Array objects

np provides an N-dimensional array type, the ndarray, which describes a collection of “items” of the same type. The items can be indexed using for example N integers.

All ndarrays are homogenous: every item takes up the same size block of memory, and all blocks are interpreted in exactly the same way. How each item in the array is to be interpreted is specified by a separate data-type object, one of which is associated with every array. In addition to basic types (integers, floats, etc.), the data type objects can also represent data structures.

An item extracted from an array, e.g., by indexing, is represented by a Python object whose type is one of the array scalar types built in NumPy. The array scalars allow easy manipulation of also more complicated arrangements of data.

Note

A major difference to numpy.ndarray is that mxnet.np.ndarray’s scalar is a 0-dim ndarray instead of a scalar object (numpy.generic).

• The N-dimensional array (ndarray)
  • Constructing arrays
  • Indexing arrays
  • Internal memory layout of an ndarray
  • Array attributes
  • Array methods
  • Arithmetic, matrix multiplication, and comparison operations
  • Special methods
• Indexing
  • Basic Slicing and Indexing
  • Advanced Indexing
  • Detailed notes

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