[Numpy-discussion] view 1d array as overlapping segments?

[Davide]

Here is some *working* code i wrote once. It uses strides, look at the 
docs for what it is.

from numpy.lib import stride_tricks

def overlap_array( y, len_blocks, overlap=0 ):
     """
     Make use of strides to return a two dimensional whose
     rows come from a one dimensional array. Strides are
     used to return rows that partially overlap.

     Parameters
     ----------
     y        : a one dimensional array
     len_blocks : the row length. The length of chunks from y.
     overlap  : number of elements that overlap. From 0 (no
                overlap) to len_blocks-1 (almost full overlap).

     Returns
     -------
     x        : a strided array

     """
     overlap = int(overlap)
     len_blocks = int(len_blocks)

     if not type(y) == np.ndarray:
         raise ValueError( 'y must be a numpy.ndarray' )

     if overlap >= len_blocks:
         raise ValueError( 'overlap must be less than n_points' )

     # compute shape and strides of the strided vector
     strides = ( (len_blocks - overlap)*y.itemsize, y.itemsize )
     shape = ( 1 + (y.nbytes - len_blocks*y.itemsize)/strides[0], 
len_blocks)

     # create a strided array
     return stride_tricks.as_strided( y, shape=shape, strides=strides )

On 03/07/2011 04:01 PM, Neal Becker wrote:
> reshape can view a 1d array as non-overlapping segments.
>
> Is there a convenient way to view a 1d array as a 2d array of overlapping
> segments?
>
> nonoverlapping:
> l: segment length
> k: overlap
> u is the 1d array
> v is a 2d array
>
> v[i] = u[l*i:(l+1)*i]
>
> overlapping:
> v[i] = u[l*i:(l+1)*i+k]
>
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