diff --git a/doc/Jamfile.v2 b/doc/Jamfile.v2 new file mode 100644 index 00000000..9a751070 --- /dev/null +++ b/doc/Jamfile.v2 @@ -0,0 +1,283 @@ +# (C) Copyright 2009 - 2012 : Karsten Ahnert, Mario Mulansky +# Distributed under the Boost Software License, Version 1.0. +# (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) + + +import quickbook ; +import boostbook ; +import doxygen ; +import modules ; + +project : requirements + $(BOOST_ROOT)/tools/auto_index/include + ; + +if --enable-index in [ modules.peek : ARGV ] +{ + ECHO "Building the odeint docs with automatic index generation enabled." ; + + using auto-index ; + + project : requirements + + on + on + + # Choose indexing method (separately for html and pdf): + html:on # on (or off) to use internally generated indexes. + # html:generate.index=0 # Don't let the XSL stylesheets generate indexes. + + pdf:off # on (or off) to use internally generated indexes. + # index # Use ... as the XML wrapper. + + pdf:index.on.type=1 # For the native stylesheets to generate the different indexes. + # PDF native index support is probably better for PDFs as then you actually get page numbers. + + odeint.idx # Specifies the name of the index script to load. + ../../../.. + + # Inform Quickbook that there is to be an index(es). + enable_index + ; +} +else +{ + ECHO "Building the odeint docs with automatic index generation disabled. To get an auto-index, try building with --enable-index." ; +} + + + +doxygen reference + : +# [ glob ../../../../boost/numeric/odeint/*.hpp ] + [ glob ../../../../boost/numeric/odeint/stepper/*.hpp ] + [ glob ../../../../boost/numeric/odeint/stepper/base/*.hpp ] +# [ glob ../../../../boost/numeric/odeint/stepper/generation/*.hpp ] +# [ glob ../../../../boost/numeric/odeint/integrate/*.hpp ] +# [ glob ../../../../boost/numeric/odeint/iterator/*.hpp ] +# [ glob ../../../../boost/numeric/odeint/algebra/*.hpp ] +# [ glob ../../../../boost/numeric/odeint/util/*.hpp ] +# ../../../../boost/numeric/odeint.hpp + : + + # Lots of parameters passed to Doxygen. You can see these in the doxygen docs, or the Wizard Expert tab displays them. + # If you have successfuly built your Doxygen docs standalone using the Wizard (strongly recommended as it is much quicker). + # The values in your project's doxyfile are what to put as the Doxygen parameters passed below. + WARNINGS=YES + WARN_LOGFILE=AutoDoxywarnings.log + WARN_IF_UNDOCUMENTED=NO # Default NO but useful if you aim to Doxygen document *all* members. + QUIET=NO + WARN_NO_PARAMDOC=NO # Default no, but YES useful if you aim to document all function parameters. + DOXYFILE_ENCODING=UTF-8 + PROJECT_NAME="odeint" + PROJECT_NUMBER=2.2 + TAB_SIZE=2 + SORT_MEMBER_DOCS=NO + SORT_BRIEF_DOCS=NO + SORT_MEMBERS_CTORS_1ST=NO + EXTRACT_PRIVATE=NO + INLINE_INHERITED_MEMB=YES + INHERIT_DOCS=YES + EXTRACT_STATIC=YES + EXTRACT_ANON_NSPACES=NO + EXTRACT_LOCAL_CLASSES=YES + EXTRACT_LOCAL_METHODS=YES + HIDE_UNDOC_MEMBERS=NO + HIDE_UNDOC_CLASSES=YES + HIDE_FRIEND_COMPOUNDS=NO + #HIDE_INBODY_DOCS=NO + INTERNAL_DOCS=YES + CASE_SENSE_NAMES=NO + HIDE_SCOPE_NAMES=NO + + # Preprocessor settings. + # Some ugly examples of predefined macro calls (from Boost.Units library) :( + "PREDEFINED= \\ + \"BOOST_UNITS_STATIC_CONSTANT(a,b)=static const b a\" \\ + \"BOOST_UNITS_TYPEOF(a)=typeof(a)\" \\ + \"BOOST_PREVENT_MACRO_SUBSTITUTION=\" \\ + \"BOOST_UNITS_HAS_TYPEOF=1\" \\ + \"DOXYGEN_SKIP=1\" " + ENABLE_PREPROCESSING=YES # Evaluates all C-preprocessor directives found in files. + MACRO_EXPANSION=YES # Will expand all macro names. + EXPAND_ONLY_PREDEF=YES # Only predefined macros expanded. See units library for an example. + SEARCH_INCLUDES=YES # Search #include files found. + INLINE_INFO=YES # If the INLINE_INFO tag is set to YES (the default) then a tag [inline] is inserted in the documentation for inline members. + + SHOW_INCLUDE_FILES=NO # List of the files that are included by a file in the documentation of that file. + REPEAT_BRIEF=YES # Prepend the brief description of a member or function before the detailed description + BRIEF_MEMBER_DESC=YES # Include brief member descriptions after the members that are listed in the file and class + MULTILINE_CPP_IS_BRIEF=YES # Treat a multi-line C++ special comment block (i.e. a block of //! or /// comments) as a brief description. + # May be best to always use \brief and \details to avoid ambiguity? + # STRIP_FROM_PATH=NO # Most useful to leave default to strip just the directory from which Doxygen is run. + # Yes gives the full path, but NO is more useful, only giving enough to be + # CPP_CLI_SUPPORT=NO # unless, most unusually, you are compiled for a 'managed' CLI application. + SHOW_USED_FILES=YES # Default YES to show a list files used to generate documention. + SHOW_DIRECTORIES=YES # Default NO, but useful to show directory heirarchy. + SHOW_FILES=YES # Default YES is to include a tab for a page of files listed. Useful. + SHOW_NAMESPACES=YES # Default YES to include tab for list of namespaces. Useful if you have namespacess other than boost:: + FILE_PATTERNS= # Types of files to be used as input. Default includes *.c *.cc *.cxx *.cpp *.c++ *.ipp *.i++ *.inl *.h *.hh *.hxx *.hpp *.h++ *.py + # Might include .qbk? + + RECURSIVE=YES # Search recursively down subdirectories. + EXCLUDE= # Files or directories that should be excluded from INPUT source files. + # Headers and footers are actually rather attractive, + # HTML_HEADER="doxygen/checks_doxygen_header.html" # A sample including a draft stamp and 'Not_Yet_In_Boost' logo. + # Take care that if you use this (recommended), you need to ensure that the html + # HTML_FOOTER="doxygen/checks_doxygen_footer.html" # This is very useful to add copyright, date of revision, versioning etc. + + # A custom stylesheet is also useful, as the default syntax coloring is 'unusual' ;-) + HTML_STYLESHEET="doxygen/doxygen.css" # Placed in the doxygen directory, + # this will change to your choice of C++ syntax coloring when viewing source from Doxygen. + # Users can place (or edit) their own personal choice CSS file here. + + # Default is just Reference but you can provide your own title for reference section here. + "boost.doxygen.reftitle=odeint Reference" +; + + +xml odeint + : + odeint.qbk + : +; + +boostbook standalone + : + odeint + : + + # Path for links to Boost: + #boost.root=\$(local-boost-root) # Link to Boost logo boost.png + # Links are relative and trying to make absolute does NOT work. + # And remember that all links MUST (unless in quotes) use backslash, not forward that is trip char. + + boost.root=../../../.. # OK but link to I:/boost_trunk/boost.png + + # Also control links to admonitions, so need to set separately. + #boost.root=../../../../../../../boost_1_47_0 # OK file:///I:/boost_1_48_0/boost.png + # Quickbook [@boost:/boost/units/detail/utility.hpp] should make it relative to xsl parameter boost.root. + + # Path for libraries index: + boost.libraries=../../../../../../../boost_1_47_0/libs/libraries.htm + # Use the main Boost stylesheet: + html.stylesheet=./boostbook.css # in /doc folder. + + # Use the your own local Boost stylesheet: + # html.stylesheet=../html/boostbook.css + + # Some general style settings: + # see http://docbook.sourceforge.net/release/xsl/current/doc/html/index.html + table.footnote.number.format=1 # Identifies the format used for footnote numbers in tables. + footnote.number.format=1 # Identifies the format used for text footnote numbers. + + # Default to not including the Boost logo in the navbar, when one expressly asks to include the navbar. + # Boost jamroot now includes + # Default to not include a navbar. + #nav.layout=none # No navigation bar (home, prev, next). + # defining creates a runtime error: Global parameter nav.layout already defined + #nav.layout=horizontal # to get a horizontal navigation bar (you probably DO want this). + + boost.image=Boost # options are: none (no logo), Boost (for boost.png), or your own logo like proposed_for_boost.png + boost.image.src=logo.jpg # + boost.image.width=294 # Width of logo in pixels. + boost.image.height=127 # Height of logo in pixels. + + + # HTML options: + # ------------ + navig.graphics=1 # Use graphics not text for navigation. + chunk.section.depth=2 # How far down we chunk nested sections, basically all of them. + chunk.first.sections=1 # Don't put the first section on the same page as the TOC. + toc.section.depth=2 # How far down sections get TOCs. + toc.max.depth=2 # Max depth in each TOC. + generate.section.toc.level=3 # How far down we go with TOCs. + + #html:admon.graphics.extension=".png" # default type for admonitions (important, warning, note ...) + #html:admon.graphics.path=$(nav-images)/ # path to admonition (warning, note...) image (.png) files. + + # http://docbook.sourceforge.net/release/images/draft.png + # but use a local copy of draft.png. + + # PDF Options: + # ----------- + # TOC Generation + fop1.extensions=0 # DISable extensions for FOP version 0.90 and later . + pdf:fop.extensions=0 # DISable extensions for FOP version 0.20.5 and earlier. + pdf:xep.extensions=1 # Use XEP extension- PDF bookmarks, document information and better index processing. + + # No indent on body text: + pdf:body.start.indent=0pt # + pdf:paper.type=A4 # Paper type = A4 + # http://xml.resource.org/public/rfc/html/rfc2346.html + # Making Postscript and PDF International, J Palme, RFC 2346 recommends + # If you are using US letter paper format, ensure that both left and right margins are at least 21 mm (0.8 in). + # If you are using A4 paper, ensure that both the top and bottom margins are at least 33 mm (1.3 in). + # Margins sizes: + #pdf:page.margin.top=1.3in + #pdf:page.margin.inner=0.8in + #pdf:page.margin.bottom=1.3in + #pdf:page.margin.outer=0.8in + + # http://docbook.sourceforge.net/release/xsl/current/doc/index.html + # DocBook XSL Stylesheets: Reference Documentation. + + # Yes, we want graphics for admonishments: + admon.graphics=1 + # Set these one for PDF generation *only*: + # In PDF format, default PNG graphics are awful, so better use SVG images (type .svg) instead. + pdf:admon.graphics.extension=".svg" # + pdf:use.role.for.mediaobject=1 # Use print role on next line. + pdf:preferred.mediaobject.role=print # pdf role is to be printed. + pdf:img.src.path=$(images_location)/ # Path of image (.svg) files. (Note trailing /) ? + pdf:admon.graphics.path=$(nav_images)/ # path to admonition (warning, note...) image (.svg) files. + pdf:draft.mode="yes" # Yes if draft watermark wanted! + #pdf:draft.watermark.image="draft.png" # Watermark (local copy). + #pdf:draft.watermark.image=http://docbook.sourceforge.net/release/images/draft.png # Watermark. + + reference # Doxygen reference section + # pdf-install # final pdf + # png-install # Boost standard icons in both png + # svg-install # and svg. +; + + +# To install a copy of 'master' boostbook.css and logo. +# install html : ../../../doc/html/boostbook.css ; +# install ../ : ../../../boost.png ; + + + +# Install (copy) the 'master' copy of boostbook Cascading Style sheet +# from your current Boost-root to the /doc/html folder. +# path-constant boost-root : [ modules.peek : BOOST ] ; +# install css-install : $(boost-root)/doc/src/boostbook.css : html ; + +# path-constant boost-root : [ modules.peek : BOOST ] ; + + +# Install (copy) the 'master' copies of all icon images (both PNG and SVG) +# and the Boost logo from your current Boost-root +# to the local /doc/html/images folder so that html is complete and standalone. +# install png-install : [ glob $(boost-root)/doc/src/images/*.png $(boost-root)/boost.png ] : html/images ; +# install svg-install : [ glob $(boost-root)/doc/src/images/*.svg ] : html/images ; + +# install unordered_pdf : standalone/pdf : . ; +# explicit unordered_pdf ; +# The explicit rule is there so that it's only installed when the target is explicitly named. + +# Effectively copies the file from \bin folder to the \doc folder. +# install pdf-install : standalone : . PDF ; +# But will not work as expected if doxygen and/or autoindex is used +# because a modified pdf file is created, so this command below +# will rename the file to the expected filename, here quick_auto_dox_index.pdf. +# . means installed in same place as this jamfile, /doc. + +install pdf-install : standalone : PDF . checks.pdf ; + +install callouts : [ glob src/images/callouts/*.png ] : html/images/callouts ; + + + + + diff --git a/doc/acknowledgements.qbk b/doc/acknowledgements.qbk new file mode 100644 index 00000000..417154e6 --- /dev/null +++ b/doc/acknowledgements.qbk @@ -0,0 +1,37 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section Acknowledgments] + + +[/ + +* Steven Watanabe for managing the Boost review process. +* All people who participated in the odeint review process on the Boost mailing list. +* Paul Bristow for helping with the documentation. +* The Google Summer Of Code (GSOC) program for funding and Andrew Sutton for supervising us during the GSOC and for lots of useful discussions and feedback about many implementation details.. +* Joachim Faulhaber for motivating us to participate in the Boost review process and many detailed comments about the library. +* All users of odeint. They are the main motivation for our efforts. + + +[h3 Contributers] + +* Andreas Angelopoulos implemented the sparse matrix implicit Euler stepper using the MTL4 library. +* Rajeev Singh implemented the stiff Van der Pol oscillator example. +* Sylwester Arabas improved the documentation. +* Denis Demidov provided the adaption to the VexCL and Viennacl libraries. +* Christoph Koke provided improved binders. +* Lee Hodgkinson provided the black hole example. +] + + +[endsect] diff --git a/doc/concepts.qbk b/doc/concepts.qbk new file mode 100644 index 00000000..84b628b2 --- /dev/null +++ b/doc/concepts.qbk @@ -0,0 +1,26 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section:concepts Concepts] +[# odeint.concepts] + +[include concepts/system.qbk] +[include concepts/symplectic_system.qbk] +[include concepts/implicit_system.qbk] +[include concepts/stepper.qbk] +[include concepts/error_stepper.qbk] +[include concepts/controlled_stepper.qbk] +[include concepts/dense_output_stepper.qbk] +[include concepts/state_algebra_operations.qbk] +[include concepts/state_wrapper.qbk] + +[endsect] \ No newline at end of file diff --git a/doc/concepts/controlled_stepper.qbk b/doc/concepts/controlled_stepper.qbk new file mode 100644 index 00000000..996b0055 --- /dev/null +++ b/doc/concepts/controlled_stepper.qbk @@ -0,0 +1,74 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section Controlled Stepper] + +This concept specifies the interface a controlled stepper has to fulfill to be used within __integrate_functions. + +[heading Description] + +A controlled stepper following this Controlled Stepper concept provides the possibility to perform one step of the solution /x(t)/ of an ODE with step-size /dt/ to obtain /x(t+dt)/ with a given step-size /dt/. +Depending on an error estimate of the solution the step might be rejected and a smaller step-size is suggested. + +[heading Associated types] + +* ''''''[*state_type]'''''' +''''''`Stepper::state_type`'''''' +''''''The type characterizing the state of the ODE, hence ['x].'''''' + +* ''''''[*deriv_type]'''''' +''''''`Stepper::deriv_type`'''''' +''''''The type characterizing the derivative of the ODE, hence ['d x/dt].'''''' + +* ''''''[*time_type]'''''' +''''''`Stepper::time_type`'''''' +''''''The type characterizing the dependent variable of the ODE, hence the time ['t].'''''' + +* ''''''[*value_type]'''''' +''''''`Stepper::value_type`'''''' +''''''The numerical data type which is used within the stepper, something like `float`, `double`, `complex< double >`.'''''' + +* ''''''[*stepper_category]'''''' +''''''`Stepper::stepper_category`'''''' +''''''A tag type characterizing the category of the stepper. This type must be convertible to `controlled_stepper_tag`.'''''' + + + +[heading Notation] + +[variablelist + [[`ControlledStepper`] [A type that is a model of Controlled Stepper]] + [[`State`] [A type representing the state /x/ of the ODE]] + [[`Time`] [A type representing the time /t/ of the ODE]] + [[`stepper`] [An object of type `ControlledStepper`]] + [[`x`] [Object of type `State`]] + [[`t`, `dt`] [Objects of type `Time`]] + [[`sys`] [An object defining the ODE, should be a model of __system, __symplectic_system, __simple_symplectic_system or __implicit_system.]] +] + +[heading Valid Expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Do step] [``stepper.try_step( sys , x , t , dt )``] [`controlled_step_result`] [Tries one step of step size `dt`. If the step was successful, `success` is returned, the resulting state is written to `x`, the new time is stored in `t` and `dt` now contains a new (possibly larger) step-size for the next step. If the error was too big, `rejected` is returned and the results are neglected - `x` and `t` are unchanged and `dt` now contains a reduced step-size to be used for the next try.] ] + [/ [Do step with reference] [`stepper.try_step( boost::ref(sys) , x , t , dt )`] [`void`] [Same as above with `System` as reference] ] +] + +[heading Models] + +* `controlled_error_stepper< runge_kutta_cash_karp54 >` +* `controlled_error_stepper_fsal< runge_kutta_dopri5 >` +* `controlled_error_stepper< runge_kutta_fehlberg78 >` +* `rosenbrock4_controller` +* `bulirsch_stoer` + +[endsect] \ No newline at end of file diff --git a/doc/concepts/dense_output_stepper.qbk b/doc/concepts/dense_output_stepper.qbk new file mode 100644 index 00000000..8834f619 --- /dev/null +++ b/doc/concepts/dense_output_stepper.qbk @@ -0,0 +1,81 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[section Dense Output Stepper] + +This concept specifies the interface a dense output stepper has to fulfill to be used within __integrate_functions. + +[heading Description] +A dense output stepper following this Dense Output Stepper concept provides the possibility to perform a single step of the solution /x(t)/ of an ODE to obtain /x(t+dt)/. +The step-size `dt` might be adjusted automatically due to error control. +Dense output steppers also can interpolate the solution to calculate the state /x(t')/ at any point /t <= t' <= t+dt/. + +[heading Associated types] + +* ''''''[*state_type]'''''' +''''''`Stepper::state_type`'''''' +''''''The type characterizing the state of the ODE, hence ['x].'''''' + +* ''''''[*deriv_type]'''''' +''''''`Stepper::deriv_type`'''''' +''''''The type characterizing the derivative of the ODE, hence ['d x/dt].'''''' + +* ''''''[*time_type]'''''' +''''''`Stepper::time_type`'''''' +''''''The type characterizing the dependent variable of the ODE, hence the time ['t].'''''' + +* ''''''[*value_type]'''''' +''''''`Stepper::value_type`'''''' +''''''The numerical data type which is used within the stepper, something like `float`, `double`, `complex< double >`.'''''' + +* ''''''[*stepper_category]'''''' +''''''`Stepper::stepper_category`'''''' +''''''A tag type characterizing the category of the stepper. This type must be convertible to `dense_output_stepper_tag`.'''''' + + +[heading Notation] + +[variablelist + [[`Stepper`] [A type that is a model of Dense Output Stepper]] + [[`State`] [A type representing the state /x/ of the ODE]] + [[`stepper`] [An object of type `Stepper`]] + [[`x0`, `x`] [Object of type `State`]] + [[`t0`, `dt0`, `t`] [Objects of type `Stepper::time_type`]] + [[`sys`] [An object defining the ODE, should be a model of __system, __symplectic_system, __simple_symplectic_system or __implicit_system.]] +] + +[heading Valid Expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + + [[Initialize integration] [`stepper.initialize( x0 , t0 , dt0 )`] [void] [Initializes the stepper with initial values `x0`, `t0` and `dt0`.]] + + [[Do step] [`stepper.do_step( sys )`] [`std::pair< Stepper::time_type , Stepper::time_type >`] [Performs one step using the ODE defined by `sys`. The step-size might be changed internally due to error control. This function returns a pair containing `t` and `t+dt` representing the interval for which interpolation can be performed.] ] + + [/ [Do step with reference] [`stepper.do_step( boost::ref( sys ) )`] [`std::pair< Stepper::time_type , Stepper::time_type >`] [Same as above with `System` as reference] ] + + [[Do interpolation] [`stepper.calc_state( t_inter , x )`] [`void`] [Performs the interpolation to calculate /x(t[sub inter]/) where /t <= t[sub inter] <= t+dt/.]] + + [[Get current time] [`stepper.current_time()`] [`const Stepper::time_type&`] [Returns the current time /t+dt/ of the stepper, that is the end time of the last step and the starting time for the next call of `do_step`]] + + [[Get current state] [`stepper.current_state()`] [`const Stepper::state_type&`] [Returns the current state of the stepper, that is /x(t+dt)/, the state at the time returned by `stepper.current_time()`]] +] + +[heading Models] + +* `dense_output_controlled_explicit_fsal< controlled_error_stepper_fsal< runge_kutta_dopri5 >` +* `bulirsch_stoer_dense_out` +* `rosenbrock4_dense_output` + +[endsect] \ No newline at end of file diff --git a/doc/concepts/error_stepper.qbk b/doc/concepts/error_stepper.qbk new file mode 100644 index 00000000..199b25a6 --- /dev/null +++ b/doc/concepts/error_stepper.qbk @@ -0,0 +1,100 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[section Error Stepper] + +This concepts specifies the interface an error stepper has to fulfill to be used within a ControlledErrorStepper. An error stepper must always fullfil the stepper concept. This can trivially implemented by + +`` +template< class System > +error_stepper::do_step( System sys , state_type &x , time_type t , time_type dt ) +{ + state_type xerr; + // allocate xerr + do_step( sys , x , t , dt , xerr ); +} +`` + +[heading Description] + +An error stepper following this Error Stepper concept is capable of doing one step of the solution /x(t)/ of an ODE with step-size /dt/ to obtain /x(t+dt)/ and also computing an error estimate ['x[sub err]] of the result. +Error Steppers can be Runge-Kutta steppers, symplectic steppers as well as implicit steppers. +Based on the stepper type, the ODE is defined as __system, __symplectic_system, __simple_symplectic_system or __implicit_system. + +[heading Refinement of] + +* DefaultConstructable +* CopyConstructable +* Stepper + +[heading Associated types] + +* ''''''[*state_type]'''''' +''''''`Stepper::state_type`'''''' +''''''The type characterizing the state of the ODE, hence ['x].'''''' + +* ''''''[*deriv_type]'''''' +''''''`Stepper::deriv_type`'''''' +''''''The type characterizing the derivative of the ODE, hence ['d x/dt].'''''' + +* ''''''[*time_type]'''''' +''''''`Stepper::time_type`'''''' +''''''The type characterizing the dependent variable of the ODE, hence the time ['t].'''''' + +* ''''''[*value_type]'''''' +''''''`Stepper::value_type`'''''' +''''''The numerical data type which is used within the stepper, something like `float`, `double`, `complex< double >`.'''''' + +* ''''''[*order_type]'''''' +''''''`Stepper::order_type`'''''' +''''''The type characterizing the order of the ODE, typically `unsigned short`.'''''' + +* ''''''[*stepper_category]'''''' +''''''`Stepper::stepper_category`'''''' +''''''A tag type characterizing the category of the stepper. This type must be convertible to `error_stepper_tag`.'''''' + + +[heading Notation] + +[variablelist + [[`ErrorStepper`] [A type that is a model of Error Stepper]] + [[`State`] [A type representing the state /x/ of the ODE]] + [[`Error`] [A type representing the error calculated by the stepper, usually same as `State`]] + [[`Time`] [A type representing the time /t/ of the ODE]] + [[`stepper`] [An object of type `ErrorStepper`]] + [[`x`] [Object of type `State`]] + [[`xerr`] [Object of type `Error`]] + [[`t`, `dt`] [Objects of type `Time`]] + [[`sys`] [An object defining the ODE, should be a model of either __system, __symplectic_system, __simple_symplectic_system or __implicit_system.]] +] + +[heading Valid Expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Get the stepper order] [`stepper.order()`] [`order_type`] [Returns the order of the stepper for one step without error estimation.]] + [[Get the stepper order] [`stepper.stepper_order()`] [`order_type`] [Returns the order of the stepper for one error estimation step which is used for error calculation.]] + [[Get the error order] [`stepper.errorr_order()`] [`order_type`] [Returns the order of the error step which is used for error calculation.]] + [[Do step] [`stepper.do_step( sys , x , t , dt )`] [`void`] [Performs one step of step size `dt`. The newly obtained state is written in-place to `x`.] ] + [[Do step with error estimation] [`stepper.do_step( sys , x , t , dt , xerr )`] [`void`] [Performs one step of step size `dt` with error estimation. The newly obtained state is written in-place to `x` and the estimated error to `xerr`.] ] + [/ [Do step with reference] [`stepper.do_step( boost::ref(sys) , x , t , dt , xerr )`] [`void`] [Performs one step of step size `dt`. The newly obtained state is written in-place to `x` and the estimated error to `xerr`.] ] +] + +[heading Models] + +* `runge_kutta_cash_karp54` +* `runge_kutta_dopri5` +* `runge_kutta_fehlberg78` +* `rosenbrock4` + +[endsect] diff --git a/doc/concepts/implicit_system.qbk b/doc/concepts/implicit_system.qbk new file mode 100644 index 00000000..2b1336d7 --- /dev/null +++ b/doc/concepts/implicit_system.qbk @@ -0,0 +1,43 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[section Implicit System] + +[heading Description] + +This concept describes how to define a ODE that can be solved by an implicit routine. +Implicit routines need not only the function /f(x,t)/ but also the Jacobian /df/dx = A(x,t)/. +/A/ is a matrix and implicit routines need to solve the linear problem /Ax = b/. +In odeint this is implemented with use of __ublas, therefore, the ['state_type] implicit routines is ['ublas::vector] and the matrix is defined as ['ublas::matrix]. + +[heading Notation] + +[variablelist + [[`System`] [A type that is a model of `Implicit System`]] + [[`Time`] [A type representing the time of the ODE]] + [[`sys`] [An object of type `System`]] + [[`x`] [Object of type ublas::vector]] + [[`dxdt`] [Object of type ublas::vector]] + [[`jacobi`] [Object of type ublas::matrix]] + [[`t`] [Object of type `Time`]] +] + +[heading Valid Expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Calculate ['dx/dt := f(x,t)]] [`sys.first( x , dxdt , t )`] [`void`] [Calculates `f(x,t)`, the result is stored into dxdt] ] + [[Calculate ['A := df/dx (x,t)]] [`sys.second( x , jacobi , t )`] [`void`] [Calculates the Jacobian of /f/ at /x/,/t/, the result is stored into `jacobi`] ] +] + +[endsect] \ No newline at end of file diff --git a/doc/concepts/state_algebra_operations.qbk b/doc/concepts/state_algebra_operations.qbk new file mode 100644 index 00000000..c807fb54 --- /dev/null +++ b/doc/concepts/state_algebra_operations.qbk @@ -0,0 +1,123 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[section State Algebra Operations] + +[note The following does not apply to implicit steppers like implicit_euler or Rosenbrock 4 as there the `state_type` can not be changed from `ublas::vector` and no algebra/operations are used.] + +[heading Description] + +The `State`, `Algebra` and `Operations` together define a concept describing how the mathematical vector operations required for the stepper algorithms are performed. +The typical vector operation done within steppers is + +['*y* = __Sigma __alpha[sub i] [*x[sub i]]]. + +The `State` represents the state variable of an ODE, usually denoted with /x/. +Algorithmically, the state is often realized as a `vector< double >` or `array< double , N >`, however, the genericity of odeint enables you to basically use anything as a state type. +The algorithmic counterpart of such mathematical expressions is divided into two parts. +First, the `Algebra` is used to account for the vector character of the equation. +In the case of a `vector` as state type this means the `Algebra` is responsible for iteration over all vector elements. +Second, the `Operations` are used to represent the actual operation applied to each of the vector elements. +So the `Algebra` iterates over all elements of the `State`s and calls an operation taken from the `Operations` for each element. +This is where `State`, `Algebra` and `Operations` have to work together to make odeint running. +Please have a look at the `range_algebra` and `default_operations` to see an example how this is implemented. + +In the following we describe how `State`, `Algebra` and `Operations` are used together within the stepper implementations. + +[section Operations] + +[heading Notation] + +[variablelist + [[`Operations`] [The operations type]] + [/[`Time`] [A type representing the time type of steppers]] + [[`Value1`, ... , `ValueN`] [Types representing the value or time type of stepper]] + [[`Scale`] [Type of the scale operation]] + [[`scale`] [Object of type `Scale`]] + [[[^ScaleSum['N]]] [Type that represents a general scale_sum operation, [^/N/] should be replaced by a number from 1 to 14.]] + [[[^scale_sum['N]]] [Object of type [^ScaleSum['N]], [^/N/] should be replaced by a number from 1 to 14.]] + [[`ScaleSumSwap2`] [Type of the scale sum swap operation]] + [[`scale_sum_swap2`] [Object of type `ScaleSumSwap2`]] + [[`a1, a2, ...`] [Objects of type `Value1`, `Value2`, ...]] + [[`y, x1, x2, ...`] [Objects of `State`'s value type]] +] + +[heading Valid Expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Get scale operation] [`Operations::scale< Value >`] [`Scale`] [Get `Scale` from `Operations`]] + [[`Scale` constructor] [`Scale< Value >( a )`] [`Scale`] [Constructs a `Scale` object]] + [[`Scale` operation] [`scale( x )`] [`void`] [Calculates `x *= a`]] + [[Get general `scale_sum` operation] [[^Operations::scale_sum['N]< Value1 , ... , ValueN >]] [[^ScaleSum['N]]] [Get the [^ScaleSum['N]] type from `Operations`, [^/N/] should be replaced by a number from 1 to 14.]] + [[`scale_sum` constructor] [[^ScaleSum['N]< Value1 , ... , ValueN >( a1 , ... , aN )]] [[^ScaleSum['N]]] [Constructs a `scale_sum` object given [^/N/] parameter values with [^/N/] between 1 and 14.]] + [[`scale_sum` operation] [[^scale_sum['N]( y , x1 , ... , xN )]] [`void`] [Calculates `y = a1*x1 + a2*x2 + ... + aN*xN`. Note that this is an [^/N/+1]-ary function call.]] + [[Get scale sum swap operation] [`Operations::scale_sum_swap2< Value1 , Value2 >`] [`ScaleSumSwap2`] [Get scale sum swap from operations]] + [[`ScaleSumSwap2` constructor] [`ScaleSumSwap2< Value1 , Value2 >( a1 , a2 )`] [`ScaleSumSwap2`] [Constructor]] + [[`ScaleSumSwap2` operation] [`scale_sum_swap2( x1 , x2 , x3 )`] [`void`] [Calculates `tmp = x1`, `x1 = a1*x2 + a2*x3` and `x2 = tmp`.]] +] + +[endsect] + +[section Algebra] + +[heading Notation] + +[variablelist + [[`State`] [The state type]] + [[`Algebra`] [The algebra type]] + [[[^Operation['N]]] [An [^/N/]-ary operation type, [^/N/] should be a number from 1 to 14.]] + [[`algebra`] [Object of type `Algebra`]] + [[[^operation['N]]] [Object of type [^Operation['N]]]] + [[`y, x1, x2, ...`] [Objects of type `State`]] +] + + +[heading Valid Expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Vector Operation with arity 2] [`algebra.for_each2( y , x , operation2 )`] [void] [Calls `operation2( y_i , x_i )` for each element `y_i` of `y` and `x_i` of `x`.]] + [[Vector Operation with arity 3] [`algebra.for_each3( y , x1 , x2 , operation3 )`] [void] [Calls `operation3( y_i , x1_i , x2_i )` for each element `y_i` of `y` and `x1_i` of `x1` and `x2_i` of `x2`.]] + [[Vector Operation with arity [^/N/]] [[^algebra.for_each['N]( y , x1 , ... , xN , operation['N] )]] [void] [Calls [^operation['N]( y_i , x1_i , ... , xN_i )] for each element `y_i` of `y` and `x1_i` of `x1` and so on. [^/N/] should be replaced by a number between 1 and 14.]] +] + +[endsect] + +[section Pre-Defined implementations] + +As standard configuration odeint uses the `range_algebra` and `default_operations` which suffices most situations. +However, a few more possibilities exist either to gain better performance or to ensure interoperability with other libraries. +In the following we list the existing `Algebra`/`Operations` configurations that can be used in the steppers. + +[table + [[`State`] [`Algebra`] [`Operations`] [Remarks]] + [[Anything supporting __boost_range, like `std::vector`, `std::list`, `boost::array`,... based on a `value_type` that supports operators +,* (typically `double`)] [`range_algebra`] [`default_operations`] [Standard implementation, applicable for most typical situations.]] + [[`boost::array` based on a `value_type` that supports operators +,*] [`array_algebra`] [`default_operations`] [Special implementation for boost::array with better performance than `range_algebra`]] + [[Anything that defines operators + within itself and * with scalar (Mathematically spoken, anything that is a vector space).] [`vector_space_algebra`] [`default_operations`] [For the use of __controlled_stepper, the template `vector_space_reduce` has to be instantiated.]] + [[`thrust::device_vector`, `thrust::host_vector`] [`thrust_algebra`] [`thrust_operations`] [For running odeint on CUDA devices by using __thrust]] + [[`boost::array` or anything which allocates the elements in a C-like manner] [`vector_space_algebra`] [`mkl_operations`] [Using the __intel_mkl in odeint for maximum performance. Currently, only the RK4 stepper is supported.]] +] + +[endsect] + +[section Example expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Vector operation] [`algebra.for_each3( y , x1 , x2 , Operations::scale_sum2< Value1 , Value2 >( a1 , a2 ) )`] [void] [Calculates ['*y* = a1 *x1* + a2 *x2*]]] +] + +[endsect] + +[endsect] \ No newline at end of file diff --git a/doc/concepts/state_wrapper.qbk b/doc/concepts/state_wrapper.qbk new file mode 100644 index 00000000..15c7a685 --- /dev/null +++ b/doc/concepts/state_wrapper.qbk @@ -0,0 +1,39 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section State Wrapper] + +[heading Description] + +The `State Wrapper` concept describes the way odeint creates temporary state objects to store intermediate results within the stepper's `do_step` methods. + +[heading Notation] + +[variablelist + [[`State`] [A type that is the `state_type` of the ODE]] + [[`WrappedState`] [A type that is a model of State Wrapper for the state type `State`.]] + [[`x`] [Object of type `State`]] + [[`w`] [Object of type `WrappedState`]] +] + +[heading Valid Expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Get resizeability] [`is_resizeable< State >`] [`boost::false_type` or `boost::true_type`] [Returns `boost::true_type` if the `State` is resizeable, `boost::false_type` otherwise.]] + [[Create `WrappedState` type] [`state_wrapper< State >`] [`WrappedState`] [Creates the type for a `WrappedState` for the state type `State`]] + [[Constructor] [`WrappedState()`] [`WrappedState`] [Constructs a state wrapper with an empty state]] + [[Copy Constructor] [`WrappedState( w )`] [`WrappedState`] [Constructs a state wrapper with a state of the same size as the state in `w`]] + [[Get state] [`w.m_v`] [`State`] [Returns the `State` object of this state wrapper.]] +] + +[endsect] \ No newline at end of file diff --git a/doc/concepts/stepper.qbk b/doc/concepts/stepper.qbk new file mode 100644 index 00000000..532ccf79 --- /dev/null +++ b/doc/concepts/stepper.qbk @@ -0,0 +1,92 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section Stepper] + +This concepts specifies the interface a simple stepper has to fulfill to be used within the __integrate_functions. + +[heading Description] + +The basic stepper concept. +A basic stepper following this Stepper concept is able to perform a single step of the solution /x(t)/ of an ODE to obtain /x(t+dt)/ using a given step size /dt/. +Basic steppers can be Runge-Kutta steppers, symplectic steppers as well as implicit steppers. +Depending on the actual stepper, the ODE is defined as __system, __symplectic_system, __simple_symplectic_system or __implicit_system. +Note that all error steppers are also basic steppers. + +[heading Refinement of] + +* DefaultConstructable +* CopyConstructable + + +[heading Associated types] + +* ''''''[*state_type]'''''' +''''''`Stepper::state_type`'''''' +''''''The type characterizing the state of the ODE, hence ['x].'''''' + +* ''''''[*deriv_type]'''''' +''''''`Stepper::deriv_type`'''''' +''''''The type characterizing the derivative of the ODE, hence ['d x/dt].'''''' + +* ''''''[*time_type]'''''' +''''''`Stepper::time_type`'''''' +''''''The type characterizing the dependent variable of the ODE, hence the time ['t].'''''' + +* ''''''[*value_type]'''''' +''''''`Stepper::value_type`'''''' +''''''The numerical data type which is used within the stepper, something like `float`, `double`, `complex< double >`.'''''' + +* ''''''[*order_type]'''''' +''''''`Stepper::order_type`'''''' +''''''The type characterizing the order of the ODE, typically `unsigned short`.'''''' + +* ''''''[*stepper_category]'''''' +''''''`Stepper::stepper_category`'''''' +''''''A tag type characterizing the category of the stepper. This type must be convertible to `stepper_tag`.'''''' + + +[heading Notation] + +[variablelist + [[`Stepper`] [A type that is a model of Stepper]] + [[`State`] [A type representing the state /x/ of the ODE]] + [[`Time`] [A type representing the time /t/ of the ODE]] + [[`stepper`] [An object of type `Stepper`]] + [[`x`] [Object of type `State`]] + [[`t`, `dt`] [Objects of type `Time`]] + [[`sys`] [An object defining the ODE. Depending on the Stepper this might be a model of __system, __symplectic_system, __simple_symplectic_system or __implicit_system ]] +] + +[heading Valid Expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Get the order] [`stepper.order()`] [`order_type`] [Returns the order of the stepper.]] + [[Do step] [`stepper.do_step( sys , x , t , dt )`] [`void`] [Performs one step of step size `dt`. The newly obtained state is written in place in `x`.] ] + + [/ [Do step with reference] [`stepper.do_step( boost::ref(sys) , x , t , dt )`] [`void`] [Performs one step of step size `dt`. The newly obtained state is written in place in `x`.] ] + + [/ [Do step out-of-place] [`stepper.do_step( sys , in , t , out , dt )`] [`void`] [Performs one step. The newly obtained state is written to `out`] ] +] + +[heading Models] + +* `runge_kutta4` +* `euler` +* `runge_kutta_cash_karp54` +* `runge_kutta_dopri5` +* `runge_kutta_fehlberg78` +* `modified_midpoint` +* `rosenbrock4` + +[endsect] diff --git a/doc/concepts/symplectic_system.qbk b/doc/concepts/symplectic_system.qbk new file mode 100644 index 00000000..0caaa31c --- /dev/null +++ b/doc/concepts/symplectic_system.qbk @@ -0,0 +1,99 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section Symplectic System] + +[heading Description] + +This concept describes how to define a symplectic system written with generalized coordinate `q` and generalized momentum `p`: + +[' q'(t) = f(p) ] + +[' p'(t) = g(q) ] + +Such a situation is typically found for Hamiltonian systems with a separable Hamiltonian: + +[' H(p,q) = H[sub kin](p) + V(q) ] + +which gives the equations of motion: + +[' q'(t) = dH[sub kin] / dp = f(p) ] + +[' p'(t) = dV / dq = g(q) ] + + +The algorithmic implementation of this situation is described by a pair of callable objects for /f/ and /g/ with a specific parameter signature. +Such a system should be implemented as a std::pair of functions or a functors. +Symplectic systems are used in symplectic steppers like `symplectic_rkn_sb3a_mclachlan`. + +[heading Notation] + +[variablelist + [[`System`] [A type that is a model of SymplecticSystem]] + [[`Coor`] [The type of the coordinate ['q]]] + [[`Momentum`] [The type of the momentum ['p]]] + [[`CoorDeriv`] [The type of the derivative of coordinate ['q']]] + [[`MomentumDeriv`] [The type of the derivative of momentum ['p']]] + [[`sys`] [An object of the type `System`]] + [[`q`] [Object of type Coor]] + [[`p`] [Object of type Momentum]] + [[`dqdt`] [Object of type CoorDeriv]] + [[`dpdt`] [Object of type MomentumDeriv]] +] + +[heading Valid expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Check for pair] [`boost::is_pair< System >::type`] [`boost::mpl::true_`] [Check if System is a pair]] + [[Calculate ['dq/dt = f(p)]] [`sys.first( p , dqdt )`] [`void`] [Calculates ['f(p)], the result is stored into `dqdt`] ] + [[Calculate ['dp/dt = g(q)]] [`sys.second( q , dpdt )`] [`void`] [Calculates ['g(q)], the result is stored into `dpdt`] ] +] + +[endsect] + + +[section Simple Symplectic System] + +[heading Description] + +In most Hamiltonian systems the kinetic term is a quadratic term in the momentum ['H[sub kin] = p^2 / 2m] and in many cases it is possible to rescale coordinates and set /m=1/ which leads to a trivial equation of motion: + +[' q'(t) = f(p) = p. ] + +while for /p'/ we still have the general form + +[' p'(t) = g(q) ] + +As this case is very frequent we introduced a concept where only the nontrivial equation for /p'/ has to be provided to the symplectic stepper. +We call this concept ['SimpleSymplecticSystem] + +[heading Notation] + +[variablelist + [[System] [A type that is a model of SimpleSymplecticSystem]] + [[Coor] [The type of the coordinate ['q]]] + [[MomentumDeriv] [The type of the derivative of momentum ['p']]] + [[sys] [An object that models System]] + [[q] [Object of type Coor]] + [[dpdt] [Object of type MomentumDeriv]] +] + +[heading Valid Expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Check for pair] [`boost::is_pair< System >::type`] [`boost::mpl::false_`] [Check if System is a pair, should be evaluated to false in this case.]] + [[Calculate ['dp/dt = g(q)]] [`sys( q , dpdt )`] [`void`] [Calculates ['g(q)], the result is stored into `dpdt`] ] +] + +[endsect] \ No newline at end of file diff --git a/doc/concepts/system.qbk b/doc/concepts/system.qbk new file mode 100644 index 00000000..09763c0e --- /dev/null +++ b/doc/concepts/system.qbk @@ -0,0 +1,43 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section System] + +[heading Description] + +The System concept models the algorithmic implementation of the rhs. of the ODE ['x' = f(x,t)]. +The only requirement for this concept is that it should be callable with a specific parameter syntax (see below). +A System is typically implemented as a function or a functor. +Systems fulfilling this concept are required by all Runge-Kutta steppers as well as the Bulirsch-Stoer steppers. +However, symplectic and implicit steppers work with other system concepts, see __symplectic_system and __implicit_system. + +[heading Notation] + +[variablelist + [[`System`] [A type that is a model of System]] + [[`State`] [A type representing the state /x/ of the ODE]] + [[`Deriv`] [A type representing the derivative /x'/ of the ODE]] + [[`Time`] [A type representing the time]] + [[`sys`] [An object of type `System`]] + [[`x`] [Object of type `State`]] + [[`dxdt`] [Object of type `Deriv`]] + [[`t`] [Object of type `Time`]] +] + +[heading Valid expressions] + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Calculate ['dx/dt := f(x,t)]] [`sys( x , dxdt , t )`] [`void`] [Calculates f(x,t), the result is stored into dxdt] ] +] + +[endsect] \ No newline at end of file diff --git a/doc/controlled_stepper_table.qbk b/doc/controlled_stepper_table.qbk new file mode 100644 index 00000000..77d94766 --- /dev/null +++ b/doc/controlled_stepper_table.qbk @@ -0,0 +1,55 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + +[table Adaptive step size algorithms + [ [Stepper] [Tolerance formula] [Norm] [Step size adaption] ] + [ [`controlled_runge_kutta`] + [ + ['val = || | err[subl i] | / ( __epsilon[subl abs] + __epsilon[subl rel] * ( a[subl x] | x[subl i] | + a[subl dxdt] | | dxdt[subl i] | )|| ] + ] + [['||x|| = max( x[subl i] )]] + [ + ['val > 1 : dt[subl new] = dt[subl current] max( 0.9 pow( val , -1 / ( O[subl E] - 1 ) ) , 0.2 )] + + ['val < 0.5 : dt[subl new] = dt[subl current] min( 0.9 pow( val , -1 / O[subl S] ) , 5 )] + + ['else : dt[subl new] = dt[subl current]] + ] ] + [ [`rosenbrock4_controller`] + [ + ['val = || err[subl i] / ( __epsilon[subl abs] + __epsilon[subl rel] max( | x[subl i] | , | xold[subl i] | ) ) || ] + ] + [['||x||=(__Sigma[subl i] x[subl i][super 2])[super 1/2]]] + [ + ['fac = max( 1 / 6 , min( 5 , pow( val , 1 / 4 ) / 0.9 ) ] + + ['fac2 = max( 1 / 6 , min( 5 , dt[subl old] / dt[subl current] pow( val[super 2] / val[subl old] , 1 / 4 ) / 0.9 ) ] + + ['val > 1 : dt[subl new] = dt[subl current] / fac ] + + ['val < 1 : dt[subl new] = dt[subl current] / max( fac , fac2 ) ] + ] + ] + [ [bulirsch_stoer] [['tol=1/2]] [-] [['dt[subl new] = dt[subl old][super 1/a]]] ] +] + +[/ + +safe = 0.9 , fac1 = 5.0 , fac2 = 1.0 / 6.0 + +value_type fac_pred = ( m_dt_old / dt ) * pow( err * err / m_err_old , 0.25 ) / safe; + fac_pred = std::max( fac2 , std::min( fac1 , fac_pred ) ); + fac = std::max( fac , fac_pred ); + dt_new = dt / fac; + + +fac = max( fac2 , min( fac1 , pow( err , 0.25 ) / safe ) ) +] \ No newline at end of file diff --git a/doc/details.qbk b/doc/details.qbk new file mode 100644 index 00000000..cb5cfc82 --- /dev/null +++ b/doc/details.qbk @@ -0,0 +1,30 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + +[section odeint in detail] + +[include details_steppers.qbk] + +[include details_generation_functions.qbk] + +[include details_integrate_functions.qbk] + +[include details_iterators.qbk] + +[include details_state_types_algebras_operations.qbk] + +[include details_boost_ref.qbk] + +[include details_boost_range.qbk] + +[include details_bind_member_functions.qbk] + +[endsect] diff --git a/doc/details_bind_member_functions.qbk b/doc/details_bind_member_functions.qbk new file mode 100644 index 00000000..8d817a46 --- /dev/null +++ b/doc/details_bind_member_functions.qbk @@ -0,0 +1,36 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section Binding member functions] + +[import ../examples/bind_member_functions.cpp] + +Binding member functions to a function objects suitable for odeint system function is not easy, at least in C++03. The usual way of using __boost_bind does not work because of the forwarding problem. odeint provides two `do_step` method which only differ in the const specifiers of the arguments and __boost_bind binders only provide the specializations up to two argument which is not enough for odeint. + +But one can easily implement the according binders themself: + +[ode_wrapper] + +One can use this binder as follows + +[bind_member_function] + +[section Binding member functions in C++11] + +[import ../examples/bind_member_functions_cpp11.cpp] +In C++11 one can use `std::bind` and one does not need to implement the bind themself: + +[bind_member_function_cpp11] + +[endsect] + +[endsect] diff --git a/doc/details_boost_range.qbk b/doc/details_boost_range.qbk new file mode 100644 index 00000000..bf81686e --- /dev/null +++ b/doc/details_boost_range.qbk @@ -0,0 +1,60 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + +[section Using boost::range] + +Most steppers in odeint also accept the state give as a range. A range is +sequence of values modeled by a range concept. See __boost_range for an +overview over existing concepts and examples of ranges. This means that the +`state_type` of the stepper need not necessarily be used to call the `do_step` method. + +One use-case for __boost_range in odeint has been shown in __tut_chaotic_system where the state consists of two parts: one for the original system and one for the perturbations. The ranges are used to initialize (solve) only the system part where the perturbation part is not touched, that is a range consisting only of the system part is used. After that the complete state including the perturbations is solved. + +Another use case is a system consisting of coupled units where you want to initialize each unit separately with the ODE of the uncoupled unit. An example is a chain of coupled van-der-Pol-oscillators which are initialized uniformly from the uncoupled van-der-Pol-oscillator. Then you can use __boost_range to solve only one individual oscillator in the chain. + +In short, you can __boost_range to use one state within two system functions which expect states with different sizes. + +An example was given in the __tut_chaotic_system tutorial. Using Boost.Range usually means that your system function needs to adapt to the iterators of Boost.Range. That is, your function is called with a range and you need to get the iterators from that range. This can easily be done. You have to implement your system as a class or a struct and you have to templatize the `operator()`. Then you can use the `range_iterator`-meta function and `boost::begin` and `boost::end` to obtain the iterators of your range: + +`` +class sys +{ + template< class State , class Deriv > + void operator()( const State &x_ , Deriv &dxdt_ , double t ) const + { + typename boost::range_iterator< const State >::type x = boost::begin( x_ ); + typename boost::range_iterator< Deriv >::type dxdt = boost::begin( dxdt_ ); + + // fill dxdt + } +}; +`` + +If your range is a random access-range you can also apply the bracket operator to the iterator to access the elements in the range: +`` +class sys +{ + template< class State , class Deriv > + void operator()( const State &x_ , Deriv &dxdt_ , double t ) const + { + typename boost::range_iterator< const State >::type x = boost::begin( x_ ); + typename boost::range_iterator< Deriv >::type dxdt = boost::begin( dxdt_ ); + + dxdt[0] = f1( x[0] , x[1] ); + dxdt[1] = f2( x[0] , x[1] ); + } +}; +`` + +The following two tables show which steppers and which algebras are compatible with __boost_range. +[include range_table.qbk] + +[endsect] diff --git a/doc/details_boost_ref.qbk b/doc/details_boost_ref.qbk new file mode 100644 index 00000000..5ba41e26 --- /dev/null +++ b/doc/details_boost_ref.qbk @@ -0,0 +1,35 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + +[section Using boost::ref] + +In odeint all system functions and observers are passed by value. For example, if you call a `do_step` method of a particular stepper or the integration functions, your system and your stepper will be passed by value: + +[c++] +`` +rk4.do_step( sys , x , t , dt ); // pass sys by value +`` + +This behavior is suitable for most systems, especially if your system does not contain any data or only a few parameters. However, in some cases you might contain some large amount of data with you system function and passing them by value is not desired since the data would be copied. + +In such cases you can easily use `boost::ref` (and its relative `boost::cref`) +which passes its argument by reference (or constant reference). odeint will +unpack the arguments and no copying at all of your system object will take place: + +`` +rk4.do_step( boost::ref( sys ) , x , t , dt ); // pass sys as references +`` + +The same mechanism can be used for the observers in the integrate functions. + +[tip If you are using C++11 you can also use `std::ref` and `std::cref`] + +[endsect] diff --git a/doc/details_generation_functions.qbk b/doc/details_generation_functions.qbk new file mode 100644 index 00000000..50f4cf62 --- /dev/null +++ b/doc/details_generation_functions.qbk @@ -0,0 +1,43 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + +[section Generation functions] + +[import ../examples/generation_functions.cpp] + +In the __tutorial we have learned how we can use the generation functions `make_controlled` and `make_dense_output` to create controlled and dense output stepper from a simple stepper or an error stepper. The syntax of these two functions is very simple: + +[generation_functions_syntax_auto] + +The first two parameters are the absolute and the relative error tolerances and the third parameter is the stepper. In C++03 you can infer the type from the `result_of` mechanism: + +[generation_functions_syntax_result_of] + +To use your own steppers with the `make_controlled` or `make_dense_output` you need to specialize two class templates. Suppose your steppers are called `custom_stepper`, `custom_controller` and `custom_dense_output`. Then, the first class you need to specialize is `boost::numeric::get_controller`, a meta function returning the type of the controller: + +[generation_functions_get_controller] + +The second one is a factory class `boost::numeric::odeint::controller_factory` which constructs the controller from the tolerances and the stepper. In our dummy implementation this class is + +[generation_functions_controller_factory] + +This is all to use the `make_controlled` mechanism. Now you can use your controller via + +[generation_functions_example_custom_controller] + +For the dense_output_stepper everything works similar. Here you have to specialize `boost::numeric::odeint::get_dense_output` and `boost::numeric::odeint::dense_output_factory`. These two classes have the same syntax as their relatives `get_controller` and `controller_factory`. + +All controllers and dense-output steppers in odeint can be used with these mechanisms. In the table below you will find, which steppers is constructed from `make_controlled` or `make_dense_output` if applied on a stepper from odeint: + +[include make_controlled_table.qbk] +[include make_dense_output_table.qbk] + +[endsect] diff --git a/doc/details_integrate_functions.qbk b/doc/details_integrate_functions.qbk new file mode 100644 index 00000000..da810e44 --- /dev/null +++ b/doc/details_integrate_functions.qbk @@ -0,0 +1,124 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + +[section Integrate functions] + +Integrate functions perform the time evolution of a given ODE from some +starting time ['t[sub 0]] to a given end time ['t[sub 1]] and starting at state ['x[sub 0]] by subsequent calls of a given stepper's `do_step` function. +Additionally, the user can provide an __observer to analyze the state during time evolution. +There are five different integrate functions which have different strategies on when to call the observer function during integration. +All of the integrate functions except `integrate_n_steps` can be called with any stepper following one of the stepper concepts: __stepper , __error_stepper , __controlled_stepper , __dense_output_stepper. +Depending on the abilities of the stepper, the integrate functions make use of step-size control or dense output. + +[heading Equidistant observer calls] + +If observer calls at equidistant time intervals /dt/ are needed, the +`integrate_const` or `integrate_n_steps` function should be used. +We start with explaining `integrate_const`: + +`integrate_const( stepper , system , x0 , t0 , t1 , dt )` + +`integrate_const( stepper , system , x0 , t0 , t1 , dt , observer )` + +These integrate the ODE given by `system` with subsequent steps from `stepper`. +Integration start at `t0` and `x0` and ends at some ['t' = t[sub 0] + n dt] with /n/ such that ['t[sub 1] - dt < t' <= t[sub 1]]. +`x0` is changed to the approximative solution ['x(t')] at the end of integration. +If provided, the `observer` is invoked at times ['t[sub 0]], ['t[sub 0] + dt], ['t[sub 0] + 2dt], ... ,['t']. +`integrate_const` returns the number of steps performed during the integration. +Note that if you are using a simple __stepper or __error_stepper and want to make exactly `n` steps you should prefer the `integrate_n_steps` function below. + +* If `stepper` is a __stepper or __error_stepper then `dt` is also the step size used for integration and the observer is called just after every step. +* If `stepper` is a __controlled_stepper then `dt` is the initial step size. +The actual step size will change due to error control during time evolution. +However, if an observer is provided the step size will be adjusted such that the algorithm always calculates /x(t)/ at ['t = t[sub 0] + n dt] and calls the observer at that point. +Note that the use of __controlled_stepper is reasonable here only if `dt` is considerably larger than typical step sizes used by the stepper. +* If `stepper` is a __dense_output_stepper then `dt` is the initial step size. +The actual step size will be adjusted during integration due to error control. +If an observer is provided dense output is used to calculate /x(t)/ at ['t = t[sub 0] + n dt]. + +[heading Integrate a given number of steps] + +This function is very similar to `integrate_const` above. The only difference +is that it does not take the end time as parameter, but rather the number of +steps. The integration is then performed until the time `t0+n*dt`. + +`integrate_n_steps( stepper , system , x0 , t0 , dt , n )` + +`integrate_n_steps( stepper , system , x0 , t0 , dt , n , observer )` + +Integrates the ODE given by `system` with subsequent steps from `stepper` starting at ['x[sub 0]] and ['t[sub 0]]. +If provided, `observer` is called after every step and at the beginning with +`t0`, similar as above. +The approximate result for ['x( t[sub 0] + n dt )] is stored in `x0`. +This function returns the end time `t0 + n*dt`. + + +[heading Observer calls at each step] + +If the observer should be called at each time step then the `integrate_adaptive` function should be used. +Note that in the case of __controlled_stepper or __dense_output_stepper this leads to non-equidistant observer calls as the step size changes. + +`integrate_adaptive( stepper , system , x0 , t0 , t1 , dt )` + +`integrate_adaptive( stepper , system , x0 , t0 , t1 , dt , observer )` + +Integrates the ODE given by `system` with subsequent steps from `stepper`. +Integration start at `t0` and `x0` and ends at ['t[sub 1]]. +`x0` is changed to the approximative solution ['x(t[sub 1])] at the end of integration. +If provided, the `observer` is called after each step (and before the first step at `t0`). +`integrate_adaptive` returns the number of steps performed during the integration. + +* If `stepper` is a __stepper or __error_stepper then `dt` is the step size used for integration and `integrate_adaptive` behaves like `integrate_const` except that for the last step the step size is reduced to ensure we end exactly at `t1`. +If provided, the observer is called at each step. +* If `stepper` is a __controlled_stepper then `dt` is the initial step size. +The actual step size is changed according to error control of the stepper. +For the last step, the step size will be reduced to ensure we end exactly at `t1`. +If provided, the observer is called after each time step (and before the first step at `t0`). +* If stepper is a __dense_output_stepper then `dt` is the initial step size and `integrate_adaptive` behaves just like for __controlled_stepper above. No dense output is used. + +[heading Observer calls at given time points] + +If the observer should be called at some user given time points the `integrate_times` function should be used. +The times for observer calls are provided as a sequence of time values. +The sequence is either defined via two iterators pointing to begin and end of the sequence or in terms of a __boost_range object. + +`integrate_times( stepper , system , x0 , times_start , times_end , dt , observer )` + +`integrate_times( stepper , system , x0 , time_range , dt , observer )` + +Integrates the ODE given by `system` with subsequent steps from `stepper`. +Integration starts at `*times_start` and ends exactly at `*(times_end-1)`. +`x0` contains the approximate solution at the end point of integration. +This function requires an observer which is invoked at the subsequent times `*times_start++` until `times_start == times_end`. +If called with a __boost_range `time_range` the function behaves the same with `times_start = boost::begin( time_range )` and `times_end = boost::end( time_range )`. +`integrate_times` returns the number of steps performed during the integration. + +* If `stepper` is a __stepper or __error_stepper `dt` is the step size used for integration. +However, whenever a time point from the sequence is approached the step size `dt` will be reduced to obtain the state /x(t)/ exactly at the time point. +* If `stepper` is a __controlled_stepper then `dt` is the initial step size. +The actual step size is adjusted during integration according to error control. +However, if a time point from the sequence is approached the step size is reduced to obtain the state /x(t)/ exactly at the time point. +* If `stepper` is a __dense_output_stepper then `dt` is the initial step size. +The actual step size is adjusted during integration according to error control. +Dense output is used to obtain the states /x(t)/ at the time points from the sequence. + +[heading Convenience integrate function] + +Additionally to the sophisticated integrate function above odeint also provides a simple `integrate` routine which uses a dense output stepper based on `runge_kutta_dopri5` with standard error bounds ['10[super -6]] for the steps. + +`integrate( system , x0 , t0 , t1 , dt )` + +`integrate( system , x0 , t0 , t1 , dt , observer )` + +This function behaves exactly like `integrate_adaptive` above but no stepper has to be provided. +It also returns the number of steps performed during the integration. + +[endsect] diff --git a/doc/details_iterators.qbk b/doc/details_iterators.qbk new file mode 100644 index 00000000..212c2cb4 --- /dev/null +++ b/doc/details_iterators.qbk @@ -0,0 +1,106 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section Iterators and Ranges] + + + +odeint supports iterators for iterating through an ordinary differential equation. They offer you an alternative to the integrate functions. Furthermore, many of the standard algorithms in the C++ standard library and Boost.Range can be used with the odeint's iterators. + +[import ../examples/const_step_iterator.cpp] + +Four iterators are provided. They are all single pass iterators. The first one is a iterator which solves the odeint with constant step size. An example is + +[const_step_iterator_accumulate] + +In this example all x-values of the solution are accumulated. The iterator itself does not occur directly in this example but it is generated by the factory functions `make_const_step_iterator_begin` and `make_const_step_iterator_end`. odeint also supports Boost.Range, that is you write the above example in a more succinct form with the factory function `make_const_step_range` + +[const_step_iterator_accumulate_range] + +The second iterator type is also a iterator with const step size. But the value type of this iterator consists here of a pair of the time and the state of the solution of the ODE. An example is + +[const_step_time_iterator_accumulate_range] + +The factory functions are now `make_const_step_time_iterator_begin`, `make_const_step_time_iterator_end` and `make_const_step_time_range`. + + +[import ../examples/adaptive_iterator.cpp] + +The other two iterator types adaptive iterators which are completely analogous to the const step iterators. Examples are + +[adaptive_iterator_accumulate_range] + +[adaptive_time_iterator_accumulate_range] + + +[section const_step_iterator] + +* Definition: `const_step_iterator< Stepper , System >` +* `value_type` is `Stepper::state_type` +* Factory functions + * `make_const_step_iterator_begin( stepper , system , state , t_start , t_end , dt )` + * `make_const_step_iterator_end( stepper , system , state )` + * `make_const_step_range( stepper , system , state , t_start , t_end , dt )` +* This stepper works with all steppers fulfilling the Stepper concept or the DenseOutputStepper concept. +* This stepper updates the value of `state`. The value of `state` is the current state of the ODE during the iteration. + +[endsect] + +[section const_step_time_iterator] + +* Definition: `const_step_iterator< Stepper , System >` +* `value_type` is `std::pair< Stepper::state_type& , Stepper::time_type >` +* Factory functions + * `make_const_step_time_iterator_begin( stepper , system , state , t_start , t_end , dt )` + * `make_const_step_time_iterator_end( stepper , system , state )` + * `make_const_step_time_range( stepper , system , state , t_start , t_end , dt )` +* This stepper works with all steppers fulfilling the Stepper concept or the DenseOutputStepper concept. +* This stepper updates the value of `state`. The value of `state` is the current state of the ODE during the iteration. + + +[endsect] + + +[section adaptive_step_iterator] + +* Definition: `adaptive_iterator< Stepper , System >` +* `value_type` is `Stepper::state_type` +* Factory functions + * `make_adaptive_iterator_begin( stepper , system , state , t_start , t_end , dt )` + * `make_adaptive_iterator_end( stepper , system , state )` + * `make_adaptive_range( stepper , system , state , t_start , t_end , dt )` +* This stepper works with all steppers fulfilling the ControlledStepper concept or the DenseOutputStepper concept. +* For steppers fulfilling the ControlledStepper concept `state` is modified according to the current state of the ODE. For DenseOutputStepper the state is not modified due to performance optimizations. + + +[endsect] + +[section adaptive_step_time_iterator] + +* Definition: `adaptive_iterator< Stepper , System >` +* `value_type` is `std::pair< Stepper::state_type& , Stepper::time_type >` +* Factory functions + * `make_adaptive_time_iterator_begin( stepper , system , state , t_start , t_end , dt )` + * `make_adaptive_time_iterator_end( stepper , system , state )` + * `make_adaptive_time_range( stepper , system , state , t_start , t_end , dt )` +* This stepper works with all steppers fulfilling the ControlledStepper concept or the DenseOutputStepper concept. +* This stepper updates the value of `state`. The value of `state` is the current state of the ODE during the iteration. + + +[endsect] + + + + + + +[endsect] diff --git a/doc/details_state_types_algebras_operations.qbk b/doc/details_state_types_algebras_operations.qbk new file mode 100644 index 00000000..a327ebdb --- /dev/null +++ b/doc/details_state_types_algebras_operations.qbk @@ -0,0 +1,473 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + +[section State types, algebras and operations] + +In odeint the stepper algorithms are implemented independently of the +underlying fundamental mathematical operations. +This is realized by giving the user full control over the state type and the +mathematical operations for this state type. +Technically, this is done by introducing three concepts: StateType, Algebra, +Operations. +Most of the steppers in odeint expect three class types fulfilling these +concepts as template parameters. +Note that these concepts are not fully independent of each other but rather a +valid combination must be provided in order to make the steppers work. +In the following we will give some examples on reasonable +state_type-algebra-operations combinations. +For the most common state types, like `vector` or `array` +the default values range_algebra and default_operations are perfectly fine and +odeint can be used as is without worrying about algebra/operations at all. + +[important state_type, algebra and operations are not independent, a valid +combination must be provided to make odeint work properly] + +Moreover, as odeint handles the memory required for intermediate temporary +objects itself, it also needs knowledge about how to create state_type objects +and maybe how to allocate memory (resizing). +All in all, the following things have to be taken care of when odeint is used +with non-standard state types: + +* construction/destruction +* resizing (if possible/required) +* algebraic operations + +Again, odeint already provides basic interfaces for most of the usual state +types. +So if you use a `std::vector`, or a `boost::array` as state type no additional +work is required, they just work out of the box. + +[section Construction/Resizing] + +We distinguish between two basic state types: fixed sized and dynamically +sized. +For fixed size state types the default constructor `state_type()` already +allocates the required memory, prominent example is `boost::array`. +Dynamically sized types have to be resized to make sure enough memory is +allocated, the standard constructor does not take care of the resizing. +Examples for this are the STL containers like `vector`. + +The most easy way of getting your own state type to work with odeint is to use +a fixed size state, base calculations on the range_algebra and provide the +following functionality: +[table + [[Name] [Expression] [Type] [Semantics]] + [[Construct State] [`State x()`] [`void`] [Creates an instance of `State` + and allocates memory.] ] + [[Begin of the sequence] [boost::begin(x)] [Iterator] [Returns an iterator + pointing to the begin of the sequence]] + [[End of the sequence] [boost::end(x)] [Iterator] [Returns an iterator + pointing to the end of the sequence]] +] + +[warning If your state type does not allocate memory by default construction, +you [*must define it as resizeable] and provide resize functionality (see +below). Otherwise segmentation faults will occur.] + +So fixed sized arrays supported by __boost_range immediately work with odeint. +For dynamically sized arrays one has to additionally supply the resize +functionality. +First, the state has to be tagged as resizeable by specializing the struct +`is_resizeable` which consists of one typedef and one bool value: +[table + [[Name] [Expression] [Type] [Semantics]] + [[Resizability] [`is_resizeable::type`] + [`boost::true_type` or `boost::false_type`] + [Determines resizeability of the state type, returns `boost::true_type` if + the state is resizeable.]] + [[Resizability] [`is_resizeable::value`] + [`bool`] + [Same as above, but with `bool` value.]] +] + +Defining `type` to be `true_type` and `value` as `true` tells odeint that your +state is resizeable. +By default, odeint now expects the support of `boost::size(x)` and a +`x.resize( boost::size(y) )` member function for resizing: +[table + [[Name] [Expression] [Type] [Semantics]] + [[Get size] [`boost::size( x )`] + [`size_type`] [Returns the current size of x.]] + [[Resize] [`x.resize( boost::size( y ) )`] + [`void`] [Resizes x to have the same size as y.]] +] + +[section Using the container interface] +[import ../examples/my_vector.cpp] + +As a first example we take the most simple case and implement our own vector +`my_vector` which will provide a container interface. +This makes __boost_range working out-of-box. +We add a little functionality to our vector which makes it allocate some +default capacity by construction. +This is helpful when using resizing as then a resize can be assured to not +require a new allocation. + +[my_vector] + + +The only thing that has to be done other than defining is thus declaring +my_vector as resizeable: + +[my_vector_resizeable] + +If we wouldn't specialize the `is_resizeable` template, the code would still +compile but odeint would not adjust the size of temporary internal instances +of my_vector and hence try to fill zero-sized vectors resulting in +segmentation faults! +The full example can be found in [github_link libs/numeric/odeint/examples/my_vector.cpp my_vector.cpp] + +[endsect] + +[section std::list] + +If your state type does work with __boost_range, but handles resizing +differently you are required to specialize two implementations used by odeint +to check a state's size and to resize: +[table + [[Name] [Expression] [Type] [Semantics]] + [[Check size] [`same_size_impl::same_size(x , y)`] + [`bool`] [Returns true if the size of x equals the size of y.]] + [[Resize] [`resize_impl::resize(x , y)`] + [`void`] [Resizes x to have the same size as y.]] +] + +As an example we will use a `std::list` as state type in odeint. +Because `std::list` is not supported by `boost::size` we have to replace the +same_size and resize implementation to get list to work with odeint. +The following code shows the required template specializations: + +[import ../examples/list_lattice.cpp] + +[list_bindings] + +With these definitions odeint knows how to resize `std::list`s and so they can +be used as state types. +A complete example can be found in [github_link libs/numeric/odeint/examples/list_lattice.cpp list_lattice.cpp]. + +[endsect] + +[endsect] + +[section Algebras and Operations] + +To provide maximum flexibility odeint is implemented in a highly modularized +way. This means it is possible to change the underlying mathematical +operations without touching the integration algorithms. +The fundamental mathematical operations are those of a vector space, that is +addition of `state_types` and multiplication of `state_type`s with a scalar +(`time_type`). In odeint this is realized in two concepts: _Algebra_ and +_Operations_. +The standard way how this works is by the range algebra which provides +functions that apply a specific operation to each of the individual elements +of a container based on the __boost_range library. +If your state type is not supported by __boost_range there are several +possibilities to tell odeint how to do algebraic operations: + +* Implement `boost::begin` and `boost::end` for your state type so it works +with __boost_range. +* Implement vector-vector addition operator `+` and scalar-vector +multiplication operator `*` and use the non-standard `vector_space_algebra`. +* Implement your own algebra that implements the required functions. + +[section GSL Vector] + +In the following example we will try to use the `gsl_vector` type from __gsl (GNU +Scientific Library) as state type in odeint. +We will realize this by implementing a wrapper around the gsl_vector that +takes care of construction/destruction. +Also, __boost_range is extended such that it works with `gsl_vector`s as well +which required also the implementation of a new `gsl_iterator`. + +[note odeint already includes all the code presented here, see [github_link +boost/numeric/odeint/external/gsl/gsl_wrapper.hpp gsl_wrapper.hpp], so `gsl_vector`s +can be used straight out-of-box. +The following description is just for educational purpose.] + +The GSL is a C library, so `gsl_vector` has neither constructor, nor +destructor or any `begin` or `end` function, no iterators at all. +So to make it work with odeint plenty of things have to be implemented. +Note that all of the work shown here is already included in odeint, so using +`gsl_vector`s in odeint doesn't require any further adjustments. +We present it here just as an educational example. +We start with defining appropriate constructors and destructors. +This is done by specializing the `state_wrapper` for `gsl_vector`. +State wrappers are used by the steppers internally to create and manage +temporary instances of state types: + +`` +template<> +struct state_wrapper< gsl_vector* > +{ + typedef double value_type; + typedef gsl_vector* state_type; + typedef state_wrapper< gsl_vector* > state_wrapper_type; + + state_type m_v; + + state_wrapper( ) + { + m_v = gsl_vector_alloc( 1 ); + } + + state_wrapper( const state_wrapper_type &x ) + { + resize( m_v , x.m_v ); + gsl_vector_memcpy( m_v , x.m_v ); + } + + + ~state_wrapper() + { + gsl_vector_free( m_v ); + } + +}; +`` + +This `state_wrapper` specialization tells odeint how gsl_vectors are created, +copied and destroyed. +Next we need resizing, this is required because gsl_vectors are dynamically +sized objects: +`` +template<> +struct is_resizeable< gsl_vector* > +{ + typedef boost::true_type type; + const static bool value = type::value; +}; + +template <> +struct same_size_impl< gsl_vector* , gsl_vector* > +{ + static bool same_size( const gsl_vector* x , const gsl_vector* y ) + { + return x->size == y->size; + } +}; + +template <> +struct resize_impl< gsl_vector* , gsl_vector* > +{ + static void resize( gsl_vector* x , const gsl_vector* y ) + { + gsl_vector_free( x ); + x = gsl_vector_alloc( y->size ); + } +}; +`` + +Up to now, we defined creation/destruction and resizing, but gsl_vectors also +don't support iterators, so we first implement a gsl iterator: + +`` +/* + * defines an iterator for gsl_vector + */ +class gsl_vector_iterator + : public boost::iterator_facade< gsl_vector_iterator , double , + boost::random_access_traversal_tag > +{ +public : + + gsl_vector_iterator( void ): m_p(0) , m_stride( 0 ) { } + explicit gsl_vector_iterator( gsl_vector *p ) : m_p( p->data ) , m_stride( p->stride ) { } + friend gsl_vector_iterator end_iterator( gsl_vector * ); + +private : + + friend class boost::iterator_core_access; + friend class const_gsl_vector_iterator; + + void increment( void ) { m_p += m_stride; } + void decrement( void ) { m_p -= m_stride; } + void advance( ptrdiff_t n ) { m_p += n*m_stride; } + bool equal( const gsl_vector_iterator &other ) const { return this->m_p == other.m_p; } + bool equal( const const_gsl_vector_iterator &other ) const; + double& dereference( void ) const { return *m_p; } + + double *m_p; + size_t m_stride; +}; +`` +A similar class exists for the `const` version of the iterator. +Then we have a function returning the end iterator (similarly for `const` again): +`` +gsl_vector_iterator end_iterator( gsl_vector *x ) +{ + gsl_vector_iterator iter( x ); + iter.m_p += iter.m_stride * x->size; + return iter; +} +`` + +Finally, the bindings for __boost_range are added: +`` +// template<> +inline gsl_vector_iterator range_begin( gsl_vector *x ) +{ + return gsl_vector_iterator( x ); +} + +// template<> +inline gsl_vector_iterator range_end( gsl_vector *x ) +{ + return end_iterator( x ); +} +`` +Again with similar definitions for the `const` versions. +This eventually makes odeint work with gsl vectors as state types. +The full code for these bindings is found in [github_link +boost/numeric/odeint/external/gsl/gsl_wrapper.hpp gsl_wrapper.hpp]. +It might look rather complicated but keep in mind that gsl is a pre-compiled C +library. +[endsect] + + +[section Vector Space Algebra] + +As seen above, the standard way of performing algebraic operations on +container-like state types in odeint is to iterate through the elements of the +container and perform the operations element-wise on the underlying value type. +This is realized by means of the `range_algebra` that uses __boost_range for +obtaining iterators of the state types. +However, there are other ways to implement the algebraic operations on +containers, one of which is defining the addition/multiplication operators for +the containers directly and then using the `vector_space_algebra`. +If you use this algebra, the following operators have to be defined for the +state_type: + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Addition] [`x + y`] [`state_type`] [Calculates the vector sum 'x+y'.]] + [[Assign addition] [`x += y`] [`state_type`] [Performs x+y in place.]] + [[Scalar multiplication] [`a * x `] [`state_type`] [Performs multiplication of vector x with scalar a.]] + [[Assign scalar multiplication] [`x *= a`] [`state_type`] [Performs in-place multiplication of vector x with scalar a.]] +] + +Defining these operators makes your state type work with any basic Runge-Kutta +stepper. +However, if you want to use step-size control, some more functionality is +required. +Specifically, operations like +[' max[sub i]( |err[sub i]| / (alpha * |s[sub i]|) )] +have to be performed. +['err] and ['s] are state_types, alpha is a scalar. +As you can see, we need element wise absolute value and division as well as an +reduce operation to get the maximum value. +So for controlled steppers the following things have to be implemented: + +[table + [[Name] [Expression] [Type] [Semantics]] + [[Division] [`x / y`] [`state_type`] [Calculates the element-wise division 'x/y']] + [[Absolute value] [`abs( x )`] [`state_type`] [Element wise absolute value]] + [[Reduce] [`vector_space_reduce_impl< state_type >::reduce( state , operation , init )`] [`value_type`] + [Performs the `operation` for subsequently each element of `state` and returns the aggregate value. + E.g. + +`init = operator( init , state[0] );` + +`init = operator( init , state[1] )` + +`...` + ]] +] + +[endsect] + +[section Boost.Ublas] +As an example for the employment of the `vector_space_algebra` we will adopt +`ublas::vector` from __ublas to work as a state type in odeint. +This is particularly easy because `ublas::vector` supports vector-vector +addition and scalar-vector multiplication described above as well as `boost::size`. +It also has a resize member function so all that has to be done in this case +is to declare resizability: + +[import ../examples/ublas/lorenz_ublas.cpp] + +[ublas_resizeable] + +Now ublas::vector can be used as state type for simple Runge-Kutta steppers +in odeint by specifying the `vector_space_algebra` as algebra in the template +parameter list of the stepper. +The following code shows the corresponding definitions: + +[ublas_main] + +Note again, that we haven't supported the requirements for controlled steppers, +but only for simple Runge-Kutta methods. +You can find the full example in [github_link +libs/numeric/odeint/examples/ublas/lorenz_ublas.cpp lorenz_ublas.cpp]. + +[endsect] + +[section Point type] + +[import ../examples/lorenz_point.cpp] + +Here we show how to implement the required operators on a state type. +As example we define a new class `point3D` representing a three-dimensional +vector with components x,y,z and define addition and scalar multiplication +operators for it. +We use __boost_operators to reduce the amount of code to be written. +The class for the point type looks as follows: + +[point3D] + +By deriving from __boost_operators classes we don't have to define outer class +operators like `operator+( point3D , point3D )` because that is taken care of +by the operators library. +Note that for simple Runge-Kutta schemes (like `runge_kutta4`) only the `+` +and `*` operators are required. +If, however, a controlled stepper is used one also needs to specify the +division operator `/` because calculation of the error term involves an +element wise division of the state types. +Additionally, controlled steppers require an `abs` function calculating the +element-wise absolute value for the state type: + +[point3D_abs_div] + +Finally, we have to add a specialization for `reduce` implementing a reduction +over the state type: + +[point3D_reduce] + +Again, note that the two last steps were only required if you want to use +controlled steppers. +For simple steppers definition of the simple `+=` and `*=` operators are +sufficient. +Having defined such a point type, we can easily perform the integration on a Lorenz +system by using the `vector_space_algebra` again: + +[point3D_main] + +The whole example can be found in [github_link +libs/numeric/odeint/examples/lorenz_point.cpp lorenz_point.cpp] + +[endsect] + +[endsect] + +gsl_vector, gsl_matrix, ublas::matrix, blitz::matrix, thrust + +[section Adapt your own operations] + +to be continued + +*thrust +*gsl_complex +*min, max, pow + +[endsect] + + + +[endsect] diff --git a/doc/details_steppers.qbk b/doc/details_steppers.qbk new file mode 100644 index 00000000..79e9d1a8 --- /dev/null +++ b/doc/details_steppers.qbk @@ -0,0 +1,420 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + +[section Steppers] + +[import ../examples/stepper_details.cpp] + +Solving ordinary differential equation numerically is usually done iteratively, that is a given state of an ordinary differential equation is iterated forward ['x(t) -> x(t+dt) -> x(t+2dt)]. The steppers in odeint perform one single step. The most general stepper type is described by the __stepper concept. The stepper concepts of odeint are described in detail in section __concepts, here we briefly present the mathematical and numerical details of the steppers. The __stepper has two versions of the `do_step` method, one with an in-place transform of the current state and one with an out-of-place transform: + +`do_step( sys , inout , t , dt )` + +`do_step( sys , in , t , out , dt )` + +The first parameter is always the system function - a function describing the +ODE. In the first version the second parameter is the step which is here +updated in-place and the third and the fourth parameters are the time and step +size (the time step). After a call to `do_step` the state `inout` is updated +and now represents an approximate solution of the ODE at time ['t+dt]. In the +second version the second argument is the state of the ODE at time ['t], the +third argument is t, the fourth argument is the approximate solution at time +['t+dt] which is filled by `do_step` and the fifth argument is the time step. +Note that these functions do not change the time `t`. + +[* System functions] + +Up to now, we have nothing said about the system function. This function +depends on the stepper. For the explicit Runge-Kutta steppers this function +can be a simple callable object hence a simple (global) C-function or a +functor. The parameter syntax is `sys( x , dxdt , t )` and it is assumed that +it calculates ['dx/dt = f(x,t)]. +The function structure in most cases looks like: + +[system_function_structure] + +Other types of system functions might represent Hamiltonian systems or systems which also compute the Jacobian needed in implicit steppers. For information which stepper uses which system function see the stepper table below. It might be possible that odeint will introduce new system types in near future. Since the system function is strongly related to the stepper type, such an introduction of a new stepper might result in a new type of system function. + +[section Explicit steppers] + +A first specialization are the explicit steppers. Explicit means that the new +state of the ode can be computed explicitly from the current state without +solving implicit equations. Such steppers have in common that they evaluate the system at time ['t] such that the result of ['f(x,t)] can be passed to the stepper. In odeint, the explicit stepper have two additional methods + +`do_step( sys , inout , dxdtin , t , dt )` + +`do_step( sys , in , dxdtin , t , out , dt )` + +Here, the additional parameter is the value of the function ['f] at state ['x] and time ['t]. An example is the Runge-Kutta stepper of fourth order: + +[explicit_stepper_detail_example] + +In fact, you do not need to call these two methods. You can always use the +simpler `do_step( sys , inout , t , dt )`, but sometimes the derivative of the +state is needed externally to do some external computations or to perform some statistical analysis. + +A special class of the explicit steppers are the FSAL (first-same-as-last) +steppers, where the last evaluation of the system function is also the first +evaluation of the following step. For such steppers the `do_step` method are +slightly different: + +`do_step( sys , inout , dxdtinout , t , dt )` + +`do_step( sys , in , dxdtin , out , dxdtout , t , dt )` + +This method takes the derivative at time `t` and also also stores +the derivative at time ['t+dt]. Calling these functions subsequently iterating +along the solution one saves one function call by passing the result for dxdt +into the next function call. +However, when using FSAL steppers without supplying derivatives: + +`do_step( sys , inout , t , dt )` + +the stepper internally satisfies the FSAL property which means it remembers +the last `dxdt` and uses it for the next step. +An example for a FSAL stepper is the Runge-Kutta-Dopri5 stepper. The FSAL trick is sometimes also referred as the Fehlberg trick. An example how the FSAL steppers can be used is + +[fsal_stepper_detail_example] + +[caution The FSAL-steppers save the derivative at time ['t+dt] internally if +they are called via `do_step( sys , in , out , t , dt )`. The first call of +`do_step` will initialize `dxdt` and for all following calls it is assumed +that the same system and the same state are used. If you use the FSAL stepper +within the integrate functions this is taken care of automatically. See the __using_steppers section for more details or look into the table below to see which stepper have an internal state.] + + +[endsect] + +[section Symplectic solvers] + +As mentioned above symplectic solvers are used for Hamiltonian systems. Symplectic solvers conserve the phase space volume exactly and if the Hamiltonian system is energy conservative they also conserve the energy approximately. A special class of symplectic systems are separable systems which can be written in the form ['dqdt/dt = f1(p)], ['dpdt/dt = f2(q)], where ['(q,p)] are the state of system. The space of ['(q,p)] is sometimes referred as the phase space and ['q] and ['p] are said the be the phase space variables. Symplectic systems in this special form occur widely in nature. For example the complete classical mechanics as written down by Newton, Lagrange and Hamilton can be formulated in this framework. The separability of the system depends on the specific choice of coordinates. + +Symplectic systems can be solved by odeint by means of the symplectic_euler stepper and a symplectic Runge-Kutta-Nystrom method of fourth order. These steppers assume that the system is autonomous, hence the time will not explicitly occur. Further they fulfill in principle the default Stepper concept, but they expect the system to be a pair of callable objects. The first entry of this pair calculates ['f1(p)] while the second calculates ['f2(q)]. The syntax is `sys.first(p,dqdt)` and `sys.second(q,dpdt)`, where the first and second part can be again simple C-functions of functors. An example is the harmonic oscillator: + +[symplectic_stepper_detail_system_function] + +The state of such an ODE consist now also of two parts, the part for q (also called the coordinates) and the part for p (the momenta). The full example for the harmonic oscillator is now: + +[symplectic_stepper_detail_example] + +If you like to represent the system with one class you can easily bind two public method: + +[symplectic_stepper_detail_system_class] + +[symplectic_stepper_detail_system_class_example] + +Many Hamiltonian system can be written as ['dq/dt=p], ['dp/dt=f(q)] which is computationally much easier than the full separable system. Very often, it is also possible to transform the original equations of motion to bring the system in this simplified form. This kind of system can be used in the symplectic solvers, by simply passing ['f(p)] to the `do_step` method, again ['f(p)] will be represented by a simple C-function or a functor. Here, the above example of the harmonic oscillator can be written as + +[simplified_symplectic_stepper_example] + +In this example the function `harm_osc_f1` is exactly the same function as in the above examples. + +Note, that the state of the ODE must not be constructed explicitly via `pair< vector_type , vector_type > x`. One can also use a combination of `make_pair` and `ref`. Furthermore, a convenience version of `do_step` exists which takes q and p without combining them into a pair: + +[symplectic_stepper_detail_ref_usage] + +[endsect] + +[section Implicit solvers] + +[caution This section is not up-to-date.] + +For some kind of systems the stability properties of the classical Runge-Kutta are not sufficient, especially if the system is said to be stiff. A stiff system possesses two or more time scales of very different order. Solvers for stiff systems are usually implicit, meaning that they solve equations like ['x(t+dt) = x(t) + dt * f(x(t+1))]. This particular scheme is the implicit Euler method. Implicit methods usually solve the system of equations by a root finding algorithm like the Newton method and therefore need to know the Jacobian of the system ['J[subl ij] = df[subl i] / dx[subl j]]. + +For implicit solvers the system is again a pair, where the first component computes ['f(x,t)] and the second the Jacobian. The syntax is `sys.first( x , dxdt , t )` and `sys.second( x , J , t )`. For the implicit solver the `state_type` is `ublas::vector` and the Jacobian is represented by `ublas::matrix`. + +[important Implicit solvers only work with ublas::vector as state type. At +the moment, no other state types are supported.] + +[endsect] + +[section Multistep methods] + +Another large class of solvers are multi-step method. They save a small part of the history of the solution and compute the next step with the help of this history. Since multi-step methods know a part of their history they do not need to compute the system function very often, usually it is only computed once. This makes multi-step methods preferable if a call of the system function is expensive. Examples are ODEs defined on networks, where the computation of the interaction is usually where expensive (and might be of order O(N^2)). + +Multi-step methods differ from the normal steppers. They save a part of their history and this part has to be explicitly calculated and initialized. In the following example an Adams-Bashforth-stepper with a history of 5 steps is instantiated and initialized; + +[multistep_detail_example] + +The initialization uses a fourth-order Runge-Kutta stepper and after the call +of `initialize` the state of `inout` has changed to the current state, such +that it can be immediately used by passing it to following calls of `do_step`. You can also use you own steppers to initialize the internal state of the Adams-Bashforth-Stepper: + +[multistep_detail_own_stepper_initialization] + +Many multi-step methods are also explicit steppers, hence the parameter of `do_step` method do not differ from the explicit steppers. + +[caution The multi-step methods have some internal variables which depend on +the explicit solution. Hence after any external changes of your state (e.g. size) or +system the initialize function has to be called again to adjust the internal +state of the stepper. If you use the integrate functions this will +be taken into account. See the __using_steppers section for more details.] + + +[endsect] + +[section Controlled steppers] + +Many of the above introduced steppers possess the possibility to use adaptive step-size control. Adaptive step size integration works in principle as follows: + +# The error of one step is calculated. This is usually done by performing two steps with different orders. The difference between these two steps is then used as a measure for the error. Stepper which can calculate the error are __error_stepper and they form an own class with an separate concept. +# This error is compared against some predefined error tolerances. Are the tolerance violated the step is reject and the step-size is decreases. Otherwise the step is accepted and possibly the step-size is increased. + +The class of controlled steppers has their own concept in odeint - the __controlled_stepper concept. They are usually constructed from the underlying error steppers. An example is the controller for the explicit Runge-Kutta steppers. The Runge-Kutta steppers enter the controller as a template argument. Additionally one can pass the Runge-Kutta stepper to the constructor, but this step is not necessary; the stepper is default-constructed if possible. + +Different step size controlling mechanism exist. They all have in common that +they somehow compare predefined error tolerance against the error and that +they might reject or accept a step. If a step is rejected the step size is +usually decreased and the step is made again with the reduced step size. This +procedure is repeated until the step is accepted. This algorithm is +implemented in the integration functions. + +A classical way to decide whether a step is rejected or accepted is to calculate + +['val = || | err[subl i] | / ( __epsilon[subl abs] + __epsilon[subl rel] * ( a[subl x] | x[subl i] | + a[subl dxdt] | | dxdt[subl i] | )|| ] + +['__epsilon[subl abs]] and ['__epsilon[subl rel]] are the absolute and the relative error tolerances, and ['|| x ||] is a norm, typically ['||x||=(__Sigma[subl i] x[subl i][super 2])[super 1/2]] or the maximum norm. The step is rejected if ['val] is greater then 1, otherwise it is accepted. For details of the used norms and error tolerance see the table below. + +For the `controlled_runge_kutta` stepper the new step size is then calculated via + +['val > 1 : dt[subl new] = dt[subl current] max( 0.9 pow( val , -1 / ( O[subl E] - 1 ) ) , 0.2 )] + +['val < 0.5 : dt[subl new] = dt[subl current] min( 0.9 pow( val , -1 / O[subl S] ) , 5 )] + +['else : dt[subl new] = dt[subl current]] + +Here, ['O[subl S]] and ['O[subl E]] are the order of the stepper and the error stepper. These formulas also contain some safety factors, avoiding that the step size is reduced or increased to much. For details of the implementations of the controlled steppers in odeint see the table below. + +[include controlled_stepper_table.qbk] + +To ease to generation of the controlled stepper, generation functions exist which take the absolute and relative error tolerances and a predefined error stepper and construct from this knowledge an appropriate controlled stepper. The generation functions are explained in detail in __generation_functions. + +[endsect] + +[section Dense output steppers] + +A fourth class of stepper exists which are the so called dense output steppers. Dense-output steppers might take larger steps and interpolate the solution between two consecutive points. This interpolated points have usually the same order as the order of the stepper. Dense-output steppers are often composite stepper which take the underlying method as a template parameter. An example is the `dense_output_runge_kutta` stepper which takes a Runge-Kutta stepper with dense-output facilities as argument. Not all Runge-Kutta steppers provide dense-output calculation; at the moment only the Dormand-Prince 5 stepper provides dense output. An example is + +[dense_output_detail_example] + +Dense output stepper have their own concept. The main difference to usual +steppers is that they manage the state and time internally. If you call +`do_step`, only the ODE is passed as argument. Furthermore `do_step` return +the last time interval: `t` and `t+dt`, hence you can interpolate the solution between these two times points. Another difference is that they must be initialized with `initialize`, otherwise the internal state of the stepper is default constructed which might produce funny errors or bugs. + +The construction of the dense output stepper looks a little bit nasty, since in the case of the `dense_output_runge_kutta` stepper a controlled stepper and an error stepper have to be nested. To simplify the generation of the dense output stepper generation functions exist: + +[dense_output_detail_generation1] + +This statement is also lengthy; it demonstrates how `make_dense_output` can be used with the `result_of` protocol. The parameters to `make_dense_output` are the absolute error tolerance, the relative error tolerance and the stepper. This explicitly assumes that the underlying stepper is a controlled stepper and that this stepper has an absolute and a relative error tolerance. For details about the generation functions see __generation_functions. The generation functions have been designed for easy use with the integrate functions: + +[dense_output_detail_generation2] + +[endsect] + +[section Using steppers] + +This section contains some general information about the usage of the steppers in odeint. + +[* Steppers are copied by value] + +The stepper in odeint are always copied by values. They are copied for the creation of the controlled steppers or the dense output steppers as well as in the integrate functions. + +[* Steppers might have a internal state] + +[caution Some of the features described in this section are not yet implemented] + +Some steppers require to store some information about the state of the ODE between two steps. Examples are the multi-step methods which store a part of the solution during the evolution of the ODE, or the FSAL steppers which store the last derivative at time ['t+dt], to be used in the next step. In both cases the steppers expect that consecutive calls of `do_step` are from the same solution and the same ODE. In this case it is absolutely necessary that you call `do_step` with the same system function and the same state, see also the examples for the FSAL steppers above. + +Stepper with an internal state support two additional methods: `reset` which resets the state and `initialize` which initializes the internal state. The parameters of `initialize` depend on the specific stepper. For example the Adams-Bashforth-Moulton stepper provides two initialize methods: `initialize( system , inout , t , dt )` which initializes the internal states with the help of the Runge-Kutta 4 stepper, and `initialize( stepper , system , inout , t , dt )` which initializes with the help of `stepper`. For the case of the FSAL steppers, `initialize` is `initialize( sys , in , t )` which simply calculates the r.h.s. of the ODE and assigns its value to the internal derivative. + +All these steppers have in common, that they initially fill their internal state by themselves. Hence you are not required to call initialize. See how this works for the Adams-Bashforth-Moulton stepper: in the example we instantiate a fourth order Adams-Bashforth-Moulton stepper, meaning that it will store 4 internal derivatives of the solution at times `(t-dt,t-2*dt,t-3*dt,t-4*dt)`. + +`` +adams_bashforth_moulton< 4 , state_type > stepper; +stepper.do_step( sys , x , t , dt ); // make one step with the classical Runge-Kutta stepper and initialize the first internal state + // the internal array is now [x(t-dt)] + +stepper.do_step( sys , x , t , dt ); // make one step with the classical Runge-Kutta stepper and initialize the second internal state + // the internal state array is now [x(t-dt), x(t-2*dt)] + +stepper.do_step( sys , x , t , dt ); // make one step with the classical Runge-Kutta stepper and initialize the third internal state + // the internal state array is now [x(t-dt), x(t-2*dt), x(t-3*dt)] + +stepper.do_step( sys , x , t , dt ); // make one step with the classical Runge-Kutta stepper and initialize the fourth internal state + // the internal state array is now [x(t-dt), x(t-2*dt), x(t-3*dt), x(t-4*dt)] + +stepper.do_step( sys , x , t , dt ); // make one step with Adam-Bashforth-Moulton, the internal array of states is now rotated +`` + +In the stepper table at the bottom of this page one can see which stepper have an internal state and hence provide the `reset` and `initialize` methods. + + +[* Stepper might be resizable] + +Nearly all steppers in odeint need to store some intermediate results of the +type `state_type` or `deriv_type`. To do so odeint need some memory management +for the internal temporaries. As this memory management is typically related +to adjusting the size of vector-like types, it is called resizing in +odeint. So, most steppers in odeint provide an additional template parameter +which controls the size adjustment of the internal variables - the resizer. In +detail odeint provides three policy classes (resizers) `always_resizer`, +`initially_resizer`, and `never_resizer`. Furthermore, all stepper have a +method `adjust_size` which takes a parameter representing a state type and +which manually adjusts the size of the internal variables matching the size of +the given instance. Before performing the actual resizing odeint always checks +if the sizes of the state and the internal variable differ and only resizes if +they are different. + +[note You only have to worry about memory allocation when using dynamically +sized vector types. If your state type is heap allocated, like `boost::array`, +no memory allocation is required whatsoever.] + +By default the resizing parameter is `initially_resizer`, meaning that the +first call to `do_step` performs the resizing, hence memory allocation. +If you have changed the size of your system and your state you have to +call `adjust_size` by hand in this case. The second resizer is the +`always_resizer` which tries to resize the internal variables at every call of +`do_step`. Typical use cases for this kind of resizer are self expanding +lattices like shown in the tutorial (__resizing_lattice_example) or partial differential equations with an +adaptive grid. Here, no calls of `adjust_size` are required, the steppers manage +everything themselves. The third class of resizer is the `never_resizer` which +means that the internal variables are never adjusted automatically and always +have to be adjusted by hand . + +There is a second mechanism which influences the resizing and which controls if a state type is at least resizeable - a meta-function `is_resizeable`. This meta-function returns a static Boolean value if any type is resizable. For example it will return `true` for `std::vector< T >` but `false` for `boost::array< T >`. By default and for unknown types `is_resizeable` returns `false`, so if you have your own type you need to specialize this meta-function. For more details on the resizing mechanism see the section __adapt_state_types. + + + +[* Which steppers should be used in which situation] + +odeint provides a quite large number of different steppers such that the user is left with the question of which stepper fits his needs. Our personal recommendations are: + +* `runge_kutta_dopri5` is maybe the best default stepper. It has step size control as well as dense-output functionality. Simple create a dense-output stepper by `make_dense_output( 1.0e-6 , 1.0e-5 , runge_kutta_dopri5< state_type >() )`. +* `runge_kutta4` is a good stepper for constant step sizes. It is widely used and very well known. If you need to create artificial time series this stepper should be the first choice. +* 'runge_kutta_fehlberg78' is similar to the 'runge_kutta4' with the advantage that it has higher precision. It can also be used with step size control. +* `adams_bashforth_moulton` is very well suited for ODEs where the r.h.s. is expensive (in terms of computation time). It will calculate the system function only once during each step. + +[endsect] + +[section Stepper overview] + +[include stepper_table.qbk] + +[endsect] + + +[section Custom steppers] + +[import ../examples/stochastic_euler.cpp] + +Finally, one can also write new steppers which are fully compatible with odeint. They only have to fulfill one or several of the stepper __concepts of odeint. + +We will illustrate how to write your own stepper with the example of the stochastic Euler method. This method is suited to solve stochastic differential equations (SDEs). A SDE has the form + +['dx/dt = f(x) + g(x) __xi(t)] + +where ['__xi] is Gaussian white noise with zero mean and a standard deviation ['__sigma(t)]. ['f(x)] is said to be the deterministic part while [' g(x) __xi] is the noisy part. In case ['g(x)] is independent of ['x] the SDE is said to have additive noise. It is not possible to solve SDE with the classical solvers for ODEs since the noisy part of the SDE has to be scaled differently then the deterministic part with respect to the time step. But there exist many solvers for SDEs. A classical and easy method is the stochastic Euler solver. It works by iterating + +['x(t+__Delta t) = x(t) + __Delta t f(x(t)) + __Delta t[super 1/2] g(x) __xi(t)] + +where __xi(t) is an independent normal distributed random variable. + +Now we will implement this method. We will call the stepper +`stochastic_euler`. It models the __stepper concept. For simplicity, we fix +the state type to be an `array< double , N >` The class definition looks like + +[stochastic_euler_class_definition] + +The types are needed in order to fulfill the stepper concept. As internal state and deriv type we use simple arrays in the stochastic Euler, they are needed for the temporaries. The stepper has the order one which is returned from the `order()` function. + +The system functions needs to calculate the deterministic and the stochastic part of our stochastic differential equation. So it might be suitable that the system function is a pair of functions. The first element of the pair computes the deterministic part and the second the stochastic one. Then, the second part also needs to calculate the random numbers in order to simulate the stochastic process. We can now implement the `do_step` method + +[stochastic_euler_do_step] + +This is all. It is quite simple and the stochastic Euler stepper implement here is quite general. Of course it can be enhanced, for example + +* use of operations and algebras as well as the resizing mechanism for maximal flexibility and portability +* use of `boost::ref` for the system functions +* use of `boost::range` for the state type in the `do_step` method +* ... + +Now, lets look how we use the new stepper. A nice example is the Ornstein-Uhlenbeck process. It consists of a simple Brownian motion overlapped with an relaxation process. Its SDE reads + +['dx/dt = - x + __xi] + +where __xi is Gaussian white noise with standard deviation ['__sigma]. Implementing the Ornstein-Uhlenbeck process is quite simple. We need two functions or functors - one for the deterministic and one for the stochastic part: + +[stochastic_euler_ornstein_uhlenbeck_def] + +In the stochastic part we have used the Mersenne twister for the random number generation and a Gaussian white noise generator `normal_distribution` with standard deviation ['__sigma]. Now, we can use the stochastic Euler stepper with the integrate functions: + +[ornstein_uhlenbeck_main] + +Note, how we have used the `make_pair` function for the generation of the system function. + +[endsect] + +[section Custom Runge-Kutta steppers] + +[import ../examples/heun.cpp] + +odeint provides a C++ template meta-algorithm for constructing arbitrary +Runge-Kutta schemes [footnote M. Mulansky, K. Ahnert, Template-Metaprogramming +applied to numerical problems, [@http://arxiv.org/abs/1110.3233 arxiv:1110.3233]]. Some schemes are predefined in odeint, for +example the classical Runge-Kutta of fourth order, or the +Runge-Kutta-Cash-Karp 54 and the Runge-Kutta-Fehlberg 78 method. +You can use this meta algorithm to construct you own solvers. This has the +advantage that you can make full use of odeint's algebra and operation system. + +Consider for example the method of Heun, defined by the following Butcher tableau: + +[pre +c1 = 0 + +c2 = 1/3, a21 = 1/3 + +c3 = 2/3, a31 = 0 , a32 = 2/3 + + b1 = 1/4, b2 = 0 , b3 = 3/4 +] + +Implementing this method is very easy. First you have to define the constants: + +[heun_define_coefficients] + +While this might look cumbersome, packing all +parameters into a templatized class which is not immediately evaluated has the +advantage that you can change the `value_type` of your stepper to any type you +like - presumably arbitrary precision types. One could also instantiate +the coefficients directly + +`` +const boost::array< double , 1 > heun_a1 = {{ 1.0 / 3.0 }}; +const boost::array< double , 2 > heun_a2 = {{ 0.0 , 2.0 / 3.0 }}; +const boost::array< double , 3 > heun_b = {{ 1.0 / 4.0 , 0.0 , 3.0 / 4.0 }}; +const boost::array< double , 3 > heun_c = {{ 0.0 , 1.0 / 3.0 , 2.0 / 3.0 }}; +`` + +But then you are nailed down to use doubles. + +Next, you need to define your stepper, note that the Heun method has 3 stages +and produces approximations of order 3: + +[heun_stepper_definition] + +That's it. Now, we have a new stepper method and we can use it, for example with the Lorenz system: + +[heun_example] + +[endsect] + + +[endsect] diff --git a/doc/examples_table.qbk b/doc/examples_table.qbk new file mode 100644 index 00000000..816908f5 --- /dev/null +++ b/doc/examples_table.qbk @@ -0,0 +1,125 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[table Examples Overview + [[File] [Brief Description]] + + [[[github_link libs/numeric/odeint/examples/adaptive_iterator.cpp adaptive_iterator.cpp]] + [The adaptive iterator examples shows the usage of the adaptive iterators and how they can be used with C++11 lambdas.]] + + [[[github_link libs/numeric/odeint/examples/bind_member_functions.cpp bind_member_functions.cpp]] + [This examples shows how member functions can be used as system functions in odeint.]] + + [[[github_link libs/numeric/odeint/examples/bind_member_functions.cpp bind_member_functions_cpp11.cpp]] + [This examples shows how member functions can be used as system functions in odeint with `std::bind` in C++11.]] + + [[[github_link libs/numeric/odeint/examples/bulirsch_stoer.cpp bulirsch_stoer.cpp]] + [Shows the usage of the Bulirsch-Stoer method.]] + + [[[github_link libs/numeric/odeint/examples/chaotic_system.cpp chaotic_system.cpp]] + [The chaotic system examples integrates the Lorenz system and calculates the Lyapunov exponents.]] + + [[[github_link libs/numeric/odeint/examples/const_step_iterator.cpp const_step_iterator.cpp]] + [The adaptive iterator examples shows the usage of the const step iterators and how they can be used with C++11 lambdas.]] + + [[[github_link libs/numeric/odeint/examples/elliptic_functions.cpp elliptic_functions.cpp]] + [Example calculating the elliptic functions using Bulirsch-Stoer and Runge-Kutta-Dopri5 Steppers with dense output.]] + + [[[github_link libs/numeric/odeint/examples/fpu.cpp fpu.cpp]] + [The Fermi-Pasta-Ulam (FPU) example shows how odeint can be used to integrate lattice systems.]] + + [[[github_link libs/numeric/odeint/examples/generation_functions.cpp generation_functions.cpp]] + [Shows skeletal code on how to implemente own factory functions.]] + + [[[github_link libs/numeric/odeint/examples/harmonic_oscillator.cpp harmonic_oscillator.cpp]] + [The harmonic oscillator examples gives a brief introduction to odeint and shows the usage of the classical Runge-Kutta-solvers.]] + + [[[github_link libs/numeric/odeint/examples/harmonic_oscillator_units.cpp harmonic_oscillator_units.cpp]] + [This examples shows how __boost_units can be used with odeint.]] + + [[[github_link libs/numeric/odeint/examples/heun.cpp heun.cpp]] + [The Heun example shows how an custom Runge-Kutta stepper can be created with odeint generic Runge-Kutta method.]] + + [[[github_link libs/numeric/odeint/examples/list_lattice.cpp list_lattice.cpp]] + [Example of a phase lattice integration using `std::list` as state type.]] + + [[[github_link libs/numeric/odeint/examples/lorenz_point.cpp lorenz_point.cpp]] + [Alternative way of integrating lorenz by using a self defined point3d data type as state type.]] + + [[[github_link libs/numeric/odeint/examples/my_vector.cpp my_vector.cpp]] + [Simple example showing how to get odeint to work with a self-defined vector type.]] + + [[[github_link libs/numeric/odeint/examples/phase_oscillator_ensemble.cpp phase_oscillator_ensemble.cpp]] + [The phase oscillator ensemble example shows how globally coupled oscillators can be analyzed and how statistical measures can be computed during integration.]] + + [[[github_link libs/numeric/odeint/examples/resizing_lattice.cpp resizing_lattice.cpp]] + [Shows the strength of odeint's memory management by simulating a Hamiltonian system on an expanding lattice.]] + + [[[github_link libs/numeric/odeint/examples/simple1d.cpp simple1d.cpp]] + [Integrating a simple, one-dimensional ODE showing the usage of integrate- and generate-functions.]] + + [[[github_link libs/numeric/odeint/examples/solar_system.cpp solar_system.cpp]] + [The solar system example shows the usage of the symplectic solvers.]] + + [[[github_link libs/numeric/odeint/examples/stepper_details.cpp stepper_details.cpp]] + [Trivial example showing the usability of the several stepper classes.]] + + [[[github_link libs/numeric/odeint/examples/stiff_system.cpp stiff_system.cpp]] + [The stiff system example shows the usage of the stiff solvers using the Jacobian of the system function.]] + + [[[github_link libs/numeric/odeint/examples/stochastic_euler.cpp stochastic_euler.cpp]] + [Implementation of a custom stepper - the stochastic euler - for solving stochastic differential equations.]] + + [[[github_link libs/numeric/odeint/examples/stuart_landau.cpp stuart_landau.cpp]] + [The Stuart-Landau example shows how odeint can be used with complex state types.]] + + [[[github_link libs/numeric/odeint/examples/two_dimensional_phase_lattice.cpp two_dimensional_phase_lattice.cpp]] + [The 2D phase oscillator example shows how a two-dimensional lattice works with odeint and how matrix types can be used as state types in odeint.]] + + [[[github_link libs/numeric/odeint/examples/van_der_pol_stiff.cpp van_der_pol_stiff.cpp]] + [This stiff system example again shows the usage of the stiff solvers by integrating the van der Pol oscillator.]] + + [[[github_link libs/numeric/odeint/examples/gmpxx/lorenz_gmpxx.cpp gmpxx/lorenz_gmpxx.cpp]] + [This examples integrates the Lorenz system by means of an arbitrary precision type.]] + + [[[github_link libs/numeric/odeint/examples/mtl/gauss_packet.cpp mtl/gauss_packet.cpp]] + [The MTL-Gauss-packet example shows how the MTL can be easily used with odeint.]] + + [[[github_link libs/numeric/odeint/examples/mtl/implicit_euler_mtl.cpp mtl/implicit_euler_mtl.cpp]] + [This examples shows the usage of the MTL implicit Euler method with a sparse matrix type.]] + + [[[github_link libs/numeric/odeint/examples/thrust/phase_oscillator_ensemble.cu thrust/phase_oscillator_ensemble.cu]] + [The Thrust phase oscillator ensemble example shows how globally coupled oscillators can be analyzed with Thrust and CUDA, employing the power of modern graphic devices.]] + + [[[github_link libs/numeric/odeint/examples/thrust/phase_oscillator_chain.cu thrust/phase_oscillator_chain.cu]] + [The Thrust phase oscillator chain example shows how chains of nearest neighbor coupled oscillators can be integrated with Thrust and odeint.]] + + [[[github_link libs/numeric/odeint/examples/thrust/lorenz_parameters.cu thrust/lorenz_parameters.cu]] + [The Lorenz parameters examples show how ensembles of ordinary differential equations can be solved by means of Thrust to study + the dependence of an ODE on some parameters.]] + + [[[github_link libs/numeric/odeint/examples/thrust/relaxation.cu thrust/relaxation.cu]] + [Another examples for the usage of Thrust.]] + + [[[github_link libs/numeric/odeint/examples/ublas/lorenz_ublas.cpp ublas/lorenz_ublas.cpp]] + [This example shows how the ublas vector types can be used with odeint.]] + + [[[github_link libs/numeric/odeint/examples/vexcl/lorenz_ensemble.cpp vexcl/lorenz_ensemble.cpp]] + [This example shows how the VexCL - a framework for OpenCL computation - can be used with odeint.]] + + [[[github_link libs/numeric/odeint/examples/2d_lattice/spreading.cpp 2d_lattice/spreading.cpp]] + [This examples shows how a `vector< vector< T > >` can be used a state type for odeint and how a resizing mechanism of this state can be implemented.]] + + [[[github_link libs/numeric/odeint/examples/quadmath/black_hole.cpp quadmath/black_hole.cpp]] + [This examples shows how gcc libquadmath can be used with odeint. It provides a high precision floating point type which is adapted to odeint in this example.]] + +] diff --git a/doc/getting_started.qbk b/doc/getting_started.qbk new file mode 100644 index 00000000..8b481257 --- /dev/null +++ b/doc/getting_started.qbk @@ -0,0 +1,143 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[section Getting started] + +[section Overview] + +[caution Boost.Numeric.Odeint is not an official boost library!] + +odeint is a library for solving initial value problems (IVP) of ordinary +differential equations. Mathematically, these problems are formulated as +follows: + +['x'(t) = f(x,t)], ['x(0) = x0]. + +['x] and ['f] can be vectors and the solution is some function ['x(t)] fulfilling both equations above. In the following we will refer to ['x'(t)] also `dxdt` which is also our notation for the derivative in the source code. + +Ordinary differential equations occur nearly everywhere in natural sciences. For example, the whole Newtonian mechanics are described by second order differential equations. Be sure, you will find them in every discipline. They also occur if partial differential equations (PDEs) are discretized. Then, a system of coupled ordinary differential occurs, sometimes also referred as lattices ODEs. + +Numerical approximations for the solution ['x(t)] are calculated iteratively. The easiest algorithm is the Euler scheme, where starting at ['x(0)] one finds ['x(dt) = x(0) + dt f(x(0),0)]. Now one can use ['x(dt)] and obtain ['x(2dt)] in a similar way and so on. The Euler method is of order 1, that means the error at each step is ['~ dt[super 2]]. This is, of course, not very satisfying, which is why the Euler method is rarely used for real life problems and serves just as illustrative example. + +The main focus of odeint is to provide numerical methods implemented in a way where the algorithm is completely independent on the data structure used to represent the state /x/. +In doing so, odeint is applicable for a broad variety of situations and it can be used with many other libraries. Besides the usual case where the state is defined as a `std::vector` or a `boost::array`, we provide native support for the following libraries: + +* __ublas +* __thrust, making odeint naturally running on CUDA devices +* gsl_vector for compatibility with the many numerical function in the GSL +* __boost_range +* __boost_fusion (the state type can be a fusion vector) +* __boost_units +* __intel_mkl for maximum performance +* __vexcl for OpenCL +* __boost_graph (still experimentally) + +In odeint, the following algorithms are implemented: + +[include stepper_table.qbk] + +[endsect] + + + +[section Usage, Compilation, Headers] + +odeint is a header-only library, no linking against pre-compiled code is required. It can be included by + +`` +#include +`` + +which includes all headers of the library. All functions and classes from odeint live in the namespace + +`` + using namespace boost::numeric::odeint; +`` + +It is also possible to include only parts of the library. This is the recommended way since it saves a lot of compilation time. + +* `#include ` - the include path for all steppers, XYZ is a placeholder for a stepper. +* `#include ` - all algebras. +* `#include ` - the utility functions like `is_resizeable`, `same_size`, or `resize`. +* `#include ` - the integrate routines. +* `#include ` - the range and iterator functions. +* `#include ` - any binders to external libraries. + + + +[endsect] + +[section Short Example] + +Imaging, you want to numerically integrate a harmonic oscillator with +friction. The equations of motion are given by ['x'' = -x + __gamma x']. +Odeint only deals with first order ODEs that have no higher derivatives than +x' involved. However, any higher order ODE can be transformed to a system of +first order ODEs by introducing the new variables ['q=x] and ['p=x'] such that ['w=(q,p)]. To apply numerical integration one first has to design the right hand side of the equation ['w' = f(w) = (p,-q+__gamma p)]: + +[import ../examples/harmonic_oscillator.cpp] +[rhs_function] + +Here we chose `vector` as the state type, but others are also +possible, for example `boost::array`. odeint is designed in such a +way that you can easily use your own state types. Next, the ODE is defined +which is in this case a simple function calculating ['f(x)]. The parameter +signature of this function is crucial: the integration methods will always +call them in the form `f(x, dxdt, t)` (there are exceptions for some special routines). So, even if there is no explicit time dependence, one has to define `t` as a function parameter. + +Now, we have to define the initial state from which the integration should start: + +[state_initialization] + +For the integration itself we'll use the `integrate` function, which is a convenient way to get quick results. It is based on the error-controlled `runge_kutta54_cash_karp` stepper (5th order) and uses adaptive step-size. + +[integration] + +The integrate function expects as parameters the rhs of the ode as defined +above, the initial state `x`, the start-and end-time of the integration as +well as the initial time step=size. Note, that `integrate` uses an adaptive step-size during +the integration steps so the time points will not be equally spaced. The +integration returns the number of steps that were applied and updates x which +is set to the approximate solution of the ODE at the end of integration. + +It is also possible to represent the ode system as a class. The +rhs must then be implemented as a functor - a class with an overloaded function call operator: + +[rhs_class] + +which can be used via + +[integration_class] + +In order to observe the solution +during the integration steps all you have to do is +to provide a reasonable observer. An example is + +[integrate_observer] + +which stores the intermediate steps in a container. +Note, the argument structure of the ()-operator: odeint calls the observer +exactly in this way, providing the current state and time. Now, you only have +to pass this container to the integration function: + +[integrate_observ] + +That is all. You can use functional libraries like __boost_lambda or __boost_phoenix to ease the creation of observer functions. + +The full cpp file for this example can be found here: [github_link libs/numeric/odeint/examples/harmonic_oscillator.cpp harmonic_oscillator.cpp] + + + +[endsect] + +[endsect] diff --git a/doc/html/logo.jpg b/doc/html/logo.jpg new file mode 100644 index 00000000..a658bbea Binary files /dev/null and b/doc/html/logo.jpg differ diff --git a/doc/html/phase_lattice_2d_0000.jpg b/doc/html/phase_lattice_2d_0000.jpg new file mode 100644 index 00000000..f98703eb Binary files /dev/null and b/doc/html/phase_lattice_2d_0000.jpg differ diff --git a/doc/html/phase_lattice_2d_0100.jpg b/doc/html/phase_lattice_2d_0100.jpg new file mode 100644 index 00000000..78628393 Binary files /dev/null and b/doc/html/phase_lattice_2d_0100.jpg differ diff --git a/doc/html/phase_lattice_2d_1000.jpg b/doc/html/phase_lattice_2d_1000.jpg new file mode 100644 index 00000000..e0ee037c Binary files /dev/null and b/doc/html/phase_lattice_2d_1000.jpg differ diff --git a/doc/html/solar_system.jpg b/doc/html/solar_system.jpg new file mode 100644 index 00000000..b89c3b3d Binary files /dev/null and b/doc/html/solar_system.jpg differ diff --git a/doc/literature.qbk b/doc/literature.qbk new file mode 100644 index 00000000..47cf94f9 --- /dev/null +++ b/doc/literature.qbk @@ -0,0 +1,53 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section Literature] + +[*General information about numerical integration of ordinary differential equations:] + +[#numerical_recipies] +[1] Press William H et al., Numerical Recipes 3rd Edition: The Art of Scientific Computing, 3rd ed. (Cambridge University Press, 2007). + +[#hairer_solving_odes_1] +[2] Ernst Hairer, Syvert P. Nørsett, and Gerhard Wanner, Solving Ordinary Differential Equations I: Nonstiff Problems, 2nd ed. (Springer, Berlin, 2009). + +[#hairer_solving_odes_2] +[3] Ernst Hairer and Gerhard Wanner, Solving Ordinary Differential Equations II: Stiff and Differential-Algebraic Problems, 2nd ed. (Springer, Berlin, 2010). + + +[*Symplectic integration of numerical integration:] + +[#hairer_geometrical_numeric_integration] +[4] Ernst Hairer, Gerhard Wanner, and Christian Lubich, Geometric Numerical Integration: Structure-Preserving Algorithms for Ordinary Differential Equations, 2nd ed. (Springer-Verlag Gmbh, 2006). + +[#leimkuhler_reich_simulating_hamiltonian_dynamics] +[5] Leimkuhler Benedict and Reich Sebastian, Simulating Hamiltonian Dynamics (Cambridge University Press, 2005). + + +[*Special symplectic methods:] + +[#symplectic_yoshida_symplectic_integrators] +[6] Haruo Yoshida, “Construction of higher order symplectic integrators,” Physics Letters A 150, no. 5 (November 12, 1990): 262-268. + +[#symplectic_mylachlan_symmetric_composition_mehtods] +[7] Robert I. McLachlan, “On the numerical integration of ordinary differential equations by symmetric composition methods,” SIAM J. Sci. Comput. 16, no. 1 (1995): 151-168. + + +[*Special systems:] + +[#fpu_scholarpedia] +[8] [@http://www.scholarpedia.org/article/Fermi-Pasta-Ulam_nonlinear_lattice_oscillations Fermi-Pasta-Ulam nonlinear lattice oscillations] + +[#synchronization_pikovsky_rosenblum] +[9] Arkady Pikovsky, Michael Rosemblum, and Jürgen Kurths, Synchronization: A Universal Concept in Nonlinear Sciences. (Cambridge University Press, 2001). + +[endsect] diff --git a/doc/make_controlled_table.qbk b/doc/make_controlled_table.qbk new file mode 100644 index 00000000..586864b5 --- /dev/null +++ b/doc/make_controlled_table.qbk @@ -0,0 +1,20 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[table Generation functions make_controlled( abs_error , rel_error , stepper ) + [[Stepper] [Result of make_controlled] [Remarks]] + [[`runge_kutta_cash_karp54`] [`controlled_runge_kutta< runge_kutta_cash_karp54 , default_error_checker<...> >`] [['a[sub x]=1], ['a[sub dxdt]=1]]] + [[`runge_kutta_fehlberg78`] [`controlled_runge_kutta< runge_kutta_fehlberg78 , default_error_checker<...> >`] [['a[sub x]=1], ['a[sub dxdt]=1]]] + [[`runge_kutta_dopri5`] [`controlled_runge_kutta< runge_kutta_dopri5 , default_error_checker<...> >`] [['a [sub x]=1], ['a[sub dxdt]=1]]] + [[`rosenbrock4`] [`rosenbrock4_controlled< rosenbrock4 >`] [-]] +] diff --git a/doc/make_dense_output_table.qbk b/doc/make_dense_output_table.qbk new file mode 100644 index 00000000..d9281346 --- /dev/null +++ b/doc/make_dense_output_table.qbk @@ -0,0 +1,19 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[table Generation functions make_dense_output( abs_error , rel_error , stepper ) + [[Stepper] [Result of make_dense_output] [Remarks]] + [[`runge_kutta_dopri5`] [`dense_output_runge_kutta< controlled_runge_kutta< runge_kutta_dopri5 , default_error_checker<...> > >`] [['a [sub x]=1], ['a[sub dxdt]=1]]] + [[`rosenbrock4`] [`rosenbrock4_dense_output< rosenbrock4_controller< rosenbrock4 > >`] [-]] +] + diff --git a/doc/odeint.qbk b/doc/odeint.qbk new file mode 100644 index 00000000..77baa997 --- /dev/null +++ b/doc/odeint.qbk @@ -0,0 +1,237 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[library Boost.Numeric.Odeint + [quickbook 1.5] + [id odeint] + [dirname odeint] + [authors [Ahnert, Karsten], [Mulansky, Mario]] + [copyright 2009-2012 Karsten Ahnert and Mario Mulansky] + [category math] + [purpose + Numerical integration of ordinary differential equations. + ] + [license + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or copy + at [@http://www.boost.org/LICENSE_1_0.txt]) + ] +] + +[include auto_index_helpers.qbk] + + + +[def __boost_lambda + [@http://www.boost.org/doc/libs/release/doc/html/lambda.html Boost.Lambda]] +[def __boost_phoenix + [@http://www.boost.org/doc/libs/1_46_1/libs/spirit/phoenix/doc/html/index.html Boost.Phoenix]] +[def __boost_operators + [@http://www.boost.org/doc/libs/release/doc/html/operators.html Boost.Operators]] +[def __boost_ref + [@http://www.boost.org/doc/libs/release/doc/html/ref.html Boost.Ref]] +[def __boost_range + [@http://www.boost.org/doc/libs/release/libs/range/index.html Boost.Range]] +[def __boost_units + [@http://www.boost.org/doc/libs/release/libs/units/index.html Boost.Units]] +[def __boost_fusion + [@http://www.boost.org/doc/libs/release/libs/fusion/index.html Boost.Fusion]] +[def __boost_graph + [@http://www.boost.org/doc/libs/1_47_0/libs/graph/doc/table_of_contents.html Boost.Graph]] + +[def __thrust + [@http://code.google.com/p/thrust/ Thrust]] +[def __ublas + [@http://www.boost.org/doc/libs/release/libs/numeric/ublas/index.html Boost.uBLAS]] +[def __intel_mkl + [@http://software.intel.com/en-us/articles/intel-mkl/ Intel Math Kernel Library]] +[def __gsl + [@http://www.gsl.org GSL]] +[def __vexcl + [@https://github.com/ddemidov/vexcl VexCL]] + +[def __concepts + [link boost_numeric_odeint.concepts Concepts]] +[def __system + [link boost_numeric_odeint.concepts.system System]] +[def __symplectic_system + [link boost_numeric_odeint.concepts.symplectic_system Symplectic System]] +[def __simple_symplectic_system + [link boost_numeric_odeint.concepts.simple_symplectic_system Simple Symplectic System]] +[def __implicit_system + [link boost_numeric_odeint.concepts.implicit_system Implicit System]] +[def __stepper + [link boost_numeric_odeint.concepts.stepper Stepper]] +[def __error_stepper + [link boost_numeric_odeint.concepts.error_stepper Error Stepper]] +[def __controlled_stepper + [link boost_numeric_odeint.concepts.controlled_stepper Controlled Stepper]] +[def __dense_output_stepper + [link boost_numeric_odeint.concepts.dense_output_stepper Dense Output Stepper]] +[def __integrate_functions + [link boost_numeric_odeint.odeint_in_detail.integrate_functions integrate functions]] +[def __tutorial + [link boost_numeric_odeint.tutorial Tutorial]] +[def __tut_solar_system + [link boost_numeric_odeint.tutorial.solar_system Solar System]] +[def __tut_chaotic_system + [link boost_numeric_odeint.tutorial.chaotic_systems_and_lyapunov_exponents Chaotic System]] +[def __tut_harmonic_oscillator + [link boost_numeric_odeint.tutorial.harmonic_oscillator Harmonic Oscillator]] +[def __using_steppers + [link boost_numeric_odeint.odeint_in_detail.steppers.using_steppers Using steppers]] +[def __generation_functions + [link boost_numeric_odeint.odeint_in_detail.generation_functions Generation functions]] +[def __adapt_state_types + [link boost_numeric_odeint.odeint_in_detail.state_types__algebras_and_operations Adapt your own state types]] +[def __resizing_lattice_example + [link boost_numeric_odeint.tutorial.self_expanding_lattices Self expanding lattices]] +[def __odeint_stepper_table + [link boost_numeric_odeint.odeint_in_detail.steppers.stepper_overview Stepper overview]] + + + +[def __nr_ref [link numerical_recipies \[1\] ]] +[def __hairer_1_ref [link hairer_solving_odes_1 \[2\] ]] +[def __hairer_2_ref [link hairer_solving_odes_2 \[3\] ]] +[def __hairer_geom_ref [link hairer_geometrical_numeric_integration \[4\] ]] +[def __leimkuhler_reich_ref [link leimkuhler_reich_simulating_hamiltonian_dynamics \[5\] ]] +[def __symplectic_integrator_1_ref [link symplectic_yoshida_symplectic_integrators \[6\] ]] +[def __symplectic_integrator_2_ref [link symplectic_mylachlan_symmetric_composition_mehtods \[7\] ]] +[def __fpu_scholarpedia_ref [link fpu_scholarpedia \[8\] ]] +[def __synchronization_pikovsky_ref [link synchronization_pikovsky_rosenblum \[9\] ]] + + + + + +[def __alpha '''α'''] +[def __beta '''β'''] +[def __delta '''δ'''] +[def __Delta '''Δ'''] +[def __lambda '''λ'''][/lower case] +[def __Lambda '''Λ'''][/upper case] +[def __gamma '''γ'''] +[def __Gamma '''Γ'''] +[def __sigma '''σ'''] +[def __Sigma '''Σ'''] +[def __Omega '''Ω'''] +[def __omega '''ω'''] +[def __phi '''φ'''] +[def __psi '''&ä968;'''] +[def __Phi '''Φ'''] +[def __Psi '''Ψ'''] +[def __epsilon '''ε'''] +[def __eta '''η'''] +[def __theta '''θ'''] +[def __Theta '''Θ'''] +[def __xi '''ξ'''] + +[def __space '''​'''] + + + +[template super[x]''''''[x]''''''] +[template sub[x]''''''[x]''''''] +[template subl[x]''''''__space[x]''''''] + +[/ [template github_link[url text]''''''[text]'''''']] +[template github_link[url text]''''''[text]''''''] + + + + +[include getting_started.qbk] + +[include tutorial.qbk] + +[include details.qbk] + +[include concepts.qbk] + +[include literature.qbk] + +[include acknowledgements.qbk] + +[xinclude reference.xml] + +[section:indexes Indexes] + +[named_index class_name Class Index] +[named_index function_name Function Index] +[/ +[named_index typedef_name Typedef Index] +[named_index macro_name Macro Index] +] +[index] + +[endsect] + + + + +[/ +# Α Α Α U+0391 Greek capital letter alpha +# Β Β Β U+0392 Greek capital letter beta +# Γ Γ Γ U+0393 Greek capital letter gamma ISOgrk3 +# Δ Δ Δ U+0394 Greek capital letter delta ISOgrk3 +# Ε Ε Ε U+0395 Greek capital letter epsilon +# Ζ Ζ Ζ U+0396 Greek capital letter zeta +# Η Η Η U+0397 Greek capital letter eta +# Θ Θ Θ U+0398 Greek capital letter theta ISOgrk3 +# Ι Ι Ι U+0399 Greek capital letter iota +# Κ Κ Κ U+039A Greek capital letter kappa +# Λ Λ Λ U+039B Greek capital letter lambda ISOgrk3 +# Μ Μ Μ U+039C Greek capital letter mu +# Ν Ν Ν U+039D Greek capital letter nu +# Ξ Ξ Ξ U+039E Greek capital letter xi ISOgrk3 +# Ο Ο Ο U+039F Greek capital letter omicron +# Π Π Π U+03A0 Greek capital letter pi ISOgrk3 +# Ρ Ρ Ρ U+03A1 Greek capital letter rho +# Σ Σ Σ U+03A3 Greek capital letter sigma ISOgrk3 +# Τ Τ Τ U+03A4 Greek capital letter tau +# Υ Υ Υ U+03A5 Greek capital letter upsilon ISOgrk3 +# Φ Φ Φ U+03A6 Greek capital letter phi ISOgrk3 +# Χ Χ Χ U+03A7 Greek capital letter chi +# Ψ Ψ Ψ U+03A8 Greek capital letter psi ISOgrk3 +# Ω Ω Ω U+03A9 Greek capital letter omega ISOgrk3 +# α α α U+03B1 Greek small letter alpha ISOgrk3 +# β β β U+03B2 Greek small letter beta ISOgrk3 +# γ γ γ U+03B3 Greek small letter gamma ISOgrk3 +# δ δ δ U+03B4 Greek small letter delta ISOgrk3 +# ε ε ε U+03B5 Greek small letter epsilon ISOgrk3 +# ζ ζ ζ U+03B6 Greek small letter zeta ISOgrk3 +# η η η U+03B7 Greek small letter eta ISOgrk3 +# θ θ θ U+03B8 Greek small letter theta ISOgrk3 +# ι ι ι U+03B9 Greek small letter iota ISOgrk3 +# κ κ κ U+03BA Greek small letter kappa ISOgrk3 +# λ λ λ U+03BB Greek small letter lambda ISOgrk3 +# μ μ μ U+03BC Greek small letter mu ISOgrk3 +# ν ν ν U+03BD Greek small letter nu ISOgrk3 +# ξ ξ ξ U+03BE Greek small letter xi ISOgrk3 +# ο ο ο U+03BF Greek small letter omicron New +# π π π U+03C0 Greek small letter pi ISOgrk3 +# ρ ρ ρ U+03C1 Greek small letter rho ISOgrk3 +# ς ς ς U+03C2 Greek small letter final sigma ISOgrk3 +# σ σ σ U+03C3 Greek small letter sigma ISOgrk3 +# τ τ τ U+03C4 Greek small letter tau ISOgrk3 +# υ υ υ U+03C5 Greek small letter upsilon ISOgrk3 +# φ φ φ U+03C6 Greek small letter phi ISOgrk3 +# χ χ χ U+03C7 Greek small letter chi ISOgrk3 +# ψ ψ ψ U+03C8 Greek small letter psi ISOgrk3 +# ω ω ω U+03C9 Greek small letter omega ISOgrk3 +# ϑ ϑ ϑ U+03D1 Greek small letter theta symbol New +# ϒ ϒ ϒ U+03D2 Greek upsilon with hook symbol New +# ϖ ϖ ϖ U+03D6 Greek pi symbol ISOgrk3 + +/] diff --git a/doc/range_table.qbk b/doc/range_table.qbk new file mode 100644 index 00000000..40995ebe --- /dev/null +++ b/doc/range_table.qbk @@ -0,0 +1,70 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[/ +Steppers supporting __boost_range: + +* adams_bashforth_moulton +* bulirsch_stoer_dense_out +* bulirsch_stoer +* controlled_runge_kutta +* dense_output_runge_kutta +* euler +* explicit_error_generic_rk +* explicit_generic_rk +* rosenbrock4_controller +* rosenbrock4_dense_output +* rosenbrock4 +* runge_kutta4_classic +* runge_kutta4 +* runge_kutta_cash_karp54_classic +* runge_kutta_cash_karp54 +* runge_kutta_dopri5 +* runge_kutta_fehlberg78 +* symplectic_euler +* symplectic_rkn_sb3a_mclachlan + +Algebras supporting __boost_range + +* range_algebra +* thrust_algebra +/] + +[table Steppers supporting Boost.Range + [[Stepper]] + [[adams_bashforth_moulton]] + [[bulirsch_stoer_dense_out]] + [[bulirsch_stoer]] + [[controlled_runge_kutta]] + [[dense_output_runge_kutta]] + [[euler]] + [[explicit_error_generic_rk]] + [[explicit_generic_rk]] + [[rosenbrock4_controller]] + [[rosenbrock4_dense_output]] + [[rosenbrock4]] + [[runge_kutta4_classic]] + [[runge_kutta4]] + [[runge_kutta_cash_karp54_classic]] + [[runge_kutta_cash_karp54]] + [[runge_kutta_dopri5]] + [[runge_kutta_fehlberg78]] + [[symplectic_euler]] + [[symplectic_rkn_sb3a_mclachlan]] +] + +[table Algebras supporting Boost.Range + [[algebra]] + [[range_algebra]] + [[thrust_algebra]] +] \ No newline at end of file diff --git a/doc/stepper_table.qbk b/doc/stepper_table.qbk new file mode 100644 index 00000000..fca0c4ce --- /dev/null +++ b/doc/stepper_table.qbk @@ -0,0 +1,40 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[table Stepper Algorithms + [[Algorithm] [Class] [Concept] [System Concept] [Order] [Error Estimation] [Dense Output] [Internal state] [Remarks]] + [[Explicit Euler] [`euler`] [__dense_output_stepper] [__system] [1] [No] [Yes] [No] [Very simple, only for demonstrating purpose]] + [[Modified Midpoint] [`modified_midpoint`] [__stepper] [__system] [configurable (2)] [No] [No] [No] [Used in Bulirsch-Stoer implementation]] + [[Runge-Kutta 4] [`runge_kutta4`] [__stepper] [__system] [4] [No] [No] [No] [The classical Runge-Kutta scheme, good general scheme without error control]] + [[Cash-Karp] [`runge_kutta_cash_karp54`] [__error_stepper] [__system] [5] [Yes (4)] [No] [No] [Good general scheme with error estimation, to be used in controlled_error_stepper]] + [[Dormand-Prince 5] [`runge_kutta_dopri5`] [__error_stepper] [__system] [5] [Yes (4)] [Yes] [Yes] [Standard method with error control and dense output, to be used in controlled_error_stepper and in dense_output_controlled_explicit_fsal.]] + [[Fehlberg 78] [`runge_kutta_fehlberg78`] [__error_stepper] [__system] [8] [Yes (7)] [No] [No] [Good high order method with error estimation, to be used in controlled_error_stepper.]] + + [[Adams Bashforth] [`adams_bashforth`] [__stepper] [__system] [configurable] [No] [No] [Yes] [Multistep method]] + [[Adams Moulton] [`adams_moulton`] [__stepper] [__system] [configurable] [No] [No] [Yes] [Multistep method]] + [[Adams Bashforth Moulton] [`adams_bashforth_moulton`] [__stepper] [__system] [configurable] [No] [No] [Yes] [Combined multistep method]] + + [[Controlled Runge-Kutta] [`controlled_runge_kutta`] [__controlled_stepper] [__system] [depends] [Yes] [No] [depends] [Error control for __error_stepper. Requires an __error_stepper from above. Order depends on the given ErrorStepper]] + [[Dense Output Runge-Kutta] [`dense_output_runge_kutta`] [__dense_output_stepper] [__system] [depends] [No] [Yes] [Yes] [Dense output for __stepper and __error_stepper from above if they provide dense output functionality (like `euler` and `runge_kutta_dopri5`). Order depends on the given stepper.]] + + [[Bulirsch-Stoer] [`bulirsch_stoer`] [__controlled_stepper] [__system] [variable] [Yes] [No] [No] [Stepper with step size and order control. Very good if high precision is required.]] + [[Bulirsch-Stoer Dense Output] [`bulirsch_stoer_dense_out`] [__dense_output_stepper] [__system] [variable] [Yes] [Yes] [No] [Stepper with step size and order control as well as dense output. Very good if high precision and dense output is required.]] + + [[Implicit Euler] [`implicit_euler`] [__stepper] [__implicit_system] [1] [No] [No] [No] [Basic implicit routine. Requires the Jacobian. Works only with __ublas vectors as state types.]] + [[Rosenbrock 4] [`rosenbrock4`] [__error_stepper] [__implicit_system] [4] [Yes] [Yes] [No] [Good for stiff systems. Works only with __ublas vectors as state types.]] + [[Controlled Rosenbrock 4] [`rosenbrock4_controller`] [__controlled_stepper] [__implicit_system] [4] [Yes] [Yes] [No] [Rosenbrock 4 with error control. Works only with __ublas vectors as state types.]] + [[Dense Output Rosenbrock 4] [`rosenbrock4_dense_output`] [__dense_output_stepper] [__implicit_system] [4] [Yes] [Yes] [No] [Controlled Rosenbrock 4 with dense output. Works only with __ublas vectors as state types.]] + + [[Symplectic Euler] [`symplectic_euler`] [__stepper] [__symplectic_system __simple_symplectic_system] [1] [No] [No] [No] [Basic symplectic solver for separable Hamiltonian system]] + [[Symplectic RKN McLachlan] [`symplectic_rkn_sb3a_mclachlan`] [__stepper] [__symplectic_system __simple_symplectic_system] [4] [No] [No] [No] [Symplectic solver for separable Hamiltonian system with 6 stages and order 4.]] + [[Symplectic RKN McLachlan] [`symplectic_rkn_sb3a_m4_mclachlan`] [__stepper] [__symplectic_system __simple_symplectic_system] [4] [No] [No] [No] [Symplectic solver with 5 stages and order 4, can be used with arbitrary precision types.]] +] diff --git a/doc/tutorial.qbk b/doc/tutorial.qbk new file mode 100644 index 00000000..daab5276 --- /dev/null +++ b/doc/tutorial.qbk @@ -0,0 +1,44 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section Tutorial] + + +[include tutorial_harmonic_oscillator.qbk] + +[include tutorial_solar_system.qbk] + +[include tutorial_chaotic_system.qbk] + +[include tutorial_stiff_systems.qbk] + +[include tutorial_special_topics.qbk] + +[include tutorial_thrust_cuda.qbk] + +[include tutorial_vexcl_opencl.qbk] + + +[section All examples] + +The following table gives an overview over all examples. + +[include examples_table.qbk] + +[endsect] + + + + + + +[endsect] diff --git a/doc/tutorial_chaotic_system.qbk b/doc/tutorial_chaotic_system.qbk new file mode 100644 index 00000000..b90d8c13 --- /dev/null +++ b/doc/tutorial_chaotic_system.qbk @@ -0,0 +1,156 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section Chaotic systems and Lyapunov exponents] + +[import ../examples/chaotic_system.cpp] + +In this example we present application of odeint to investigation of the properties of chaotic +deterministic systems. In mathematical terms chaotic refers to an exponential +growth of perturbations ['__delta x]. In order to observe this exponential growth one usually solves the equations for the tangential dynamics which is again an ordinary differential equation. These equations are linear but time dependent and can be obtained via + +['d __delta x / dt = J(x) __delta x] + +where ['J] is the Jacobian of the system under consideration. ['__delta x] can +also be interpreted as a perturbation of the original system. In principle +['n] of these perturbations exist, they form a hypercube and evolve in the +time. The Lyapunov exponents are then defined as logarithmic growth rates of +the perturbations. If one Lyapunov exponent is larger then zero the nearby +trajectories diverge exponentially hence they are chaotic. If the largest +Lyapunov exponent is zero one is usually faced with periodic motion. In the +case of a largest Lyapunov exponent smaller then zero convergence to a +fixed point is expected. More information's about Lyapunov exponents and nonlinear +dynamical systems can be found in many textbooks, see for example: E. Ott "Chaos is +Dynamical Systems", Cambridge. + +To calculate the Lyapunov exponents numerically one usually solves the equations of motion for ['n] perturbations and orthonormalizes them every ['k] steps. The Lyapunov exponent is the average of the logarithm of the stretching factor of each perturbation. + +To demonstrate how one can use odeint to determine the Lyapunov exponents we choose the Lorenz system. It is one of the most studied dynamical systems in the nonlinear dynamics community. For the standard parameters it possesses a strange attractor with non-integer dimension. The Lyapunov exponents take values of approximately 0.9, 0 and -12. + +The implementation of the Lorenz system is + +`` +const double sigma = 10.0; +const double R = 28.0; +const double b = 8.0 / 3.0; + +typedef boost::array< double , 3 > lorenz_state_type; + +void lorenz( const lorenz_state_type &x , lorenz_state_type &dxdt , double t ) +{ + dxdt[0] = sigma * ( x[1] - x[0] ); + dxdt[1] = R * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -b * x[2] + x[0] * x[1]; +} +`` +We need also to integrate the set of the perturbations. This is done in parallel to the original system, hence within one system function. Of course, we want to use the above definition of the Lorenz system, hence the definition of the system function including the Lorenz system itself and the perturbation could look like: + +`` +const size_t n = 3; +const size_t num_of_lyap = 3; +const size_t N = n + n*num_of_lyap; + +typedef std::tr1::array< double , N > state_type; +typedef std::tr1::array< double , num_of_lyap > lyap_type; + +void lorenz_with_lyap( const state_type &x , state_type &dxdt , double t ) +{ + lorenz( x , dxdt , t ); + + for( size_t l=0 ; l + void operator()( const StateIn &x , StateOut &dxdt , Value t ) + { + dxdt[0] = sigma * ( x[1] - x[0] ); + dxdt[1] = R * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -b * x[2] + x[0] * x[1]; + } +}; + +void lorenz_with_lyap( const state_type &x , state_type &dxdt , double t ) +{ + lorenz()( x , dxdt , t ); + ... +} + +`` +This works fine and `lorenz_with_lyap` can be used for example via +`` +state_type x; +// initialize x +explicit_rk4< state_type > rk4; +integrate_n_steps( rk4 , lorenz_with_lyap , x , 0.0 , 0.01 , 1000 ); +`` +This code snippet performs 1000 steps with constant step size 0.01. + +A real world use case for the calculation of the Lyapunov exponents of Lorenz system would always include some transient steps, just to ensure that the current state lies on the attractor, hence it would look like + +`` +state_type x; +// initialize x +explicit_rk4< state_type > rk4; +integrate_n_steps( rk4 , lorenz , x , 0.0 , 0.01 , 1000 ); +`` +The problem is now, that `x` is the full state containing also the +perturbations and `integrate_n_steps` does not know that it should only use 3 +elements. In detail, odeint and its steppers determine the length of the +system under consideration by determining the length of the state. In the +classical solvers, e.g. from Numerical Recipes, the problem was solved by +pointer to the state and an appropriate length, something similar to + +`` +void lorenz( double* x , double *dxdt , double t, void* params ) +{ + ... +} + +int system_length = 3; +rk4( x , system_length , t , dt , lorenz ); +`` + +But odeint supports a similar and much more sophisticated concept: __boost_range. To make the steppers and the system ready to work with __boost_range the system has to by changed: + +[system_function_without_perturbations] + +This is in principle all. Now, we only have to call `integrate_n_steps` with a +range including only the first 3 components of ['x]: + +[integrate_transients_with_range] + +Having integrated a sufficient number of transients steps we are now able to calculate the Lyapunov exponents: + +# Initialize the perturbations. They are stored linearly behind the state of the Lorenz system. The perturbations are initialized such that [' p [subl ij] = __delta [subl ij]], where ['p [subl ij]] is the ['j]-component of the ['i].-th perturbation and ['__delta [subl ij]] is the Kronecker symbol. +# Integrate 100 steps of the full system with perturbations +# Orthonormalize the perturbation using Gram-Schmidt orthonormalization algorithm. +# Repeat step 2 and 3. Every 10000 steps write the current Lyapunov exponent. + +[lyapunov_full_code] + +The full code can be found here: [github_link libs/numeric/odeint/examples/chaotic_system.cpp chaotic_system.cpp] + +[endsect] diff --git a/doc/tutorial_harmonic_oscillator.qbk b/doc/tutorial_harmonic_oscillator.qbk new file mode 100644 index 00000000..93dee8f6 --- /dev/null +++ b/doc/tutorial_harmonic_oscillator.qbk @@ -0,0 +1,122 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[section Harmonic oscillator] + +[section Define the ODE] + +First of all, you have to specify the data type that represents a state ['x] of your system. Mathematically, this usually is an n-dimensional vector with real numbers or complex numbers as scalar objects. For odeint the most natural way is to use `vector< double >` or `vector< complex< double > >` to represent the system state. However, odeint can deal with other container types as well, e.g. `boost::array< double , N >`, as long as it fulfills some requirements defined below. + +To integrate a differential equation numerically, one also has to define the rhs of the equation ['x' = f(x)]. In odeint you supply this function in terms of an object that implements the ()-operator with a certain parameter structure. Hence, the straightforward way would be to just define a function, e.g: + +[rhs_function] + +The parameters of the function must follow the example above where `x` is the +current state, here a two-component vector containing position ['q] and +momentum ['p] of the oscillator, `dxdt` is the derivative ['x'] and should be +filled by the function with ['f(x)], and `t` is the current time. +Note that in this example ['t] is not required to calculate ['f], however +odeint expects the function signature to have exactly three parameters (there +are exception, discussed later). + +A more sophisticated approach is to implement the system as a class where the rhs function is defined as the ()-operator of the class with the same parameter structure as above: + +[rhs_class] + +odeint can deal with instances of such classes instead of pure functions which +allows for cleaner code. + +[endsect] + +[section Stepper Types] + +Numerical integration works iteratively, that means you start at a state ['x(t)] and perform a time-step of length ['dt] to obtain the approximate state ['x(t+dt)]. There exist many different methods to perform such a time-step each of which has a certain order ['q]. If the order of a method is ['q] than it is accurate up to term ['~dt[super q]] that means the error in ['x] made by such a step is ['~dt[super q+1]]. odeint provides several steppers of different orders, see __odeint_stepper_table. + +Some of steppers in the table above are special: Some need the Jacobian of the ODE, others are constructed for special ODE-systems like Hamiltonian systems. We will show typical examples and use-cases in this tutorial and which kind of steppers should be applied. + +[endsect] + +[section Integration with Constant Step Size] + +The basic stepper just performs one time-step and doesn't give you any information about the error that was made (except that you know it is of order ['q+1]). Such steppers are used with constant step size that should be chosen small enough to have reasonable small errors. However, you should apply some sort of validity check of your results (like observing conserved quantities) because you have no other control of the error. The following example defines a basic stepper based on the classical Runge-Kutta scheme of 4th order. The declaration of the stepper requires the state type as template parameter. The integration can now be done by using the `integrate_const( Stepper, System, state, start_time, end_time, step_size )` function from odeint: + +[define_const_stepper] + +This call integrates the system defined by `harmonic_oscillator` using the RK4 method from ['t=0] to ['10] with a step-size ['dt=0.01] and the initial condition given in `x`. The result, ['x(t=10)] is stored in `x` (in-place). Each stepper defines a `do_step` method which can also be used directly. So, you write down the above example as + +[integrate_const_loop] + +[tip If you have a C++11 enabled compiler you can easily use lambdas to create the system function : + +[define_const_stepper_cpp11] + +] + +[endsect] + +[section Integration with Adaptive Step Size] + +To improve the numerical results and additionally minimize the computational +effort, the application of a step size control is advisable. Step size control +is realized via stepper algorithms that additionally provide an error +estimation of the applied step. odeint provides a number of such +*ErrorSteppers* and we will show their usage on the example of +`explicit_error_rk54_ck` - a 5th order Runge-Kutta method with 4th order +error estimation and coefficients introduced by Cash and Karp. + +[define_adapt_stepper] + +Given the error stepper, one still needs an instance that checks the error and adjusts the step size accordingly. In odeint, this is done by *ControlledSteppers*. For the `runge_kutta_cash_karp54` stepper a `controlled_runge_kutta` stepper exists which can be used via + +[integrate_adapt] + +As above, this integrates the system defined by `harmonic_oscillator`, but now using an adaptive step size method based on the Runge-Kutta Cash-Karp 54 scheme from ['t=0] to ['10] with an initial step size of ['dt=0.01] (will be adjusted) and the initial condition given in x. The result, ['x(t=10)], will also be stored in x (in-place). + +In the above example an error stepper is nested in a controlled stepper. This is a nice technique; however one drawback is that one always needs to define both steppers. One could also write the instantiation of the controlled stepper into the call of the integrate function but a complete knowledge of the underlying stepper types is still necessary. Another point is, that the error tolerances for the step size control are not easily included into the controlled stepper. Both issues can be solved by using `make_controlled`: + +[integrate_adapt_make_controlled] + +`make_controlled` can be used with many of the steppers of odeint. The first +parameter is the absolute error tolerance ['eps_abs] and the second is the +relative error tolerance ['eps_rel] which is used during the integration. The template parameter determines from which error stepper a controlled stepper should be instantiated. An alternative syntax of `make_controlled` is + +[integrate_adapt_make_controlled_alternative] + +For the Runge-Kutta controller the error made during one step is compared with ['eps_abs + eps_rel * ( a[sub x] * |x| + a[sub dxdt] * dt * |dxdt| )]. If the error is smaller than this value the current step is accepted, otherwise it is rejected and the step size is decreased. Note, that the step size is also increased if the error gets too small compared to the rhs of the above relation. The full instantiation of the `controlled_runge_kutta` with all parameters is therefore + +[integrate_adapt_full] + +When using `make_controlled` the parameter ['a[sub x]] and ['a[sub dxdt]] are used with their standard values of 1. + +In the tables below, one can find all steppers which are working with `make_controlled` and `make_dense_output` which is the analog for the dense output steppers. + +[include make_controlled_table.qbk] + +[include make_dense_output_table.qbk] + +When using `make_controlled` or `make_dense_output` one should be aware which exact type is used and how the step size control works. + +[endsect] + +[section Using iterators] + +odeint supports iterators for solving ODEs. That is you instantiate a pair of iterators and instead of using the integrate routines with an appropriate observer you put the iterators in one of the algorithm from the C++ standard library or from Boost.Range. An example is + +[harm_iterator_const_step] + +[endsect] + +The full source file for this example can be found here: [github_link libs/numeric/odeint/examples/harmonic_oscillator.cpp harmonic_oscillator.cpp] + + +[endsect] diff --git a/doc/tutorial_solar_system.qbk b/doc/tutorial_solar_system.qbk new file mode 100644 index 00000000..5151f6f5 --- /dev/null +++ b/doc/tutorial_solar_system.qbk @@ -0,0 +1,108 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[section Solar system] + +[section Gravitation and energy conservation] + +The next example in this tutorial is a simulation of the outer solar system, consisting of the sun, Jupiter, Saturn, Uranus, Neptune and Pluto. + +[$solar_system.jpg] + +Each planet and of course the sun will be represented by mass points. The interaction force between each object is the gravitational force which can be written as + +['F[subl ij] = -__gamma m[subl i] m[subl j] ( q[subl i] - q[subl j] ) / | q[subl i] - q[subl j] | [super 3]] + +where [' __gamma] is the gravitational constant, ['m[subl i]] and ['m[subl j]] are the masses and ['q[subl i]] and ['q[subl j]] are the locations of the two objects. The equations of motion are then + +['dq[subl i] / dt = p[subl i]] + +['dp[subl i] / dt = 1 / m[subl i] __Sigma[subl ji] F[subl ij]] + +where ['p[subl i]] is the momenta of object ['i]. The equations of motion can also be derived from the Hamiltonian + +['H = __Sigma[subl i] p[subl i][super 2] / ( 2 m[subl i] ) + __Sigma[subl j] V( q[subl i] , q[subl j] )] + +with the interaction potential ['V(q[subl i],q[subl j])]. The Hamiltonian equations give the +equations of motion + +['dq[subl i] / dt = dH / dp[subl i]] + +['dp[subl i] / dt = -dH / dq[subl i]] + +In time independent Hamiltonian system the energy and the phase space volume +are conserved and special integration methods have to be applied in order to +ensure these conservation laws. The odeint library provides classes for +separable Hamiltonian systems, which can be written in the form ['H = __Sigma +p[subl i][super 2] / (2m[subl i]) + H[subl q](q)], where ['H[subl q](q)] only +depends on the coordinates. Although this functional form might look a bit +arbitrary, it covers nearly all classical mechanical systems with inertia and +without dissipation, or where the equations of motion can be written in the +form ['dq[subl i] / dt = p[subl i]] / m[subl i] , ['dp[subl i] / dt = f( +q[subl i] )]. + +[note A short physical note: While the two-body-problem is known to be +integrable, that means it can be solved with purely analytic techniques, +already the three-body-problem is not solvable. This was found in the end of the +19th century by H. Poincare which led to the whole new subject of +[@http://en.wikipedia.org/wiki/Chaos_theory Chaos Theory].] + +[endsect] + + +[section Define the system function] + +To implement this system we define a 3D point type which will represent the space as well as the velocity. Therefore, we use the operators from __boost_operators: + +[import ../examples/point_type.hpp] +[point_type] + + +The next step is to define a container type storing the values of ['q] and ['p] and to define system functions. As container type we use `boost::array` + +[import ../examples/solar_system.cpp] +[container_type_definition] + +The `container_type` is different from the state type of the ODE. The state type of the ode is simply a `pair< container_type , container_type >` since it needs the information about the coordinates and the momenta. + +Next we define the system's equations. +As we will use a stepper that accounts for the Hamiltonian (energy-preserving) +character of the system, we have to define the rhs different from the usual +case where it is just a single function. +The stepper will make use of the separable character, which means the system +will be defined by two objects representing ['f(p) = -dH/dq] and ['g(q) = dH/dp]: + +[coordinate_function] + +[momentum_function] + +In general a three body-system is chaotic, hence we can not expect that arbitrary initial conditions of the system will lead to a solution comparable with the solar system dynamics. That is we have to define proper initial conditions, which are taken from the book of Hairer, Wannier, Lubich __hairer_geom_ref. + +As mentioned above, we need to use some special integrators in order to +conserve phase space volume. There is a well known family of such integrators, +the so-called Runge-Kutta-Nystroem solvers, which we apply here in terms of a +`symplectic_rkn_sb3a_mclachlan` stepper: + +[integration_solar_system] + +These integration routine was used to produce the above sketch of the solar system. Note, that there are two particularities in this example. First, the state of the symplectic stepper is not `container_type` but a pair of `container_type`. Hence, we must pass such a pair to the integrate function. Since, we want to pass them as references we can simply pack them into __boost_ref. The second point is the observer, which is called with a state type, hence a pair of `container_type`. The reference wrapper is also passed, but this is not a problem at all: + +[streaming_observer] + +[tip You can use C++11 lambda to create the observers] + +The full example can be found here: [github_link libs/numeric/odeint/examples/solar_system.cpp solar_system.cpp] + +[endsect] + +[endsect] diff --git a/doc/tutorial_special_topics.qbk b/doc/tutorial_special_topics.qbk new file mode 100644 index 00000000..141ec62a --- /dev/null +++ b/doc/tutorial_special_topics.qbk @@ -0,0 +1,258 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[/ [section Special topics] /] + +[section Complex state types] + +[import ../examples/stuart_landau.cpp] + +Thus far we have seen several examples defined for real values. +odeint can handle complex state types, hence ODEs which are defined on complex +vector spaces, as well. An example is the Stuart-Landau oscillator + +['d __Psi / dt = ( 1 + i __eta ) __Psi + ( 1 + i __alpha ) | __Psi |[super 2] __Psi ] + +where ['__Psi] and ['i] is a complex variable. The definition of this ODE in C++ +using complex< double > as a state type may look as follows + +[stuart_landau_system_function] + +One can also use a function instead of a functor to implement it + +[stuart_landau_system_function_alternative] + +We strongly recommend to use the first ansatz. In this case you have explicit control over the parameters of the system and are not restricted to use global variables to parametrize the oscillator. + +When choosing the stepper type one has to account for the "unusual" state type: +it is a single `complex` opposed to the vector types used in the +previous examples. This means that no iterations over vector elements have to +be performed inside the stepper algorithm. You can enforce this by supplying +additional template arguments to the stepper including the +`vector_space_algebra`. Details on the usage of algebras can be found in the +section __adapt_state_types. + +[stuart_landau_integration] + +The full cpp file for the Stuart-Landau example can be found here [github_link +libs/numeric/odeint/examples/stuart_landau.cpp stuart_landau.cpp] + +[note The fact that we have to configure a different algebra is solely due to +the fact that we use a non-vector state type and not to the usage of complex +values. So for, e.g. `vector< complex >`, this would not be required.] + +[endsect] + +[section Lattice systems] + +[import ../examples/fpu.cpp] + + +odeint can also be used to solve ordinary differential equations defined on lattices. A prominent example is the Fermi-Pasta-Ulam system __fpu_scholarpedia_ref. It is a Hamiltonian system of nonlinear coupled harmonic oscillators. The Hamiltonian is + +[' H = __Sigma[subl i] p[subl i][super 2]/2 + 1/2 ( q[subl i+1] - q[subl i] )^2 + __beta / 4 ( q[subl i+1] - q[subl i] )^4 ] + +Remarkably, the Fermi-Pasta-Ulam system was the first numerical experiment to be implemented on a computer. It was studied at Los Alamos in 1953 on one of the first computers (a MANIAC I) and it triggered a whole new tree of mathematical and physical science. + +Like the __tut_solar_system, the FPU is solved again by a symplectic solver, but in this case we can speed up the computation because the ['q] components trivially reduce to ['dq[subl i] / dt = p[subl i]]. odeint is capable of doing this performance improvement. All you have to do is to call the symplectic solver with an state function for the ['p] components. Here is how this function looks like + +[fpu_system_function] + +You can also use `boost::array< double , N >` for the state type. + +Now, you have to define your initial values and perform the integration: + +[fpu_integration] + +The observer uses a reference to the system object to calculate the local energies: + +[fpu_observer] + +The full cpp file for this FPU example can be found here [github_link libs/numeric/odeint/examples/fpu.cpp fpu.cpp] + +[endsect] + +[section Ensembles of oscillators] + +[import ../examples/phase_oscillator_ensemble.cpp] + +Another important high dimensional system of coupled ordinary differential equations is an ensemble of ['N] all-to-all coupled phase oscillators __synchronization_pikovsky_ref. It is defined as + +[' d__phi[subl k] / dt = __omega[subl k] + __epsilon / N __Sigma[subl j] sin( __phi[subl j] - __phi[subl k] )] + +The natural frequencies ['__omega[subl i]] of each oscillator follow some distribution and ['__epsilon] is the coupling strength. We choose here a Lorentzian distribution for ['__omega[subl i]]. Interestingly a phase transition can be observed if the coupling strength exceeds a critical value. Above this value synchronization sets in and some of the oscillators oscillate with the same frequency despite their different natural frequencies. The transition is also called Kuramoto transition. Its behavior can be analyzed by employing the mean field of the phase + +['Z = K e[super i __Theta] = 1 / N __Sigma[subl k]e[super i __phi[subl k]]] + +The definition of the system function is now a bit more complex since we also need to store the individual frequencies of each oscillator. + +[phase_oscillator_ensemble_system_function] + +Note, that we have used ['Z] to simplify the equations of motion. Next, we create an observer which computes the value of ['Z] and we record ['Z] for different values of ['__epsilon]. + +[phase_oscillator_ensemble_observer] + +Now, we do several integrations for different values of ['__epsilon] and record ['Z]. The result nicely confirms the analytical result of the phase transition, i.e. in our example the standard deviation of the Lorentzian is 1 such that the transition will be observed at ['__epsilon = 2]. + +[phase_oscillator_ensemble_integration] + +The full cpp file for this example can be found here [github_link libs/numeric/odeint/examples/phase_oscillator_ensemble.cpp phase_oscillator_ensemble.cpp] + +[endsect] + +[section Using boost::units] + +[import ../examples/harmonic_oscillator_units.cpp] + +odeint also works well with __boost_units - a library for compile time unit +and dimension analysis. It works by decoding unit information into the types +of values. For a one-dimensional unit you can just use the Boost.Unit types as +state type, deriv type and time type and hand the `vector_space_algebra` to +the stepper definition and everything works just fine: + +``` +typedef units::quantity< si::time , double > time_type; +typedef units::quantity< si::length , double > length_type; +typedef units::quantity< si::velocity , double > velocity_type; + +typedef runge_kutta4< length_type , double , velocity_type , time_type , + vector_space_algebra > stepper_type; +``` + +If you want to solve more-dimensional problems the individual entries +typically have different units. That means that the `state_type` is now +possibly heterogeneous, meaning that every entry might have a different type. +To solve this problem, compile-time sequences from __boost_fusion can be used. + +To illustrate how odeint works with __boost_units we use the harmonic oscillator as primary example. We start with defining all quantities + +[units_define_basic_quantities] + +Note, that the `state_type` and the `deriv_type` are now a compile-time fusion +sequences. `deriv_type` represents ['x'] and is now different from the state +type as it has different unit definitions. Next, we define the ordinary +differential equation which is completely equivalent to the example in __tut_harmonic_oscillator: + +[units_define_ode] + +Next, we instantiate an appropriate stepper. We must explicitly parametrize +the stepper with the `state_type`, `deriv_type`, `time_type`. Furthermore, the +iteration over vector elements is now done by the `fusion_algebra` which must +also be given. For more on the state types / algebras see chapter __adapt_state_types. + +[units_define_stepper] + +It is quite easy but the compilation time might take very long. Furthermore, the observer is defined a bit different + +[units_observer] + +[caution Using __boost_units works nicely but compilation can be very time and +memory consuming. For example the unit test for the usage of __boost_units in odeint take up to 4 GB +of memory at compilation.] + +The full cpp file for this example can be found here [github_link libs/numeric/odeint/examples/harmonic_oscillator_units.cpp harmonic_oscillator_units.cpp]. + +[endsect] + +[section Using matrices as state types] + +[import ../examples/two_dimensional_phase_lattice.cpp] + +odeint works well with a variety of different state types. It is not restricted to pure vector-wise types, like `vector< double >`, `array< double , N >`, `fusion::vector< double , double >`, etc. but also works with types having a different topology then simple vectors. Here, we show how odeint can be used with matrices as states type, in the next section we will show how can be used to solve ODEs defined on complex networks. + +By default, odeint can be used with `ublas::matrix< T >` as state type for matrices. A simple example is a two-dimensional lattice of coupled phase oscillators. Other matrix types like `mtl::dense_matrix` or blitz arrays and matrices can used as well but need some kind of activation in order to work with odeint. This activation is described in following sections, + +The definition of the system is + +[two_dimensional_phase_lattice_definition] + +In principle this is all. Please note, that the above code is far from being optimal. Better performance can be achieved if every interaction is only calculated once and iterators for columns and rows are used. Below are some visualizations of the evolution of this lattice equation. + +[$phase_lattice_2d_0000.jpg] [$phase_lattice_2d_0100.jpg] [$phase_lattice_2d_1000.jpg] + +The full cpp for this example can be found here [github_link libs/numeric/odeint/examples/two_dimensional_phase_lattice.cpp two_dimensional_phase_lattice.cpp]. + +[endsect] + +[/ +[section Partial differential equations] +To be continued: +*Wave equation +*KdV +*Ginzburg-Landau +[endsect] +[section Ordinary differential equations on networks] +to be continued +[endsect] +] + +[section Using arbitrary precision floating point types] + +[import ../examples/gmpxx/lorenz_gmpxx.cpp] + +Besides the classical floating point number like `float`, `double`, `complex< double >` you can also use arbitrary precision types, like the types from [@http://gmplib.org/ gmp] and [@http://www.mpfr.org/ mpfr]. But you have to be careful about instantiating any numbers. + +For gmp types you have to set the default precision before any number is instantiated. This can be done by calling `mpf_set_default_prec( precision )` as the first function in your main program. Secondly, you can not use any global constant variables since they will not be set with the default precision you have already set. + +Here is a simple example: + +[gmpxx_lorenz] + +which can be integrated: + +[gmpxx_integration] + +[caution The full support of arbitrary precision types depends on the functionality they provide. For example, the types from gmp are lacking of functions for calculating the power and arbitrary roots, hence they can not be used with the controlled steppers. In detail, for full support the `min( x , y )`, `max( x , y )`, `pow( x , y )` must be callable.] + +The full example can be found at [github_link libs/numeric/odeint/examples/lorenz_gmpxx.cpp lorenz_gmpxx.cpp]. + + +[endsect] + +[section Self expanding lattices] + +[import ../examples/resizing_lattice.cpp] + +odeint supports changes of the state size during integration if a state_type +is used which can be resized, like `std::vector`. +The adjustment of the state's size has to be done from outside and the stepper +has to be instantiated with `always_resizer` as the template argument for the +`resizer_type`. +In this configuration, the stepper checks for changes in the state size and +adjust it's internal storage accordingly. + +We show this for a Hamiltonian system of nonlinear, disordered oscillators with nonlinear nearest neighbor coupling. + +The system function is implemented in terms of a class that also provides functions for calculating the energy. +Note, that this class stores the random potential internally which is not resized, but rather a start index is kept which should be changed whenever the states' size change. + +[resizing_lattice_system_class] + +The total size we allow is 1024 and we start with an initial state size of 60. + +[resizing_lattice_initialize] + +The lattice gets resized whenever the energy distribution comes close to the borders `distr[10] > 1E-150`, `distr[distr.size()-10] > 1E-150`. +If we increase to the left, `q` and `p` have to be rotated because their resize function always appends at the end. +Additionally, the start index of the potential changes in this case. + +[resizing_lattice_steps_loop] + +The `do_resize` function simply calls `vector.resize` of `q` , `p` and `distr`. + +[resizing_lattice_resize_function] + +The full example can be found in [github_link libs/numeric/odeint/examples/resizing_lattice.cpp resizing_lattice.cpp] + +[endsect] + +[/ [endsect] /] diff --git a/doc/tutorial_stiff_systems.qbk b/doc/tutorial_stiff_systems.qbk new file mode 100644 index 00000000..5416fb41 --- /dev/null +++ b/doc/tutorial_stiff_systems.qbk @@ -0,0 +1,61 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + + +[section Stiff systems] + +[import ../examples/stiff_system.cpp] + +An important class of ordinary differential equations are so called stiff +system which are characterized by two or more time scales of different +order. Examples of such systems are found in chemical systems where reaction +rates of individual sub-reaction might differ over large ranges, for example: + +['d S[subl 1] / dt = - 101 S[subl 2] - 100 S[subl 1]] + +['d S[subl 2] / dt = S[subl 1]] + + +In order to efficiently solve stiff systems numerically the Jacobian + +['J = d f[subl i] / d x[subl j]] + +is needed. Here is the definition of the above example + +[stiff_system_definition] + +The state type has to be a `ublas::vector` and the matrix type must by a +`ublas::matrix` since the stiff integrator only accepts these types. +However, you might want use non-stiff intgrators on this system, too - we will +do so later for demonstration. Therefore we want to use the same function also +with other state_types, realized by templatizing the `operator()`: + +[stiff_system_alternative_definition] + +Now you can use `stiff_system` in combination with `std::vector` or +`boost::array`. In the example the explicit time derivative of ['f(x,t)] is +introduced separately in the Jacobian. If ['df / dt = 0] simply fill `dfdt` with zeros. + +A well know solver for stiff systems is the Rosenbrock method. It has a step size control and dense output facilities and can be used like all the other steppers: + +[integrate_stiff_system] + +During the integration 71 steps have been done. Comparing to a classical Runge-Kutta solver this is a very good result. For example the Dormand-Prince 5 method with step size control and dense output yields 1531 steps. + +[integrate_stiff_system_alternative] + +Note, that we have used __boost_phoenix, a great functional programming library, to create and compose the observer. + +The full example can be found here: [github_link libs/numeric/odeint/examples/stiff_system.cpp stiff_system.cpp] + + +[endsect] diff --git a/doc/tutorial_thrust_cuda.qbk b/doc/tutorial_thrust_cuda.qbk new file mode 100644 index 00000000..a2e30686 --- /dev/null +++ b/doc/tutorial_thrust_cuda.qbk @@ -0,0 +1,165 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section Using CUDA (or OpenMP, TBB, ...) via Thrust] + +Modern graphic cards (graphic processing units - GPUs) can be used to speed up +the performance of time consuming algorithms by means of massive +parallelization. They are designed to execute many operations in +parallel. odeint can utilize the power of GPUs by means of CUDA and __thrust, +which is a STL-like interface for the native CUDA API. + +[important Thrust also supports parallelization using OpenMP and Intel Threading Building Blocks (TBB). You can switch +between CUDA, OpenMP and TBB parallelizations by a simple compiler +switch. Hence, this also provides an easy way to get basic OpenMP +parallelization into odeint. The examples discussed below are focued on GPU parallelization, though. ] + +To use odeint with CUDA a few points have to be taken into account. First of all, the problem has to be well chosen. It makes absolutely no sense to try to parallelize the code for a three dimensional system, it is simply too small and not worth the effort. One single function call (kernel execution) on the GPU is slow but you can do the operation on a huge set of data with only one call. We have experienced that the vector size over which is parallelized should be of the order of ['10[super 6]] to make full use of the GPU. Secondly, you have to use __thrust's algorithms and functors when implementing the rhs the ODE. This might be tricky since it involves some kind of functional programming knowledge. + +Typical applications for CUDA and odeint are large systems, like lattices or discretizations of PDE, and parameter studies. We introduce now three examples which show how the power of GPUs can be used in combination with odeint. + +[important The full power of CUDA is only available for really large systems where the number of coupled ordinary differential equations is of order ['N=10[super 6]] or larger. For smaller systems the CPU is usually much faster. You can also integrate an ensemble of different uncoupled ODEs in parallel as shown in the last example.] + +[section Phase oscillator ensemble] + +[import ../examples/thrust/phase_oscillator_ensemble.cu] + +The first example is the phase oscillator ensemble from the previous +section: + +[' d__phi[subl k] / dt = __omega[subl k] + __epsilon / N __Sigma[subl j] sin( __phi[subl j] - __phi[subl k] ).] + +It has a phase transition at ['__epsilon = 2] in the limit of +infinite numbers of oscillators ['N]. In the case of finite ['N] this +transition is smeared out but still clearly visible. + +__thrust and CUDA are perfectly suited for such kinds of problems where one needs a large number of particles (oscillators). We start by defining the state type which is a `thrust::device_vector`. The content of this vector lives on the GPU. If you are not familiar with this we recommend reading the ['Getting started] section on the __thrust website. + +[thrust_phase_ensemble_state_type] + +Thrust follows a functional programming approach. If you want to perform a calculation on the GPU you usually have to call a global function like `thrust::for_each`, `thrust::reduce`, ... with an appropriate local functor which performs the basic operation. An example is +`` +struct add_two +{ + template< class T > + __host__ __device__ + void operator()( T &t ) const + { + t += T( 2 ); + } +}; + +// ... + +thrust::for_each( x.begin() , x.end() , add_two() ); +`` +This code generically adds two to every element in the container `x`. + +For the purpose of integrating the phase oscillator ensemble we need + +* to calculate the system function, hence the r.h.s. of the ODE. +* this involves computing the mean field of the oscillator example, i.e. the values of ['R] and ['__theta] + +The mean field is calculated in a class `mean_field_calculator` + +[thrust_phase_ensemble_mean_field_calculator] + +Inside this class two member structures `sin_functor` and `cos_functor` are defined. They compute the sine and the cosine of a value and they are used within a transform iterator to calculate the sum of ['sin(__phi[subl k])] and ['cos(__phi[subl k])]. The classifiers `__host__` and `__device__` are CUDA specific and define a function or operator which can be executed on the GPU as well as on the CPU. The line + +[thrust_phase_ensemble_sin_sum] + +performs the calculation of this sine-sum on the GPU (or on the CPU, depending on your thrust configuration). + +The system function is defined via + +[thrust_phase_ensemble_sys_function] + +This class is used within the `do_step` and `integrate` method. It defines a member structure `sys_functor` for the r.h.s. of each individual oscillator and the `operator()` for the use in the steppers and integrators of odeint. The functor computes first the mean field of ['__phi[subl k]] and secondly calculates the whole r.h.s. of the ODE using this mean field. Note, how nicely `thrust::tuple` and `thrust::zip_iterator` play together. + +Now, we are ready to put everything together. All we have to do for making odeint ready for using the GPU is to parametrize the stepper with the appropriate thrust algebra/operations: + +[thrust_phase_ensemble_define_rk4] + +You can also use a controlled or dense output stepper, e.g. + +[thrust_phase_ensemble_define_dopri5] + +Then, it is straightforward to integrate the phase ensemble by creating an instance of the rhs class and using an integration function: + +[thrust_phase_ensemble_system_instance] +[thrust_phase_ensemble_integration] + +We have to use `boost::ref` here in order to pass the rhs class as reference and not by value. This ensures that the natural frequencies of each oscillator are not copied when calling `integrate_const`. In the full example the performance and results of the Runge-Kutta-4 and the Dopri5 solver are compared. + +The full example can be found at [github_link libs/numeric/odeint/examples/thrust/phase_oscillator_ensemble.cu phase_oscillator_example.cu]. + +[endsect] + +[section Large oscillator chains] + +[import ../examples/thrust/phase_oscillator_chain.cu] + +The next example is a large, one-dimensional chain of nearest-neighbor coupled phase oscillators with the following equations of motion: + +['d __phi[subl k] / dt = __omega[subl k] + sin( __phi[subl k+1] - __phi[subl k] ) + sin( __phi[subl k] - __phi[subl k-1])] + +In principle we can use all the techniques from the previous phase oscillator ensemble example, but we have to take special care about the coupling of the oscillators. To efficiently implement the coupling you can use a very elegant way employing Thrust's permutation iterator. A permutation iterator behaves like a normal iterator on a vector but it does not iterate along the usual order of the elements. +It rather iterates along some permutation of the elements defined by some index map. To realize the nearest neighbor coupling we create one permutation iterator which travels one step behind a usual iterator and another permutation iterator which travels one step in front. The full system class is: + +[thrust_phase_chain_system] + +Note, how easy you can obtain the value for the left and right neighboring oscillator in the system functor using the permutation iterators. But, the call of the `thrust::for_each` function looks relatively complicated. Every term of the r.h.s. of the ODE is resembled by one iterator packed in exactly the same way as it is unpacked in the functor above. + +Now we put everything together. We create random initial conditions and decreasing frequencies such that we should get synchronization. We copy the frequencies and the initial conditions onto the device and finally initialize and perform the integration. As result we simply write out the current state, hence the phase of each oscillator. + +[thrust_phase_chain_integration] + +The full example can be found at [github_link libs/numeric/odeint/examples/thrust/phase_oscillator_chain.cu phase_oscillator_chain.cu]. + +[endsect] + +[section Parameter studies] + +[import ../examples/thrust/lorenz_parameters.cu] + +Another important use case for __thrust and CUDA are parameter studies of relatively small systems. Consider for example the three-dimensional Lorenz system from the chaotic systems example in the previous section which has three parameters. If you want to study the behavior of this system for different parameters you usually have to integrate the system for many parameter values. Using thrust and odeint you can do this integration in parallel, hence you integrate a whole ensemble of Lorenz systems where each individual realization has a different parameter value. +[/ The Lorenz system is dissipative, such that you can assume that different initial conditions will lead to the same attractor so . For Hamiltonian systems this is not the case. Here it might be interesting to study a range of initial conditions to quantify different regions in the phase space.] + +In the following we will show how you can use __thrust to integrate the above mentioned ensemble of Lorenz systems. We will vary only the parameter ['__beta] but it is straightforward to vary other parameters or even two or all three parameters. Furthermore, we will use the largest Lyapunov exponent to quantify the behavior of the system (chaoticity). + +We start by defining the range of the parameters we want to study. The state_type is again a `thrust::device_vector< value_type >`. + +[thrust_lorenz_parameters_define_beta] + +The next thing we have to implement is the Lorenz system without perturbations. Later, a system with perturbations is also implemented in order to calculate the Lyapunov exponent. We will use an ansatz where each device function calculates one particular realization of the Lorenz ensemble + +[thrust_lorenz_parameters_define_simple_system] + +As `state_type` a `thrust::device_vector` or a __boost_range of a `device_vector` is used. The length of the state is ['3N] where ['N] is the number of systems. The system is encoded into this vector such that all ['x] components come first, then every ['y] components and finally every ['z] components. Implementing the device function is then a simple task, you only have to decompose the tuple originating from the zip iterators. + +Besides the system without perturbations we furthermore need to calculate the system including linearized equations governing the time evolution of small perturbations. Using the method from above this is straightforward, with a small difficulty that Thrust's tuples have a maximal arity of 10. But this is only a small problem since we can create a zip iterator packed with zip iterators. So the top level zip iterator contains one zip iterator for the state, one normal iterator for the parameter, and one zip iterator for the derivative. Accessing the elements of this tuple in the system function is then straightforward, you unpack the tuple with `thrust::get<>()`. We will not show the code here, it is to large. It can be found [github_link libs/numeric/odeint/examples/thrust/lorenz_parameters.cu here] and is easy to understand. + +Furthermore, we need an observer which determines the norm of the perturbations, normalizes them and averages the logarithm of the norm. The device functor which is used within this observer is defined + +[thrust_lorenz_parameters_observer_functor] + +Note, that this functor manipulates the state, i.e. the perturbations. + +Now we complete the whole code to calculate the Lyapunov exponents. First, we have to define a state vector. This vector contains ['6N] entries, the state ['x,y,z] and its perturbations ['dx,dy,dz]. We initialize them such that ['x=y=z=10], ['dx=1], and ['dy=dz=0]. We define a stepper type, a controlled Runge-Kutta Dormand-Prince 5 stepper. We start with some integration to overcome the transient behavior. For this, we do not involve the perturbation and run the algorithm only on the state ['x,y,z] without any observer. Note, how __boost_range is used for partial integration of the state vector without perturbations (the first half of the whole state). After the transient, the full system with perturbations is integrated and the Lyapunov exponents are calculated and written to `stdout`. + +[thrust_lorenz_parameters_integration] + +The full example can be found at [github_link libs/numeric/odeint/examples/thrust/lorenz_parameters.cu lorenz_parameters.cu]. + +[endsect] + +[endsect] diff --git a/doc/tutorial_vexcl_opencl.qbk b/doc/tutorial_vexcl_opencl.qbk new file mode 100644 index 00000000..082eba4f --- /dev/null +++ b/doc/tutorial_vexcl_opencl.qbk @@ -0,0 +1,46 @@ +[/============================================================================ + Boost.odeint + + Copyright (c) 2009-2012 Karsten Ahnert + Copyright (c) 2009-2012 Mario Mulansky + + Use, modification and distribution is subject to the Boost Software License, + Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at + http://www.boost.org/LICENSE_1_0.txt) +=============================================================================/] + + +[section Using OpenCL via VexCL] + +[import ../examples/vexcl/lorenz_ensemble.cpp] + +In the previous section the usage of odeint in combination with __thrust was shown. In this section we show how one can use OpenCL with odeint. The point of odeint is not to implement its own low-level data structures and algorithms, but to use high level libraries doing this task. Here, we will use the __vexcl framework to use OpenCL. __vexcl is a nice library for general computations and it uses heavily expression templates. With the help of __vexcl it is possible to write very compact and expressive application. + +[note vexcl needs C++11 features! So you have to compile with C++11 support enabled.] + +To use __vexcl one needs to include one additional header which includes the data-types and algorithms from vexcl and the adaption to odeint. Adaption to odeint means here only to adapt the resizing functionality of __vexcl to odeint. + +[vexcl_includes] + +To demonstrate the use of __vexcl we integrate an ensemble of Lorenz system. The example is very similar to the parameter study of the Lorenz system in the previous section except that we do not compute the Lyapunov exponents. Again, we vary the parameter R of the Lorenz system an solve a whole ensemble of Lorenz systems in parallel (each with a different parameter R). First, we define the state type and a vector type + +[vexcl_state_types ] + +The `vector_type` is used to represent the parameter R. The `state_type` is a multi-vector of three sub vectors and is used to represent. The first component of this multi-vector represent all `x` components of the Lorenz system, while the second all `y` components and the third all `z` components. The components of this vector can be obtained via + +`` +auto &x = X(0); +auto &y = X(1); +auto &z = X(2); +`` + +As already mentioned __vexcl supports expression templates and we will use them to implement the system function for the Lorenz ensemble: + +[vexcl_system] + +It's very easy, isn't it? These three little lines do all the computations for you. There is no need to write your own OpenCL kernels. __vexcl does everything for you. Next we have to write the main application. We initialize the vector of parameters (R) and the initial state. Since __vexcl supports odeint we can already use the `vector_space_algebra` in combination with the `default_operations` for the stepper and we are done: + +[vexcl_main] + + +[endsect] diff --git a/examples/2d_lattice/Jamfile.v2 b/examples/2d_lattice/Jamfile.v2 new file mode 100644 index 00000000..f52381d7 --- /dev/null +++ b/examples/2d_lattice/Jamfile.v2 @@ -0,0 +1,12 @@ +# Copyright 2011 Karsten Ahnert and Mario Mulansky. +# Distributed under the Boost Software License, Version 1.0. (See +# accompanying file LICENSE_1_0.txt or copy at +# http://www.boost.org/LICENSE_1_0.txt) + +project + : requirements + ../../../../.. + BOOST_ALL_NO_LIB=1 + ; + +exe spreading : spreading.cpp ; \ No newline at end of file diff --git a/examples/2d_lattice/lattice2d.hpp b/examples/2d_lattice/lattice2d.hpp new file mode 100644 index 00000000..13b703d8 --- /dev/null +++ b/examples/2d_lattice/lattice2d.hpp @@ -0,0 +1,165 @@ +/* + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +/* stronlgy nonlinear hamiltonian lattice in 2d */ + +#ifndef LATTICE2D_HPP +#define LATTICE2D_HPP + +#include + +#include + +using boost::math::pow; + +template< int Kappa , int Lambda > +struct lattice2d { + + const double m_beta; + std::vector< std::vector< double > > m_omega; + + lattice2d( const double beta ) + : m_beta( beta ) + { } + + template< class StateIn , class StateOut > + void operator()( const StateIn &q , StateOut &dpdt ) + { + // q and dpdt are 2d + const int N = q.size(); + + int i; + for( i = 0 ; i < N ; ++i ) + { + const int i_l = (i-1+N) % N; + const int i_r = (i+1) % N; + for( int j = 0 ; j < N ; ++j ) + { + const int j_l = (j-1+N) % N; + const int j_r = (j+1) % N; + dpdt[i][j] = - m_omega[i][j] * pow( q[i][j] ) + - m_beta * pow( q[i][j] - q[i][j_l] ) + - m_beta * pow( q[i][j] - q[i][j_r] ) + - m_beta * pow( q[i][j] - q[i_l][j] ) + - m_beta * pow( q[i][j] - q[i_r][j] ); + } + } + } + + template< class StateIn > + double energy( const StateIn &q , const StateIn &p ) + { + // q and dpdt are 2d + const int N = q.size(); + double energy = 0.0; + int i; + for( i = 0 ; i < N ; ++i ) + { + const int i_l = (i-1+N) % N; + const int i_r = (i+1) % N; + for( int j = 0 ; j < N ; ++j ) + { + const int j_l = (j-1+N) % N; + const int j_r = (j+1) % N; + energy += p[i][j]*p[i][j] / 2.0 + + m_omega[i][j] * pow( q[i][j] ) / Kappa + + m_beta * pow( q[i][j] - q[i][j_l] ) / Lambda / 2 + + m_beta * pow( q[i][j] - q[i][j_r] ) / Lambda / 2 + + m_beta * pow( q[i][j] - q[i_l][j] ) / Lambda / 2 + + m_beta * pow( q[i][j] - q[i_r][j] ) / Lambda / 2; + } + } + return energy; + } + + + template< class StateIn , class StateOut > + double local_energy( const StateIn &q , const StateIn &p , StateOut &energy ) + { + // q and dpdt are 2d + const int N = q.size(); + double e = 0.0; + int i; + for( i = 0 ; i < N ; ++i ) + { + const int i_l = (i-1+N) % N; + const int i_r = (i+1) % N; + for( int j = 0 ; j < N ; ++j ) + { + const int j_l = (j-1+N) % N; + const int j_r = (j+1) % N; + energy[i][j] = p[i][j]*p[i][j] / 2.0 + + m_omega[i][j] * pow( q[i][j] ) / Kappa + + m_beta * pow( q[i][j] - q[i][j_l] ) / Lambda / 2 + + m_beta * pow( q[i][j] - q[i][j_r] ) / Lambda / 2 + + m_beta * pow( q[i][j] - q[i_l][j] ) / Lambda / 2 + + m_beta * pow( q[i][j] - q[i_r][j] ) / Lambda / 2; + e += energy[i][j]; + } + } + //rescale + e = 1.0/e; + for( i = 0 ; i < N ; ++i ) + for( int j = 0 ; j < N ; ++j ) + energy[i][j] *= e; + return 1.0/e; + } + + void load_pot( const char* filename , const double W , const double gap , + const size_t dim ) + { + std::ifstream in( filename , std::ios::in | std::ios::binary ); + if( !in.is_open() ) { + std::cerr << "pot file not found: " << filename << std::endl; + exit(0); + } else { + std::cout << "using pot file: " << filename << std::endl; + } + + m_omega.resize( dim ); + for( int i = 0 ; i < dim ; ++i ) + { + m_omega[i].resize( dim ); + for( size_t j = 0 ; j < dim ; ++j ) + { + if( !in.good() ) + { + std::cerr << "I/O Error: " << filename << std::endl; + exit(0); + } + double d; + in.read( (char*) &d , sizeof(d) ); + if( (d < 0) || (d > 1.0) ) + { + std::cerr << "ERROR: " << d << std::endl; + exit(0); + } + m_omega[i][j] = W*d + gap; + } + } + + } + + void generate_pot( const double W , const double gap , const size_t dim ) + { + m_omega.resize( dim ); + for( size_t i = 0 ; i < dim ; ++i ) + { + m_omega[i].resize( dim ); + for( size_t j = 0 ; j < dim ; ++j ) + { + m_omega[i][j] = W*static_cast(rand())/RAND_MAX + gap; + } + } + } + +}; + +#endif diff --git a/examples/2d_lattice/nested_range_algebra.hpp b/examples/2d_lattice/nested_range_algebra.hpp new file mode 100644 index 00000000..27eec124 --- /dev/null +++ b/examples/2d_lattice/nested_range_algebra.hpp @@ -0,0 +1,46 @@ +/* + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +/* nested range algebra */ + +#ifndef NESTED_RANGE_ALGEBRA +#define NESTED_RANGE_ALGEBRA + +namespace detail { + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Operation , class Algebra > + void for_each3( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, Operation op , Algebra &algebra ) +{ + for( ; first1 != last1 ; ) + algebra.for_each3( *first1++ , *first2++ , *first3++ , op ); +} +} + + +template< class InnerAlgebra > +struct nested_range_algebra +{ + + nested_range_algebra() + : m_inner_algebra() + { } + + template< class S1 , class S2 , class S3 , class Op > + void for_each3( S1 &s1 , S2 &s2 , S3 &s3 , Op op ) + { + detail::for_each3( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , op , m_inner_algebra ); + } + + +private: + InnerAlgebra m_inner_algebra; +}; + +#endif diff --git a/examples/2d_lattice/spreading.cpp b/examples/2d_lattice/spreading.cpp new file mode 100644 index 00000000..7e0db2f1 --- /dev/null +++ b/examples/2d_lattice/spreading.cpp @@ -0,0 +1,122 @@ +/* + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +/* + * Example of a 2D simulation of nonlinearly coupled oscillators. + * Program just prints final energy which should be close to the initial energy (1.0). + * No parallelization is employed here. + * Run time on a 2.3GHz Intel Core-i5: about 10 seconds for 100 steps. + * Compile simply via bjam or directly: + * g++ -O3 -I${BOOST_ROOT} -I../../../../.. spreading.cpp + */ + + +#include +#include +#include +#include +#include + +#include +#include + +// we use a vector< vector< double > > as state type, +// for that some functionality has to be added for odeint to work +#include "nested_range_algebra.hpp" +#include "vector_vector_resize.hpp" + +// defines the rhs of our dynamical equation +#include "lattice2d.hpp" +/* dynamical equations (Hamiltonian structure): +dqdt_{i,j} = p_{i,j} +dpdt_{i,j} = - omega_{i,j}*q_{i,j} - \beta*[ (q_{i,j} - q_{i,j-1})^3 + +(q_{i,j} - q_{i,j+1})^3 + +(q_{i,j} - q_{i-1,j})^3 + +(q_{i,j} - q_{i+1,j})^3 ] +*/ + + +using namespace std; + +static const int MAX_N = 1024;//2048; + +static const size_t KAPPA = 2; +static const size_t LAMBDA = 4; +static const double W = 1.0; +static const double gap = 0.0; +static const size_t steps = 100; +static const double dt = 0.1; + +double initial_e = 1.0; +double beta = 1.0; +int realization_index = 0; + +//the state type +typedef vector< vector< double > > state_type; + +//the stepper, choose a symplectic one to account for hamiltonian structure +//use nested_range_algebra for calculations on vector< vector< ... > > +typedef boost::numeric::odeint::symplectic_rkn_sb3a_mclachlan< + state_type , state_type , double , state_type , state_type , double , + nested_range_algebra< boost::numeric::odeint::range_algebra > , + boost::numeric::odeint::default_operations > stepper_type; + +double time_diff_in_ms( timeval &t1 , timeval &t2 ) +{ return (t2.tv_sec - t1.tv_sec)*1000.0 + (t2.tv_usec - t1.tv_usec)/1000.0 + 0.5; } + + +int main( int argc, const char* argv[] ) { + + srand( time(NULL) ); + + lattice2d< KAPPA , LAMBDA > lattice( beta ); + + + lattice.generate_pot( W , gap , MAX_N ); + + state_type q( MAX_N , vector< double >( MAX_N , 0.0 ) ); + + state_type p( q ); + + state_type energy( q ); + + p[MAX_N/2][MAX_N/2] = sqrt( 0.5*initial_e ); + p[MAX_N/2+1][MAX_N/2] = sqrt( 0.5*initial_e ); + p[MAX_N/2][MAX_N/2+1] = sqrt( 0.5*initial_e ); + p[MAX_N/2+1][MAX_N/2+1] = sqrt( 0.5*initial_e ); + + cout.precision(10); + + lattice.local_energy( q , p , energy ); + double e=0.0; + for( size_t i=0 ; i + +#include + +namespace boost { namespace numeric { namespace odeint { + +template<> +struct is_resizeable< std::vector< std::vector< double > > > +{ + typedef boost::true_type type; + const static bool value = type::value; +}; + +template<> +struct same_size_impl< std::vector< std::vector< double > > , std::vector< std::vector< double > > > +{ + typedef std::vector< std::vector< double > > state_type; + + static bool same_size( const state_type &x1 , + const state_type &x2 ) + { + bool same = ( boost::size( x1 ) == boost::size( x2 ) ); + if( !same ) + return false; + typename state_type::const_iterator begin1 = boost::begin( x1 ); + typename state_type::const_iterator begin2 = boost::begin( x2 ); + while( begin1 != boost::end( x1 ) ) + same &= ( boost::size( *begin1++ ) == boost::size( *begin2++ ) ); + return same; + } +}; + +template<> +struct resize_impl< std::vector< std::vector< double > > , std::vector< std::vector< double > > > +{ + typedef std::vector< std::vector< double > > state_type; + + static void resize( state_type &x1 , const state_type &x2 ) + { + x1.resize( boost::size( x2 ) ); + typename state_type::iterator begin1 = boost::begin( x1 ); + typename state_type::const_iterator begin2 = boost::begin( x2 ); + while( begin1 != boost::end( x1 ) ) + (*begin1++).resize( boost::size( *begin2++ ) ); + } +}; + +template<> +struct state_wrapper< std::vector< std::vector< double > > > +{ + typedef std::vector< std::vector< double > > state_type; + typedef state_wrapper< state_type > state_wrapper_type; + typedef boost::true_type is_resizeable; + + state_type m_v; + + template< class State > + bool same_size( const State &x ) + { + bool same = ( boost::size( m_v ) == boost::size( x ) ); + if( !same ) + return false; + typename state_type::iterator begin1 = boost::begin( m_v ); + typename State::const_iterator begin2 = boost::begin( x ); + while( begin1 != boost::end( m_v ) ) + same &= ( boost::size( *begin1++ ) == boost::size( *begin2++ ) ); + return same; + } + + template< class State > + bool resize( const State &x ) + { + if( !same_size( x ) ) + { + m_v.resize( boost::size( x ) ); + typename state_type::iterator begin1 = boost::begin( m_v ); + typename State::const_iterator begin2 = boost::begin( x ); + while( begin1 != boost::end( m_v ) ) + (*begin1++).resize( boost::size( *begin2++ ) ); + + return true; + } else + return false; + } + +}; + +} } } + +#endif diff --git a/examples/Jamfile.v2 b/examples/Jamfile.v2 new file mode 100644 index 00000000..946faa0e --- /dev/null +++ b/examples/Jamfile.v2 @@ -0,0 +1,43 @@ +# Copyright 2009 Karsten Ahnert and Mario Mulansky. +# Distributed under the Boost Software License, Version 1.0. (See +# accompanying file LICENSE_1_0.txt or copy at +# http://www.boost.org/LICENSE_1_0.txt) + + +project + : requirements + ../../../.. + BOOST_ALL_NO_LIB=1 + : + ; + + +exe harmonic_oscillator : harmonic_oscillator.cpp ; +exe solar_system : solar_system.cpp ; +exe chaotic_system : chaotic_system.cpp ; +exe stiff_system : stiff_system.cpp ; +exe fpu : fpu.cpp ; +exe phase_oscillator_ensemble : phase_oscillator_ensemble.cpp ; +exe harmonic_oscillator_units : harmonic_oscillator_units.cpp ; +exe stuart_landau : stuart_landau.cpp ; +exe two_dimensional_phase_lattice : two_dimensional_phase_lattice.cpp ; +exe bulirsch_stoer : bulirsch_stoer.cpp ; +exe elliptic_functions : elliptic_functions.cpp ; +exe resizing_lattice : resizing_lattice.cpp ; +exe list_lattice : list_lattice.cpp ; +exe stepper_details : stepper_details.cpp ; +exe my_vector : my_vector.cpp ; +exe lorenz_point : lorenz_point.cpp ; +exe van_der_pol_stiff : van_der_pol_stiff.cpp ; +exe simple1d : simple1d.cpp ; +exe stochastic_euler : stochastic_euler.cpp ; +exe generation_functions : generation_functions.cpp ; +exe heun : heun.cpp ; +exe const_step_iterator : const_step_iterator.cpp : -std=c++0x ; +exe adaptive_iterator : adaptive_iterator.cpp : -std=c++0x ; +exe bind_member_functions : bind_member_functions.cpp ; +exe bind_member_functions_cpp11 : bind_member_functions_cpp11.cpp : -std=c++0x ; + +# build-project mtl ; +# build-project ublas ; +# build-project gmpxx ; diff --git a/examples/adaptive_iterator.cpp b/examples/adaptive_iterator.cpp new file mode 100644 index 00000000..4ba61aa1 --- /dev/null +++ b/examples/adaptive_iterator.cpp @@ -0,0 +1,361 @@ +/* + * adaptive_iterator.cpp + * + * Copyright 2009-2012 Karsten Ahnert + * Copyright 2009-2012 Mario Mulansky + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + + +#include +#include +#include +#include +#include + +#include + +#include +#include +#include + +#include +#include +#include +#include + +#include +#include + +#define tab "\t" + +using namespace std; +using namespace boost::numeric::odeint; + +const double sigma = 10.0; +const double R = 28.0; +const double b = 8.0 / 3.0; + +struct lorenz +{ + template< class State , class Deriv > + void operator()( const State &x , Deriv &dxdt , double t ) const + { + dxdt[0] = sigma * ( x[1] - x[0] ); + dxdt[1] = R * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -b * x[2] + x[0] * x[1]; + } +}; + +#include + +int main( int argc , char **argv ) +{ + typedef boost::array< double , 3 > state_type; + + /* + * Controlled steppers with time iterator + */ + + // std::for_each + { + auto stepper = make_controlled( 1.0e-6 , 1.0e-6 , runge_kutta_cash_karp54< state_type >() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + std::for_each( make_adaptive_time_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_adaptive_time_iterator_end( stepper , lorenz() , x ) , + []( const std::pair< state_type&, double > &x ) { + std::cout << x.second << tab << x.first[0] << tab << x.first[1] << tab << x.first[2] << "\n"; } ); + } + + // std::copy_if + { + std::vector< pair< state_type , double > > res; + auto stepper = make_controlled( 1.0e-6 , 1.0e-6 , runge_kutta_cash_karp54< state_type >() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + std::copy_if( make_adaptive_time_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_adaptive_time_iterator_end( stepper , lorenz() , x ) , + std::back_inserter( res ) , + []( const pair< state_type& , double > &x ) { + return ( x.first[0] > 0.0 ) ? true : false; } ); + for( size_t i=0 ; i() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + double res = std::accumulate( make_adaptive_time_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_adaptive_time_iterator_end( stepper , lorenz() , x ) , + 0.0 , + []( double sum , const pair< state_type& , double > &x ) { + return sum + x.first[0]; } ); + cout << res << endl; + } + + + // std::transform + { + auto stepper = make_controlled( 1.0e-6 , 1.0e-6 , runge_kutta_cash_karp54< state_type >() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + vector< double > weights; + std::transform( make_adaptive_time_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_adaptive_time_iterator_end( stepper , lorenz() , x ) , + back_inserter( weights ) , + []( const pair< state_type& , double > &x ) { + return sqrt( x.first[0] * x.first[0] + x.first[1] * x.first[1] + x.first[2] * x.first[2] ); } ); + for( size_t i=0 ; i() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + boost::range::for_each( make_adaptive_time_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + []( const std::pair< state_type& , double > &x ) { + std::cout << x.second << tab << x.first[0] << tab << x.first[1] << tab << x.first[2] << "\n"; } ); + } + + + // boost::range::copy with filtered adaptor (simulating std::copy_if) + { + auto stepper = make_controlled( 1.0e-6 , 1.0e-6 , runge_kutta_cash_karp54< state_type >() ); + std::vector< std::pair< state_type , double > > res; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + boost::range::copy( make_adaptive_time_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) | + boost::adaptors::filtered( [] ( const pair< state_type& , double > &x ) { return ( x.first[0] > 0.0 ); } ) , + std::back_inserter( res ) ); + for( size_t i=0 ; i() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + double res = boost::accumulate( make_adaptive_time_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , 0.0 , + []( double sum , const pair< state_type& , double > &x ) { + return sum + x.first[0]; } ); + cout << res << endl; + //] + } + + + // boost::range::transform + { + auto stepper = make_controlled( 1.0e-6 , 1.0e-6 , runge_kutta_cash_karp54< state_type >() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + vector< double > weights; + boost::transform( make_adaptive_time_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , back_inserter( weights ) , + []( const pair< state_type& , double > &x ) { + return sqrt( x.first[0] * x.first[0] + x.first[1] * x.first[1] + x.first[2] * x.first[2] ); } ); + for( size_t i=0 ; i() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + auto iter = boost::find_if( make_adaptive_time_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + []( const std::pair< state_type & , double > &x ) { + return ( x.first[0] < 0.0 ); } ); + cout << iter->second << "\t" << iter->first[0] << "\t" << iter->first[1] << "\t" << iter->first[2] << "\n"; + } + + + + + + + + + + + + + // /* + // * Boost.Range versions for dense output steppers + // */ + + // // boost::range::for_each + // { + // runge_kutta_dopri5< state_type > stepper; + // state_type x = {{ 10.0 , 10.0 , 10.0 }}; + // boost::range::for_each( make_adaptive_range( make_dense_output( 1.0e-6 , 1.0e-6 , stepper ) , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + // []( const state_type &x ) { + // std::cout << x[0] << tab << x[1] << tab << x[2] << "\n"; } ); + // } + + + // // boost::range::for_each with time iterator + // { + // runge_kutta_dopri5< state_type > stepper; + // state_type x = {{ 10.0 , 10.0 , 10.0 }}; + // boost::range::for_each( make_adaptive_time_range( make_dense_output( 1.0e-6 , 1.0e-6 , stepper ) , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + // []( const std::pair< state_type& , double > &x ) { + // std::cout << x.second << tab << x.first[0] << tab << x.first[1] << tab << x.first[2] << "\n"; } ); + + // } + + + + + + /* + * Pure iterators for controlled stepper without time iterator + */ + + // std::for_each + { + auto stepper = make_controlled( 1.0e-6 , 1.0e-6 , runge_kutta_cash_karp54< state_type >() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + std::for_each( make_adaptive_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_adaptive_iterator_end( stepper , lorenz() , x ) , + []( const state_type& x ) { + std::cout << x[0] << tab << x[1] << tab << x[2] << "\n"; } ); + } + + // std::copy_if + { + std::vector< state_type > res; + auto stepper = make_controlled( 1.0e-6 , 1.0e-6 , runge_kutta_cash_karp54< state_type >() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + std::copy_if( make_adaptive_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_adaptive_iterator_end( stepper , lorenz() , x ) , + std::back_inserter( res ) , + []( const state_type& x ) { + return ( x[0] > 0.0 ) ? true : false; } ); + for( size_t i=0 ; i() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + double res = std::accumulate( make_adaptive_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_adaptive_iterator_end( stepper , lorenz() , x ) , + 0.0 , + []( double sum , const state_type& x ) { + return sum + x[0]; } ); + cout << res << endl; + } + + + // std::transform + { + auto stepper = make_controlled( 1.0e-6 , 1.0e-6 , runge_kutta_cash_karp54< state_type >() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + vector< double > weights; + std::transform( make_adaptive_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_adaptive_iterator_end( stepper , lorenz() , x ) , + back_inserter( weights ) , + []( const state_type& x ) { + return sqrt( x[0] * x[0] + x[1] * x[1] + x[2] * x[2] ); } ); + for( size_t i=0 ; i() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + boost::range::for_each( make_adaptive_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + []( const state_type &x ) { + std::cout << x[0] << tab << x[1] << tab << x[2] << "\n"; } ); + } + + + // boost::range::copy with filtered adaptor (simulating std::copy_if) + { + auto stepper = make_controlled( 1.0e-6 , 1.0e-6 , runge_kutta_cash_karp54< state_type >() ); + std::vector< state_type > res; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + boost::range::copy( make_adaptive_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) | + boost::adaptors::filtered( [] ( const state_type& x ) { return ( x[0] > 0.0 ); } ) , + std::back_inserter( res ) ); + for( size_t i=0 ; i() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + double res = boost::accumulate( make_adaptive_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , 0.0 , + []( double sum , const state_type& x ) { + return sum + x[0]; } ); + cout << res << endl; + //] + } + + + // boost::range::transform + { + auto stepper = make_controlled( 1.0e-6 , 1.0e-6 , runge_kutta_cash_karp54< state_type >() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + vector< double > weights; + boost::transform( make_adaptive_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , back_inserter( weights ) , + []( const state_type& x ) { + return sqrt( x[0] * x[0] + x[1] * x[1] + x[2] * x[2] ); } ); + for( size_t i=0 ; i() ); + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + auto iter = boost::find_if( make_adaptive_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + []( const state_type &x ) { + return ( x[0] < 0.0 ); } ); + cout << (*iter)[0] << "\t" << (*iter)[1] << "\t" << (*iter)[2] << "\n"; + } + + + + + + return 0; +} diff --git a/examples/bind_member_functions.cpp b/examples/bind_member_functions.cpp new file mode 100644 index 00000000..8eb5a689 --- /dev/null +++ b/examples/bind_member_functions.cpp @@ -0,0 +1,126 @@ +/* + [auto_generated] + libs/numeric/odeint/examples/bind_member_functions.hpp + + [begin_description] + tba. + [end_description] + + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#include + +#include + +namespace odeint = boost::numeric::odeint; + +typedef boost::array< double , 3 > state_type; + +//[ ode_wrapper +template< class Obj , class Mem > +class ode_wrapper +{ + Obj m_obj; + Mem m_mem; + +public: + + ode_wrapper( Obj obj , Mem mem ) : m_obj( obj ) , m_mem( mem ) { } + + template< class State , class Deriv , class Time > + void operator()( const State &x , Deriv &dxdt , Time t ) + { + (m_obj.*m_mem)( x , dxdt , t ); + } +}; + +template< class Obj , class Mem > +ode_wrapper< Obj , Mem > make_ode_wrapper( Obj obj , Mem mem ) +{ + return ode_wrapper< Obj , Mem >( obj , mem ); +} +//] + + +template< class Obj , class Mem > +class observer_wrapper +{ + Obj m_obj; + Mem m_mem; + +public: + + observer_wrapper( Obj obj , Mem mem ) : m_obj( obj ) , m_mem( mem ) { } + + template< class State , class Time > + void operator()( const State &x , Time t ) + { + (m_obj.*m_mem)( x , t ); + } +}; + +template< class Obj , class Mem > +observer_wrapper< Obj , Mem > make_observer_wrapper( Obj obj , Mem mem ) +{ + return observer_wrapper< Obj , Mem >( obj , mem ); +} + + + +//[ bind_member_function +struct lorenz +{ + void ode( const state_type &x , state_type &dxdt , double t ) const + { + dxdt[0] = 10.0 * ( x[1] - x[0] ); + dxdt[1] = 28.0 * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -8.0 / 3.0 * x[2] + x[0] * x[1]; + } +}; + +int main( int argc , char *argv[] ) +{ + using namespace boost::numeric::odeint; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + integrate_const( runge_kutta4< state_type >() , make_ode_wrapper( lorenz() , &lorenz::ode ) , + x , 0.0 , 10.0 , 0.01 ); + return 0; +} +//] + + +/* +struct lorenz +{ + void ode( const state_type &x , state_type &dxdt , double t ) const + { + dxdt[0] = 10.0 * ( x[1] - x[0] ); + dxdt[1] = 28.0 * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -8.0 / 3.0 * x[2] + x[0] * x[1]; + } + + void obs( const state_type &x , double t ) const + { + std::cout << t << " " << x[0] << " " << x[1] << " " << x[2] << "\n"; + } +}; + +int main( int argc , char *argv[] ) +{ + using namespace boost::numeric::odeint; + + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + integrate_const( runge_kutta4< state_type >() , + make_ode_wrapper( lorenz() , &lorenz::ode ) , + x , 0.0 , 10.0 , 0.01 , + make_observer_wrapper( lorenz() , &lorenz::obs ) ); + + return 0; +} +*/ diff --git a/examples/bind_member_functions_cpp11.cpp b/examples/bind_member_functions_cpp11.cpp new file mode 100644 index 00000000..de018854 --- /dev/null +++ b/examples/bind_member_functions_cpp11.cpp @@ -0,0 +1,56 @@ +/* + [auto_generated] + libs/numeric/odeint/examples/bind_member_functions.hpp + + [begin_description] + tba. + [end_description] + + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#include +#include +#include + +#include + +namespace odeint = boost::numeric::odeint; + + + +typedef std::array< double , 3 > state_type; + +struct lorenz +{ + void ode( const state_type &x , state_type &dxdt , double t ) const + { + const double sigma = 10.0; + const double R = 28.0; + const double b = 8.0 / 3.0; + + dxdt[0] = sigma * ( x[1] - x[0] ); + dxdt[1] = R * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -b * x[2] + x[0] * x[1]; + } +}; + +int main( int argc , char *argv[] ) +{ + using namespace boost::numeric::odeint; + //[ bind_member_function_cpp11 + namespace pl = std::placeholders; + + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + integrate_const( runge_kutta4< state_type >() , + std::bind( &lorenz::ode , lorenz() , pl::_1 , pl::_2 , pl::_3 ) , + x , 0.0 , 10.0 , 0.01 ); + //] + return 0; +} + diff --git a/examples/bulirsch_stoer.cpp b/examples/bulirsch_stoer.cpp new file mode 100644 index 00000000..97064dbf --- /dev/null +++ b/examples/bulirsch_stoer.cpp @@ -0,0 +1,100 @@ +/* + * bulirsch_stoer.cpp + * + * Copyright 2009-2012 Karsten Ahnert + * Copyright 2009-2012 Mario Mulansky + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#include +#include +#define _USE_MATH_DEFINES +#include + +#include +#include + +#include + +#include +#include +#include + +using namespace std; +using namespace boost::numeric::odeint; + +typedef boost::array< double , 1 > state_type; + +/* + * x' = ( - x*sin t + 2 tan x ) y + * with x( pi/6 ) = 2/sqrt(3) the analytic solution is 1/cos t + */ + +void rhs( const state_type &x , state_type &dxdt , const double t ) +{ + dxdt[0] = ( - x[0] * sin( t ) + 2.0 * tan( t ) ) * x[0]; +} + +void rhs2( const state_type &x , state_type &dxdt , const double t ) +{ + dxdt[0] = sin(t); +} + + +ofstream out; + +void write_out( const state_type &x , const double t ) +{ + out << t << '\t' << x[0] << endl; +} + +int main() +{ + bulirsch_stoer_dense_out< state_type > stepper( 1E-8 , 0.0 , 0.0 , 0.0 ); + bulirsch_stoer< state_type > stepper2( 1E-8 , 0.0 , 0.0 , 0.0 ); + + state_type x = {{ 2.0 / sqrt(3.0) }}; + + double t = M_PI/6.0; + //double t = 0.0; + double dt = 0.01; + double t_end = M_PI/2.0 - 0.1; + //double t_end = 100.0; + + out.open( "bs.dat" ); + out.precision(16); + integrate_const( stepper , rhs , x , t , t_end , dt , write_out ); + out.close(); + + x[0] = 2.0 / sqrt(3.0); + + out.open( "bs2.dat" ); + out.precision(16); + integrate_adaptive( stepper , rhs , x , t , t_end , dt , write_out ); + out.close(); + + x[0] = 2.0 / sqrt(3.0); + + out.open( "bs3.dat" ); + out.precision(16); + integrate_adaptive( stepper2 , rhs , x , t , t_end , dt , write_out ); + out.close(); + + + typedef runge_kutta_dopri5< state_type > dopri5_type; + typedef controlled_runge_kutta< dopri5_type > controlled_dopri5_type; + typedef dense_output_runge_kutta< controlled_dopri5_type > dense_output_dopri5_type; + + dense_output_dopri5_type dopri5( controlled_dopri5_type( default_error_checker< double >( 1E-2 , 0.0 , 0.0 , 0.0 ) ) ); + + x[0] = 2.0 / sqrt(3.0); + + out.open( "bs4.dat" ); + out.precision(16); + integrate_adaptive( dopri5 , rhs , x , t , t_end , dt , write_out ); + out.close(); + +} diff --git a/examples/chaotic_system.cpp b/examples/chaotic_system.cpp new file mode 100644 index 00000000..762317c8 --- /dev/null +++ b/examples/chaotic_system.cpp @@ -0,0 +1,117 @@ +/* + * chaotic_system.cpp + * + * This example demonstrates how one can use odeint to determine the Lyapunov + * exponents of a chaotic system namely the well known Lorenz system. Furthermore, + * it shows how odeint interacts with boost.range. + * + * Copyright 2009-2012 Karsten Ahnert + * Copyright 2009-2012 Mario Mulansky + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#include +#include + +#include + +#include "gram_schmidt.hpp" + +using namespace std; +using namespace boost::numeric::odeint; + + +const double sigma = 10.0; +const double R = 28.0; +const double b = 8.0 / 3.0; + +//[ system_function_without_perturbations +struct lorenz +{ + template< class State , class Deriv > + void operator()( const State &x_ , Deriv &dxdt_ , double t ) const + { + typename boost::range_iterator< const State >::type x = boost::begin( x_ ); + typename boost::range_iterator< Deriv >::type dxdt = boost::begin( dxdt_ ); + + dxdt[0] = sigma * ( x[1] - x[0] ); + dxdt[1] = R * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -b * x[2] + x[0] * x[1]; + } +}; +//] + + + +//[ system_function_with_perturbations +const size_t n = 3; +const size_t num_of_lyap = 3; +const size_t N = n + n*num_of_lyap; + +typedef boost::array< double , N > state_type; +typedef boost::array< double , num_of_lyap > lyap_type; + +void lorenz_with_lyap( const state_type &x , state_type &dxdt , double t ) +{ + lorenz()( x , dxdt , t ); + + for( size_t l=0 ; l rk4; + + fill( x.begin() , x.end() , 0.0 ); + x[0] = 10.0 ; x[1] = 10.0 ; x[2] = 5.0; + + const double dt = 0.01; + + //[ integrate_transients_with_range + // perform 10000 transient steps + integrate_n_steps( rk4 , lorenz() , std::make_pair( x.begin() , x.begin() + n ) , 0.0 , dt , 10000 ); + //] + + //[ lyapunov_full_code + fill( x.begin()+n , x.end() , 0.0 ); + for( size_t i=0 ; i( x , lyap , n ); + ++count; + + if( !(count % 100000) ) + { + cout << t; + for( size_t i=0 ; i +#include +#include +#include +#include +#include + +#include +#include +#include + +#include +#include +#include +#include +#include + +#define tab "\t" + +using namespace std; +using namespace boost::numeric::odeint; + +const double sigma = 10.0; +const double R = 28.0; +const double b = 8.0 / 3.0; + +struct lorenz +{ + template< class State , class Deriv > + void operator()( const State &x , Deriv &dxdt , double t ) const + { + dxdt[0] = sigma * ( x[1] - x[0] ); + dxdt[1] = R * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -b * x[2] + x[0] * x[1]; + } +}; + + + +int main( int argc , char **argv ) +{ + typedef std::array< double , 3 > state_type; + + // std::for_each + { + runge_kutta4< state_type > stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + std::for_each( make_const_step_time_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_const_step_time_iterator_end( stepper , lorenz() , x ) , + []( const std::pair< state_type&, double > &x ) { + std::cout << x.second << tab << x.first[0] << tab << x.first[1] << tab << x.first[2] << "\n"; } ); + } + + // std::copy_if + { + std::vector< state_type > res; + runge_kutta4< state_type > stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + std::copy_if( make_const_step_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_const_step_iterator_end( stepper , lorenz() , x ) , + std::back_inserter( res ) , + []( const state_type& x ) { + return ( x[0] > 0.0 ) ? true : false; } ); + for( size_t i=0 ; i stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + double res = std::accumulate( make_const_step_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_const_step_iterator_end( stepper , lorenz() , x ) , + 0.0 , + []( double sum , const state_type &x ) { + return sum + x[0]; } ); + cout << res << endl; + //] + } + + + // std::transform + { + runge_kutta4< state_type > stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + vector< double > weights; + std::transform( make_const_step_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_const_step_iterator_end( stepper , lorenz() , x ) , + back_inserter( weights ) , + []( const state_type &x ) { + return sqrt( x[0] * x[0] + x[1] * x[1] + x[2] * x[2] ); } ); + for( size_t i=0 ; i stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + vector< double > weights; + std::transform( make_const_step_time_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + make_const_step_time_iterator_end( stepper , lorenz() , x ) , + back_inserter( weights ) , + []( const std::pair< state_type &, double > &x ) { + return sqrt( x.first[0] * x.first[0] + x.first[1] * x.first[1] + x.first[2] * x.first[2] ); } ); + for( size_t i=0 ; i stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + boost::range::for_each( make_const_step_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + []( const state_type &x ) { + std::cout << x[0] << tab << x[1] << tab << x[2] << "\n"; } ); + } + + // boost::range::for_each with time iterator + { + runge_kutta4< state_type > stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + boost::range::for_each( make_const_step_time_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + []( const std::pair< state_type& , double > &x ) { + std::cout << x.second << tab << x.first[0] << tab << x.first[1] << tab << x.first[2] << "\n"; } ); + } + + + // boost::range::copy with filtered adaptor (simulating std::copy_if) + { + std::vector< state_type > res; + runge_kutta4< state_type > stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + boost::range::copy( make_const_step_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) | + boost::adaptors::filtered( [] ( const state_type &x ) { return ( x[0] > 0.0 ); } ) , + std::back_inserter( res ) ); + for( size_t i=0 ; i stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + double res = boost::accumulate( make_const_step_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , 0.0 , + []( double sum , const state_type &x ) { + return sum + x[0]; } ); + cout << res << endl; + //] + } + + // boost::range::accumulate with time iterator + { + //[const_step_time_iterator_accumulate_range + runge_kutta4< state_type > stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + double res = boost::accumulate( make_const_step_time_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , 0.0 , + []( double sum , const std::pair< state_type &, double > &x ) { + return sum + x.first[0]; } ); + cout << res << endl; + //] + } + + + // boost::range::transform + { + runge_kutta4< state_type > stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + vector< double > weights; + boost::transform( make_const_step_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , back_inserter( weights ) , + []( const state_type &x ) { + return sqrt( x[0] * x[0] + x[1] * x[1] + x[2] * x[2] ); } ); + for( size_t i=0 ; i stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + auto iter = boost::find_if( make_const_step_time_range( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + []( const std::pair< state_type & , double > &x ) { + return ( x.first[0] < 0.0 ); } ); + cout << iter->second << "\t" << iter->first[0] << "\t" << iter->first[1] << "\t" << iter->first[2] << "\n"; + + } + + + + + + + + + + + + + /* + * Boost.Range versions for dense output steppers + */ + + // boost::range::for_each + { + runge_kutta_dopri5< state_type > stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + boost::range::for_each( make_const_step_range( make_dense_output( 1.0e-6 , 1.0e-6 , stepper ) , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + []( const state_type &x ) { + std::cout << x[0] << tab << x[1] << tab << x[2] << "\n"; } ); + } + + + // boost::range::for_each with time iterator + { + runge_kutta_dopri5< state_type > stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + boost::range::for_each( make_const_step_time_range( make_dense_output( 1.0e-6 , 1.0e-6 , stepper ) , lorenz() , x , 0.0 , 1.0 , 0.01 ) , + []( const std::pair< state_type& , double > &x ) { + std::cout << x.second << tab << x.first[0] << tab << x.first[1] << tab << x.first[2] << "\n"; } ); + + } + + + + + + /* + * Pure iterators + */ + { + runge_kutta4< state_type > stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + auto first = make_const_step_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ); + auto last = make_const_step_iterator_end( stepper , lorenz() , x ); + while( first != last ) + { + assert( last != first ); + cout << (*first)[0] << tab << (*first)[1] << tab << (*first)[2] << "\n"; + ++first; + } + } + + { + runge_kutta4< state_type > stepper; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + auto first = make_const_step_time_iterator_begin( stepper , lorenz() , x , 0.0 , 1.0 , 0.01 ); + auto last = make_const_step_time_iterator_end( stepper , lorenz() , x ); + while( first != last ) + { + assert( last != first ); + cout << first->second << tab << first->first[0] << tab << first->first[1] << tab << first->first[2] << "\n"; + ++first; + } + } + + + + + + + + return 0; +} diff --git a/examples/elliptic.py b/examples/elliptic.py new file mode 100644 index 00000000..99a6a24e --- /dev/null +++ b/examples/elliptic.py @@ -0,0 +1,31 @@ +""" + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + Stochastic euler stepper example and Ornstein-Uhlenbeck process + + Distributed under the Boost Software License, Version 1.0. +(See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) +""" + + +from pylab import * +from scipy import special + +data1 = loadtxt("elliptic1.dat") +data2 = loadtxt("elliptic2.dat") +data3 = loadtxt("elliptic3.dat") + +sn1,cn1,dn1,phi1 = special.ellipj( data1[:,0] , 0.51 ) +sn2,cn2,dn2,phi2 = special.ellipj( data2[:,0] , 0.51 ) +sn3,cn3,dn3,phi3 = special.ellipj( data3[:,0] , 0.51 ) + +semilogy( data1[:,0] , abs(data1[:,1]-sn1) ) +semilogy( data2[:,0] , abs(data2[:,1]-sn2) , 'ro' ) +semilogy( data3[:,0] , abs(data3[:,1]-sn3) , '--' ) + +show() + + + diff --git a/examples/elliptic_functions.cpp b/examples/elliptic_functions.cpp new file mode 100644 index 00000000..c993ad4b --- /dev/null +++ b/examples/elliptic_functions.cpp @@ -0,0 +1,87 @@ +/* + * elliptic_functions.cpp + * + * Copyright 2009-2012 Karsten Ahnert + * Copyright 2009-2012 Mario Mulansky + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + + + +#include +#include +#include + +#include + +#include + +#include +#include +#include + +using namespace std; +using namespace boost::numeric::odeint; + +typedef boost::array< double , 3 > state_type; + +/* + * x1' = x2*x3 + * x2' = -x1*x3 + * x3' = -m*x1*x2 + */ + +void rhs( const state_type &x , state_type &dxdt , const double t ) +{ + static const double m = 0.51; + + dxdt[0] = x[1]*x[2]; + dxdt[1] = -x[0]*x[2]; + dxdt[2] = -m*x[0]*x[1]; +} + +ofstream out; + +void write_out( const state_type &x , const double t ) +{ + out << t << '\t' << x[0] << '\t' << x[1] << '\t' << x[2] << endl; +} + +int main() +{ + bulirsch_stoer_dense_out< state_type > stepper( 1E-9 , 1E-9 , 1.0 , 0.0 ); + + state_type x1 = {{ 0.0 , 1.0 , 1.0 }}; + + double t = 0.0; + double dt = 0.01; + + out.open( "elliptic1.dat" ); + out.precision(16); + integrate_const( stepper , rhs , x1 , t , 100.0 , dt , write_out ); + out.close(); + + state_type x2 = {{ 0.0 , 1.0 , 1.0 }}; + + out.open( "elliptic2.dat" ); + out.precision(16); + integrate_adaptive( stepper , rhs , x2 , t , 100.0 , dt , write_out ); + out.close(); + + typedef runge_kutta_dopri5< state_type > dopri5_type; + typedef controlled_runge_kutta< dopri5_type > controlled_dopri5_type; + typedef dense_output_runge_kutta< controlled_dopri5_type > dense_output_dopri5_type; + + dense_output_dopri5_type dopri5( controlled_dopri5_type( default_error_checker< double >( 1E-9 , 0.0 , 0.0 , 0.0 ) ) ); + + state_type x3 = {{ 0.0 , 1.0 , 1.0 }}; + + out.open( "elliptic3.dat" ); + out.precision(16); + integrate_adaptive( dopri5 , rhs , x3 , t , 100.0 , dt , write_out ); + out.close(); +} diff --git a/examples/fpu.cpp b/examples/fpu.cpp new file mode 100644 index 00000000..5fc459e7 --- /dev/null +++ b/examples/fpu.cpp @@ -0,0 +1,168 @@ +/* + * fpu.cpp + * + * This example demonstrates how one can use odeint to solve the Fermi-Pasta-Ulam system. + + * Created on: July 13, 2011 + * + * Copyright 2009 Karsten Ahnert and Mario Mulansky. + * Distributed under the Boost Software License, Version 1.0. (See + * accompanying file LICENSE_1_0.txt or copy at + * http://www.boost.org/LICENSE_1_0.txt) + */ + +#include +#include +#include +#include + +#include + +#ifndef M_PI //not there on windows +#define M_PI 3.1415927 //... +#endif + +using namespace std; +using namespace boost::numeric::odeint; + +//[ fpu_system_function +typedef vector< double > container_type; + +struct fpu +{ + const double m_beta; + + fpu( const double beta = 1.0 ) : m_beta( beta ) { } + + // system function defining the ODE + void operator()( const container_type &q , container_type &dpdt ) const + { + size_t n = q.size(); + double tmp = q[0] - 0.0; + double tmp2 = tmp + m_beta * tmp * tmp * tmp; + dpdt[0] = -tmp2; + for( size_t i=0 ; i + } + + // calculates the local energy of the system + void local_energy( const container_type &q , const container_type &p , container_type &e ) const + { + // ... + //<- + size_t n = q.size(); + double tmp = q[0]; + double tmp2 = 0.5 * tmp * tmp + 0.25 * m_beta * tmp * tmp * tmp * tmp; + e[0] = tmp2; + for( size_t i=0 ; i + } +}; +//] + + + +//[ fpu_observer +struct streaming_observer +{ + std::ostream& m_out; + const fpu &m_fpu; + size_t m_write_every; + size_t m_count; + + streaming_observer( std::ostream &out , const fpu &f , size_t write_every = 100 ) + : m_out( out ) , m_fpu( f ) , m_write_every( write_every ) , m_count( 0 ) { } + + template< class State > + void operator()( const State &x , double t ) + { + if( ( m_count % m_write_every ) == 0 ) + { + container_type &q = x.first; + container_type &p = x.second; + container_type energy( q.size() ); + m_fpu.local_energy( q , p , energy ); + for( size_t i=0 ; i stepper_type; + fpu fpu_instance( 8.0 ); + + integrate_const( stepper_type() , fpu_instance , + make_pair( boost::ref( q ) , boost::ref( p ) ) , + 0.0 , 1000.0 , dt , streaming_observer( cout , fpu_instance , 10 ) ); + //] + + return 0; +} diff --git a/examples/generation_functions.cpp b/examples/generation_functions.cpp new file mode 100644 index 00000000..9b762bb1 --- /dev/null +++ b/examples/generation_functions.cpp @@ -0,0 +1,99 @@ +/* + libs/numeric/odeint/examples/stochastic_euler.hpp + + Copyright 2009 Karsten Ahnert + Copyright 2009 Mario Mulansky + + Stochastic euler stepper example and Ornstein-Uhlenbeck process + + Distributed under the Boost Software License, Version 1.0. +(See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#include + +#include + +typedef boost::array< double , 1 > state_type; + +using namespace boost::numeric::odeint; + + +//[ generation_functions_own_steppers +class custom_stepper +{ +public: + + typedef double value_type; + // ... +}; + +class custom_controller +{ + // ... +}; + +class custom_dense_output +{ + // ... +}; +//] + + +//[ generation_functions_get_controller +namespace boost { namespace numeric { namespace odeint { + +template<> +struct get_controller< custom_stepper > +{ + typedef custom_controller type; +}; + +} } } +//] + +//[ generation_functions_controller_factory +namespace boost { namespace numeric { namespace odeint { + +template<> +struct controller_factory< custom_stepper , custom_controller > +{ + custom_controller operator()( double abs_tol , double rel_tol , const custom_stepper & ) const + { + return custom_controller(); + } +}; + +} } } +//] + +int main( int argc , char **argv ) +{ + { + typedef runge_kutta_dopri5< state_type > stepper_type; + + /* + //[ generation_functions_syntax_auto + auto stepper1 = make_controlled( 1.0e-6 , 1.0e-6 , stepper_type() ); + auto stepper2 = make_dense_output( 1.0e-6 , 1.0e-6 , stepper_type() ); + //] + */ + + //[ generation_functions_syntax_result_of + boost::numeric::odeint::result_of::make_controlled< stepper_type >::type stepper3 = make_controlled( 1.0e-6 , 1.0e-6 , stepper_type() ); + boost::numeric::odeint::result_of::make_dense_output< stepper_type >::type stepper4 = make_dense_output( 1.0e-6 , 1.0e-6 , stepper_type() ); + //] + } + + { + /* + //[ generation_functions_example_custom_controller + auto stepper5 = make_controlled( 1.0e-6 , 1.0e-6 , custom_stepper() ); + //] + */ + + boost::numeric::odeint::result_of::make_controlled< custom_stepper >::type stepper5 = make_controlled( 1.0e-6 , 1.0e-6 , custom_stepper() ); + } + return 0; +} diff --git a/examples/gmpxx/Jamfile b/examples/gmpxx/Jamfile new file mode 100644 index 00000000..65f110d7 --- /dev/null +++ b/examples/gmpxx/Jamfile @@ -0,0 +1,19 @@ +# Copyright 2009 Karsten Ahnert and Mario Mulansky. +# Distributed under the Boost Software License, Version 1.0. (See +# accompanying file LICENSE_1_0.txt or copy at +# http://www.boost.org/LICENSE_1_0.txt) + + +project + : requirements + ../../../.. + BOOST_ALL_NO_LIB=1 + ; + +lib libgmp : : gmp shared ; +lib libgmpxx : : gmpxx shared ; + + + +exe lorenz_gmpxx : lorenz_gmpxx.cpp libgmp libgmpxx ; + diff --git a/examples/gmpxx/lorenz_gmpxx.cpp b/examples/gmpxx/lorenz_gmpxx.cpp new file mode 100644 index 00000000..2bdd562b --- /dev/null +++ b/examples/gmpxx/lorenz_gmpxx.cpp @@ -0,0 +1,83 @@ +/* + * lorenz_gmpxx.cpp + * + * This example demonstrates how odeint can be used with arbitrary precision types. + * + * Copyright 2009-2012 Karsten Ahnert + * Copyright 2009-2012 Mario Mulansky + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + + +#include +#include + +#include + +#include + +using namespace std; +using namespace boost::numeric::odeint; + +//[ gmpxx_lorenz +typedef mpf_class value_type; +typedef boost::array< value_type , 3 > state_type; + +struct lorenz +{ + void operator()( const state_type &x , state_type &dxdt , value_type t ) const + { + const value_type sigma( 10.0 ); + const value_type R( 28.0 ); + const value_type b( value_type( 8.0 ) / value_type( 3.0 ) ); + + dxdt[0] = sigma * ( x[1] - x[0] ); + dxdt[1] = R * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -b * x[2] + x[0] * x[1]; + } +}; +//] + + + + +struct streaming_observer +{ + std::ostream& m_out; + + streaming_observer( std::ostream &out ) : m_out( out ) { } + + template< class State , class Time > + void operator()( const State &x , Time t ) const + { + m_out << t; + for( size_t i=0 ; i() , + lorenz() , x , value_type( 0.0 ) , value_type( 10.0 ) , value_type( value_type( 1.0 ) / value_type( 10.0 ) ) , + streaming_observer( cout ) ); + //] + + return 0; +} diff --git a/examples/gram_schmidt.hpp b/examples/gram_schmidt.hpp new file mode 100644 index 00000000..9198491f --- /dev/null +++ b/examples/gram_schmidt.hpp @@ -0,0 +1,88 @@ +/* + boost header: numeric/odeint/gram_schmitt.hpp + + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#ifndef BOOST_NUMERIC_ODEINT_GRAM_SCHMITT_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_GRAM_SCHMITT_HPP_INCLUDED + +#include +#include +#include + +namespace boost { +namespace numeric { +namespace odeint { + +template< class Iterator , class T > +void normalize( Iterator first , Iterator last , T norm ) +{ + while( first != last ) *first++ /= norm; +} + +template< class Iterator , class T > +void substract_vector( Iterator first1 , Iterator last1 , + Iterator first2 , T val ) +{ + while( first1 != last1 ) *first1++ -= val * ( *first2++ ); +} + +template< size_t num_of_lyap , class StateType , class LyapType > +void gram_schmidt( StateType &x , LyapType &lyap , size_t n ) +{ + if( !num_of_lyap ) return; + if( ptrdiff_t( ( num_of_lyap + 1 ) * n ) != std::distance( x.begin() , x.end() ) ) + throw std::domain_error( "renormalization() : size of state does not match the number of lyapunov exponents." ); + + typedef typename StateType::value_type value_type; + typedef typename StateType::iterator iterator; + + value_type norm[num_of_lyap]; + value_type tmp[num_of_lyap]; + iterator first = x.begin() + n; + iterator beg1 = first , end1 = first + n ; + + std::fill( norm , norm+num_of_lyap , 0.0 ); + + // normalize first vector + norm[0] = sqrt( std::inner_product( beg1 , end1 , beg1 , 0.0 ) ); + normalize( beg1 , end1 , norm[0] ); + + beg1 += n; + end1 += n; + + for( size_t j=1 ; j +#include + +#include + + + +//[ rhs_function +/* The type of container used to hold the state vector */ +typedef std::vector< double > state_type; + +const double gam = 0.15; + +/* The rhs of x' = f(x) */ +void harmonic_oscillator( const state_type &x , state_type &dxdt , const double /* t */ ) +{ + dxdt[0] = x[1]; + dxdt[1] = -x[0] - gam*x[1]; +} +//] + + + + + +//[ rhs_class +/* The rhs of x' = f(x) defined as a class */ +class harm_osc { + + double m_gam; + +public: + harm_osc( double gam ) : m_gam(gam) { } + + void operator() ( const state_type &x , state_type &dxdt , const double /* t */ ) + { + dxdt[0] = x[1]; + dxdt[1] = -x[0] - m_gam*x[1]; + } +}; +//] + + + + + +//[ integrate_observer +struct push_back_state_and_time +{ + std::vector< state_type >& m_states; + std::vector< double >& m_times; + + push_back_state_and_time( std::vector< state_type > &states , std::vector< double > × ) + : m_states( states ) , m_times( times ) { } + + void operator()( const state_type &x , double t ) + { + m_states.push_back( x ); + m_times.push_back( t ); + } +}; +//] + +struct write_state +{ + void operator()( const state_type &x ) const + { + std::cout << x[0] << "\t" << x[1] << "\n"; + } +}; + + +int main(int /* argc */ , char** /* argv */ ) +{ + using namespace std; + using namespace boost::numeric::odeint; + + + //[ state_initialization + state_type x(2); + x[0] = 1.0; // start at x=1.0, p=0.0 + x[1] = 0.0; + //] + + + + //[ integration + size_t steps = integrate( harmonic_oscillator , + x , 0.0 , 10.0 , 0.1 ); + //] + + + + //[ integration_class + harm_osc ho(0.15); + steps = integrate( ho , + x , 0.0 , 10.0 , 0.1 ); + //] + + + + + + //[ integrate_observ + vector x_vec; + vector times; + + steps = integrate( harmonic_oscillator , + x , 0.0 , 10.0 , 0.1 , + push_back_state_and_time( x_vec , times ) ); + + /* output */ + for( size_t i=0; i<=steps; i++ ) + { + cout << times[i] << '\t' << x_vec[i][0] << '\t' << x_vec[i][1] << '\n'; + } + //] + + + + + + + + //[ define_const_stepper + runge_kutta4< state_type > stepper; + integrate_const( stepper , harmonic_oscillator , x , 0.0 , 10.0 , 0.01 ); + //] + + + + + //[ integrate_const_loop + const double dt = 0.01; + for( double t=0.0 ; t<10.0 ; t+= dt ) + stepper.do_step( harmonic_oscillator , x , t , dt ); + //] + + + + + //[ define_adapt_stepper + typedef runge_kutta_cash_karp54< state_type > error_stepper_type; + //] + + + + //[ integrate_adapt + typedef controlled_runge_kutta< error_stepper_type > controlled_stepper_type; + controlled_stepper_type controlled_stepper; + integrate_adaptive( controlled_stepper , harmonic_oscillator , x , 0.0 , 10.0 , 0.01 ); + //] + + { + //[integrate_adapt_full + double abs_err = 1.0e-10 , rel_err = 1.0e-6 , a_x = 1.0 , a_dxdt = 1.0; + controlled_stepper_type controlled_stepper( + default_error_checker< double >( abs_err , rel_err , a_x , a_dxdt ) ); + integrate_adaptive( controlled_stepper , harmonic_oscillator , x , 0.0 , 10.0 , 0.01 ); + //] + } + + + //[integrate_adapt_make_controlled + integrate_adaptive( make_controlled< error_stepper_type >( 1.0e-10 , 1.0e-6 ) , + harmonic_oscillator , x , 0.0 , 10.0 , 0.01 ); + //] + + + + + //[integrate_adapt_make_controlled_alternative + integrate_adaptive( make_controlled( 1.0e-10 , 1.0e-6 , error_stepper_type() ) , + harmonic_oscillator , x , 0.0 , 10.0 , 0.01 ); + //] + + #ifdef BOOST_NUMERIC_ODEINT_CXX11 + //[ define_const_stepper_cpp11 + runge_kutta4< state_type > stepper; + integrate_const( stepper , []( const state_type &x , state_type &dxdt , double t ) { + dxdt[0] = x[1]; dxdt[1] = -x[0] - gam*x[1]; } + , x , 0.0 , 10.0 , 0.01 ); + //] + #endif + + + //[harm_iterator_const_step + std::for_each( make_adaptive_iterator_begin( controlled_stepper , harmonic_oscillator , x , 0.0 , 10.0 , 0.01 ) , + make_adaptive_iterator_end( controlled_stepper , harmonic_oscillator , x ) , + write_state() ); + //] + +} diff --git a/examples/harmonic_oscillator_units.cpp b/examples/harmonic_oscillator_units.cpp new file mode 100644 index 00000000..2448b54c --- /dev/null +++ b/examples/harmonic_oscillator_units.cpp @@ -0,0 +1,119 @@ +/* + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#include +#include + + +/* WARNING: Compilation in debug mode might consume enormous memory + (e.g. ~2GB on gcc 4.4 ) +*/ + +// first increase fusion macro variables (now done by odeint itself) +//#define BOOST_FUSION_INVOKE_MAX_ARITY 15 +//#define BOOST_RESULT_OF_NUM_ARGS 15 + +//[ units_define_basic_quantities + +#include +#include + +#include +#include +#include +#include +#include + +#include + +using namespace std; +using namespace boost::numeric::odeint; +namespace fusion = boost::fusion; +namespace units = boost::units; +namespace si = boost::units::si; + +typedef units::quantity< si::time , double > time_type; +typedef units::quantity< si::length , double > length_type; +typedef units::quantity< si::velocity , double > velocity_type; +typedef units::quantity< si::acceleration , double > acceleration_type; +typedef units::quantity< si::frequency , double > frequency_type; + +typedef fusion::vector< length_type , velocity_type > state_type; +typedef fusion::vector< velocity_type , acceleration_type > deriv_type; +//] + + + +//[ units_define_ode +struct oscillator +{ + frequency_type m_omega; + + oscillator( const frequency_type &omega = 1.0 * si::hertz ) : m_omega( omega ) { } + + void operator()( const state_type &x , deriv_type &dxdt , time_type t ) const + { + fusion::at_c< 0 >( dxdt ) = fusion::at_c< 1 >( x ); + fusion::at_c< 1 >( dxdt ) = - m_omega * m_omega * fusion::at_c< 0 >( x ); + } +}; +//] + + +//[ units_observer +struct streaming_observer +{ + std::ostream& m_out; + + streaming_observer( std::ostream &out ) : m_out( out ) { } + + struct write_element + { + std::ostream &m_out; + write_element( std::ostream &out ) : m_out( out ) { }; + + template< class T > + void operator()( const T &t ) const + { + m_out << "\t" << t; + } + }; + + template< class State , class Time > + void operator()( const State &x , const Time &t ) const + { + m_out << t; + fusion::for_each( x , write_element( m_out ) ); + m_out << "\n"; + } +}; +//] + + +int main( int argc , char**argv ) +{ +// typedef dense_output_runge_kutta +// < +// controlled_runge_kutta +// < +// runge_kutta_dopri5< state_type , double , deriv_type , time_type , fusion_algebra > +// > +// > stepper_type; + + //[ units_define_stepper + typedef runge_kutta_dopri5< state_type , double , deriv_type , time_type , fusion_algebra > stepper_type; + + state_type x( 1.0 * si::meter , 0.0 * si::meter_per_second ); + + integrate_const( make_dense_output( 1.0e-6 , 1.0e-6 , stepper_type() ) , oscillator( 2.0 * si::hertz ) , x , 0.0 * si::second , 100.0 * si::second , 0.1 * si::second , streaming_observer( cout ) ); + //] + + return 0; +} diff --git a/examples/heun.cpp b/examples/heun.cpp new file mode 100644 index 00000000..1c9c284c --- /dev/null +++ b/examples/heun.cpp @@ -0,0 +1,170 @@ +/* + [auto_generated] + libs/numeric/odeint/examples/heun.cpp + + [begin_description] + Examplary implementation of the method of Heun. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#include + + +#include +#include + +#include + +#include + + + + + + +namespace fusion = boost::fusion; + +//[ heun_define_coefficients +template< class Value = double > +struct heun_a1 : boost::array< Value , 1 > { + heun_a1( void ) + { + (*this)[0] = static_cast< Value >( 1 ) / static_cast< Value >( 3 ); + } +}; + +template< class Value = double > +struct heun_a2 : boost::array< Value , 2 > +{ + heun_a2( void ) + { + (*this)[0] = static_cast< Value >( 0 ); + (*this)[1] = static_cast< Value >( 2 ) / static_cast< Value >( 3 ); + } +}; + + +template< class Value = double > +struct heun_b : boost::array< Value , 3 > +{ + heun_b( void ) + { + (*this)[0] = static_cast( 1 ) / static_cast( 4 ); + (*this)[1] = static_cast( 0 ); + (*this)[2] = static_cast( 3 ) / static_cast( 4 ); + } +}; + +template< class Value = double > +struct heun_c : boost::array< Value , 3 > +{ + heun_c( void ) + { + (*this)[0] = static_cast< Value >( 0 ); + (*this)[1] = static_cast< Value >( 1 ) / static_cast< Value >( 3 ); + (*this)[2] = static_cast< Value >( 2 ) / static_cast< Value >( 3 ); + } +}; +//] + + +//[ heun_stepper_definition +template< + class State , + class Value = double , + class Deriv = State , + class Time = Value , + class Algebra = boost::numeric::odeint::range_algebra , + class Operations = boost::numeric::odeint::default_operations , + class Resizer = boost::numeric::odeint::initially_resizer +> +class heun : public +boost::numeric::odeint::explicit_generic_rk< 3 , 3 , State , Value , Deriv , Time , + Algebra , Operations , Resizer > +{ + +public: + + typedef boost::numeric::odeint::explicit_generic_rk< 3 , 3 , State , Value , Deriv , Time , + Algebra , Operations , Resizer > stepper_base_type; + + typedef typename stepper_base_type::state_type state_type; + typedef typename stepper_base_type::wrapped_state_type wrapped_state_type; + typedef typename stepper_base_type::value_type value_type; + typedef typename stepper_base_type::deriv_type deriv_type; + typedef typename stepper_base_type::wrapped_deriv_type wrapped_deriv_type; + typedef typename stepper_base_type::time_type time_type; + typedef typename stepper_base_type::algebra_type algebra_type; + typedef typename stepper_base_type::operations_type operations_type; + typedef typename stepper_base_type::resizer_type resizer_type; + typedef typename stepper_base_type::stepper_type stepper_type; + + heun( const algebra_type &algebra = algebra_type() ) + : stepper_base_type( + fusion::make_vector( + heun_a1() , + heun_a2() ) , + heun_b() , heun_c() , algebra ) + { } +}; +//] + + +const double sigma = 10.0; +const double R = 28.0; +const double b = 8.0 / 3.0; + +struct lorenz +{ + template< class State , class Deriv > + void operator()( const State &x_ , Deriv &dxdt_ , double t ) const + { + typename boost::range_iterator< const State >::type x = boost::begin( x_ ); + typename boost::range_iterator< Deriv >::type dxdt = boost::begin( dxdt_ ); + + dxdt[0] = sigma * ( x[1] - x[0] ); + dxdt[1] = R * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -b * x[2] + x[0] * x[1]; + } +}; + +struct streaming_observer +{ + std::ostream &m_out; + streaming_observer( std::ostream &out ) : m_out( out ) { } + template< typename State , typename Value > + void operator()( const State &x , Value t ) const + { + m_out << t; + for( size_t i=0 ; i state_type; + heun< state_type > h; + state_type x = {{ 10.0 , 10.0 , 10.0 }}; + + integrate_const( h , lorenz() , x , 0.0 , 100.0 , 0.01 , + streaming_observer( std::cout ) ); + + //] + + return 0; +} diff --git a/examples/list_lattice.cpp b/examples/list_lattice.cpp new file mode 100644 index 00000000..bc95897d --- /dev/null +++ b/examples/list_lattice.cpp @@ -0,0 +1,78 @@ +/* + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +/* example showing how odeint can be used with std::list */ + +#include +#include +#include + +#include + +//[ list_bindings +typedef std::list< double > state_type; + +namespace boost { namespace numeric { namespace odeint { + +template< > +struct is_resizeable< state_type > +{ // declare resizeablility + typedef boost::true_type type; + const static bool value = type::value; +}; + +template< > +struct same_size_impl< state_type , state_type > +{ // define how to check size + static bool same_size( const state_type &v1 , + const state_type &v2 ) + { + return v1.size() == v2.size(); + } +}; + +template< > +struct resize_impl< state_type , state_type > +{ // define how to resize + static void resize( state_type &v1 , + const state_type &v2 ) + { + v1.resize( v2.size() ); + } +}; + +} } } +//] + +void lattice( const state_type &x , state_type &dxdt , const double /* t */ ) +{ + state_type::const_iterator x_begin = x.begin(); + state_type::const_iterator x_end = x.end(); + state_type::iterator dxdt_begin = dxdt.begin(); + + x_end--; // stop one before last + while( x_begin != x_end ) + { + *(dxdt_begin++) = std::sin( *(x_begin) - *(x_begin++) ); + } + *dxdt_begin = sin( *x_begin - *(x.begin()) ); // periodic boundary +} + +using namespace boost::numeric::odeint; + +int main() +{ + const int N = 32; + state_type x; + for( int i=0 ; i() , lattice , x , 0.0 , 10.0 , 0.1 ); +} diff --git a/examples/lorenz_point.cpp b/examples/lorenz_point.cpp new file mode 100644 index 00000000..8edf41bc --- /dev/null +++ b/examples/lorenz_point.cpp @@ -0,0 +1,124 @@ +/* + * Copyright 2009-2012 Karsten Ahnert + * Copyright 2009-2012 Mario Mulansky + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + * + * Example for the lorenz system with a 3D point type +*/ + +#include +#include + +#include + +#include + + +//[point3D +class point3D : + boost::additive1< point3D , + boost::additive2< point3D , double , + boost::multiplicative2< point3D , double > > > +{ +public: + + double x , y , z; + + point3D() + : x( 0.0 ) , y( 0.0 ) , z( 0.0 ) + { } + + point3D( const double val ) + : x( val ) , y( val ) , z( val ) + { } + + point3D( const double _x , const double _y , const double _z ) + : x( _x ) , y( _y ) , z( _z ) + { } + + point3D& operator+=( const point3D &p ) + { + x += p.x; y += p.y; z += p.z; + return *this; + } + + point3D& operator*=( const double a ) + { + x *= a; y *= a; z *= a; + return *this; + } + +}; +//] + +//[point3D_abs_div +// only required for steppers with error control +point3D operator/( const point3D &p1 , const point3D &p2 ) +{ + return point3D( p1.x/p2.x , p1.y/p2.y , p1.z/p1.z ); +} + +point3D abs( const point3D &p ) +{ + return point3D( std::abs(p.x) , std::abs(p.y) , std::abs(p.z) ); +} +//] + + +//[point3D_reduce +namespace boost { namespace numeric { namespace odeint { +// specialization of vector_space_reduce, only required for steppers with error control +template<> +struct vector_space_reduce< point3D > +{ + template< class Value , class Op > + Value operator() ( const point3D &p , Op op , Value init ) + { + init = op( init , p.x ); + //std::cout << init << " "; + init = op( init , p.y ); + //std::cout << init << " "; + init = op( init , p.z ); + //std::cout << init << std::endl; + return init; + } +}; +} } } +//] + +std::ostream& operator<<( std::ostream &out , const point3D &p ) +{ + out << p.x << " " << p.y << " " << p.z; + return out; +} + +//[point3D_main +const double sigma = 10.0; +const double R = 28.0; +const double b = 8.0 / 3.0; + +void lorenz( const point3D &x , point3D &dxdt , const double t ) +{ + dxdt.x = sigma * ( x.y - x.x ); + dxdt.y = R * x.x - x.y - x.x * x.z; + dxdt.z = -b * x.z + x.x * x.y; +} + +using namespace boost::numeric::odeint; + +int main() +{ + + point3D x( 10.0 , 5.0 , 5.0 ); + // point type defines it's own operators -> use vector_space_algebra ! + typedef runge_kutta_dopri5< point3D , double , point3D , + double , vector_space_algebra > stepper; + int steps = integrate_adaptive( make_controlled( 1E-10 , 1E-10 ) , lorenz , x , + 0.0 , 10.0 , 0.1 ); + std::cout << x << std::endl; + std::cout << "steps: " << steps << std::endl; +} +//] diff --git a/examples/mtl/Jamfile.v2 b/examples/mtl/Jamfile.v2 new file mode 100644 index 00000000..3b5ce8e8 --- /dev/null +++ b/examples/mtl/Jamfile.v2 @@ -0,0 +1,16 @@ +# Copyright 2009 Karsten Ahnert and Mario Mulansky. +# Distributed under the Boost Software License, Version 1.0. (See +# accompanying file LICENSE_1_0.txt or copy at +# http://www.boost.org/LICENSE_1_0.txt) + +MTL4_INCLUDE = /home/karsten/boost/MTL-4.0.8862-Linux/usr/include ; + +project + : requirements + ../../../../.. + $(MTL4_INCLUDE) + BOOST_ALL_NO_LIB=1 + ; + +exe gauss_packet : gauss_packet.cpp ; +exe implicit_euler_mtl : implicit_euler_mtl.cpp ; \ No newline at end of file diff --git a/examples/mtl/gauss_packet.cpp b/examples/mtl/gauss_packet.cpp new file mode 100644 index 00000000..59e38ea3 --- /dev/null +++ b/examples/mtl/gauss_packet.cpp @@ -0,0 +1,141 @@ +/* + * gauss_packet.cpp + * + * Schroedinger equation with potential barrier and periodic boundary conditions + * Initial Gauss packet moving to the right + * + * pipe output into gnuplot to see animation + * + * Implementation of Hamilton operator via MTL library + * + * Copyright 2009-2012 Karsten Ahnert + * Copyright 2009-2012 Mario Mulansky + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#include +#include + +#include +#include + +#include + + +using namespace std; +using namespace boost::numeric::odeint; + +typedef mtl::dense_vector< complex< double > > state_type; + +struct hamiltonian { + + typedef mtl::compressed2D< complex< double > > matrix_type; + matrix_type m_H; + + hamiltonian( const int N ) : m_H( N , N ) + { + // constructor with zero potential + m_H = 0.0; + initialize_kinetic_term(); + } + + //template< mtl::compressed2D< double > > + hamiltonian( mtl::compressed2D< double > &V ) : m_H( num_rows( V ) , num_cols( V ) ) + { + // use potential V in hamiltonian + m_H = complex( 0.0 , -1.0 ) * V; + initialize_kinetic_term(); + } + + void initialize_kinetic_term( ) + { + const int N = num_rows( m_H ); + mtl::matrix::inserter< matrix_type , mtl::update_plus< complex > > ins( m_H ); + const double z = 1.0; + // fill diagonal and upper and lower diagonal + for( int i = 0 ; i( 0.0 , -z ); + ins[ i ][ i ] << complex< double >( 0.0 , z ); + ins[ (i+1) % N ][ i ] << complex< double >( 0.0 , -z ); + } + } + + void operator()( const state_type &psi , state_type &dpsidt , const double t ) + { + dpsidt = m_H * psi; + } + +}; + +struct write_for_gnuplot +{ + size_t m_every , m_count; + + write_for_gnuplot( size_t every = 10 ) + : m_every( every ) , m_count( 0 ) { } + + void operator()( const state_type &x , double t ) + { + if( ( m_count % m_every ) == 0 ) + { + //clog << t << endl; + cout << "p [0:" << mtl::size(x) << "][0:0.02] '-'" << endl; + for( size_t i=0 ; i( 0.0 , k0*i ) ); + //x[i] += 2.0*exp( -(i+N0-N)*(i+N0-N) / ( 4.0*sigma0*sigma0 ) ) * exp( complex< double >( 0.0 , -k0*i ) ); + } + x /= mtl::two_norm( x ); + + typedef runge_kutta4< state_type , double , state_type , double , vector_space_algebra > stepper; + + // create potential barrier + mtl::compressed2D< double > V( N , N ); + V = 0.0; + { + mtl::matrix::inserter< mtl::compressed2D< double > > ins( V ); + for( int i=0 ; i +#include +#include +#include "time.h" + +#include +#include +#include + +#include + +using namespace std; +using namespace boost::numeric::odeint; + +namespace phoenix = boost::phoenix; + + + +typedef mtl::dense_vector< double > vec_mtl4; +typedef mtl::compressed2D< double > mat_mtl4; + +typedef boost::numeric::ublas::vector< double > vec_ublas; +typedef boost::numeric::ublas::matrix< double > mat_ublas; + + +// two systems defined 1 & 2 both are mostly sparse with the number of element variable +struct system1_mtl4 +{ + + void operator()( const vec_mtl4 &x , vec_mtl4 &dxdt , double t ) + { + int size = mtl::size(x); + + dxdt[ 0 ] = -0.06*x[0]; + + for (int i =1; i< size ; ++i){ + + dxdt[ i ] = 4.2*x[i-1]-2.2*x[i]*x[i]; + } + + } +}; + +struct jacobi1_mtl4 +{ + void operator()( const vec_mtl4 &x , mat_mtl4 &J , const double &t ) + { + int size = mtl::size(x); + mtl::matrix::inserter ins(J); + + ins[0][0]=-0.06; + + for (int i =1; i< size ; ++i) + { + ins[i][i-1] = + 4.2; + ins[i][i] = -4.2*x[i]; + } + } +}; + + + +struct system1_ublas +{ + + void operator()( const vec_ublas &x , vec_ublas &dxdt , double t ) + { + int size = x.size(); + + dxdt[ 0 ] = -0.06*x[0]; + + for (int i =1; i< size ; ++i){ + + dxdt[ i ] = 4.2*x[i-1]-2.2*x[i]*x[i]; + } + + } +}; + +struct jacobi1_ublas +{ + void operator()( const vec_ublas &x , mat_ublas &J , const double &t ) + { + int size = x.size(); +// mtl::matrix::inserter ins(J); + + J(0,0)=-0.06; + + for (int i =1; i< size ; ++i){ +//ins[i][0]=120.0*x[i]; + J(i,i-1) = + 4.2; + J(i,i) = -4.2*x[i]; + + } + } +}; + +struct system2_mtl4 +{ + + void operator()( const vec_mtl4 &x , vec_mtl4 &dxdt , double t ) + { + int size = mtl::size(x); + + + for (int i =0; i< size/5 ; i+=5){ + + dxdt[ i ] = -0.5*x[i]; + dxdt[i+1]= +25*x[i+1]*x[i+2]-740*x[i+3]*x[i+3]+4.2e-2*x[i]; + dxdt[i+2]= +25*x[i]*x[i]-740*x[i+3]*x[i+3]; + dxdt[i+3]= -25*x[i+1]*x[i+2]+740*x[i+3]*x[i+3]; + dxdt[i+4] = 0.250*x[i]*x[i+1]-44.5*x[i+3]; + + } + + } +}; + +struct jacobi2_mtl4 +{ + void operator()( const vec_mtl4 &x , mat_mtl4 &J , const double &t ) + { + int size = mtl::size(x); + mtl::matrix::inserter ins(J); + + for (int i =0; i< size/5 ; i+=5){ + + ins[ i ][i] = -0.5; + ins[i+1][i+1]=25*x[i+2]; + ins[i+1][i+2] = 25*x[i+1]; + ins[i+1][i+3] = -740*2*x[i+3]; + ins[i+1][i] =+4.2e-2; + + ins[i+2][i]= 50*x[i]; + ins[i+2][i+3]= -740*2*x[i+3]; + ins[i+3][i+1] = -25*x[i+2]; + ins[i+3][i+2] = -25*x[i+1]; + ins[i+3][i+3] = +740*2*x[i+3]; + ins[i+4][i] = 0.25*x[i+1]; + ins[i+4][i+1] =0.25*x[i]; + ins[i+4][i+3]=-44.5; + + + + } + } +}; + + + +struct system2_ublas +{ + + void operator()( const vec_ublas &x , vec_ublas &dxdt , double t ) + { + int size = x.size(); + for (int i =0; i< size/5 ; i+=5){ + + dxdt[ i ] = -4.2e-2*x[i]; + dxdt[i+1]= +25*x[i+1]*x[i+2]-740*x[i+3]*x[i+3]+4.2e-2*x[i]; + dxdt[i+2]= +25*x[i]*x[i]-740*x[i+3]*x[i+3]; + dxdt[i+3]= -25*x[i+1]*x[i+2]+740*x[i+3]*x[i+3]; + dxdt[i+4] = 0.250*x[i]*x[i+1]-44.5*x[i+3]; + + } + + } +}; + +struct jacobi2_ublas +{ + void operator()( const vec_ublas &x , mat_ublas &J , const double &t ) + { + int size = x.size(); + + for (int i =0; i< size/5 ; i+=5){ + + J(i ,i) = -4.2e-2; + J(i+1,i+1)=25*x[i+2]; + J(i+1,i+2) = 25*x[i+1]; + J(i+1,i+3) = -740*2*x[i+3]; + J(i+1,i) =+4.2e-2; + + J(i+2,i)= 50*x[i]; + J(i+2,i+3)= -740*2*x[i+3]; + J(i+3,i+1) = -25*x[i+2]; + J(i+3,i+2) = -25*x[i+1]; + J(i+3,i+3) = +740*2*x[i+3]; + J(i+4,i) = 0.25*x[i+1]; + J(i+4,i+1) =0.25*x[i]; + J(i+4,i+3)=-44.5; + + + + } + + + } +}; + + + + +void testRidiculouslyMassiveArray( int size ) +{ + typedef boost::numeric::odeint::implicit_euler_mtl4 < double > mtl4stepper; + typedef boost::numeric::odeint::implicit_euler< double > booststepper; + + vec_mtl4 x(size , 0.0); + x[0]=1; + + + double dt = 0.02; + double endtime = 10.0; + + clock_t tstart_mtl4 = clock(); + size_t num_of_steps_mtl4 = integrate_const( + mtl4stepper() , + make_pair( system1_mtl4() , jacobi1_mtl4() ) , + x , 0.0 , endtime , dt ); + clock_t tend_mtl4 = clock() ; + + clog << x[0] << endl; + clog << num_of_steps_mtl4 << " time elapsed: " << (double)(tend_mtl4-tstart_mtl4 )/CLOCKS_PER_SEC << endl; + + vec_ublas x_ublas(size , 0.0); + x_ublas[0]=1; + + clock_t tstart_boost = clock(); + size_t num_of_steps_ublas = integrate_const( + booststepper() , + make_pair( system1_ublas() , jacobi1_ublas() ) , + x_ublas , 0.0 , endtime , dt ); + clock_t tend_boost = clock() ; + + clog << x_ublas[0] << endl; + clog << num_of_steps_ublas << " time elapsed: " << (double)(tend_boost-tstart_boost)/CLOCKS_PER_SEC<< endl; + + clog << "dt_ublas/dt_mtl4 = " << (double)( tend_boost-tstart_boost )/( tend_mtl4-tstart_mtl4 ) << endl << endl; + return ; +} + + + +void testRidiculouslyMassiveArray2( int size ) +{ + typedef boost::numeric::odeint::implicit_euler_mtl4 < double > mtl4stepper; + typedef boost::numeric::odeint::implicit_euler< double > booststepper; + + + vec_mtl4 x(size , 0.0); + x[0]=100; + + + double dt = 0.01; + double endtime = 10.0; + + clock_t tstart_mtl4 = clock(); + size_t num_of_steps_mtl4 = integrate_const( + mtl4stepper() , + make_pair( system1_mtl4() , jacobi1_mtl4() ) , + x , 0.0 , endtime , dt ); + + + clock_t tend_mtl4 = clock() ; + + clog << x[0] << endl; + clog << num_of_steps_mtl4 << " time elapsed: " << (double)(tend_mtl4-tstart_mtl4 )/CLOCKS_PER_SEC << endl; + + vec_ublas x_ublas(size , 0.0); + x_ublas[0]=100; + + clock_t tstart_boost = clock(); + size_t num_of_steps_ublas = integrate_const( + booststepper() , + make_pair( system1_ublas() , jacobi1_ublas() ) , + x_ublas , 0.0 , endtime , dt ); + + + clock_t tend_boost = clock() ; + + clog << x_ublas[0] << endl; + clog << num_of_steps_ublas << " time elapsed: " << (double)(tend_boost-tstart_boost)/CLOCKS_PER_SEC<< endl; + + clog << "dt_ublas/dt_mtl4 = " << (double)( tend_boost-tstart_boost )/( tend_mtl4-tstart_mtl4 ) << endl << endl; + return ; +} + + + + +int main( int argc , char **argv ) +{ + std::vector< size_t > length; + length.push_back( 8 ); + length.push_back( 16 ); + length.push_back( 32 ); + length.push_back( 64 ); + length.push_back( 128 ); + length.push_back( 256 ); + + for( size_t i=0 ; i + +#include + +//[my_vector +template< int MAX_N > +class my_vector +{ + typedef std::vector< double > vector; + +public: + typedef vector::iterator iterator; + typedef vector::const_iterator const_iterator; + +public: + my_vector( const size_t N ) + : m_v( N ) + { + m_v.reserve( MAX_N ); + } + + my_vector() + : m_v() + { + m_v.reserve( MAX_N ); + } + +// ... [ implement container interface ] +//] + const double & operator[]( const size_t n ) const + { return m_v[n]; } + + double & operator[]( const size_t n ) + { return m_v[n]; } + + iterator begin() + { return m_v.begin(); } + + const_iterator begin() const + { return m_v.begin(); } + + iterator end() + { return m_v.end(); } + + const_iterator end() const + { return m_v.end(); } + + size_t size() const + { return m_v.size(); } + + void resize( const size_t n ) + { m_v.resize( n ); } + +private: + std::vector< double > m_v; + +}; + +//[my_vector_resizeable +// define my_vector as reizeable + +namespace boost { namespace numeric { namespace odeint { + +template +struct is_resizeable< my_vector > +{ + typedef boost::true_type type; + static const bool value = type::value; +}; + +} } } +//] + + +typedef my_vector<3> state_type; + +void lorenz( const state_type &x , state_type &dxdt , const double t ) +{ + const double sigma( 10.0 ); + const double R( 28.0 ); + const double b( 8.0 / 3.0 ); + + dxdt[0] = sigma * ( x[1] - x[0] ); + dxdt[1] = R * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -b * x[2] + x[0] * x[1]; +} + +using namespace boost::numeric::odeint; + +int main() +{ + state_type x(3); + x[0] = 5.0 ; x[1] = 10.0 ; x[2] = 10.0; + + // my_vector works with range_algebra as it implements + // the required parts of a container interface + // no further work is required + + integrate_const( runge_kutta4< state_type >() , lorenz , x , 0.0 , 10.0 , 0.1 ); +} diff --git a/examples/phase_oscillator_ensemble.cpp b/examples/phase_oscillator_ensemble.cpp new file mode 100644 index 00000000..e5073638 --- /dev/null +++ b/examples/phase_oscillator_ensemble.cpp @@ -0,0 +1,150 @@ +/* + * phase_oscillator_ensemble.cpp + * + * Demonstrates the phase transition from an unsynchronized to an synchronized state. + * + * Copyright 2009-2012 Karsten Ahnert and Mario Mulansky. + * Distributed under the Boost Software License, Version 1.0. (See + * accompanying file LICENSE_1_0.txt or copy at + * http://www.boost.org/LICENSE_1_0.txt) + * + */ + +#include +#include + +#include + +#ifndef M_PI //not there on windows +#define M_PI 3.141592653589793 //... +#endif + +#include + +using namespace std; +using namespace boost::numeric::odeint; + +//[ phase_oscillator_ensemble_system_function +typedef vector< double > container_type; + + +pair< double , double > calc_mean_field( const container_type &x ) +{ + size_t n = x.size(); + double cos_sum = 0.0 , sin_sum = 0.0; + for( size_t i=0 ; i cauchy( 0.0 , g ); + boost::variate_generator< boost::mt19937&, boost::cauchy_distribution<> > gen( rng , cauchy ); + generate( m_omega.begin() , m_omega.end() , gen ); + } + + void set_epsilon( double epsilon ) { m_epsilon = epsilon; } + + double get_epsilon( void ) const { return m_epsilon; } + + void operator()( const container_type &x , container_type &dxdt , double /* t */ ) const + { + pair< double , double > mean = calc_mean_field( x ); + for( size_t i=0 ; i + void operator()( const State &x , double t ) + { + pair< double , double > mean = calc_mean_field( x ); + m_K_mean += mean.first; + ++m_count; + } + + double get_K_mean( void ) const { return ( m_count != 0 ) ? m_K_mean / double( m_count ) : 0.0 ; } + + void reset( void ) { m_K_mean = 0.0; m_count = 0; } +}; +//] + + + + + + + + +int main( int argc , char **argv ) +{ + //[ phase_oscillator_ensemble_integration + const size_t n = 16384; + const double dt = 0.1; + + container_type x( n ); + + boost::mt19937 rng; + boost::uniform_real<> unif( 0.0 , 2.0 * M_PI ); + boost::variate_generator< boost::mt19937&, boost::uniform_real<> > gen( rng , unif ); + + // gamma = 1, the phase transition occurs at epsilon = 2 + phase_ensemble ensemble( n , 1.0 ); + statistics_observer obs; + + for( double epsilon = 0.0 ; epsilon < 5.0 ; epsilon += 0.1 ) + { + ensemble.set_epsilon( epsilon ); + obs.reset(); + + // start with random initial conditions + generate( x.begin() , x.end() , gen ); + + // calculate some transients steps + integrate_const( runge_kutta4< container_type >() , boost::ref( ensemble ) , x , 0.0 , 10.0 , dt ); + + // integrate and compute the statistics + integrate_const( runge_kutta4< container_type >() , boost::ref( ensemble ) , x , 0.0 , 100.0 , dt , boost::ref( obs ) ); + cout << epsilon << "\t" << obs.get_K_mean() << endl; + } + + + //] + + return 0; +} diff --git a/examples/point_type.hpp b/examples/point_type.hpp new file mode 100644 index 00000000..f397dee4 --- /dev/null +++ b/examples/point_type.hpp @@ -0,0 +1,177 @@ +/* Boost libs/numeric/odeint/examples/point_type.hpp + + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + solar system example for Hamiltonian stepper + + Distributed under the Boost Software License, Version 1.0. +(See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#ifndef POINT_TYPE_HPP_INCLUDED +#define POINT_TYPE_HPP_INCLUDED + + +#include +#include + + +//[ point_type +/*the point type */ +template< class T , size_t Dim > +class point : + boost::additive1< point< T , Dim > , + boost::additive2< point< T , Dim > , T , + boost::multiplicative2< point< T , Dim > , T + > > > + { + public: + + const static size_t dim = Dim; + typedef T value_type; + typedef point< value_type , dim > point_type; + + // ... + // constructors + //<- + point( void ) + { + for( size_t i=0 ; i 0 ) m_val[0] = x; + if( dim > 1 ) m_val[1] = y; + if( dim > 2 ) m_val[2] = z; + } + //-> + + // ... + // operators + //<- + T operator[]( size_t i ) const { return m_val[i]; } + T& operator[]( size_t i ) { return m_val[i]; } + + point_type& operator+=( const point_type& p ) + { + for( size_t i=0 ; i + + private: + + T m_val[dim]; + }; + + //... + // more operators + //] + + // + // the - operator + // + template< class T , size_t Dim > + point< T , Dim > operator-( const point< T , Dim > &p ) + { + point< T , Dim > tmp; + for( size_t i=0 ; i + T scalar_prod( const point< T , Dim > &p1 , const point< T , Dim > &p2 ) + { + T tmp = 0.0; + for( size_t i=0 ; i + T norm( const point< T , Dim > &p1 ) + { + return scalar_prod( p1 , p1 ); + } + + + + + // + // absolute value + // + template< class T , size_t Dim > + T abs( const point< T , Dim > &p1 ) + { + return sqrt( norm( p1 ) ); + } + + + + + // + // output operator + // + template< class T , size_t Dim > + std::ostream& operator<<( std::ostream &out , const point< T , Dim > &p ) + { + if( Dim > 0 ) out << p[0]; + for( size_t i=1 ; i../../../.. + BOOST_ALL_NO_LIB=1 + : + ; + +lib quadmath : : quadmath shared ; + +exe black_hole : black_hole.cpp quadmath : -std=c++0x ; \ No newline at end of file diff --git a/examples/quadmath/black_hole.cpp b/examples/quadmath/black_hole.cpp new file mode 100644 index 00000000..f8c54823 --- /dev/null +++ b/examples/quadmath/black_hole.cpp @@ -0,0 +1,151 @@ +/* + [auto_generated] + libs/numeric/odeint/examples/black_hole.cpp + + [begin_description] + This example shows how the __float128 from gcc libquadmath can be used with odeint. + [end_description] + + Copyright 2012 Lee Hodgkinson + Copyright 2012 Karsten Ahnert + Copyright 2012 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +extern "C" { +#include +} + +const __float128 zero =strtoflt128 ("0.0", NULL); + +namespace std { + + inline __float128 abs( __float128 x ) + { + return fabsq( x ); + } + + inline __float128 sqrt( __float128 x ) + { + return sqrtq( x ); + } + + inline __float128 pow( __float128 x , __float128 y ) + { + return powq( x , y ); + } + + inline __float128 abs( std::complex< __float128 > x ) + { + return sqrtq( x.real() * x.real() + x.imag() * x.imag() ); + } + + inline std::complex< __float128 > pow( std::complex< __float128> x , __float128 y ) + { + __float128 r = pow( abs(x) , y ); + __float128 phi = atanq( x.imag() / x.real() ); + return std::complex< __float128 >( r * cosq( y * phi ) , r * sinq( y * phi ) ); + } +} + +inline std::ostream& operator<< (std::ostream& os, const __float128& f) { + + char* y = new char[1000]; + quadmath_snprintf(y, 1000, "%.30Qg", f) ; + os.precision(30); + os< +#include +#include +#include +#include + + + +using namespace boost::numeric::odeint; +using namespace std; + +typedef __float128 my_float; +typedef std::vector< std::complex < my_float > > state_type; + +struct radMod +{ + my_float m_om; + my_float m_l; + + radMod( my_float om , my_float l ) + : m_om( om ) , m_l( l ) { } + + void operator()( const state_type &x , state_type &dxdt , my_float r ) const + { + + dxdt[0] = x[1]; + dxdt[1] = -(2*(r-1)/(r*(r-2)))*x[1]-((m_om*m_om*r*r/((r-2)*(r-2)))-(m_l*(m_l+1)/(r*(r-2))))*x[0]; + } +}; + + + + + + + +int main( int argc , char **argv ) +{ + + + state_type x(2); + + my_float re0 = strtoflt128( "-0.00008944230755601224204687038354994353820468" , NULL ); + my_float im0 = strtoflt128( "0.00004472229441850588228136889483397204368247" , NULL ); + my_float re1 = strtoflt128( "-4.464175354293244250869336196695966076150E-6 " , NULL ); + my_float im1 = strtoflt128( "-8.950483248390306670770345406051469584488E-6" , NULL ); + + x[0] = complex< my_float >( re0 ,im0 ); + x[1] = complex< my_float >( re1 ,im1 ); + + const my_float dt =strtoflt128 ("-0.001", NULL); + const my_float start =strtoflt128 ("10000.0", NULL); + const my_float end =strtoflt128 ("9990.0", NULL); + const my_float omega =strtoflt128 ("2.0", NULL); + const my_float ell =strtoflt128 ("1.0", NULL); + + + + my_float abs_err = strtoflt128( "1.0E-15" , NULL ) , rel_err = strtoflt128( "1.0E-10" , NULL ); + my_float a_x = strtoflt128( "1.0" , NULL ) , a_dxdt = strtoflt128( "1.0" , NULL ); + + typedef runge_kutta_dopri5< state_type, my_float > dopri5_type; + typedef controlled_runge_kutta< dopri5_type > controlled_dopri5_type; + typedef dense_output_runge_kutta< controlled_dopri5_type > dense_output_dopri5_type; + + dense_output_dopri5_type dopri5( controlled_dopri5_type( default_error_checker< my_float >( abs_err , rel_err , a_x , a_dxdt ) ) ); + + std::for_each( make_adaptive_time_iterator_begin(dopri5 , radMod(omega , ell) , x , start , end , dt) , + make_adaptive_time_iterator_end(dopri5 , radMod(omega , ell) , x ) , + []( const std::pair< state_type&, my_float > &x ) { + std::cout << x.second << ", " << x.first[0].real() << "\n"; } + ); + + + + return 0; +} diff --git a/examples/resizing_lattice.cpp b/examples/resizing_lattice.cpp new file mode 100644 index 00000000..70993e99 --- /dev/null +++ b/examples/resizing_lattice.cpp @@ -0,0 +1,168 @@ +/* + * resizing_lattice.cpp + * + * Demonstrates the usage of resizing of the state type during integration. + * Examplary system is a strongly nonlinear, disordered Hamiltonian lattice + * where the spreading of energy is invastigated + * + * Copyright 2009-2012 Karsten Ahnert and Mario Mulansky. + * Distributed under the Boost Software License, Version 1.0. (See + * accompanying file LICENSE_1_0.txt or copy at + * http://www.boost.org/LICENSE_1_0.txt) + * + */ + +#include +#include + +#include + +#include +#include + +using namespace std; +using namespace boost::numeric::odeint; + +//[ resizing_lattice_system_class +typedef vector< double > coord_type; +typedef pair< coord_type , coord_type > state_type; + +struct compacton_lattice +{ + const int m_max_N; + const double m_beta; + int m_pot_start_index; + vector< double > m_pot; + + compacton_lattice( int max_N , double beta , int pot_start_index ) + : m_max_N( max_N ) , m_beta( beta ) , m_pot_start_index( pot_start_index ) , m_pot( max_N ) + { + srand( time( NULL ) ); + // fill random potential with iid values from [0,1] + boost::mt19937 rng; + boost::uniform_real<> unif( 0.0 , 1.0 ); + boost::variate_generator< boost::mt19937&, boost::uniform_real<> > gen( rng , unif ); + generate( m_pot.begin() , m_pot.end() , gen ); + } + + void operator()( const coord_type &q , coord_type &dpdt ) + { + // calculate dpdt = -dH/dq of this hamiltonian system + // dp_i/dt = - V_i * q_i^3 - beta*(q_i - q_{i-1})^3 + beta*(q_{i+1} - q_i)^3 + const int N = q.size(); + double diff = q[0] - q[N-1]; + for( int i=0 ; i hamiltonian_stepper; + hamiltonian_stepper stepper; + hamiltonian_stepper::state_type state = make_pair( q , p ); + //] + + //[ resizing_lattice_steps_loop + double t = 0.0; + const double dt = 0.1; + const int steps = 10000; + for( int step = 0 ; step < steps ; ++step ) + { + stepper.do_step( boost::ref(lattice) , state , t , dt ); + lattice.energy_distribution( state.first , state.second , distr ); + if( distr[10] > 1E-150 ) + { + do_resize( state.first , state.second , distr , state.first.size()+20 ); + rotate( state.first.begin() , state.first.end()-20 , state.first.end() ); + rotate( state.second.begin() , state.second.end()-20 , state.second.end() ); + lattice.change_pot_start( -20 ); + cout << t << ": resized left to " << distr.size() << ", energy = " << lattice.energy( state.first , state.second ) << endl; + } + if( distr[distr.size()-10] > 1E-150 ) + { + do_resize( state.first , state.second , distr , state.first.size()+20 ); + cout << t << ": resized right to " << distr.size() << ", energy = " << lattice.energy( state.first , state.second ) << endl; + } + t += dt; + } + //] + + cout << "final lattice size: " << distr.size() << ", final energy: " << lattice.energy( state.first , state.second ) << endl; +} diff --git a/examples/simple1d.cpp b/examples/simple1d.cpp new file mode 100644 index 00000000..de1591fd --- /dev/null +++ b/examples/simple1d.cpp @@ -0,0 +1,44 @@ +/* Boost libs/numeric/odeint/examples/simple1d.cpp + + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + example for a simple one-dimensional 1st order ODE + + Distributed under the Boost Software License, Version 1.0. +(See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#include +#include + +using namespace std; +using namespace boost::numeric::odeint; + + +/* we solve the simple ODE x' = 3/(2t^2) + x/(2t) + * with initial condition x(1) = 0. + * Analytic solution is x(t) = sqrt(t) - 1/t + */ + +void rhs( const double x , double &dxdt , const double t ) +{ + dxdt = 3.0/(2.0*t*t) + x/(2.0*t); +} + +void write_cout( const double &x , const double t ) +{ + cout << t << '\t' << x << endl; +} + +// state_type = value_type = deriv_type = time_type = double +typedef runge_kutta_dopri5< double , double , double , double , vector_space_algebra , default_operations , never_resizer > stepper_type; + +int main() +{ + double x = 0.0; //initial value x(1) = 0 + // use dopri5 with stepsize control and allowed errors 10^-12, integrate t=1...10 + integrate_adaptive( make_controlled( 1E-12 , 1E-12 , stepper_type() ) , rhs , x , 1.0 , 10.0 , 0.1 , write_cout ); +} diff --git a/examples/solar_system.agr b/examples/solar_system.agr new file mode 100644 index 00000000..87f8c38e --- /dev/null +++ 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+#include + +#include + +#include "point_type.hpp" + +//[ container_type_definition +// we simulate 5 planets and the sun +const size_t n = 6; + +typedef point< double , 3 > point_type; +typedef boost::array< point_type , n > container_type; +typedef boost::array< double , n > mass_type; +//] + + + + + + + +//[ coordinate_function +const double gravitational_constant = 2.95912208286e-4; + +struct solar_system_coor +{ + const mass_type &m_masses; + + solar_system_coor( const mass_type &masses ) : m_masses( masses ) { } + + void operator()( const container_type &p , container_type &dqdt ) const + { + for( size_t i=0 ; i + void operator()( const State &x , double t ) const + { + container_type &q = x.first; + m_out << t; + for( size_t i=0 ; i stepper_type; + const double dt = 100.0; + + integrate_const( + stepper_type() , + make_pair( solar_system_coor( masses ) , solar_system_momentum( masses ) ) , + make_pair( boost::ref( q ) , boost::ref( p ) ) , + 0.0 , 200000.0 , dt , streaming_observer( cout ) ); + //] + + + return 0; +} + + +/* +Plot with gnuplot: +p "solar_system.dat" u 2:4 w l,"solar_system.dat" u 5:7 w l,"solar_system.dat" u 8:10 w l,"solar_system.dat" u 11:13 w l,"solar_system.dat" u 14:16 w l,"solar_system.dat" u 17:19 w l + */ diff --git a/examples/stepper_details.cpp b/examples/stepper_details.cpp new file mode 100644 index 00000000..ccafbb12 --- /dev/null +++ b/examples/stepper_details.cpp @@ -0,0 +1,197 @@ +/* + * stepper_details.cpp + * + * This example demonstrates some details about the steppers in odeint. + * + * + * Copyright 2009-2012 Karsten Ahnert + * Copyright 2009-2012 Mario Mulansky + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#include +#include + +#include + +using namespace std; +using namespace boost::numeric::odeint; + +const size_t N = 3; + +typedef boost::array< double , N > state_type; + +//[ system_function_structure +void sys( const state_type & /*x*/ , state_type & /*dxdt*/ , const double /*t*/ ) +{ + // ... +} +//] + +void sys1( const state_type &/*x*/ , state_type &/*dxdt*/ , const double /*t*/ ) +{ +} + +void sys2( const state_type &/*x*/ , state_type &/*dxdt*/ , const double /*t*/ ) +{ +} + + +//[ symplectic_stepper_detail_system_function +typedef boost::array< double , 1 > vector_type; + + +struct harm_osc_f1 +{ + void operator()( const vector_type &p , vector_type &dqdt ) + { + dqdt[0] = p[0]; + } +}; + +struct harm_osc_f2 +{ + void operator()( const vector_type &q , vector_type &dpdt ) + { + dpdt[0] = -q[0]; + } +}; +//] + +//[ symplectic_stepper_detail_system_class +struct harm_osc +{ + void f1( const vector_type &p , vector_type &dqdt ) const + { + dqdt[0] = p[0]; + } + + void f2( const vector_type &q , vector_type &dpdt ) const + { + dpdt[0] = -q[0]; + } +}; +//] + +int main( int argc , char **argv ) +{ + using namespace std; + + // Explicit stepper example + { + double t( 0.0 ) , dt( 0.1 ); + state_type in , out , dxdtin , inout; + //[ explicit_stepper_detail_example + runge_kutta4< state_type > rk; + rk.do_step( sys1 , inout , t , dt ); // In-place transformation of inout + rk.do_step( sys2 , inout , t , dt ); // call with different system: Ok + rk.do_step( sys1 , in , t , out , dt ); // Out-of-place transformation + rk.do_step( sys1 , inout , dxdtin , t , dt ); // In-place tranformation of inout + rk.do_step( sys1 , in , dxdtin , t , out , dt ); // Out-of-place transformation + //] + } + + + + // FSAL stepper example + { + double t( 0.0 ) , dt( 0.1 ); + state_type in , in2 , in3 , out , dxdtin , dxdtout , inout , dxdtinout; + //[ fsal_stepper_detail_example + runge_kutta_dopri5< state_type > rk; + rk.do_step( sys1 , in , t , out , dt ); + rk.do_step( sys2 , in , t , out , dt ); // DONT do this, sys1 is assumed + + rk.do_step( sys2 , in2 , t , out , dt ); + rk.do_step( sys2 , in3 , t , out , dt ); // DONT do this, in2 is assumed + + rk.do_step( sys1 , inout , dxdtinout , t , dt ); + rk.do_step( sys2 , inout , dxdtinout , t , dt ); // Ok, internal derivative is not used, dxdtinout is updated + + rk.do_step( sys1 , in , dxdtin , t , out , dxdtout , dt ); + rk.do_step( sys2 , in , dxdtin , t , out , dxdtout , dt ); // Ok, internal derivative is not used + //] + } + + + // Symplectic harmonic oscillator example + { + double t( 0.0 ) , dt( 0.1 ); + //[ symplectic_stepper_detail_example + pair< vector_type , vector_type > x; + x.first[0] = 1.0; x.second[0] = 0.0; + symplectic_rkn_sb3a_mclachlan< vector_type > rkn; + rkn.do_step( make_pair( harm_osc_f1() , harm_osc_f2() ) , x , t , dt ); + //] + + //[ symplectic_stepper_detail_system_class_example + harm_osc h; + rkn.do_step( make_pair( boost::bind( &harm_osc::f1 , h , _1 , _2 ) , boost::bind( &harm_osc::f2 , h , _1 , _2 ) ) , + x , t , dt ); + //] + } + + // Simplified harmonic oscillator example + { + double t = 0.0, dt = 0.1; + //[ simplified_symplectic_stepper_example + pair< vector_type , vector_type > x; + x.first[0] = 1.0; x.second[0] = 0.0; + symplectic_rkn_sb3a_mclachlan< vector_type > rkn; + rkn.do_step( harm_osc_f1() , x , t , dt ); + //] + + vector_type q = {{ 1.0 }} , p = {{ 0.0 }}; + //[ symplectic_stepper_detail_ref_usage + rkn.do_step( harm_osc_f1() , make_pair( boost::ref( q ) , boost::ref( p ) ) , t , dt ); + rkn.do_step( harm_osc_f1() , q , p , t , dt ); + rkn.do_step( make_pair( harm_osc_f1() , harm_osc_f2() ) , q , p , t , dt ); + //] + } + + // adams_bashforth_moulton stepper example + { + double t = 0.0 , dt = 0.1; + state_type inout; + //[ multistep_detail_example + adams_bashforth_moulton< 5 , state_type > abm; + abm.initialize( sys , inout , t , dt ); + abm.do_step( sys , inout , t , dt ); + //] + + //[ multistep_detail_own_stepper_initialization + abm.initialize( runge_kutta_fehlberg78< state_type >() , sys , inout , t , dt ); + //] + } + + + + // dense output stepper examples + { + double t = 0.0 , dt = 0.1; + state_type in; + //[ dense_output_detail_example + dense_output_runge_kutta< controlled_runge_kutta< runge_kutta_dopri5< state_type > > > dense; + dense.initialize( in , t , dt ); + pair< double , double > times = dense.do_step( sys ); + //] + + state_type inout; + double t_start = 0.0 , t_end = 1.0; + //[ dense_output_detail_generation1 + typedef boost::numeric::odeint::result_of::make_dense_output< + runge_kutta_dopri5< state_type > >::type dense_stepper_type; + dense_stepper_type dense2 = make_dense_output( 1.0e-6 , 1.0e-6 , runge_kutta_dopri5< state_type >() ); + //] + + //[ dense_output_detail_generation2 + integrate_const( make_dense_output( 1.0e-6 , 1.0e-6 , runge_kutta_dopri5< state_type >() ) , sys , inout , t_start , t_end , dt ); + //] + } + + + return 0; +} diff --git a/examples/stiff_system.cpp b/examples/stiff_system.cpp new file mode 100644 index 00000000..b6886eb8 --- /dev/null +++ b/examples/stiff_system.cpp @@ -0,0 +1,117 @@ +/* + * rosenbrock4.cpp + * + * Copyright 2009-2012 Karsten Ahnert + * Copyright 2009-2012 Mario Mulansky + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#include +#include +#include + +#include + +#include + +#include +#include + +using namespace std; +using namespace boost::numeric::odeint; +namespace phoenix = boost::phoenix; + + + +//[ stiff_system_definition +typedef boost::numeric::ublas::vector< double > vector_type; +typedef boost::numeric::ublas::matrix< double > matrix_type; + +struct stiff_system +{ + void operator()( const vector_type &x , vector_type &dxdt , double /* t */ ) + { + dxdt[ 0 ] = -101.0 * x[ 0 ] - 100.0 * x[ 1 ]; + dxdt[ 1 ] = x[ 0 ]; + } +}; + +struct stiff_system_jacobi +{ + void operator()( const vector_type & /* x */ , matrix_type &J , const double & /* t */ , vector_type &dfdt ) + { + J( 0 , 0 ) = -101.0; + J( 0 , 1 ) = -100.0; + J( 1 , 0 ) = 1.0; + J( 1 , 1 ) = 0.0; + dfdt[0] = 0.0; + dfdt[1] = 0.0; + } +}; +//] + + + +/* +//[ stiff_system_alternative_definition +typedef boost::numeric::ublas::vector< double > vector_type; +typedef boost::numeric::ublas::matrix< double > matrix_type; + +struct stiff_system +{ + template< class State > + void operator()( const State &x , State &dxdt , double t ) + { + ... + } +}; + +struct stiff_system_jacobi +{ + template< class State , class Matrix > + void operator()( const State &x , Matrix &J , const double &t , State &dfdt ) + { + ... + } +}; +//] + */ + + + +int main( int argc , char **argv ) +{ +// typedef rosenbrock4< double > stepper_type; +// typedef rosenbrock4_controller< stepper_type > controlled_stepper_type; +// typedef rosenbrock4_dense_output< controlled_stepper_type > dense_output_type; + //[ integrate_stiff_system + vector_type x( 2 , 1.0 ); + + size_t num_of_steps = integrate_const( make_dense_output< rosenbrock4< double > >( 1.0e-6 , 1.0e-6 ) , + make_pair( stiff_system() , stiff_system_jacobi() ) , + x , 0.0 , 50.0 , 0.01 , + cout << phoenix::arg_names::arg2 << " " << phoenix::arg_names::arg1[0] << "\n" ); + //] + clog << num_of_steps << endl; + + + +// typedef runge_kutta_dopri5< vector_type > dopri5_type; +// typedef controlled_runge_kutta< dopri5_type > controlled_dopri5_type; +// typedef dense_output_runge_kutta< controlled_dopri5_type > dense_output_dopri5_type; + //[ integrate_stiff_system_alternative + + vector_type x2( 2 , 1.0 ); + + size_t num_of_steps2 = integrate_const( make_dense_output< runge_kutta_dopri5< vector_type > >( 1.0e-6 , 1.0e-6 ) , + stiff_system() , x2 , 0.0 , 50.0 , 0.01 , + cout << phoenix::arg_names::arg2 << " " << phoenix::arg_names::arg1[0] << "\n" ); + //] + clog << num_of_steps2 << endl; + + + return 0; +} diff --git a/examples/stochastic_euler.cpp b/examples/stochastic_euler.cpp new file mode 100644 index 00000000..ccb9f7a7 --- /dev/null +++ b/examples/stochastic_euler.cpp @@ -0,0 +1,146 @@ +/* + libs/numeric/odeint/examples/stochastic_euler.hpp + + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + Stochastic euler stepper example and Ornstein-Uhlenbeck process + + Distributed under the Boost Software License, Version 1.0. +(See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#include +#include +#include +#include + +#include + + +/* +//[ stochastic_euler_class_definition +template< size_t N > class stochastic_euler +{ +public: + + typedef boost::array< double , N > state_type; + typedef boost::array< double , N > deriv_type; + typedef double value_type; + typedef double time_type; + typedef unsigned short order_type; + typedef boost::numeric::odeint::stepper_tag stepper_category; + + static order_type order( void ) { return 1; } + + // ... +}; +//] +*/ + + +/* +//[ stochastic_euler_do_step +template< size_t N > class stochastic_euler +{ +public: + + // ... + + template< class System > + void do_step( System system , state_type &x , time_type t , time_type dt ) const + { + deriv_type det , stoch ; + system.first( x , det ); + system.second( x , stoch ); + for( size_t i=0 ; i +class stochastic_euler +{ +public: + + typedef boost::array< double , N > state_type; + typedef boost::array< double , N > deriv_type; + typedef double value_type; + typedef double time_type; + typedef unsigned short order_type; + + typedef boost::numeric::odeint::stepper_tag stepper_category; + + static order_type order( void ) { return 1; } + + template< class System > + void do_step( System system , state_type &x , time_type t , time_type dt ) const + { + deriv_type det , stoch ; + system.first( x , det ); + system.second( x , stoch ); + for( size_t i=0 ; i state_type; + +struct ornstein_det +{ + void operator()( const state_type &x , state_type &dxdt ) const + { + dxdt[0] = -x[0]; + } +}; + +struct ornstein_stoch +{ + boost::mt19937 m_rng; + boost::normal_distribution<> m_dist; + + ornstein_stoch( double sigma ) : m_rng() , m_dist( 0.0 , sigma ) { } + + void operator()( const state_type &x , state_type &dxdt ) + { + dxdt[0] = m_dist( m_rng ); + } +}; +//] + +struct streaming_observer +{ + template< class State > + void operator()( const State &x , double t ) const + { + std::cout << t << "\t" << x[0] << "\n"; + } +}; + + +int main( int argc , char **argv ) +{ + using namespace std; + using namespace boost::numeric::odeint; + + //[ ornstein_uhlenbeck_main + double dt = 0.1; + state_type x = {{ 1.0 }}; + integrate_const( stochastic_euler< N >() , make_pair( ornstein_det() , ornstein_stoch( 1.0 ) ) , + x , 0.0 , 10.0 , dt , streaming_observer() ); + //] + return 0; +} diff --git a/examples/stuart_landau.cpp b/examples/stuart_landau.cpp new file mode 100644 index 00000000..10891b59 --- /dev/null +++ b/examples/stuart_landau.cpp @@ -0,0 +1,87 @@ +/* + * stuart_landau.cpp + * + * This example demonstrates how one can use odeint can be used with state types consisting of complex variables. + * + * Copyright 2009-2012 Karsten Ahnert and Mario Mulansky. + * Distributed under the Boost Software License, Version 1.0. (See + * accompanying file LICENSE_1_0.txt or copy at + * http://www.boost.org/LICENSE_1_0.txt) + */ + +#include +#include +#include + +#include + +using namespace std; +using namespace boost::numeric::odeint; + +//[ stuart_landau_system_function +typedef complex< double > state_type; + +struct stuart_landau +{ + double m_eta; + double m_alpha; + + stuart_landau( double eta = 1.0 , double alpha = 1.0 ) + : m_eta( eta ) , m_alpha( alpha ) { } + + void operator()( const state_type &x , state_type &dxdt , double t ) const + { + const complex< double > I( 0.0 , 1.0 ); + dxdt = ( 1.0 + m_eta * I ) * x - ( 1.0 + m_alpha * I ) * norm( x ) * x; + } +}; +//] + + +/* +//[ stuart_landau_system_function_alternative +double eta = 1.0; +double alpha = 1.0; + +void stuart_landau( const state_type &x , state_type &dxdt , double t ) +{ + const complex< double > I( 0.0 , 1.0 ); + dxdt[0] = ( 1.0 + m_eta * I ) * x[0] - ( 1.0 + m_alpha * I ) * norm( x[0] ) * x[0]; +} +//] +*/ + + +struct streaming_observer +{ + std::ostream& m_out; + + streaming_observer( std::ostream &out ) : m_out( out ) { } + + template< class State > + void operator()( const State &x , double t ) const + { + m_out << t; + m_out << "\t" << x.real() << "\t" << x.imag() ; + m_out << "\n"; + } +}; + + + + +int main( int argc , char **argv ) +{ + //[ stuart_landau_integration + state_type x = complex< double >( 1.0 , 0.0 ); + + const double dt = 0.1; + + typedef runge_kutta4< state_type , double , state_type , double , + vector_space_algebra > stepper_type; + + integrate_const( stepper_type() , stuart_landau( 2.0 , 1.0 ) , x , 0.0 , 10.0 , dt , streaming_observer( cout ) ); + //] + + return 0; +} diff --git a/examples/thrust/Makefile b/examples/thrust/Makefile new file mode 100644 index 00000000..7c0dc1d7 --- /dev/null +++ b/examples/thrust/Makefile @@ -0,0 +1,66 @@ +# Copyright 2009-2012 Karsten Ahnert +# Copyright 2009-2012 Mario Mulansky +# +# Distributed under the Boost Software License, Version 1.0. +# (See accompanying file LICENSE_1_0.txt or +# copy at http://www.boost.org/LICENSE_1_0.txt) + + + +# CUDA_ROOT = /home/karsten/boost/cuda4.1/cuda/ +CUDA_ROOT = /usr/local/cuda +ARCH = sm_13 + +CC = gcc-4.4 +CXX = gcc-4.4 +NVCC = $(CUDA_ROOT)/bin/nvcc +# NVCC = g++ + +INCLUDES += -I$(BOOST_ROOT) -I$(THRUST_ROOT) -I$(CUDA_ROOT)/include -I../../../../.. + +NVCCFLAGS = -O3 $(INCLUDES) -arch $(ARCH) --compiler-bindir=/usr/bin/g++-4.4 -Xcompiler -fopenmp -DTHRUST_DEVICE_BACKEND=THRUST_DEVICE_BACKEND_OMP +# NVCCFLAGS = -O3 $(INCLUDES) -arch $(ARCH) --compiler-bindir=/usr/bin/g++-4.3 -Xcompiler -fopenmp -DTHRUST_DEVICE_BACKEND=THRUST_DEVICE_BACKEND_OMP + +# NVCCFLAGS = -O3 $(INCLUDES) -arch $(ARCH) --compiler-bindir=/usr/bin/g++-4.3 + +#--compiler-bindir=/usr/bin/g++-4.4 +#-Xcompiler -fopenmp -DTHRUST_DEVICE_BACKEND=THRUST_DEVICE_BACKEND_OMP +# NVCCFLAGS = -O3 $(INCLUDES) -arch $(ARCH) --compiler-bindir=/usr/bin/g++-4.3 +#-Xcompiler -fopenmp -DTHRUST_DEVICE_BACKEND=THRUST_DEVICE_BACKEND_OMP + + +LDLIBS = -lcudart -lgomp +LDFLAGS = -L$(CUDA_ROOT)/lib64 + +%.co : %.cu + $(NVCC) $(NVCCFLAGS) -c $< -o $@ + + +all : phase_oscillator_chain phase_oscillator_ensemble lorenz_parameters relaxation + + +phase_oscillator_chain.co : phase_oscillator_chain.cu +phase_oscillator_chain : phase_oscillator_chain.co + $(CC) -o phase_oscillator_chain $(LDFLAGS) $(LDLIBS) phase_oscillator_chain.co + + + +phase_oscillator_ensemble.co : phase_oscillator_ensemble.cu +phase_oscillator_ensemble : phase_oscillator_ensemble.co + $(CC) -o phase_oscillator_ensemble $(LDFLAGS) $(LDLIBS) phase_oscillator_ensemble.co + + + +lorenz_parameters : lorenz_parameters.co + $(CC) -o lorenz_parameters $(LDFLAGS) $(LDLIBS) lorenz_parameters.co +lorenz_parameters.co : lorenz_parameters.cu + + +relaxation : relaxation.co + $(CC) -o relaxation $(LDFLAGS) $(LDLIBS) relaxation.co +relaxation.co : relaxation.cu + + + +clean : + -rm *~ *.o *.co phase_oscillator_chain phase_oscillator_ensemble lorenz_parameters relaxation diff --git a/examples/thrust/lorenz_parameters.cu b/examples/thrust/lorenz_parameters.cu new file mode 100644 index 00000000..5eaef00a --- /dev/null +++ b/examples/thrust/lorenz_parameters.cu @@ -0,0 +1,299 @@ + /* + * phase_oscillator_ensemble.cu + * + * The example how the phase_oscillator ensemble can be implemented using CUDA and thrust + * + * Created on: July 15, 2011 + * Author: karsten + */ + + +#include +#include +#include + + +#include +#include +#include + +#include + +#include +#include +#include + +#include +#include +#include + + +using namespace std; +using namespace boost::numeric::odeint; + +//change this to float if your device does not support double computation +typedef double value_type; + +//change this to host_vector< ... > of you want to run on CPU +typedef thrust::device_vector< value_type > state_type; +typedef thrust::device_vector< size_t > index_vector_type; +// typedef thrust::host_vector< value_type > state_type; +// typedef thrust::host_vector< size_t > index_vector_type; + + +const value_type sigma = 10.0; +const value_type b = 8.0 / 3.0; + + +//[ thrust_lorenz_parameters_define_simple_system +struct lorenz_system +{ + struct lorenz_functor + { + template< class T > + __host__ __device__ + void operator()( T t ) const + { + // unpack the parameter we want to vary and the Lorenz variables + value_type R = thrust::get< 3 >( t ); + value_type x = thrust::get< 0 >( t ); + value_type y = thrust::get< 1 >( t ); + value_type z = thrust::get< 2 >( t ); + thrust::get< 4 >( t ) = sigma * ( y - x ); + thrust::get< 5 >( t ) = R * x - y - x * z; + thrust::get< 6 >( t ) = -b * z + x * y ; + + } + }; + + lorenz_system( size_t N , const state_type &beta ) + : m_N( N ) , m_beta( beta ) { } + + template< class State , class Deriv > + void operator()( const State &x , Deriv &dxdt , value_type t ) const + { + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( + boost::begin( x ) , + boost::begin( x ) + m_N , + boost::begin( x ) + 2 * m_N , + m_beta.begin() , + boost::begin( dxdt ) , + boost::begin( dxdt ) + m_N , + boost::begin( dxdt ) + 2 * m_N ) ) , + thrust::make_zip_iterator( thrust::make_tuple( + boost::begin( x ) + m_N , + boost::begin( x ) + 2 * m_N , + boost::begin( x ) + 3 * m_N , + m_beta.begin() , + boost::begin( dxdt ) + m_N , + boost::begin( dxdt ) + 2 * m_N , + boost::begin( dxdt ) + 3 * m_N ) ) , + lorenz_functor() ); + } + size_t m_N; + const state_type &m_beta; +}; +//] + +struct lorenz_perturbation_system +{ + struct lorenz_perturbation_functor + { + template< class T > + __host__ __device__ + void operator()( T t ) const + { + value_type R = thrust::get< 1 >( t ); + value_type x = thrust::get< 0 >( thrust::get< 0 >( t ) ); + value_type y = thrust::get< 1 >( thrust::get< 0 >( t ) ); + value_type z = thrust::get< 2 >( thrust::get< 0 >( t ) ); + value_type dx = thrust::get< 3 >( thrust::get< 0 >( t ) ); + value_type dy = thrust::get< 4 >( thrust::get< 0 >( t ) ); + value_type dz = thrust::get< 5 >( thrust::get< 0 >( t ) ); + thrust::get< 0 >( thrust::get< 2 >( t ) ) = sigma * ( y - x ); + thrust::get< 1 >( thrust::get< 2 >( t ) ) = R * x - y - x * z; + thrust::get< 2 >( thrust::get< 2 >( t ) ) = -b * z + x * y ; + thrust::get< 3 >( thrust::get< 2 >( t ) ) = sigma * ( dy - dx ); + thrust::get< 4 >( thrust::get< 2 >( t ) ) = ( R - z ) * dx - dy - x * dz; + thrust::get< 5 >( thrust::get< 2 >( t ) ) = y * dx + x * dy - b * dz; + } + }; + + lorenz_perturbation_system( size_t N , const state_type &beta ) + : m_N( N ) , m_beta( beta ) { } + + template< class State , class Deriv > + void operator()( const State &x , Deriv &dxdt , value_type t ) const + { + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( + thrust::make_zip_iterator( thrust::make_tuple( + boost::begin( x ) , + boost::begin( x ) + m_N , + boost::begin( x ) + 2 * m_N , + boost::begin( x ) + 3 * m_N , + boost::begin( x ) + 4 * m_N , + boost::begin( x ) + 5 * m_N ) ) , + m_beta.begin() , + thrust::make_zip_iterator( thrust::make_tuple( + boost::begin( dxdt ) , + boost::begin( dxdt ) + m_N , + boost::begin( dxdt ) + 2 * m_N , + boost::begin( dxdt ) + 3 * m_N , + boost::begin( dxdt ) + 4 * m_N , + boost::begin( dxdt ) + 5 * m_N ) ) + ) ) , + thrust::make_zip_iterator( thrust::make_tuple( + thrust::make_zip_iterator( thrust::make_tuple( + boost::begin( x ) + m_N , + boost::begin( x ) + 2 * m_N , + boost::begin( x ) + 3 * m_N , + boost::begin( x ) + 4 * m_N , + boost::begin( x ) + 5 * m_N , + boost::begin( x ) + 6 * m_N ) ) , + m_beta.begin() , + thrust::make_zip_iterator( thrust::make_tuple( + boost::begin( dxdt ) + m_N , + boost::begin( dxdt ) + 2 * m_N , + boost::begin( dxdt ) + 3 * m_N , + boost::begin( dxdt ) + 4 * m_N , + boost::begin( dxdt ) + 5 * m_N , + boost::begin( dxdt ) + 6 * m_N ) ) + ) ) , + lorenz_perturbation_functor() ); + } + + size_t m_N; + const state_type &m_beta; +}; + +struct lyap_observer +{ + //[thrust_lorenz_parameters_observer_functor + struct lyap_functor + { + template< class T > + __host__ __device__ + void operator()( T t ) const + { + value_type &dx = thrust::get< 0 >( t ); + value_type &dy = thrust::get< 1 >( t ); + value_type &dz = thrust::get< 2 >( t ); + value_type norm = sqrt( dx * dx + dy * dy + dz * dz ); + dx /= norm; + dy /= norm; + dz /= norm; + thrust::get< 3 >( t ) += log( norm ); + } + }; + //] + + lyap_observer( size_t N , size_t every = 100 ) + : m_N( N ) , m_lyap( N ) , m_every( every ) , m_count( 0 ) + { + thrust::fill( m_lyap.begin() , m_lyap.end() , 0.0 ); + } + + template< class Lyap > + void fill_lyap( Lyap &lyap ) + { + thrust::copy( m_lyap.begin() , m_lyap.end() , lyap.begin() ); + for( size_t i=0 ; i + void operator()( State &x , value_type t ) + { + if( ( m_count != 0 ) && ( ( m_count % m_every ) == 0 ) ) + { + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( + boost::begin( x ) + 3 * m_N , + boost::begin( x ) + 4 * m_N , + boost::begin( x ) + 5 * m_N , + m_lyap.begin() ) ) , + thrust::make_zip_iterator( thrust::make_tuple( + boost::begin( x ) + 4 * m_N , + boost::begin( x ) + 5 * m_N , + boost::begin( x ) + 6 * m_N , + m_lyap.end() ) ) , + lyap_functor() ); + clog << t << "\n"; + } + ++m_count; + m_t_overall = t; + } + + size_t m_N; + state_type m_lyap; + size_t m_every; + size_t m_count; + value_type m_t_overall; +}; + +const size_t N = 1024*2; +const value_type dt = 0.01; + + +int main( int arc , char* argv[] ) +{ + int driver_version , runtime_version; + cudaDriverGetVersion( &driver_version ); + cudaRuntimeGetVersion ( &runtime_version ); + cout << driver_version << "\t" << runtime_version << endl; + + + //[ thrust_lorenz_parameters_define_beta + vector< value_type > beta_host( N ); + const value_type beta_min = 0.0 , beta_max = 56.0; + for( size_t i=0 ; i stepper_type; + + + lorenz_system lorenz( N , beta ); + lorenz_perturbation_system lorenz_perturbation( N , beta ); + lyap_observer obs( N , 1 ); + + // calculate transients + integrate_adaptive( make_controlled( 1.0e-6 , 1.0e-6 , stepper_type() ) , lorenz , std::make_pair( x.begin() , x.begin() + 3 * N ) , 0.0 , 10.0 , dt ); + + // calculate the Lyapunov exponents -- the main loop + double t = 0.0; + while( t < 10000.0 ) + { + integrate_adaptive( make_controlled( 1.0e-6 , 1.0e-6 , stepper_type() ) , lorenz_perturbation , x , t , t + 1.0 , 0.1 ); + t += 1.0; + obs( x , t ); + } + + vector< value_type > lyap( N ); + obs.fill_lyap( lyap ); + + for( size_t i=0 ; i +#include + +#include +#include +#include + +#include +#include +#include +#include +#include + +using namespace std; + +using namespace boost::numeric::odeint; + + +//change this to float if your device does not support double computation +typedef double value_type; + + +//[ thrust_phase_chain_system +//change this to host_vector< ... > if you want to run on CPU +typedef thrust::device_vector< value_type > state_type; +typedef thrust::device_vector< size_t > index_vector_type; +//typedef thrust::host_vector< value_type > state_type; +//typedef thrust::host_vector< size_t > index_vector_type; + +//<- +/* + * This implements the rhs of the dynamical equation: + * \phi'_0 = \omega_0 + sin( \phi_1 - \phi_0 ) + * \phi'_i = \omega_i + sin( \phi_i+1 - \phi_i ) + sin( \phi_i - \phi_i-1 ) + * \phi'_N-1 = \omega_N-1 + sin( \phi_N-1 - \phi_N-2 ) + */ +//-> +class phase_oscillators +{ + +public: + + struct sys_functor + { + template< class Tuple > + __host__ __device__ + void operator()( Tuple t ) // this functor works on tuples of values + { + // first, unpack the tuple into value, neighbors and omega + const value_type phi = thrust::get<0>(t); + const value_type phi_left = thrust::get<1>(t); // left neighbor + const value_type phi_right = thrust::get<2>(t); // right neighbor + const value_type omega = thrust::get<3>(t); + // the dynamical equation + thrust::get<4>(t) = omega + sin( phi_right - phi ) + sin( phi - phi_left ); + } + }; + + phase_oscillators( const state_type &omega ) + : m_omega( omega ) , m_N( omega.size() ) , m_prev( omega.size() ) , m_next( omega.size() ) + { + // build indices pointing to left and right neighbours + thrust::counting_iterator c( 0 ); + thrust::copy( c , c+m_N-1 , m_prev.begin()+1 ); + m_prev[0] = 0; // m_prev = { 0 , 0 , 1 , 2 , 3 , ... , N-1 } + + thrust::copy( c+1 , c+m_N , m_next.begin() ); + m_next[m_N-1] = m_N-1; // m_next = { 1 , 2 , 3 , ... , N-1 , N-1 } + } + + void operator() ( const state_type &x , state_type &dxdt , const value_type dt ) + { + thrust::for_each( + thrust::make_zip_iterator( + thrust::make_tuple( + x.begin() , + thrust::make_permutation_iterator( x.begin() , m_prev.begin() ) , + thrust::make_permutation_iterator( x.begin() , m_next.begin() ) , + m_omega.begin() , + dxdt.begin() + ) ), + thrust::make_zip_iterator( + thrust::make_tuple( + x.end() , + thrust::make_permutation_iterator( x.begin() , m_prev.end() ) , + thrust::make_permutation_iterator( x.begin() , m_next.end() ) , + m_omega.end() , + dxdt.end()) ) , + sys_functor() + ); + } + +private: + + const state_type &m_omega; + const size_t m_N; + index_vector_type m_prev; + index_vector_type m_next; +}; +//] + +const size_t N = 32768; +const value_type pi = 3.1415926535897932384626433832795029; +const value_type epsilon = 6.0 / ( N * N ); // should be < 8/N^2 to see phase locking +const value_type dt = 0.1; + +int main( int arc , char* argv[] ) +{ + //[ thrust_phase_chain_integration + // create initial conditions and omegas on host: + vector< value_type > x_host( N ); + vector< value_type > omega_host( N ); + for( size_t i=0 ; i stepper; + + // create phase oscillator system function + phase_oscillators sys( omega ); + + // integrate + integrate_const( stepper , sys , x , 0.0 , 10.0 , dt ); + + thrust::copy( x.begin() , x.end() , std::ostream_iterator< value_type >( std::cout , "\n" ) ); + std::cout << std::endl; + //] +} diff --git a/examples/thrust/phase_oscillator_ensemble.cu b/examples/thrust/phase_oscillator_ensemble.cu new file mode 100644 index 00000000..04d31951 --- /dev/null +++ b/examples/thrust/phase_oscillator_ensemble.cu @@ -0,0 +1,281 @@ +/* + * phase_oscillator_ensemble.cu + * + * The example how the phase_oscillator ensemble can be implemented using CUDA and thrust + * + * Created on: July 15, 2011 + * Author: karsten + */ + + +#include +#include +#include +#include + +#include +#include +#include + +#include +#include +#include +#include + +#include +#include + +using namespace std; + +using namespace boost::numeric::odeint; + +/* + * Sorry for that dirty hack, but nvcc has large problems with boost::random. + * + * Nevertheless we need the cauchy distribution from boost::random, and therefore + * we need a generator. Here it is: + */ +struct drand48_generator +{ + typedef double result_type; + result_type operator()( void ) const { return drand48(); } + result_type min( void ) const { return 0.0; } + result_type max( void ) const { return 1.0; } +}; + +//[ thrust_phase_ensemble_state_type +//change this to float if your device does not support double computation +typedef double value_type; + +//change this to host_vector< ... > of you want to run on CPU +typedef thrust::device_vector< value_type > state_type; +// typedef thrust::host_vector< value_type > state_type; +//] + + +//[ thrust_phase_ensemble_mean_field_calculator +struct mean_field_calculator +{ + struct sin_functor : public thrust::unary_function< value_type , value_type > + { + __host__ __device__ + value_type operator()( value_type x) const + { + return sin( x ); + } + }; + + struct cos_functor : public thrust::unary_function< value_type , value_type > + { + __host__ __device__ + value_type operator()( value_type x) const + { + return cos( x ); + } + }; + + static std::pair< value_type , value_type > get_mean( const state_type &x ) + { + //[ thrust_phase_ensemble_sin_sum + value_type sin_sum = thrust::reduce( + thrust::make_transform_iterator( x.begin() , sin_functor() ) , + thrust::make_transform_iterator( x.end() , sin_functor() ) ); + //] + value_type cos_sum = thrust::reduce( + thrust::make_transform_iterator( x.begin() , cos_functor() ) , + thrust::make_transform_iterator( x.end() , cos_functor() ) ); + + cos_sum /= value_type( x.size() ); + sin_sum /= value_type( x.size() ); + + value_type K = sqrt( cos_sum * cos_sum + sin_sum * sin_sum ); + value_type Theta = atan2( sin_sum , cos_sum ); + + return std::make_pair( K , Theta ); + } +}; +//] + + + +//[ thrust_phase_ensemble_sys_function +class phase_oscillator_ensemble +{ + +public: + + struct sys_functor + { + value_type m_K , m_Theta , m_epsilon; + + sys_functor( value_type K , value_type Theta , value_type epsilon ) + : m_K( K ) , m_Theta( Theta ) , m_epsilon( epsilon ) { } + + template< class Tuple > + __host__ __device__ + void operator()( Tuple t ) + { + thrust::get<2>(t) = thrust::get<1>(t) + m_epsilon * m_K * sin( m_Theta - thrust::get<0>(t) ); + } + }; + + // ... + //<- + phase_oscillator_ensemble( size_t N , value_type g = 1.0 , value_type epsilon = 1.0 ) + : m_omega() , m_N( N ) , m_epsilon( epsilon ) + { + create_frequencies( g ); + } + + void create_frequencies( value_type g ) + { + boost::cauchy_distribution< value_type > cauchy( 0.0 , g ); +// boost::variate_generator< boost::mt19937&, boost::cauchy_distribution< value_type > > gen( rng , cauchy ); + drand48_generator d48; + vector< value_type > omega( m_N ); + for( size_t i=0 ; i + + void operator() ( const state_type &x , state_type &dxdt , const value_type dt ) const + { + std::pair< value_type , value_type > mean_field = mean_field_calculator::get_mean( x ); + + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( x.begin() , m_omega.begin() , dxdt.begin() ) ), + thrust::make_zip_iterator( thrust::make_tuple( x.end() , m_omega.end() , dxdt.end()) ) , + sys_functor( mean_field.first , mean_field.second , m_epsilon ) + ); + } + + // ... + //<- +private: + + state_type m_omega; + const size_t m_N; + value_type m_epsilon; + //-> +}; +//] + + +//[ thrust_phase_ensemble_observer +struct statistics_observer +{ + value_type m_K_mean; + size_t m_count; + + statistics_observer( void ) + : m_K_mean( 0.0 ) , m_count( 0 ) { } + + template< class State > + void operator()( const State &x , value_type t ) + { + std::pair< value_type , value_type > mean = mean_field_calculator::get_mean( x ); + m_K_mean += mean.first; + ++m_count; + } + + value_type get_K_mean( void ) const { return ( m_count != 0 ) ? m_K_mean / value_type( m_count ) : 0.0 ; } + + void reset( void ) { m_K_mean = 0.0; m_count = 0; } +}; +//] + + + +// const size_t N = 16384 * 128; +const size_t N = 16384; +const value_type pi = 3.1415926535897932384626433832795029; +const value_type dt = 0.1; +const value_type d_epsilon = 0.1; +const value_type epsilon_min = 0.0; +const value_type epsilon_max = 5.0; +const value_type t_transients = 10.0; +const value_type t_max = 100.0; + +int main( int arc , char* argv[] ) +{ + // initial conditions on host + vector< value_type > x_host( N ); + for( size_t i=0 ; i stepper_type; + //] + + ofstream fout( "phase_ensemble_dopri5.dat" ); + timer.restart(); + for( value_type epsilon = epsilon_min ; epsilon < epsilon_max ; epsilon += d_epsilon ) + { + ensemble.set_epsilon( epsilon ); + statistics_observer obs; + state_type x = x_host; + + timer_local.restart(); + + // calculate some transients steps + //[ thrust_phase_ensemble_integration + size_t steps1 = integrate_const( make_controlled( 1.0e-6 , 1.0e-6 , stepper_type() ) , boost::ref( ensemble ) , x , 0.0 , t_transients , dt ); + //] + + // integrate and compute the statistics + size_t steps2 = integrate_const( make_dense_output( 1.0e-6 , 1.0e-6 , stepper_type() ) , boost::ref( ensemble ) , x , 0.0 , t_max , dt , boost::ref( obs ) ); + + fout << epsilon << "\t" << obs.get_K_mean() << endl; + cout << "Dopri5 : " << epsilon << "\t" << obs.get_K_mean() << "\t" << timer_local.elapsed() << "\t" << steps1 << "\t" << steps2 << endl; + } + dopri5_time = timer.elapsed(); + } + + + + { + //[ thrust_phase_ensemble_define_rk4 + typedef runge_kutta4< state_type , value_type , state_type , value_type , thrust_algebra , thrust_operations > stepper_type; + //] + + ofstream fout( "phase_ensemble_rk4.dat" ); + timer.restart(); + for( value_type epsilon = epsilon_min ; epsilon < epsilon_max ; epsilon += d_epsilon ) + { + ensemble.set_epsilon( epsilon ); + statistics_observer obs; + state_type x = x_host; + + timer_local.restart(); + + // calculate some transients steps + size_t steps1 = integrate_const( stepper_type() , boost::ref( ensemble ) , x , 0.0 , t_transients , dt ); + + // integrate and compute the statistics + size_t steps2 = integrate_const( stepper_type() , boost::ref( ensemble ) , x , 0.0 , t_max , dt , boost::ref( obs ) ); + fout << epsilon << "\t" << obs.get_K_mean() << endl; + cout << "RK4 : " << epsilon << "\t" << obs.get_K_mean() << "\t" << timer_local.elapsed() << "\t" << steps1 << "\t" << steps2 << endl; + } + rk4_time = timer.elapsed(); + } + + cout << "Dopri 5 : " << dopri5_time << " s\n"; + cout << "RK4 : " << rk4_time << "\n"; + + return 0; +} diff --git a/examples/thrust/relaxation.cu b/examples/thrust/relaxation.cu new file mode 100644 index 00000000..8590b85f --- /dev/null +++ b/examples/thrust/relaxation.cu @@ -0,0 +1,73 @@ +/* + * Solves many relaxation equations dxdt = - a * x in parallel and for different values of a. + * The relaxation equations are completely uncoupled. + */ + +#include + +#include + +#include +#include +#include +#include + + +using namespace std; +using namespace boost::numeric::odeint; + +// change to float if your GPU does not support doubles +typedef double value_type; +typedef thrust::device_vector< value_type > state_type; +typedef runge_kutta4< state_type , value_type , state_type , value_type , thrust_algebra , thrust_operations > stepper_type; + +struct relaxation +{ + struct relaxation_functor + { + template< class T > + __host__ __device__ + void operator()( T t ) const + { + // unpack the parameter we want to vary and the Lorenz variables + value_type a = thrust::get< 1 >( t ); + value_type x = thrust::get< 0 >( t ); + thrust::get< 2 >( t ) = -a * x; + } + }; + + relaxation( size_t N , const state_type &a ) + : m_N( N ) , m_a( a ) { } + + void operator()( const state_type &x , state_type &dxdt , value_type t ) const + { + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( x.begin() , m_a.begin() , dxdt.begin() ) ) , + thrust::make_zip_iterator( thrust::make_tuple( x.end() , m_a.end() , dxdt.end() ) ) , + relaxation_functor() ); + } + + size_t m_N; + const state_type &m_a; +}; + +const size_t N = 1024 * 1024; +const value_type dt = 0.01; + +int main( int arc , char* argv[] ) +{ + // initialize the relaxation constants a + vector< value_type > a_host( N ); + for( size_t i=0 ; i +#include +#include +#include + +#ifndef M_PI //not there on windows +#define M_PI 3.1415927 //... +#endif + +#include + +using namespace std; +using namespace boost::numeric::odeint; + +//[ two_dimensional_phase_lattice_definition +typedef boost::numeric::ublas::matrix< double > state_type; + +struct two_dimensional_phase_lattice +{ + two_dimensional_phase_lattice( double gamma = 0.5 ) + : m_gamma( gamma ) { } + + void operator()( const state_type &x , state_type &dxdt , double /* t */ ) const + { + size_t size1 = x.size1() , size2 = x.size2(); + + for( size_t i=1 ; i map_type; + + write_snapshots( void ) : m_count( 0 ) { } + + void operator()( const state_type &x , double t ) + { + map< size_t , string >::const_iterator it = m_snapshots.find( m_count ); + if( it != m_snapshots.end() ) + { + ofstream fout( it->second.c_str() ); + for( size_t i=0 ; i( rand() ) / RAND_MAX * 2.0 * M_PI; + + write_snapshots snapshots; + snapshots.snapshots().insert( make_pair( size_t( 0 ) , string( "lat_0000.dat" ) ) ); + snapshots.snapshots().insert( make_pair( size_t( 100 ) , string( "lat_0100.dat" ) ) ); + snapshots.snapshots().insert( make_pair( size_t( 1000 ) , string( "lat_1000.dat" ) ) ); + observer_collection< state_type , double > obs; + obs.observers().push_back( write_for_gnuplot( 10 ) ); + obs.observers().push_back( snapshots ); + + cout << "set term x11" << endl; + cout << "set pm3d map" << endl; + integrate_const( runge_kutta4< state_type >() , two_dimensional_phase_lattice( 1.2 ) , + x , 0.0 , 1001.0 , 0.1 , boost::ref( obs ) ); + + + return 0; +} diff --git a/examples/ublas/Jamfile.v2 b/examples/ublas/Jamfile.v2 new file mode 100644 index 00000000..28c15045 --- /dev/null +++ b/examples/ublas/Jamfile.v2 @@ -0,0 +1,13 @@ +# Copyright 2009 Karsten Ahnert and Mario Mulansky. +# Distributed under the Boost Software License, Version 1.0. (See +# accompanying file LICENSE_1_0.txt or copy at +# http://www.boost.org/LICENSE_1_0.txt) + + +project + : requirements + ../../../../.. + BOOST_ALL_NO_LIB=1 + ; + +exe lorenz_ublas : lorenz_ublas.cpp ; diff --git a/examples/ublas/lorenz_ublas.cpp b/examples/ublas/lorenz_ublas.cpp new file mode 100644 index 00000000..c3394d55 --- /dev/null +++ b/examples/ublas/lorenz_ublas.cpp @@ -0,0 +1,59 @@ +/* + * Copyright 2009-2012 Karsten Ahnert + * Copyright 2009-2012 Mario Mulansky + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#include + +#include +#include + +/* define ublas::vector as resizeable + * this is not neccessarily required because this definition already + * exists in util/ublas_wrapper.hpp. + * However, for completeness and educational purpose it is repeated here. + */ + +//[ ublas_resizeable +typedef boost::numeric::ublas::vector< double > state_type; + +namespace boost { namespace numeric { namespace odeint { + +template<> +struct is_resizeable< state_type > +{ + typedef boost::true_type type; + const static bool value = type::value; +}; + +} } } +//] + +void lorenz( const state_type &x , state_type &dxdt , const double t ) +{ + const double sigma( 10.0 ); + const double R( 28.0 ); + const double b( 8.0 / 3.0 ); + + dxdt[0] = sigma * ( x[1] - x[0] ); + dxdt[1] = R * x[0] - x[1] - x[0] * x[2]; + dxdt[2] = -b * x[2] + x[0] * x[1]; +} + +using namespace boost::numeric::odeint; + +//[ublas_main +int main() +{ + state_type x(3); + x[0] = 10.0; x[1] = 5.0 ; x[2] = 0.0; + typedef runge_kutta4< state_type , double , state_type , double , vector_space_algebra > stepper; + integrate_const( stepper() , lorenz , x , + 0.0 , 10.0 , 0.1 ); +} +//] diff --git a/examples/van_der_pol_stiff.cpp b/examples/van_der_pol_stiff.cpp new file mode 100644 index 00000000..4b433b24 --- /dev/null +++ b/examples/van_der_pol_stiff.cpp @@ -0,0 +1,93 @@ +/* + * van_der_pol_stiff.cpp + * + * Created on: Dec 12, 2011 + * + * Copyright 2011 Rajeev Singh + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#include +#include +#include + +#include + +#include +#include + +using namespace std; +using namespace boost::numeric::odeint; +namespace phoenix = boost::phoenix; + +const double mu = 1000.0; + + +typedef boost::numeric::ublas::vector< double > vector_type; +typedef boost::numeric::ublas::matrix< double > matrix_type; + +struct vdp_stiff +{ + void operator()( const vector_type &x , vector_type &dxdt , double t ) + { + dxdt[0] = x[1]; + dxdt[1] = -x[0] - mu * x[1] * (x[0]*x[0]-1.0); + } +}; + +struct vdp_stiff_jacobi +{ + void operator()( const vector_type &x , matrix_type &J , const double &t , vector_type &dfdt ) + { + J(0, 0) = 0.0; + J(0, 1) = 1.0; + J(1, 0) = -1.0 - 2.0*mu * x[0] * x[1]; + J(1, 1) = -mu * ( x[0] * x[0] - 1.0); + + dfdt[0] = 0.0; + dfdt[1] = 0.0; + } +}; + + +int main( int argc , char **argv ) +{ + //[ integrate_stiff_system + vector_type x( 2 ); + /* initialize random seed: */ + srand ( time(NULL) ); + + // initial conditions + for (int i=0; i<2; i++) + x[i] = 1.0; //(1.0 * rand()) / RAND_MAX; + + size_t num_of_steps = integrate_const( make_dense_output< rosenbrock4< double > >( 1.0e-6 , 1.0e-6 ) , + make_pair( vdp_stiff() , vdp_stiff_jacobi() ) , + x , 0.0 , 1000.0 , 1.0 + , cout << phoenix::arg_names::arg2 << " " << phoenix::arg_names::arg1[0] << " " << phoenix::arg_names::arg1[1] << "\n" + ); + //] + clog << num_of_steps << endl; + + + + //[ integrate_stiff_system_alternative + + vector_type x2( 2 ); + // initial conditions + for (int i=0; i<2; i++) + x2[i] = 1.0; //(1.0 * rand()) / RAND_MAX; + + size_t num_of_steps2 = integrate_const( make_dense_output< runge_kutta_dopri5< vector_type > >( 1.0e-6 , 1.0e-6 ) , + vdp_stiff() , x2 , 0.0 , 1000.0 , 1.0 + , cout << phoenix::arg_names::arg2 << " " << phoenix::arg_names::arg1[0] << " " << phoenix::arg_names::arg1[1] << "\n" + ); + //] + clog << num_of_steps2 << endl; + + + return 0; +} diff --git a/examples/vexcl/Jamfile.v2 b/examples/vexcl/Jamfile.v2 new file mode 100644 index 00000000..a4192664 --- /dev/null +++ b/examples/vexcl/Jamfile.v2 @@ -0,0 +1,31 @@ +# Copyright 2009-2012 Karsten Ahnert +# Copyright 2009-2012 Mario Mulansky +# +# Distributed under the Boost Software License, Version 1.0. +# (See accompanying file LICENSE_1_0.txt or +# copy at http://www.boost.org/LICENSE_1_0.txt) + + +import boost ; +import os ; + +boost.use-project ; + + +# change these lines to fit you configuration +local HOME = [ os.environ HOME ] ; +VEXCL_INCLUDE = $(HOME)/boost/vexcl ; +CUDA_INCLUDE = /usr/local/cuda/include ; + + +lib opencl : : OpenCL ; + +project : requirements + /boost//headers + ../../../../.. + $(VEXCL_INCLUDE) + $(CUDA_INCLUDE) + gcc:-std=c++0x + ; + +exe lorenz_ensemble : lorenz_ensemble.cpp opencl ; \ No newline at end of file diff --git a/examples/vexcl/lorenz_ensemble.cpp b/examples/vexcl/lorenz_ensemble.cpp new file mode 100644 index 00000000..53b3b45f --- /dev/null +++ b/examples/vexcl/lorenz_ensemble.cpp @@ -0,0 +1,89 @@ +/* + * Copyright 2009-2012 Karsten Ahnert + * Copyright 2009-2012 Mario Mulansky + * + * Distributed under the Boost Software License, Version 1.0. + * (See accompanying file LICENSE_1_0.txt or + * copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#include +#include + +#include + +#include +//[ vexcl_includes +#include +//] + +namespace odeint = boost::numeric::odeint; + +//[ vexcl_state_types +typedef vex::vector< double > vector_type; +typedef vex::multivector< double, 3 > state_type; +//] + + +//[ vexcl_system +const double sigma = 10.0; +const double b = 8.0 / 3.0; + +struct sys_func +{ + const vector_type &R; + + sys_func( const vector_type &_R ) : R( _R ) { } + + void operator()( const state_type &x , state_type &dxdt , double t ) const + { + dxdt(0) = -sigma * ( x(0) - x(1) ); + dxdt(1) = R * x(0) - x(1) - x(0) * x(2); + dxdt(2) = - b * x(2) + x(0) * x(1); + } +}; +//] + + +int main( int argc , char **argv ) +{ + using namespace std; + using namespace odeint; + + //[ vexcl_main + // setup the opencl context + vex::Context ctx( vex::Filter::Type(CL_DEVICE_TYPE_GPU) ); + std::cout << ctx << std::endl; + + // set up number of system, time step and integration time + const size_t n = 1024 * 1024; + const double dt = 0.01; + const double t_max = 100.0; + + // initialize R + double Rmin = 0.1 , Rmax = 50.0 , dR = ( Rmax - Rmin ) / double( n - 1 ); + std::vector x( n * 3 ) , r( n ); + for( size_t i=0 ; i stepper; + + // solve the system + integrate_const( stepper , sys_func( R ) , X , 0.0 , t_max , dt ); + //] + + std::vector< double > res( 3 * n ); + vex::copy( X(0) , res ); + for( size_t i=0 ; i + +namespace boost { +namespace numeric { +namespace odeint { + +struct array_algebra +{ + template< typename T , size_t dim , class Op > + static void for_each1( boost::array< T , dim > &s1 , Op op ) + { + for( size_t i=0 ; i + static void for_each2( boost::array< T1 , dim > &s1 , + const boost::array< T2 , dim > &s2 , Op op ) + { + for( size_t i=0 ; i + static void for_each3( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , Op op ) + { + for( size_t i=0 ; i + static void for_each3( boost::array< T , dim > &s1 , + boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , Op op ) + { + for( size_t i=0 ; i + static void for_each4( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , Op op ) + { + for( size_t i=0 ; i + static void for_each5( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , + const boost::array< T , dim > &s5 , Op op ) + { + for( size_t i=0 ; i + static void for_each6( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , + const boost::array< T , dim > &s5 , + const boost::array< T , dim > &s6 , Op op ) + { + for( size_t i=0 ; i + static void for_each7( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , + const boost::array< T , dim > &s5 , + const boost::array< T , dim > &s6 , + const boost::array< T , dim > &s7 , Op op ) + { + for( size_t i=0 ; i + static void for_each8( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , + const boost::array< T , dim > &s5 , + const boost::array< T , dim > &s6 , + const boost::array< T , dim > &s7 , + const boost::array< T , dim > &s8 , Op op ) + { + for( size_t i=0 ; i + static void for_each9( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , + const boost::array< T , dim > &s5 , + const boost::array< T , dim > &s6 , + const boost::array< T , dim > &s7 , + const boost::array< T , dim > &s8 , + const boost::array< T , dim > &s9 , Op op ) + { + for( size_t i=0 ; i + static void for_each10( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , + const boost::array< T , dim > &s5 , + const boost::array< T , dim > &s6 , + const boost::array< T , dim > &s7 , + const boost::array< T , dim > &s8 , + const boost::array< T , dim > &s9 , + const boost::array< T , dim > &s10 , Op op ) + { + for( size_t i=0 ; i + static void for_each11( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , + const boost::array< T , dim > &s5 , + const boost::array< T , dim > &s6 , + const boost::array< T , dim > &s7 , + const boost::array< T , dim > &s8 , + const boost::array< T , dim > &s9 , + const boost::array< T , dim > &s10 , + const boost::array< T , dim > &s11 , Op op ) + { + for( size_t i=0 ; i + static void for_each12( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , + const boost::array< T , dim > &s5 , + const boost::array< T , dim > &s6 , + const boost::array< T , dim > &s7 , + const boost::array< T , dim > &s8 , + const boost::array< T , dim > &s9 , + const boost::array< T , dim > &s10 , + const boost::array< T , dim > &s11 , + const boost::array< T , dim > &s12 , Op op ) + { + for( size_t i=0 ; i + static void for_each13( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , + const boost::array< T , dim > &s5 , + const boost::array< T , dim > &s6 , + const boost::array< T , dim > &s7 , + const boost::array< T , dim > &s8 , + const boost::array< T , dim > &s9 , + const boost::array< T , dim > &s10 , + const boost::array< T , dim > &s11 , + const boost::array< T , dim > &s12 , + const boost::array< T , dim > &s13 , Op op ) + { + for( size_t i=0 ; i + static void for_each14( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , + const boost::array< T , dim > &s5 , + const boost::array< T , dim > &s6 , + const boost::array< T , dim > &s7 , + const boost::array< T , dim > &s8 , + const boost::array< T , dim > &s9 , + const boost::array< T , dim > &s10 , + const boost::array< T , dim > &s11 , + const boost::array< T , dim > &s12 , + const boost::array< T , dim > &s13 , + const boost::array< T , dim > &s14 , Op op ) + { + for( size_t i=0 ; i + static void for_each15( boost::array< T , dim > &s1 , + const boost::array< T , dim > &s2 , + const boost::array< T , dim > &s3 , + const boost::array< T , dim > &s4 , + const boost::array< T , dim > &s5 , + const boost::array< T , dim > &s6 , + const boost::array< T , dim > &s7 , + const boost::array< T , dim > &s8 , + const boost::array< T , dim > &s9 , + const boost::array< T , dim > &s10 , + const boost::array< T , dim > &s11 , + const boost::array< T , dim > &s12 , + const boost::array< T , dim > &s13 , + const boost::array< T , dim > &s14 , + const boost::array< T , dim > &s15 , Op op ) + { + for( size_t i=0 ; i + static Value reduce( const boost::array< T , dim > &s , Red red , Value init) + { + for( size_t i=0 ; i ... + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_ALGEBRA_DEFAULT_OPERATIONS_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_ALGEBRA_DEFAULT_OPERATIONS_HPP_INCLUDED + +#include + +#include +#include + +#include + + +namespace boost { +namespace numeric { +namespace odeint { + + + +/* + * Notes: + * + * * the results structs are needed in order to work with fusion_algebra + */ +struct default_operations +{ + + template< class Fac1 = double > + struct scale + { + const Fac1 m_alpha1; + + scale( Fac1 alpha1 ) : m_alpha1( alpha1 ) { } + + template< class T1 > + void operator()( T1 &t1 ) const + { + t1 *= m_alpha1; + } + + typedef void result_type; + }; + + template< class Fac1 = double > + struct scale_sum1 + { + const Fac1 m_alpha1; + + scale_sum1( Fac1 alpha1 ) : m_alpha1( alpha1 ) { } + + template< class T1 , class T2 > + void operator()( T1 &t1 , const T2 &t2 ) const + { + t1 = m_alpha1 * t2; + } + + typedef void result_type; + }; + + + template< class Fac1 = double , class Fac2 = Fac1 > + struct scale_sum2 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + + scale_sum2( Fac1 alpha1 , Fac2 alpha2 ) : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) { } + + template< class T1 , class T2 , class T3 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3; + } + + typedef void result_type; + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 > + struct scale_sum3 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + + scale_sum3( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) { } + + template< class T1 , class T2 , class T3 , class T4 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 ) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4; + } + + typedef void result_type; + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 > + struct scale_sum4 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + + scale_sum4( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5; + } + + typedef void result_type; + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , class Fac5 = Fac4 > + struct scale_sum5 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + + scale_sum5( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 , Fac5 alpha5 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6; + } + + typedef void result_type; + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , class Fac5 = Fac4 , class Fac6 = Fac5 > + struct scale_sum6 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + const Fac6 m_alpha6; + + scale_sum6( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 , Fac5 alpha5 , Fac6 alpha6 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) , m_alpha6( alpha6 ){ } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 , class T7 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6 ,const T7 &t7) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6 + m_alpha6 * t7; + } + + typedef void result_type; + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , class Fac5 = Fac4 , class Fac6 = Fac5 , class Fac7 = Fac6 > + struct scale_sum7 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + const Fac6 m_alpha6; + const Fac7 m_alpha7; + + scale_sum7( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 , + Fac5 alpha5 , Fac6 alpha6 , Fac7 alpha7 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) , m_alpha6( alpha6 ) , m_alpha7( alpha7 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 , class T7 , class T8 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6 , const T7 &t7 , const T8 &t8 ) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6 + m_alpha6 * t7 + m_alpha7 * t8; + } + + typedef void result_type; + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , class Fac5 = Fac4 , class Fac6 = Fac5 , class Fac7 = Fac6 , class Fac8 = Fac7 > + struct scale_sum8 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + const Fac6 m_alpha6; + const Fac7 m_alpha7; + const Fac8 m_alpha8; + + scale_sum8( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 , + Fac5 alpha5 , Fac6 alpha6 , Fac7 alpha7 , Fac8 alpha8 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) , m_alpha6( alpha6 ) , m_alpha7( alpha7 ) , m_alpha8( alpha8 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 , class T7 , class T8 , class T9 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6 , const T7 &t7 , const T8 &t8 , const T9 &t9 ) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6 + m_alpha6 * t7 + m_alpha7 * t8 + m_alpha8 * t9; + } + + typedef void result_type; + }; + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , class Fac5 = Fac4 , class Fac6 = Fac5 , class Fac7 = Fac6 , class Fac8 = Fac7 , class Fac9 = Fac8 > + struct scale_sum9 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + const Fac6 m_alpha6; + const Fac7 m_alpha7; + const Fac8 m_alpha8; + const Fac9 m_alpha9; + + scale_sum9( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 , + Fac5 alpha5 , Fac6 alpha6 , Fac7 alpha7 , Fac8 alpha8 , Fac9 alpha9 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) , m_alpha6( alpha6 ) , m_alpha7( alpha7 ) , m_alpha8( alpha8 ) , m_alpha9( alpha9 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 , class T7 , class T8 , class T9 , class T10 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6 , const T7 &t7 , const T8 &t8 , const T9 &t9 , const T10 &t10 ) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6 + m_alpha6 * t7 + m_alpha7 * t8 + m_alpha8 * t9 + m_alpha9 * t10; + } + + typedef void result_type; + }; + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , class Fac5 = Fac4 , class Fac6 = Fac5 , class Fac7 = Fac6 , class Fac8 = Fac7 , class Fac9 = Fac8 , class Fac10 = Fac9 > + struct scale_sum10 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + const Fac6 m_alpha6; + const Fac7 m_alpha7; + const Fac8 m_alpha8; + const Fac9 m_alpha9; + const Fac10 m_alpha10; + + scale_sum10( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 , + Fac5 alpha5 , Fac6 alpha6 , Fac7 alpha7 , Fac8 alpha8 , Fac9 alpha9 , Fac10 alpha10 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) , m_alpha6( alpha6 ) , m_alpha7( alpha7 ) , m_alpha8( alpha8 ) , m_alpha9( alpha9 ) , m_alpha10( alpha10 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 , class T7 , class T8 , class T9 , class T10 , class T11 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6 , const T7 &t7 , const T8 &t8 , const T9 &t9 , const T10 &t10 , const T11 &t11 ) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6 + m_alpha6 * t7 + m_alpha7 * t8 + m_alpha8 * t9 + m_alpha9 * t10 + m_alpha10 * t11; + } + + typedef void result_type; + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , class Fac5 = Fac4 , class Fac6 = Fac5 , class Fac7 = Fac6 , class Fac8 = Fac7 , class Fac9 = Fac8 , class Fac10 = Fac9 , class Fac11 = Fac10 > + struct scale_sum11 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + const Fac6 m_alpha6; + const Fac7 m_alpha7; + const Fac8 m_alpha8; + const Fac9 m_alpha9; + const Fac10 m_alpha10; + const Fac11 m_alpha11; + + scale_sum11( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 , + Fac5 alpha5 , Fac6 alpha6 , Fac7 alpha7 , Fac8 alpha8 , Fac9 alpha9 , + Fac10 alpha10 , Fac11 alpha11 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) , m_alpha6( alpha6 ) , m_alpha7( alpha7 ) , m_alpha8( alpha8 ) , m_alpha9( alpha9 ) , m_alpha10( alpha10 ) , m_alpha11( alpha11 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 , class T7 , class T8 , class T9 , class T10 , class T11 , class T12 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6 , const T7 &t7 , const T8 &t8 , const T9 &t9 , const T10 &t10 , const T11 &t11 , const T12 &t12 ) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6 + m_alpha6 * t7 + m_alpha7 * t8 + m_alpha8 * t9 + m_alpha9 * t10 + m_alpha10 * t11 + m_alpha11 * t12; + } + + typedef void result_type; + }; + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , class Fac5 = Fac4 , class Fac6 = Fac5 , class Fac7 = Fac6 , class Fac8 = Fac7 , class Fac9 = Fac8 , class Fac10 = Fac9 , class Fac11 = Fac10 , class Fac12 = Fac11 > + struct scale_sum12 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + const Fac6 m_alpha6; + const Fac7 m_alpha7; + const Fac8 m_alpha8; + const Fac9 m_alpha9; + const Fac10 m_alpha10; + const Fac11 m_alpha11; + const Fac12 m_alpha12; + + scale_sum12( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 , + Fac5 alpha5 , Fac6 alpha6 , Fac7 alpha7 , Fac8 alpha8 , Fac9 alpha9 , + Fac10 alpha10 , Fac11 alpha11 , Fac12 alpha12 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) , m_alpha6( alpha6 ) , m_alpha7( alpha7 ) , m_alpha8( alpha8 ) , m_alpha9( alpha9 ) , m_alpha10( alpha10 ) , m_alpha11( alpha11 ) , m_alpha12( alpha12 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 , class T7 , class T8 , class T9 , class T10 , class T11 , class T12 , class T13 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6 , const T7 &t7 , const T8 &t8 , const T9 &t9 , const T10 &t10 , const T11 &t11 , const T12 &t12 , const T13 &t13 ) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6 + m_alpha6 * t7 + m_alpha7 * t8 + m_alpha8 * t9 + m_alpha9 * t10 + m_alpha10 * t11 + m_alpha11 * t12 + m_alpha12 * t13; + } + + typedef void result_type; + }; + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , class Fac5 = Fac4 , class Fac6 = Fac5 , class Fac7 = Fac6 , class Fac8 = Fac7 , class Fac9 = Fac8 , class Fac10 = Fac9 , class Fac11 = Fac10 , class Fac12 = Fac11 , class Fac13 = Fac12 > + struct scale_sum13 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + const Fac6 m_alpha6; + const Fac7 m_alpha7; + const Fac8 m_alpha8; + const Fac9 m_alpha9; + const Fac10 m_alpha10; + const Fac11 m_alpha11; + const Fac12 m_alpha12; + const Fac13 m_alpha13; + + scale_sum13( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 , + Fac5 alpha5 , Fac6 alpha6 , Fac7 alpha7 , Fac8 alpha8 , Fac9 alpha9 , + Fac10 alpha10 , Fac11 alpha11 , Fac12 alpha12 , Fac13 alpha13 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) , m_alpha6( alpha6 ) , m_alpha7( alpha7 ) , m_alpha8( alpha8 ) , m_alpha9( alpha9 ) , m_alpha10( alpha10 ) , m_alpha11( alpha11 ) , m_alpha12( alpha12 ) , m_alpha13( alpha13 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 , class T7 , class T8 , class T9 , class T10 , class T11 , class T12 , class T13 , class T14 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6 , const T7 &t7 , const T8 &t8 , const T9 &t9 , const T10 &t10 , const T11 &t11 , const T12 &t12 , const T13 &t13 , const T14 &t14 ) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6 + m_alpha6 * t7 + m_alpha7 * t8 + m_alpha8 * t9 + m_alpha9 * t10 + m_alpha10 * t11 + m_alpha11 * t12 + m_alpha12 * t13 + m_alpha13 * t14; + } + + typedef void result_type; + }; + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , class Fac5 = Fac4 , class Fac6 = Fac5 , class Fac7 = Fac6 , class Fac8 = Fac7 , class Fac9 = Fac8 , class Fac10 = Fac9 , class Fac11 = Fac10 , class Fac12 = Fac11 , class Fac13 = Fac12 , class Fac14 = Fac13 > + struct scale_sum14 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + const Fac6 m_alpha6; + const Fac7 m_alpha7; + const Fac8 m_alpha8; + const Fac9 m_alpha9; + const Fac10 m_alpha10; + const Fac11 m_alpha11; + const Fac12 m_alpha12; + const Fac13 m_alpha13; + const Fac14 m_alpha14; + + scale_sum14( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 , + Fac5 alpha5 , Fac6 alpha6 , Fac7 alpha7 , Fac8 alpha8 , Fac9 alpha9 , + Fac10 alpha10 , Fac11 alpha11 , Fac12 alpha12 , Fac13 alpha13 , Fac14 alpha14 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) , m_alpha6( alpha6 ) , m_alpha7( alpha7 ) , m_alpha8( alpha8 ) , m_alpha9( alpha9 ) , m_alpha10( alpha10 ) , m_alpha11( alpha11 ) , m_alpha12( alpha12 ) , m_alpha13( alpha13 ) , m_alpha14( alpha14 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 , class T7 , class T8 , class T9 , class T10 , class T11 , class T12 , class T13 , class T14 , class T15 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6 , const T7 &t7 , const T8 &t8 , const T9 &t9 , const T10 &t10 , const T11 &t11 , const T12 &t12 , const T13 &t13 , const T14 &t14 , const T15 &t15 ) const + { + t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6 + m_alpha6 * t7 + m_alpha7 * t8 + m_alpha8 * t9 + m_alpha9 * t10 + m_alpha10 * t11 + m_alpha11 * t12 + m_alpha12 * t13 + m_alpha13 * t14 + m_alpha14 * t15; + } + + typedef void result_type; + }; + + template< class Fac1 = double , class Fac2 = Fac1 > + struct scale_sum_swap2 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + + scale_sum_swap2( Fac1 alpha1 , Fac2 alpha2 ) : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) { } + + template< class T1 , class T2 , class T3 > + void operator()( T1 &t1 , T2 &t2 , const T3 &t3) const + { + const T1 tmp( t1 ); + t1 = m_alpha1 * t2 + m_alpha2 * t3; + t2 = tmp; + } + + typedef void result_type; + }; + + /* + * for usage in for_each2 + * + * Works with boost::units by eliminating the unit + */ + template< class Fac1 = double > + struct rel_error + { + const Fac1 m_eps_abs , m_eps_rel , m_a_x , m_a_dxdt; + + rel_error( Fac1 eps_abs , Fac1 eps_rel , Fac1 a_x , Fac1 a_dxdt ) + : m_eps_abs( eps_abs ) , m_eps_rel( eps_rel ) , m_a_x( a_x ) , m_a_dxdt( a_dxdt ) { } + + + template< class T1 , class T2 , class T3 > + void operator()( T3 &t3 , const T1 &t1 , const T2 &t2 ) const + { + using std::abs; + set_unit_value( t3 , abs( get_unit_value( t3 ) ) / ( m_eps_abs + m_eps_rel * ( m_a_x * abs( get_unit_value( t1 ) ) + m_a_dxdt * abs( get_unit_value( t2 ) ) ) ) ); + } + + typedef void result_type; + }; + + + /* + * for usage in for_each3 + * + * used in the controller for the rosenbrock4 method + * + * Works with boost::units by eliminating the unit + */ + template< class Fac1 = double > + struct default_rel_error + { + const Fac1 m_eps_abs , m_eps_rel ; + + default_rel_error( Fac1 eps_abs , Fac1 eps_rel ) + : m_eps_abs( eps_abs ) , m_eps_rel( eps_rel ) { } + + + /* + * xerr = xerr / ( eps_abs + eps_rel * max( x , x_old ) ) + */ + template< class T1 , class T2 , class T3 > + void operator()( T3 &t3 , const T1 &t1 , const T2 &t2 ) const + { + BOOST_USING_STD_MAX(); + using std::abs; + Fac1 x1 = abs( get_unit_value( t1 ) ) , x2 = abs( get_unit_value( t2 ) ); + set_unit_value( t3 , abs( get_unit_value( t3 ) ) / ( m_eps_abs + m_eps_rel * max BOOST_PREVENT_MACRO_SUBSTITUTION ( x1 , x2 ) ) ); + } + + typedef void result_type; + }; + + + + /* + * for usage in reduce + */ + + template< class Value > + struct maximum + { + template< class Fac1 , class Fac2 > + Value operator()( Fac1 t1 , const Fac2 t2 ) const + { + using std::abs; + Value a1 = abs( get_unit_value( t1 ) ) , a2 = abs( get_unit_value( t2 ) ); + return ( a1 < a2 ) ? a2 : a1 ; + } + + typedef Value result_type; + }; + + + + + + template< class Fac1 = double > + struct rel_error_max + { + const Fac1 m_eps_abs , m_eps_rel; + + rel_error_max( Fac1 eps_abs , Fac1 eps_rel ) + : m_eps_abs( eps_abs ) , m_eps_rel( eps_rel ) + { } + + template< class Res , class T1 , class T2 , class T3 > + Res operator()( Res r , const T1 &x_old , const T2 &x , const T3 &x_err ) + { + BOOST_USING_STD_MAX(); + using std::abs; + Res tmp = abs( get_unit_value( x_err ) ) / ( m_eps_abs + m_eps_rel * max BOOST_PREVENT_MACRO_SUBSTITUTION ( abs( x_old ) , abs( x ) ) ); + return max BOOST_PREVENT_MACRO_SUBSTITUTION ( r , tmp ); + } + }; + + + template< class Fac1 = double > + struct rel_error_max2 + { + const Fac1 m_eps_abs , m_eps_rel , m_a_x , m_a_dxdt; + + rel_error_max2( Fac1 eps_abs , Fac1 eps_rel , Fac1 a_x , Fac1 a_dxdt ) + : m_eps_abs( eps_abs ) , m_eps_rel( eps_rel ) , m_a_x( a_x ) , m_a_dxdt( a_dxdt ) + { } + + template< class Res , class T1 , class T2 , class T3 , class T4 > + Res operator()( Res r , const T1 &x_old , const T2 &x , const T3 &dxdt_old , const T4 &x_err ) + { + BOOST_USING_STD_MAX(); + using std::abs; + Res tmp = abs( get_unit_value( x_err ) ) / + ( m_eps_abs + m_eps_rel * ( m_a_x * abs( get_unit_value( x_old ) ) + m_a_dxdt * abs( get_unit_value( dxdt_old ) ) ) ); + return max BOOST_PREVENT_MACRO_SUBSTITUTION ( r , tmp ); + } + }; + + + + + template< class Fac1 = double > + struct rel_error_l2 + { + const Fac1 m_eps_abs , m_eps_rel; + + rel_error_l2( Fac1 eps_abs , Fac1 eps_rel ) + : m_eps_abs( eps_abs ) , m_eps_rel( eps_rel ) + { } + + template< class Res , class T1 , class T2 , class T3 > + Res operator()( Res r , const T1 &x_old , const T2 &x , const T3 &x_err ) + { + BOOST_USING_STD_MAX(); + using std::abs; + Res tmp = abs( get_unit_value( x_err ) ) / ( m_eps_abs + m_eps_rel * max BOOST_PREVENT_MACRO_SUBSTITUTION ( abs( x_old ) , abs( x ) ) ); + return r + tmp * tmp; + } + }; + + + + + template< class Fac1 = double > + struct rel_error_l2_2 + { + const Fac1 m_eps_abs , m_eps_rel , m_a_x , m_a_dxdt; + + rel_error_l2_2( Fac1 eps_abs , Fac1 eps_rel , Fac1 a_x , Fac1 a_dxdt ) + : m_eps_abs( eps_abs ) , m_eps_rel( eps_rel ) , m_a_x( a_x ) , m_a_dxdt( a_dxdt ) + { } + + template< class Res , class T1 , class T2 , class T3 , class T4 > + Res operator()( Res r , const T1 &x_old , const T2 &x , const T3 &dxdt_old , const T4 &x_err ) + { + using std::abs; + Res tmp = abs( get_unit_value( x_err ) ) / + ( m_eps_abs + m_eps_rel * ( m_a_x * abs( get_unit_value( x_old ) ) + m_a_dxdt * abs( get_unit_value( dxdt_old ) ) ) ); + return r + tmp * tmp; + } + }; + + + + + + +}; + + +} // odeint +} // numeric +} // boost + + +#endif // BOOST_NUMERIC_ODEINT_ALGEBRA_DEFAULT_OPERATIONS_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/algebra/detail/for_each.hpp b/include/boost/numeric/odeint/algebra/detail/for_each.hpp new file mode 100644 index 00000000..8693e845 --- /dev/null +++ b/include/boost/numeric/odeint/algebra/detail/for_each.hpp @@ -0,0 +1,165 @@ +/* + [auto_generated] + boost/numeric/odeint/algebra/detail/for_each.hpp + + [begin_description] + Default for_each implementations. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_ALGEBRA_DETAIL_FOR_EACH_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_ALGEBRA_DETAIL_FOR_EACH_HPP_INCLUDED + +namespace boost { +namespace numeric { +namespace odeint { +namespace detail { + + + template< class Iterator1 , class Operation > + inline void for_each1( Iterator1 first1 , Iterator1 last1 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ ); + } + + + template< class Iterator1 , class Iterator2 , class Operation > + inline void for_each2( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ ); + } + + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Operation > + inline void for_each3( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ ); + } + + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Operation > + inline void for_each4( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, Iterator4 first4, Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ ); + } + + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Iterator5 , class Operation > + inline void for_each5( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, + Iterator4 first4, Iterator5 first5, Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ , *first5++ ); + } + + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Iterator5 , class Iterator6 , class Operation > + inline void for_each6( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, + Iterator4 first4, Iterator5 first5, Iterator6 first6 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ , *first5++ , *first6++ ); + } + + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Iterator5 , class Iterator6 , class Iterator7 , class Operation > + inline void for_each7( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, + Iterator4 first4, Iterator5 first5, Iterator6 first6 , Iterator7 first7 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ , *first5++ , *first6++ , *first7++ ); + } + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Iterator5 , class Iterator6 , class Iterator7 , class Iterator8 , class Operation > + inline void for_each8( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, + Iterator4 first4, Iterator5 first5, Iterator6 first6 , Iterator7 first7 , Iterator8 first8 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ , *first5++ , *first6++ , *first7++ , *first8++ ); + } + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Iterator5 , class Iterator6 , class Iterator7 , class Iterator8 , class Iterator9 , class Operation > + inline void for_each9( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, + Iterator4 first4, Iterator5 first5, Iterator6 first6 , Iterator7 first7 , Iterator8 first8 , + Iterator9 first9 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ , *first5++ , *first6++ , *first7++ , *first8++ , *first9++ ); + } + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Iterator5 , class Iterator6 , class Iterator7 , class Iterator8 , class Iterator9 , class Iterator10 , class Operation > + inline void for_each10( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, + Iterator4 first4, Iterator5 first5, Iterator6 first6 , Iterator7 first7 , Iterator8 first8 , + Iterator9 first9 , Iterator10 first10 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ , *first5++ , *first6++ , *first7++ , *first8++ , *first9++ , *first10++ ); + } + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Iterator5 , class Iterator6 , class Iterator7 , class Iterator8 , class Iterator9 , class Iterator10 , class Iterator11 , class Operation > + inline void for_each11( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, + Iterator4 first4, Iterator5 first5, Iterator6 first6 , Iterator7 first7 , Iterator8 first8 , + Iterator9 first9 , Iterator10 first10 , Iterator11 first11 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ , *first5++ , *first6++ , *first7++ , *first8++ , *first9++ , *first10++ , *first11++ ); + } + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Iterator5 , class Iterator6 , class Iterator7 , class Iterator8 , class Iterator9 , class Iterator10 , class Iterator11 , class Iterator12 , class Operation > + inline void for_each12( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, + Iterator4 first4, Iterator5 first5, Iterator6 first6 , Iterator7 first7 , Iterator8 first8 , + Iterator9 first9 , Iterator10 first10 , Iterator11 first11 , Iterator12 first12 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ , *first5++ , *first6++ , *first7++ , *first8++ , *first9++ , *first10++ , *first11++ , *first12++ ); + } + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Iterator5 , class Iterator6 , class Iterator7 , class Iterator8 , class Iterator9 , class Iterator10 , class Iterator11 , class Iterator12 , class Iterator13 , class Operation > + inline void for_each13( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, + Iterator4 first4, Iterator5 first5, Iterator6 first6 , Iterator7 first7 , Iterator8 first8 , + Iterator9 first9 , Iterator10 first10 , Iterator11 first11 , Iterator12 first12 , Iterator13 first13 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ , *first5++ , *first6++ , *first7++ , *first8++ , *first9++ , *first10++ , *first11++ , *first12++ , *first13++ ); + } + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Iterator5 , class Iterator6 , class Iterator7 , class Iterator8 , class Iterator9 , class Iterator10 , class Iterator11 , class Iterator12 , class Iterator13 , class Iterator14 , class Operation > + inline void for_each14( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, + Iterator4 first4, Iterator5 first5, Iterator6 first6 , Iterator7 first7 , Iterator8 first8 , + Iterator9 first9 , Iterator10 first10 , Iterator11 first11 , Iterator12 first12 , Iterator13 first13 , + Iterator14 first14 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ , *first5++ , *first6++ , *first7++ , *first8++ , *first9++ , *first10++ , *first11++ , *first12++ , *first13++ , *first14++ ); + } + + template< class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Iterator5 , class Iterator6 , class Iterator7 , class Iterator8 , class Iterator9 , class Iterator10 , class Iterator11 , class Iterator12 , class Iterator13 , class Iterator14 , class Iterator15 , class Operation > + inline void for_each15( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3, + Iterator4 first4, Iterator5 first5, Iterator6 first6 , Iterator7 first7 , Iterator8 first8 , + Iterator9 first9 , Iterator10 first10 , Iterator11 first11 , Iterator12 first12 , Iterator13 first13 , + Iterator14 first14 , Iterator15 first15 , Operation op ) + { + for( ; first1 != last1 ; ) + op( *first1++ , *first2++ , *first3++ , *first4++ , *first5++ , *first6++ , *first7++ , *first8++ , *first9++ , *first10++ , *first11++ , *first12++ , *first13++ , *first14++ , *first15++ ); + } + + +} // detail +} // odeint +} // numeric +} // boost + + +#endif // BOOST_NUMERIC_ODEINT_ALGEBRA_DETAIL_FOR_EACH_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/algebra/detail/macros.hpp b/include/boost/numeric/odeint/algebra/detail/macros.hpp new file mode 100644 index 00000000..ef97327c --- /dev/null +++ b/include/boost/numeric/odeint/algebra/detail/macros.hpp @@ -0,0 +1,43 @@ +/* + [auto_generated] + boost/numeric/odeint/algebra/detail/macros.hpp + + [begin_description] + Some macros for type checking. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_ALGEBRA_DETAIL_MACROS_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_ALGEBRA_DETAIL_MACROS_HPP_INCLUDED + + +//type traits aren't working with nvcc +#ifndef __CUDACC__ +#include +#include + +#define BOOST_ODEINT_CHECK_CONTAINER_TYPE( Type1 , Type2 ) \ + BOOST_STATIC_ASSERT(( boost::is_same< typename boost::remove_const< Type1 >::type , Type2 >::value )) + +#else +//empty macro for nvcc +#define BOOST_ODEINT_CHECK_CONTAINER_TYPE( Type1 , Type2 ) + +#endif // __CUDACC__ + + + +/* +#define BOOST_ODEINT_CHECK_OPERATION_ARITY( Operation , Arity ) \ + BOOST_STATIC_ASSERT(( boost::function_traits< Operation >::arity == Arity )) + */ + +#endif // BOOST_NUMERIC_ODEINT_ALGEBRA_DETAIL_MACROS_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/algebra/detail/reduce.hpp b/include/boost/numeric/odeint/algebra/detail/reduce.hpp new file mode 100644 index 00000000..247d03df --- /dev/null +++ b/include/boost/numeric/odeint/algebra/detail/reduce.hpp @@ -0,0 +1,67 @@ +/* + [auto_generated] + boost/numeric/odeint/algebra/detail/reduce.hpp + + [begin_description] + Default reduce implementation. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_ALGEBRA_DETAIL_REDUCE_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_ALGEBRA_DETAIL_REDUCE_HPP_INCLUDED + + +namespace boost { +namespace numeric { +namespace odeint { +namespace detail { + +template< class ValueType , class Iterator1 , class Reduction > +inline ValueType reduce( Iterator1 first1 , Iterator1 last1 , Reduction red, ValueType init) +{ + for( ; first1 != last1 ; ) + init = red( init , *first1++ ); + return init; +} + + +template< class ValueType , class Iterator1 , class Iterator2 , class Reduction > +inline ValueType reduce2( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Reduction red, ValueType init) +{ + for( ; first1 != last1 ; ) + init = red( init , *first1++ , *first2++ ); + return init; +} + +template< class ValueType , class Iterator1 , class Iterator2 , class Iterator3 , class Reduction > +inline ValueType reduce3( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3 , Reduction red, ValueType init) +{ + for( ; first1 != last1 ; ) + init = red( init , *first1++ , *first2++ , *first3++ ); + return init; +} + +template< class ValueType , class Iterator1 , class Iterator2 , class Iterator3 , class Iterator4 , class Reduction > +inline ValueType reduce4( Iterator1 first1 , Iterator1 last1 , Iterator2 first2 , Iterator3 first3 , Iterator4 first4 , Reduction red, ValueType init) +{ + for( ; first1 != last1 ; ) + init = red( init , *first1++ , *first2++ , *first3++ , *first4++ ); + return init; +} + + +} // detail +} // odeint +} // numeric +} // boost + + +#endif // BOOST_NUMERIC_ODEINT_ALGEBRA_DETAIL_REDUCE_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/algebra/fusion_algebra.hpp b/include/boost/numeric/odeint/algebra/fusion_algebra.hpp new file mode 100644 index 00000000..81c4070f --- /dev/null +++ b/include/boost/numeric/odeint/algebra/fusion_algebra.hpp @@ -0,0 +1,186 @@ +/* + [auto_generated] + boost/numeric/odeint/algebra/fusion_algebra.hpp + + [begin_description] + Algebra for boost::fusion sequences. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_ALGEBRA_FUSION_ALGEBRA_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_ALGEBRA_FUSION_ALGEBRA_HPP_INCLUDED + + +#include +#include +#include +#include +#include + +namespace boost { +namespace numeric { +namespace odeint { + + +struct fusion_algebra +{ + template< class S1 , class Op > + static void for_each1( S1 &s1 , Op op ) + { + boost::fusion::for_each( s1 , op ); + }; + + + template< class S1 , class S2 , class Op > + static void for_each2( S1 &s1 , S2 &s2 , Op op ) + { + typedef boost::fusion::vector< S1& , S2& > Sequences; + Sequences sequences( s1 , s2 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + + template< class S1 , class S2 , class S3 , class Op > + static void for_each3( S1 &s1 , S2 &s2 , S3 &s3 , Op op ) + { + typedef boost::fusion::vector< S1& , S2& , S3& > Sequences; + Sequences sequences( s1 , s2 , s3 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + template< class S1 , class S2 , class S3 , class S4 , class Op > + static void for_each4( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , Op op ) + { + typedef boost::fusion::vector< S1& , S2& , S3& , S4& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class Op > + static void for_each5( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , Op op ) + { + typedef boost::fusion::vector< S1& , S2& , S3& , S4& , S5& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 , s5 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class Op > + static void for_each6( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , Op op ) + { + typedef boost::fusion::vector< S1& , S2& , S3& , S4& , S5& , S6& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 , s5 , s6 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class S7 , class Op > + static void for_each7( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , Op op ) + { + typedef boost::fusion::vector< S1& , S2& , S3& , S4& , S5& , S6& , S7& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 , s5 , s6 , s7 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class S7 , class S8 , class Op > + static void for_each8( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , Op op ) + { + BOOST_STATIC_ASSERT_MSG( BOOST_FUSION_INVOKE_MAX_ARITY >= 8 , "Macro Parameter BOOST_FUSION_INVOKE_MAX_ARITY to small!" ); + typedef boost::fusion::vector< S1& , S2& , S3& , S4& , S5& , S6& , S7& , S8& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class S7 , class S8 , class S9 , class Op > + static void for_each9( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , Op op ) + { + BOOST_STATIC_ASSERT_MSG( BOOST_FUSION_INVOKE_MAX_ARITY >= 9 , "Macro Parameter BOOST_FUSION_INVOKE_MAX_ARITY to small!" ); + typedef boost::fusion::vector< S1& , S2& , S3& , S4& , S5& , S6& , S7& , S8& , S9& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class S7 , class S8 , class S9 , class S10 , class Op > + static void for_each10( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , Op op ) + { + BOOST_STATIC_ASSERT_MSG( BOOST_FUSION_INVOKE_MAX_ARITY >= 10 , "Macro Parameter BOOST_FUSION_INVOKE_MAX_ARITY to small!" ); + typedef boost::fusion::vector< S1& , S2& , S3& , S4& , S5& , S6& , S7& , S8& , S9& , S10& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class S7 , class S8 , class S9 , class S10 , class S11 , class Op > + static void for_each11( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , Op op ) + { + BOOST_STATIC_ASSERT_MSG( BOOST_FUSION_INVOKE_MAX_ARITY >= 11 , "Macro Parameter BOOST_FUSION_INVOKE_MAX_ARITY to small!" ); + BOOST_STATIC_ASSERT_MSG( BOOST_RESULT_OF_NUM_ARGS >= 11 , "Macro Parameter BOOST_RESULT_OF_NUM_ARGS to small!" ); + typedef boost::fusion::vector< S1& , S2& , S3& , S4& , S5& , S6& , S7& , S8& , S9& , S10& , S11& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 , s11 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class Op > + static void for_each12( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , Op op ) + { + BOOST_STATIC_ASSERT_MSG( BOOST_FUSION_INVOKE_MAX_ARITY >= 12 , "Macro Parameter BOOST_FUSION_INVOKE_MAX_ARITY to small!" ); + BOOST_STATIC_ASSERT_MSG( BOOST_RESULT_OF_NUM_ARGS >= 12 , "Macro Parameter BOOST_RESULT_OF_NUM_ARGS to small!" ); + typedef boost::fusion::vector< S1& , S2& , S3& , S4& , S5& , S6& , S7& , S8& , S9& , S10& , S11& , S12& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 , s11 , s12 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class S13 , class Op > + static void for_each13( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , S13 &s13 , Op op ) + { + BOOST_STATIC_ASSERT_MSG( BOOST_FUSION_INVOKE_MAX_ARITY >= 13 , "Macro Parameter BOOST_FUSION_INVOKE_MAX_ARITY to small!" ); + BOOST_STATIC_ASSERT_MSG( BOOST_RESULT_OF_NUM_ARGS >= 13 , "Macro Parameter BOOST_RESULT_OF_NUM_ARGS to small!" ); + typedef boost::fusion::vector< S1& , S2& , S3& , S4& , S5& , S6& , S7& , S8& , S9& , S10& , S11& , S12& , S13& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 , s11 , s12 , s13 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class S13 , class S14 , class Op > + static void for_each14( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , S13 &s13 , S14 &s14 , Op op ) + { + BOOST_STATIC_ASSERT_MSG( BOOST_FUSION_INVOKE_MAX_ARITY >= 14 , "Macro Parameter BOOST_FUSION_INVOKE_MAX_ARITY to small!" ); + BOOST_STATIC_ASSERT_MSG( BOOST_RESULT_OF_NUM_ARGS >= 14 , "Macro Parameter BOOST_RESULT_OF_NUM_ARGS to small!" ); + typedef boost::fusion::vector< S1& , S2& , S3& , S4& , S5& , S6& , S7& , S8& , S9& , S10& , S11& , S12& , S13& , S14& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 , s11 , s12 , s13 , s14 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class S13 , class S14 , class S15 , class Op > + static void for_each15( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , S13 &s13 , S14 &s14 , S15 &s15 , Op op ) + { + BOOST_STATIC_ASSERT_MSG( BOOST_FUSION_INVOKE_MAX_ARITY >= 15 , "Macro Parameter BOOST_FUSION_INVOKE_MAX_ARITY to small!" ); + BOOST_STATIC_ASSERT_MSG( BOOST_RESULT_OF_NUM_ARGS >= 15 , "Macro Parameter BOOST_RESULT_OF_NUM_ARGS to small!" ); + typedef boost::fusion::vector< S1& , S2& , S3& , S4& , S5& , S6& , S7& , S8& , S9& , S10& , S11& , S12& , S13& , S14& , S15& > Sequences; + Sequences sequences( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 , s11 , s12 , s13 , s14 , s15 ); + boost::fusion::for_each( boost::fusion::zip_view< Sequences >( sequences ) , boost::fusion::make_fused( op ) ); + } + + template< class Value , class S , class Reduction > + static Value reduce( const S &s , Reduction red , Value init) + { + return boost::fusion::accumulate( s , init , red ); + } +}; + + + +} // odeint +} // numeric +} // boost + + +#endif // BOOST_NUMERIC_ODEINT_ALGEBRA_FUSION_ALGEBRA_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/algebra/range_algebra.hpp b/include/boost/numeric/odeint/algebra/range_algebra.hpp new file mode 100644 index 00000000..c54e09bf --- /dev/null +++ b/include/boost/numeric/odeint/algebra/range_algebra.hpp @@ -0,0 +1,159 @@ +/* + [auto_generated] + boost/numeric/odeint/algebra/range_algebra.hpp + + [begin_description] + Default algebra, which works with the most state types, like vector< double >, boost::array< double >, boost::range. + Internally is uses boost::range to obtain the begin and end iterator of the according sequence. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_ALGEBRA_RANGE_ALGEBRA_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_ALGEBRA_RANGE_ALGEBRA_HPP_INCLUDED + +#include +#include + +#include +#include +#include + +namespace boost { +namespace numeric { +namespace odeint { + +struct range_algebra +{ + template< class S1 , class Op > + static void for_each1( S1 &s1 , Op op ) + { + detail::for_each1( boost::begin( s1 ) , boost::end( s1 ) , + op ); + } + + template< class S1 , class S2 , class Op > + static void for_each2( S1 &s1 , S2 &s2 , Op op ) + { + detail::for_each2( boost::begin( s1 ) , boost::end( s1 ) , + boost::begin( s2 ) , op ); + } + + template< class S1 , class S2 , class S3 , class Op > + static void for_each3( S1 &s1 , S2 &s2 , S3 &s3 , Op op ) + { + detail::for_each3( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class Op > + static void for_each4( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , Op op ) + { + detail::for_each4( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class Op > + static void for_each5( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , Op op ) + { + detail::for_each5( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , boost::begin( s5 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class Op > + static void for_each6( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , Op op ) + { + detail::for_each6( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , boost::begin( s5 ) , boost::begin( s6 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class Op > + static void for_each7( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , Op op ) + { + detail::for_each7( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , boost::begin( s5 ) , boost::begin( s6 ) , boost::begin( s7 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class Op > + static void for_each8( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , Op op ) + { + detail::for_each8( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , boost::begin( s5 ) , boost::begin( s6 ) , boost::begin( s7 ) , boost::begin( s8 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class Op > + static void for_each9( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , Op op ) + { + detail::for_each9( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , boost::begin( s5 ) , boost::begin( s6 ) , boost::begin( s7 ) , boost::begin( s8 ) , boost::begin( s9 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class Op > + static void for_each10( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , Op op ) + { + detail::for_each10( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , boost::begin( s5 ) , boost::begin( s6 ) , boost::begin( s7 ) , boost::begin( s8 ) , boost::begin( s9 ) , boost::begin( s10 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class S11 , class Op > + static void for_each11( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , Op op ) + { + detail::for_each11( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , boost::begin( s5 ) , boost::begin( s6 ) , boost::begin( s7 ) , boost::begin( s8 ) , boost::begin( s9 ) , boost::begin( s10 ) , boost::begin( s11 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class Op > + static void for_each12( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , Op op ) + { + detail::for_each12( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , boost::begin( s5 ) , boost::begin( s6 ) , boost::begin( s7 ) , boost::begin( s8 ) , boost::begin( s9 ) , boost::begin( s10 ) , boost::begin( s11 ) , boost::begin( s12 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class S13 , class Op > + static void for_each13( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , S13 &s13 , Op op ) + { + detail::for_each13( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , boost::begin( s5 ) , boost::begin( s6 ) , boost::begin( s7 ) , boost::begin( s8 ) , boost::begin( s9 ) , boost::begin( s10 ) , boost::begin( s11 ) , boost::begin( s12 ) , boost::begin( s13 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class S13 , class S14 , class Op > + static void for_each14( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , S13 &s13 , S14 &s14 , Op op ) + { + detail::for_each14( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , boost::begin( s5 ) , boost::begin( s6 ) , boost::begin( s7 ) , boost::begin( s8 ) , boost::begin( s9 ) , boost::begin( s10 ) , boost::begin( s11 ) , boost::begin( s12 ) , boost::begin( s13 ) , boost::begin( s14 ) , op ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class S13 , class S14 , class S15 , class Op > + static void for_each15( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , S13 &s13 , S14 &s14 , S15 &s15 , Op op ) + { + detail::for_each15( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , boost::begin( s5 ) , boost::begin( s6 ) , boost::begin( s7 ) , boost::begin( s8 ) , boost::begin( s9 ) , boost::begin( s10 ) , boost::begin( s11 ) , boost::begin( s12 ) , boost::begin( s13 ) , boost::begin( s14 ) , boost::begin( s15 ) , op ); + } + + template< class Value , class S , class Red > + static Value reduce( const S &s , Red red , Value init) + { + return detail::reduce( boost::begin( s ) , boost::end( s ) , red , init ); + } + + template< class Value , class S1 , class S2 , class Red > + static Value reduce2( const S1 &s1 , const S2 &s2 , Red red , Value init ) + { + return detail::reduce2( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , red , init ); + } + + template< class Value , class S1 , class S2 , class S3 , class Red > + static Value reduce3( const S1 &s1 , const S2 &s2 , const S3 &s3 , Red red , Value init ) + { + return detail::reduce3( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , red , init ); + } + + template< class Value , class S1 , class S2 , class S3 , class S4 , class Red > + static Value reduce4( const S1 &s1 , const S2 &s2 , const S3 &s3 , const S4 &s4 , Red red , Value init ) + { + return detail::reduce4( boost::begin( s1 ) , boost::end( s1 ) , boost::begin( s2 ) , boost::begin( s3 ) , boost::begin( s4 ) , red , init ); + } + + +}; + +} // odeint +} // numeric +} // boost + + +#endif // BOOST_NUMERIC_ODEINT_ALGEBRA_RANGE_ALGEBRA_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/algebra/vector_space_algebra.hpp b/include/boost/numeric/odeint/algebra/vector_space_algebra.hpp new file mode 100644 index 00000000..4673b9b2 --- /dev/null +++ b/include/boost/numeric/odeint/algebra/vector_space_algebra.hpp @@ -0,0 +1,156 @@ +/* + [auto_generated] + boost/numeric/odeint/algebra/vector_space_algebra.hpp + + [begin_description] + An algebra for types which have vector space semantics, hence types on which the operators +,-,* are well defined. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_ALGEBRA_VECTOR_SPACE_ALGEBRA_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_ALGEBRA_VECTOR_SPACE_ALGEBRA_HPP_INCLUDED + +#include + + +namespace boost { +namespace numeric { +namespace odeint { + + +/* + * This class template has to be overload in order to call vector_space_algebra::reduce + */ +template< class State > struct vector_space_reduce; + +/* + * Example: instantiation for sole doubles + */ +template<> +struct vector_space_reduce< double > +{ + template< class Op > + double operator()( double x , Op op , double init ) const + { + init = op( init , x ); + return init; + } +}; + + +struct vector_space_algebra +{ + template< class S1 , class Op > + static void for_each1( S1 &s1 , Op op ) + { + // ToDo : build checks, that the +-*/ operators are well defined + op( s1 ); + } + + template< class S1 , class S2 , class Op > + static void for_each2( S1 &s1 , S2 &s2 , Op op ) + { + op( s1 , s2 ); + } + + template< class S1 , class S2 , class S3 , class Op > + static void for_each3( S1 &s1 , S2 &s2 , S3 &s3 , Op op ) + { + op( s1 , s2 , s3 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class Op > + static void for_each4( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , Op op ) + { + op( s1 , s2 , s3 , s4 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class Op > + static void for_each5( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , Op op ) + { + op( s1 , s2 , s3 , s4 , s5 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 , class Op > + static void for_each6( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , Op op ) + { + op( s1 , s2 , s3 , s4 , s5 , s6 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class Op > + static void for_each7( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , Op op ) + { + op( s1 , s2 , s3 , s4 , s5 , s6 , s7 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class Op > + static void for_each8( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , Op op ) + { + op( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class Op > + static void for_each9( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , Op op ) + { + op( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class Op > + static void for_each10( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , Op op ) + { + op( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class S11 , class Op > + static void for_each11( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , Op op ) + { + op( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 , s11 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class Op > + static void for_each12( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , Op op ) + { + op( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 , s11 , s12 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class S13 , class Op > + static void for_each13( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , S13 &s13 , Op op ) + { + op( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 , s11 , s12 , s13 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class S13 , class S14 , class Op > + static void for_each14( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , S13 &s13 , S14 &s14 , Op op ) + { + op( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 , s11 , s12 , s13 , s14 ); + } + + template< class S1 , class S2 , class S3 , class S4 , class S5 , class S6 ,class S7 , class S8 , class S9 , class S10 , class S11 , class S12 , class S13 , class S14 , class S15 , class Op > + static void for_each15( S1 &s1 , S2 &s2 , S3 &s3 , S4 &s4 , S5 &s5 , S6 &s6 , S7 &s7 , S8 &s8 , S9 &s9 , S10 &s10 , S11 &s11 , S12 &s12 , S13 &s13 , S14 &s14 , S15 &s15 , Op op ) + { + op( s1 , s2 , s3 , s4 , s5 , s6 , s7 , s8 , s9 , s10 , s11 , s12 , s13 , s14 , s15 ); + } + + template< class Value , class S , class Red > + static Value reduce( const S &s , Red red , Value init ) + { + boost::numeric::odeint::vector_space_reduce< S > r; + return r( s , red , init ); + } +}; + + +} // odeint +} // numeric +} // boost + + +#endif // BOOST_NUMERIC_ODEINT_ALGEBRA_VECTOR_SPACE_ALGEBRA_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/config.hpp b/include/boost/numeric/odeint/config.hpp new file mode 100644 index 00000000..0d08982b --- /dev/null +++ b/include/boost/numeric/odeint/config.hpp @@ -0,0 +1,47 @@ +/* + [auto_generated] + boost/numeric/odeint/config.hpp + + [begin_description] + Sets configurations for odeint and used libraries. Should be included before any other odeint library + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#ifndef BOOST_NUMERIC_ODEINT_CONFIG_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_CONFIG_HPP_INCLUDED + +//increase macro variable to allow rk78 scheme +#ifndef FUSION_MAX_VECTOR_SIZE +#define FUSION_MAX_VECTOR_SIZE 15 +#endif + +/* + * the following definitions are only required if fusion vectors are used as state types + * in the rk78 scheme + * they should be defined by the user if required, see e.g. libs/numeric/examples/harmonic_oscillator_units.cpp + */ +#ifndef BOOST_FUSION_INVOKE_MAX_ARITY +#define BOOST_FUSION_INVOKE_MAX_ARITY 15 +#endif + +#ifndef BOOST_RESULT_OF_NUM_ARGS +#define BOOST_RESULT_OF_NUM_ARGS 15 +#endif +/* + */ + +#include + +#if __cplusplus >= 201103L +#define BOOST_NUMERIC_ODEINT_CXX11 1 +#endif + + +#endif // BOOST_NUMERIC_ODEINT_CONFIG_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/external/gsl/gsl_wrapper.hpp b/include/boost/numeric/odeint/external/gsl/gsl_wrapper.hpp new file mode 100644 index 00000000..c961a894 --- /dev/null +++ b/include/boost/numeric/odeint/external/gsl/gsl_wrapper.hpp @@ -0,0 +1,229 @@ +/* + [auto_generated] + boost/numeric/odeint/external/gsl/gsl_wrapper.hpp + + [begin_description] + Wrapper for gsl_vector. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_EXTERNAL_GSL_GSL_WRAPPER_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_EXTERNAL_GSL_GSL_WRAPPER_HPP_INCLUDED + +#include + +#include + +#include +#include +#include + + +#include +#include +#include + +class const_gsl_vector_iterator; + +/* + * defines an iterator for gsl_vector + */ +class gsl_vector_iterator : public boost::iterator_facade< gsl_vector_iterator , double , boost::random_access_traversal_tag > +{ +public : + + gsl_vector_iterator( void ): m_p(0) , m_stride( 0 ) { } + explicit gsl_vector_iterator( gsl_vector *p ) : m_p( p->data ) , m_stride( p->stride ) { } + friend gsl_vector_iterator end_iterator( gsl_vector * ); + +private : + + friend class boost::iterator_core_access; + friend class const_gsl_vector_iterator; + + void increment( void ) { m_p += m_stride; } + void decrement( void ) { m_p -= m_stride; } + void advance( ptrdiff_t n ) { m_p += n*m_stride; } + bool equal( const gsl_vector_iterator &other ) const { return this->m_p == other.m_p; } + bool equal( const const_gsl_vector_iterator &other ) const; + double& dereference( void ) const { return *m_p; } + + double *m_p; + size_t m_stride; +}; + + + +/* + * defines an const iterator for gsl_vector + */ +class const_gsl_vector_iterator : public boost::iterator_facade< const_gsl_vector_iterator , const double , boost::random_access_traversal_tag > +{ +public : + + const_gsl_vector_iterator( void ): m_p(0) , m_stride( 0 ) { } + explicit const_gsl_vector_iterator( const gsl_vector *p ) : m_p( p->data ) , m_stride( p->stride ) { } + const_gsl_vector_iterator( const gsl_vector_iterator &p ) : m_p( p.m_p ) , m_stride( p.m_stride ) { } + +private : + + friend class boost::iterator_core_access; + friend class gsl_vector_iterator; + friend const_gsl_vector_iterator end_iterator( const gsl_vector * ); + + void increment( void ) { m_p += m_stride; } + void decrement( void ) { m_p -= m_stride; } + void advance( ptrdiff_t n ) { m_p += n*m_stride; } + bool equal( const const_gsl_vector_iterator &other ) const { return this->m_p == other.m_p; } + bool equal( const gsl_vector_iterator &other ) const { return this->m_p == other.m_p; } + const double& dereference( void ) const { return *m_p; } + + const double *m_p; + size_t m_stride; +}; + + +bool gsl_vector_iterator::equal( const const_gsl_vector_iterator &other ) const { return this->m_p == other.m_p; } + + +gsl_vector_iterator end_iterator( gsl_vector *x ) +{ + gsl_vector_iterator iter( x ); + iter.m_p += iter.m_stride * x->size; + return iter; +} + +const_gsl_vector_iterator end_iterator( const gsl_vector *x ) +{ + const_gsl_vector_iterator iter( x ); + iter.m_p += iter.m_stride * x->size; + return iter; +} + + + + +namespace boost +{ +template<> +struct range_mutable_iterator< gsl_vector* > +{ + typedef gsl_vector_iterator type; +}; + +template<> +struct range_const_iterator< gsl_vector* > +{ + typedef const_gsl_vector_iterator type; +}; +} // namespace boost + + + + +// template<> +inline gsl_vector_iterator range_begin( gsl_vector *x ) +{ + return gsl_vector_iterator( x ); +} + +// template<> +inline const_gsl_vector_iterator range_begin( const gsl_vector *x ) +{ + return const_gsl_vector_iterator( x ); +} + +// template<> +inline gsl_vector_iterator range_end( gsl_vector *x ) +{ + return end_iterator( x ); +} + +// template<> +inline const_gsl_vector_iterator range_end( const gsl_vector *x ) +{ + return end_iterator( x ); +} + + + + + + + +namespace boost { +namespace numeric { +namespace odeint { + + +template<> +struct is_resizeable< gsl_vector* > +{ + //struct type : public boost::true_type { }; + typedef boost::true_type type; + const static bool value = type::value; +}; + +template <> +struct same_size_impl< gsl_vector* , gsl_vector* > +{ + static bool same_size( const gsl_vector* x , const gsl_vector* y ) + { + return x->size == y->size; + } +}; + +template <> +struct resize_impl< gsl_vector* , gsl_vector* > +{ + static void resize( gsl_vector* x , const gsl_vector* y ) + { + gsl_vector_free( x ); + x = gsl_vector_alloc( y->size ); + } +}; + +template<> +struct state_wrapper< gsl_vector* > +{ + typedef double value_type; + typedef gsl_vector* state_type; + typedef state_wrapper< gsl_vector* > state_wrapper_type; + + state_type m_v; + + state_wrapper( ) + { + m_v = gsl_vector_alloc( 1 ); + } + + state_wrapper( const state_wrapper_type &x ) + { + resize( m_v , x.m_v ); + gsl_vector_memcpy( m_v , x.m_v ); + } + + + ~state_wrapper() + { + gsl_vector_free( m_v ); + } + +}; + +} // odeint +} // numeric +} // boost + + + + +#endif // BOOST_NUMERIC_ODEINT_EXTERNAL_GSL_GSL_WRAPPER_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/external/mkl/mkl_operations.hpp b/include/boost/numeric/odeint/external/mkl/mkl_operations.hpp new file mode 100644 index 00000000..82c66055 --- /dev/null +++ b/include/boost/numeric/odeint/external/mkl/mkl_operations.hpp @@ -0,0 +1,181 @@ +/* + [auto_generated] + boost/numeric/odeint/external/mkl/mkl_operations.hpp + + [begin_description] + Wrapper classes for intel math kernel library types. + Get a free, non-commercial download of MKL at + http://software.intel.com/en-us/articles/non-commercial-software-download/ + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_EXTERNAL_MKL_MKL_OPERATIONS_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_EXTERNAL_MKL_MKL_OPERATIONS_HPP_INCLUDED + +#include + +#include +#include + +/* exemplary example for writing bindings to the Intel MKL library + * see test/mkl for how to use mkl with odeint + * this is a quick and dirty implementation showing the general possibility. + * It works only with containers based on double and sequentiel memory allocation. + */ + +namespace boost { +namespace numeric { +namespace odeint { + +/* only defined for doubles */ +struct mkl_operations +{ + //template< class Fac1 , class Fac2 > struct scale_sum2; + + template< class F1 = double , class F2 = F1 > + struct scale_sum2 + { + typedef double Fac1; + typedef double Fac2; + const Fac1 m_alpha1; + const Fac2 m_alpha2; + + scale_sum2( const Fac1 alpha1 , const Fac2 alpha2 ) : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) { } + + template< class T1 , class T2 , class T3 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3) const + { // t1 = m_alpha1 * t2 + m_alpha2 * t3; + // we get Containers that have size() and [i]-access + + const int n = t1.size(); + //boost::numeric::odeint::copy( t1 , t3 ); + if( &(t2[0]) != &(t1[0]) ) + { + cblas_dcopy( n , &(t2[0]) , 1 , &(t1[0]) , 1 ); + } + cblas_dscal( n , m_alpha1 , &(t1[0]) , 1 ); + cblas_daxpy( n , m_alpha2 , &(t3[0]) , 1 , &(t1[0]) , 1 ); + //daxpby( &n , &m_alpha2 , &(t3[0]) , &one , &m_alpha1 , &(t1[0]) , &one ); + } + }; + + template< class F1 = double , class F2 = F1 , class F3 = F2 > + struct scale_sum3 + { + typedef double Fac1; + typedef double Fac2; + typedef double Fac3; + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + + scale_sum3( const Fac1 alpha1 , const Fac2 alpha2 , const Fac3 alpha3 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) { } + + template< class T1 , class T2 , class T3 , class T4 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 ) const + { // t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4; + // we get Containers that have size() and [i]-access + + const int n = t1.size(); + //boost::numeric::odeint::copy( t1 , t3 ); + if( &(t2[0]) != &(t1[0]) ) + { + cblas_dcopy( n , &(t2[0]) , 1 , &(t1[0]) , 1 ); + } + cblas_dscal( n , m_alpha1 , &(t1[0]) , 1 ); + cblas_daxpy( n , m_alpha2 , &(t3[0]) , 1 , &(t1[0]) , 1 ); + //daxpby( &n , &m_alpha2 , &(t3[0]) , &one , &m_alpha1 , &(t1[0]) , &one ); + cblas_daxpy( n , m_alpha3 , &(t4[0]) , 1 , &(t1[0]) , 1 ); + } + }; + + template< class F1 = double , class F2 = F1 , class F3 = F2 , class F4 = F3 > + struct scale_sum4 + { + typedef double Fac1; + typedef double Fac2; + typedef double Fac3; + typedef double Fac4; + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + + scale_sum4( const Fac1 alpha1 , const Fac2 alpha2 , const Fac3 alpha3 , const Fac4 alpha4 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 ) const + { // t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5; + // we get Containers that have size() and [i]-access + + const int n = t1.size(); + //boost::numeric::odeint::copy( t1 , t3 ); + if( &(t2[0]) != &(t1[0]) ) + { + cblas_dcopy( n , &(t2[0]) , 1 , &(t1[0]) , 1 ); + } + + cblas_dscal( n , m_alpha1 , &(t1[0]) , 1 ); + cblas_daxpy( n , m_alpha2 , &(t3[0]) , 1 , &(t1[0]) , 1 ); + //daxpby( &n , &m_alpha2 , &(t3[0]) , &one , &m_alpha1 , &(t1[0]) , &one ); + cblas_daxpy( n , m_alpha3 , &(t4[0]) , 1 , &(t1[0]) , 1 ); + cblas_daxpy( n , m_alpha4 , &(t5[0]) , 1 , &(t1[0]) , 1 ); + } + }; + + + template< class F1 = double , class F2 = F1 , class F3 = F2 , class F4 = F3 , class F5 = F4 > + struct scale_sum5 + { + typedef double Fac1; + typedef double Fac2; + typedef double Fac3; + typedef double Fac4; + typedef double Fac5; + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + + scale_sum5( const Fac1 alpha1 , const Fac2 alpha2 , const Fac3 alpha3 , const Fac4 alpha4 , const Fac5 alpha5 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 > + void operator()( T1 &t1 , const T2 &t2 , const T3 &t3 , const T4 &t4 , const T5 &t5 , const T6 &t6 ) const + { // t1 = m_alpha1 * t2 + m_alpha2 * t3 + m_alpha3 * t4 + m_alpha4 * t5 + m_alpha5 * t6; + // we get Containers that have size() and [i]-access + + const int n = t1.size(); + //boost::numeric::odeint::copy( t1 , t3 ); + if( &(t2[0]) != &(t1[0]) ) + { + cblas_dcopy( n , &(t2[0]) , 1 , &(t1[0]) , 1 ); + } + + cblas_dscal( n , m_alpha1 , &(t1[0]) , 1 ); + cblas_daxpy( n , m_alpha2 , &(t3[0]) , 1 , &(t1[0]) , 1 ); + //daxpby( &n , &m_alpha2 , &(t3[0]) , &one , &m_alpha1 , &(t1[0]) , &one ); + cblas_daxpy( n , m_alpha3 , &(t4[0]) , 1 , &(t1[0]) , 1 ); + cblas_daxpy( n , m_alpha4 , &(t5[0]) , 1 , &(t1[0]) , 1 ); + cblas_daxpy( n , m_alpha5 , &(t6[0]) , 1 , &(t1[0]) , 1 ); + } + }; + +}; + +} // odeint +} // numeric +} // boost + +#endif // BOOST_NUMERIC_ODEINT_EXTERNAL_MKL_MKL_OPERATIONS_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/external/mtl4/implicit_euler_mtl4.hpp b/include/boost/numeric/odeint/external/mtl4/implicit_euler_mtl4.hpp new file mode 100644 index 00000000..7a6fdc62 --- /dev/null +++ b/include/boost/numeric/odeint/external/mtl4/implicit_euler_mtl4.hpp @@ -0,0 +1,162 @@ +/* +[begin_description] +Modification of the implicit Euler method, works with the MTL4 matrix library only. +[end_description] + +Copyright 2009-2011 Karsten Ahnert +Copyright 2009-2011 Mario Mulansky +Copyright 2012 Andreas Angelopoulos + +Distributed under the Boost Software License, Version 1.0. +(See accompanying file LICENSE_1_0.txt or +copy at http://www.boost.org/LICENSE_1_0.txt) +*/ + + +#ifndef BOOST_NUMERIC_ODEINT_EXTERNAL_IMPLICIT_EULER_MTL4_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_EXTERNAL_IMPLICIT_EULER_MTL4_HPP_INCLUDED + + +#include + +#include +#include +#include + +#include + +#include +#include + + + + +namespace boost { +namespace numeric { +namespace odeint { + + +template< class ValueType , class Resizer = initially_resizer > +class implicit_euler_mtl4 +{ + +public: + + typedef ValueType value_type; + typedef value_type time_type; + typedef mtl::dense_vector state_type; + + typedef state_wrapper< state_type > wrapped_state_type; + typedef state_type deriv_type; + typedef state_wrapper< deriv_type > wrapped_deriv_type; + typedef mtl::compressed2D< value_type > matrix_type; + typedef state_wrapper< matrix_type > wrapped_matrix_type; + + typedef Resizer resizer_type; + typedef stepper_tag stepper_category; + + typedef implicit_euler_mtl4< ValueType , Resizer > stepper_type; + + + implicit_euler_mtl4( const value_type epsilon = 1E-6 ) + : m_epsilon( epsilon ) , m_resizer() , + m_dxdt() , m_x() , + m_identity() , m_jacobi() + { } + + + template< class System > + void do_step( System system , state_type &x , time_type t , time_type dt ) + { + typedef typename odeint::unwrap_reference< System >::type system_type; + typedef typename odeint::unwrap_reference< typename system_type::first_type >::type deriv_func_type; + typedef typename odeint::unwrap_reference< typename system_type::second_type >::type jacobi_func_type; + system_type &sys = system; + deriv_func_type &deriv_func = sys.first; + jacobi_func_type &jacobi_func = sys.second; + + m_resizer.adjust_size( x , detail::bind( + &stepper_type::template resize_impl< state_type > , detail::ref( *this ) , detail::_1 ) ); + + m_identity.m_v = 1; + + t += dt; + m_x.m_v = x; + + deriv_func( x , m_dxdt.m_v , t ); + jacobi_func( x , m_jacobi.m_v , t ); + + + m_dxdt.m_v *= -dt; + + m_jacobi.m_v *= dt; + m_jacobi.m_v -= m_identity.m_v ; + + + + // using ilu_0 preconditioning -incomplete LU factorisation + // itl::pc::diagonal L(m_jacobi.m_v); + itl::pc::ilu_0 L( m_jacobi.m_v ); + + solve( m_jacobi.m_v , m_x.m_v , m_dxdt.m_v , L ); + x+= m_x.m_v; + + + } + + + template< class StateType > + void adjust_size( const StateType &x ) + { + resize_impl( x ); + } + + +private: + + + /* + Applying approximate iteractive linear solvers + default solver is Biconjugate gradient stabilized method + itl::bicgstab(A, x, b, L, iter); + */ + template < class LinearOperator, class HilbertSpaceX, class HilbertSpaceB, class Preconditioner> + void solve(const LinearOperator& A, HilbertSpaceX& x, const HilbertSpaceB& b, + const Preconditioner& L, int max_iteractions =500) + { + // Termination criterion: r < 1e-6 * b or N iterations + itl::basic_iteration< double > iter( b , max_iteractions , 1e-6 ); + itl::bicgstab( A , x , b , L , iter ); + + } + + + template< class StateIn > + bool resize_impl( const StateIn &x ) + { + bool resized = false; + resized |= adjust_size_by_resizeability( m_dxdt , x , typename is_resizeable::type() ); + resized |= adjust_size_by_resizeability( m_x , x , typename is_resizeable::type() ); + resized |= adjust_size_by_resizeability( m_identity , x , typename is_resizeable::type() ); + resized |= adjust_size_by_resizeability( m_jacobi , x , typename is_resizeable::type() ); + return resized; + } + + +private: + + value_type m_epsilon; + resizer_type m_resizer; + wrapped_deriv_type m_dxdt; + wrapped_state_type m_x; + wrapped_matrix_type m_identity; + wrapped_matrix_type m_jacobi; +}; + + +} // odeint +} // numeric +} // boost + + +#endif // BOOST_NUMERIC_ODEINT_EXTERNAL_IMPLICIT_EULER_MTL4_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/external/mtl4/mtl4_resize.hpp b/include/boost/numeric/odeint/external/mtl4/mtl4_resize.hpp new file mode 100644 index 00000000..93569747 --- /dev/null +++ b/include/boost/numeric/odeint/external/mtl4/mtl4_resize.hpp @@ -0,0 +1,133 @@ +/* +[begin_description] +Modification of the implicit Euler method, works with the MTL4 matrix library only. +[end_description] + +Copyright 2009-2011 Karsten Ahnert +Copyright 2009-2011 Mario Mulansky +Copyright 2012 Andreas Angelopoulos + +Distributed under the Boost Software License, Version 1.0. +(See accompanying file LICENSE_1_0.txt or +copy at http://www.boost.org/LICENSE_1_0.txt) +*/ + + +#ifndef BOOST_NUMERIC_ODEINT_EXTERNAL_MTL4_RESIZE_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_EXTERNAL_MTL4_RESIZE_HPP_INCLUDED + +#include +#include +#include + +#include +#include +#include + + +namespace boost { +namespace numeric { +namespace odeint { + + +template< class Value , class Parameters > +struct is_resizeable< mtl::dense_vector< Value , Parameters > > +{ + typedef boost::true_type type; + const static bool value = type::value; +}; + +template< class Value , class Parameters > +struct is_resizeable< mtl::dense2D< Value , Parameters > > +{ + typedef boost::true_type type; + const static bool value = type::value; +}; + +template< class Value , class Parameters > +struct is_resizeable< mtl::compressed2D< Value , Parameters > > +{ + typedef boost::true_type type; + const static bool value = type::value; +}; + + + + +template< class Value , class Parameters > +struct same_size_impl< mtl::dense_vector< Value , Parameters > , mtl::dense_vector< Value , Parameters > > +{ + static bool same_size( const mtl::dense_vector< Value , Parameters > &v1 , + const mtl::dense_vector< Value , Parameters > &v2 ) + { + return mtl::size( v1 ) == mtl::size( v2 ); + } +}; + +template< class Value , class Parameters > +struct resize_impl< mtl::dense_vector< Value , Parameters > , mtl::dense_vector< Value , Parameters > > +{ + static void resize( mtl::dense_vector< Value , Parameters > &v1 , + const mtl::dense_vector< Value , Parameters > &v2 ) + { + v1.change_dim( mtl::size( v2 ) ); + } +}; + + + +template< class Value , class MatrixParameters , class VectorParameters > +struct same_size_impl< mtl::dense2D< Value , MatrixParameters > , mtl::dense_vector< Value , VectorParameters > > +{ + static bool same_size( const mtl::dense2D< Value , MatrixParameters > &m , + const mtl::dense_vector< Value , VectorParameters > &v ) + { + return ( ( mtl::size( v ) == m.num_cols() ) && ( mtl::size( v ) == m.num_rows() ) ); + } +}; + +template< class Value , class MatrixParameters , class VectorParameters > +struct resize_impl< mtl::dense2D< Value , MatrixParameters > , mtl::dense_vector< Value , VectorParameters > > +{ + static void resize( mtl::dense2D< Value , MatrixParameters > &m , + const mtl::dense_vector< Value , VectorParameters > &v ) + { + m.change_dim( mtl::size( v ) , mtl::size( v ) , false ); + } +}; + + + + +template< class Value , class MatrixParameters , class VectorParameters > +struct same_size_impl< mtl::compressed2D< Value , MatrixParameters > , mtl::dense_vector< Value , VectorParameters > > +{ + static bool same_size( const mtl::compressed2D< Value , MatrixParameters > &m , + const mtl::dense_vector< Value , VectorParameters > &v ) + { + return ( ( mtl::size( v ) == m.num_cols() ) && ( mtl::size( v ) == m.num_rows() ) ); + } +}; + +template< class Value , class MatrixParameters , class VectorParameters > +struct resize_impl< mtl::compressed2D< Value , MatrixParameters > , mtl::dense_vector< Value , VectorParameters > > +{ + static void resize( mtl::compressed2D< Value , MatrixParameters > &m , + const mtl::dense_vector< Value , VectorParameters > &v ) + { + m.change_dim( mtl::size( v ) , mtl::size( v ) ); + } +}; + + + + + + + + +} // namespace odeint +} // namesapce numeric +} // namespace boost + +#endif // BOOST_NUMERIC_ODEINT_EXTERNAL_MTL4_RESIZE_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/external/thrust/thrust_algebra.hpp b/include/boost/numeric/odeint/external/thrust/thrust_algebra.hpp new file mode 100644 index 00000000..0f6b5939 --- /dev/null +++ b/include/boost/numeric/odeint/external/thrust/thrust_algebra.hpp @@ -0,0 +1,198 @@ +/* + [auto_generated] + boost/numeric/odeint/external/thrust/thrust_algebra.hpp + + [begin_description] + An algebra for thrusts device_vectors. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_EXTERNAL_THRUST_THRUST_ALGEBRA_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_EXTERNAL_THRUST_THRUST_ALGEBRA_HPP_INCLUDED + + +#include +#include +#include + +#include + +namespace boost { +namespace numeric { +namespace odeint { + + + +/** ToDO extend until for_each14 for rk78 */ + +/* + * The const versions are needed for boost.range to work, i.e. + * it allows you to do + * for_each1( make_pair( vec1.begin() , vec1.begin() + 10 ) , op ); + */ + +struct thrust_algebra +{ + template< class StateType , class Operation > + static void for_each1( StateType &s , Operation op ) + { + thrust::for_each( boost::begin(s) , boost::begin(s) , op ); + } + + template< class StateType1 , class StateType2 , class Operation > + static void for_each2( StateType1 &s1 , StateType2 &s2 , Operation op ) + { + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( boost::begin(s1) , + boost::begin(s2) ) ) , + thrust::make_zip_iterator( thrust::make_tuple( boost::end(s1) , + boost::end(s2) ) ) , + op); + } + + template< class StateType1 , class StateType2 , class StateType3 , class Operation > + static void for_each3( StateType1 &s1 , StateType2 &s2 , StateType3 &s3 , Operation op ) + { + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( boost::begin(s1) , + boost::begin(s2) , + boost::begin(s3) ) ) , + thrust::make_zip_iterator( thrust::make_tuple( boost::end(s1) , + boost::end(s2) , + boost::end(s3) ) ) , + op); + } + + template< class StateType1 , class StateType2 , class StateType3 , class StateType4 , + class Operation > + static void for_each4( StateType1 &s1 , StateType2 &s2 , StateType3 &s3 , StateType4 &s4 , + Operation op ) + { + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( boost::begin(s1) , + boost::begin(s2) , + boost::begin(s3) , + boost::begin(s4) ) ) , + thrust::make_zip_iterator( thrust::make_tuple( boost::end(s1) , + boost::end(s2) , + boost::end(s3) , + boost::end(s4) ) ) , + op); + } + + template< class StateType1 , class StateType2 , class StateType3 , + class StateType4 , class StateType5 ,class Operation > + static void for_each5( StateType1 &s1 , StateType2 &s2 , StateType3 &s3 , StateType4 &s4 , + StateType5 &s5 , Operation op ) + { + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( boost::begin(s1) , + boost::begin(s2) , + boost::begin(s3) , + boost::begin(s4) , + boost::begin(s5) ) ) , + thrust::make_zip_iterator( thrust::make_tuple( boost::end(s1) , + boost::end(s2) , + boost::end(s3) , + boost::end(s4) , + boost::end(s5) ) ) , + op); + } + + template< class StateType1 , class StateType2 , class StateType3 , + class StateType4 , class StateType5 , class StateType6 , class Operation > + static void for_each6( StateType1 &s1 , StateType2 &s2 , StateType3 &s3 , StateType4 &s4 , + StateType5 &s5 , StateType6 &s6 , Operation op ) + { + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( boost::begin(s1) , + boost::begin(s2) , + boost::begin(s3) , + boost::begin(s4) , + boost::begin(s5) , + boost::begin(s6) ) ) , + thrust::make_zip_iterator( thrust::make_tuple( boost::end(s1) , + boost::end(s2) , + boost::end(s3) , + boost::end(s4) , + boost::end(s5) , + boost::end(s6) ) ) , + op); + } + + template< class StateType1 , class StateType2 , class StateType3 , class StateType4 , + class StateType5 , class StateType6 , class StateType7 , class Operation > + static void for_each7( StateType1 &s1 , StateType2 &s2 , StateType3 &s3 , StateType4 &s4 , + StateType5 &s5 , StateType6 &s6 , StateType7 &s7 , Operation op ) + { + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( boost::begin(s1) , + boost::begin(s2) , + boost::begin(s3) , + boost::begin(s4) , + boost::begin(s5) , + boost::begin(s6) , + boost::begin(s7) ) ) , + thrust::make_zip_iterator( thrust::make_tuple( boost::end(s1) , + boost::end(s2) , + boost::end(s3) , + boost::end(s4) , + boost::end(s5) , + boost::end(s6) , + boost::end(s7) ) ) , + op); + } + + template< class StateType1 , class StateType2 , class StateType3 , class StateType4 , + class StateType5 , class StateType6 , class StateType7 , class StateType8 , class Operation > + static void for_each8( StateType1 &s1 , StateType2 &s2 , StateType3 &s3 , StateType4 &s4 , + StateType5 &s5 , StateType6 &s6 , StateType7 &s7 , StateType8 &s8 , Operation op ) + { + thrust::for_each( + thrust::make_zip_iterator( thrust::make_tuple( boost::begin(s1) , + boost::begin(s2) , + boost::begin(s3) , + boost::begin(s4) , + boost::begin(s5) , + boost::begin(s6) , + boost::begin(s7) , + boost::begin(s8) ) ) , + thrust::make_zip_iterator( thrust::make_tuple( boost::end(s1) , + boost::end(s2) , + boost::end(s3) , + boost::end(s4) , + boost::end(s5) , + boost::end(s6) , + boost::end(s7) , + boost::end(s8) ) ) , + op); + } + + + template< class Value , class S , class Red > + Value reduce( const S &s , Red red , Value init) + { + return thrust::reduce( boost::begin( s ) , boost::end( s ) , init , red ); + } + + + + +}; + + +} // odeint +} // numeric +} // boost + + + +#endif // BOOST_NUMERIC_ODEINT_EXTERNAL_THRUST_THRUST_ALGEBRA_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/external/thrust/thrust_operations.hpp b/include/boost/numeric/odeint/external/thrust/thrust_operations.hpp new file mode 100644 index 00000000..710657ae --- /dev/null +++ b/include/boost/numeric/odeint/external/thrust/thrust_operations.hpp @@ -0,0 +1,252 @@ +/* + [auto_generated] + boost/numeric/odeint/external/thrust/thrust_operations.hpp + + [begin_description] + Operations of thrust zipped iterators. Is the counterpart of the thrust_algebra. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_EXTERNAL_THRUST_THRUST_OPERATIONS_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_EXTERNAL_THRUST_THRUST_OPERATIONS_HPP_INCLUDED + +namespace boost { +namespace numeric { +namespace odeint { + +#include +#include + +/**ToDo extend to scale_sum13 for rk78 */ + +struct thrust_operations +{ + template< class Fac1 = double , class Fac2 = Fac1 > + struct scale_sum2 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + + scale_sum2( const Fac1 alpha1 , const Fac2 alpha2 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) { } + + template< class Tuple > + __host__ __device__ + void operator()( Tuple t ) const + { + thrust::get<0>(t) = m_alpha1 * thrust::get<1>(t) + m_alpha2 * thrust::get<2>(t); + } + }; + + template< class Fac1 = double , class Fac2 = Fac1 > + struct scale_sum_swap2 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + + scale_sum_swap2( const Fac1 alpha1 , const Fac2 alpha2 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) { } + + template< class Tuple > + __host__ __device__ + void operator()( Tuple t ) const + { + typename thrust::tuple_element<0,Tuple>::type tmp = thrust::get<0>(t); + thrust::get<0>(t) = m_alpha1 * thrust::get<1>(t) + m_alpha2 * thrust::get<2>(t); + thrust::get<1>(t) = tmp; + } + }; + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 > + struct scale_sum3 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + + scale_sum3( const Fac1 alpha1 , const Fac2 alpha2 , const Fac3 alpha3 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) { } + + template< class Tuple > + __host__ __device__ + void operator()( Tuple t ) const + { + thrust::get<0>(t) = m_alpha1 * thrust::get<1>(t) + + m_alpha2 * thrust::get<2>(t) + + m_alpha3 * thrust::get<3>(t); + } + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 > + struct scale_sum4 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + + scale_sum4( const Fac1 alpha1 , const Fac2 alpha2 , const Fac3 alpha3 , const Fac4 alpha4 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ){ } + + template< class Tuple > + __host__ __device__ + void operator()( Tuple t ) const + { + thrust::get<0>(t) = m_alpha1 * thrust::get<1>(t) + + m_alpha2 * thrust::get<2>(t) + + m_alpha3 * thrust::get<3>(t) + + m_alpha4 * thrust::get<4>(t); + } + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , + class Fac4 = Fac3 , class Fac5 = Fac4 > + struct scale_sum5 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + + scale_sum5( const Fac1 alpha1 , const Fac2 alpha2 , const Fac3 alpha3 , + const Fac4 alpha4 , const Fac5 alpha5 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , + m_alpha4( alpha4 ) , m_alpha5( alpha5 ) { } + + template< class Tuple > + __host__ __device__ + void operator()( Tuple t ) const + { + thrust::get<0>(t) = m_alpha1 * thrust::get<1>(t) + + m_alpha2 * thrust::get<2>(t) + + m_alpha3 * thrust::get<3>(t) + + m_alpha4 * thrust::get<4>(t) + + m_alpha5 * thrust::get<5>(t); + } + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , + class Fac4 = Fac3 , class Fac5 = Fac4 , class Fac6 = Fac5 > + struct scale_sum6 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + const Fac6 m_alpha6; + + scale_sum6( const Fac1 alpha1 , const Fac2 alpha2 , const Fac3 alpha3 , + const Fac4 alpha4 , const Fac5 alpha5 , const Fac6 alpha6 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , + m_alpha4( alpha4 ) , m_alpha5( alpha5 ) , m_alpha6( alpha6 ) { } + + template< class Tuple > + __host__ __device__ + void operator()( Tuple t ) const + { + thrust::get<0>(t) = m_alpha1 * thrust::get<1>(t) + + m_alpha2 * thrust::get<2>(t) + + m_alpha3 * thrust::get<3>(t) + + m_alpha4 * thrust::get<4>(t) + + m_alpha5 * thrust::get<5>(t) + + m_alpha6 * thrust::get<6>(t); + } + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , + class Fac5 = Fac4 , class Fac6 = Fac5 , class Fac7 = Fac6 > + struct scale_sum7 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + const Fac6 m_alpha6; + const Fac7 m_alpha7; + + scale_sum7( const Fac1 alpha1 , const Fac2 alpha2 , const Fac3 alpha3 , + const Fac4 alpha4 , const Fac5 alpha5 , const Fac6 alpha6 , const Fac7 alpha7 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , + m_alpha4( alpha4 ) , m_alpha5( alpha5 ) , m_alpha6( alpha6 ) , m_alpha7( alpha7 ) { } + + template< class Tuple > + __host__ __device__ + void operator()( Tuple t ) const + { + thrust::get<0>(t) = m_alpha1 * thrust::get<1>(t) + + m_alpha2 * thrust::get<2>(t) + + m_alpha3 * thrust::get<3>(t) + + m_alpha4 * thrust::get<4>(t) + + m_alpha5 * thrust::get<5>(t) + + m_alpha6 * thrust::get<6>(t) + + m_alpha7 * thrust::get<7>(t) ; + } + }; + + + + + template< class Fac1 = double > + struct rel_error + { + const Fac1 m_eps_abs , m_eps_rel , m_a_x , m_a_dxdt; + + rel_error( const Fac1 eps_abs , const Fac1 eps_rel , const Fac1 a_x , const Fac1 a_dxdt ) + : m_eps_abs( eps_abs ) , m_eps_rel( eps_rel ) , m_a_x( a_x ) , m_a_dxdt( a_dxdt ) { } + + + template< class Tuple > + __host__ __device__ + void operator()( Tuple t ) const + { + using std::abs; + thrust::get< 0 >( t ) = abs( thrust::get< 0 >( t ) ) / + ( m_eps_abs + m_eps_rel * ( m_a_x * abs( thrust::get< 1 >( t ) + m_a_dxdt * abs( thrust::get< 2 >( t ) ) ) ) ); + } + + typedef void result_type; + }; + + + /* + * for usage in reduce + */ + + template< class Value > + struct maximum + { + template< class Fac1 , class Fac2 > + __host__ __device__ + Value operator()( const Fac1 t1 , const Fac2 t2 ) const + { + using std::max; + return ( abs( t1 ) < abs( t2 ) ) ? t2 : t1 ; + } + + typedef Value result_type; + }; + + +}; + +} // odeint +} // numeric +} // boost + + +#endif // BOOST_NUMERIC_ODEINT_EXTERNAL_THRUST_THRUST_OPERATIONS_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/external/thrust/thrust_resize.hpp b/include/boost/numeric/odeint/external/thrust/thrust_resize.hpp new file mode 100644 index 00000000..843a1003 --- /dev/null +++ b/include/boost/numeric/odeint/external/thrust/thrust_resize.hpp @@ -0,0 +1,119 @@ +/* + [auto_generated] + boost/numeric/odeint/external/thrust/thrust_resize.hpp + + [begin_description] + Enable resizing for thrusts device and host_vector. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_EXTERNAL_THRUST_THRUST_RESIZE_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_EXTERNAL_THRUST_THRUST_RESIZE_HPP_INCLUDED + + +#include +#include + +#include + +namespace boost { +namespace numeric { +namespace odeint { + +template< class T > +struct is_resizeable< thrust::device_vector< T > > +{ + struct type : public boost::true_type { }; + const static bool value = type::value; +}; + +template< class T > +struct same_size_impl< thrust::device_vector< T > , thrust::device_vector< T > > +{ + static bool same_size( const thrust::device_vector< T > &x , const thrust::device_vector< T > &y ) + { + return x.size() == y.size(); + } +}; + +template< class T > +struct resize_impl< thrust::device_vector< T > , thrust::device_vector< T > > +{ + static void resize( thrust::device_vector< T > &x , const thrust::device_vector< T > &y ) + { + x.resize( y.size() ); + } +}; + + +template< class T > +struct is_resizeable< thrust::host_vector< T > > +{ + struct type : public boost::true_type { }; + const static bool value = type::value; +}; + +template< class T > +struct same_size_impl< thrust::host_vector< T > , thrust::host_vector< T > > +{ + static bool same_size( const thrust::host_vector< T > &x , const thrust::host_vector< T > &y ) + { + return x.size() == y.size(); + } +}; + +template< class T > +struct resize_impl< thrust::host_vector< T > , thrust::host_vector< T > > +{ + static void resize( thrust::host_vector< T > &x , const thrust::host_vector< T > &y ) + { + x.resize( y.size() ); + } +}; + + + +template< class Container1, class Value > +struct copy_impl< Container1 , thrust::device_vector< Value > > +{ + static void copy( const Container1 &from , thrust::device_vector< Value > &to ) + { + thrust::copy( boost::begin( from ) , boost::end( from ) , boost::begin( to ) ); + } +}; + +template< class Value , class Container2 > +struct copy_impl< thrust::device_vector< Value > , Container2 > +{ + static void copy( const thrust::device_vector< Value > &from , Container2 &to ) + { + thrust::copy( boost::begin( from ) , boost::end( from ) , boost::begin( to ) ); + } +}; + +template< class Value > +struct copy_impl< thrust::device_vector< Value > , thrust::device_vector< Value > > +{ + static void copy( const thrust::device_vector< Value > &from , thrust::device_vector< Value > &to ) + { + thrust::copy( boost::begin( from ) , boost::end( from ) , boost::begin( to ) ); + } +}; + + + + +} // odeint +} // numeric +} // boost + + +#endif // BOOST_NUMERIC_ODEINT_EXTERNAL_THRUST_THRUST_RESIZE_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/external/vexcl/vexcl_resize.hpp b/include/boost/numeric/odeint/external/vexcl/vexcl_resize.hpp new file mode 100644 index 00000000..990a0ea2 --- /dev/null +++ b/include/boost/numeric/odeint/external/vexcl/vexcl_resize.hpp @@ -0,0 +1,92 @@ +/* + [auto_generated] + boost/numeric/odeint/external/vexcl/vexcl_resize.hpp + + [begin_description] + Enable resizing for vexcl vector and multivector. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_EXTERNAL_VEXCL_VEXCL_RESIZE_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_EXTERNAL_VEXCL_VEXCL_RESIZE_HPP_INCLUDED + +#include + +#include +#include +#include + +namespace boost { +namespace numeric { +namespace odeint { + + + +/* + * specializations for vex::vector< T > + */ +template< typename T > +struct is_resizeable< vex::vector< T > > : boost::true_type { }; + +template< typename T > +struct resize_impl< vex::vector< T > , vex::vector< T > > +{ + static void resize( vex::vector< T > &x1 , const vex::vector< T > &x2 ) + { + x1.resize( x2.queue_list() , x2.size() ); + } +}; + +template< typename T > +struct same_size_impl< vex::vector< T > , vex::vector< T > > +{ + static bool same_size( const vex::vector< T > &x1 , const vex::vector< T > &x2 ) + { + return x1.size() == x2.size(); + } +}; + + + + + +/* + * specializations for vex::multivector< T > + */ +template< typename T , uint N > +struct is_resizeable< vex::multivector< T , N > > : boost::true_type { }; + +template< typename T , uint N > +struct resize_impl< vex::multivector< T , N > , vex::multivector< T , N > > +{ + static void resize( vex::multivector< T , N > &x1 , const vex::multivector< T , N > &x2 ) + { + x1.resize( x2.queue_list() , x2.size() ); + } +}; + +template< typename T , uint N > +struct same_size_impl< vex::multivector< T , N > , vex::multivector< T , N > > +{ + static bool same_size( const vex::multivector< T , N > &x1 , const vex::multivector< T , N > &x2 ) + { + return x1.size() == x2.size(); + } +}; + + +} // namespace odeint +} // namespace numeric +} // namespace boost + + + +#endif // BOOST_NUMERIC_ODEINT_EXTERNAL_VEXCL_VEXCL_RESIZE_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/external/viennacl/viennacl_operations.hpp b/include/boost/numeric/odeint/external/viennacl/viennacl_operations.hpp new file mode 100644 index 00000000..d621b35e --- /dev/null +++ b/include/boost/numeric/odeint/external/viennacl/viennacl_operations.hpp @@ -0,0 +1,245 @@ +/* + [auto_generated] + boost/numeric/odeint/external/viennacl_operations.hpp + + [begin_description] + ViennaCL operations. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_EXTERNAL_VIENNACL_VIENNACL_OPERATIONS_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_EXTERNAL_VIENNACL_VIENNACL_OPERATIONS_HPP_INCLUDED + +#include +#include + +namespace boost { +namespace numeric { +namespace odeint { + + + +struct viennacl_operations +{ + + template< class Fac1 = double , class Fac2 = Fac1 > + struct scale_sum2 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + + scale_sum2( Fac1 alpha1 , Fac2 alpha2 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) + { } + + template< class T1 , class T2 , class T3 > + void operator()( viennacl::vector &v1 , + const viennacl::vector &v2 , + const viennacl::vector &v3 + ) const + { + using namespace viennacl; + + static generator::symbolic_vector <0, T1> sym_v1; + static generator::symbolic_vector <1, T2> sym_v2; + static generator::symbolic_vector <2, T3> sym_v3; + static generator::cpu_symbolic_scalar<3, Fac1> sym_a1; + static generator::cpu_symbolic_scalar<4, Fac2> sym_a2; + + static generator::custom_operation op( + sym_v1 = sym_a1 * sym_v2 + + sym_a2 * sym_v3 + ); + + ocl::enqueue( op(v1, + const_cast< viennacl::vector& >(v2), + const_cast< viennacl::vector& >(v3), + const_cast< Fac1& >(m_alpha1), + const_cast< Fac2& >(m_alpha2) + ) ); + } + + typedef void result_type; + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 > + struct scale_sum3 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + + scale_sum3( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) + { } + + template< class T1 , class T2 , class T3 , class T4 > + void operator()( viennacl::vector &v1 , + const viennacl::vector &v2 , + const viennacl::vector &v3 , + const viennacl::vector &v4 + ) const + { + using namespace viennacl; + + static generator::symbolic_vector <0, T1> sym_v1; + static generator::symbolic_vector <1, T2> sym_v2; + static generator::symbolic_vector <2, T3> sym_v3; + static generator::symbolic_vector <3, T4> sym_v4; + static generator::cpu_symbolic_scalar<4, Fac1> sym_a1; + static generator::cpu_symbolic_scalar<5, Fac2> sym_a2; + static generator::cpu_symbolic_scalar<6, Fac3> sym_a3; + + static generator::custom_operation op( + sym_v1 = sym_a1 * sym_v2 + + sym_a2 * sym_v3 + + sym_a3 * sym_v4 + ); + + ocl::enqueue( op(v1, + const_cast< viennacl::vector& >(v2), + const_cast< viennacl::vector& >(v3), + const_cast< viennacl::vector& >(v4), + const_cast< Fac1& >(m_alpha1), + const_cast< Fac2& >(m_alpha2), + const_cast< Fac3& >(m_alpha3) + ) ); + } + + typedef void result_type; + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 > + struct scale_sum4 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + + scale_sum4( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 > + void operator()( viennacl::vector &v1 , + const viennacl::vector &v2 , + const viennacl::vector &v3 , + const viennacl::vector &v4 , + const viennacl::vector &v5 + ) const + { + using namespace viennacl; + + static generator::symbolic_vector <0, T1> sym_v1; + static generator::symbolic_vector <1, T2> sym_v2; + static generator::symbolic_vector <2, T3> sym_v3; + static generator::symbolic_vector <3, T4> sym_v4; + static generator::symbolic_vector <4, T5> sym_v5; + static generator::cpu_symbolic_scalar<5, Fac1> sym_a1; + static generator::cpu_symbolic_scalar<6, Fac2> sym_a2; + static generator::cpu_symbolic_scalar<7, Fac3> sym_a3; + static generator::cpu_symbolic_scalar<8, Fac4> sym_a4; + + static generator::custom_operation op( + sym_v1 = sym_a1 * sym_v2 + + sym_a2 * sym_v3 + + sym_a3 * sym_v4 + + sym_a4 * sym_v5 + ); + + ocl::enqueue( op(v1, + const_cast< viennacl::vector& >(v2), + const_cast< viennacl::vector& >(v3), + const_cast< viennacl::vector& >(v4), + const_cast< viennacl::vector& >(v5), + const_cast< Fac1& >(m_alpha1), + const_cast< Fac2& >(m_alpha2), + const_cast< Fac3& >(m_alpha3), + const_cast< Fac4& >(m_alpha4) + ) ); + } + + typedef void result_type; + }; + + + template< class Fac1 = double , class Fac2 = Fac1 , class Fac3 = Fac2 , class Fac4 = Fac3 , class Fac5 = Fac4 > + struct scale_sum5 + { + const Fac1 m_alpha1; + const Fac2 m_alpha2; + const Fac3 m_alpha3; + const Fac4 m_alpha4; + const Fac5 m_alpha5; + + scale_sum5( Fac1 alpha1 , Fac2 alpha2 , Fac3 alpha3 , Fac4 alpha4 , Fac5 alpha5 ) + : m_alpha1( alpha1 ) , m_alpha2( alpha2 ) , m_alpha3( alpha3 ) , m_alpha4( alpha4 ) , m_alpha5( alpha5 ) { } + + template< class T1 , class T2 , class T3 , class T4 , class T5 , class T6 > + void operator()( viennacl::vector &v1 , + const viennacl::vector &v2 , + const viennacl::vector &v3 , + const viennacl::vector &v4 , + const viennacl::vector &v5 , + const viennacl::vector &v6 + ) const + { + using namespace viennacl; + + static generator::symbolic_vector < 0, T1> sym_v1; + static generator::symbolic_vector < 1, T2> sym_v2; + static generator::symbolic_vector < 2, T3> sym_v3; + static generator::symbolic_vector < 3, T4> sym_v4; + static generator::symbolic_vector < 4, T5> sym_v5; + static generator::symbolic_vector < 5, T6> sym_v6; + static generator::cpu_symbolic_scalar< 6, Fac1> sym_a1; + static generator::cpu_symbolic_scalar< 7, Fac2> sym_a2; + static generator::cpu_symbolic_scalar< 8, Fac3> sym_a3; + static generator::cpu_symbolic_scalar< 9, Fac4> sym_a4; + static generator::cpu_symbolic_scalar<10, Fac5> sym_a5; + + static generator::custom_operation op( + sym_v1 = sym_a1 * sym_v2 + + sym_a2 * sym_v3 + + sym_a3 * sym_v4 + + sym_a4 * sym_v5 + + sym_a5 * sym_v6 + ); + + ocl::enqueue( op(v1, + const_cast< viennacl::vector& >(v2), + const_cast< viennacl::vector& >(v3), + const_cast< viennacl::vector& >(v4), + const_cast< viennacl::vector& >(v5), + const_cast< viennacl::vector& >(v6), + const_cast< Fac1& >(m_alpha1), + const_cast< Fac2& >(m_alpha2), + const_cast< Fac3& >(m_alpha3), + const_cast< Fac4& >(m_alpha4), + const_cast< Fac5& >(m_alpha5) + ) ); + } + + typedef void result_type; + }; + + +}; + + +} // odeint +} // numeric +} // boost + + +#endif // BOOST_NUMERIC_ODEINT_EXTERNAL_VIENNACL_VIENNACL_OPERATIONS_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/external/viennacl/viennacl_resize.hpp b/include/boost/numeric/odeint/external/viennacl/viennacl_resize.hpp new file mode 100644 index 00000000..677cfce8 --- /dev/null +++ b/include/boost/numeric/odeint/external/viennacl/viennacl_resize.hpp @@ -0,0 +1,65 @@ +/* + [auto_generated] + boost/numeric/odeint/external/viennacl/viennacl_resize.hpp + + [begin_description] + Enable resizing for viennacl vector. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_EXTERNAL_VIENNACL_VIENNACL_RESIZE_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_EXTERNAL_VIENNACL_VIENNACL_RESIZE_HPP_INCLUDED + +#include + +#include +#include +#include + +namespace boost { +namespace numeric { +namespace odeint { + + + +/* + * specializations for viennacl::vector< T > + */ +template< typename T > +struct is_resizeable< viennacl::vector< T > > : boost::true_type { }; + +template< typename T > +struct resize_impl< viennacl::vector< T > , viennacl::vector< T > > +{ + static void resize( viennacl::vector< T > &x1 , const viennacl::vector< T > &x2 ) + { + x1.resize( x2.size() , false ); + } +}; + +template< typename T > +struct same_size_impl< viennacl::vector< T > , viennacl::vector< T > > +{ + static bool same_size( const viennacl::vector< T > &x1 , const viennacl::vector< T > &x2 ) + { + return x1.size() == x2.size(); + } +}; + + + +} // namespace odeint +} // namespace numeric +} // namespace boost + + + +#endif // BOOST_NUMERIC_ODEINT_EXTERNAL_VIENNACL_VIENNACL_RESIZE_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/integrate/detail/integrate_adaptive.hpp b/include/boost/numeric/odeint/integrate/detail/integrate_adaptive.hpp new file mode 100644 index 00000000..f32fa624 --- /dev/null +++ b/include/boost/numeric/odeint/integrate/detail/integrate_adaptive.hpp @@ -0,0 +1,154 @@ +/* + [auto_generated] + boost/numeric/odeint/integrate/detail/integrate_adaptive.hpp + + [begin_description] + Default Integrate adaptive implementation. + [end_description] + + Copyright 2009-2011 Karsten Ahnert + Copyright 2009-2011 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + + +#ifndef BOOST_NUMERIC_ODEINT_INTEGRATE_DETAIL_INTEGRATE_ADAPTIVE_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_INTEGRATE_DETAIL_INTEGRATE_ADAPTIVE_HPP_INCLUDED + +#include + +#include +#include +#include +#include +#include +#include + +#include + + +#include + +namespace boost { +namespace numeric { +namespace odeint { +namespace detail { + +// forward declaration +template< class Stepper , class System , class State , class Time , class Observer> +Time integrate_n_steps( + Stepper stepper , System system , State &start_state , + Time start_time , Time dt , size_t num_of_steps , + Observer observer , stepper_tag ); + +/* + * integrate_adaptive for simple stepper is basically an integrate_const + some last step + */ +template< class Stepper , class System , class State , class Time , class Observer > +size_t integrate_adaptive( + Stepper stepper , System system , State &start_state , + Time start_time , Time end_time , Time dt , + Observer observer , stepper_tag +) +{ + size_t steps = static_cast< size_t >( (end_time-start_time)/dt ); + Time end = detail::integrate_n_steps( stepper , system , start_state , start_time , + dt , steps , observer , stepper_tag() ); + if( less_with_sign( end , end_time , dt ) ) + { //make a last step to end exactly at end_time + stepper.do_step( system , start_state , end , end_time - end ); + steps++; + typename odeint::unwrap_reference< Observer >::type &obs = observer; + obs( start_state , end_time ); + } + return steps; +} + + +/* + * classical integrate adpative + */ +template< class Stepper , class System , class State , class Time , class Observer > +size_t integrate_adaptive( + Stepper stepper , System system , State &start_state , + Time &start_time , Time end_time , Time &dt , + Observer observer , controlled_stepper_tag +) +{ + typename odeint::unwrap_reference< Observer >::type &obs = observer; + + const size_t max_attempts = 1000; + const char *error_string = "Integrate adaptive : Maximal number of iterations reached. A step size could not be found."; + size_t count = 0; + while( less_with_sign( start_time , end_time , dt ) ) + { + obs( start_state , start_time ); + if( less_with_sign( end_time , start_time + dt , dt ) ) + { + dt = end_time - start_time; + } + + size_t trials = 0; + controlled_step_result res = success; + do + { + res = stepper.try_step( system , start_state , start_time , dt ); + ++trials; + } + while( ( res == fail ) && ( trials < max_attempts ) ); + if( trials == max_attempts ) throw std::overflow_error( error_string ); + + ++count; + } + obs( start_state , start_time ); + return count; +} + + +/* + * integrate adaptive for dense output steppers + * + * step size control is used if the stepper supports it + */ +template< class Stepper , class System , class State , class Time , class Observer > +size_t integrate_adaptive( + Stepper stepper , System system , State &start_state , + Time start_time , Time end_time , Time dt , + Observer observer , dense_output_stepper_tag ) +{ + typename odeint::unwrap_reference< Observer >::type &obs = observer; + + size_t count = 0; + stepper.initialize( start_state , start_time , dt ); + + while( less_with_sign( stepper.current_time() , end_time , stepper.current_time_step() ) ) + { + while( less_eq_with_sign( stepper.current_time() + stepper.current_time_step() , + end_time , + stepper.current_time_step() ) ) + { //make sure we don't go beyond the end_time + obs( stepper.current_state() , stepper.current_time() ); + stepper.do_step( system ); + ++count; + } + stepper.initialize( stepper.current_state() , stepper.current_time() , end_time - stepper.current_time() ); + } + obs( stepper.current_state() , stepper.current_time() ); + // overwrite start_state with the final point + boost::numeric::odeint::copy( stepper.current_state() , start_state ); + return count; +} + + + + +} // namespace detail +} // namespace odeint +} // namespace numeric +} // namespace boost + + +#endif // BOOST_NUMERIC_ODEINT_INTEGRATE_DETAIL_INTEGRATE_ADAPTIVE_HPP_INCLUDED diff --git a/include/boost/numeric/odeint/integrate/detail/integrate_const.hpp b/include/boost/numeric/odeint/integrate/detail/integrate_const.hpp new file mode 100644 index 00000000..2eb7ae0a --- /dev/null +++ b/include/boost/numeric/odeint/integrate/detail/integrate_const.hpp @@ -0,0 +1,159 @@ +/* + [auto_generated] + boost/numeric/odeint/integrate/detail/integrate_const.hpp + + [begin_description] + integrate const implementation + [end_description] + + Copyright 2009-2012 Karsten Ahnert + Copyright 2009-2012 Mario Mulansky + + Distributed under the Boost Software License, Version 1.0. + (See accompanying file LICENSE_1_0.txt or + copy at http://www.boost.org/LICENSE_1_0.txt) + */ + +#ifndef BOOST_NUMERIC_ODEINT_INTEGRATE_DETAIL_INTEGRATE_CONST_HPP_INCLUDED +#define BOOST_NUMERIC_ODEINT_INTEGRATE_DETAIL_INTEGRATE_CONST_HPP_INCLUDED + +#include +#include +#include +#include + +#include + +namespace boost { +namespace numeric { +namespace odeint { +namespace detail { + +// forward declaration +template< class Stepper , class System , class State , class Time , class Observer > +size_t integrate_adaptive( + Stepper stepper , System system , State &start_state , + Time &start_time , Time end_time , Time &dt , + Observer observer , controlled_stepper_tag +); + + +template< class Stepper , class System , class State , class Time , class Observer > +size_t integrate_const( + Stepper stepper , System system , State &start_state , + Time start_time , Time end_time , Time dt , + Observer observer , stepper_tag +) +{ + typename odeint::unwrap_reference< Observer >::type &obs = observer; + + Time time = start_time; + int step = 0; + + while( less_eq_with_sign( time+dt , end_time , dt ) ) + { + obs( start_state , time ); + stepper.do_step( system , start_state , time , dt ); + // direct computation of the time avoids error propagation happening when using time += dt + // we need clumsy type analysis to get boost units working here + ++step; + time = start_time + static_cast< typename unit_value_type