Stacking arrays
You can also concatenate and stack multiple existing arrays. Explore the output in the examples below. I think they should be pretty self-explanatory.
a = np.array([[1, 2], [3, 4]])
b = np.array([[5, 6]])
print(np.concatenate((a, b), axis=0))
## [[1 2]
## [3 4]
## [5 6]]
print(np.concatenate((a, b.T), axis=1))
## [[1 2 5]
## [3 4 6]]
c = np.array([1, 2, 3])
d = np.array([4, 5, 6])
print(np.stack((c, d), axis=0))
## [[1 2 3]
## [4 5 6]]
print(np.stack((c, d), axis=1))
## [[1 4]
## [2 5]
## [3 6]]
Again, there are specialised versions of np.stack():
np.vstack(tuple): same asnp.stack(tuple, axis=0)np.hstack(tuple): same asnp.stack(tuple, axis=1)np.dstack(tuple): same asnp.stack(tuple, axis=2)
Repeating an array
You can also repeat an array easily with np.repeat().
print(np.repeat(0, 2))
## [0 0]
x = np.array([[1, 2],[3, 4]])
print(x)
## [[1 2]
## [3 4]]
print(np.repeat(x, 2))
## [1 1 2 2 3 3 4 4]
print(np.repeat(x, 2, axis=0))
## [[1 2]
## [1 2]
## [3 4]
## [3 4]]
print(np.repeat(x, 2, axis=1))
## [[1 1 2 2]
## [3 3 4 4]]
# You can also specify the number of repeats individually
print(np.repeat(x, [1, 2], axis=0))
## [[1 2]
## [3 4]
## [3 4]]
print(np.repeat(x, [3, 2], axis=0))
## [[1 2]
## [1 2]
## [1 2]
## [3 4]
## [3 4]]