Có cách nào hơn 'toán học' để làm như sau không:
1.2738 * [list_of_items]
Vì vậy, cho những gì tôi đang làm là:
[1.2738 * item for item in list_of_items]
Đã hỏi ngày 2 tháng 3 năm 2015 lúc 23:40Mar 2, 2015 at 23:40
David542David542David542
105K163 Huy hiệu vàng444 Huy hiệu bạc760 Huy hiệu đồng163 gold badges444 silver badges760 bronze badges
2
Tương đương toán học của những gì bạn mô tả là hoạt động của phép nhân bằng vô hướng cho một vectơ. Do đó, đề xuất của tôi sẽ là chuyển đổi danh sách các phần tử của bạn thành "vectơ" và sau đó nhân đó với vô hướng.
Một cách tiêu chuẩn để làm điều đó sẽ là sử dụng
[1.2738 * item for item in list_of_items]
0.Thay vì
1.2738 * [list_of_items]
Bạn có thể dùng
import numpy
1.2738 * numpy.array[list_of_items]
Đầu ra mẫu:
In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
Đã trả lời ngày 2 tháng 3 năm 2015 lúc 23:42Mar 2, 2015 at 23:42
Cách tiếp cận khác
map[lambda x:x*1.2738,list_of_items]
Đã trả lời ngày 2 tháng 3 năm 2015 lúc 23:43Mar 2, 2015 at 23:43
Levilevilevi
21.1k7 Huy hiệu vàng66 Huy hiệu bạc71 Huy hiệu đồng7 gold badges66 silver badges71 bronze badges
Đăng vào: ngày 12 tháng 3 năm 2021 bởi Deven March 12, 2021 by Deven
Trong bài viết này, bạn sẽ học cách nhân mảng với vô hướng trong Python.multiply array by scalar in python.
Hãy nói rằng bạn có 2 mảng cần được nhân với vô hướng
[1.2738 * item for item in list_of_items]
1.array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
Numpy nhân mảng theo vô hướng
Để nhân mảng với vô hướng trong Python, bạn có thể sử dụng phương thức
[1.2738 * item for item in list_of_items]
2.multiply array by scalar in
python, you can use [1.2738 * item for item in list_of_items]
2 method.import numpy as np
array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
np.multiply[array1,n]
np.multiply[array2,n]
Chia sẻ trên phương tiện truyền thông xã hội
///
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Đọc
Examples:
Input : mat[][] = {{2, 3} {5, 4}} k = 5 Output : 10 15 25 20 We multiply 5 with every element. Input : 1 2 3 4 5 6 7 8 9 k = 4 Output : 4 8 12 16 20 24 28 32 36
Bàn luậnscalar multiplication of a number k[scalar], multiply it on every entry in the matrix. and a matrix A is the matrix kA.
C++
[1.2738 * item for item in list_of_items]
3Đưa ra một ma trận và phần tử vô hướng K, nhiệm vụ của chúng tôi là tìm ra sản phẩm vô hướng của ma trận đó. & Nbsp; ví dụ: & nbsp; & nbsp;
[1.2738 * item for item in list_of_items]
7Sự nhân vô hướng của một số k [vô hướng], nhân nó trên mỗi mục nhập trong ma trận. và một ma trận A là ma trận ka. & nbsp;
1.2738 * [list_of_items]
4[1.2738 * item for item in list_of_items]
4 [1.2738 * item for item in list_of_items]
5 [1.2738 * item for item in list_of_items]
6[1.2738 * item for item in list_of_items]
8 [1.2738 * item for item in list_of_items]
91.2738 * [list_of_items]
0 1.2738 * [list_of_items]
11.2738 * [list_of_items]
0 1.2738 * [list_of_items]
3import numpy
1.2738 * numpy.array[list_of_items]
5import numpy
1.2738 * numpy.array[list_of_items]
6import numpy
1.2738 * numpy.array[list_of_items]
71.2738 * [list_of_items]
51.2738 * [list_of_items]
6 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 1.2738 * [list_of_items]
91.2738 * [list_of_items]
4import numpy
1.2738 * numpy.array[list_of_items]
0____26 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 import numpy
1.2738 * numpy.array[list_of_items]
4In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
4In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
5In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
4In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
71.2738 * [list_of_items]
0 import numpy
1.2738 * numpy.array[list_of_items]
91.2738 * [list_of_items]
5map[lambda x:x*1.2738,list_of_items]
21.2738 * [list_of_items]
5map[lambda x:x*1.2738,list_of_items]
41.2738 * [list_of_items]
7map[lambda x:x*1.2738,list_of_items]
6map[lambda x:x*1.2738,list_of_items]
71.2738 * [list_of_items]
51.2738 * [list_of_items]
0 In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
3[1.2738 * item for item in list_of_items]
8 [1.2738 * item for item in list_of_items]
91.2738 * [list_of_items]
0 1.2738 * [list_of_items]
11.2738 * [list_of_items]
0 1.2738 * [list_of_items]
3import numpy
1.2738 * numpy.array[list_of_items]
5map[lambda x:x*1.2738,list_of_items]
41.2738 * [list_of_items]
7import numpy as np
array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
np.multiply[array1,n]
np.multiply[array2,n]
1import numpy as np
array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
np.multiply[array1,n]
np.multiply[array2,n]
2import numpy
1.2738 * numpy.array[list_of_items]
0map[lambda x:x*1.2738,list_of_items]
41.2738 * [list_of_items]
7import numpy as np
array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
np.multiply[array1,n]
np.multiply[array2,n]
6map[lambda x:x*1.2738,list_of_items]
71.2738 * [list_of_items]
5import numpy
1.2738 * numpy.array[list_of_items]
71.2738 * [list_of_items]
51.2738 * [list_of_items]
6 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 1.2738 * [list_of_items]
9import numpy
1.2738 * numpy.array[list_of_items]
7import numpy
1.2738 * numpy.array[list_of_items]
0____26 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 import numpy
1.2738 * numpy.array[list_of_items]
4
import numpy
1.2738 * numpy.array[list_of_items]
1.2738 * [list_of_items]
1.2738 * [list_of_items]
import numpy
1.2738 * numpy.array[list_of_items]
1.2738 * [list_of_items]
0 import numpy
1.2738 * numpy.array[list_of_items]
91.2738 * [list_of_items]
51.2738 * [list_of_items]
0 In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
31.2738 * [list_of_items]
51.2738 * [list_of_items]
0 map[lambda x:x*1.2738,list_of_items]
01.2738 * [list_of_items]
51.2738 * [list_of_items]
6 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
21.2738 * [list_of_items]
5Input : mat[][] = {{2, 3} {5, 4}} k = 5 Output : 10 15 25 20 We multiply 5 with every element. Input : 1 2 3 4 5 6 7 8 9 k = 4 Output : 4 8 12 16 20 24 28 32 361
Input : mat[][] = {{2, 3} {5, 4}} k = 5 Output : 10 15 25 20 We multiply 5 with every element. Input : 1 2 3 4 5 6 7 8 9 k = 4 Output : 4 8 12 16 20 24 28 32 362
1.2738 * [list_of_items]
4Java
import numpy
1.2738 * numpy.array[list_of_items]
0____26 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 [1.2738 * item for item in list_of_items]
14[1.2738 * item for item in list_of_items]
08[1.2738 * item for item in list_of_items]
16import numpy
1.2738 * numpy.array[list_of_items]
5[1.2738 * item for item in list_of_items]
18import numpy
1.2738 * numpy.array[list_of_items]
7[1.2738 * item for item in list_of_items]
20 Input : mat[][] = {{2, 3} {5, 4}} k = 5 Output : 10 15 25 20 We multiply 5 with every element. Input : 1 2 3 4 5 6 7 8 9 k = 4 Output : 4 8 12 16 20 24 28 32 368
[1.2738 * item for item in list_of_items]
8 [1.2738 * item for item in list_of_items]
231.2738 * [list_of_items]
4Các
[1.2738 * item for item in list_of_items]
34[1.2738 * item for item in list_of_items]
35[1.2738 * item for item in list_of_items]
36[1.2738 * item for item in list_of_items]
29[1.2738 * item for item in list_of_items]
38[1.2738 * item for item in list_of_items]
29[1.2738 * item for item in list_of_items]
40 [1.2738 * item for item in list_of_items]
33[1.2738 * item for item in list_of_items]
34[1.2738 * item for item in list_of_items]
35[1.2738 * item for item in list_of_items]
44[1.2738 * item for item in list_of_items]
29[1.2738 * item for item in list_of_items]
46[1.2738 * item for item in list_of_items]
29[1.2738 * item for item in list_of_items]
481.2738 * [list_of_items]
51.2738 * [list_of_items]
0 [1.2738 * item for item in list_of_items]
52[1.2738 * item for item in list_of_items]
36Scalar Product Matrix is : 4 8 12 16 20 24 28 32 363
1.2738 * [list_of_items]
5map[lambda x:x*1.2738,list_of_items]
21.2738 * [list_of_items]
5[1.2738 * item for item in list_of_items]
58[1.2738 * item for item in list_of_items]
59map[lambda x:x*1.2738,list_of_items]
71.2738 * [list_of_items]
51.2738 * [list_of_items]
6 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 [1.2738 * item for item in list_of_items]
07[1.2738 * item for item in list_of_items]
08[1.2738 * item for item in list_of_items]
091.2738 * [list_of_items]
51.2738 * [list_of_items]
4import numpy
1.2738 * numpy.array[list_of_items]
0____26 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 [1.2738 * item for item in list_of_items]
14[1.2738 * item for item in list_of_items]
08[1.2738 * item for item in list_of_items]
16
import numpy
1.2738 * numpy.array[list_of_items]
5[1.2738 * item for item in list_of_items]
78[1.2738 * item for item in list_of_items]
79map[lambda x:x*1.2738,list_of_items]
7import numpy
1.2738 * numpy.array[list_of_items]
0[1.2738 * item for item in list_of_items]
821.2738 * [list_of_items]
5import numpy
1.2738 * numpy.array[list_of_items]
7import numpy
1.2738 * numpy.array[list_of_items]
7import numpy
1.2738 * numpy.array[list_of_items]
7Python 3
[1.2738 * item for item in list_of_items]
87[1.2738 * item for item in list_of_items]
88 Scalar Product Matrix is : 4 8 12 16 20 24 28 32 362
[1.2738 * item for item in list_of_items]
90 [1.2738 * item for item in list_of_items]
911.2738 * [list_of_items]
51.2738 * [list_of_items]
6 [1.2738 * item for item in list_of_items]
94[1.2738 * item for item in list_of_items]
95 [1.2738 * item for item in list_of_items]
96[1.2738 * item for item in list_of_items]
97import numpy
1.2738 * numpy.array[list_of_items]
0____26 1.2738 * [list_of_items]
00[1.2738 * item for item in list_of_items]
95 [1.2738 * item for item in list_of_items]
96[1.2738 * item for item in list_of_items]
97import numpy
1.2738 * numpy.array[list_of_items]
51.2738 * [list_of_items]
05[1.2738 * item for item in list_of_items]
88 1.2738 * [list_of_items]
051.2738 * [list_of_items]
08 1.2738 * [list_of_items]
091.2738 * [list_of_items]
10 1.2738 * [list_of_items]
11[1.2738 * item for item in list_of_items]
88[1.2738 * item for item in list_of_items]
88 1.2738 * [list_of_items]
141.2738 * [list_of_items]
15Các
1.2738 * [list_of_items]
261.2738 * [list_of_items]
27[1.2738 * item for item in list_of_items]
36[1.2738 * item for item in list_of_items]
29[1.2738 * item for item in list_of_items]
38[1.2738 * item for item in list_of_items]
29[1.2738 * item for item in list_of_items]
40 1.2738 * [list_of_items]
25Các
1.2738 * [list_of_items]
51.2738 * [list_of_items]
43[1.2738 * item for item in list_of_items]
88 [1.2738 * item for item in list_of_items]
361.2738 * [list_of_items]
51.2738 * [list_of_items]
471.2738 * [list_of_items]
51.2738 * [list_of_items]
491.2738 * [list_of_items]
7[1.2738 * item for item in list_of_items]
591.2738 * [list_of_items]
521.2738 * [list_of_items]
51.2738 * [list_of_items]
6 [1.2738 * item for item in list_of_items]
94[1.2738 * item for item in list_of_items]
95 [1.2738 * item for item in list_of_items]
961.2738 * [list_of_items]
58import numpy
1.2738 * numpy.array[list_of_items]
0____26 1.2738 * [list_of_items]
00[1.2738 * item for item in list_of_items]
95 [1.2738 * item for item in list_of_items]
961.2738 * [list_of_items]
58import numpy
1.2738 * numpy.array[list_of_items]
51.2738 * [list_of_items]
491.2738 * [list_of_items]
67[1.2738 * item for item in list_of_items]
88 [1.2738 * item for item in list_of_items]
791.2738 * [list_of_items]
52import numpy
1.2738 * numpy.array[list_of_items]
01.2738 * [list_of_items]
491.2738 * [list_of_items]
73C#
[1.2738 * item for item in list_of_items]
4 1.2738 * [list_of_items]
75Input : mat[][] = {{2, 3} {5, 4}} k = 5 Output : 10 15 25 20 We multiply 5 with every element. Input : 1 2 3 4 5 6 7 8 9 k = 4 Output : 4 8 12 16 20 24 28 32 366
1.2738 * [list_of_items]
77Input : mat[][] = {{2, 3} {5, 4}} k = 5 Output : 10 15 25 20 We multiply 5 with every element. Input : 1 2 3 4 5 6 7 8 9 k = 4 Output : 4 8 12 16 20 24 28 32 368
1.2738 * [list_of_items]
0 1.2738 * [list_of_items]
80Input : mat[][] = {{2, 3} {5, 4}} k = 5 Output : 10 15 25 20 We multiply 5 with every element. Input : 1 2 3 4 5 6 7 8 9 k = 4 Output : 4 8 12 16 20 24 28 32 368
[1.2738 * item for item in list_of_items]
8 [1.2738 * item for item in list_of_items]
91.2738 * [list_of_items]
01.2738 * [list_of_items]
85Scalar Product Matrix is : 4 8 12 16 20 24 28 32 369
1.2738 * [list_of_items]
0 1.2738 * [list_of_items]
31.2738 * [list_of_items]
41.2738 * [list_of_items]
51.2738 * [list_of_items]
6 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 1.2738 * [list_of_items]
9import numpy
1.2738 * numpy.array[list_of_items]
0____26 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 import numpy
1.2738 * numpy.array[list_of_items]
4import numpy
1.2738 * numpy.array[list_of_items]
5import numpy
1.2738 * numpy.array[list_of_items]
01import numpy
1.2738 * numpy.array[list_of_items]
7Input : mat[][] = {{2, 3} {5, 4}} k = 5 Output : 10 15 25 20 We multiply 5 with every element. Input : 1 2 3 4 5 6 7 8 9 k = 4 Output : 4 8 12 16 20 24 28 32 368
[1.2738 * item for item in list_of_items]
20 [1.2738 * item for item in list_of_items]
8 import numpy
1.2738 * numpy.array[list_of_items]
061.2738 * [list_of_items]
41.2738 * [list_of_items]
51.2738 * [list_of_items]
0import numpy
1.2738 * numpy.array[list_of_items]
10import numpy
1.2738 * numpy.array[list_of_items]
11import numpy
1.2738 * numpy.array[list_of_items]
12import numpy
1.2738 * numpy.array[list_of_items]
11import numpy
1.2738 * numpy.array[list_of_items]
141.2738 * [list_of_items]
51.2738 * [list_of_items]
0 map[lambda x:x*1.2738,list_of_items]
01.2738 * [list_of_items]
5map[lambda x:x*1.2738,list_of_items]
21.2738 * [list_of_items]
5import numpy
1.2738 * numpy.array[list_of_items]
21[1.2738 * item for item in list_of_items]
59map[lambda x:x*1.2738,list_of_items]
71.2738 * [list_of_items]
51.2738 * [list_of_items]
6 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
2import numpy
1.2738 * numpy.array[list_of_items]
0____26 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 import numpy
1.2738 * numpy.array[list_of_items]
4import numpy
1.2738 * numpy.array[list_of_items]
5import numpy
1.2738 * numpy.array[list_of_items]
35[1.2738 * item for item in list_of_items]
79map[lambda x:x*1.2738,list_of_items]
7import numpy
1.2738 * numpy.array[list_of_items]
0import numpy
1.2738 * numpy.array[list_of_items]
391.2738 * [list_of_items]
5import numpy
1.2738 * numpy.array[list_of_items]
7import numpy
1.2738 * numpy.array[list_of_items]
7import numpy
1.2738 * numpy.array[list_of_items]
7Input : mat[][] = {{2, 3}
{5, 4}}
k = 5
Output : 10 15
25 20
We multiply 5 with every element.
Input : 1 2 3
4 5 6
7 8 9
k = 4
Output : 4 8 12
16 20 24
28 32 36
8 [1.2738 * item for item in list_of_items]
20 [1.2738 * item for item in list_of_items]
8 import numpy
1.2738 * numpy.array[list_of_items]
06
[1.2738 * item for item in list_of_items]
[1.2738 * item for item in list_of_items]
import numpy
1.2738 * numpy.array[list_of_items]
import numpy
1.2738 * numpy.array[list_of_items]
441.2738 * [list_of_items]
51.2738 * [list_of_items]
0import numpy
1.2738 * numpy.array[list_of_items]
10import numpy
1.2738 * numpy.array[list_of_items]
49import numpy
1.2738 * numpy.array[list_of_items]
501.2738 * [list_of_items]
521.2738 * [list_of_items]
51.2738 * [list_of_items]
0 map[lambda x:x*1.2738,list_of_items]
01.2738 * [list_of_items]
51.2738 * [list_of_items]
6 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
2PHP
import numpy
1.2738 * numpy.array[list_of_items]
45 [1.2738 * item for item in list_of_items]
9import numpy
1.2738 * numpy.array[list_of_items]
47import numpy
1.2738 * numpy.array[list_of_items]
48import numpy
1.2738 * numpy.array[list_of_items]
5import numpy
1.2738 * numpy.array[list_of_items]
47import numpy
1.2738 * numpy.array[list_of_items]
80import numpy
1.2738 * numpy.array[list_of_items]
59import numpy
1.2738 * numpy.array[list_of_items]
82import numpy
1.2738 * numpy.array[list_of_items]
70import numpy
1.2738 * numpy.array[list_of_items]
84import numpy
1.2738 * numpy.array[list_of_items]
47import numpy
1.2738 * numpy.array[list_of_items]
80import numpy
1.2738 * numpy.array[list_of_items]
59import numpy
1.2738 * numpy.array[list_of_items]
82import numpy
1.2738 * numpy.array[list_of_items]
70import numpy
1.2738 * numpy.array[list_of_items]
90import numpy
1.2738 * numpy.array[list_of_items]
50Scalar Product Matrix is : 4 8 12 16 20 24 28 32 363
1.2738 * [list_of_items]
4import numpy
1.2738 * numpy.array[list_of_items]
71.2738 * [list_of_items]
5import numpy
1.2738 * numpy.array[list_of_items]
54 import numpy
1.2738 * numpy.array[list_of_items]
55Is
import numpy
1.2738 * numpy.array[list_of_items]
01.2738 * [list_of_items]
6 1.2738 * [list_of_items]
7import numpy
1.2738 * numpy.array[list_of_items]
70 import numpy
1.2738 * numpy.array[list_of_items]
60__370In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
06In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
02In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
111.2738 * [list_of_items]
5Input : mat[][] = {{2, 3} {5, 4}} k = 5 Output : 10 15 25 20 We multiply 5 with every element. Input : 1 2 3 4 5 6 7 8 9 k = 4 Output : 4 8 12 16 20 24 28 32 361
import numpy
1.2738 * numpy.array[list_of_items]
47Scalar Product Matrix is : 4 8 12 16 20 24 28 32 363
import numpy
1.2738 * numpy.array[list_of_items]
54 import numpy
1.2738 * numpy.array[list_of_items]
55import numpy
1.2738 * numpy.array[list_of_items]
47 In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
01In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
022.In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
06In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
02In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
081.2738 * [list_of_items]
4import numpy
1.2738 * numpy.array[list_of_items]
50 In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
13import numpy
1.2738 * numpy.array[list_of_items]
0In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
201.2738 * [list_of_items]
7In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
14import numpy
1.2738 * numpy.array[list_of_items]
80import numpy
1.2738 * numpy.array[list_of_items]
59import numpy
1.2738 * numpy.array[list_of_items]
82import numpy
1.2738 * numpy.array[list_of_items]
70In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
56[1.2738 * item for item in list_of_items]
79map[lambda x:x*1.2738,list_of_items]
7In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
14 In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
15import numpy
1.2738 * numpy.array[list_of_items]
47[1.2738 * item for item in list_of_items]
29import numpy
1.2738 * numpy.array[list_of_items]
50map[lambda x:x*1.2738,list_of_items]
7import numpy
1.2738 * numpy.array[list_of_items]
7In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
201.2738 * [list_of_items]
7[1.2738 * item for item in list_of_items]
59 In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
23import numpy as np
array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
np.multiply[array1,n]
np.multiply[array2,n]
6map[lambda x:x*1.2738,list_of_items]
7
In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
1.2738 * [list_of_items]
[1.2738 * item for item in list_of_items]
In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
import numpy as np
array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
np.multiply[array1,n]
np.multiply[array2,n]
map[lambda x:x*1.2738,list_of_items]
In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
64In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
65Is
1.2738 * [list_of_items]
4Is
1.2738 * [list_of_items]
5In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
20 import numpy as np
array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
np.multiply[array1,n]
np.multiply[array2,n]
6Scalar Product Matrix is : 4 8 12 16 20 24 28 32 363
import numpy
1.2738 * numpy.array[list_of_items]
5import numpy
1.2738 * numpy.array[list_of_items]
6import numpy
1.2738 * numpy.array[list_of_items]
7JavaScript
In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
84In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
85In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
84In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
87import numpy
1.2738 * numpy.array[list_of_items]
45 1.2738 * [list_of_items]
47map[lambda x:x*1.2738,list_of_items]
2In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
91In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
92map[lambda x:x*1.2738,list_of_items]
71.2738 * [list_of_items]
51.2738 * [list_of_items]
6 1.2738 * [list_of_items]
7In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
72 1.2738 * [list_of_items]
91.2738 * [list_of_items]
51.2738 * [list_of_items]
0 map[lambda x:x*1.2738,list_of_items]
01.2738 * [list_of_items]
51.2738 * [list_of_items]
6 1.2738 * [list_of_items]
71.2738 * [list_of_items]
0 array1 = np.array[[1, 2, 3]]
array2 = np.array[[[1, 2], [3, 4]]]
n = 5
2import numpy
1.2738 * numpy.array[list_of_items]
0map[lambda x:x*1.2738,list_of_items]
05[1.2738 * item for item in list_of_items]
79map[lambda x:x*1.2738,list_of_items]
71.2738 * [list_of_items]
5In [8]: list_of_items
Out[8]: [1, 2, 4, 5]
In [9]: import numpy
In [10]: 1.2738 * numpy.array[list_of_items]
Out[10]: array[[ 1.2738, 2.5476, 5.0952, 6.369 ]]
91map[lambda x:x*1.2738,list_of_items]
10map[lambda x:x*1.2738,list_of_items]
7import numpy
1.2738 * numpy.array[list_of_items]
7map[lambda x:x*1.2738,list_of_items]
13Output:
Scalar Product Matrix is : 4 8 12 16 20 24 28 32 36
PHP O[n2],
45 import numpy
1.2738 * numpy.array[list_of_items]
9[1.2738 * item for item in list_of_items]
47import numpy
1.2738 * numpy.array[list_of_items]
48 O[1], since no extra space has been taken.import numpy
1.2738 * numpy.array[list_of_items]