1import itertools
2
3a = [[1, 2], [3, 4], [5, 6]]
4list(itertools.chain.from_iterable(a))
5
6Output:- [1, 2, 3, 4, 5, 6]
1import numpy as np
2
3# 1D array
4one_dim_arr = np.array([1, 2, 3, 4, 5, 6])
5
6# to convert to 2D array
7# we can use the np.ndarray.reshape(shape) function
8# here shape is given by two integers seperated by a comma
9# the two integers specify m,n for the new matrix
10# ensure that the matrix that you are trying to generate
11# has a size that meets the number of elements in the 1D array.
12# for that make sure that
13# m * n = number of elements in the one dimentional array
14
15two_dim_arr = one_dim_arr.reshape(1, 6)
16
17#which returns a 2D array
18print(two_dim_arr)
19
20
21# confirmed by the array.ndim attribute
22print(two_dim_arr.ndim)
23
24# you can even specify one of the dimensions as unknown by passing -1
25# numpy will infer the length using the array and remaining dimensions
26
27two_dim_arr = one_dim_arr.reshape(1,-1)
1 int array[width * height];
2
3 int SetElement(int row, int col, int value)
4 {
5 array[width * row + col] = value;
6 }
1import numpy as np
2ini_array1 = np.array([[1, 2, 3], [2, 4, 5], [1, 2, 3]])
3result = ini_array1.flatten()