以下是顺序开始的numpy操作练习，水平欠佳，请多包涵。
import numpy as np
a = np.array([1,1,1,1])
b = np.array([[1],[1],[1],[1]])
print(a+b)
c = np.array([[1,1,1,1]])
print(c+b)
运行结果（不必要）
[[2 2 2 2]
[2 2 2 2]
[2 2 2 2]
[2 2 2 2]]
[[2 2 2 2]
[2 2 2 2]
[2 2 2 2]
[2 2 2 2]]
import numpy as np
W = np.array([[1,1,1],[2,2,2]])
#array[1,2]
W[:,1]
#array[2,2,2]
W[:,1] = np.array([5,5])
print(W)
运行结果
[[1 5 1]
[2 5 2]]
import numpy as np
matrix = [
[1,2,3,4],
[5,6,7,8],
[9,10,11,12]
]
p1 = np.delete(matrix, 1, 0)
print('>>>>p1>>>>\n',p1)
p2 = np.delete(matrix, 1, 1)
print('>>>>p2>>>>\n',p2)
p3 = np.delete(matrix, 1)
print('>>>>p3>>>>\n',p3)
p4 = np.delete(matrix, [0,1], 1)
print('>>>>p4>>>>\n',p4)
运行结果
>>>>p1>>>>
[[ 1 2 3 4]
[ 9 10 11 12]]
>>>>p2>>>>
[[ 1 3 4]
[ 5 7 8]
[ 9 11 12]]
>>>>p3>>>>
[ 1 3 4 5 6 7 8 9 10 11 12]
>>>>p4>>>>
[[ 3 4]
[ 7 8]
[11 12]]
import numpy as np
matrix = [
[1,2,3,4],
[5,6,7,8],
[9,10,11,12]
]
m1 = np.append(matrix,[[1,1,1,1]],axis=0)
print('>>>>m1>>>>\n',m1)
m2 = np.append(matrix,[[1],[1],[1]],axis=1)
print('>>>>m2>>>>\n',m2)
m3 = np.append(matrix,[1,1,1,1])
print('>>>>m3>>>>\n',m3)
运行结果
>>>>m1>>>>
[[ 1 2 3 4]
[ 5 6 7 8]
[ 9 10 11 12]
[ 1 1 1 1]]
>>>>m2>>>>
[[ 1 2 3 4 1]
[ 5 6 7 8 1]
[ 9 10 11 12 1]]
>>>>m3>>>>
[ 1 2 3 4 5 6 7 8 9 10 11 12 1 1 1 1]
import numpy as np
a1 = np.random.choice(7,5)
print(a1)
a2 = np.random.choice([0,1,2,3,4,5,6],5)
print(a2)
a3 = np.random.choice(np.array([0,1,2,3,4,5,6]),5)
print(a3)
a4 = np.random.choice([0,1,2,3,4,5,6],5,replace=False)
print(a4)
a5 = np.random.choice(np.array([0,1,2,3,4,5,6]),5,p=[0.1,0.1,0.1,0.1,0.1,0.1,0.4])
print(a5)
运行结果
[2 5 3 4 4]
[5 2 6 6 5]
[0 1 0 3 6]
[6 4 1 2 0]
[4 3 6 3 2]
import numpy as np
a = np.array([[1,1,1],[2,2,2],[0,3,6]])
print(a)
b1 = np.argmax(a)
print(b1)
b2 = np.argmax(a, axis=0)
print(b2)
b3 = np.argmax(a, axis=1)
print(b3)
运行结果
[[1 1 1]
[2 2 2]
[0 3 6]]
8
[1 2 2]
[0 0 2]
import numpy as np
y1 = np.linspace(-10.0,10.0)
print(y1)
y2 = np.linspace(1,10,10)
print(y2)
y3 = np.linspace(1,10,10,endpoint=False)
print(y3)
y4= np.linspace(1, 10, 6, retstep=True)
print(y4)
运行结果
[-10. -9.59183673 -9.18367347 -8.7755102 -8.36734694
-7.95918367 -7.55102041 -7.14285714 -6.73469388 -6.32653061
-5.91836735 -5.51020408 -5.10204082 -4.69387755 -4.28571429
-3.87755102 -3.46938776 -3.06122449 -2.65306122 -2.24489796
-1.83673469 -1.42857143 -1.02040816 -0.6122449 -0.20408163
0.20408163 0.6122449 1.02040816 1.42857143 1.83673469
2.24489796 2.65306122 3.06122449 3.46938776 3.87755102
4.28571429 4.69387755 5.10204082 5.51020408 5.91836735
6.32653061 6.73469388 7.14285714 7.55102041 7.95918367
8.36734694 8.7755102 9.18367347 9.59183673 10. ]
[ 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.]
[1. 1.9 2.8 3.7 4.6 5.5 6.4 7.3 8.2 9.1]
(array([ 1. , 2.8, 4.6, 6.4, 8.2, 10. ]), 1.8)
import numpy as np
x = np.array([[1,2,3],[4,5,6],[1,2,3]])
x.flatten()
print(x)
x.ravel()
print(x)
x.ravel('F')
print(x)
x.flatten('F')
print(x)
x.flatten()[1] = 20
print(x)
x.ravel()[1] = 20
print(x)
x.reshape(1,-1)
print(x)
x = np.array([1,2,3,6,7,8])
x[None,:]
print(x)
x[:,None]
print(x)
x[np.newaxis, :]
print(x)
运行结果
[[1 2 3]
[4 5 6]
[1 2 3]]
[[1 2 3]
[4 5 6]
[1 2 3]]
[[1 2 3]
[4 5 6]
[1 2 3]]
[[1 2 3]
[4 5 6]
[1 2 3]]
[[1 2 3]
[4 5 6]
[1 2 3]]
[[ 1 20 3]
[ 4 5 6]
[ 1 2 3]]
[[ 1 20 3]
[ 4 5 6]
[ 1 2 3]]
[1 2 3 6 7 8]
[1 2 3 6 7 8]
[1 2 3 6 7 8]
import numpy as np
x = np.array([[1,2,3],[2,3,4]])
np.prod(x)
print(x)
np.prod(x,axis=1)
print(x)
np.prod(x,axis=0)
print(x)
运行结果
[[1 2 3]
[2 3 4]]
[[1 2 3]
[2 3 4]]
[[1 2 3]
[2 3 4]]
import numpy as np
x = np.array([[1,2,3],[-3,2,4],[5,-2,9]])
y1 = np.maximum(0,x)
y2 = np.minimum(0,x)
x1 = x.copy()
x1[x1 < 0] = 0
x2 = x.copy()
x2[x2 > 0] = 0
print(x,y1,y2,x1,x2)
运行结果
[[ 1 2 3]
[-3 2 4]
[ 5 -2 9]] [[1 2 3]
[0 2 4]
[5 0 9]] [[ 0 0 0]
[-3 0 0]
[ 0 -2 0]] [[1 2 3]
[0 2 4]
[5 0 9]] [[ 0 0 0]
[-3 0 0]
[ 0 -2 0]]
import numpy as np
x = np.array([[1,2,3],[-3,2,4],[5,-2,9]])
x1 = x.copy()
x2 = x
x2[x2>0] = 0
x3 = x[2]
x3[2] = 100
print(x,x1,x2,x3)
运行结果
[[ 0 0 0]
[ -3 0 0]
[ 0 -2 100]] [[ 1 2 3]
[-3 2 4]
[ 5 -2 9]] [[ 0 0 0]
[ -3 0 0]
[ 0 -2 100]] [ 0 -2 100]
import numpy as np
x = np.array([[1,2,3],[4,5,6]])
np.zeros_like(x)
print(x)
运行结果
[[1 2 3]
[4 5 6]]
import numpy as np
n = np.random.rand(3,4)
print(n)
运行结果
[[0.68349442 0.24978251 0.66088426 0.62908655]
[0.3180283 0.84395154 0.47903128 0.85330565]
[0.17018147 0.32764189 0.49378254 0.02179647]]
import numpy as np
x = np.random.randn(2,3)
y = np.multiply(0.1,np.random.randn(2,3))+0.5
print(x,y)
运行结果
[[-0.07092933 1.3036258 0.52427686]
[-0.31677738 0.27788768 -1.01646193]] [[0.67346834 0.43525842 0.38115849]
[0.66065731 0.3363384 0.5394227 ]]
import numpy as np
z = np.random.randint(2,9,(2,3))
m = np.random.randint(9,size = (2,3))
print(z,m)
运行结果
[[7 5 4]
[7 5 5]] [[3 6 2]
[6 2 0]]
#判别
x = 'You are right'
type(x)
str
assert type(x)==str, 'x is not str'
x = [1,2,3]
type(x)
list
assert type(x)==str, ‘x is not str’
Traceback (most recent call last):
File "<ipython-input-29-7613f9660e71>", line 1
assert type(x)==str, ‘x is not str’
^
SyntaxError: invalid character in identifier
import numpy as np
A = np.arange(95,99).reshape(2,2)
b = np.array([[[1,2],[3,4]],[[3,4],[7,8]],[[4,5],[1,2]]])
print(A,b)
运行结果
[[95 96]
[97 98]] [[[1 2]
[3 4]]
[[3 4]
[7 8]]
[[4 5]
[1 2]]]
import numpy as np
x = np.empty([3,2], dtype = int)
print (x)
运行结果
[[1587560704 607]
[ 0 0]
[ 1 6881396]]
import numpy as np
c = np.array([[1,2],[3,4]])
c.astype(np.float32)
print(c)
运行结果
[[1 2]
[3 4]]
import numpy as np
x = np.array([1,3,5])
y = np.array([4,6])
XX,YY = np.meshgrid(x,y)
print(XX,YY)
运行结果
[[1 3 5]
[1 3 5]] [[4 4 4]
[6 6 6]]
import numpy as np
x = np.array([[3,4,5],[1,3,4]])
y = np.array([[1,1,1],[2,2,2]])
np.hstack((x,y))
print(x,y)
np.vstack((x,y))
print(x,y)
运行结果
[[3 4 5]
[1 3 4]] [[1 1 1]
[2 2 2]]
[[3 4 5]
[1 3 4]] [[1 1 1]
[2 2 2]]
import numpy as np
a = np.array([0.125,0.568,5.688])
np.round(a)
#np.round(a,decimals = 2)
#array([0.12, 0.57, 5.69])
#np.floor(a)
#array([0., 0., 5.])
#np.ceil(a)
#array([1., 1., 6.])
运行结果
array([0., 1., 6.])
import numpy as np
c = np.array([1,2,5,4])
c[:,np.newaxis]
print(c)
运行结果
[1 2 5 4]
import numpy as np
a = np.array([[1,2,3],[4,5,6]])
a = np.array([[1,2,3,6],[4,5,6,6]])
a1 = a.reshape((1,2,4))
b = np.array([[3,4,5,6],[1,2,3,4],[4,5,5,5]])
b1 = b.reshape((1,3,4)).transpose((1,0,2))
print(a,b,a1,b1,a1+b1)
运行结果
[[1 2 3 6]
[4 5 6 6]] [[3 4 5 6]
[1 2 3 4]
[4 5 5 5]] [[[1 2 3 6]
[4 5 6 6]]] [[[3 4 5 6]]
[[1 2 3 4]]
[[4 5 5 5]]] [[[ 4 6 8 12]
[ 7 9 11 12]]
[[ 2 4 6 10]
[ 5 7 9 10]]
[[ 5 7 8 11]
[ 8 10 11 11]]]
import numpy as np
a = np.array([2,2,3,4,5,5,6,7])
a[0:7:2]
运行结果
array([2, 3, 5, 6])
import numpy as np
a = np.array([2,2,3,4,5,5,6,7])
a[0::2]
运行结果
array([2, 3, 5, 6])
import numpy as np
a = np.array([2,2,3,4,5,5,6,7])
a[::-1]
运行结果
array([7, 6, 5, 5, 4, 3, 2, 2])
import numpy as np
a = np.array([2,2,3,4,5,5,6,7])
s = slice(0,7,2)
a[s]
运行结果
array([2, 3, 5, 6])
