What's the fastest way to convert an interleaved NumPy integer array to complex64?

I have a stream of incoming data that has interleaved real and imaginary integers. Converting these to complex64 values is the slowest operation in my program. This is my current approach:

import numpy as np

a = np.zeros(1000000, dtype=np.int16)
b = np.complex64(a[::2]) +开发者_如何学C np.complex64(1j) * np.complex64(a[1::2])

Can I do better without making a C extension or using something like cython? If I can't do better, what's my easiest approach using a technology like one of these?

---

[~]
|1> import numpy as np

[~]
|2> a = np.zeros(1000000, dtype=np.int16)

[~]
|3> b = a.astype(np.float32).view(np.complex64)

[~]
|4> b.shape
(500000,)

[~]
|5> b.dtype
dtype('complex64')