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2-D arrays with numpy arange

so i am trying to build 2-D arrays with numpy arange function and i am having problems.

I would like to build a 2D array from int where the record at position i, j is (i + j). That is, such an array (it is recommended to use arange):

[[ 0  1  2  3  4  5  6  7  8  9]
 [ 1  2  3  4  5  6  7  8  9 10]
 [ 2  3  4  5  6  7  8  9 10 11]
 [ 3  4  5  6  7  8  9 10 11 12]
 [ 4  5  6  7  8  9 10 11 12 13]
 [ 5  6  7  8  9 10 11 12 13 14]
 [ 6  7  8  9 10 11 12 13 14 15]
 [ 7  8  9 10 11 12 13 14 15 16]
 [ 8  9 10 11 12 13 14 15 16 17]
 [ 9 10 11 12 13 14 15 16 17 18]]

I also need to build another array (100x100), where the value in index i, j is True if j is a divisor of I and False otherwise. That is, an array that looks like this:

[[False False False ..., False False False]
 [ True  True  True ...,  True  True  True]
 [ True False  True ..., False  True False]
 ..., 
 [ True False False ...,  True False False]
 [ True False False ..., False  True False]
 [ True False False ..., False False  True]]

I cannot use nested loops (although I can use loops to build lists), and I cannot use the np.array function. Currently, I have the following that works for the first part, but I would like to have it all as a single array, not multiple printed ones.

i = 0
j= 10
for i in range(10):
    lis = np.arange(i, j)
    i += 1
    j += 1
    print(np.array(lis))

If I could get some help, that would be great

EDIT: :

[0 1 2 3 4 5 6 7 8 9]
[ 1  2  3  4  5  6  7  8  9 10]
[ 2  3  4  5  6  7  8  9 10 11]
[ 3  4  5  6  7  8  9 10 11 12]
[ 4  5  6  7  8  9 10 11 12 13]
[ 5  6  7  8  9 10 11 12 13 14]
[ 6  7  8  9 10 11 12 13 14 15]
[ 7  8  9 10 11 12 13 14 15 16]
[ 8  9 10 11 12 13 14 15 16 17]
[ 9 10 11 12 13 14 15 16 17 18]

?

+4
4

:

np.add(*np.indices((nrow, ncol)))

nrow=5, ncol=6

array([[0, 1, 2, 3, 4, 5],
       [1, 2, 3, 4, 5, 6],
       [2, 3, 4, 5, 6, 7],
       [3, 4, 5, 6, 7, 8],
       [4, 5, 6, 7, 8, 9]])

numpy.arange, . , , nrow != ncol.

+2

numpy:

>>> a = np.arange(11)
>>> a[:,None]+a
array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10],  
  [ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11],  
  [ 2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12],  
  [ 3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13],  
  [ 4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14],  
  [ 5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15],  
  [ 6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16],  
  [ 7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17],  
  [ 8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18],  
  [ 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19],  
  [10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]])

@Divakar . , :

>>> (a%a[:,None])==0
array([[ True,  True,  True,  True,  True,  True,  True,  True,  True, True,  True],
   [ True,  True,  True,  True,  True,  True,  True,  True,  True, True,  True],
   [ True, False,  True, False,  True, False,  True, False,  True, False,  True],
   [ True, False, False,  True, False, False,  True, False, False, True, False],
   [ True, False, False, False,  True, False, False, False,  True, False, False],
   [ True, False, False, False, False,  True, False, False, False, False,  True],
   [ True, False, False, False, False, False,  True, False, False, False, False],
   [ True, False, False, False, False, False, False,  True, False, False, False],
   [ True, False, False, False, False, False, False, False,  True, False, False],
   [ True, False, False, False, False, False, False, False, False, True, False],
   [ True, False, False, False, False, False, False, False, False, False,  True]], dtype=bool)
+4

broadcasting -

a = np.arange(10)
out = (np.mod(a,a[:,None])==0) & (a[:,None]!=0)

-

In [511]: a = np.arange(10)

In [512]: print (np.mod(a,a[:,None])==0) & (a[:,None]!=0)
[[False False False False False False False False False False]
 [ True  True  True  True  True  True  True  True  True  True]
 [ True False  True False  True False  True False  True False]
 [ True False False  True False False  True False False  True]
 [ True False False False  True False False False  True False]
 [ True False False False False  True False False False False]
 [ True False False False False False  True False False False]
 [ True False False False False False False  True False False]
 [ True False False False False False False False  True False]
 [ True False False False False False False False False  True]]
+3

, :

np.array([range(i,i+10) for i in range(10)])

:

np.array([[i>0 and j%i==0 for j in range(10)] for i in range(10)])
0

Source: https://habr.com/ru/post/1661508/

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