jax.numpy.ravel(a, order='C')[source]#

Return a contiguous flattened array.

LAX-backend implementation of numpy.ravel().

The JAX version of this function may in some cases return a copy rather than a view of the input.

Original docstring below.

A 1-D array, containing the elements of the input, is returned. A copy is made only if needed.

As of NumPy 1.10, the returned array will have the same type as the input array. (for example, a masked array will be returned for a masked array input)

  • a (array_like) – Input array. The elements in a are read in the order specified by order, and packed as a 1-D array.

  • order ({'C','F', 'A', 'K'}, optional) – The elements of a are read using this index order. β€˜C’ means to index the elements in row-major, C-style order, with the last axis index changing fastest, back to the first axis index changing slowest. β€˜F’ means to index the elements in column-major, Fortran-style order, with the first index changing fastest, and the last index changing slowest. Note that the β€˜C’ and β€˜F’ options take no account of the memory layout of the underlying array, and only refer to the order of axis indexing. β€˜A’ means to read the elements in Fortran-like index order if a is Fortran contiguous in memory, C-like order otherwise. β€˜K’ means to read the elements in the order they occur in memory, except for reversing the data when strides are negative. By default, β€˜C’ index order is used.


y – y is a contiguous 1-D array of the same subtype as a, with shape (a.size,). Note that matrices are special cased for backward compatibility, if a is a matrix, then y is a 1-D ndarray.

Return type: