Create matrix 100×100 each row with next ordinal number
Question:
I try to create a matrix 100×100 which should have in each row next ordinal number like below:
I created a vector from 1 to 100 and then using for loop I copied this vector 100 times. I received an array with correct data so I tried to sort arrays using np.argsort, but it didn’t worked as I want (I don’t know even why there are zeros in after sorting).
Is there any option to get this matrix using another functions? I tried many approaches, but the final layout was not what I expected.
max_x = 101
z = np.arange(1,101)
print(z)
x = []
for i in range(1,max_x):
x.append(z.copy())
print(x)
y = np.argsort(x)
y
Answers:
argsort
returns the indices to sort by, that’s why you get zeros. You don’t need that, what you want is to transpose the array.
Make x
a numpy
array and use T
y = np.array(x).T
Output
[[ 1 1 1 ... 1 1 1]
[ 2 2 2 ... 2 2 2]
[ 3 3 3 ... 3 3 3]
...
[ 98 98 98 ... 98 98 98]
[ 99 99 99 ... 99 99 99]
[100 100 100 ... 100 100 100]]
You also don’t need to loop to copy the array, use np.tile
instead
z = np.arange(1, 101)
x = np.tile(z, (100, 1))
y = x.T
# or one liner
y = np.tile(np.arange(1, 101), (100, 1)).T
import numpy as np
np.asarray([ (k+1)*np.ones(100) for k in range(100) ])
Or simply
np.tile(np.arange(1,101),(100,1)).T
I try to create a matrix 100×100 which should have in each row next ordinal number like below:
I created a vector from 1 to 100 and then using for loop I copied this vector 100 times. I received an array with correct data so I tried to sort arrays using np.argsort, but it didn’t worked as I want (I don’t know even why there are zeros in after sorting).
Is there any option to get this matrix using another functions? I tried many approaches, but the final layout was not what I expected.
max_x = 101
z = np.arange(1,101)
print(z)
x = []
for i in range(1,max_x):
x.append(z.copy())
print(x)
y = np.argsort(x)
y
argsort
returns the indices to sort by, that’s why you get zeros. You don’t need that, what you want is to transpose the array.
Make x
a numpy
array and use T
y = np.array(x).T
Output
[[ 1 1 1 ... 1 1 1]
[ 2 2 2 ... 2 2 2]
[ 3 3 3 ... 3 3 3]
...
[ 98 98 98 ... 98 98 98]
[ 99 99 99 ... 99 99 99]
[100 100 100 ... 100 100 100]]
You also don’t need to loop to copy the array, use np.tile
instead
z = np.arange(1, 101)
x = np.tile(z, (100, 1))
y = x.T
# or one liner
y = np.tile(np.arange(1, 101), (100, 1)).T
import numpy as np
np.asarray([ (k+1)*np.ones(100) for k in range(100) ])
Or simply
np.tile(np.arange(1,101),(100,1)).T