# numpy.nditer¶

class numpy.nditer

Efficient multi-dimensional iterator object to iterate over arrays.

Notes

nditer supersedes flatiter. The iterator implementation behind nditer is also exposed by the Numpy C API.

The Python exposure supplies two iteration interfaces, one which follows the Python iterator protocol, and another which mirrors the C-style do-while pattern. The native Python approach is better in most cases, but if you need the iterator’s coordinates or index, use the C-style pattern.

Examples

Here is how we might write an iter_add function, using the Python iterator protocol:

```def iter_add_py(x, y, out=None):
it = np.nditer([x, y, out], [],
for (a, b, c) in it:
return it.operands[2]
```

Here is the same function, but following the C-style pattern:

```def iter_add(x, y, out=None):

it = np.nditer([x, y, out], [],

while not it.finished:
it.iternext()

return it.operands[2]
```

Here is an example outer product function:

```def outer_it(x, y, out=None):
mulop = np.multiply

it = np.nditer([x, y, out], ['external_loop'],
op_axes=[range(x.ndim)+[-1]*y.ndim,
[-1]*x.ndim+range(y.ndim),
None])

for (a, b, c) in it:
mulop(a, b, out=c)

return it.operands[2]

>>> a = np.arange(2)+1
>>> b = np.arange(3)+1
>>> outer_it(a,b)
array([[1, 2, 3],
[2, 4, 6]])```

Here is an example function which operates like a “lambda” ufunc:

```def luf(lamdaexpr, *args, **kwargs):
"luf(lambdaexpr, op1, ..., opn, out=None, order='K', casting='safe', buffersize=0)"
nargs = len(args)
op = (kwargs.get('out',None),) + args
it = np.nditer(op, ['buffered','external_loop'],
order=kwargs.get('order','K'),
casting=kwargs.get('casting','safe'),
buffersize=kwargs.get('buffersize',0))
while not it.finished:
it[0] = lamdaexpr(*it[1:])
it.iternext()
return it.operands[0]

>>> a = np.arange(5)
>>> b = np.ones(5)
>>> luf(lambda i,j:i*i + j/2, a, b)
array([  0.5,   1.5,   4.5,   9.5,  16.5])```

Attributes

 dtypes finished has_delayed_bufalloc has_index has_multi_index iterationneedsapi iterindex itersize ndim(a) Return the number of dimensions of an array. nop operands shape(a) Return the shape of an array.

Methods

 copy(a) Return an array copy of the given object. debug_print enable_external_loop iternext next remove_axis remove_multi_index reset

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numpy.fill_diagonal