Code to classify elements on np.array on lists
You have essentially one chunk of code that's duplicated three times:
list_N = []
a,b,c = 0,0,0
for j in indexes_N[0]:
    if testy_L2[j] == 0.0:
        a += 1
    if testy_L2[j] == 1.0:
        b += 1
    if testy_L2[j] == 2.0:
        c += 1
list_N.append(a)
list_N.append(b)
list_N.append(c)

This could be easily wrapped in a function:
def process_the_stuff(indexes):
    acc = []
    a,b,c = 0,0,0
    for j in indexes[0]:
        if testy_L2[j] == 0.0:
            a += 1
        if testy_L2[j] == 1.0:
            b += 1
        if testy_L2[j] == 2.0:
            c += 1
    acc.append(a)
    acc.append(b)
    acc.append(c)
    return acc

Then just:
list_0 = process_the_stuff(indexes_0)
list_1 = process_the_stuff(indexes_1)
list_2 = process_the_stuff(indexes_2)


I'd clean up some other stuff though:

I'm not a fan of assigning multiple variables on a line in the vast majority of cases. I think a, b, and c should be initially assigned on separate lines.
The three append calls at the bottom could be cleaned up a bit by using extend, or just simply returning a tuple/list directly.
All three if checks are necessarily exclusive of each other (since testy_L2[j] can't be equal to 0, 1, and 2 at the same time). Those should be elifs instead so that once one is true, the others aren't checked.

After fixing these things, you'd be left with:
def process_the_stuff(indexes):
    a = 0
    b = 0
    c = 0
    for j in indexes[0]:
        if testy_L2[j] == 0.0:
            a += 1
        elif testy_L2[j] == 1.0:
            b += 1
        elif testy_L2[j] == 2.0:
            c += 1
    return [a, b, c]  # May make more sense to return a tuple instead unless you need a list

list_0 = process_the_stuff(indexes_0)
list_1 = process_the_stuff(indexes_1)
list_2 = process_the_stuff(indexes_2)


Minor, but &quot;indexes&quot; should be &quot;indices&quot; for the plural of &quot;index&quot;.