Numpy学习练习代码 ——（一）

import numpy as np

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a = np.array([1,2,3])
print(a)
print(type(a))
print(a.dtype)
# 几行
print(a.ndim)
print(a.size)
print(a.shape)
print(a.data)
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a = np.array([[1,2,3],[4,5,6]])
b = np.array(((1,2,3),(4,5,6)))
c = np.array([(1,2,3),(4,5,6)])
print(a)
print(b)
print(c)

print(np.zeros((3,3)))
print(np.ones((3,3)))

print(np.arange(4,10))
print(np.arange(4,10,3))
print(np.arange(4,10,0.5))
# 开头和结尾所指定范围分成多少部分
print(np.linspace(0,10,5))
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A = np.arange(0,9).reshape(3,3)
print(A)
print(A+4)
print(A*2)
print(np.sin(A))
print(np.sqrt(A))
B = np.arange(12,21).reshape(3,3)
print(A+B)
print(A*B)
# 矩阵的积
print(np.dot(A,B))
print(A.dot(B))
print(np.dot(B,A))
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a = np.arange(10,19).reshape(3,3)
print(a)
# 取单个值
print(a[1,2])

a = np.arange(1,17).reshape(4,4)
print(a)
# 切一行
print(a[1,:])
# 切一列
print(a[:,2])
# 抽取小矩阵
print(a[0:3,1:4])
# 抽取索引不连续
print(a[[0,3],0:2])
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# 数组迭代
a = np.arange(11,27).reshape(4,4)
print(a)
# 遍历行
# for row in a:
#     print(row)
# 遍历每一个元素
# for i in a.flat:
#     print(i)
# 按列进行迭代(axis 控制行列)
num = np.apply_along_axis(np.mean,axis=0,arr=a)
print(num)
# 按行进行迭代(计算每一行的平均数)
num = np.apply_along_axis(np.mean,axis=1,arr=a)
print(num)

def foo(x):
    return x/2

num = np.apply_along_axis(foo,axis=0,arr=a)
print(num)
num = np.apply_along_axis(foo,axis=1,arr=a)
print(num)
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A = np.random.random((4,4))
# 布尔数组
print(A<0.5)
# 抽取小于0.5的元素
print(A[A<0.5])

a = np.random.random(12)
print(a)
A = a.reshape(3,4)
print(A)
a.shape = (3,4)
print(a)
# 变回原型
a = a.ravel()
print(a)
a.shape = (12)
print(a)
# 交换行列位置
print(A.transpose())
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A = np.ones((3,3))
B = np.zeros((3,3))
# 垂直连接
print(np.vstack((A,B)))
# 水平连接
print(np.hstack((A,B)))

A = np.arange(0,16).reshape(4,4)
B = np.array([1,2,3,4])
print(np.column_stack((A,B)))
print(np.row_stack((A,B)))

[B,C] = np.hsplit(A,2)
print(B)
print(C)
[B,C] = np.vsplit(A,2)
print(B)
print(C)
# 按列切分
[A1,A2,A3] = np.split(A,[1,3],axis=1)
print(A1)
print(A2)
print(A3)
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a = np.array([1,2,3,4])
b = a
a[2] = 0
print(b)
c = a.copy()
a[1] = 0
print(a)
print(c)
# 注意与Python列表区分，列表操作得到的是副本
a = np.array([1,2,3,4])
c = a[0:2]
print(c)
a[0] = 0
print(c)
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m = np.arange(6).reshape(3,1,2)
n = np.arange(6).reshape(3,2,1)
print(m)
print(n)
# 结构不同需扩展维度
print(m+n)