【小睿的ML之路】Numpy矩阵属性和矩阵操作篇

import numpy as np

print(np.arange(15))

a = np.arange(15).reshape(5,3) # 矩阵重组
print(a)

[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14]
[[ 0  1  2]
 [ 3  4  5]
 [ 6  7  8]
 [ 9 10 11]
 [12 13 14]]

a.shape # 属性：矩阵的行列

(5, 3)

a.ndim # 矩阵纬度

2

a.dtype.name #矩阵类型

'int32'

a.size #矩阵元素数

15

b= np.zeros((2,4,5)) 
print(b)
b.ndim

[[[0. 0. 0. 0. 0.]
  [0. 0. 0. 0. 0.]
  [0. 0. 0. 0. 0.]
  [0. 0. 0. 0. 0.]]

 [[0. 0. 0. 0. 0.]
  [0. 0. 0. 0. 0.]
  [0. 0. 0. 0. 0.]
  [0. 0. 0. 0. 0.]]]





3

np.zeros((3,4))  # 0矩阵

array([[0., 0., 0., 0.],
       [0., 0., 0., 0.],
       [0., 0., 0., 0.]])

np.ones((2,3,4),dtype=np.int32)

array([[[1, 1, 1, 1],
        [1, 1, 1, 1],
        [1, 1, 1, 1]],

       [[1, 1, 1, 1],
        [1, 1, 1, 1],
        [1, 1, 1, 1]]])

np.arange(10,30,5) # 开始，结束，步长

array([10, 15, 20, 25])

np.arange(0,2,0.2) 

array([0. , 0.2, 0.4, 0.6, 0.8, 1. , 1.2, 1.4, 1.6, 1.8])

np.arange(0,2,0.2).reshape(2,5)

array([[0. , 0.2, 0.4, 0.6, 0.8],
       [1. , 1.2, 1.4, 1.6, 1.8]])

np.random.random((2,3)) # 随机生成

array([[0.82026386, 0.16358246, 0.24346123],
       [0.67492434, 0.30967117, 0.20575276]])

from numpy import pi
np.linspace(0, 2*pi ,100) # 开始，结束，元素数。在区间内平均找到n个数

array([0.        , 0.06346652, 0.12693304, 0.19039955, 0.25386607,
       0.31733259, 0.38079911, 0.44426563, 0.50773215, 0.57119866,
       0.63466518, 0.6981317 , 0.76159822, 0.82506474, 0.88853126,
       0.95199777, 1.01546429, 1.07893081, 1.14239733, 1.20586385,
       1.26933037, 1.33279688, 1.3962634 , 1.45972992, 1.52319644,
       1.58666296, 1.65012947, 1.71359599, 1.77706251, 1.84052903,
       1.90399555, 1.96746207, 2.03092858, 2.0943951 , 2.15786162,
       2.22132814, 2.28479466, 2.34826118, 2.41172769, 2.47519421,
       2.53866073, 2.60212725, 2.66559377, 2.72906028, 2.7925268 ,
       2.85599332, 2.91945984, 2.98292636, 3.04639288, 3.10985939,
       3.17332591, 3.23679243, 3.30025895, 3.36372547, 3.42719199,
       3.4906585 , 3.55412502, 3.61759154, 3.68105806, 3.74452458,
       3.8079911 , 3.87145761, 3.93492413, 3.99839065, 4.06185717,
       4.12532369, 4.1887902 , 4.25225672, 4.31572324, 4.37918976,
       4.44265628, 4.5061228 , 4.56958931, 4.63305583, 4.69652235,
       4.75998887, 4.82345539, 4.88692191, 4.95038842, 5.01385494,
       5.07732146, 5.14078798, 5.2042545 , 5.26772102, 5.33118753,
       5.39465405, 5.45812057, 5.52158709, 5.58505361, 5.64852012,
       5.71198664, 5.77545316, 5.83891968, 5.9023862 , 5.96585272,
       6.02931923, 6.09278575, 6.15625227, 6.21971879, 6.28318531])

# numpy arrays加减乘除运算

a = np.array([20,30,40,50])
b = np.arange(4)
print(a)
print(b)

[20 30 40 50]
[0 1 2 3]

c=a-b
print(c)

[20 29 38 47]

c=c-1
print(c)

[19 28 37 46]

print(b**2)

[0 1 4 9]

print(a<35)

[ True  True False False]

print(a*b) # 求内积

[  0  30  80 150]

print(a)
print(b)
print(a.dot(b)) # 该函数的作用是获取两个元素a,b的乘积. 30+80+150=260

[20 30 40 50]
[0 1 2 3]
260

print(np.dot(a,b)) # 该函数的作用是获取两个元素a,b的乘积.

260