def test_frequency():
dictogram = Dictogram(fish_words)
# Verify frequency count of all words
assert dictogram.frequency('one') == 1
assert dictogram.frequency('two') == 1
assert dictogram.frequency('red') == 1
assert dictogram.frequency('blue') == 1
assert dictogram.frequency('fish') == 4
def test_frequency(self):
histogram = Dictogram(self.fish_words)
# Verify frequency count of all words
assert histogram.frequency('one') == 1
assert histogram.frequency('two') == 1
assert histogram.frequency('red') == 1
assert histogram.frequency('blue') == 1
assert histogram.frequency('fish') == 4
# Verify frequency count of unseen words
assert histogram.frequency('food') == 0
def test_frequency():
fish_words = ['one', 'fish', 'two', 'fish', 'red', 'fish', 'blue', 'fish']
histogram = Dictogram(fish_words)
# Verify frequency count of all words
assert histogram.frequency('one') == 1
assert histogram.frequency('two') == 1
assert histogram.frequency('red') == 1
assert histogram.frequency('blue') == 1
assert histogram.frequency('fish') == 4
# Verify frequency count of unseen words
assert histogram.frequency('food') == 0
def test_add_count(self):
histogram = Dictogram(self.fish_words)
# Add more words to update frequency counts
histogram.add_count('two', 2)
histogram.add_count('blue', 3)
histogram.add_count('fish', 4)
histogram.add_count('food', 5)
# Verify updated frequency count of all words
assert histogram.frequency('one') == 1
assert histogram.frequency('two') == 3
assert histogram.frequency('red') == 1
assert histogram.frequency('blue') == 4
assert histogram.frequency('fish') == 8
assert histogram.frequency('food') == 5
# Verify count of distinct word types
assert histogram.types == 6
# Verify total count of all word tokens
assert histogram.tokens == 8 + 14
def test_sample():
dictogram = Dictogram(fish_words)
# Create a list of 10,000 word samples from histogram
samples_list = [dictogram.sample() for _ in range(10000)]
# Create a histogram to count frequency of each word
samples_hist = Dictogram(samples_list)
# Check each word in original histogram
for word, count in dictogram.dictionary_histogram.items():
# Calculate word's observed frequency
observed_freq = count / dictogram.tokens
# Calculate word's sampled frequency
samples = samples_hist.frequency(word)
sampled_freq = samples / samples_hist.tokens
# Verify word's sampled frequency is close to observed frequency
lower_bound = observed_freq * 0.9 # 10% below = 90% = 0.9
upper_bound = observed_freq * 1.1 # 10% above = 110% = 1.1
assert lower_bound <= sampled_freq <= upper_bound