SciPy 0.6.0 API Documentation Generated by Endo, 2007-10-17

Variables

• ALLOCSIZE

  ALLOCSIZE = 1000
  
  

• MAXPRINT

  MAXPRINT = 50
  
  

• NZMAX

  NZMAX = 100
  
  

• issparse

  issparse = isspmatrix
  
  

Classes

• coo_matrix - A sparse matrix in coordinate list format
• csc_matrix
• csr_matrix
• dok_matrix - A dictionary of keys based matrix
• lil_matrix - Row-based linked list matrix, by Ed Schofield
• spmatrix - This class provides a base class for all sparse matrices

Function summary

• extract_diagonal(A)
• getdtype(dtype, a = None, default = None)
• isdense(x)
• isintlike(x)
• isscalarlike(x)
• issequence(t)
• isshape(x)
• isspmatrix(x)
• isspmatrix_coo(x)
• isspmatrix_csc(x)
• isspmatrix_csr(x)
• isspmatrix_dok(x)
• isspmatrix_lil(x)
• lil_diags(diags, offsets, (m, n), dtype = float)
• lil_eye((r, c), k = 0, dtype = float)
• resize1d(arr, newlen)
• spdiags(diags, offsets, M, N)
• speye(n, m, k = 0, dtype = 'd')
• spidentity(n, dtype = 'd')

Functions

• extract_diagonal(A)

  extract_diagonal(A) returns the main diagonal of A.

• getdtype(dtype, a = None, default = None)

  Function used to simplify argument processing. If 'dtype' is not specified (is None), returns a.dtype; otherwise returns a numpy.dtype object created from the specified dtype argument. If 'dtype' and 'a' are both None, construct a data type out of the 'default' parameter. Furthermore, 'dtype' must be in 'allowed' set.

• isdense(x)
• isintlike(x)

  Is x appropriate as an index into a sparse matrix? Returns True if it can be cast safely to a machine int.

• isscalarlike(x)

  Is x either a scalar, an array scalar, or a 0-dim array?

• issequence(t)
• isshape(x)

  Is x a valid 2-tuple of dimensions?

• isspmatrix(x)
• isspmatrix_coo(x)
• isspmatrix_csc(x)
• isspmatrix_csr(x)
• isspmatrix_dok(x)
• isspmatrix_lil(x)
• lil_diags(diags, offsets, (m, n), dtype = float)

  Generate a lil_matrix with the given diagonals.
  
  :Parameters:
      diags : list of list of values e.g. [[1,2,3],[4,5]]
          Values to be placed on each indicated diagonal.
      offsets : list of ints
          Diagonal offsets.  This indicates the diagonal on which
          the given values should be placed.
      (r,c) : tuple of ints
          Row and column dimensions of the output.
      dtype : dtype
         Output data-type.
  
  Example:
  -------
  
  >>> lil_diags([[1,2,3],[4,5],[6]],[0,1,2],(3,3)).todense()
  matrix([[ 1.,  4.,  6.],
          [ 0.,  2.,  5.],
          [ 0.,  0.,  3.]])
  
  

• lil_eye((r, c), k = 0, dtype = float)

  Generate a lil_matrix of dimensions (r,c) with the k-th diagonal set to 1.

  Parameters:	r,c : int Row and column-dimensions of the output. k : int Diagonal offset. In the output matrix, out[m,m+k] == 1 for all m. dtype : dtype Data-type of the output array.

• resize1d(arr, newlen)
• spdiags(diags, offsets, M, N)

  Return a sparse matrix in CSC format given its diagonals.

  B = spdiags(diags, offsets, M, N)

  Inputs:

  diags -- rows contain diagonal values offsets -- diagonals to set (0 is main) M, N -- sparse matrix returned is M X N

• speye(n, m, k = 0, dtype = 'd')

  speye(n, m) returns a (n x m) matrix stored in CSC sparse matrix format, where the k-th diagonal is all ones, and everything else is zeros.

• spidentity(n, dtype = 'd')

  spidentity( n ) returns the identity matrix of shape (n, n) stored in CSC sparse matrix format.

Imported Names