Revision: 5828
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5828&view=rev
Author: dmkaplan
Date: 2008-07-24 07:59:18 +0000 (Thu, 24 Jul 2008)
Log Message:
-----------
Changes to documentation of norm and orth functions and deprecation
warning for norm in favor of numpy version.
Modified Paths:
--------------
trunk/matplotlib/lib/matplotlib/mlab.py
Modified: trunk/matplotlib/lib/matplotlib/mlab.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/mlab.py 2008-07-24 02:28:20 UTC (rev
5827)
+++ trunk/matplotlib/lib/matplotlib/mlab.py 2008-07-24 07:59:18 UTC (rev
5828)
@@ -1816,25 +1816,25 @@
def norm(x,y=2):
"""
- Norm of a matrix or a vector according to Matlab.
- The description is taken from Matlab:
+ This function is deprecated - use numpy.linalg.norm instead.
- For matrices...
- NORM(X) is the largest singular value of X, max(svd(X)).
- NORM(X,2) is the same as NORM(X).
- NORM(X,1) is the 1-norm of X, the largest column sum,
- = max(sum(abs((X)))).
- NORM(X,inf) is the infinity norm of X, the largest row sum,
- = max(sum(abs((X')))).
- NORM(X,'fro') is the Frobenius norm, sqrt(sum(diag(X'*X))).
- NORM(X,P) is available for matrix X only if P is 1, 2, inf or 'fro'.
+ Norm of a matrix or a vector. Functions similar to the Matlab (TM)
+ function of the same name.
- For vectors...
- NORM(V,P) = sum(abs(V).^P)^(1/P).
- NORM(V) = norm(V,2).
- NORM(V,inf) = max(abs(V)).
- NORM(V,-inf) = min(abs(V)).
+ Call signature::
+
+ norm(x,y=2)
+
+ This function behaves differently for vectors and matrices. For vectors,
+ it returns the y'th norm of x (i.e. (sum(abs(x)**y))**(1.0/y).
+
+ For matrices, if y=2, then it returns the largest singular value
+ of X, namely max(linalg.svd(x)). If y=1, returns the largest
+ column sum of x (i.e., max(sum(abs(x),axis=0)) ). If y=inf,
+ returns the largest row sum. If y='fro', returns the Frobenius
+ norm, sqrt(sum(diag(dot(x.transpose(),x)))).
"""
+ warnings.warn( "Use numpy.linalg.norm instead", DeprecationWarning )
x = np.asarray(x)
if x.ndim == 2:
@@ -1862,13 +1862,16 @@
def orth(A):
"""
- Orthogonalization procedure by Matlab.
- The description is taken from its help:
+ Orthogonalization procedure similar to Matlab (TM) function of the same
+ name.
- Q = ORTH(A) is an orthonormal basis for the range of A.
- That is, Q'*Q = I, the columns of Q span the same space as
- the columns of A, and the number of columns of Q is the
- rank of A.
+ Call signature::
+
+ Q = orth(A)
+
+ Returns an orthonormal basis with the range of A. Q is an orthonormal
+ matrix (i.e., dot( Q.transpose(), Q ) is an identity matrix) and the
+ columns of Q span the same space as the columns of A.
"""
A = np.asarray(A)
@@ -2086,9 +2089,9 @@
join record arrays r1 and r2 on key; key is a tuple of field
names. If r1 and r2 have equal values on all the keys in the key
tuple, then their fields will be merged into a new record array
- containing the intersection of the fields of r1 and r2.
+ containing the intersection of the fields of r1 and r2.
- r1 (also r2) must not have any duplicate keys.
+ r1 (also r2) must not have any duplicate keys.
The jointype keyword can be 'inner', 'outer', 'leftouter'.
To do a rightouter join just reverse r1 and r2.
@@ -2702,8 +2705,8 @@
griddata interpolates this surface at the points specified by (xi,yi)
to produce zi. xi and yi must describe a regular grid, can be
either 1D or 2D, but must be monotonically increasing.
-
- A masked array is returned if any grid points are outside convex
+
+ A masked array is returned if any grid points are outside convex
hull defined by input data (no extrapolation is done).
Uses natural neighbor interpolation based on Delaunay triangulation.
@@ -2712,7 +2715,7 @@
package is known to fail on some nearly pathological cases. For
this reason, a separate toolkit (mpl_tookits.natgrid) has been created
that provides a more robust algorithm fof triangulation and interpolation.
- This toolkit is based on the NCAR natgrid library, which contains code
+ This toolkit is based on the NCAR natgrid library, which contains code
that is not redistributable under a BSD-compatible license. When
installed,
this function will use the mpl_toolkits.natgrid algorithm, otherwise it
will use the built-in matplotlib.delaunay package.
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