Version 1.0b1 API Documentation generated by Endo 2006-08-14

Variables

• c_

  c_ = c_class()
  
  

• index_exp

  index_exp = _index_expression_class(1)
  
  

• makemat

  makemat = matrix.matrix
  
  

• mgrid

  mgrid = nd_grid(sparse = False)
  
  

• ogrid

  ogrid = nd_grid(sparse = True)
  
  

• r_

  r_ = r_class()
  
  

• s_

  s_ = _index_expression_class(0)
  
  

Classes

• c_class - Translates slice objects to concatenation along the second axis.
• concatenator - Translates slice objects to concatenation along an axis.
• nd_grid - Construct a "meshgrid" in N-dimensions.
• ndenumerate - A simple nd index iterator over an array.
• ndindex - Pass in a sequence of integers corresponding
• r_class - Translates slice objects to concatenation along the first axis.

Function summary

• ix_(args)
• unravel_index(x, dims)

Functions

• ix_(args)

  Construct an open mesh from multiple sequences.

  This function takes n 1-d sequences and returns n outputs with n dimensions each such that the shape is 1 in all but one dimension and the dimension with the non-unit shape value cycles through all n dimensions.

  Using ix_() one can quickly construct index arrays that will index the cross product.

  a[ix_([1,3,7],[2,5,8])] returns the array

  a[1,2] a[1,5] a[1,8] a[3,2] a[3,5] a[3,8] a[7,2] a[7,5] a[7,8]

• unravel_index(x, dims)

  Convert a flat index into an index tuple for an array of given shape.

  e.g. for a 2x2 array, unravel_index(2,(2,2)) returns (1,0).

  Example usage:

  p = x.argmax() idx = unravel_index(p,x.shape) x[idx] == x.max()

  Note: x.flat[p] == x.max()

  Thus, it may be easier to use flattened indexing than to re-map the index to a tuple.

Imported names