To the large original array whose memory will not be released untilĪll arrays derived from it are garbage-collected. NumPy slicing creates a view instead of a copy as in the case ofīuilt-in Python sequences such as string, tuple and list.Ī small portion from a large array which becomes useless after theĮxtraction, because the small portion extracted contains a reference Interpreted as counting from the end of the array ( i.e., ifĪll arrays generated by basic slicing are always views The valid range is \(0 \le n_i < d_i\) where \(d_i\) is the Python, all indices are zero-based: for the i-th index \(n_i\),

Scalar representing the corresponding item. The simplest case of indexing with N integers returns an array EllipsisĪnd newaxis objects can be interspersed with these as Integer, or a tuple of slice objects and integers. (constructed by start:stop:step notation inside of brackets), an Basic slicing occurs when obj is a slice object Slicing and striding #īasic slicing extends Python’s basic concept of slicing to Nĭimensions. Unlike Fortran or IDL, where the first index represents the most Index usually represents the most rapidly changing memory location,