num = 5
lst = mList
if letter == "V":
num = 9
lst = vList
if letter == "W":
num = 9
lst = wList
j = 0
for i in range(num):
while letter + str(j) in lst:
j += 1
if j > (150 - len(lst)) - 1:
break
G = z[0][letters[letter]][j]
G = t.main_component(G=G, report=False)
pos = t.get_pos(G)
l_inputs.append((G, pos))
l_labels.append(letter + str(j))
l_target.append(letter)
j += 1
matrix = classify.get_matrix(l_inputs, frames, True, True, average="median")
flat = classify.condense(matrix)
# This plot may render with the axes flippeed
points = classify.mds(input_list=l_inputs,
target_list=l_target,
frames=frames,
D=matrix,
colorize=True,
for i in range(0, 32):
count += 2250 - i
print(count)
outliers = [
] # Make sure you comment this out if you stop and try to pick up again
# otherwise you'll lose your progress
num = letters["K"] # Change the "K" to be the letter you want, then run
letter = key[num]
# Shouldn't need to touch anything else
for i in range(150):
g = z[0][num][i]
g = t.main_component(G=g, report=False)
nx.draw(g, t.get_pos(g))
plt.title(str(i))
plt.show()
print("\nType 'exit' at any time to stop.")
answer = input(
"Outlier? Press enter for no. \nType anything else (except for 'exit') for yes. "
)
if answer == "exit":
print("\nYou stopped at", letter + str(i))
print("\nMake sure you don't lose the outliers you've picked so far.")
break
elif answer != "":
one = letter + str(i)
outliers.append(one)
