Python 绘制分形图(曼德勃罗集、分形树叶、科赫曲线、分形龙、谢尔宾斯基三角等)附代码
lypr7463
8年前
<p style="text-align:center"><img src="https://simg.open-open.com/show/f948af9904df92b647cf12887064b80f.jpg"></p> <h3>1. 曼德勃罗集</h3> <pre> <code class="language-python">import numpy as np import pylab as pl import time from matplotlib import cm def iter_point(c): z = c for i in xrange(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): """ 绘制点(cx, cy)附近正负d的范围的Mandelbrot """ 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.jet, 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()</code></pre> <p style="text-align:center"><img src="https://simg.open-open.com/show/00d8f6099cea9215ef1da4e88a6eddf0.png"></p> <h3>2. 分形树叶</h3> <pre> <code class="language-python">import numpy as np import matplotlib.pyplot as pl import time # 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): """ 进行函数迭代 p: 每个函数的选择概率列表 eq: 迭代函数列表 init: 迭代初始点 n: 迭代次数 返回值: 每次迭代所得的X坐标数组, Y坐标数组, 计算所用的函数下标 """ # 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) 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("#D3D3D3") pl.show()</code></pre> <p style="text-align:center"><img src="https://simg.open-open.com/show/69f23767aeb42c7016652bd1a1aa79c2.png"></p> <h3>3. 其它分形图(科赫曲线、分形龙、谢尔宾斯基三角等)</h3> <pre> <code class="language-python">from math import sin, cos, pi import matplotlib.pyplot as pl from matplotlib import collections class L_System(object): def __init__(self, rule): info = rule['S'] for i in range(rule['iter']): ninfo = [] for c in info: if c in rule: ninfo.append(rule[c]) else: ninfo.append(c) info = "".join(ninfo) self.rule = rule self.info = info def get_lines(self): d = self.rule['direct'] a = self.rule['angle'] p = (0.0, 0.0) l = 1.0 lines = [] stack = [] for c in self.info: if c in "Ff": r = d * pi / 180 t = p[0] + l*cos(r), p[1] + l*sin(r) lines.append(((p[0], p[1]), (t[0], t[1]))) p = t elif c == "+": d += a elif c == "-": d -= a elif c == "[": stack.append((p,d)) elif c == "]": p, d = stack[-1] del stack[-1] return lines rules = [ { "F":"F+F--F+F", "S":"F", "direct":180, "angle":60, "iter":5, "title":"Koch" }, { "X":"X+YF+", "Y":"-FX-Y", "S":"FX", "direct":0, "angle":90, "iter":13, "title":"Dragon" }, { "f":"F-f-F", "F":"f+F+f", "S":"f", "direct":0, "angle":60, "iter":7, "title":"Triangle" }, { "X":"F-[[X]+X]+F[+FX]-X", "F":"FF", "S":"X", "direct":-45, "angle":25, "iter":6, "title":"Plant" }, { "S":"X", "X":"-YF+XFX+", "Y":"+XF-YFY-FX+", "direct":0, "angle":90, "iter":6, "title":"Hilbert" }, { "S":"L--F--L--F", "L":"+R-F-R+", "R":"-L+F+", "direct":0, "angle":45, "iter":10, "title":"Sierpinski" }, ] def draw(ax, rule, iter=None): if iter!=None: rule["iter"] = iter lines = L_System(rule).get_lines() linecollections = collections.LineCollection(lines) ax.add_collection(linecollections, autolim=True) ax.axis("equal") ax.set_axis_off() ax.set_xlim(ax.dataLim.xmin, ax.dataLim.xmax) ax.invert_yaxis() fig = pl.figure(figsize=(7,4.5)) fig.patch.set_facecolor("papayawhip") for i in xrange(6): ax = fig.add_subplot(231+i) draw(ax, rules[i]) fig.subplots_adjust(left=0,right=1,bottom=0,top=1,wspace=0,hspace=0) pl.show()</code></pre> <p style="text-align:center"><img src="https://simg.open-open.com/show/713231ec1f45ae415511556aa469fc06.png"></p> <p> </p> <p> </p> <p>来自:https://zhuanlan.zhihu.com/p/25792397</p> <p> </p>