How do I do this? (in a computationally efficient way)
arr1 = np.array([0, 4, 8, 12, 16])
arr2 = np.array([1, 5, 9, 13, 17])
arr3 = np.array([2, 6, 10, 14, 18])
arr4 = np.array([3, 7, 11, 15, 19])
what_i_want = [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19]
You can directly pass a list of arrays to np.ravel to flatten in Fortran order:
np.ravel([arr1, arr2, arr3, arr4], 'F')
Slower alternative with stack and ravel:
np.stack([arr1, arr2, arr3, arr4]).ravel('F')
output:
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19])
using transpose of np.vstack and flattening:
np.vstack((arr1, arr2, arr3, arr4)).T.ravel()
# np.array((arr1, arr2, arr3, arr4)).T.ravel() # alternative way
"""
np.vstack
[[ 0 4 8 12 16]
[ 1 5 9 13 17]
[ 2 6 10 14 18]
[ 3 7 11 15 19]]
np.vstack().T
[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]
[12 13 14 15]
[16 17 18 19]]
np.vstack().T.ravel()
[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19]
"""
Try with the following:
np.array([arr1, arr2, arr3, arr4]).T.reshape(1, -1)[0]
Output:
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19])
I think this is the easiest way to reach your goal.
import numpy as np arr1 = np.array([0, 4, 8, 12, 16]) arr2 = np.array([1, 5, 9, 13, 17]) arr3 = np.array([2, 6, 10, 14, 18]) arr4 = np.array([3, 7, 11, 15, 19]) newArray = np.array((arr1, arr2, arr3, arr4)).T.ravel() print(newArray)
what_you_want:
Output :
[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19]
#importing dependencies
import numpy as np
arr1 = np.array([0, 4, 8, 12, 16])
arr2 = np.array([1, 5, 9, 13, 17])
arr3 = np.array([2, 6, 10, 14, 18])
arr4 = np.array([3, 7, 11, 15, 19])
#creating an array to store results
X = []
#writing a loop to add each element(i) of the arr1,2,3,4 in the result. but
all the arrays must be of the same lenght as are in your case.
for i in range (0 , len(arr1)):
X.append(arr1[i])
X.append(arr2[i])
X.append(arr3[i])
X.append(arr4[i])
print("X = " , X)
You can use np.concatenate like this:
what_you_want = np.concatenate((arr1, arr2, arr3, arr4))
Source: https://numpy.org/doc/stable/user/absolute_beginners.html#adding-removing-and-sorting-elements
You can also look this: https://numpy.org/doc/stable/reference/generated/numpy.concatenate.html?highlight=concatenate#numpy.concatenate
