def experiment10(cls):
alike_distances = []
for median_num in range(0, 30):
metrics = lambda x, y: PictureMetrics.dameray_levenstein_distance_sum(x, y, median_num=median_num)
fontFamilies = FontFamily.get_all_families()
alike_distance = 0
for fontFamily in fontFamilies:
print "--new font family---"
signes = fontFamily.get_signes(30)
for pair_of_signes in signes:
distance = metrics(pair_of_signes[0], pair_of_signes[1])
alike_distance += distance
alike_distances.append(alike_distance)
diff_distances = []
for median_num in range(0, 30):
metrics = lambda x, y: PictureMetrics.dameray_levenstein_distance_sum(x, y, median_num=median_num)
fontFamilies = FontFamily.get_all_families()
diff_distance = 0
for fontFamily in fontFamilies:
print "--new font family---"
signes = fontFamily.get_signes(15)
for pair_of_signes in signes:
for j, sign in enumerate(pair_of_signes):
ind = random_but_not_this(j, len(signes))
distance = metrics(sign, signes[ind][j])
diff_distance += distance
diff_distances.append(diff_distance)
substaction = []
for alike, diff in zip(alike_distances, diff_distances):
substaction.append(diff - alike)
plt.plot(range(0, 30), substaction, 'ro')
plt.show()
def optimize_weights(cls, weights, num_of_signes=100):
print weights
metrics = lambda x, y: PictureMetrics.dameray_levenstein_distance_sum(x, y, weights=weights)
fontFamilies = FontFamily.get_all_families()
alike_distance = 0
alike_num = 0
for fontFamily in fontFamilies:
signes = fontFamily.get_signes(num_of_signes)
for pair_of_signes in signes:
distance = metrics(pair_of_signes[0], pair_of_signes[1])
alike_distance += distance
alike_num += 1
print "alike distance=", alike_distance
#print "alike num=", alike_num
diff_distance = 0
diff_num = 0
for fontFamily in fontFamilies:
signes = fontFamily.get_signes(num_of_signes / 2)
for pair_of_signes in signes:
for j, sign in enumerate(pair_of_signes):
ind = random_but_not_this(j, len(signes))
distance = metrics(sign, signes[ind][j])
diff_distance += max(25 - distance, 0)
diff_num += 1
print "diff distance=", diff_distance
#print "diff num=", diff_num
result = alike_distance + diff_distance
print "total=", result
return result
def experiment3(cls):
metrics = lambda x, y: PictureMetrics.dameray_levenstein_distance_v(x, y)
fontFamilies = FontFamily.get_all_families()
alikes = []
for fontFamily in fontFamilies:
signes = fontFamily.get_signes(1000)
for pair_of_signes in signes:
distance = metrics(pair_of_signes[0], pair_of_signes[1])
alikes.append(distance)
plt.hist(alikes)
plt.show()
def experiment7(cls):
metrics = lambda x, y: PictureMetrics.dameray_levenstein_distance_sum(x, y)
fontFamilies = FontFamily.get_all_families()
differences = []
for fontFamily in fontFamilies:
signes = fontFamily.get_signes(1000)
for i, sign_array in enumerate(signes):
for j, sign in enumerate(sign_array):
ind = random_but_not_this(j, len(signes))
distance = metrics(sign, signes[ind][j])
differences.append(distance)
plt.hist(differences)
plt.show()
def experiment8(cls):
alike_distances = []
for median_num in range(0, 30):
metrics = lambda x, y: PictureMetrics.dameray_levenstein_distance_sum(x, y, median_num=median_num)
fontFamilies = FontFamily.get_all_families()
alike_distance = 0
for fontFamily in fontFamilies:
print "--new font family---"
signes = fontFamily.get_signes(50)
for pair_of_signes in signes:
distance = metrics(pair_of_signes[0], pair_of_signes[1])
alike_distance += distance
alike_distances.append(alike_distance)
plt.plot(range(0, 30), alike_distances, 'ro')
plt.show()
def experiment9(cls):
diff_distances = []
for median_num in range(0, 30):
metrics = lambda x, y: PictureMetrics.dameray_levenstein_distance_sum(x, y, median_num=median_num)
fontFamilies = FontFamily.get_all_families()
diff_distance = 0
for fontFamily in fontFamilies:
print "--new font family---"
signes = fontFamily.get_signes(50)
for pair_of_signes in signes:
for j, sign in enumerate(pair_of_signes):
ind = random_but_not_this(j, len(signes))
distance = metrics(sign, signes[ind][j])
diff_distance += distance
diff_distances.append(diff_distance)
plt.plot(range(0, 30), diff_distances, 'ro')
plt.show()
def count_penalty(cls, metrics):
fontFamilies = FontFamily.get_all_families()
penalty = 0
alikes = []
print "----getting signes from family----"
for fontFamily in fontFamilies:
signes = fontFamily.get_signes(1000)
family_penalty = 0
family_penalty_alike = 0
sum_alike = 0
sum_dif = 0
family_penalty_different = 0
diffs = []
alikes = []
for i, sign_set in enumerate(signes):
for j, sign in enumerate(sign_set):
for k, sign2 in enumerate(sign_set[j + 1:]):
alike = metrics(sign, sign2)
family_penalty_alike += alike
sum_alike += 1
alikes.append(alike)
if i < len(signes) and i != (len(signes) - i) % len(signes):
diff = metrics(sign, signes[-i][j])
family_penalty_different += max(18 - diff, 0)
sum_dif += 1
diffs.append(diff)
dif_to_alike = sum_dif / float(sum_alike)
family_penalty = family_penalty_alike * dif_to_alike + family_penalty_different
print "Family penalty alike:", family_penalty_alike, "sum_alike", sum_alike
print "Family penalty different:", family_penalty_different, "sum_dif", sum_dif
print "Family penalty total:", family_penalty
penalty += family_penalty
plt.hist(alikes)
plt.show()
print "Total penalty: ", penalty
