¿Cuál es la diferencia entre NumPy append
y concatenate
?
Mi observación es que concatenate
es un poco más rápido y append
aplanar la matriz si no se especifica el eje.
In [52]: print a [[1 2] [3 4] [5 6] [5 6] [1 2] [3 4] [5 6] [5 6] [1 2] [3 4] [5 6] [5 6] [5 6]] In [53]: print b [[1 2] [3 4] [5 6] [5 6] [1 2] [3 4] [5 6] [5 6] [5 6]] In [54]: timeit -n 10000 -r 5 np.concatenate((a, b)) 10000 loops, best of 5: 2.05 µs per loop In [55]: timeit -n 10000 -r 5 np.append(a, b, axis = 0) 10000 loops, best of 5: 2.41 µs per loop In [58]: np.concatenate((a, b)) Out[58]: array([[1, 2], [3, 4], [5, 6], [5, 6], [1, 2], [3, 4], [5, 6], [5, 6], [1, 2], [3, 4], [5, 6], [5, 6], [5, 6], [1, 2], [3, 4], [5, 6], [5, 6], [1, 2], [3, 4], [5, 6], [5, 6], [5, 6]]) In [59]: np.append(a, b, axis = 0) Out[59]: array([[1, 2], [3, 4], [5, 6], [5, 6], [1, 2], [3, 4], [5, 6], [5, 6], [1, 2], [3, 4], [5, 6], [5, 6], [5, 6], [1, 2], [3, 4], [5, 6], [5, 6], [1, 2], [3, 4], [5, 6], [5, 6], [5, 6]]) In [60]: np.append(a, b) Out[60]: array([1, 2, 3, 4, 5, 6, 5, 6, 1, 2, 3, 4, 5, 6, 5, 6, 1, 2, 3, 4, 5, 6, 5, 6, 5, 6, 1, 2, 3, 4, 5, 6, 5, 6, 1, 2, 3, 4, 5, 6, 5, 6, 5, 6])
np.append
utiliza np.concatenate
:
def append(arr, values, axis=None): arr = asanyarray(arr) if axis is None: if arr.ndim != 1: arr = arr.ravel() values = ravel(values) axis = arr.ndim-1 return concatenate((arr, values), axis=axis)