def test_shift():
assert fn_exists("shift"), """\
Utility function: shift
As a quick aside, we need to build a function called 'shift' with
certain useful behavior. I promise that you will use this later, but
it is non-obvious right now how. Still, this is a good time to build
it.
The signature of shift looks like this:
shift(tuple, anything) => tuple
Shift takes a tuple, removes the first element, then adds the second
argument to the end, and returns the new tuple.
t = (1,2)
shift(t, 3)
=> (2, 3)
'Shifting' values onto the end of a collection while removing them
from the front is a commonly used operation.
Try experimenting with adding tuples together in the console to get an
idea of how to write this function."""
assert markov.shift((1, 2), 3) == (2, 3), """\
Here are more test cases to try out your shift function."""
assert markov.shift(("cat", "in"), "the") == ("in", "the"), """\
def test_shift():
assert fn_exists("shift"), """\
Utility function: shift
As a quick aside, we need to build a function called 'shift' with
certain useful behavior. I promise that you will use this later, but
it is non-obvious right now how. Still, this is a good time to build
it.
The signature of shift looks like this:
shift(tuple, anything) => tuple
Shift takes a tuple, removes the first element, then adds the second
argument to the end, and returns the new tuple.
t = (1,2)
shift(t, 3)
=> (2, 3)
'Shifting' values onto the end of a collection while removing them
from the front is a commonly used operation.
Try experimenting with adding tuples together in the console to get an
idea of how to write this function."""
assert markov.shift((1,2), 3) == (2,3), """\
Here are more test cases to try out your shift function."""
assert markov.shift(("cat", "in"), "the") == ("in","the"), """\
def process_word(self, word, order=2):
"""Processes each word.
word: string
order: integer
During the first few iterations, all we do is store up the words;
after that we start adding entries to the dictionary.
"""
if len(self.prefix) < order:
self.prefix += (word, )
return
try:
self.suffix_map[self.prefix].append(word)
except KeyError:
# if there is no entry for this prefix, make one
self.suffix_map[self.prefix] = [word]
self.prefix = shift(self.prefix, word)
def process_word(self, word, order=2):
"""Processes each word.
word: string
order: integer
During the first few iterations, all we do is store up the words;
after that we start adding entries to the dictionary.
"""
if len(self.prefix) < order:
self.prefix += (word,)
return
try:
self.suffix_map[self.prefix].append(word)
except KeyError:
# if there is no entry for this prefix, make one
self.suffix_map[self.prefix] = [word]
self.prefix = shift(self.prefix, word)
def random_text(self, n=100):
"""Generates random wordsfrom the analyzed text.
Starts with a random prefix from the dictionary.
n: number of words to generate
"""
# choose a random prefix (not weighted by frequency)
start = random.choice(list(self.suffix_map.keys()))
for i in range(n):
suffixes = self.suffix_map.get(start, None)
if suffixes == None:
# if the prefix isn't in map, we got to the end of the
# original text, so we have to start again.
self.random_text(n - i)
return
# choose a random suffix
word = random.choice(suffixes)
print(word, end=' ')
start = shift(start, word)
def random_text(self, n=100):
"""Generates random wordsfrom the analyzed text.
Starts with a random prefix from the dictionary.
n: number of words to generate
"""
# choose a random prefix (not weighted by frequency)
start = random.choice(list(self.suffix_map.keys()))
for i in range(n):
suffixes = self.suffix_map.get(start, None)
if suffixes == None:
# if the prefix isn't in map, we got to the end of the
# original text, so we have to start again.
self.random_text(n-i)
return
# choose a random suffix
word = random.choice(suffixes)
print(word, end=' ')
start = shift(start, word)