import numpy as np
from numpy.linalg import norm
import matplotlib.pyplot as plt
from numpy import sin,cos
import tkinter as tk
# from PIL import Image, ImageTk
from scipy.interpolate.interpnd import LinearNDInterpolator

class ImageHolder:
    def __init__(self):
        self.img1 = None

# 创建类实例
image_holder = ImageHolder()
def mesh(b,a,n):
    x=np.linspace(b,a,n)
    y=np.linspace(b,a,n)
    
    
    p=np.array([[np.array([x[i],y[j],0]) for i in range(x.shape[0])] for j in range(x.shape[0]) ])
    n=p.shape[1]
    pp=p.reshape([n*n,3])
    return(pp)




        
       

# 定义旋转函数
def rotate_points_to_normal(points, normal):
    # 步骤1：计算法向量的单位向量
    
   
    normal_unit = normal / np.linalg.norm(normal)
    
    if normal_unit[0]>0:
        normal_unit=-normal_unit

    # 步骤2：计算旋转轴
    z_axis = np.array([0, 0, 1])

    
    theta1 = np.arctan(normal_unit[1]/normal_unit[0])
    theta2 = -np.arccos(normal_unit[2]/norm(normal_unit))
    

    # 步骤4：创建旋转矩阵
    c = np.cos(theta1)
    s = np.sin(theta1)
    
    
    tr1= np.array([
        [c,s,0],[-s,c,0],[0,0,1]
    ])
    s=np.sin(theta2)
    c = np.cos(theta2)
    tr2=np.array([
        [c,0,-s],[0,1,0],[s,0,c]
    ])
    tr=tr2@tr1
    # 步骤5：应用旋转矩阵到点集
    rotated_points = np.dot(points, tr)  # 使用转置矩阵来进行点的旋转





    
    
   
    # normal_unit = normal / np.linalg.norm(normal)
    
    # if normal_unit[0]>0:
    #     normal_unit=-normal_unit

    # # 步骤2：计算旋转轴
    # z_axis = np.array([0, 0, 1])
    
    # theta1 =np.pi/2- np.arctan(normal_unit[1]/normal_unit[0])
    # theta2 = -np.arccos(normal_unit[2]/norm(normal_unit))

    # # 步骤4：创建旋转矩阵
    # c = np.cos(theta1)
    # s = np.sin(theta1)
    
    
    # tr1= np.array([
    #     [c,s,0],[-s,c,0],[0,0,1]
    # ])
    # s=np.sin(theta2)
    # c = np.cos(theta2)
    # tr2=np.array([
    #     [1,0,0],[0,c,s],[0,-s,c]
    # ])
    # tr=tr2@tr1
    # # 步骤5：应用旋转矩阵到点集
    # rotated_points = np.dot(points, tr)  # 使用转置矩阵来进行点的旋转

    return rotated_points
    
def trans(m,n,r=np.array([0,0,0])):
    return(rotate_points_to_normal(m,n)+r)

def retrans(m,normal,r=np.array([0,0,0])):
    points=m-r
     # 步骤1：计算法向量的单位向量
    
   
    normal_unit = normal / np.linalg.norm(normal)
    if normal_unit[0]>0:
        normal_unit=-normal_unit
    
    # 步骤2：计算旋转轴
    z_axis = np.array([0, 0, 1])
    
    # 步骤3：计算旋转角度
    theta1 = np.arctan(normal_unit[1]/normal_unit[0])
    theta2 = -np.arccos(normal_unit[2]/norm(normal_unit))

    # 步骤4：创建旋转矩阵
    c = np.cos(theta1)
    s = np.sin(theta1)
    
    
    tr1= np.array([
        [c,s,0],[-s,c,0],[0,0,1]
    ])
    s=np.sin(theta2)
    c = np.cos(theta2)
    tr2=np.array([
        [c,0,-s],[0,1,0],[s,0,c]
    ])
    tr=tr2@tr1
    # 步骤5：应用旋转矩阵到点集
    rotated_points = np.dot(points,tr.T)  # 使用转置矩阵来进行点的旋转

    return rotated_points
def egg(s):
    global img
    if s=="夏轩哲nb":
        tk.messagebox.showinfo("确实nb!","确实nb!")
        return(0)
    elif s=="谢昀城nb":
        tk.messagebox.showinfo("确实nb!","确实nb!")
        return(0)
    elif s=="谢昀城":
        tk.messagebox.showinfo("来自作者的彩蛋()","来自作者的彩蛋()")
        return(0)
    elif "原神" in s:
        tk.messagebox.showinfo("启动!","启动!")
        return(0)
    elif "崩坏三" in s:
        tk.messagebox.showinfo("为世界上所有美好而战!","为世界上所有美好而战!")
        return(0)
    elif "爱莉希雅" in s:
        
        
        tk.messagebox.showinfo("爱门!","爱门!")
        # wd2=tk.Tk()
        # image_path = r"C:\Users\xyc\Desktop\光学荣誉\1.jpg"
        # image_holder.img1 = Image.open(image_path)
        # image_holder.img1 = ImageTk.PhotoImage(image_holder.img1)

        # # 创建Label并插入图片
        # image_label = tk.Label(wd2, image= image_holder.img1)
        # image_label.pack()
       
        return(0)
    elif "星穹铁道" in s:
        tk.messagebox.showinfo("愿此行终抵群星!","愿此行终抵群星!")
        return(0)

    else:
        return 1