scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
See Also:
b : array, shape (M, M)
Right-hand side matrix in a generalized eigenvalue problem. If omitted, identity
matrix is assumed.
overwrite_a : boolean
Whether to overwrite data in a (may improve performance)
Returns
w : double or complex array, shape (M,)
The eigenvalues, each repeated according to its multiplicity, but not in any specific
order.
Raises LinAlgError if eigenvalue computation does not converge :
eigvalsh
eigenvalues of symmetric or Hemitiean arrays
eig
eigenvalues and right eigenvectors of general arrays
eigh
eigenvalues and eigenvectors of symmetric/Hermitean arrays.
eigh(a, b=None, lower=True, eigvals_only=False, overwrite_a=False, overwrite_b=False, turbo=True,
eigvals=None, type=1)
Solve an ordinary or generalized eigenvalue problem for a complex Hermitian or real symmetric matrix.
Find eigenvalues w and optionally eigenvectors v of matrix a, where b is positive definite:
a v[:,i] = w[i] b v[:,i]
v[i,:].conj() a v[:,i] = w[i]
v[i,:].conj() b v[:,i] = 1
Parameters
a : array, shape (M, M)
A complex Hermitian or real symmetric matrix whose eigenvalues and eigenvectors
will be computed.
b : array, shape (M, M)
A complex Hermitian or real symmetric definite positive matrix in. If omitted, identity
matrix is assumed.
lower : boolean
Whether the pertinent array data is taken from the lower or upper triangle of a. (Default:
lower)
eigvals_only : boolean
Whether to calculate only eigenvalues and no eigenvectors. (Default: both are calculated)
turbo : boolean
Use divide and conquer algorithm (faster but expensive in memory, only for generalized
eigenvalue problem and if eigvals=None)
228 Chapter 3. Reference