1st job -Numpy practice

1. Create a value of 1 and the inner boundary of the array is 0, the following legend:

[Note:] solving this problem can put all the values are set to 1, this is a big square; secondly, the boundary except small squares are all set to 0.
The title uses a slice of numpy principle. X multidimensional arrays follow the same principle [start: step: stop] is.
[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
[1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]
[1. 0.0 0. 0. 0. 0. 0. 0. 1.]
[1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]
[1. 0. 0. 0. 0. 0 0. 0. 0. 1.]
[1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]
[1. 0. 0. 0. 0. 0. 0. 0. 0 1.]
[1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]
[1. 0. 0. 0. 0. 0. 0. 0. 0. 1.]
[1 1. 1. 1. 1. 1. 1. 1. 1. 1.]

1 import numpy as np
2 a=np.ones((10,10))
3 a[1:-1,1:-1]=0
4 print(a)

2. Create a value on the main diagonal array 1,2,3,4 5x5 matrix, the following legend:

[1000]
[0200]
[0030]
[0004 ]

1  import numpy as for example
 2 a = np.arange (1.5 )
 3 z = np.diag (a)
 four  print (z)

2. Create a value on the main diagonal array 1,2,3,4 5x5 matrix, the following legend:

[1000]
[0200]
[0030]
[0004 ]

1  import numpy as example
 2 with np.random.random = ((10,10 ))
 3 zmax, zmin = z.max () z.min ()
 4 z = (z-Zmin) / (zmax- m and n)
 5  print (z)