Python光学仿真光的偏振编程理解学习

#偏振光演示
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D as axd
def polarShow():
    z = np.arange(0,5,0.01)      #传播方向，单位um
    dWave = 0.6328   
    x1 = z*0
    y1 = np.cos(2*np.pi*z/dWave)#此光波偏振方向为y
    x2 = np.cos(2*np.pi*z/dWave)#此光波偏振方向为y
    y2 = z*0
    fig = plt.figure()
    ax = axd(fig)
    ax.plot3D(z,x1,y1)
    ax.plot3D(z,x2,y2)
    ax.plot3D(z,x1,y2)
    plt.show()

#两个存在相位差的线偏振光演示
def polarShow(dWave = 0.6328,delta=0.5):
    z = np.arange(0,5,0.01)      
    x1 = z*0
    y1 = np.cos(2*np.pi*z/dWave+delta)#此光波偏振方向为y
    x2 = np.cos(2*np.pi*z/dWave)#此光波偏振方向为x
    y2 = z*0
    x3 = x1+x2
    y3 = y1+y2
    fig = plt.figure()
    ax = axd(fig)
    ax.plot3D(z,x1,y1)
    ax.plot3D(z,x2,y2)
    ax.plot3D(z,x3,y3)
    ax.plot3D(z,x1,y2)
    plt.show()

#偏振光演示
def polarShow(dWave = 0.6328):
    z = np.arange(0,5,0.01)      
    x = np.cos(2*np.pi*z/dWave) #x偏振光
    delta = [0,np.pi/6,np.pi/4,\
             np.pi/3,np.pi/2,2*np.pi/3,\
             3*np.pi/4,5*np.pi/6,np.pi]    
    titles = ["0","30°","45°","60°","90°",\
        "120°","135°","150°","180°"]
    #fig = plt.figure()
    for i in range(9):
        ax =plt.subplot(331+i)  #子图绘制，表示3×3的布局中的第(1+i)个图
        ax.set_title(titles[i])
        y = np.cos(2*np.pi*z/dWave+delta[i])#此光波偏振方向为y
        plt.plot(x,y)
        plt.xticks([])
        plt.yticks([])  #去掉坐标轴
    plt.subplots_adjust(wspace=0.5,hspace=0.5)#调整子图间距
    plt.show()