# -*- coding: utf-8 -*-

"""

@description:

@author:XuMing

"""

from __future__ import print_function

from __future__ import unicode_literals

import numpy as np

# 生成数组的函数

# arange 生成数组，[start,stop)

# arange(start, stop=None, step=1, dtype=None)

print(np.arange(5)) # [0 1 2 3 4]

a = np.arange(0, 2 * np.pi, np.pi / 4)

print(a)

# linspace

# linspace(start,stop,N)

# 产生N个等距分布在[start,stop]间的元素组成的数组，包括start,stop

print(np.linspace(0, 1, 5)) # [ 0. 0.25 0.5 0.75 1. ]

# logspace

# logspace(start, stop, N)

# 产生 N 个对数等距分布的数组，默认以10为底：

print(np.logspace(0, 1, 5))

# 产生的值为$\left[10^0, 10^{0.25},10^{0.5},10^{0.75},10^1\right]$。

# 二维平面中生成一个网格:meshgrid

x_ticks = np.linspace(-1, 1, 5)

y_ticks = np.linspace(-1, 1, 5)

x, y = np.meshgrid(x_ticks, y_ticks)

print(x_ticks)

print(x)

# 图例

import matplotlib.pyplot as plt

from matplotlib import cm

def f(x, y):

# sinc 函数

r = np.sqrt(x ** 2 + y ** 2)

result = np.sin(r) / r

result[r == 0] = 1.0

return result

x_ticks = np.linspace(-10, 10, 51)

y_ticks = np.linspace(-10, 10, 51)

x, y = np.meshgrid(x_ticks, y_ticks, sparse=True)

print(x) # x, y 中有很多冗余的元素，这里提供了一个 sparse 的选项去冗余

z = f(x, y)

fig = plt.figure()

ax = fig.add_subplot(111, projection='3d')

ax.plot_surface(x, y, z,

rstride=1, cstride=1,

cmap=cm.YlGnBu_r)

ax.set_xlabel('x')

ax.set_ylabel('y')

ax.set_zlabel('z')

plt.show()