python简单使用

 1 from random import random  //导入随机函数库
 2 Area=1000*1000　　　　　　　　//设置随机区域
 3 hits=0　　　　　　　　　　　　　//初始化计数值
 4 for i in range(1,Area+1):  //蒙特卡洛算法
 5         x,y=random(),random()
 6         dist=pow(x**2+y**2,0.5)
 7         if dist<=1.0:
 8                 hits=hits+1
 9 pi=4*(hits/Area)
10 print("圆周率值：{}".format(pi))

from cycler import cycler
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

# Define a list of markevery cases and color cases to plot
cases = [None,
         8,
         (30, 8),
         [16, 24, 30],
         [0, -1],
         slice(100, 200, 3),
         0.1,
         0.3,
         1.5,
         (0.0, 0.1),
         (0.45, 0.1)]

colors = [‘#1f77b4‘,
          ‘#ff7f0e‘,
          ‘#2ca02c‘,
          ‘#d62728‘,
          ‘#9467bd‘,
          ‘#8c564b‘,
          ‘#e377c2‘,
          ‘#7f7f7f‘,
          ‘#bcbd22‘,
          ‘#17becf‘,
          ‘#1a55FF‘]

# Configure rcParams axes.prop_cycle to simultaneously cycle cases and colors.
mpl.rcParams[‘axes.prop_cycle‘] = cycler(markevery=cases, color=colors)

# Create data points and offsets
x = np.linspace(0, 2 * np.pi)
offsets = np.linspace(0, 2 * np.pi, 11, endpoint=False)
yy = np.transpose([np.sin(x + phi) for phi in offsets])

# Set the plot curve with markers and a title
fig = plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.6, 0.75])

for i in range(len(cases)):
    ax.plot(yy[:, i], marker=‘o‘, label=str(cases[i]))
    ax.legend(bbox_to_anchor=(1.05, 1), loc=‘upper left‘, borderaxespad=0.)

plt.title(‘Support for axes.prop_cycle cycler with markevery‘)

plt.show()