
INFO:gensim.models.ldamodel:topic #18 (0.042): 0.007*spaces + 0.006*signals + 0.006*mathematical + 0.006*branges + 0.006*theory, + 0.006*de + 0.005*x-ray + 0.005*theory + 0.005*when + 0.004*nature
INFO:gensim.models.ldamodel:topic diff=0.686908, rho=0.291111
INFO:gensim.models.ldamodel:-10.414 per-word bound, 1364.4 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 4, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 4, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 4, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 4, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 4, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 4, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 4, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 4, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.013*recommender + 0.008*systems + 0.007*develop + 0.006*system + 0.006*rssa + 0.005*team + 0.005*support + 0.004*unique + 0.004*benefit + 0.004*recommendations
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.008*infrastructure + 0.007*emerging + 0.006*develop + 0.006*critical + 0.005*human + 0.005*simulation + 0.005*adaptive + 0.005*model + 0.005*preferences + 0.005*real-time
INFO:gensim.models.ldamodel:topic #15 (0.042): 0.008*power + 0.008*ejected + 0.006*particle + 0.006*particles + 0.005*performance + 0.005*energy + 0.005*measurement + 0.004*aspect + 0.004*supports + 0.004*quality
INFO:gensim.models.ldamodel:topic #14 (0.042): 0.012*stem + 0.006*grades + 0.005*affect + 0.005*highly + 0.005*polymer + 0.005*noyce + 0.005*clemson + 0.004*students + 0.004*graphene + 0.004*work
INFO:gensim.models.ldamodel:topic #11 (0.042): 0.010*science + 0.008*education + 0.007*network + 0.007*students + 0.006*development + 0.006*anions + 0.006*support + 0.005*security + 0.005*charging + 0.005*faculty
INFO:gensim.models.ldamodel:topic diff=0.602822, rho=0.279508
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #14 (0.042): 0.008*stem + 0.007*affect + 0.006*protein + 0.006*phases + 0.006*separations + 0.005*clemson + 0.005*area + 0.005*commercial + 0.005*purification + 0.005*ligands
INFO:gensim.models.ldamodel:topic #16 (0.042): 0.016*sustainability + 0.012*amulet + 0.010*faculty + 0.009*courses + 0.009*stand-alone + 0.007*engineering + 0.007*water + 0.007*different + 0.006*mhealth + 0.006*technology
INFO:gensim.models.ldamodel:topic #4 (0.042): 0.013*program + 0.012*outcomes + 0.012*learning + 0.011*students + 0.010*geoscience + 0.010*programs + 0.006*observational + 0.006*participants + 0.006*conference + 0.006*participant
INFO:gensim.models.ldamodel:topic #22 (0.042): 0.010*technology + 0.008*team + 0.007*cybersecurity + 0.007*data + 0.005*homes + 0.005*studies + 0.005*existing + 0.005*network + 0.005*number + 0.004*researchers
INFO:gensim.models.ldamodel:topic #0 (0.042): 0.018*mercury + 0.016*water + 0.015*extreme + 0.013*coastal + 0.013*carbon + 0.011*flooding + 0.010*wetlands + 0.008*study + 0.007*blackwater + 0.007*organic
INFO:gensim.models.ldamodel:topic diff=0.507316, rho=0.279508
INFO:gensim.models.ldamodel:-10.277 per-word bound, 1240.4 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 5, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #0 (0.042): 0.017*water + 0.013*extreme + 0.013*mercury + 0.010*quality + 0.009*carbon + 0.009*coastal + 0.009*flooding + 0.008*implant + 0.007*materials + 0.007*wetlands
INFO:gensim.models.ldamodel:topic #20 (0.042): 0.019*field + 0.012*physical + 0.012*students + 0.010*experiences + 0.008*effective + 0.008*learning + 0.008*reality + 0.007*related + 0.006*impact + 0.006*world
INFO:gensim.models.ldamodel:topic #11 (0.042): 0.010*science + 0.008*education + 0.007*network + 0.007*students + 0.006*anions + 0.006*development + 0.006*support + 0.005*security + 0.005*charging + 0.005*faculty
INFO:gensim.models.ldamodel:topic #18 (0.042): 0.009*spaces + 0.008*signals + 0.008*mathematical + 0.008*branges + 0.008*theory, + 0.008*de + 0.007*x-ray + 0.006*theory + 0.006*when + 0.005*nature
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.008*infrastructure + 0.008*emerging + 0.006*develop + 0.006*critical + 0.006*human + 0.005*simulation + 0.005*adaptive + 0.005*model + 0.005*preferences + 0.005*real-time
INFO:gensim.models.ldamodel:topic diff=0.446260, rho=0.269191
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #22 (0.042): 0.010*technology + 0.008*team + 0.007*cybersecurity + 0.007*data + 0.005*homes + 0.005*studies + 0.005*existing + 0.005*network + 0.005*number + 0.004*materials
INFO:gensim.models.ldamodel:topic #7 (0.042): 0.018*cyberbullying + 0.009*social + 0.009*visual + 0.008*engineering + 0.008*systems + 0.007*workshop + 0.005*automatic + 0.005*mobile + 0.005*design + 0.004*identify
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.011*infrastructure + 0.009*emerging + 0.007*simulation + 0.007*adaptive + 0.007*model + 0.007*preferences + 0.007*critical + 0.007*human + 0.006*real-time + 0.006*cognitive
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.011*recommender + 0.007*systems + 0.006*develop + 0.006*system + 0.006*rssa + 0.004*team + 0.004*support + 0.004*unique + 0.004*benefit + 0.004*recommendations
INFO:gensim.models.ldamodel:topic #1 (0.042): 0.008*development + 0.006*multimodal + 0.005*information + 0.005*students + 0.004*undergraduate + 0.004*work + 0.004*sensors + 0.004*tactons + 0.004*means + 0.004*based
INFO:gensim.models.ldamodel:topic diff=0.363230, rho=0.269191
INFO:gensim.models.ldamodel:-10.213 per-word bound, 1187.3 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 6, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.008*infrastructure + 0.008*emerging + 0.007*critical + 0.006*develop + 0.006*human + 0.005*simulation + 0.005*adaptive + 0.005*model + 0.005*preferences + 0.005*real-time
INFO:gensim.models.ldamodel:topic #7 (0.042): 0.022*cyberbullying + 0.011*social + 0.011*visual + 0.009*engineering + 0.009*systems + 0.008*workshop + 0.006*automatic + 0.006*mobile + 0.006*design + 0.005*identify
INFO:gensim.models.ldamodel:topic #0 (0.042): 0.017*water + 0.014*mercury + 0.013*extreme + 0.010*carbon + 0.010*coastal + 0.009*quality + 0.009*flooding + 0.008*implant + 0.007*wetlands + 0.007*materials
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.014*recommender + 0.009*systems + 0.007*develop + 0.007*system + 0.007*rssa + 0.005*team + 0.005*support + 0.005*unique + 0.005*benefit + 0.005*recommendations
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.008*engineering + 0.008*privacy + 0.008*students + 0.008*origami + 0.007*network + 0.007*develop + 0.006*hpc + 0.006*data + 0.006*systems + 0.006*system
INFO:gensim.models.ldamodel:topic diff=0.325694, rho=0.259938
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #15 (0.042): 0.007*power + 0.007*ejected + 0.005*particle + 0.005*particles + 0.005*performance + 0.005*energy + 0.004*measurement + 0.004*aspect + 0.004*supports + 0.004*home+
INFO:gensim.models.ldamodel:topic #1 (0.042): 0.008*development + 0.006*multimodal + 0.005*information + 0.005*students + 0.004*undergraduate + 0.004*work + 0.004*sensors + 0.004*tactons + 0.004*means + 0.004*vnc
INFO:gensim.models.ldamodel:topic #16 (0.042): 0.016*sustainability + 0.012*amulet + 0.010*faculty + 0.009*courses + 0.009*stand-alone + 0.008*engineering + 0.007*different + 0.007*water + 0.006*mhealth + 0.006*technology
INFO:gensim.models.ldamodel:topic #0 (0.042): 0.019*mercury + 0.016*water + 0.015*extreme + 0.014*carbon + 0.013*coastal + 0.012*flooding + 0.010*wetlands + 0.009*study + 0.008*organic + 0.008*blackwater
INFO:gensim.models.ldamodel:topic #20 (0.042): 0.023*field + 0.014*physical + 0.014*students + 0.013*experiences + 0.010*effective + 0.010*learning + 0.010*reality + 0.008*related + 0.008*impact + 0.008*world
INFO:gensim.models.ldamodel:topic diff=0.261891, rho=0.259938
INFO:gensim.models.ldamodel:-10.186 per-word bound, 1164.7 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 7, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #20 (0.042): 0.020*field + 0.013*physical + 0.012*students + 0.011*experiences + 0.009*effective + 0.009*learning + 0.009*reality + 0.007*related + 0.007*impact + 0.007*world
INFO:gensim.models.ldamodel:topic #13 (0.042): 0.010*technology + 0.009*design + 0.009*microwave + 0.007*ice + 0.007*yeast + 0.007*material + 0.006*internet + 0.006*students + 0.005*detection + 0.005*nucleation
INFO:gensim.models.ldamodel:topic #5 (0.042): 0.013*process + 0.007*uv + 0.007*biobased + 0.006*study + 0.006*lower + 0.006*long-term + 0.006*thermospheric + 0.006*investigate + 0.006*curing + 0.006*scale-up
INFO:gensim.models.ldamodel:topic #17 (0.042): 0.011*disposal + 0.009*development + 0.008*graduate + 0.008*methods + 0.006*infrastructure + 0.006*quantify + 0.006*life + 0.006*contribute + 0.006*sustainable + 0.006*environmental
INFO:gensim.models.ldamodel:topic #19 (0.042): 0.012*membrane + 0.007*fouling + 0.007*voc + 0.006*discovery + 0.006*undergraduate + 0.006*geometric + 0.006*water + 0.006*surface + 0.005*body + 0.005*robots
INFO:gensim.models.ldamodel:topic diff=0.242570, rho=0.251577
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #20 (0.042): 0.023*field + 0.014*physical + 0.014*students + 0.013*experiences + 0.010*effective + 0.010*learning + 0.010*reality + 0.008*related + 0.008*impact + 0.008*world
INFO:gensim.models.ldamodel:topic #10 (0.042): 0.019*computing + 0.012*grain + 0.012*steel + 0.010*national + 0.009*consortium + 0.009*campuses + 0.008*size + 0.007*capabilities + 0.007*carc + 0.007*campus
INFO:gensim.models.ldamodel:topic #23 (0.042): 0.014*lab + 0.011*space + 0.007*support + 0.007*activities + 0.007*design + 0.007*major + 0.007*landscape + 0.007*faculty + 0.007*workspace + 0.007*screened
INFO:gensim.models.ldamodel:topic #5 (0.042): 0.013*process + 0.006*uv + 0.006*biobased + 0.005*to, + 0.005*study + 0.005*lower + 0.005*long-term + 0.005*thermospheric + 0.005*investigate + 0.005*curing
INFO:gensim.models.ldamodel:topic #6 (0.042): 0.008*market + 0.008*biologics + 0.008*design + 0.008*product + 0.008*membrane + 0.008*capacity + 0.007*function + 0.007*modeling + 0.006*production + 0.006*business
INFO:gensim.models.ldamodel:topic diff=0.197046, rho=0.251577
INFO:gensim.models.ldamodel:-10.174 per-word bound, 1155.3 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 8, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #18 (0.042): 0.009*spaces + 0.008*signals + 0.008*mathematical + 0.008*branges + 0.008*theory, + 0.008*de + 0.008*x-ray + 0.006*theory + 0.006*when + 0.006*membrane
INFO:gensim.models.ldamodel:topic #15 (0.042): 0.008*power + 0.008*ejected + 0.006*particle + 0.006*particles + 0.006*performance + 0.005*energy + 0.005*measurement + 0.005*aspect + 0.005*home+ + 0.005*model
INFO:gensim.models.ldamodel:topic #10 (0.042): 0.016*grain + 0.016*steel + 0.015*computing + 0.011*size + 0.008*corrosion + 0.008*national + 0.007*consortium + 0.007*campuses + 0.006*capabilities + 0.006*carc
INFO:gensim.models.ldamodel:topic #11 (0.042): 0.010*science + 0.008*education + 0.007*students + 0.007*network + 0.006*development + 0.006*anions + 0.006*support + 0.006*security + 0.005*charging + 0.005*faculty
INFO:gensim.models.ldamodel:topic #0 (0.042): 0.016*water + 0.015*mercury + 0.014*extreme + 0.011*carbon + 0.010*coastal + 0.010*flooding + 0.009*quality + 0.008*implant + 0.008*wetlands + 0.007*study
INFO:gensim.models.ldamodel:topic diff=0.189263, rho=0.243975
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #21 (0.042): 0.011*guides + 0.011*learning + 0.011*students + 0.007*logical + 0.007*reasoning + 0.006*help + 0.006*develop + 0.006*biological + 0.006*environmental + 0.005*engineering
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.011*infrastructure + 0.009*emerging + 0.007*critical + 0.007*simulation + 0.007*adaptive + 0.007*model + 0.007*preferences + 0.007*human + 0.006*real-time + 0.006*cognitive
INFO:gensim.models.ldamodel:topic #18 (0.042): 0.008*spaces + 0.007*signals + 0.007*mathematical + 0.007*branges + 0.007*theory, + 0.007*de + 0.007*x-ray + 0.006*theory + 0.005*when + 0.005*membrane
INFO:gensim.models.ldamodel:topic #2 (0.042): 0.010*heat + 0.009*mtbe + 0.007*microbial + 0.006*materials + 0.006*energy + 0.006*processing + 0.005*power + 0.005*temperature + 0.004*program + 0.004*devices
INFO:gensim.models.ldamodel:topic #7 (0.042): 0.019*cyberbullying + 0.010*social + 0.010*visual + 0.008*engineering + 0.008*systems + 0.007*workshop + 0.006*automatic + 0.006*mobile + 0.006*design + 0.004*identify
INFO:gensim.models.ldamodel:topic diff=0.158744, rho=0.243975
INFO:gensim.models.ldamodel:-10.169 per-word bound, 1151.7 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 9, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #13 (0.042): 0.010*technology + 0.009*design + 0.009*microwave + 0.007*ice + 0.007*yeast + 0.007*material + 0.006*internet + 0.006*students + 0.006*detection + 0.005*nucleation
INFO:gensim.models.ldamodel:topic #4 (0.042): 0.015*students + 0.013*geoscience + 0.012*program + 0.011*learning + 0.011*outcomes + 0.009*programs + 0.009*conference + 0.008*graduate + 0.006*participants + 0.006*current
INFO:gensim.models.ldamodel:topic #7 (0.042): 0.022*cyberbullying + 0.011*social + 0.011*visual + 0.009*engineering + 0.009*systems + 0.008*workshop + 0.006*automatic + 0.006*mobile + 0.006*design + 0.005*identify
INFO:gensim.models.ldamodel:topic #14 (0.042): 0.012*stem + 0.007*protein + 0.006*grades + 0.006*affect + 0.005*purification + 0.005*highly + 0.005*performance + 0.005*clemson + 0.005*phases + 0.005*separations
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.008*privacy + 0.008*engineering + 0.008*origami + 0.008*students + 0.007*network + 0.007*hpc + 0.007*develop + 0.006*systems + 0.006*data + 0.006*system
INFO:gensim.models.ldamodel:topic diff=0.156744, rho=0.237023
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #1 (0.042): 0.008*development + 0.006*multimodal + 0.005*information + 0.005*students + 0.004*work + 0.004*undergraduate + 0.004*tactons + 0.004*means + 0.004*vnc + 0.004*sensors
INFO:gensim.models.ldamodel:topic #10 (0.042): 0.019*computing + 0.012*grain + 0.012*steel + 0.010*national + 0.009*consortium + 0.009*campuses + 0.008*size + 0.007*capabilities + 0.007*carc + 0.007*campus
INFO:gensim.models.ldamodel:topic #15 (0.042): 0.008*power + 0.008*ejected + 0.005*particle + 0.005*particles + 0.005*performance + 0.005*energy + 0.004*measurement + 0.004*home+ + 0.004*model + 0.004*aspect
INFO:gensim.models.ldamodel:topic #17 (0.042): 0.009*disposal + 0.008*development + 0.007*graduate + 0.007*methods + 0.005*infrastructure + 0.005*quantify + 0.005*life + 0.005*contribute + 0.005*sustainable + 0.005*environmental
INFO:gensim.models.ldamodel:topic #4 (0.042): 0.013*outcomes + 0.013*program + 0.012*learning + 0.011*students + 0.011*programs + 0.010*geoscience + 0.007*study + 0.007*observational + 0.007*participant + 0.007*informal
INFO:gensim.models.ldamodel:topic diff=0.137526, rho=0.237023
INFO:gensim.models.ldamodel:-10.168 per-word bound, 1150.5 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 10, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #18 (0.042): 0.009*spaces + 0.008*signals + 0.008*mathematical + 0.008*branges + 0.008*theory, + 0.008*de + 0.008*x-ray + 0.006*theory + 0.006*when + 0.006*membrane
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.011*students + 0.010*ambic + 0.008*infrastructure + 0.008*graduate + 0.007*biomanufacturing + 0.007*training + 0.007*science + 0.006*stem + 0.006*biopharmaceutical + 0.005*development
INFO:gensim.models.ldamodel:topic #22 (0.042): 0.010*technology + 0.007*team + 0.006*cybersecurity + 0.006*data + 0.005*homes + 0.005*number + 0.005*studies + 0.004*existing + 0.004*national + 0.004*surface
INFO:gensim.models.ldamodel:topic #15 (0.042): 0.008*power + 0.008*ejected + 0.006*particle + 0.006*particles + 0.006*performance + 0.005*energy + 0.005*measurement + 0.005*home+ + 0.005*model + 0.005*furnishings
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.014*recommender + 0.010*systems + 0.007*develop + 0.007*system + 0.007*rssa + 0.005*team + 0.005*support + 0.005*unique + 0.005*benefit + 0.005*recommendations
INFO:gensim.models.ldamodel:topic diff=0.137019, rho=0.230633
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #15 (0.042): 0.008*power + 0.008*ejected + 0.005*particle + 0.005*particles + 0.005*performance + 0.005*energy + 0.004*measurement + 0.004*home+ + 0.004*model + 0.004*furnishings
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.011*infrastructure + 0.009*emerging + 0.007*critical + 0.007*human + 0.007*simulation + 0.007*adaptive + 0.007*model + 0.007*preferences + 0.006*real-time + 0.006*cognitive
INFO:gensim.models.ldamodel:topic #11 (0.042): 0.010*science + 0.009*education + 0.008*network + 0.007*students + 0.006*anions + 0.006*security + 0.006*charging + 0.006*development + 0.005*support + 0.005*faculty
INFO:gensim.models.ldamodel:topic #22 (0.042): 0.011*technology + 0.008*team + 0.007*cybersecurity + 0.007*data + 0.005*homes + 0.005*studies + 0.005*existing + 0.005*number + 0.005*network + 0.004*materials
INFO:gensim.models.ldamodel:topic #6 (0.042): 0.009*market + 0.009*biologics + 0.008*design + 0.008*product + 0.008*membrane + 0.008*capacity + 0.007*function + 0.007*modeling + 0.006*production + 0.006*business
INFO:gensim.models.ldamodel:topic diff=0.125457, rho=0.230633
INFO:gensim.models.ldamodel:-10.168 per-word bound, 1150.4 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 11, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #20 (0.042): 0.020*field + 0.013*physical + 0.012*students + 0.011*experiences + 0.009*effective + 0.009*learning + 0.009*reality + 0.007*related + 0.007*impact + 0.007*world
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.012*students + 0.010*ambic + 0.008*infrastructure + 0.008*graduate + 0.007*biomanufacturing + 0.007*training + 0.007*science + 0.006*stem + 0.006*biopharmaceutical + 0.006*development
INFO:gensim.models.ldamodel:topic #10 (0.042): 0.016*grain + 0.016*steel + 0.015*computing + 0.011*size + 0.008*corrosion + 0.008*national + 0.008*consortium + 0.008*campuses + 0.006*analytical + 0.006*capabilities
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.008*privacy + 0.008*engineering + 0.008*origami + 0.007*students + 0.007*network + 0.007*hpc + 0.007*develop + 0.007*systems + 0.006*data + 0.006*system
INFO:gensim.models.ldamodel:topic #4 (0.042): 0.015*students + 0.013*geoscience + 0.012*program + 0.011*learning + 0.011*outcomes + 0.009*programs + 0.008*conference + 0.007*graduate + 0.006*study + 0.006*participants
INFO:gensim.models.ldamodel:topic diff=0.124823, rho=0.224733
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #16 (0.042): 0.016*sustainability + 0.012*amulet + 0.010*faculty + 0.009*courses + 0.009*stand-alone + 0.008*water + 0.007*engineering + 0.007*different + 0.006*mhealth + 0.006*technology
INFO:gensim.models.ldamodel:topic #18 (0.042): 0.008*spaces + 0.007*signals + 0.007*mathematical + 0.007*branges + 0.007*theory, + 0.007*de + 0.007*x-ray + 0.006*theory + 0.006*when + 0.005*membrane
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.012*students + 0.010*ambic + 0.009*infrastructure + 0.008*graduate + 0.008*biomanufacturing + 0.007*science + 0.007*training + 0.007*stem + 0.006*biopharmaceutical + 0.006*cell
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.010*privacy + 0.010*origami + 0.008*network + 0.008*hpc + 0.007*engineering + 0.007*latency + 0.007*develop + 0.006*computing + 0.006*students + 0.005*variation
INFO:gensim.models.ldamodel:topic #21 (0.042): 0.011*guides + 0.011*learning + 0.011*students + 0.007*logical + 0.007*reasoning + 0.006*help + 0.006*develop + 0.006*biological + 0.006*environmental + 0.005*engineering
INFO:gensim.models.ldamodel:topic diff=0.117972, rho=0.224733
INFO:gensim.models.ldamodel:-10.168 per-word bound, 1150.8 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 12, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.012*students + 0.010*ambic + 0.008*infrastructure + 0.008*graduate + 0.007*biomanufacturing + 0.007*training + 0.007*science + 0.006*stem + 0.006*biopharmaceutical + 0.006*development
INFO:gensim.models.ldamodel:topic #1 (0.042): 0.009*development + 0.007*multimodal + 0.006*information + 0.006*students + 0.005*work + 0.005*tactons + 0.005*means + 0.005*vnc + 0.005*detection + 0.005*undergraduate
INFO:gensim.models.ldamodel:topic #16 (0.042): 0.014*sustainability + 0.011*water + 0.010*amulet + 0.009*faculty + 0.008*courses + 0.008*stand-alone + 0.006*engineering + 0.006*different + 0.005*mhealth + 0.005*technology
INFO:gensim.models.ldamodel:topic #7 (0.042): 0.022*cyberbullying + 0.011*social + 0.011*visual + 0.009*engineering + 0.009*systems + 0.008*workshop + 0.006*automatic + 0.006*mobile + 0.006*design + 0.005*identify
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.008*privacy + 0.008*engineering + 0.008*origami + 0.007*students + 0.007*hpc + 0.007*network + 0.007*develop + 0.007*systems + 0.006*data + 0.006*system
INFO:gensim.models.ldamodel:topic diff=0.116941, rho=0.219265
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #1 (0.042): 0.008*development + 0.006*multimodal + 0.005*information + 0.005*students + 0.004*work + 0.004*tactons + 0.004*means + 0.004*vnc + 0.004*detection + 0.004*undergraduate
INFO:gensim.models.ldamodel:topic #2 (0.042): 0.010*heat + 0.009*mtbe + 0.007*microbial + 0.006*materials + 0.006*processing + 0.006*energy + 0.005*power + 0.005*temperature + 0.004*program + 0.004*devices
INFO:gensim.models.ldamodel:topic #6 (0.042): 0.009*biologics + 0.009*market + 0.008*design + 0.008*product + 0.008*membrane + 0.008*capacity + 0.007*function + 0.007*modeling + 0.006*production + 0.006*business
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.012*students + 0.010*ambic + 0.009*infrastructure + 0.008*graduate + 0.008*biomanufacturing + 0.007*science + 0.007*training + 0.007*stem + 0.006*biopharmaceutical + 0.006*cell
INFO:gensim.models.ldamodel:topic #21 (0.042): 0.011*guides + 0.011*learning + 0.011*students + 0.007*logical + 0.007*reasoning + 0.006*help + 0.006*develop + 0.006*biological + 0.006*environmental + 0.005*engineering
INFO:gensim.models.ldamodel:topic diff=0.112789, rho=0.219265
INFO:gensim.models.ldamodel:-10.169 per-word bound, 1151.4 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 13, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #19 (0.042): 0.012*membrane + 0.007*fouling + 0.007*voc + 0.006*discovery + 0.006*undergraduate + 0.006*geometric + 0.006*water + 0.006*surface + 0.006*body + 0.006*robots
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.008*privacy + 0.008*engineering + 0.008*origami + 0.007*hpc + 0.007*network + 0.007*students + 0.007*develop + 0.007*systems + 0.006*data + 0.006*system
INFO:gensim.models.ldamodel:topic #7 (0.042): 0.022*cyberbullying + 0.011*social + 0.011*visual + 0.009*engineering + 0.009*systems + 0.008*workshop + 0.006*automatic + 0.006*mobile + 0.006*design + 0.005*identify
INFO:gensim.models.ldamodel:topic #21 (0.042): 0.009*students + 0.008*guides + 0.008*learning + 0.007*biological + 0.007*environmental + 0.006*develop + 0.006*study + 0.006*determine + 0.006*np + 0.006*nps
INFO:gensim.models.ldamodel:topic #2 (0.042): 0.011*heat + 0.010*mtbe + 0.007*microbial + 0.006*materials + 0.006*processing + 0.006*energy + 0.005*power + 0.005*temperature + 0.004*program + 0.004*devices
INFO:gensim.models.ldamodel:topic diff=0.111507, rho=0.214176
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #2 (0.042): 0.010*heat + 0.009*mtbe + 0.007*microbial + 0.006*materials + 0.006*processing + 0.006*energy + 0.005*power + 0.005*temperature + 0.004*program + 0.004*devices
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.012*recommender + 0.008*systems + 0.006*develop + 0.006*system + 0.006*rssa + 0.004*team + 0.004*support + 0.004*unique + 0.004*benefit + 0.004*recommendations
INFO:gensim.models.ldamodel:topic #13 (0.042): 0.011*microwave + 0.011*technology + 0.009*yeast + 0.008*internet + 0.007*design + 0.006*detection + 0.006*flow + 0.006*properties + 0.006*based + 0.005*ice
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.010*privacy + 0.010*origami + 0.008*network + 0.008*hpc + 0.007*engineering + 0.007*latency + 0.007*develop + 0.006*computing + 0.006*students + 0.005*variation
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.011*infrastructure + 0.009*emerging + 0.007*critical + 0.007*human + 0.007*simulation + 0.007*adaptive + 0.007*model + 0.007*preferences + 0.006*real-time + 0.006*cognitive
INFO:gensim.models.ldamodel:topic diff=0.108809, rho=0.214176
INFO:gensim.models.ldamodel:-10.170 per-word bound, 1152.2 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 14, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #14 (0.042): 0.011*stem + 0.008*protein + 0.006*purification + 0.006*performance + 0.006*grades + 0.006*affect + 0.005*potential + 0.005*highly + 0.005*clemson + 0.005*phases
INFO:gensim.models.ldamodel:topic #7 (0.042): 0.022*cyberbullying + 0.011*social + 0.011*visual + 0.009*engineering + 0.009*systems + 0.008*workshop + 0.006*automatic + 0.006*mobile + 0.006*design + 0.005*identify
INFO:gensim.models.ldamodel:topic #6 (0.042): 0.009*design + 0.008*function + 0.008*modeling + 0.008*market + 0.008*product + 0.008*biologics + 0.007*production + 0.007*membrane + 0.007*capacity + 0.006*patterns
INFO:gensim.models.ldamodel:topic #2 (0.042): 0.011*heat + 0.010*mtbe + 0.007*microbial + 0.006*processing + 0.006*materials + 0.006*energy + 0.005*power + 0.005*temperature + 0.004*program + 0.004*devices
INFO:gensim.models.ldamodel:topic #22 (0.042): 0.010*technology + 0.007*team + 0.006*cybersecurity + 0.006*data + 0.005*homes + 0.005*number + 0.005*studies + 0.005*existing + 0.004*national + 0.004*surface
INFO:gensim.models.ldamodel:topic diff=0.107443, rho=0.209427
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #22 (0.042): 0.011*technology + 0.008*team + 0.007*cybersecurity + 0.007*data + 0.005*homes + 0.005*studies + 0.005*existing + 0.005*number + 0.005*network + 0.004*materials
INFO:gensim.models.ldamodel:topic #20 (0.042): 0.023*field + 0.014*physical + 0.014*students + 0.013*experiences + 0.010*effective + 0.010*learning + 0.010*reality + 0.008*related + 0.008*impact + 0.008*world
INFO:gensim.models.ldamodel:topic #15 (0.042): 0.008*power + 0.008*ejected + 0.005*particle + 0.005*particles + 0.005*performance + 0.005*energy + 0.004*measurement + 0.004*home+ + 0.004*model + 0.004*furnishings
INFO:gensim.models.ldamodel:topic #5 (0.042): 0.014*process + 0.007*uv + 0.007*biobased + 0.006*to, + 0.005*study + 0.005*lower + 0.005*long-term + 0.005*thermospheric + 0.005*curing + 0.005*scale-up
INFO:gensim.models.ldamodel:topic #17 (0.042): 0.010*disposal + 0.008*development + 0.007*graduate + 0.007*methods + 0.005*infrastructure + 0.005*quantify + 0.005*life + 0.005*contribute + 0.005*sustainable + 0.005*environmental
INFO:gensim.models.ldamodel:topic diff=0.105516, rho=0.209427
INFO:gensim.models.ldamodel:-10.171 per-word bound, 1153.0 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 15, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #19 (0.042): 0.012*membrane + 0.007*fouling + 0.007*voc + 0.006*discovery + 0.006*undergraduate + 0.006*geometric + 0.006*water + 0.006*surface + 0.006*body + 0.006*robots
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.008*privacy + 0.008*engineering + 0.008*origami + 0.007*hpc + 0.007*network + 0.007*students + 0.007*develop + 0.007*systems + 0.006*data + 0.006*latency
INFO:gensim.models.ldamodel:topic #10 (0.042): 0.016*grain + 0.016*steel + 0.015*computing + 0.011*size + 0.008*corrosion + 0.008*national + 0.008*consortium + 0.008*campuses + 0.007*analytical + 0.006*novel
INFO:gensim.models.ldamodel:topic #16 (0.042): 0.014*sustainability + 0.011*water + 0.010*amulet + 0.009*faculty + 0.008*courses + 0.008*stand-alone + 0.006*engineering + 0.006*different + 0.005*mhealth + 0.005*technology
INFO:gensim.models.ldamodel:topic #4 (0.042): 0.015*students + 0.013*geoscience + 0.012*program + 0.011*learning + 0.011*outcomes + 0.010*programs + 0.008*conference + 0.007*graduate + 0.007*study + 0.006*participants
INFO:gensim.models.ldamodel:topic diff=0.104130, rho=0.204980
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #5 (0.042): 0.014*process + 0.007*uv + 0.007*biobased + 0.006*to, + 0.005*study + 0.005*lower + 0.005*long-term + 0.005*thermospheric + 0.005*curing + 0.005*scale-up
INFO:gensim.models.ldamodel:topic #17 (0.042): 0.010*disposal + 0.008*development + 0.007*graduate + 0.007*methods + 0.006*infrastructure + 0.006*quantify + 0.006*life + 0.006*contribute + 0.006*sustainable + 0.005*environmental
INFO:gensim.models.ldamodel:topic #14 (0.042): 0.010*protein + 0.009*stem + 0.008*purification + 0.007*performance + 0.007*affect + 0.006*potential + 0.006*phases + 0.006*separations + 0.006*column + 0.006*commercial
INFO:gensim.models.ldamodel:topic #20 (0.042): 0.023*field + 0.014*physical + 0.014*students + 0.013*experiences + 0.010*effective + 0.010*learning + 0.010*reality + 0.008*related + 0.008*impact + 0.008*world
INFO:gensim.models.ldamodel:topic #3 (0.042): 0.010*privacy + 0.010*origami + 0.008*network + 0.008*hpc + 0.007*engineering + 0.007*latency + 0.007*develop + 0.006*computing + 0.006*students + 0.005*variation
INFO:gensim.models.ldamodel:topic diff=0.102652, rho=0.204980
INFO:gensim.models.ldamodel:-10.172 per-word bound, 1153.9 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 16, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #19 (0.042): 0.012*membrane + 0.007*fouling + 0.007*voc + 0.006*discovery + 0.006*undergraduate + 0.006*geometric + 0.006*water + 0.006*surface + 0.006*body + 0.006*robots
INFO:gensim.models.ldamodel:topic #11 (0.042): 0.010*science + 0.008*education + 0.007*students + 0.007*network + 0.006*development + 0.006*anions + 0.006*security + 0.006*support + 0.005*charging + 0.005*faculty
INFO:gensim.models.ldamodel:topic #4 (0.042): 0.015*students + 0.013*geoscience + 0.012*program + 0.011*learning + 0.011*outcomes + 0.010*programs + 0.008*conference + 0.007*graduate + 0.007*study + 0.006*participants
INFO:gensim.models.ldamodel:topic #15 (0.042): 0.008*power + 0.008*ejected + 0.006*particle + 0.006*particles + 0.006*performance + 0.005*energy + 0.005*measurement + 0.005*home+ + 0.005*model + 0.005*furnishings
INFO:gensim.models.ldamodel:topic #23 (0.042): 0.012*lab + 0.010*space + 0.006*carolina + 0.006*support + 0.006*activities + 0.006*design + 0.006*major + 0.006*landscape + 0.006*faculty + 0.006*workspace
INFO:gensim.models.ldamodel:topic diff=0.101291, rho=0.200805
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #22 (0.042): 0.011*technology + 0.008*team + 0.007*cybersecurity + 0.007*data + 0.005*homes + 0.005*studies + 0.005*existing + 0.005*number + 0.005*network + 0.004*materials
INFO:gensim.models.ldamodel:topic #2 (0.042): 0.010*heat + 0.009*mtbe + 0.007*microbial + 0.006*processing + 0.006*materials + 0.006*energy + 0.005*power + 0.005*temperature + 0.004*program + 0.004*devices
INFO:gensim.models.ldamodel:topic #0 (0.042): 0.019*mercury + 0.016*water + 0.015*extreme + 0.014*carbon + 0.013*coastal + 0.012*flooding + 0.010*wetlands + 0.009*study + 0.008*organic + 0.007*blackwater
INFO:gensim.models.ldamodel:topic #20 (0.042): 0.023*field + 0.014*physical + 0.014*students + 0.013*experiences + 0.010*effective + 0.010*learning + 0.010*reality + 0.008*related + 0.008*impact + 0.008*world
INFO:gensim.models.ldamodel:topic #10 (0.042): 0.018*computing + 0.012*grain + 0.012*steel + 0.009*national + 0.009*consortium + 0.009*campuses + 0.008*size + 0.007*capabilities + 0.007*carc + 0.007*campus
INFO:gensim.models.ldamodel:topic diff=0.100084, rho=0.200805
INFO:gensim.models.ldamodel:-10.173 per-word bound, 1154.8 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 17, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #7 (0.042): 0.022*cyberbullying + 0.011*social + 0.011*visual + 0.009*engineering + 0.009*systems + 0.008*workshop + 0.006*automatic + 0.006*mobile + 0.006*design + 0.005*identify
INFO:gensim.models.ldamodel:topic #2 (0.042): 0.011*heat + 0.010*mtbe + 0.007*microbial + 0.007*processing + 0.006*materials + 0.006*energy + 0.005*power + 0.005*temperature + 0.004*program + 0.004*devices
INFO:gensim.models.ldamodel:topic #15 (0.042): 0.008*power + 0.008*ejected + 0.006*particle + 0.006*particles + 0.006*performance + 0.005*energy + 0.005*measurement + 0.005*home+ + 0.005*model + 0.005*furnishings
INFO:gensim.models.ldamodel:topic #19 (0.042): 0.012*membrane + 0.007*fouling + 0.007*voc + 0.006*discovery + 0.006*undergraduate + 0.006*geometric + 0.006*water + 0.006*surface + 0.006*body + 0.006*robots
INFO:gensim.models.ldamodel:topic #6 (0.042): 0.009*design + 0.008*function + 0.008*modeling + 0.008*market + 0.008*biologics + 0.008*product + 0.007*production + 0.007*membrane + 0.007*capacity + 0.006*patterns
INFO:gensim.models.ldamodel:topic diff=0.098766, rho=0.196875
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.012*recommender + 0.008*systems + 0.006*develop + 0.006*system + 0.006*rssa + 0.004*team + 0.004*support + 0.004*unique + 0.004*benefit + 0.004*recommendations
INFO:gensim.models.ldamodel:topic #10 (0.042): 0.018*computing + 0.012*grain + 0.012*steel + 0.009*national + 0.009*consortium + 0.009*campuses + 0.008*size + 0.007*capabilities + 0.007*carc + 0.007*campus
INFO:gensim.models.ldamodel:topic #13 (0.042): 0.011*microwave + 0.011*technology + 0.009*yeast + 0.007*internet + 0.007*design + 0.007*detection + 0.006*flow + 0.006*properties + 0.006*based + 0.006*ice
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.010*infrastructure + 0.009*emerging + 0.007*critical + 0.007*human + 0.007*simulation + 0.007*adaptive + 0.007*model + 0.007*preferences + 0.006*real-time + 0.006*cognitive
INFO:gensim.models.ldamodel:topic #0 (0.042): 0.019*mercury + 0.016*water + 0.015*extreme + 0.014*carbon + 0.013*coastal + 0.012*flooding + 0.010*wetlands + 0.009*study + 0.008*organic + 0.007*blackwater
INFO:gensim.models.ldamodel:topic diff=0.097730, rho=0.196875
INFO:gensim.models.ldamodel:-10.175 per-word bound, 1155.8 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 18, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #1 (0.042): 0.009*development + 0.007*multimodal + 0.006*information + 0.006*students + 0.005*tactons + 0.005*means + 0.005*vnc + 0.005*work + 0.005*detection + 0.005*activities
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.012*students + 0.010*ambic + 0.009*infrastructure + 0.008*graduate + 0.008*biomanufacturing + 0.007*training + 0.007*science + 0.006*stem + 0.006*biopharmaceutical + 0.006*development
INFO:gensim.models.ldamodel:topic #0 (0.042): 0.016*water + 0.015*mercury + 0.014*extreme + 0.011*carbon + 0.011*coastal + 0.010*flooding + 0.009*quality + 0.008*wetlands + 0.008*implant + 0.008*study
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.008*infrastructure + 0.008*emerging + 0.007*critical + 0.007*human + 0.006*develop + 0.006*simulation + 0.006*adaptive + 0.006*model + 0.006*preferences + 0.005*real-time
INFO:gensim.models.ldamodel:topic #17 (0.042): 0.011*disposal + 0.009*development + 0.008*graduate + 0.008*methods + 0.006*infrastructure + 0.006*quantify + 0.006*life + 0.006*contribute + 0.006*sustainable + 0.006*environmental
INFO:gensim.models.ldamodel:topic diff=0.096459, rho=0.193167
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #1 (0.042): 0.008*development + 0.006*multimodal + 0.005*information + 0.005*students + 0.004*tactons + 0.004*means + 0.004*vnc + 0.004*work + 0.004*detection + 0.004*activities
INFO:gensim.models.ldamodel:topic #19 (0.042): 0.011*membrane + 0.006*fouling + 0.006*voc + 0.006*discovery + 0.006*undergraduate + 0.005*geometric + 0.005*water + 0.005*surface + 0.005*body + 0.005*robots
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.012*students + 0.010*ambic + 0.009*infrastructure + 0.008*graduate + 0.008*biomanufacturing + 0.007*science + 0.007*training + 0.007*stem + 0.006*biopharmaceutical + 0.006*cell
INFO:gensim.models.ldamodel:topic #6 (0.042): 0.010*biologics + 0.010*market + 0.008*design + 0.008*product + 0.008*membrane + 0.008*capacity + 0.007*function + 0.007*modeling + 0.007*production + 0.006*business
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.012*recommender + 0.008*systems + 0.006*develop + 0.006*system + 0.006*rssa + 0.004*team + 0.004*support + 0.004*unique + 0.004*benefit + 0.004*recommendations
INFO:gensim.models.ldamodel:topic diff=0.095550, rho=0.193167
INFO:gensim.models.ldamodel:-10.176 per-word bound, 1156.7 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #0 = documents up to #10/78, outstanding queue size 1
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #1 = documents up to #20/78, outstanding queue size 2
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #2 = documents up to #30/78, outstanding queue size 3
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #3 = documents up to #40/78, outstanding queue size 4
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #4 = documents up to #50/78, outstanding queue size 5
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #5 = documents up to #60/78, outstanding queue size 6
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #6 = documents up to #70/78, outstanding queue size 7
INFO:gensim.models.ldamulticore:PROGRESS: pass 19, dispatched chunk #7 = documents up to #78/78, outstanding queue size 8
INFO:gensim.models.ldamodel:merging changes from 50 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #9 (0.042): 0.008*infrastructure + 0.008*emerging + 0.007*critical + 0.007*human + 0.006*develop + 0.006*simulation + 0.006*adaptive + 0.006*model + 0.006*preferences + 0.005*real-time
INFO:gensim.models.ldamodel:topic #19 (0.042): 0.012*membrane + 0.007*fouling + 0.007*voc + 0.006*discovery + 0.006*undergraduate + 0.006*geometric + 0.006*water + 0.006*surface + 0.006*body + 0.006*robots
INFO:gensim.models.ldamodel:topic #0 (0.042): 0.016*water + 0.015*mercury + 0.014*extreme + 0.011*carbon + 0.011*coastal + 0.010*flooding + 0.009*quality + 0.008*wetlands + 0.008*implant + 0.008*study
INFO:gensim.models.ldamodel:topic #6 (0.042): 0.009*design + 0.008*function + 0.008*modeling + 0.008*biologics + 0.008*market + 0.008*product + 0.007*production + 0.007*membrane + 0.007*capacity + 0.006*patterns
INFO:gensim.models.ldamodel:topic #8 (0.042): 0.014*recommender + 0.010*systems + 0.007*develop + 0.007*system + 0.007*rssa + 0.005*team + 0.005*support + 0.005*unique + 0.005*benefit + 0.005*recommendations
INFO:gensim.models.ldamodel:topic diff=0.094340, rho=0.189661
INFO:gensim.models.ldamodel:merging changes from 28 documents into a model of 78 documents
INFO:gensim.models.ldamodel:topic #22 (0.042): 0.011*technology + 0.008*team + 0.007*cybersecurity + 0.007*data + 0.005*homes + 0.005*studies + 0.005*existing + 0.005*number + 0.005*network + 0.004*materials
INFO:gensim.models.ldamodel:topic #13 (0.042): 0.011*microwave + 0.011*technology + 0.009*yeast + 0.007*design + 0.007*internet + 0.007*detection + 0.006*flow + 0.006*properties + 0.006*based + 0.006*ice
INFO:gensim.models.ldamodel:topic #12 (0.042): 0.012*students + 0.010*ambic + 0.009*infrastructure + 0.008*graduate + 0.008*biomanufacturing + 0.007*science + 0.007*training + 0.007*stem + 0.006*biopharmaceutical + 0.006*cell
INFO:gensim.models.ldamodel:topic #16 (0.042): 0.016*sustainability + 0.012*amulet + 0.010*faculty + 0.009*courses + 0.009*stand-alone + 0.008*water + 0.007*engineering + 0.007*different + 0.006*mhealth + 0.006*technology
INFO:gensim.models.ldamodel:topic #19 (0.042): 0.011*membrane + 0.006*fouling + 0.006*voc + 0.006*discovery + 0.006*undergraduate + 0.005*geometric + 0.005*water + 0.005*surface + 0.005*body + 0.005*robots
INFO:gensim.models.ldamodel:topic diff=0.093515, rho=0.189661
INFO:gensim.models.ldamodel:-10.177 per-word bound, 1157.6 perplexity estimate based on a held-out corpus of 8 documents with 1580 words
INFO:gensim.utils:saving LdaState object under /tmp/CuModel_1.lda.state, separately None
INFO:gensim.utils:saving LdaMulticore object under /tmp/CuModel_1.lda, separately None
INFO:gensim.utils:not storing attribute dispatcher
INFO:gensim.utils:not storing attribute state

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