numpy.tril_indices()
  • References/Python/NumPy/Routines/Indexing routines

numpy.tril_indices(n, k=0, m=None)

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Arrayterator.shape
  • References/Python/NumPy/Routines/Indexing routines/numpy.lib.Arrayterator

Arrayterator.shape The shape of the array to be iterated over. For an example, see

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numpy.indices()
  • References/Python/NumPy/Routines/Indexing routines

numpy.indices(dimensions, dtype=)

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numpy.ndenumerate()
  • References/Python/NumPy/Routines/Indexing routines

class numpy.ndenumerate(arr)

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numpy.ndindex()
  • References/Python/NumPy/Routines/Indexing routines

class numpy.ndindex(*shape)

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flatiter.coords
  • References/Python/NumPy/Routines/Indexing routines/numpy.flatiter

flatiter.coords An N-dimensional tuple of current coordinates. Examples

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numpy.s_
  • References/Python/NumPy/Routines/Indexing routines

numpy.s_ = A nicer way to build up index tuples for arrays. Note

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nditer.debug_print()
  • References/Python/NumPy/Routines/Indexing routines/numpy.nditer

nditer.debug_print() Print the current state of the

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numpy.r_
  • References/Python/NumPy/Routines/Indexing routines

numpy.r_ = Translates slice objects to concatenation along the first axis. This is a simple way to build up arrays quickly. There

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numpy.c_
  • References/Python/NumPy/Routines/Indexing routines

numpy.c_ = Translates slice objects to concatenation along the second axis. This is short-hand for np.r_['-1,2,0', index

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