final37另一种插值方法：在端点处插入相等的值

import numpy as np
import operator
import os
import copy
from matplotlib.font_manager import FontProperties
from scipy.interpolate import lagrange
import random
import matplotlib.pyplot as plt
import math 
np.set_printoptions(suppress=True)
# 把opt文件内的逗号变为空格
#数据在我的百度云数据库txt文件,及opt文件
np.set_printoptions(threshold=np.inf) #输出全部矩阵不带省略号
random.seed(10)
##########################################
data = np.loadtxt('txt//final37.txt')
# data = data[0:100]#抽取一部分
x1 = data[:,5]#x起点坐标
x2 = data[:,9]#x终点坐标
y1 = data[:,6]#y起
y2 = data[:,10]#y起
z1 = data[:,4]#IDpart
z2 = data[:,8]#IDpart
diam = data[:,12]
s1 = [a1 for a1 in range(1,len(x1)-1) if z1[a1]==z2[a1-1]!=-1 or z1[a1]!= z2[a1-1]]#id相同不等于0，或id不同
# print(s1)
lx = []#x1,x2相同的部分组成的列表
lxqi = []
lxzg = []
for i1 in range(len(s1)-1):
    b1 = x1[s1[i1]:s1[i1+1]]
    b1 = b1.tolist()
    b2 = x2[s1[i1+1]-1]#s1[i1]相当于a1
#     b1 = b1 + [b2]#把与x2最后相连的一个数和x1拼接起来
    b5 = z1[s1[i1]]#x,y起点id
    b1qi_id = [b5]+b1 +[b2]
    b6 = z2[s1[i1+1]-1]#x,y终点id
    b1zg_id = [b6] + b1+[b2]
    lx.append(b1)
    lxqi.append(b1qi_id)
    lxzg.append(b1zg_id)
###################################################
ly = []#y坐标以及管径大小
for i3 in range(len(s1)-1):
    b3 = y1[s1[i3]:s1[i3+1]]
    b3 = b3.tolist()
    b4 = y2[s1[i3+1]-1]#y最后一个不相等的数
    b3 = b3 + [b4]
    dm = diam[s1[i3+1]-1]
    b3 = b3 + [dm]#加上管径
    ly.append(b3)
#####################################################
#带有起点id的x坐标与y坐标合并
for q1 in range(len(lxqi)):
    for q2 in range(len(ly[q1])):
        lxqi[q1].append(ly[q1][q2])
#带有终点id的x坐标与y坐标合并
for p1 in range(len(lxzg)):
    for p2 in range(len(ly[p1])):
        lxzg[p1].append(ly[p1][p2])
lxqi.sort(key=operator.itemgetter(0))#排序，只按照第一个索引大小排序
tou = lxqi
lxzg.sort(key=operator.itemgetter(0))  
wei = lxzg 
# #########################################
toudeng = []
weideng = []
for dwei in wei:
    for i in range(len(tou)-1):
        if dwei[0] ==tou[i][0] and dwei[0]==tou[i+1][0]:
            toud = [dwei,tou[i],tou[i+1]]
            toudeng.append(toud)
for dtou in tou:
    for i in range(len(wei)-1):
        if dtou[0] == wei[i][0] and dtou[0]==wei[i+1][0]:
            weid = [wei[i],wei[i+1],dtou]
            weideng.append(weid)
# ###################################################
datatoudeng = []
dataweideng = []
#去掉起点id
for i in range(len(toudeng)):
    a = toudeng[i][0][1::]
    b = toudeng[i][1][1::]
    c = toudeng[i][2][1::]
    d = [a]+[b]+[c]
    datatoudeng.append(d)
for i in range(len(weideng)):
    a1 = weideng[i][0][1::]
    b1 = weideng[i][1][1::]
    c1 = weideng[i][2][1::]
    d1 = [a1]+[b1]+[c1]
    dataweideng.append(d1)
# print(dataweideng)
####################################################################
#判断管径信息是否加进列表，若未加进则只为x,y坐标，为偶数
for i in range(len(dataweideng)):
    a = dataweideng[i]
    assert len(a[0])%2==1
    assert len(a[1])%2==1
    assert len(a[2])%2==1
for i in range(len(datatoudeng)):
    a = datatoudeng[i]
    assert len(a[0])%2==1
    assert len(a[1])%2==1
    assert len(a[2])%2==1
finaldata = datatoudeng +dataweideng#未插值
final = datatoudeng #所有分叉，头等分叉，尾等分叉
# print(final)
################################################################################
#插值方法：第二张策略，在端点处，补上与端点的值相等的数，然后使每个分支维度相等。
finaldata = []
for i in range(len(final)):#final[i]代表一个分叉，它有三个不同长度的分支
    zhu = final[i][0]
    zuo = final[i][1]
    you = final[i][2]
    zhu_diam = [zhu[-1]]
    zuo_diam = [zuo[-1]]
    you_diam = [you[-1]]
    zhu_x = zhu[0:len(zhu)//2]
    zuo_x = zuo[0:len(zuo)//2]
    you_x = you[0:len(you)//2]
    zhu_y = zhu[len(zhu)//2:(len(zhu)-1)]
    zuo_y = zuo[len(zuo)//2:(len(zuo)-1)]
    you_y = you[len(you)//2:(len(you)-1)]
    #从这里开始插值，对于头部相等的数主分支，在头部插值，左右分支分别在尾部端点插值，对于final37希望每一个维度为60，所以，让他们每一个列表插入（30-len(zhu_x))个值
    zhu_insert_x = zhu_x[0]#主分支的第一个坐标
    zhu_insert_y = zhu_y[0]
    zuo_insert_x = zuo_x[-1]#左分支的最后一个坐标
    zuo_insert_y = zuo_y[-1]
    you_insert_x = you_x[-1]#右分支的最后一个坐标
    you_insert_y = you_y[-1]
    for i in range(30-len(zhu_x)):
        zhu_x.insert(0,zhu_insert_x)
        zhu_y.insert(0,zhu_insert_y)
    #左右分支在尾部插入与尾部端点坐标相等的值，因为左右分支头部要去掉一个值，所以应比主分支多插入一个
    for i in range(31-len(zuo_x)):
        zuo_x.append(zuo_insert_x)
        zuo_y.append(zuo_insert_y)
    for i in range(31-len(you_x)):
        you_x.append(you_insert_x)
        you_y.append(you_insert_y)
    #从这里去掉左右分支开头与主分支相等的部分
    zuo_x = zuo_x[1::] 
    you_x = you_x[1::]
    zuo_y = zuo_y[1::]
    you_y = you_y[1::]
    #这里将x和y列表再接起来
    zhu_xy = zhu_x + zhu_y
    zuo_xy = zuo_x + zuo_y
    you_xy = you_x + you_y
    #这里再将坐标点与管径接起来
    zhu = zhu_xy + zhu_diam
    zuo = zuo_xy + zuo_diam
    you = you_xy + you_diam
    fencha = [zhu]+[zuo]+[you]
    finaldata.append(fencha)
final = np.array(finaldata) #数组维度(-1,3,61)
print(final.shape)
#################################################################################
# final = final[0:2,:,:]#选取一个分叉测试旋转效果
x = final[:,:,0:30]
y = final[:,:,30:60]
diam = final[:,:,-1]
diam = diam.reshape(-1,3,1)
#########################################
#旋转
def rotate(angle,valuex,valuey):
    rotatex = math.cos(angle)*valuex -math.sin(angle)*valuey
    rotatey = math.cos(angle)*valuey + math.sin(angle)* valuex
    return rotatex,rotatey
rotatedata = []
for i in range(0,360,3): #每隔3度旋转一次
    x1,y1 = rotate(i,x,y)
    rotate_final = np.concatenate((x1,y1,diam),axis=2)
    rotatedata.append(rotate_final)
finaldata = []
for file in rotatedata:
    for data in file:
        finaldata.append(data)
finaldata = np.array(finaldata)
max1 = np.max(finaldata)
min1 = np.min(finaldata)
print(max1)
print(min1)
print(finaldata.shape)
##############################################################
#归一化前可视化单张图片
# final = finaldata
# for i in range(len(final)):
# #     plt.figure(figsize=(128,128),dpi=1)
#     plt.plot(final[i][0][0:30],final[i][0][30:60])
#     plt.plot(final[i][1][0:30],final[i][1][30:60])
#     plt.plot(final[i][2][0:30],final[i][2][30:60])
# #     plt.axis('off')
#     plt.show()
# #     plt.savefig('C:\\Users\\Administrator\\Desktop\\调整分辨率\\原始图\\resouce%d.jpg' %(i),dpi=1)
# #     plt.close()
################################################
#归一化处理不去除管径信息
finalSubCAM = []
final = finaldata
for i in range(len(final)):
    finalx = final[i][:,0:30]#(7,10,30)
    finaly = final[i][:,30:60]#(10,30,60)
    diameter = final[i][:,-1]
    diameter = diameter.reshape(3,1)
    Xmax = np.max(finalx)
    Xmin = np.min(finalx)
    Ymax = np.max(finaly)
    Ymin = np.min(finaly)
    Dmax = np.max(diameter)
    Dmin = np.min(diameter)
    normx = (finalx-Xmin)/(Xmax-Xmin)
    normy = (finaly-Ymin)/(Ymax-Ymin)
    normd = (diameter-Dmin)/(Dmax-Dmin)
    normxy = np.concatenate((normx,normy,diameter),axis=1) #加入原始管径diameter，或归一化管径normd
    finalSubCAM.append(normxy)
finaldata = np.array(finalSubCAM)
np.random.shuffle(finaldata)
print(np.min(finaldata))
print(np.max(finaldata))
print(finaldata.shape)
######################################################
#一种普通的可视化方法，此时画出来的图端点都连在了原点位置
# finaldata = finaldata.tolist()
# for i in range(len(finaldata)):
#     plt.plot(finaldata[i][0][0:30],finaldata[i][0][30:60])
#     plt.plot([finaldata[i][0][29]]+finaldata[i][1][0:30],[finaldata[i][0][59]]+finaldata[i][1][30:60])
#     plt.plot([finaldata[i][0][29]]+finaldata[i][2][0:30],[finaldata[i][0][59]]+finaldata[i][2][30:60])
#     plt.xticks(np.arange(0,1,0.1))
#     plt.yticks(np.arange(0,1,0.1))
#     plt.show()
#############################################################
np.save('C:\\Users\\Administrator\\Desktop\\重新整理血管网络\\final37在端点处插值.npy',finaldata)
###################################################################
#每100张图片显示在一张图中
# rows,cols = 10, 10
# fig,axs = plt.subplots(rows,cols)
# cnt = 0
# for i in range(rows):
#     for j in range(cols):
#         xy = finaldata[cnt]#第n个分叉图，有三个分支，每个分支21个数
#         for k in range(len(xy)):
#             x = xy[k][0:30]
#             y = xy[k][30:60]
#             axs[i,j].plot(x,y,linewidth=2)
#             axs[i,j].axis('off')
#         cnt +=1
# plt.show()