I’m very happily starting to use Java 8 and am making lots of use of JavaFX
(not so relevant to Math), and lambdas and streams (playing around with a
little numpy like interface to Math).
So, on the one hand I’m all for Java 8, but on the other hand there are things
I’d rather see done for the
When I click on the documentation link ( at
http://commons.apache.org/proper/commons-math/apidocs/index.html
http://commons.apache.org/proper/commons-math/apidocs/index.html )
for ParameterValidator in the fitting.leastsquares package I get:
The requested URL
attention to the that there is no ambiguity. On the other hand I might not be
the only person that sees a method called getCovariance and expects that it
will give X'X.
Bruce
On Oct 7, 2014, at 9:59 PM, Bruce A Johnson johns...@umbc.edu wrote:
As I understand it (which could easily be wrong
As I understand it (which could easily be wrong), calculation of the covariance
(X'X) via SVD follows the following logic:
X = USV'(via SVD, the X' indicates transpose)
X'X = (USV')' USV'
this reduces to
X'X = VSU'USV'
= V S S V'
In the SingularValueDecomposition class the
The CMAESOptimizer repairs points that are out of bounds by moving them into
bounds, and adding a penalty based on how far they were moved.
The penalty added is scaled by the range of values in the current population
(valueRange field in code below).
double[] x, final double[] repaired) {
The NonLinearConjugateGradientOptimizer does a line search for a zero in the
gradient (see comment from source below), rather than a search for a minimum of
the function (the latter is what is used in Numerical Recipes and in the simple
discussion on Wikipedia (
The NonLinearConjugateGradientOptimizer does a line search for a zero in the
gradient (see comment from source below), rather than a search for a minimum of
the function (the latter is what is used in Numerical Recipes and in the simple
discussion on Wikipedia (
On Feb 26, 2014, at 6:23 PM, Bruce A Johnson johns...@umbc.edu wrote:
The NonLinearConjugateGradientOptimizer does a line search for a zero in the
gradient (see comment from source below), rather than a search for a minimum
of the function (the latter is what is used in Numerical Recipes
I use CM in my NMR (Nuclear Magnetic Resonance) data analysis package for
Fourier transforms, fitting experimental data (optimization package), molecular
structure refinement, statistics and more.
Bruce
http://www.onemoonscientific.com
On Jan 31, 2013, at 3:50 PM, Becksfort, Jared
On Nov 17, 2012, at 6:57 PM, Konstantin Berlin wrote:
There are numerous examples when the optimization might not have
converged to the stopping condition, but the minimum discovered point
is better than the starting point that was initially provided. The
user should have the ability to at
On Aug 23, 2012, at 8:31 AM, Clemens Novak wrote:
On 2012-08-20 19:25, Luc Maisonobe wrote:
Le 20/08/2012 17:00, Clemens Novak a écrit :
Dear all,
Hi Clemens,
I would like to work on some signal processing functions (as indicated
on the wiki WishList) and started with the convolution
On Mar 27, 2012, at 5:55 AM, Gilles Sadowski wrote:
Hello.
it would be nice to have an interpreter for mathematical expressions so that
functions may be defined at runtime.
Example for f(x):
ExpInter ei = new ExpInter();
ei.setFunction(ln(3*sin(2*x)+3));
// Plot the function:
Interesting article about value types in the JVM with relevance to better
support for Complex numbers (something I've long wished for)
https://blogs.oracle.com/jrose/entry/value_types_in_the_vm
Perhaps there is a role for the Commons Math project in item 2 of his section
More Work
Bruce
On Mar 1, 2012, at 7:59 PM, Gilles Sadowski wrote:
Hi.
I managed to complete part of the release process:
Tag on SVN:
https://svn.apache.org/repos/asf/commons/proper/math/tags/MATH_3_0_RC1/
Artefacts on Nexus:
https://repository.apache.org/content/repositories/orgapachecommons-010/
On Feb 7, 2012, at 6:34 AM, Gilles Sadowski wrote:
Hello.
Hello Sébastien,
Kurt has recently proposed a patch for 1D-FFT which is much faster
than our current impl, while still passing the tests (of course).
Am I likely to hurt anyone's feelings if I replace the old impl by the new
On Feb 7, 2012, at 8:05 AM, Sébastien Brisard wrote:
---CUT---
public double[][] transform(double[][] dataRI) { /* ... */ }
---CUT---
And you can pass your data to the CM code in a matter of two array reference
assignments.
OK, I like this idea (this is more or less what I meant by
Hi,
I'm currently working on a scripted interface to Commons Math. I support both
Real and Field (Complex) matrices, and Real and Field (Complex) vectors.
Checking the size of the matrices is trivial because they both implement
AnyMatrix which has row and column size getters, but because
I had exactly this problem (where it wasn't obvious that the sigma parameter
needed to be normalized to [0-1]), a few days ago. I think your second
solution is the more user friendly.
Bruce
On Nov 7, 2011, at 7:58 AM, Luc Maisonobe wrote:
Hello,
I am trying to use CMA-ES optimizer with
I'd be quite interested in seeing Numerical Derivatives in CM. There are some
interesting ideas about Numerical Differentiation here:
http://www.holoborodko.com/pavel/numerical-methods/
Bruce
On Aug 11, 2011, at 6:30 PM, Patrick Meyer wrote:
I like the idea of adding this feature. What
While there is a discussion of solvers going on I thought I would point out
that I have done a Java translation of Dario Bini's implementation of Aberth's
method. I've attached the header of the original Fortran file below. I'd be
happy to donate my translation to Commons Math if there is
One thing that will make plotting possible is a project I'm working
on. Not ready for use, but here's a summary.
The amath4jtcl project provides an extension for the JTcl project
that allows one to use Commons Math Vectors and Matrices within Tcl
Expressions. In combination with my
Joe Darcy at Oracle
http://blogs.sun.com/darcy/category/Numerics
might be a good contact as he has an interest and background in Java
numerics and has been overseeing Project Coin which is about small
additions to the Java language for JDK 7.
Bruce
On Jun 9, 2010, at 9:31 AM, James
The 2.1 API docs for the Singular Value Decomposition say:
The size p depends on the chosen algorithm:
for full SVD, p is n,
for compact SVD, p is the rank r of the matrix (i. e. the number of
positive singular values),
for truncated SVD p is min(r, t) where t is user-specified.
but I don't
23 matches
Mail list logo
