def prob_sample(histo):
''' Input a histogram. Output a randomly chosen word from the histogram
relative to its frequency in the body of text.
'''
words = stoch(histo)
# print(words)
dart = random.randint(0, 100)
counter = 0
word = None
for pair in words:
if counter < dart:
counter += pair[1]
word = pair[0]
return dart, counter, word
if __name__ == "__main__":
listo_histo = list_hist("source.txt")
dicto_histo = dict_hist("source.txt")
print(dicto_histo)
print(prob_sample(listo_histo))
print(prob_sample(dicto_histo))
def hello_world():
my_file = ('source.txt')
my_histogram = list_hist(my_file)
word = prob_sample(my_histogram)
return word
def hello_world():
my_file = open("./words.txt", "r")
lines = clean(my_file)
my_histogram = list_hist(lines)
word = prob_sample(my_histogram)
return word
def hello_world():
num_words = 10
sentence = []
my_file = ('source.txt')
my_histogram = list_hist(my_file)
for i in range(num_words):
word = prob_sample(my_histogram)
sentence += ' ' + word
return sentence
import random
from histogram import unique_words, frequency, list_hist
def stoch(histo):
''' Stochastic sampling means taking an element from a given collection at random '''
percentages = []
total_wc = 0
for item in histo:
total_wc += int(item[1])
for item in histo:
freq = frequency(item[0], histo)
perc = freq / total_wc
instance = (item[0], perc)
percentages.append(instance)
return percentages
if __name__ == "__main__":
source = 'one fish two fish red fish blue fish'
print(stoch(list_hist(source)))
''' Input a histogram. Output a randomly chosen word from the histogram
relative to its frequency in the body of text.
'''
words = stoch(histo)
# print(words)
dart = random.randint(0, 100)
counter = 0
word = None
# for pair in words: # pair = word and freq in percent
# if counter < dart:
# counter += pair[1] # since words already in percent - we just keep adding til we hit the dart
# word = pair[0]
# else:
# return
while counter < dart:
for pair in words:
counter += pair[1]
word = pair[0]
return dart, counter, word
if __name__ == "__main__":
listo_histo = list_hist("source.txt")
# dicto_histo = dict_hist("source.txt")
# print(dicto_histo)
print(prob_sample(listo_histo))
# print(prob_sample(dicto_histo))
import random
from histogram import unique_words, frequency, list_hist
def stoch(histo):
''' Stochastic sampling means taking an element from a given collection at random '''
percentages = []
total_wc = 0
for item in histo:
total_wc += int(item[1])
for item in histo:
freq = frequency(item[0], histo)
perc = freq / total_wc
instance = (item[0], perc)
percentages.append(instance)
return percentages
if __name__ == "__main__":
source = 'one fish two fish red fish blue fish'
listo_histo = list_hist("source.txt")
print(stoch(list_hist(source)))
import random
from histogram import unique_words, list_hist
def stochastic(histo):
''' Stochastic sampling means taking an element from a given collection at random '''
unique = unique_words(histo) # number of unique words
print(unique)
rand_num = random.randint(
1, unique) # random number in range of number of unique words
print(rand_num)
counter = 0
word = None
# count until we hit the random number
for item in histo:
while counter < rand_num:
counter += 1
word = item
print(word[0])
return word[0]
if __name__ == '__main__':
source = 'one fish two fish red fish blue fish'
stochastic(list_hist(source))
import random
from histogram import unique_words, list_hist
def stochastic(histo):
''' Stochastic sampling means taking an element from a given collection at random '''
unique = unique_words(histo) # number of unique words
print(unique)
rand_num = random.randint(1, unique) # random number in range of number of unique words
print(rand_num)
counter = 0
word = None
# count until we hit the random number
for item in histo:
if counter < rand_num:
counter += 1
word = item
print(word[0])
return word[0]
if __name__ == '__main__':
stochastic(list_hist(sample.txt))
import random
import sample
from histogram import unique_words, list_hist
def stochastic(histo):
''' Stochastic sampling means taking an element from a given collection at random '''
unique = unique_words(histo) # number of unique words
print(unique)
rand_num = random.randint(
1, unique) # random number in range of number of unique words
print(rand_num)
counter = 0
word = None
# count until we hit the random number
for item in histo:
if counter < rand_num:
counter += 1
word = item
print(word[0])
return word[0]
if __name__ == '__main__':
stochastic(list_hist('sample.txt'))
total_wc = 0
for item in histo:
total_wc += item[0]
for item in histo:
freq = freq(item[0], histo)
perc = freq / total_wc
instance = [item[0], perc]
percentages.append(instance)
return percentages
if __name__ == "__main__":
stochastic(list_hist(source.txt))
counter = 0
word = None
# count until we hit the random number
for item in histo:
if counter < rand_num:
counter += 1
word = item
print(word[0])
return word[0]
if __name__ == '__main__':
source = 'one fish two fish red fish blue fish'
stochastic(list_hist(source))
import random
import sample
from histogram import unique_words, list_hist
def stochastic(histo):
''' Stochastic sampling means taking an element from a given collection at random '''
unique = unique_words(histo) # number of unique words
print(unique)
rand_num = random.randint(
1, unique) # random number in range of number of unique words
print(rand_num)
counter = 0
word = None
# count until we hit the random number
for item in histo:
if counter < rand_num:
counter += 1
word = item
print(word[0])
return word[0]
if __name__ == '__main__':
stochastic(list_hist(sample))
import random
from histogram import unique_words, list_hist
def stochastic(histo):
''' Stochastic sampling means taking an element from a given collection at random '''
unique = unique_words(histo) # number of unique words
print(unique)
rand_num = random.randint(1, unique) # random number in range of number of unique words
print(rand_num)
counter = 0
word = None
# count until we hit the random number
for item in histo:
if counter < rand_num:
counter += 1
word = item
print(word[0])
return word[0]
if __name__ == '__main__':
stochastic(list_hist('source.txt'))
