# -*- coding: utf-8 -*-

import os, sys
import re
import numpy as np 
from Bio import pairwise2
import networkx as nx
import matplotlib.pyplot as plt

def network_project():
    gene=[]     
    header=[]
    lecture=''
    i=0
    j=0
    file='exemple_sequence.txt'
    lecture=open(file,"r")      
    seq=''     
    for line in lecture:    
        sequence=len(re.findall(r"[>]",line))   
        if(sequence>0):     
            gene.append(seq)    
            seq=''
            sequence=0
            header.append(line[1:-1])  
            i=i+1
        else:
            seq=seq+line[:-1] 
    gene.append(seq)    
    lecture.close()   
    
    score=[]
    for i in range(len(gene)):
        for j in range((i+1),len(gene)):
            score.append(pairwise2.align.globalms(gene[i],gene[j], 3, -2, -1, -.5,score_only=True))
    liste=[]
    seuil=(np.mean(score)+0.05*np.std(score))  
    s=0
    edge_labels={}
    for i in range(len(gene)):
        for j in range((i+1),len(gene)):
            if(score[s]>seuil):
                liste.append((header[i],header[j]))
                edge_labels[(header[i],header[j])]=score[s]
            s=s+1
    G=nx.Graph()
    G.add_nodes_from(header)
    G.add_edges_from(liste)
    pos=nx.spring_layout(G)
    node_s=[]
    t=0
    for t in range(len(gene)):
        node_s.append(20*np.log(len(seq[t])))
    nx.draw_networkx_nodes(G,pos,node_color='green',label=True,alpha=1,node_size=node_s)
    Width=dict(edge_labels)
    for key,value in Width.items() :
        Width[key] = np.log10(value)/2
    nx.draw_networkx_edges(G,pos,width=Width.values(),style='solid',edge_color='red',alpha=1)
    nx.draw_networkx_edge_labels(G,pos,edge_labels=edge_labels,font_size=2,alpha=0.5,font_color='black')
    nx.draw_networkx_labels(G,pos,font_size=3,font_color='blue')

    namefordoc=input('Nom du PDF sans .pdf ?\n')
    plt.savefig(namefordoc+'.pdf')