In [9]:
import sys, csv, math, random
import numpy as np
import pandas as pd
from matplotlib import pyplot
%matplotlib inline
from scipy.stats import pearsonr
In [2]:
# A useful function
def getdoc(anid):
'''
Gets the docid part of a character id
'''
if '|' in anid:
thedoc = anid.split('|')[0]
else:
print('error', anid)
thedoc = anid
return thedoc
In [3]:
# Initialize some variables
# We're going to do this for a 200-topic model.
doctopic_path = '../fic200/fic200_doctopics.txt'
veclen = 200
# Two variables that will hold a list of CVs and means
# for each topic. Each item in the list represents a
# coefficient of variation, or a mean, for a different
# document.
doc_cvs = dict()
doc_means= dict()
for i in range(veclen):
doc_means[i] = []
doc_cvs[i] = []
In [4]:
names = ['theindex', 'charid']
names.extend(["topic" + str(x) for x in range (200)])
dtm = pd.read_csv(doctopic_path, sep = '\t', names = names)
In [5]:
dtm = dtm.assign(docid = dtm.charid.map(getdoc))
In [43]:
alldocs = set(dtm.docid)
randomsample = random.sample(alldocs, 200)
In [44]:
topicbytopic = dict()
for i in range(veclen):
topicbytopic[i] = dict()
In [45]:
for idx, d in enumerate(randomsample):
if idx % 10 == 1:
print(idx)
group = dtm.loc[dtm.docid == d, :]
if len(group) < 3:
continue
for i in range(veclen):
for j in range(veclen):
if j not in topicbytopic[i]:
topicbytopic[i][j] = []
ival = group['topic' + str(i)]
jval = group['topic' + str(j)]
r, p = pearsonr(ival, jval)
topicbytopic[i][j].append((r, np.mean(ival) + np.mean(jval)))
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In [46]:
keypath = '../fic200/fic200_keys.txt'
keys = []
boring = {'said', 'had', 'was'}
with open(keypath, encoding = 'utf-8') as f:
for line in f:
fields = line.strip().split('\t')
text = fields[2]
words = text.split()[1 : ]
interestingwords = []
for w in words:
if w not in boring:
interestingwords.append(w)
if len(interestingwords) > 15:
break
keys.append(interestingwords)
keys = [' '.join(x) for x in keys]
In [47]:
tuples = []
for i in range(veclen):
for j in range(i + 1, veclen):
weight_tuples = topicbytopic[i][j]
vector, weights = list(zip(*weight_tuples))
mean = np.average(vector, weights = weights)
tuples.append((mean, i, j))
tuples.sort()
for t in tuples[0: 12]:
mean, i, j = t
print(mean)
print(i, keys[i])
print(j, keys[j])
print()
-0.414284941012
57 was-miss nd said-lh ty said-tw vo said-ba lh said-md said-jr said-mrs thought m.d or l looked
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
-0.409789294622
29 said-hy said-heen was-cried heen was-replied said-hythe said-sir said-lord said-hack said-hetter hy said-yon hut said-cried said-lady cried
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
-0.404947298925
94 said-knight said-king said-lancelot said-knights said-hee said-unto said-fair said-ever said-lady was-sir said-lord said-doe said-therefore said-sword said-god said-bee
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
-0.402040236433
121 said-beth said-first said-find said-miss godmother said-rose said-mrs find fingers bury said-carew said-lennard said-scot first finished said-yes
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
-0.40003226061
73 square said-copperfield said-micawber street fields lane said-et folly park hall said-traddles said-septimius said-lovaine said-uriah said-trotwood said-albinia
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
-0.377920645167
122 companion eye eyes said-though turned friend saw was-returned continued returned hand said-young was-exclaimed was-cried is head
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
-0.374750162028
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
167 said-ze said-dat said-der said-dot said-iss said-vill said-te said-vas said-pe said-vat said-goot said-und said-ees said-mine said-mit said-ta
-0.372303592623
117 said-miss said-sir said-lady said-st pride said-forester was-returned said-dane said-home face said-bouverie said-walsingham was-cried is said-falkland said-asked
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
-0.365175833812
41 asked said-why said-want said-mean said-thing said-maybe said-something said-anything said-look thought said-better said-oh said-hell said-thought said-god said-gates
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
-0.362637423549
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
199 said-ya ass said-ah mouth said-ta body prick cunt legs said-dont said-fuck tongue dick balls penis thighs
-0.36174281598
15 said-brother saw went asked took replied heard said-chinese said-take said-why said-elder heart said-back said-ch came answered
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
-0.361471552975
131 replied said-sir hand companion eyes continued added said-de was-cried said-replied said-though head said-lord said-give said-indeed said-dear
174 said-sir head said-dear said-mrs hand returned was-returned said-miss eyes said-friend hands said-gentleman said-quite was-cried said-young friend
In [48]:
topicmeans = dict()
for i in range(200):
topicmeans[i] = []
for idx, d in enumerate(randomsample):
if idx % 10 == 1:
print(idx)
group = dtm.loc[dtm.docid == d, :]
if len(group) < 1:
continue
for i in range(veclen):
ival = group['topic' + str(i)]
topicmeans[i].append(np.mean(ival))
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In [52]:
bookcorrelations = dict()
for i in range(200):
if i not in bookcorrelations:
bookcorrelations[i] = dict()
for j in range(i + 1, 200):
bookcorrelations[i][j], p = pearsonr(topicmeans[i], topicmeans[j])
In [59]:
tuples = []
for i in range(veclen):
for j in range(i + 1, veclen):
weight_tuples = topicbytopic[i][j]
vector, weights = list(zip(*weight_tuples))
mean = np.average(vector, weights = weights)
if mean < 0 and bookcorrelations[i][j] > 0.2:
tuples.append((mean, bookcorrelations[i][j], i, j))
tuples.sort()
for t in tuples[0: 12]:
mean, bookc, i, j = t
print(mean, bookc)
print(i, keys[i])
print(j, keys[j])
print()
-0.148163974954 0.240298258068
29 said-hy said-heen was-cried heen was-replied said-hythe said-sir said-lord said-hack said-hetter hy said-yon hut said-cried said-lady cried
165 said-wo said-why said-game said-take said-thing said-oh said-look said-play said-back said-boy said-big said-give said-enough said-fellow said-better said-guess
-0.139549492338 0.227229758496
4 looked head nodded smiled asked shook turned said-want eyes hand face laughed said-yes stood said-why took
47 said-lady said-ladyship carriage said-lord maid said-dear husband woman was-cried party lord friends said-miss house has was-exclaimed
-0.138524999246 0.595019133799
29 said-hy said-heen was-cried heen was-replied said-hythe said-sir said-lord said-hack said-hetter hy said-yon hut said-cried said-lady cried
176 felt said-dear said-miss was-replied thought friend said-quite said-wish looked mind manner said-lady said-indeed said-mrs feelings said-sure
-0.128795885417 0.297329165015
124 said-ai said-reckon said-take said-sure said-boys eyes said-ranch said-around said-camp said-hell said-trail said-gold rode said-look said-wo said-big
165 said-wo said-why said-game said-take said-thing said-oh said-look said-play said-back said-boy said-big said-give said-enough said-fellow said-better said-guess
-0.127160099235 0.230409383394
74 nodded smiled shook eyes looked said-yes turned murmured shrugged laughed said-why paused glanced sighed grinned said-oh
166 said-oh said-want said-yes said-really said-why said-course said-dear said-look said-quite said-love said-mean said-people laughed looked said-wo said-because
-0.123638354934 0.336156094281
57 was-miss nd said-lh ty said-tw vo said-ba lh said-md said-jr said-mrs thought m.d or l looked
194 said-miss replied said-mrs friend was-asked said-yes entered said-home said-friend left room hand said-sir continued took returned
-0.122346068804 0.267167591424
4 looked head nodded smiled asked shook turned said-want eyes hand face laughed said-yes stood said-why took
60 said-de said-padre said-spanish said-la said-el said-sefior said-san said-senora said-friend said-senorita said-god said-mexican said-si said-que said-dios said-excellency
-0.12070517066 0.407569514818
123 friend found mind thought received felt made knew wished took saw friends return returned left heart
183 said-heart said-young said-mind said-beauty said-life said-ever said-lady said-nature said-character said-world said-though said-feelings said-happiness said-society said-friend said-felt
-0.114147200938 0.365664695291
18 said-white said-indians said-chief rifle said-river said-people said-camp said-red said-woods said-back said-kill said-young said-take said-soon said-war said-fire
186 said-sea said-water said-island said-fish said-river said-shore boat said-land said-wind said-back said-beach said-lake said-take said-fishing said-away said-long
-0.112352000525 0.207167433622
123 friend found mind thought received felt made knew wished took saw friends return returned left heart
190 was-replied was-cried said-yes said-love said-ah said-nothing was-asked said-wish said-take took said-give said-dear replied said-god said-count said-friend
-0.110735707014 0.355572502067
22 said-dear said-lady said-friend was-replied said-indeed said-miss said-hope said-wish said-present said-give said-madam said-honour said-believe replied said-young said-ever
99 said-signora said-di was-don said-italian said-signore said-count said-ah said-la said-signorina said-san said-messer said-che said-marchese said-pietro said-english said-signer
-0.110432697328 0.424798965515
148 rifle said-shoot said-gun said-shot said-back said-take shouted said-kill hand shot fired pistol said-god said-fire said-hell head
165 said-wo said-why said-game said-take said-thing said-oh said-look said-play said-back said-boy said-big said-give said-enough said-fellow said-better said-guess
In [30]:
topicbytopic[1][2]
Out[30]:
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Content source: tedunderwood/biographies
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