全局比对-python

sequence1="AGWGAHEA"
sequence2 = "PAWHEAEAG"
gap= -8
Blosum50

import numpy as np
import pandas as pd
import os
sequence1="AGWGAHEA"
sequence2 = "PAWHEAEAG"
s1=''
s2=''
gap=-8
os.chdir(r"C:/Users/16926/Desktop/")
score_matrix=pd.read_excel("sample.xlsx")
best_matrix=np.empty(shape= (len(sequence2)+1,len(sequence1)+1),dtype = int)

def get_match_score(s1,s2):
    score=score_matrix[s1][s2]
    return score

for i in range(len(sequence2)+1):
    for j in range(len(sequence1)+1):
        if i==0:
            best_matrix[i][j]=gap*j
        elif j==0:
            best_matrix[i][j]=gap*i
        else:
            match =get_match_score(sequence2[i-1],sequence1[j-1])
            gap1_score=best_matrix[i-1][j]+gap
            gap2_score = best_matrix[i][j-1]+gap
            match_score = best_matrix[i-1][j-1]+match
            best_matrix[i][j] = max(gap1_score,gap2_score,match_score)
print(best_matrix)
i,j = len(sequence2),len(sequence1)
while(i>0 or j>0):
    match = get_match_score(sequence2[i-1],sequence1[j-1])
    if i>0 and j>0 and best_matrix[i][j] == best_matrix[i-1][j-1]+match:
        s1 += sequence1[j-1]
        s2 += sequence2[i-1]
        i-=1;j-=1
    elif i>0 and best_matrix[i,j] == best_matrix[i-1,j]+gap:
        s1+='-'
        s2+=sequence2[i-1]
        i-=1
    else:
        s1+=sequence1[j-1]
        s2+='-'
        j-=1
print(s1[::-1]+'\n'+s2[::-1])

[[  0  -8 -16 -24 -32 -40 -48 -56 -64]
 [ -8  -1  -9 -17 -25 -33 -41 -49 -57]
 [-16  -3 -11 -19 -27 -20 -28 -36 -44]
 [-24 -11  -6   4  -4 -12 -20 -28 -36]
 [-32 -19 -13  -4   2  -6  -2 -10 -18]
 [-40 -27 -21 -12  -6   1  -7   4  -4]
 [-48 -35 -29 -20 -14  -1  -9  -4   9]
 [-56 -43 -37 -28 -22  -9 -17  -3   1]
 [-64 -51 -45 -36 -30 -17 -25 -11   2]
 [-72 -59 -43 -44 -28 -25 -33 -19  -6]]
-AGWG-AHEA-
PA-WHEA-EAG

score_matrix
    A   E   G   H   P   W
A   5.0 -1.0    0.0 -2.0    -1.0    -3
E   NaN 6.0 -3.0    0.0 -1.0    -3
G   NaN NaN 8.0 -2.0    -2.0    -3
H   NaN NaN NaN 10.0    -2.0    -3
P   NaN NaN NaN NaN 10.0    -4
W   NaN NaN NaN NaN NaN 15