Aider generer sequence aleaoire et calcul

Bonjour, j'ai un programme a faire qui consiste a generer des sequence aleatoirement, les substituer de maniere aleatoire aussi et calculer la distance de jukes cantor. NOtre consigne est d'importer que random et utiliser randint , et math. Mais j'ai un petit soucis, je n'arrive pas à avoir les bonne valeur dans la liste data[1], je ne sais pas pourquoi il me dit que seq n'a pas de longueur...
pourriez vous m'aider :

#exo1 
def alphabet(name):
    if name=="nucleic":
        alpha="acgt"
        return alpha
    if name=="protein":
        alpha="ARNDBCEQZGHILKMFPSTWYV"
        return alpha
    if name=="iupac_nucleic":
        alpha="ACGTRYSWKMBDHVN"
        return alpha
    if name=="iupac_protein":
        alpha="ABCDEFGHIJKLMNOPQRSTUVWXYZ"
        return alpha

#print (alphabet("nucleic"))

#exo2 
def randseq(num, alphabet):
    randseq=""
    for i in range(num):
        ind=random.randint(0, len(alphabet)-1)
        randseq=randseq+alphabet[ind]
    return randseq

#anuc=alphabet("nucleic")
#test=randseq(20,anuc)
#print (test,len(test))

#exo3
def hamming(seq1,seq2):
    d=0
    for i in range(0,len(seq1)):
        if seq1[i]!=seq2[i]:
            d=d+1
    return d

#hamming("acgtacgt","aggtacga")

#exo4
def mutate(seq,num_subs):
    seqmut=list(seq)
    for i in range(num_subs):  
        ahboni=random.randint(0,(len(seq)-1))
        seqmut[ahboni]=randseq(1,alphabet('nucleic'))
    return hamming(seq,seqmut)



#h=mutate("acgtacg",5)
#print (h)
    
def experiments(le,su,nb):
    v=[]
    for i in range(nb):
        seq=randseq(le,alphabet("nucleic"))
        v.append(mutate(seq,su))
    return v

#results=experiments(1000,1000,10)
#print (results)

#STAT
#1.5
def mean(data):
    somme=0.0
    moyenne=0.0
    for i in list(data):
        somme=somme+data[i]
    moyenne=somme/len(data)
    return moyenne

#1.6
def variance(data):
    k = 0
    for x in data:
        k=k+ 1
        if k == 1:
            M = x
            S = 0
        else:
            Mnext = M + (x - M) / k
            S = S + (x - M)*(x - Mnext)
            M = Mnext
    return (S/(k-1))
#1.7
def std(data):    
    return math.sqrt(variance)

#1.8    
def distanceJC69(mean,L):
    d=(-3/4)*math.log(abs(1.0-((mean/L)*(4/3))))
    return d

#v =[109,107,99,105,109]
#print (mean(v))
#L =700
#d = distanceJC69(mean,L)
#print(d)

#1.9

def generate(le,nb,xx):
    seq1000nt=randseq(1000,alphabet('nucleic'))
    listham=[]
    listjuke=[] 
    listfinal=[]
    for i in xx:
        nb=i
        seq_mutated=mutate(seq1000nt,nb)
        hamming_distances=hamming(seq_mutated,seq1000nt)
        juke=distanceJC69(nb,L)
        listham.append(hamming_distances)
        listjuke.append(juke)
    listfinal.append(listham)
    listfinal.append(listjuke)
    return listfinal
    


v=[]
L =1000
R =10
x =list(range(100,10000,200))
data = generate(L,R,x)



import matplotlib.pyplot as plt



xx=[0]*len(x)
yy=[0]*len(x)
for i in range(len(x)):
    xx[i]=x[i]
    yy[i]=data[1][i]
plt.plot(xx,yy)

xxx=[0]*len(x)
yyy=[0]*len(x)
for i in range(len(x)):
    xxx[i]=x[i]
    yyy[i]=data[0][i]
plt.plot(xxx,yyy)



plt.show()