# numpy预览

import numpy as np
import matplotlib.pyplot as plt
# numpy预览
a = [1, 2, 3, 4]
print(a)
a = np.array(a)

print(a)
a = a + 1
print(a)
a = a + a
print(a)
a = np.array([1, 2, 1, 4])
b = np.array([2, 3, 4, 5])
print(a * b)
# [ 2  6  4 20] 对应元素乘法
print(a ** b)
# [   1    8    1 1024] 对应元素乘方

print(b[:2])  # 前两个元素
print(b[-2:])  # 后两个元素

# b = np.array([2, 3, 4, 5])
a = np.array([[1, 2], [3, 4], [5, 6]])
print(a.shape)
# a.shape = x, y 把a分成 x行 y列 也就是 x组 每组有y个元素 -1为自适应
# 每个行中有两个元素
a.shape = -1, 2
print(' a.shape = -1 ,2')
print(a)
# 每个行中有一个元素
a.shape = -1, 1
print('a.shape = -1,1')
print(a)
# 一共有3 行
a.shape = 3, -1
print('a.shape = 3, -1')
print(a)

a = np.array([1, 2, 3, 4])
b = np.array([2, 3, 4, 5])
a.shape = b.shape = 2, -1
""""
a = [[1,2]  b = [ [2,3]
     [3,4]        [4,5] 
    ]           ]
"""
print(a + b)  # 矩阵加法
print(a * b)  # 矩阵乘法
"""
a+b = [[3,5]  b = [ [2,6]
       [7,9]        [12,20] 
    ]           ]
"""
a = np.linspace(0, 2 * np.pi, 21)
# np.linspace(x, y, conunt) 在x，y中等距生成 count个数据
print(a)
b = np.sin(a)  # 取正弦值
print(b)
plt.plot(a, b)  # plot（x，y） 函数 绘图
plt.show()  # 展示
mask = b >= 0
print(a[mask])  # 输入A对应mask中true值 正值
plt.plot(a[mask], b[mask], 'ro')
plt.show()  # 作图