Shape Manipulation

Transpose

Use the property T, the method transpose(axes: [Int]? = nil) or Matft.transpose(_:axes:).

let a = Matft.arange(start: 0, to: 27, by: 1, shape: [3,3,3])
print(a.T)
print(a.transpose(axes: [0,2,1]))
/*
mfarray = 
[[[	0,		9,		18],
[	3,		12,		21],
[	6,		15,		24]],

[[	1,		10,		19],
[	4,		13,		22],
[	7,		16,		25]],

[[	2,		11,		20],
[	5,		14,		23],
[	8,		17,		26]]], type=Int, shape=[3, 3, 3]
mfarray = 
[[[	0,		3,		6],
[	1,		4,		7],
[	2,		5,		8]],

[[	9,		12,		15],
[	10,		13,		16],
[	11,		14,		17]],

[[	18,		21,		24],
[	19,		22,		25],
[	20,		23,		26]]], type=Int, shape=[3, 3, 3]
*/

Reshape

Use the method reshape(_:) or Matft.reshape(_:newshape:).

let b = Matft.arange(start: 0, to: 16, by: 1, shape: [2,4,2])
print(b.reshape([4,4]))
print(b.reshape([1,2,1,8]))
/*
mfarray = 
[[	0,		1,		2,		3],
[	4,		5,		6,		7],
[	8,		9,		10,		11],
[	12,		13,		14,		15]], type=Int, shape=[4, 4]
mfarray = 
[[[[	0,		1,		2,		3,		4,		5,		6,		7]],

[[	8,		9,		10,		11,		12,		13,		14,		15]]]], type=Int, shape=[1, 2, 1, 8]
*/

Others

expand_dims, squeeze, broadcast_to, flatten, flip, swapaxes, moveaxis, roll, pad, concatenate, vstack, hstack and more are available. See NumPy Mapping › Conversion and Creation for the full list.