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Class MaskedIterator

numpy/ma/core.py:2660–2766  ·  view source on GitHub ↗

Flat iterator object to iterate over masked arrays. A `MaskedIterator` iterator is returned by ``x.flat`` for any masked array `x`. It allows iterating over the array as if it were a 1-D array, either in a for-loop or by calling its `next` method. Iteration is done in C-contig

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2658
2659
2660class MaskedIterator:
2661 """
2662 Flat iterator object to iterate over masked arrays.
2663
2664 A `MaskedIterator` iterator is returned by ``x.flat`` for any masked array
2665 `x`. It allows iterating over the array as if it were a 1-D array,
2666 either in a for-loop or by calling its `next` method.
2667
2668 Iteration is done in C-contiguous style, with the last index varying the
2669 fastest. The iterator can also be indexed using basic slicing or
2670 advanced indexing.
2671
2672 See Also
2673 --------
2674 MaskedArray.flat : Return a flat iterator over an array.
2675 MaskedArray.flatten : Returns a flattened copy of an array.
2676
2677 Notes
2678 -----
2679 `MaskedIterator` is not exported by the `ma` module. Instead of
2680 instantiating a `MaskedIterator` directly, use `MaskedArray.flat`.
2681
2682 Examples
2683 --------
2684 >>> import numpy as np
2685 >>> x = np.ma.array(arange(6).reshape(2, 3))
2686 >>> fl = x.flat
2687 >>> type(fl)
2688 <class 'numpy.ma.MaskedIterator'>
2689 >>> for item in fl:
2690 ... print(item)
2691 ...
2692 0
2693 1
2694 2
2695 3
2696 4
2697 5
2698
2699 Extracting more than a single element b indexing the `MaskedIterator`
2700 returns a masked array:
2701
2702 >>> fl[2:4]
2703 masked_array(data = [2 3],
2704 mask = False,
2705 fill_value = 999999)
2706
2707 """
2708
2709 def __init__(self, ma):
2710 self.ma = ma
2711 self.dataiter = ma._data.flat
2712
2713 if ma._mask is nomask:
2714 self.maskiter = None
2715 else:
2716 self.maskiter = ma._mask.flat
2717

Callers 1

flatMethod · 0.85

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