If you are new to `Python`

, you should probably stop reading here.
But, if you have used `Python`

and `numpy`

, then read on. Before, that
try these bits of code.

import numpy
a = numpy.array([1,2])
a = a + 0.5j
print a

The "same thing", in a slightly different way.

import numpy
a = numpy.array([1,2])
a += 0.5j
print a

Both the code blocks, look really the same, until you look carefully.
Under normal circumstances `a = a + b`

and `a += b`

behave exactly
similarly, and we really don't need to bother about the differences
between them.

But, `+=`

, which is an augmented assignment operator, actually tries
to perform the operation in-place, unlike the other statement where
`+`

actually returns a new object which is again being referenced by
the name `a`

.

But, when dealing with `numpy`

arrays, this will lead to trouble.
When assigning to an array, it's `dtype`

is not changed and hence the
trouble.

The right way to use the augmented assignment operator, would be:

import numpy
a = numpy.array([1,2], dtype=complex)
a += 0.5j
print a

The same thing is explained in this thread. Also, Thanks to
Bhanukiran for asking me this.