[Scipy-svn] r6828 - in trunk/scipy/sparse/linalg: . eigen/lobpcg isolve
scipy-svn at scipy.org
scipy-svn at scipy.org
Fri Oct 1 06:23:35 EDT 2010
Author: ptvirtan
Date: 2010-10-01 05:23:34 -0500 (Fri, 01 Oct 2010)
New Revision: 6828
Modified:
trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py
trunk/scipy/sparse/linalg/interface.py
trunk/scipy/sparse/linalg/isolve/iterative.py
Log:
DOC: sparse.linalg: reformat docstrings
Modified: trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py
===================================================================
--- trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py 2010-09-28 02:08:26 UTC (rev 6827)
+++ trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py 2010-10-01 10:23:34 UTC (rev 6828)
@@ -158,7 +158,6 @@
This function implements the Locally Optimal Block Preconditioned
Conjugate Gradient Method (LOBPCG).
-
Parameters
----------
A : {sparse matrix, dense matrix, LinearOperator}
@@ -167,44 +166,40 @@
X : array_like
Initial approximation to the k eigenvectors. If A has
shape=(n,n) then X should have shape shape=(n,k).
-
- Returns
- -------
- w : array
- Array of k eigenvalues
- v : array
- An array of k eigenvectors. V has the same shape as X.
-
-
- Optional Parameters
- -------------------
- B : {dense matrix, sparse matrix, LinearOperator}
+ B : {dense matrix, sparse matrix, LinearOperator}, optional
the right hand side operator in a generalized eigenproblem.
by default, B = Identity
often called the "mass matrix"
- M : {dense matrix, sparse matrix, LinearOperator}
+ M : {dense matrix, sparse matrix, LinearOperator}, optional
preconditioner to A; by default M = Identity
M should approximate the inverse of A
- Y : array_like
+ Y : array_like, optional
n-by-sizeY matrix of constraints, sizeY < n
The iterations will be performed in the B-orthogonal complement
of the column-space of Y. Y must be full rank.
+ Returns
+ -------
+ w : array
+ Array of k eigenvalues
+ v : array
+ An array of k eigenvectors. V has the same shape as X.
+
Other Parameters
----------------
- tol : scalar
+ tol : scalar, optional
Solver tolerance (stopping criterion)
by default: tol=n*sqrt(eps)
- maxiter: integer
+ maxiter: integer, optional
maximum number of iterations
by default: maxiter=min(n,20)
- largest : boolean
+ largest : boolean, optional
when True, solve for the largest eigenvalues, otherwise the smallest
- verbosityLevel : integer
+ verbosityLevel : integer, optional
controls solver output. default: verbosityLevel = 0.
- retLambdaHistory : boolean
+ retLambdaHistory : boolean, optional
whether to return eigenvalue history
- retResidualNormsHistory : boolean
+ retResidualNormsHistory : boolean, optional
whether to return history of residual norms
Modified: trunk/scipy/sparse/linalg/interface.py
===================================================================
--- trunk/scipy/sparse/linalg/interface.py 2010-09-28 02:08:26 UTC (rev 6827)
+++ trunk/scipy/sparse/linalg/interface.py 2010-10-01 10:23:34 UTC (rev 6828)
@@ -21,8 +21,8 @@
matvec : callable f(v)
Returns returns A * v.
- Optional Parameters
- -------------------
+ Other Parameters
+ ----------------
rmatvec : callable f(v)
Returns A^H * v, where A^H is the conjugate transpose of A.
matmat : callable f(V)
Modified: trunk/scipy/sparse/linalg/isolve/iterative.py
===================================================================
--- trunk/scipy/sparse/linalg/isolve/iterative.py 2010-09-28 02:08:26 UTC (rev 6827)
+++ trunk/scipy/sparse/linalg/isolve/iterative.py 2010-10-01 10:23:34 UTC (rev 6828)
@@ -21,8 +21,18 @@
b : {array, matrix}
Right hand side of the linear system. Has shape (N,) or (N,1).
-Optional Parameters
--------------------
+Returns
+-------
+x : {array, matrix}
+ The converged solution.
+info : integer
+ Provides convergence information:
+ 0 : successful exit
+ >0 : convergence to tolerance not achieved, number of iterations
+ <0 : illegal input or breakdown
+
+Other Parameters
+----------------
x0 : {array, matrix}
Starting guess for the solution.
tol : float
@@ -39,26 +49,16 @@
callback : function
User-supplied function to call after each iteration. It is called
as callback(xk), where xk is the current solution vector.
-
-Outputs
--------
-x : {array, matrix}
- The converged solution.
-info : integer
- Provides convergence information:
- 0 : successful exit
- >0 : convergence to tolerance not achieved, number of iterations
- <0 : illegal input or breakdown
-
-Deprecated Parameters
-----------------------
xtype : {'f','d','F','D'}
+ This parameter is deprecated -- avoid using it.
+
The type of the result. If None, then it will be determined from
A.dtype.char and b. If A does not have a typecode method then it
will compute A.matvec(x0) to get a typecode. To save the extra
computation when A does not have a typecode attribute use xtype=0
for the same type as b or use xtype='f','d','F',or 'D'.
This parameter has been superceeded by LinearOperator.
+
"""
@@ -314,8 +314,18 @@
b : {array, matrix}
Right hand side of the linear system. Has shape (N,) or (N,1).
- Optional Parameters
- -------------------
+ Returns
+ -------
+ x : {array, matrix}
+ The converged solution.
+ info : integer
+ Provides convergence information:
+ 0 : successful exit
+ >0 : convergence to tolerance not achieved, number of iterations
+ <0 : illegal input or breakdown
+
+ Other Parameters
+ ----------------
x0 : {array, matrix}
Starting guess for the solution.
tol : float
@@ -336,24 +346,9 @@
callback : function
User-supplied function to call after each iteration. It is called
as callback(rk), where rk is the current residual vector.
-
- Outputs
- -------
- x : {array, matrix}
- The converged solution.
- info : integer
- Provides convergence information:
- 0 : successful exit
- >0 : convergence to tolerance not achieved, number of iterations
- <0 : illegal input or breakdown
-
- See Also
- --------
- LinearOperator
-
- Deprecated Parameters
- ---------------------
xtype : {'f','d','F','D'}
+ This parameter is DEPRECATED --- avoid using it.
+
The type of the result. If None, then it will be determined from
A.dtype.char and b. If A does not have a typecode method then it
will compute A.matvec(x0) to get a typecode. To save the extra
@@ -361,6 +356,10 @@
for the same type as b or use xtype='f','d','F',or 'D'.
This parameter has been superceeded by LinearOperator.
+ See Also
+ --------
+ LinearOperator
+
"""
# Change 'restrt' keyword to 'restart'
@@ -460,8 +459,18 @@
b : {array, matrix}
Right hand side of the linear system. Has shape (N,) or (N,1).
- Optional Parameters
- -------------------
+ Returns
+ -------
+ x : {array, matrix}
+ The converged solution.
+ info : integer
+ Provides convergence information:
+ 0 : successful exit
+ >0 : convergence to tolerance not achieved, number of iterations
+ <0 : illegal input or breakdown
+
+ Other Parameters
+ ----------------
x0 : {array, matrix}
Starting guess for the solution.
tol : float
@@ -479,24 +488,9 @@
callback : function
User-supplied function to call after each iteration. It is called
as callback(xk), where xk is the current solution vector.
-
- Outputs
- -------
- x : {array, matrix}
- The converged solution.
- info : integer
- Provides convergence information:
- 0 : successful exit
- >0 : convergence to tolerance not achieved, number of iterations
- <0 : illegal input or breakdown
-
- See Also
- --------
- LinearOperator
-
- Deprecated Parameters
- ---------------------
xtype : {'f','d','F','D'}
+ This parameter is DEPRECATED -- avoid using it.
+
The type of the result. If None, then it will be determined from
A.dtype.char and b. If A does not have a typecode method then it
will compute A.matvec(x0) to get a typecode. To save the extra
@@ -504,6 +498,10 @@
for the same type as b or use xtype='f','d','F',or 'D'.
This parameter has been superceeded by LinearOperator.
+ See Also
+ --------
+ LinearOperator
+
"""
A_ = A
A,M,x,b,postprocess = make_system(A,None,x0,b,xtype)
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