You can subscribe to this list here.
2001 
_{Jan}

_{Feb}

_{Mar}

_{Apr}

_{May}

_{Jun}

_{Jul}
(10) 
_{Aug}
(5) 
_{Sep}
(3) 
_{Oct}
(41) 
_{Nov}
(41) 
_{Dec}
(33) 

2002 
_{Jan}
(75) 
_{Feb}
(10) 
_{Mar}
(170) 
_{Apr}
(174) 
_{May}
(66) 
_{Jun}
(11) 
_{Jul}
(10) 
_{Aug}
(44) 
_{Sep}
(73) 
_{Oct}
(28) 
_{Nov}
(139) 
_{Dec}
(52) 
2003 
_{Jan}
(35) 
_{Feb}
(93) 
_{Mar}
(62) 
_{Apr}
(10) 
_{May}
(55) 
_{Jun}
(70) 
_{Jul}
(37) 
_{Aug}
(16) 
_{Sep}
(56) 
_{Oct}
(31) 
_{Nov}
(57) 
_{Dec}
(83) 
2004 
_{Jan}
(85) 
_{Feb}
(67) 
_{Mar}
(27) 
_{Apr}
(37) 
_{May}
(75) 
_{Jun}
(85) 
_{Jul}
(160) 
_{Aug}
(68) 
_{Sep}
(104) 
_{Oct}
(25) 
_{Nov}
(39) 
_{Dec}
(23) 
2005 
_{Jan}
(10) 
_{Feb}
(45) 
_{Mar}
(43) 
_{Apr}
(19) 
_{May}
(108) 
_{Jun}
(31) 
_{Jul}
(41) 
_{Aug}
(23) 
_{Sep}
(65) 
_{Oct}
(58) 
_{Nov}
(44) 
_{Dec}
(54) 
2006 
_{Jan}
(96) 
_{Feb}
(27) 
_{Mar}
(69) 
_{Apr}
(59) 
_{May}
(67) 
_{Jun}
(35) 
_{Jul}
(13) 
_{Aug}
(461) 
_{Sep}
(160) 
_{Oct}
(399) 
_{Nov}
(32) 
_{Dec}
(72) 
2007 
_{Jan}
(316) 
_{Feb}
(305) 
_{Mar}
(318) 
_{Apr}
(54) 
_{May}
(194) 
_{Jun}
(173) 
_{Jul}
(282) 
_{Aug}
(91) 
_{Sep}
(227) 
_{Oct}
(365) 
_{Nov}
(168) 
_{Dec}
(18) 
2008 
_{Jan}
(71) 
_{Feb}
(111) 
_{Mar}
(155) 
_{Apr}
(173) 
_{May}
(70) 
_{Jun}
(67) 
_{Jul}
(55) 
_{Aug}
(83) 
_{Sep}
(32) 
_{Oct}
(68) 
_{Nov}
(80) 
_{Dec}
(29) 
2009 
_{Jan}
(46) 
_{Feb}
(18) 
_{Mar}
(95) 
_{Apr}
(76) 
_{May}
(140) 
_{Jun}
(98) 
_{Jul}
(84) 
_{Aug}
(123) 
_{Sep}
(94) 
_{Oct}
(131) 
_{Nov}
(142) 
_{Dec}
(125) 
2010 
_{Jan}
(128) 
_{Feb}
(158) 
_{Mar}
(172) 
_{Apr}
(134) 
_{May}
(94) 
_{Jun}
(84) 
_{Jul}
(32) 
_{Aug}
(127) 
_{Sep}
(167) 
_{Oct}
(109) 
_{Nov}
(69) 
_{Dec}
(78) 
2011 
_{Jan}
(39) 
_{Feb}
(58) 
_{Mar}
(52) 
_{Apr}
(47) 
_{May}
(56) 
_{Jun}
(76) 
_{Jul}
(55) 
_{Aug}
(54) 
_{Sep}
(165) 
_{Oct}
(255) 
_{Nov}
(328) 
_{Dec}
(263) 
2012 
_{Jan}
(82) 
_{Feb}
(147) 
_{Mar}
(400) 
_{Apr}
(216) 
_{May}
(209) 
_{Jun}
(160) 
_{Jul}
(86) 
_{Aug}
(141) 
_{Sep}
(156) 
_{Oct}
(6) 
_{Nov}

_{Dec}

2015 
_{Jan}

_{Feb}

_{Mar}

_{Apr}

_{May}

_{Jun}

_{Jul}
(1) 
_{Aug}

_{Sep}
(1) 
_{Oct}

_{Nov}
(1) 
_{Dec}
(2) 
2016 
_{Jan}

_{Feb}
(2) 
_{Mar}
(2) 
_{Apr}
(1) 
_{May}
(1) 
_{Jun}
(2) 
_{Jul}
(1) 
_{Aug}
(1) 
_{Sep}

_{Oct}

_{Nov}

_{Dec}

S  M  T  W  T  F  S 





1
(7) 
2
(17) 
3
(7) 
4
(13) 
5
(17) 
6
(9) 
7
(25) 
8

9
(2) 
10

11
(3) 
12
(1) 
13

14
(2) 
15

16

17

18
(9) 
19

20
(31) 
21
(10) 
22
(7) 
23
(112) 
24
(5) 
25

26
(1) 
27
(2) 
28
(25) 
29
(11) 
30
(2) 
31

From: Thomas Treichl <treichl@us...>  20070314 21:42:51

Update of /cvsroot/octave/octaveforge/main/odepkg/doc In directory sc8prcvs3.sourceforge.net:/tmp/cvsserv20964 Modified Files: odepkg.texi Log Message: Updated. Index: odepkg.texi =================================================================== RCS file: /cvsroot/octave/octaveforge/main/odepkg/doc/odepkg.texi,v retrieving revision 1.10 retrieving revision 1.11 diff u d r1.10 r1.11  odepkg.texi 6 Mar 2007 18:23:06 0000 1.10 +++ odepkg.texi 14 Mar 2007 21:42:47 0000 1.11 @@ 32,6 +32,7 @@ @titlepage @title OdePkg @subtitle A package for solving differential equations with Octave +@subtitle @b{This document currently is under development} @author by Thomas Treichl @page @vskip 0pt plus 1filll @@ 42,43 +43,43 @@ @c %*** Start of BODY @contents @ifnottex @... Top, Beginners's Guide, (dir), (dir) +@node Top, Beginner's Guide, (dir), (dir) @top Copyright @insertcopying @end ifnottex @menu * Beginners's Guide:: Manual for users that are completely new to OdePkg * User's Guide:: Manual for users that are already familiar with OdePkg * Coder's Guide:: Manual for users that want to make changes to OdePkg +* Beginner's Guide:: Manual for users that are completely new to OdePkg +* User's Guide:: Manual for users that are already familiar with OdePkg +* Coder's Guide:: Manual for users that want to make changes to OdePkg * Appendix:: @end menu @c %*** Start of first chapter: Beginner's Guide @... Beginners's Guide, User's Guide, Top, Top @... Beginners's Guide The ``Beginner's Guide'' is intended for new users who want to solve differential equations with the higher level interpreter language Octave and the toolbox OdePkg. In this chapter it will be explained what OdePkg is about in @ref{About OdePkg} and how OdePkg grew up from the beginning in @ref{OdePkg history and roadmap}. In @ref{Installation and deinstallation} it is explained how OdePkg can be installed and in @ref{First tests and demos} the first examples are explained. +@node Beginner's Guide, User's Guide, Top, Top +@chapter Beginner's Guide +The ``Beginner's Guide'' is intended for new users who want to solve differential equations with the higher level language Octave and the toolbox OdePkg. In this chapter it will be explained what OdePkg is about in @ref{About OdePkg} and how OdePkg grew up from the beginning in @ref{OdePkg history and road map}. In @ref{Installation and deinstallation} it is explained how OdePkg can be installed and in @ref{First tests and demos} the first examples are explained. @menu * About OdePkg:: An introduction about OdePkg * OdePkg history and roadmap:: From the initial release until now * Installation and deinstallation:: Setting up OdePkg on your system * Reporting Bugs:: Writing about comments and bugs * First tests and demos:: The foo example and others +* About OdePkg:: An introduction about OdePkg +* OdePkg history and road map:: From the initial release until now +* Installation and deinstallation:: Setting up OdePkg on your system +* Reporting Bugs:: Writing comments and bugs +* First tests and demos:: The foo example and others @end menu @... About OdePkg, OdePkg history and roadmap, Beginners's Guide, Beginners's Guide +@node About OdePkg, OdePkg history and road map, Beginner's Guide, Beginner's Guide @section About OdePkg OdePkg is part of the @b{GNU Octave Repository} (resp. the OctaveForge project) that was initiated by Paul Kienzle in 2000 and that is hosted at @url{http://octave.sourceforge.net}. The package includes commands for setting up various options, output functions etc. before solving a set of differential equations with the solver functions that are also included. OdePkg formerly was initiated to solve explicitly formulated ordinary differential equations (ODEs) only, but there are already improvements so that differential algebraic equations (DAEs) in explicit form can also be solved. At this time OdePkg is under development with the main target, to make a package that is mostly compatible to the solver functions of commercial Octave . +OdePkg is part of the @b{GNU Octave Repository} (resp. the OctaveForge project) that was initiated by Paul Kienzle in the year 2000 and that is hosted at @url{http://octave.sourceforge.net}. The package includes commands for setting up various options, output functions etc. before solving a set of differential equations with the solver functions that are also included. OdePkg formerly was initiated to solve explicitly formulated ordinary differential equations (ODEs) only, but there are already improvements so that differential algebraic equations (DAEs) in explicit form can also be solved. At this time OdePkg is under development with the main target, to make a package that is mostly compatible to commercial solver products. @... OdePkg history and roadmap, Installation and deinstallation, About OdePkg, Beginners's Guide @... OdePkg history and roadmap +@node OdePkg history and road map, Installation and deinstallation, About OdePkg, Beginner's Guide +@section OdePkg history and road map @cindex history @... roadmap +@cindex road map @multitable @columnfractions .25 .75 @item OdePkg Version 0.0.1 @... The initial release was already a modification of the old ``ode package'' that was hosted at OctaveForge and that was written by Marc Compere somewhen between 2000 and 2001. The four variable stepsize RungeKutta algorithms in three solver files and the three fixed stepsize solvers have been merged. It was possible to set some options for these solvers. The four outputfunctions (@command{odeprint}, @command{odeplot}, @command{odephas2} and @command{odephas3}) have been added along with other examples that initialy have not been there. +@tab The initial release was already a modification of the old ``ode package'' that was hosted at OctaveForge and that was written by Marc Compere some when between 2000 and 2001. The four variable stepsize RungeKutta algorithms in three solver files and the three fixed stepsize solvers have been merged. It was possible to set some options for these solvers. The four outputfunctions (@command{odeprint}, @command{odeplot}, @command{odephas2} and @command{odephas3}) have been added along with other examples that initially have not been there. @item OdePkg Version 0.1.x @tab The major milestone along versions 0.1.x was that four stable solvers have been implemented (ie. @command{ode23}, @command{ode45}, @command{ode54} and @command{ode78}) supporting all options that can be set for these kind of solvers and also all necessary functions for setting their options (eg. @command{odeset}, @command{odepkg_structure_check}, etc.). Since version 0.1.3 there is also code available that interfaces the Fortran solver @file{dopri5.f} that is written by Ernst Hairer and Gerhard Wanner (cf. @file{odepkg_mexsolver_dopri5.c} and the helper files @file{odepkgext.c} and @file{odepkgmex.c}). @item @b{(current)} Version 0.2.x @@ 95,7 +96,7 @@ @tab Completed odepkg release 1.0.0 with msolvers and mexsolvers. @end multitable @... Installation and deinstallation, Reporting Bugs, OdePkg history and roadmap, Beginners's Guide +@node Installation and deinstallation, Reporting Bugs, OdePkg history and road map, Beginner's Guide @section Installation and deinstallation @cindex installation @cindex deinstallation @@ 108,7 +109,7 @@ @example pkg uninstall odepkgx.x.x.tar.gz @end example If you encounter problems during the installation process of OdePkg with the @command{pkg} command or if you have an OdePkg that seems to be broken then please report this on the mailinglist of OctaveForge using the email adress +If you encounter problems during the installation process of OdePkg with the @command{pkg} command or if you have an OdePkg that seems to be broken then please report this on the mailinglist of OctaveForge using the email address @ifnothtml @email{octavedev@@lists.sourceforge.net} @end ifnothtml @@ 117,17 +118,17 @@ @end ifhtml . @... Reporting Bugs, First tests and demos, Installation and deinstallation, Beginners's Guide +@node Reporting Bugs, First tests and demos, Installation and deinstallation, Beginner's Guide @section Reporting Bugs @cindex bugs If you encounter problems while using OdePkg or if you find bugs in the source codes then please report that via email at the OctaveForge mailinglist using the email adress +If you encounter problems while using OdePkg or if you find bugs in the source codes then please report that via email at the OctaveForge mailinglist using the email address @ifnothtml @email{octavedev@@lists.sourceforge.net} @end ifnothtml @ifhtml @email{octavedev @{at] lists.sourceforge.net} (replace @{at] with @@) @end ifhtml and directly send a copy to the email adress +and directly send a copy to the email address @ifnothtml @email{treichl@@users.sourceforge.net} @end ifnothtml @@ 136,7 +137,7 @@ @end ifhtml . @... First tests and demos, , Reporting Bugs, Beginners's Guide +@node First tests and demos, , Reporting Bugs, Beginner's Guide @section First tests and demos @cindex First tests and demos Let's have a look at the first ordinary differential equation with the name ``foo''. The ``foo'' equation of second order may be of the form @math{y''(t) + C_1 y'(t) + C_2 y(t) = C_3}. With the substitutions @math{y_1(t) = y(t)} and @math{y_2(t) = y'(t)} this differential equation of second order can be split into two differential equations of first order, ie. @math{y'_1(t) = y_2(t)} and @math{y'_2(t) =  C_1 y_2(t)  C_2 y_1(t) + C_3}. Next the numerical values for the constants need to be defined, ie. @math{C_1 = 2.0}, @math{C_2 = 5.0}, @math{C_3 = 10.0}. This set of ordinary differential equations can now be written as an Octave function like @@ 171,48 +172,120 @@ @end example The OdePkg can do much more while solving ODEs and DAEs, eg. you can set up other output functions instead of the function @command{odeplot}. So as a last example in this beginning chapter it is shown how this can be done, ie. with the command @command{odeset} @example A = odeset ('OutputFcn', @@odeset); +A = odeset ('OutputFcn', @@odeprint); ode45 (@@newfoo, [0 5], [0 0], A, 2.0, 5.0, 10.0); @end example The options structure @command{A} that can be set up with with the command @command{odeset} must always be the fourth input argument when using the mfile RungeKutta solvers (read the help files for the other solvers if there may be changes). The options that can be set are described in @ref{ODE/DAE options}. +The options structure @command{A} that can be set up with with the command @command{odeset} must always be the fourth input argument when using the ODEsolvers and the DAEsolvers (read the help files for the other solvers if there may be changes in the future). The options that can be set are described in @ref{ODE/DAE options}. Before you continue reading the next chapter notice that nearly every function that belongs to the OdePkg has its own help describtion and demos, so you can have a look for yourself how the different functions can be used. If you want to have a look at the help describition then type +Other examples have also been added to the OdePkg. These example files and functions are of the form @command{odepkg_equations_*}. Demos have been added to these functions as well so their functionality can be viewed very quickly. + +Before you continue reading the next chapter notice that nearly every function that belongs to the OdePkg has its own help description and demos, so you can have a look for yourself how the different functions can be used. If you want to have a look at the help description then type @example help fcnname @end example in the Octave interpreter window where @command{fcnname} is the name of the function for the help describtion to be viewed. Type +in the Octave interpreter window where @command{fcnname} is the name of the function for the help description to be viewed. Type @example demo fcnname @end example in the Octave interpreter window where @command{fcnname} is the name of the function of the demo to run. +in the Octave interpreter window where @command{fcnname} is the name of the function of the demo to run. Last but not least write +@example +doc odepkg +@end example +for opening this manual in the texinfo reader of the octave interpreter window. @c %*** End of first chapter: Beginner's Guide @c %*** Start of second chapter: User's Guide @... User's Guide, Coder's Guide, Beginners's Guide, Top +@node User's Guide, Coder's Guide, Beginner's Guide, Top @chapter User's Guide @cindex User's Guide The ``User's Guide'' is intended for users who already do know in principal how to solve differential equations with the higher level language Octave and OdePkg. In this chapter it will be explained which solvers can be used for the different kind of problems in @ref{Solver families} and which options can be set for the optimisation of the solving process in @ref{ODE/DAE options}. +The ``User's Guide'' is intended for trained users who already do know in principal how to solve differential equations with the higher level language Octave and OdePkg. In this chapter it will be explained which solvers can be used for the different kind of problems in @ref{Solver families} and which options can be set for the optimization of the solving process in @ref{ODE/DAE options}. @menu * Solver families:: * ODE/DAE options:: +* Solver families:: The different kind of solvers +* ODE/DAE options:: Options that can be set @end menu @node Solver families, ODE/DAE options, User's Guide, User's Guide @section Solver families @cindex Solver +In this section the different kinds of solvers are explained. It is started with the standard Mfile RungeKutta solvers in section @ref{Mfile RungeKutta solvers} and then it is continued with the Mexfile HairerWanner solvers in section @ref{Mexfile HairerWanner solvers}. Other solvers are described in section @ref{Other solvers}. Performance tests have also been added to the OdePkg. Some of these performance results have been added to section @ref{ODE solver performances}. @menu * Mfile RungeKutta solvers:: * Mexfile HairerWanner solvers:: * Other solvers:: * ODE solver performances:: +* Mfile RungeKutta solvers:: The ODE solvers written in the Octave language +* Mexfile HairerWanner solvers:: Fast ODE/DAE solvers written in CMex +* Other solvers:: Not implemented by now +* ODE solver performances:: Cross Platform performance tests @end menu @node Mfile RungeKutta solvers, Mexfile HairerWanner solvers, Solver families, Solver families @subsection Mfile RungeKutta solvers The mfile RungeKutta solvers are written in the Octave interpreter language and ... +The Mfile RungeKutta solvers are written in the Octave interpreter language. There have been implemented four different solvers within OdePkg, ie. @command{ode23}, @command{ode45}, @command{ode54} and @command{ode78} that are explained in the following. +@table @code +@item ode23 +Integrates a system of ordinary differential equations using 2nd and 3rd order RungeKutta formulas. This particular 3rdorder method reduces to Simpson's 1/3 rule and uses the 3rd order estimation for the output solutions. 3rdorder accurate RungeKutta methods have local and global errors of @math{O(h^4)} and @math{O(h^3)} (where @math{h} is the step size from one to another integration step), respectively and yield exact results when the solution is a cubic. + +The order of the RungeKutta method is the order of the local truncation error, which is the principle error term in the portion of the Taylor series expansion that gets dropped, or intentionally truncated. This is different from the local error which is the difference between the estimated solution and the actual, or true solution. The local error is used in stepsize selection and may be approximated by the difference between two estimates of different order, ie. @math{l(h) = x(O(h+1))  x(O(h))}. With this definition, the local error will be as large as the error in the lower order method. The local truncation error is within the group of terms that gets multipled by the step size @math{h} when solving for a solution from the general RungeKutta method. Therefore, the orderp solution created by the RungeKutta method will be roughly accurate to @math{O(h^{(p+1)})} since the local truncation error shows up in the solution as h*d, which is h times an O(h^(p)) term, or rather O(h^(p+1)). + +@c Summary: For an orderp accurate RK method, +@c  the local truncation error is O(h^p) +@c  the local error used for stepsize adjustment and that +@c is actually realized in a solution is O(h^(p+1)) + +This requires 3 function evaluations per integration step. + +@c Relevant discussion on step size choice can be found on pp.90,91 in +@c U.M. Ascher, L.R. Petzold, Computer Methods for Ordinary Differential Equations +@c and DifferentialAgebraic Equations, Society for Industrial and Applied Mathematics +@c (SIAM), Philadelphia, 1998 + +@c The error estimate formula and slopes are from +@c Numerical Methods for Engineers, 2nd Ed., Chapra & Canale, McGrawHill, 1985 + +@item ode45 +Integrates a system of ordinary differential equations using 4th and 5th order embedded formulas from DormandPrince or Fehlberg. +@c The Fehlberg 4(5) pair is established and works well, however, the DormandPrince 4(5) pair minimizes the local truncation error in the 5thorder estimate which is what is used to step forward (local extrapolation.) Generally it produces more accurate results and costs roughly the same computationally. The DormandPrince pair is the default. +@c This is a 4thorder accurate integrator therefore the local error normally expected is O(h^5). However, because this particular implementation uses the 5thorder estimate for x_out (i.e. local extrapolation) moving forward with the 5thorder estimate should yield local error of O(h^6). +@c The order of the RK method is the order of the local *truncation* error, d, which is the principle error term in the portion of the Taylor series expansion that gets dropped, or intentionally truncated. This is different from the local error which is the difference between the estimated solution and the actual, or true solution. The local error is used in stepsize selection and may be approximated by the difference between two estimates of different order, l(h) = x_(O(h+1))  x_(O(h)). With this definition, the local error will be as large as the error in the lower order method. The local truncation error is within the group of terms that gets multipled by h when solving for a solution from the general RK method. Therefore, the orderp solution created by the RK method will be roughly accurate to O(h^(p+1)) since the local truncation error shows up in the solution as h*d, which is h times an O(h^(p)) term, or rather O(h^(p+1)). +@c Summary: For an orderp accurate RK method, +@c  the local truncation error is O(h^p) +@c  the local error used for stepsize adjustment and that +@c is actually realized in a solution is O(h^(p+1)) +@c This requires 6 function evaluations per integration step. +@c % Both the DormandPrince and Fehlberg 4(5) coefficients are from a tableu in +@c % U.M. Ascher, L.R. Petzold, Computer Methods for Ordinary Differential Equations +@c % and DifferentialAgebraic Equations, Society for Industrial and Applied Mathematics +@c % (SIAM), Philadelphia, 1998 +@c % +@c % The error estimate formula and slopes are from +@c % Numerical Methods for Engineers, 2nd Ed., Chappra & Cannle, McGrawHill, 1985 + +@item ode54 +todo + +@item ode78 +Integrates a system of ordinary differential equations using 7th and 8th order formulas. +@c This is a 7thorder accurate integrator therefore the local error normally expected is O(h^8). However, because this particular implementation uses the 8thorder estimate for xout (i.e. local extrapolation) moving forward with the 8thorder estimate will yield errors on the order of O(h^9). +@c The order of the RK method is the order of the local *truncation* error, d, which is the principle error term in the portion of the Taylor series expansion that gets dropped, or intentionally truncated. This is different from the local error which is the difference between the estimated solution and the actual, or true solution. The local error is used in stepsize selection and may be approximated by the difference between two estimates of different order, l(h) = x_(O(h+1))  x_(O(h)). With this definition, the local error will be as large as the error in the lower order method. The local truncation error is within the group of terms that gets multipled by h when solving for a solution from the general RK method. Therefore, the orderp solution created by the RK method will be roughly accurate to O(h^(p+1)) since the local truncation error shows up in the solution as h*d, which is h times an O(h^(p)) term, or rather O(h^(p+1)). +@c Summary: For an orderp accurate RK method, +@c  the local truncation error is O(h^p) +@c  the local error used for stepsize adjustment and that +@c is actually realized in a solution is O(h^(p+1)) +@c +@c This requires 13 function evaluations per integration step. +@c +@c Relevant discussion on step size choice can be found on pp.90,91 in +@c U.M. Ascher, L.R. Petzold, Computer Methods for Ordinary Differential Equations +@c and DifferentialAgebraic Equations, Society for Industrial and Applied Mathematics +@c (SIAM), Philadelphia, 1998 +@c +@c More may be found in the original author's text containing numerous +@c applications on ordinary and partial differential equations using Matlab: +@c +@c Howard Wilson and Louis Turcotte, 'Advanced Mathematics and +@c Mechanics Applications Using MATLAB', 2nd Ed, CRC Press, 1997 + +@end table @node Mexfile HairerWanner solvers, Other solvers, Mfile RungeKutta solvers, Solver families @subsection Mexfile HairerWanner solvers @@ 221,7 +294,7 @@ @node Other solvers, ODE solver performances, Mexfile HairerWanner solvers, Solver families @subsection Other solvers @... The solvers from Jeff Cash http://www.ma.ic.ac.uk/~jcash have not been added to the OdePkg because it seems that there may exist some unfixed bugs. Modified solver files with bugfixes can be found at http://pitagora.dm.uniba.it/~testset, but the disclaimer's part of this site is not clear and maybe the modified solver files are not GPL compatible. +@c The solvers from Jeff Cash http://www.ma.ic.ac.uk/~jcash have not been added to the OdePkg because it seems that there may exist some unfixed bugs. Modified solver files with bug fixes can be found at http://pitagora.dm.uniba.it/~testset, but the disclaimer's part of this site is not clear and maybe the modified solver files are not GPL compatible. @c The people from the University of Bari at http://pitagora.dm.uniba.it/~testset have been created the solvers BIMD and GAMD. But like before the disclaimer's part of this internet site is not clear and maybe is not GPL compatible. @@ 310,7 +383,7 @@ @table @samp @item RelTol The option @option{RelTol} is used to set the relative error tolerance for the error estimation of the solver while solving. It can either be a positive scalar or a vector with every element of the vector being a positive scalar (this depends on the solver that is used). The definite error estimation equation also depends on the solver that is used, but generalised it may be of the form @math{e(t) = max (RelTol^T y(t), AbsTol)}. Run +The option @option{RelTol} is used to set the relative error tolerance for the error estimation of the solver while solving. It can either be a positive scalar or a vector with every element of the vector being a positive scalar (this depends on the solver that is used). The definite error estimation equation also depends on the solver that is used, but generalized it may be of the form @math{e(t) = max (RelTol^T y(t), AbsTol)}. Run @example A = odeset ('RelTol', 1, 'OutputFcn', @@odeplot); ode78 (@@odepkg_equations_vanderpol, [0 20], [2 0], A); @@ 320,7 +393,7 @@ to see the effect of using different values for the option @option{RelTol}. @item AbsTol The option @option{AbsTol} is used to set the absolute error tolerance for the error estimation of the solver while solving. It can either be a positive scalar or a vector with every element of the vector being a positive scalar (this depends on the solver that is used). The definite error estimation equation also depends on the solver that is used, but generalised it may be of the form @math{e(t) = max (RelTol^T y(t), AbsTol)}. Run +The option @option{AbsTol} is used to set the absolute error tolerance for the error estimation of the solver while solving. It can either be a positive scalar or a vector with every element of the vector being a positive scalar (this depends on the solver that is used). The definite error estimation equation also depends on the solver that is used, but generalized it may be of the form @math{e(t) = max (RelTol^T y(t), AbsTol)}. Run @example A = odeset ('AbsTol', 1e3, 'OutputFcn', @@odeplot); ode78 (@@odepkg_equations_vanderpol, [0 20], [2 0], A); @@ 330,7 +403,7 @@ to see the effect of using different values for the option @option{AbsTol}. @item NormControl The option @option{NormControl} is used to set the type of error tolerance calculation of the solver while solving. It can either be the string @command{'on'} or @command{'off'}. At the time the solver starts the initialisation procedure a warning message may be displayed if the solver will ignore the @command{'on'} setting of this option because of an unhandled resp. missing implementation. The definite error estimation equation if set @command{'on'} also depends on the solver that is used, but generalised it may be of the form @math{e(t) = max (RelTol^T max ( norm (y(t), Inf)), AbsTol)}. Run +The option @option{NormControl} is used to set the type of error tolerance calculation of the solver while solving. It can either be the string @command{'on'} or @command{'off'}. At the time the solver starts the initialization procedure a warning message may be displayed if the solver will ignore the @command{'on'} setting of this option because of an unhandled resp. missing implementation. The definite error estimation equation if set @command{'on'} also depends on the solver that is used, but generalized it may be of the form @math{e(t) = max (RelTol^T max ( norm (y(t), Inf)), AbsTol)}. Run @example A = odeset ('NormControl', 'on', 'OutputFcn', @@odeplot); ode78 (@@odepkg_equations_vanderpol, [0 20], [2 0], A); @@ 398,7 +471,7 @@ to see the effect of using different values for the option @option{Refine}. @item OutputSel The option @option{OutputSel} is used to set the componentes for which output has to be performed if an output function is also set with the option @option{OutputFcn}. It can only be a vector of integer values. Run +The option @option{OutputSel} is used to set the components for which output has to be performed if an output function is also set with the option @option{OutputFcn}. It can only be a vector of integer values. Run @example A = odeset ('OutputSel', [1, 2], 'OutputFcn', @@odeplot); ode78 (@@odepkg_equations_vanderpol, [0 20], [2 0], A); @@ 415,7 +488,7 @@ B = odeset ('Stats', 'on'); [c, d] = ode78 (@@odepkg_equations_vanderpol, [0 2], [2 0], B); @end example to see the effect of using different values for the option @option{Stats}. The cost statistics cn also be obtained if the solver calculation routine is called with one output argument. The cost statistics then are in the output structure in field @option{stats}. Run +to see the effect of using different values for the option @option{Stats}. The cost statistics can also be obtained if the solver calculation routine is called with one output argument. The cost statistics then are in the output structure in field @option{stats}. Run @example A = odeset ('Stats', 'on'); B = ode78 (@@odepkg_equations_vanderpol, [0 2], [2 0], A); 
From: Jorge Barros <ficmatinfmag@us...>  20070314 07:12:33

Update of /cvsroot/octave/octaveforge/language/base/help/octave In directory sc8prcvs3.sourceforge.net:/tmp/cvsserv6780 Modified Files: glpk imagesc imshow pkg rlocus Added Files: cast nbincdf nbininv nbinpdf unidcdf unidinv unidpdf nbinrnd Log Message: added and/or changed in octave.orgcvs  NEW FILE: nbinrnd  * texinfo * @deftypefn {Function File} {} nbinrnd (@var{n}, @var{p}, @var{r}, @var{c}) @deftypefnx {Function File} {} nbinrnd (@var{n}, @var{p}, @var{sz}) Return an @var{r} by @var{c} matrix of random samples from the Pascal (negative binomial) distribution with parameters @var{n} and @var{p}. Both @var{n} and @var{p} must be scalar or of size @var{r} by @var{c}. If @var{r} and @var{c} are omitted, the size of the result matrix is the common size of @var{n} and @var{p}. Or if @var{sz} is a vector, create a matrix of size @var{sz}. @end deftypefn Index: imagesc =================================================================== RCS file: /cvsroot/octave/octaveforge/language/base/help/octave/imagesc,v retrieving revision 1.1 retrieving revision 1.2 diff u d r1.1 r1.2  imagesc 29 Jan 2007 20:19:36 0000 1.1 +++ imagesc 14 Mar 2007 07:12:29 0000 1.2 @@ 1,19 +1,17 @@ * texinfo * @deftypefn {Function File} {} imagesc (@var{A}) @deftypefnx {Function File} {} imagesc (@var{x}, @var{y}, @var{A}) @... {Function File} {} imagesc (@dots{}, @var{zoom}) @deftypefnx {Function File} {} imagesc (@dots{}, @var{limits}) @deftypefnx {Function File} { @var{B} = } imagesc (@dots{}) Display a scaled version of the matrix @var{A} as a color image. The matrix is scaled so that its entries are indices into the current colormap. The scaled matrix is returned. If @var{zoom} is omitted, a comfortable size is chosen. If @var{limits} = [@var{lo}, @var{hi}] are +colormap. The scaled matrix is returned. If @var{limits} = [@var{lo}, @var{hi}] are given, then that range maps into the full range of the colormap rather than the minimum and maximum values of @var{A}. The axis values corresponding to the matrix elements are specified in @var{x} and @var{y}, either as pairs giving the minimum and maximum values for the respective axes, or as values for each row and column of the matrix @var{A}. At present they are ignored. +of the matrix @var{A}. @seealso{image, imshow} @end deftypefn  NEW FILE: nbincdf  * texinfo * @deftypefn {Function File} {} nbincdf (@var{x}, @var{n}, @var{p}) For each element of @var{x}, compute the CDF at x of the Pascal (negative binomial) distribution with parameters @var{n} and @var{p}. The number of failures in a Bernoulli experiment with success probability @var{p} before the @var{n}th success follows this distribution. @end deftypefn Index: rlocus =================================================================== RCS file: /cvsroot/octave/octaveforge/language/base/help/octave/rlocus,v retrieving revision 1.1 retrieving revision 1.2 diff u d r1.1 r1.2  rlocus 29 Jan 2007 20:19:41 0000 1.1 +++ rlocus 14 Mar 2007 07:12:29 0000 1.2 @@ 1,5 +1,5 @@ * texinfo * @... {Function File} {[@var{rldata}, @var{k_break}, @var{rlpol}, @var{gvec}, @var{real_ax_pts}] =} rlocus (@var{sys}[, @var{increment}, @var{min_k}, @var{max_k}]) +@deftypefn {Function File} {[@var{rldata}, @var{k}] =} rlocus (@var{sys}[, @var{increment}, @var{min_k}, @var{max_k}]) Display root locus plot of the specified @acronym{SISO} system. @example @@ 30,14 +30,7 @@ @table @var @item rldata Data points plotted: in column 1 real values, in column 2 the imaginary values. @... k_break +@item k Gains for real axis break points. @... rlpol Closedloop roots for each gain value: 1 locus branch per row; 1 pole set per column @... gvec Gains vector @... real_ax_pts Real axis breakpoints @end table @end deftypefn Index: imshow =================================================================== RCS file: /cvsroot/octave/octaveforge/language/base/help/octave/imshow,v retrieving revision 1.2 retrieving revision 1.3 diff u d r1.2 r1.3  imshow 20 Feb 2007 20:10:38 0000 1.2 +++ imshow 14 Mar 2007 07:12:29 0000 1.3 @@ 5,7 +5,7 @@ @deftypefnx {Function File} {} imshow (@var{R}, @var{G}, @var{B}, @dots{}) @deftypefnx {Function File} {} imshow (@var{filename}) @deftypefnx {Function File} {} imshow (@dots{}, @var{string_param1}, @var{value1}, @dots{}) Display the image @var{im}, where @var{im} can a 2dimensional +Display the image @var{im}, where @var{im} can be a 2dimensional (grayscale image) or a 3dimensional (RGB image) matrix. If three matrices of the same size are given as arguments, they will be concatenated into a 3dimensional (RGB image) matrix. @@ 25,12 +25,8 @@ If given, the parameter @var{string_param1} has value @var{value1}. @var{string_param1} can be any of the following: @table @samp @... "display_range" +@item "displayrange" @var{value1} is the display range as described above.  @... "InitialMagnification" @...{value1} sets the zoom level in percent. If @var{value1} is 100 the image is showed unscaled. @end table @seealso{image, imagesc, colormap, gray2ind, rgb2ind} @end deftypefn  NEW FILE: unidpdf  * texinfo * @deftypefn {Function File} {} unidpdf (@var{x}, @var{v}) For each element of @var{x}, compute the probability density function (pDF) at @var{x} of a univariate discrete distribution which assumes the values in @var{v} with equal probability. @end deftypefn  NEW FILE: nbininv  * texinfo * @deftypefn {Function File} {} nbininv (@var{x}, @var{n}, @var{p}) For each element of @var{x}, compute the quantile at @var{x} of the Pascal (negative binomial) distribution with parameters @var{n} and @var{p}. The number of failures in a Bernoulli experiment with success probability @var{p} before the @var{n}th success follows this distribution. @end deftypefn  NEW FILE: unidinv  * texinfo * @deftypefn {Function File} {} unidinv (@var{x}, @var{v}) For each component of @var{x}, compute the quantile (the inverse of the CDF) at @var{x} of the univariate distribution which assumes the values in @var{v} with equal probability @end deftypefn  NEW FILE: cast  * texinfo * @deftypefn {Function File} {} cast (@var{val}, @var{type}) Convert @var{val} to data type @var{type}. @seealso{int8, uint8, int16, uint16, int32, uint32, int64, uint64, double} @end deftypefn  NEW FILE: nbinpdf  * texinfo * @deftypefn {Function File} {} nbinpdf (@var{x}, @var{n}, @var{p}) For each element of @var{x}, compute the probability density function (PDF) at @var{x} of the Pascal (negative binomial) distribution with parameters @var{n} and @var{p}. The number of failures in a Bernoulli experiment with success probability @var{p} before the @var{n}th success follows this distribution. @end deftypefn Index: pkg =================================================================== RCS file: /cvsroot/octave/octaveforge/language/base/help/octave/pkg,v retrieving revision 1.2 retrieving revision 1.3 diff u d r1.2 r1.3  pkg 3 Feb 2007 19:57:26 0000 1.2 +++ pkg 14 Mar 2007 07:12:29 0000 1.3 @@ 2,7 +2,7 @@ @deftypefn {Command} pkg @var{command} @var{pkg_name} @deftypefnx {Command} pkg @var{command} @var{option} @var{pkg_name} This command interacts with the package manager. Different actions will be taking depending on the value of @var{command}. +be taken depending on the value of @var{command}. @table @samp @item install  NEW FILE: unidcdf  * texinfo * @deftypefn {Function File} {} unidcdf (@var{x}, @var{v}) For each element of @var{x}, compute the cumulative distribution function (CDF) at @var{x} of a univariate discrete distribution which assumes the values in @var{v} with equal probability. @end deftypefn Index: glpk =================================================================== RCS file: /cvsroot/octave/octaveforge/language/base/help/octave/glpk,v retrieving revision 1.2 retrieving revision 1.3 diff u d r1.2 r1.3  glpk 2 Feb 2007 07:34:50 0000 1.2 +++ glpk 14 Mar 2007 07:12:27 0000 1.3 @@ 342,7 +342,8 @@ @item time Time (in seconds) used for solving LP/MIP problem. @item mem Memory (in bytes) used for solving LP/MIP problem. +Memory (in bytes) used for solving LP/MIP problem (this is not +available if the version of GLPK is 4.15 or later). @end table @end table 