使用 matplotlib.pyplot 和 numpy 显示 python 中的 Mandelbrot 集
displaying Mandelbrot set in python using matplotlib.pyplot and numpy
我正在尝试绘制 Mandelbrot 集的图,但在绘制预期图时遇到了问题。
据我了解,Mandelbrot 集由值 c 组成,如果通过以下等式 z = z**2 + c 进行迭代,它将收敛。我使用了 z = 0 的初始值。
最初,我得到的是一条直线。我在网上寻找解决方案,看看我哪里出错了。特别是使用以下 link,我试图改进我的代码:
https://scipy-lectures.org/intro/numpy/auto_examples/plot_mandelbrot.html
这是我改进后的代码。我真的不明白使用 np.newaxis 的原因以及为什么我要绘制收敛的最终 z 值。我误解了 Mandelbrot 集的定义吗?
# initial values
loop = 50 # number of interations
div = 600 # divisions
# all possible values of c
c = np.linspace(-2,2,div)[:,np.newaxis] + 1j*np.linspace(-2,2,div)[np.newaxis,:]
z = 0
for n in range(0,loop):
z = z**2 + c
plt.rcParams['figure.figsize'] = [12, 7.5]
z = z[abs(z) < 2] # removing z values that diverge
plt.scatter(z.real, z.imag, color = "black" ) # plotting points
plt.xlabel("Real")
plt.ylabel("i (imaginary)")
plt.xlim(-2,2)
plt.ylim(-1.5,1.5)
plt.savefig("plot.png")
plt.show()
并得到了下面的图像,它看起来比我目前得到的任何图像都更接近 Mandelbrot 集。但它看起来更像是一个周围散布着圆点的海星。
Image
作为参考,这是我改进前的初始代码:
# initial values
loop = 50
div = 50
clist = np.linspace(-2,2,div) + 1j*np.linspace(-1.5,1.5,div) # range of c values
all_results = []
for c in clist: # for each value of c
z = 0 # starting point
for a in range(0,loop):
negative = 0 # unstable
z = z**2 + c
if np.abs(z) > 2:
negative +=1
if negative > 2:
break
if negative == 0:
all_results.append([c,"blue"]) #converging
else:
all_results.append([c,"black"]) # not converging
绘图看起来不正确,因为在问题的代码中绘制了 z
(即迭代变量)。迭代 z = z*z + c
,Mandelbrot 集由 c
的那些实部、虚部对给出,对于它们,级数不发散。因此,如下所示对代码的小改动给出了正确的 Mandelbrot 图:
import pylab as plt
import numpy as np
# initial values
loop = 50 # number of interations
div = 600 # divisions
# all possible values of c
c = np.linspace(-2,2,div)[:,np.newaxis] + 1j*np.linspace(-2,2,div)[np.newaxis,:]
z = 0
for n in range(0,loop):
z = z**2 + c
plt.rcParams['figure.figsize'] = [12, 7.5]
p = c[abs(z) < 2] # removing c values for which z has diverged
plt.scatter(p.real, p.imag, color = "black" ) # plotting points
plt.xlabel("Real")
plt.ylabel("i (imaginary)")
plt.xlim(-2,2)
plt.ylim(-1.5,1.5)
plt.savefig("plot.png")
plt.show()
或者,通过对问题中的代码进行另一个小的更改,可以使用 z
的值对图进行着色。可以存储 n
的值,其中系列的绝对值变得大于 2(意味着它发散),并用它为 Mandelbrot 集之外的点着色:
import pylab as plt
import numpy as np
# initial values
loop = 50 # number of interations
div = 600 # divisions
# all possible values of c
c = np.linspace(-2,2,div)[:,np.newaxis] + 1j*np.linspace(-2,2,div)[np.newaxis,:]
# array of ones of same dimensions as c
ones = np.ones(np.shape(c), np.int)
# Array that will hold colors for plot, initial value set here will be
# the color of the points in the mandelbrot set, i.e. where the series
# converges.
# For the code below to work, this initial value must at least be 'loop'.
# Here it is loop + 5
color = ones * loop + 5
z = 0
for n in range(0,loop):
z = z**2 + c
diverged = np.abs(z)>2
# Store value of n at which series was detected to diverge.
# The later the series is detected to diverge, the higher
# the 'color' value.
color[diverged] = np.minimum(color[diverged], ones[diverged]*n)
plt.rcParams['figure.figsize'] = [12, 7.5]
# contour plot with real and imaginary parts of c as axes
# and colored according to 'color'
plt.contourf(c.real, c.imag, color)
plt.xlabel("Real($c$)")
plt.ylabel("Imag($c$)")
plt.xlim(-2,2)
plt.ylim(-1.5,1.5)
plt.savefig("plot.png")
plt.show()
我正在尝试绘制 Mandelbrot 集的图,但在绘制预期图时遇到了问题。
据我了解,Mandelbrot 集由值 c 组成,如果通过以下等式 z = z**2 + c 进行迭代,它将收敛。我使用了 z = 0 的初始值。
最初,我得到的是一条直线。我在网上寻找解决方案,看看我哪里出错了。特别是使用以下 link,我试图改进我的代码:
https://scipy-lectures.org/intro/numpy/auto_examples/plot_mandelbrot.html
这是我改进后的代码。我真的不明白使用 np.newaxis 的原因以及为什么我要绘制收敛的最终 z 值。我误解了 Mandelbrot 集的定义吗?
# initial values
loop = 50 # number of interations
div = 600 # divisions
# all possible values of c
c = np.linspace(-2,2,div)[:,np.newaxis] + 1j*np.linspace(-2,2,div)[np.newaxis,:]
z = 0
for n in range(0,loop):
z = z**2 + c
plt.rcParams['figure.figsize'] = [12, 7.5]
z = z[abs(z) < 2] # removing z values that diverge
plt.scatter(z.real, z.imag, color = "black" ) # plotting points
plt.xlabel("Real")
plt.ylabel("i (imaginary)")
plt.xlim(-2,2)
plt.ylim(-1.5,1.5)
plt.savefig("plot.png")
plt.show()
并得到了下面的图像,它看起来比我目前得到的任何图像都更接近 Mandelbrot 集。但它看起来更像是一个周围散布着圆点的海星。 Image
作为参考,这是我改进前的初始代码:
# initial values
loop = 50
div = 50
clist = np.linspace(-2,2,div) + 1j*np.linspace(-1.5,1.5,div) # range of c values
all_results = []
for c in clist: # for each value of c
z = 0 # starting point
for a in range(0,loop):
negative = 0 # unstable
z = z**2 + c
if np.abs(z) > 2:
negative +=1
if negative > 2:
break
if negative == 0:
all_results.append([c,"blue"]) #converging
else:
all_results.append([c,"black"]) # not converging
绘图看起来不正确,因为在问题的代码中绘制了 z
(即迭代变量)。迭代 z = z*z + c
,Mandelbrot 集由 c
的那些实部、虚部对给出,对于它们,级数不发散。因此,如下所示对代码的小改动给出了正确的 Mandelbrot 图:
import pylab as plt
import numpy as np
# initial values
loop = 50 # number of interations
div = 600 # divisions
# all possible values of c
c = np.linspace(-2,2,div)[:,np.newaxis] + 1j*np.linspace(-2,2,div)[np.newaxis,:]
z = 0
for n in range(0,loop):
z = z**2 + c
plt.rcParams['figure.figsize'] = [12, 7.5]
p = c[abs(z) < 2] # removing c values for which z has diverged
plt.scatter(p.real, p.imag, color = "black" ) # plotting points
plt.xlabel("Real")
plt.ylabel("i (imaginary)")
plt.xlim(-2,2)
plt.ylim(-1.5,1.5)
plt.savefig("plot.png")
plt.show()
或者,通过对问题中的代码进行另一个小的更改,可以使用 z
的值对图进行着色。可以存储 n
的值,其中系列的绝对值变得大于 2(意味着它发散),并用它为 Mandelbrot 集之外的点着色:
import pylab as plt
import numpy as np
# initial values
loop = 50 # number of interations
div = 600 # divisions
# all possible values of c
c = np.linspace(-2,2,div)[:,np.newaxis] + 1j*np.linspace(-2,2,div)[np.newaxis,:]
# array of ones of same dimensions as c
ones = np.ones(np.shape(c), np.int)
# Array that will hold colors for plot, initial value set here will be
# the color of the points in the mandelbrot set, i.e. where the series
# converges.
# For the code below to work, this initial value must at least be 'loop'.
# Here it is loop + 5
color = ones * loop + 5
z = 0
for n in range(0,loop):
z = z**2 + c
diverged = np.abs(z)>2
# Store value of n at which series was detected to diverge.
# The later the series is detected to diverge, the higher
# the 'color' value.
color[diverged] = np.minimum(color[diverged], ones[diverged]*n)
plt.rcParams['figure.figsize'] = [12, 7.5]
# contour plot with real and imaginary parts of c as axes
# and colored according to 'color'
plt.contourf(c.real, c.imag, color)
plt.xlabel("Real($c$)")
plt.ylabel("Imag($c$)")
plt.xlim(-2,2)
plt.ylim(-1.5,1.5)
plt.savefig("plot.png")
plt.show()