def distribution_of_improvement(patterns,
base_patterns=ortho_matching.default_patterns,
n=5,
removed=False):
ignore_n = 200
consider_n = 10000
top_effects = []
total_freq = 0
total_effect = 0
for freq, word in freqs[ignore_n:ignore_n + consider_n]:
base_result = ortho_matching.match_text(word.upper(),
patterns=base_patterns)
result = ortho_matching.match_text(word.upper(), patterns=patterns)
if result is not None and base_result is not None:
if removed:
effect_size = (len(result) - len(base_result)) * freq
else:
effect_size = (len(base_result) - len(result)) * freq
if effect_size < 0:
effect_size = 0
if len(top_effects) < n:
top_effects.append((effect_size, freq, word))
elif effect_size > top_effects[0][0]:
top_effects[0] = (effect_size, freq, word)
top_effects.sort()
total_effect += effect_size
total_freq += freq
improvements = []
for effect_size, freq, word in top_effects:
improvements.append(float(total_effect) / total_freq)
total_effect -= effect_size
total_freq -= freq
words = [w for e, f, w in top_effects]
return improvements, words
def get_avg_strokes(patterns=ortho_matching.default_patterns,
assume_one_n=200):
consider_n = 10000
count = 0
l_count = 0
index = 0
total_count = 0
fail_count = 0
for freq, word in freqs[:consider_n]:
result = ortho_matching.match_text(word.upper(), patterns=patterns)
old_strokes = ortho_matching.match_text(word.upper())
if old_strokes is not None:
for chord in old_strokes:
if chord['end'] == TESTEND:
if len(old_strokes) < len(result):
print(word, freq, len(result), len(old_strokes))
if old_strokes is not None and result is not None:
if len(old_strokes) > len(result):
pass
index += 1
total_count += freq
if result is not None:
if index < assume_one_n:
n_chords = 1
else:
n_chords = len(result)
else:
n_chords = None #1000000
fail_count += freq
if n_chords is not None:
count += freq
l_count += freq * n_chords
return (float(l_count) / count, float(fail_count) / total_count)
def get_avg_strokes(patterns=ortho_matching.default_patterns, assume_one_n=200):
consider_n = 10000
count = 0
l_count = 0
index = 0
total_count = 0
fail_count = 0
for freq, word in freqs[:consider_n]:
result = ortho_matching.match_text(word.upper(), patterns=patterns)
old_strokes = ortho_matching.match_text(word.upper())
if old_strokes is not None:
for chord in old_strokes:
if chord["end"] == TESTEND:
if len(old_strokes) < len(result):
print(word, freq, len(result), len(old_strokes))
if old_strokes is not None and result is not None:
if len(old_strokes) > len(result):
pass
index += 1
total_count += freq
if result is not None:
if index < assume_one_n:
n_chords = 1
else:
n_chords = len(result)
else:
n_chords = None # 1000000
fail_count += freq
if n_chords is not None:
count += freq
l_count += freq * n_chords
return (float(l_count) / count, float(fail_count) / total_count)
def distribution_of_improvement(patterns, base_patterns=ortho_matching.default_patterns, n=5, removed=False):
ignore_n = 200
consider_n = 10000
top_effects = []
total_freq = 0
total_effect = 0
for freq, word in freqs[ignore_n : ignore_n + consider_n]:
base_result = ortho_matching.match_text(word.upper(), patterns=base_patterns)
result = ortho_matching.match_text(word.upper(), patterns=patterns)
if result is not None and base_result is not None:
if removed:
effect_size = (len(result) - len(base_result)) * freq
else:
effect_size = (len(base_result) - len(result)) * freq
if effect_size < 0:
effect_size = 0
if len(top_effects) < n:
top_effects.append((effect_size, freq, word))
elif effect_size > top_effects[0][0]:
top_effects[0] = (effect_size, freq, word)
top_effects.sort()
total_effect += effect_size
total_freq += freq
improvements = []
for effect_size, freq, word in top_effects:
improvements.append(float(total_effect) / total_freq)
total_effect -= effect_size
total_freq -= freq
words = [w for e, f, w in top_effects]
return improvements, words
def get_change(text, patterns, base_patterns=ortho_matching.default_patterns):
base_result = ortho_matching.match_text(text.upper(), patterns=base_patterns)
result = ortho_matching.match_text(text.upper(), patterns=patterns)
if result is None and base_result is None:
effect_size = None
else:
effect_size = len(result) - len(base_result)
return effect_size
def get_change(text, patterns, base_patterns=ortho_matching.default_patterns):
base_result = ortho_matching.match_text(text.upper(),
patterns=base_patterns)
result = ortho_matching.match_text(text.upper(), patterns=patterns)
if result is None and base_result is None:
effect_size = None
else:
effect_size = len(result) - len(base_result)
return effect_size
def test_first():
n = 0
for f, w in freqs[:200]:
result = ortho_matching.match_text(w.upper())
if result is None or len(result) > 1:
print(w)
n += 1
print(n)
def test_first():
n = 0
for f, w in freqs[:200]:
result = ortho_matching.match_text(w.upper())
if result is None or len(result) > 1:
print(w)
n += 1
print(n)
def main():
data = DataStorage()
while True:
possible_questions = get_words(data)
data.save()
p_random = 0.5
if random.random() < p_random:
random_int = random.randint(0, len(possible_questions) - 1)
else:
random_int = 0
score, question, answer = possible_questions[random_int]
clear()
attempt = input('Type {}: '.format(question))
data.answer(question, attempt == answer)
if attempt == answer:
print('Correct!')
else:
print('Incorrect!')
chords = None
if question[-1] == '-':
raise Exception('Unimplemented')
#keys = ortho_keys.chord_to_keys(answer.upper(), None, None)
elif question[0] == '-':
raise Exception('Unimplemented')
#keys = ortho_keys.chord_to_keys(None, None, answer.upper())
else:
chords = ortho_matching.match_text(answer.upper())
if not chords:
raise Exception('Could not match text {}'.format(
answer.upper()))
for chord in chords:
keys = ortho_keys.chord_to_keys(chord['start'], chord['vowel'],
chord['end'])
vchord = visualize.visualize_keys(keys)
print(vchord)
while attempt != answer:
attempt = input('Type {}: '.format(question))
if attempt == answer:
print('Correct!')
else:
print('Incorrect!')
