From 772d74b0fb2161f825d0bccf81ad563553033d1b Mon Sep 17 00:00:00 2001
From: Dirk Verbeeck
Date: Sat, 15 Nov 2003 18:38:16 +0000
Subject: [PATCH] Reapply changeset (mdiggory 2003/11/09 12:17:50) Adding
documentation for Contributors. Adding xsl stylesheets to render xdoc in
browser and css to style content, this makes testing documentation additions
easier without rendering the entire site. Simply open up xdoc in browser to
see what it will look like after rendering.
git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@141018 13f79535-47bb-0310-9956-ffa450edef68
---
xdocs/developers.xml | 63 ++-
xdocs/index.xml | 3 +-
xdocs/navigation.xml | 2 +-
xdocs/proposal.xml | 3 +-
xdocs/stylesheets/maven.css | 114 +++++
xdocs/stylesheets/print.css | 7 +
xdocs/stylesheets/tigris.css | 789 ++++++++++++++++++++++++++++++++++
xdocs/tasks.xml | 5 +-
xdocs/userguide/analysis.xml | 171 ++++----
xdocs/userguide/index.xml | 3 +-
xdocs/userguide/linear.xml | 2 +
xdocs/userguide/overview.xml | 3 +-
xdocs/userguide/random.xml | 2 +
xdocs/userguide/special.xml | 81 ++--
xdocs/userguide/stat.xml | 183 ++++----
xdocs/userguide/utilities.xml | 2 +
xdocs/xdoc.xsl | 42 ++
17 files changed, 1251 insertions(+), 224 deletions(-)
create mode 100644 xdocs/stylesheets/maven.css
create mode 100644 xdocs/stylesheets/print.css
create mode 100644 xdocs/stylesheets/tigris.css
create mode 100644 xdocs/xdoc.xsl
diff --git a/xdocs/developers.xml b/xdocs/developers.xml
index 3eb7d4475..c90396671 100644
--- a/xdocs/developers.xml
+++ b/xdocs/developers.xml
@@ -1,5 +1,6 @@
-
+
+
Developers Guide
@@ -23,6 +24,66 @@
will not be committed. Our aim will be to fix all of the exceptions to the
"should" guidelines prior to a release.
+
+
+ Becoming involved with a community project such as Commons Math can at
+ first appear to be very daunting. The Math projects motivations are to
+ design and build a well thoughtout API. With this in mind, there is a great
+ deal of review and discussion revolving around how and why a particular
+ package is included or written into the project. It is understandable that
+ individuals may have an interest in donating either their time or code to the
+ project, and we want to promote this. For this reason, we are working to
+ maintain guidelines for proposing additional packages or coding efforts
+ within the project.
+
+
+
+
Formost it is important to review the overall objectives
+ and proposal upon which the project is
+ founded.
+
+
Review the completed, current and future
+ tasks of the project.
+
+
Be sure to join the Commons Developer and Interest
+ email lists and use them appropriately (make sure the string "[math]" is
+ somewhere in the Subject line of all your postings). Make any proposals here
+ where the group can comment on them
+
+
+ Setup an account on Bugzilla
+ and use it to formally submit Patches and identify bugs. Read the
+ directions for
+ submitting bugs and search the database to determine if an issue exists or has
+ already been dealt with.
+
+
diff --git a/xdocs/userguide/analysis.xml b/xdocs/userguide/analysis.xml
index c7878b226..bdf9d9fb2 100644
--- a/xdocs/userguide/analysis.xml
+++ b/xdocs/userguide/analysis.xml
@@ -1,85 +1,86 @@
-
-
-
-
- The Commons Math User Guide - Numerical Analysis
- Phil Steitz
-
-
-
-
-
This is yet to be written. Any contributions will be gratefully
- accepted!
-
-
-
- org.apache.commons.math.analysis.UnivariateRealSolver provides the means to
- find roots of univariate, real valued, functions. Commons-Math supports various
- implementations of UnivariateRealSolver to solve functions with differing
- characteristics.
-
-
- In order to use the root-finding features, first a solver object must be created. It is
- encouraged that all solver object creation occurs via the org.apache.commons.math.analysis.UnivariateRealSolverFactory
- class. UnivariateRealSolverFactory is a simple factory used to create all
- of the solver objects supported by Commons-Math. The typical usage of UnivariateRealSolverFactory
- to create a solver object would be:
-
-
- The solvers that can be instantiated via the UnivariateRealSolverFactory are detailed below:
-
-
Solver
Factory Method
Notes on Use
-
Bisection
newBisectionSolver
Root must be bracketted.
Linear, guaranteed convergence
-
Brent
newBrentSolver
Root must be bracketted.
Super-linear, guaranteed convergence
-
Secant
newSecantSolver
Root must be bracketted.
Super-linear, non-guaranteed convergence
-
-
-
- Using a solver object, roots of functions are easily found using the solve
- methods. For a function f, and two domain values, min and
- max, solve computes the value c such that:
-
-
f(c) = 0.0
-
min <= c <= max
-
-
-
-
- Along with the solve methods, the UnivariateRealSolver
- interface provides many properties to control the convergence of a solver. For the most
- part, these properties should not have to change from their default values to produce
- quality results. In the circumstances where changing these property values is needed, it
- is easily done through getter and setter methods on UnivariateRealSolver:
-
-
Property
Methods
Purpose
-
Absolute accuracy
-
getAbsoluteAccuracy
-
resetAbsoluteAccuracy
-
setAbsoluteAccuracy
This is yet to be written. Any contributions will be greatfully accepted!
-
Function value accuracy
-
getFunctionValueAccuracy
-
resetFunctionValueAccuracy
-
setFunctionValueAccuracy
This is yet to be written. Any contributions will be greatfully accepted!
-
Maximum iteration count
-
getMaximumIterationCount
-
resetMaximumIterationCount
-
setMaximumIterationCount
This is yet to be written. Any contributions will be greatfully accepted!
-
Relative accuracy
-
getRelativeAccuracy
-
resetRelativeAccuracy
-
setRelativeAccuracy
This is yet to be written. Any contributions will be greatfully accepted!
-
-
-
-
-
This is yet to be written. Any contributions will be gratefully
- accepted!
-
-
-
-
+
+
+
+
+
+ The Commons Math User Guide - Numerical Analysis
+ Phil Steitz
+
+
+
+
+
This is yet to be written. Any contributions will be gratefully
+ accepted!
+
+
+
+ org.apache.commons.math.analysis.UnivariateRealSolver provides the means to
+ find roots of univariate, real valued, functions. Commons-Math supports various
+ implementations of UnivariateRealSolver to solve functions with differing
+ characteristics.
+
+
+ In order to use the root-finding features, first a solver object must be created. It is
+ encouraged that all solver object creation occurs via the org.apache.commons.math.analysis.UnivariateRealSolverFactory
+ class. UnivariateRealSolverFactory is a simple factory used to create all
+ of the solver objects supported by Commons-Math. The typical usage of UnivariateRealSolverFactory
+ to create a solver object would be:
+
+
+ The solvers that can be instantiated via the UnivariateRealSolverFactory are detailed below:
+
+
Solver
Factory Method
Notes on Use
+
Bisection
newBisectionSolver
Root must be bracketted.
Linear, guaranteed convergence
+
Brent
newBrentSolver
Root must be bracketted.
Super-linear, guaranteed convergence
+
Secant
newSecantSolver
Root must be bracketted.
Super-linear, non-guaranteed convergence
+
+
+
+ Using a solver object, roots of functions are easily found using the solve
+ methods. For a function f, and two domain values, min and
+ max, solve computes the value c such that:
+
+
f(c) = 0.0
+
min <= c <= max
+
+
+
+
+ Along with the solve methods, the UnivariateRealSolver
+ interface provides many properties to control the convergence of a solver. For the most
+ part, these properties should not have to change from their default values to produce
+ quality results. In the circumstances where changing these property values is needed, it
+ is easily done through getter and setter methods on UnivariateRealSolver:
+
+
Property
Methods
Purpose
+
Absolute accuracy
+
getAbsoluteAccuracy
+
resetAbsoluteAccuracy
+
setAbsoluteAccuracy
This is yet to be written. Any contributions will be greatfully accepted!
+
Function value accuracy
+
getFunctionValueAccuracy
+
resetFunctionValueAccuracy
+
setFunctionValueAccuracy
This is yet to be written. Any contributions will be greatfully accepted!
+
Maximum iteration count
+
getMaximumIterationCount
+
resetMaximumIterationCount
+
setMaximumIterationCount
This is yet to be written. Any contributions will be greatfully accepted!
+
Relative accuracy
+
getRelativeAccuracy
+
resetRelativeAccuracy
+
setRelativeAccuracy
This is yet to be written. Any contributions will be greatfully accepted!
+
+
+
+
+
This is yet to be written. Any contributions will be gratefully
+ accepted!
+
+
+
+
diff --git a/xdocs/userguide/index.xml b/xdocs/userguide/index.xml
index 54e1ea729..0339b7912 100644
--- a/xdocs/userguide/index.xml
+++ b/xdocs/userguide/index.xml
@@ -1,6 +1,7 @@
+
+
-
Phil SteitzThe Commons Math User Guide - Table of Contents
diff --git a/xdocs/userguide/linear.xml b/xdocs/userguide/linear.xml
index 6b7cb8ac7..9f9a31520 100644
--- a/xdocs/userguide/linear.xml
+++ b/xdocs/userguide/linear.xml
@@ -1,4 +1,6 @@
+
+
diff --git a/xdocs/userguide/overview.xml b/xdocs/userguide/overview.xml
index 16ea34871..3f85556c7 100644
--- a/xdocs/userguide/overview.xml
+++ b/xdocs/userguide/overview.xml
@@ -1,5 +1,6 @@
-
+
+
User Guide - Overview
diff --git a/xdocs/userguide/random.xml b/xdocs/userguide/random.xml
index 92c974b5f..f25d4a906 100644
--- a/xdocs/userguide/random.xml
+++ b/xdocs/userguide/random.xml
@@ -1,4 +1,6 @@
+
+
diff --git a/xdocs/userguide/special.xml b/xdocs/userguide/special.xml
index ec0f1e8bf..e3ccaa848 100644
--- a/xdocs/userguide/special.xml
+++ b/xdocs/userguide/special.xml
@@ -1,40 +1,41 @@
-
-
-
-
- The Commons Math User Guide - Special Functions
- Phil Steitz
-
-
-
-
-
- The special functions portion of Commons-Math contains several useful functions not
- provided by java.lang.Math. These functions mostly serve as building blocks
- for other portions of Commons-Math but, as others may find them useful as stand-alone
- methods, these special functions were included as part of the Commons-Math public API.
-
-
-
-
- org.apache.commons.math.special.Gamma contains several useful functions involving the Gamma Function.
-
-
-
-
-
-
+
+
+
+
+
+ The Commons Math User Guide - Special Functions
+ Phil Steitz
+
+
+
+
+
+ The special functions portion of Commons-Math contains several useful functions not
+ provided by java.lang.Math. These functions mostly serve as building blocks
+ for other portions of Commons-Math but, as others may find them useful as stand-alone
+ methods, these special functions were included as part of the Commons-Math public API.
+
+
+
+
+ org.apache.commons.math.special.Gamma contains several useful functions involving the Gamma Function.
+
+
+
+
+
+
diff --git a/xdocs/userguide/stat.xml b/xdocs/userguide/stat.xml
index fdee0d946..f5a353b6d 100644
--- a/xdocs/userguide/stat.xml
+++ b/xdocs/userguide/stat.xml
@@ -1,91 +1,92 @@
-
-
-
-
- The Commons Math User Guide - Statistics
- Phil Steitz
-
-
-
-
-
This is yet to be written. Any contributions will be greatfully
- accepted!
-
-
-
This is yet to be written. Any contributions will be gratefully
- accepted!
-
-
-
This is yet to be written. Any contributions will be gratefully
- accepted!
-
-
-
This is yet to be written. Any contributions will be gratefully
- accepted!
-
-
-
This is yet to be written. Any contributions will be gratefully
- accepted!
-
-
-
- The distribution framework provides the means to compute probability density
- function (PDF) probabilities and cumulative distribution function (CDF)
- probabilities for common probability distributions. Along with the direct
- computation of PDF and CDF probabilities, the framework also allows for the
- computation of inverse PDF and inverse CDF values.
-
-
- In order to use the distribution framework, first a distribution object must
- be created. It is encouraged that all distribution object creation occurs via
- the org.apache.commons.math.stat.distribution.DistributionFactory
- class. DistributionFactory is a simple factory used to create all
- of the distribution objects supported by Commons-Math. The typical usage of
- DistributionFactory to create a distribution object would be:
-
-
-
- The distributions that can be instantiated via the DistributionFactory
- are detailed below:
-
-
Distribution
Factory Method
Parameters
-
Binomial
createBinomialDistribution
Number of trials
Probability of success
-
Chi-Squared
createChiSquaredDistribution
Degrees of freedom
-
Exponential
createExponentialDistribution
Mean
-
F
createFDistribution
Numerator degrees of freedom
Denominator degrees of freedom
-
Gamma
createGammaDistribution
Alpha
Beta
-
Hypergeometric
createHypogeometricDistribution
Population size
Number of successes in population
Sample size
-
t
createTDistribution
Degrees of freedom
-
-
-
- Using a distribution object, PDF and CDF probabilities are easily computed
- using the cummulativeProbability methods. For a distribution X,
- and a domain value, x, cummulativeProbability computes
- P(X <= x) (i.e. the lower tail probability of X).
-
-
-
- The inverse PDF and CDF values are just as easily computed using the
- inverseCummulativeProbabilitymethods. For a distribution X,
- and a probability, p, inverseCummulativeProbability
- computes the domain value x, such that:
-
-
P(X <= x) = p, for continuous distributions
-
P(X <= x) <= p, for discrete distributions
-
- Notice the different cases for continuous and discrete distributions. This is the result
- of PDFs not being invertible functions. As such, for discrete distributions, an exact
- domain value can not be returned. Only the "best" domain value. For Commons-Math, the "best"
- domain value is determined by the largest domain value whose cummulative probability is
- less-than or equal to the given probability.
-
-
-
-
-
-
+
+
+
+
+
+ The Commons Math User Guide - Statistics
+ Phil Steitz
+
+
+
+
+
This is yet to be written. Any contributions will be greatfully
+ accepted!
+
+
+
This is yet to be written. Any contributions will be gratefully
+ accepted!
+
+
+
This is yet to be written. Any contributions will be gratefully
+ accepted!
+
+
+
This is yet to be written. Any contributions will be gratefully
+ accepted!
+
+
+
This is yet to be written. Any contributions will be gratefully
+ accepted!
+
+
+
+ The distribution framework provides the means to compute probability density
+ function (PDF) probabilities and cumulative distribution function (CDF)
+ probabilities for common probability distributions. Along with the direct
+ computation of PDF and CDF probabilities, the framework also allows for the
+ computation of inverse PDF and inverse CDF values.
+
+
+ In order to use the distribution framework, first a distribution object must
+ be created. It is encouraged that all distribution object creation occurs via
+ the org.apache.commons.math.stat.distribution.DistributionFactory
+ class. DistributionFactory is a simple factory used to create all
+ of the distribution objects supported by Commons-Math. The typical usage of
+ DistributionFactory to create a distribution object would be:
+
+
+
+ The distributions that can be instantiated via the DistributionFactory
+ are detailed below:
+
+
Distribution
Factory Method
Parameters
+
Binomial
createBinomialDistribution
Number of trials
Probability of success
+
Chi-Squared
createChiSquaredDistribution
Degrees of freedom
+
Exponential
createExponentialDistribution
Mean
+
F
createFDistribution
Numerator degrees of freedom
Denominator degrees of freedom
+
Gamma
createGammaDistribution
Alpha
Beta
+
Hypergeometric
createHypogeometricDistribution
Population size
Number of successes in population
Sample size
+
t
createTDistribution
Degrees of freedom
+
+
+
+ Using a distribution object, PDF and CDF probabilities are easily computed
+ using the cummulativeProbability methods. For a distribution X,
+ and a domain value, x, cummulativeProbability computes
+ P(X <= x) (i.e. the lower tail probability of X).
+
+
+
+ The inverse PDF and CDF values are just as easily computed using the
+ inverseCummulativeProbabilitymethods. For a distribution X,
+ and a probability, p, inverseCummulativeProbability
+ computes the domain value x, such that:
+
+
P(X <= x) = p, for continuous distributions
+
P(X <= x) <= p, for discrete distributions
+
+ Notice the different cases for continuous and discrete distributions. This is the result
+ of PDFs not being invertible functions. As such, for discrete distributions, an exact
+ domain value can not be returned. Only the "best" domain value. For Commons-Math, the "best"
+ domain value is determined by the largest domain value whose cummulative probability is
+ less-than or equal to the given probability.
+
+
+
+
+
+
diff --git a/xdocs/userguide/utilities.xml b/xdocs/userguide/utilities.xml
index ff527cb3d..9b447fa92 100644
--- a/xdocs/userguide/utilities.xml
+++ b/xdocs/userguide/utilities.xml
@@ -1,4 +1,6 @@
+
+
diff --git a/xdocs/xdoc.xsl b/xdocs/xdoc.xsl
new file mode 100644
index 000000000..ece067ae4
--- /dev/null
+++ b/xdocs/xdoc.xsl
@@ -0,0 +1,42 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+