试下代码高亮

# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as pl
import time
import pylab as pl
from matplotlib import cm

def shuye():
    # 蕨类植物叶子的迭代函数和其概率值
    eq1 = np.array([[0,0,0],[0,0.16,0]])
    p1 = 0.01
    
    eq2 = np.array([[0.2,-0.26,0],[0.23,0.22,1.6]])
    p2 = 0.07
    
    eq3 = np.array([[-0.15, 0.28, 0],[0.26,0.24,0.44]])
    p3 = 0.07
    
    eq4 = np.array([[0.85, 0.04, 0],[-0.04, 0.85, 1.6]])
    p4 = 0.85
    
    def ifs(p, eq, init, n):
    
        # 迭代向量的初始化
        pos = np.ones(3, dtype=np.float)
        pos[:2] = init
        
        # 通过函数概率，计算函数的选择序列
        p = np.add.accumulate(p)    
        rands = np.random.rand(n)
        select = np.ones(n, dtype=np.int)*(n-1)
        for i, x in enumerate(p[::-1]):
            select[rands<x] = len(p)-i-1
        
        # 结果的初始化
        result = np.zeros((n,2), dtype=np.float)
        c = np.zeros(n, dtype=np.float)
        
        for i in range(n):
            eqidx = select[i] # 所选的函数下标
            tmp = np.dot(eq[eqidx], pos) # 进行迭代
            pos[:2] = tmp # 更新迭代向量
    
            # 保存结果
            result[i] = tmp
            c[i] = eqidx
            
        return result[:,0], result[:, 1], c
    
    start = time.clock()
    x, y, c = ifs([p1,p2,p3,p4],[eq1,eq2,eq3,eq4], [0,0], 100000)
    print(time.clock() - start)
    pl.figure(figsize=(6,6))
    pl.subplot(121)
    pl.scatter(x, y, s=1, c="g", marker="s", linewidths=0)
    pl.axis("equal")
    pl.axis("off")
    pl.subplot(122)
    pl.scatter(x, y, s=1,c = c, marker="s", linewidths=0)
    pl.axis("equal")
    pl.axis("off")
    pl.subplots_adjust(left=0,right=1,bottom=0,top=1,wspace=0,hspace=0)
    pl.gcf().patch.set_facecolor("white")
    pl.show()

def	mandelbrot():	
    def iter_point(c):
        z = c
        for i in range(1, 100): # 最多迭代100次
            if abs(z)>2: break # 半径大于2则认为逃逸
            z = z*z+c
        return i # 返回迭代次数
        
    def draw_mandelbrot(cx, cy, d):
        x0, x1, y0, y1 = cx-d, cx+d, cy-d, cy+d 
        y, x = np.ogrid[y0:y1:200j, x0:x1:200j]
        c = x + y*1j
        start = time.clock()
        mandelbrot = np.frompyfunc(iter_point,1,1)(c).astype(np.float)
        print("time=",time.clock() - start)
        pl.imshow(mandelbrot, cmap=cm.Blues_r, extent=[x0,x1,y0,y1])
        pl.gca().set_axis_off()

    x,y = 0.27322626, 0.595153338
    
    pl.subplot(231)
    draw_mandelbrot(-0.5,0,1.5)
    for i in range(2,7):    
        pl.subplot(230+i)
        draw_mandelbrot(x, y, 0.2**(i-1))
    pl.subplots_adjust(0.02, 0, 0.98, 1, 0.02, 0)
    pl.show()		
	
if __name__ == '__main__':
    mandelbrot()