ParaMonte C++ 2.0.0

Table of Contents

• What is ParaMonte?
• ParaMonte Project Repository
• ParaMonte Prebuilt Releases
• ParaMonte Documentation Website
• ParaMonte C++ Documentation Website
• ParaMonte C++ Library Modules
• ParaMonte C++ Naming Conventions
  • ParaMonte C++ Naming Conventions: Variables
  • ParaMonte C++ Naming Conventions: Procedures
• ParaMonte C++ Abbreviation Guidelines
• ParaMonte C++ Developer Guidelines and Warnings
• ParaMonte C++ Documentation Guidelines
• ParaMonte C++ Language Examples
• ParaMonte C++ Language Benchmarks
• ParaMonte C++ Documentation Troubleshooting

This is the ParaMonte C++ documentation website for the C users and developers.

⛓

What is ParaMonte?

ParaMonte is a library of serial and parallel Monte Carlo and Machine Learning routines scientific inference, e.g., for sampling mathematical density functions of arbitrary-dimensions, with the design goal of unifying

• the automation of simulations and inference,
• the user-friendliness of the library and routines,
• the accessibility from multiple programming environments,
• the high-performance at runtime, and,
• the scalability across many parallel processors.

⛓

ParaMonte Project Repository

The ParaMonte library is open-source and is permanently located and maintained on GitHub at:

 https://github.com/cdslaborg/paramonte

⛓

ParaMonte Prebuilt Releases

The pre-built releases of the ParaMonte library for select configurations and compilers are available on GitHub Release page at:

 https://github.com/cdslaborg/paramonte/releases

For instructions to build the ParaMonte library from source files, visit the ParaMonte library main documentation website linked below.

⛓

ParaMonte Documentation Website

For information about the ParaMonte library in general and in other supported programming languages, visit:

 https://www.cdslab.org/paramonte

⛓

ParaMonte C++ Documentation Website

The documentation for the latest version of the ParaMonte C++ library is always available on this page.

⛓

ParaMonte C++ Library Modules

The ParaMonte C++ library currently contains,

1. A set of routines that can be used for optimization and sampling of mathematical density functions with arbitrary precision.

The ParaMonte C++ library is currently under active development to extend the library functionalities to other tasks supported by the ParaMonte Fortran library.
For a full list of all available functionalities and modules, see the modules listing of this documentation website.

Module	Functionality
pm_sampling	This module contains procedures and generic interfaces for the ParaMonte C++ library sampler routines.

The following modules are currently under development for future addition to the ParaMonte C++ library.

Module	Functionality
pm_optimization	This module contains procedures, generic interfaces, and types for numerical optimizations of mathematical functions.
pm_quadPack	This module contains procedures for non-adaptive and adaptive global numerical quadrature.
pm_quadRomb	This module contains procedures for numerical integrations.

⛓

ParaMonte C++ Naming Conventions

• The CamelCase naming style is enforced throughout the ParaMonte C++ library.

⛓⛓

ParaMonte C++ Naming Conventions: Variables

By convention in this library,

• All variables and procedure names except compile-time constants begin with an lowercase letter.
• All constants and parameters should generally be typed in uppercase.
• The names of variables that always represent vectors of values may suffixed with Vec or Vector.
• The names of variables that always represent matrices of values can be suffixed with Mat or Matrix.
• A significant attempt has been made to end all Boolean variables with a passive verb.
  This is to ensure that the full variable name virtually forms a proposition.
  In other words, a Boolean variable name should be an English-language statement that evaluates to either true or false.
  For example, parallelismMpiFinalizeEnabled is one such proposition.
  
  • Occasionally, names that begin with the verb is can also be used to label _Bool objects.
    
  • But as a general rule, names that begin with a verb should be reserved for procedures.
    

⛓⛓

ParaMonte C++ Naming Conventions: Procedures

• Procedure names should be descriptive of the action performed by the procedure. For example,
  • getCov means generate (a) covariance matrix.
  • setMatCopy means copy the matrix into the specified buffer.
• Procedure names should virtually always begin with a lowercase verb.
• Exceptions to the above and below rules are allowed when,
  • the procedure name is exceptionally famous, or
  • it is very inconvenient to prefix the procedure name with a verb.
• The names of functions with return values should preferably begin with get.
  The reasoning is simple: Functions in mathematics generate and obtain a new object instead of changing (resetting) the state of an existing object.
  For example, the function getMatSym(mat) result(matsym) generates a symmetric version of the input matrix and returns it as the function result.
  Exceptions to this naming convention are allowed, for example, when the get prefix is inconvenient or when the function returns a _Bool result.
  
• Functions that return objects of type _Bool should be preferably prefixed with is or be named such that the name begins with a verb and reads as a proposition, evaluating to either .true. or .false..
• The keyword get should be avoided as a prefix for void function names since void functions do not generate and get a new object as their results, rather they (re)set the state of existing objects passed to them.
  
• A more appropriate prefix for void functions is set, i.e., setReplaced().

⛓

ParaMonte C++ Abbreviation Guidelines

The following list of abbreviations is in alphabetical order to enable faster search:

• The abbreviation avg stands for average (rarely used).
• The abbreviation cdf stands for Cumulative Distribution Function in the context of statistics. Example: getNormCDF().
• The abbreviation cho stands for Cholesky factorization. Example: setChoLow().
• The abbreviation chol stands for Cholesky factorization. Example: setMatChol().
• The abbreviation cor stands for correlation. Example: getCor().
• The abbreviation cov stands for covariance. Example: getCov().
• The abbreviation cum stands for cumulative. Example: getCumSum().
• The abbreviation coef stands for coefficient. Example: corcoef_type().
• The abbreviation def stands for default in variable names (mostly as a prefix def_ or suffix _def).
• The abbreviation def stands for definite (mostly in procedure names dealing with positive-definite matrices)
• The abbreviation den stands for density, mostly in the context of statistical procedures and objects. Example: getLogProbDen().
• The abbreviation det stands for determinant, mostly in the context of Matrix and linear algebra. Example: getMatDet().
• The abbreviation dia stands for diagonal, mostly in the context of matrix algebra, matrix packing, or Cholesky factorization. Example: dia_type().
• The abbreviation diag stands for diagonal, mostly as dummy argument in matrix algebra procedures.
• The abbreviation desc stands for description, mostly as a dummy argument in tests.
• The abbreviation diff stands for difference. Example: setDisSortedExpDiff().
• The abbreviation dist stands for distance or distribution depending on the context. Example: DistMulti_type.
• The abbreviation eff stands for effective. Example: effSamSize.
• The abbreviation exp stands for exponential or exponentiated. Example: setDisSortedExpDiff().
• The abbreviation herm stands for hermitian in matrix algebra.
• The abbreviation ICE stands for Internal Compiler Error. It typically appears in the bug descriptions tagged via Doxygen command \bug.
• The abbreviation inv stands for inverse. Example: getMatInv().
• The abbreviation ks stands for Kolmogorov-Smirnov test. Example: getProbKS().
• The abbreviation lin stands for linear. Example: getLinSpace().
• The abbreviation low stands for lower triangle of a matrix or lower limits. Example: setChoLow().
• The abbreviation mahal stands for Mahalanobis distance. Example: getMahalSq().
• The abbreviation mat stands for matrix. Example: getMatInv().
• The abbreviation multi stands for multivariate mostly used in the context of statistical distributions. Example: getMultiNormRand().
• The abbreviation msn stands for Multivariate Skew-Normal mostly used in the context of the statistical MultiVariate Skew-Normal distribution.
• The abbreviation mvn stands for MultiVariate Normal mostly used in the context of the statistical MultiVariate Normal distribution.
• The abbreviation mvu stands for MultiVariate Uniform mostly used in the context of the statistical MultiVariate (ellipsoidal) Uniform distribution.
• The abbreviation norm stands for normal in the context of statistical distributions or normalization factor. Example: DistMultiNorm_type.
• The abbreviation normed stands for normalized mostly in the context of statistical samples. Example: NormedSample.
• The abbreviation pdf stands for Probability Density Function in the context of statistics. Example: getNormLogPDF().
• The abbreviation pos stands for positive. Example: getInvPosDefMat().
• The abbreviation prob stands for probability, mostly in the context of statistical applications. Example: getLogProb().
• The abbreviation proc stands for procedure, particularly, when it appears as the suffix _proc in abstract interface definitions.
• The abbreviation quan stands for quantile, mostly in the context of statistics. Example: getParetoLogQuan().
• The abbreviation rand stands for random, mostly in the context of statistics. Example: getUnifRand().
• The abbreviation ref stands for reference, mostly in the context of testings to represent the reference values for comparison. Example: mean_ref.
• The abbreviation sam stands for sample, mostly in the context of statistics. Example: effSamSize.
• The abbreviation sq stands for squared. Example: getMahalSq().
• The abbreviation stat stands for statistics. Example: StatDRAM_type.
• The abbreviation std stands for standard deviation. Example: StdVec.
• The abbreviation sym stands for symmetric.
• The abbreviation symm stands for symmetric.
• The abbreviation udf stands for Unnormalized Density Function in the context of statistics. Example: getEggBoxLogUDF().
• The abbreviation uni stands for univariate, mostly used in the context of statistical distributions. Example: DistUni_type.
• The abbreviation unif stands for uniform, mostly in the context of the uniform statistical distribution. Example: getUnifRand().
• The abbreviation upp stands for upper triangle of a matrix or upper limits. Example: setChoUpp().
• The abbreviation vec stands for vector. Example: stdVec.

⛓

ParaMonte C++ Developer Guidelines and Warnings

The ParaMonte C++ library development and guidelines are summarized in CONTRIBUTING.md.

⛓

ParaMonte C++ Documentation Guidelines

• Doxygen custom command orderings.
  • The Doxygen tag \brief must always be the first line of the documentation of modules, types, and procedures.
    Example: pm_sampling.
    
  • The Doxygen tag \details, if it exists, must always immediately follow the Doxygen tag \brief.
    Example: pm_sampling.
    
  • The Doxygen tag \param, if any number of it exists, must always immediately follow the Doxygen tag \brief (or \details if it exists).
    Example: runParaDRAMD().
    
  • The Doxygen tag \return, must be exclusively used to indicate the return value of functions.
    If it exists, it must appear immediately after the set of \param tags. Example: runParaDRAMD().
    
  • If a generic interface is being documented, the ParaMonte custom command \interface must appear immediately after the Doxygen \return, \param, \details, or \brief tags in the specified order, if any exists.
    
  • The Doxygen tag \warning, if any number of it exists, must immediately follow the Doxygen tag \return if it exists, otherwise \param if it exists, otherwise \details if it exists, otherwise \brief.
    The \warning tag must be used to highlight situations that require special attention of the user, otherwise, there is a danger for the code section being documented to not behave normally as one may expect.
    
  • The Doxygen tag \attention has the same functionality and usage as \warning.
    Therefore, \warning should be preferred wherever \attention is needed.
    Exceptions are allowed and if they occur, the same documentation conventions as those of \warning also apply to the tag \attention.
    
  • The Doxygen tag \remark, if any number of it exists, must immediately follow the Doxygen tag \warning if it exists, otherwise the Doxygen tag \return if it exists, otherwise \param if it exists, otherwise \details if it exists, otherwise \brief.
    The tag \remark should be reserved for explaining behavior that is directly related to the code segment being documented, but its knowledge is not so critical as warrant the use of a \warning tag.
    
  • The Doxygen tag \note, if it exists, must appear after all \warning and \attention and \remark tags and immediately before the ParaMonte custom command tag \see if it exists, otherwise immediately before \example for examples (if it exists).
    
  • The Doxygen tag \see, if it exists, must appear after all \warning and \remark and \note tags.
    If more than one item for the \see command exists, each must be written on a separate line and each line must end with the HTML line-break tag <br>. Example: See below.
    
  • If any example exists, it must appear immediately after the \see tag, otherwise after \note, \remark, \warning, \param, \details, or \brief if any exists.
    ParaMonte examples are initiated by the custom command \example devised in the config.txt file of ParaMonte Doxygen documentation.
    If the example exists in an external file, then it must be included via the Doxygen \include command, followed immediately by the ParaMonte custom Doxygen command \compile which inserts the generic example compile commands for the example, followed optionally but immediately by the output file of the example inserted in the documentation via the \include command, followed immediately by the inclusion of any other visualization or postprocessing scripts and output.
    In all steps, it is imperative to not leave any empty lines between the successive commands of the example section, designated by the \example, otherwise, each empty line will start a new paragraph in the documentation.
    Example: See below.
    
  • The Doxygen \test tag, if any exists, must appear immediately after the example section designated by the \example tag.
    
  • The Doxygen \todo tag, if any exists, must appear immediately after the \test tag or any other tag immediately preceding it.
    
  • The Doxygen \bug tag, if any exists, must appear immediately after the \todo tag or any other tag immediately preceding it.
    
  • The closing command of each documentation section must be the ParaMonte custom command \finmain separated from the tags before and after by an empty line.
    
  • The Doxygen \xrefitem authors "Author" "Authors" tag is the last command to appear in any documentation section, and it must preferably have the format exemplified in the example below.
    
    
    

• ParaMonte Doxygen custom commands.
  To simplify documentation and avoid retyping certain frequently used keywords and sentences, a number of Doxygen aliases are predfined in the ParaMonte Doxygen config.txt file. These include (but are not limited to):

  • \warnpure Inserts a \warning about procedures that are impure when the library is built the preprocessor macro CHECK_ENABLED=1.
  • \elemental Inserts a \remark tag indicating that the procedure of interest is elemental.
  • \pure Inserts a \remark tag indicating that the procedure of interest is pure.
  • \interface Starts a Possible calling interfaces paragraph where different calling interfaces of a procedure can be listed.
  • \benchmark Starts a new Benchmark paragraph which is hyper-linked to the generic anchor #benchmark at the same location on the same page.
  • \benchmark{xxx} Starts a new Benchmark paragraph which is hyper-linked to the specific anchor #benchmark-xxx at the same location on the same page.
  • \benchmark{xxx, This is the benchmark title} Starts a new Benchmark paragraph which is hyper-linked to the specific anchor #benchmark-xxx at the same location on the same page with the title This is the benchmark title.
  • \example Starts a new Example usage paragraph which is hyper-linked to the generic anchor #example at the same location on the same page.
  • \example{xxx} Starts a new Example usage paragraph which is hyper-linked to the specific anchor #example-xxx at the same location on the same page.
  • \compile Inserts the set of example compile commands.
  • \output Inserts a title line for the output section of an example paragraph.
  • \postproc Inserts a title line for the postprocessing section of an example paragraph.
  • \abbr Inserts a \remark tag about the naming abbreviations used in the library.
  • \naming Inserts a \remark tag about the naming conventions used in the library.
  • \license Inserts a \remark tag about the generic licensing of the library.
  • \finmain Inserts the set of final generic remarks that should appear at the end of each documentation section.
  • \RK Inserts a hyper-link reference RK to the default real kind used in the library.
  • \RK32 Inserts a hyper-link reference RK32 to the real32 real kind used in the library.
  • \RK64 Inserts a hyper-link reference RK64 to the real64 real kind used in the library.
  • \RK128 Inserts a hyper-link reference RK128 to the real128 real kind used in the library.
  • \CK Inserts a hyper-link reference CK to the default complex kind used in the library.
  • \CK32 Inserts a hyper-link reference CK32 to the real32 complex kind used in the library.
  • \CK64 Inserts a hyper-link reference CK64 to the real64 complex kind used in the library.
  • \CK128 Inserts a hyper-link reference CK128 to the real128 complex kind used in the library.
  • \IK8 Inserts a hyper-link reference IK8 to the int8 integer kind used in the library.
  • \IK16 Inserts a hyper-link reference IK16 to the int16 integer kind used in the library.
  • \IK32 Inserts a hyper-link reference IK32 to the int32 integer kind used in the library.
  • \IK64 Inserts a hyper-link reference IK64 to the int64 integer kind used in the library.
  • \SKALL Inserts a hyper-link reference to all major character kinds like: any supported by the processor (e.g., SK, SKA, SKD , or SKU).
  • \IKALL Inserts a hyper-link reference to all major integer kinds like: any supported by the processor (e.g., IK, IK8, IK16, IK32, or IK64).
  • \LKALL Inserts a hyper-link reference to all major _Bool kinds like: any supported by the processor (e.g., LK).
  • \CKALL Inserts a hyper-link reference to all major complex kinds like: any supported by the processor (e.g., CK, CK32, CK64, or CK128).
  • \RKALL Inserts a hyper-link reference to all major real kinds like: any supported by the processor (e.g., RK, RK32, RK64, or RK128).
    
    

  For an up-to-date list of all available aliases, check the value of the Doxygen ALIASES option in config.txt in the ParaMonte C++ documentation repository.

• Escaping the Doxygen reserved characters.
  Doxygen has a set of reserved characters whose usage in the documentation must be handled properly.
  

  • Most importantly, the backslash character \ begins a Doxygen command.
    To print a backslash character to the output one should escape it via \\.
    
  • Also, the use of the percentage symbol % requires special care in some instances.
    This is particularly important when defining Windows environment variables that should typically be enclosed with percentage character.
    
    

  For more information, see the relevant page on Doxygen documentation website.
  

• Avoid the insertion of an empty documentation line between any two lines of a single Doxygen paragraph.
  This is crucial when the whole paragraph is indented by a vertical line as is done by Doxygen for \warning, \remark, \note and other similar tags.
  
  Example usage ⛓

  The following is an example documentation for a procedure:

  ///
  ///
  /// \ingroup pm_sampling
  ///
  /// \defgroup runParaDRAM runParaDRAM
  ///
  /// \brief
  /// Generate and return a non-zero value (`1`) if the procedure fails to fully accomplish the task of generating
  /// a Monte Carlo sample of the specified input mathematical objective function, otherwise, return `0`.
  ///
  /// \details
  /// This interface group is the entry point to all **C-style interfaces** to the ParaDRAM samplers of mathematical density functions.<br>
  /// Although the procedures of this generic interface return a single scalar of type `int32_t`, the procedures generate
  /// massive amounts of information about each simulation which are stored in appropriate external hard drive files.<br>
  ///
  /// \param[in]  getLogFunc  :   The input user-specified procedure pointer to the natural logarithm of the target density function.<br>
  ///                             On input, the function must take an input vector `state` of size `ndim` of type floating-point of kind \C_RKALL
  ///                             representing a state (point) from within the domain of the user-specified target density function whose function value must be returned.<br>
  ///                             On output, the user-specified procedure `getLogFunc()` must return the function value corresponding to the input `state[ndim]`.<br>
  ///                             The following illustrate the generic interface of input function pointer `getLogFunc(state, ndim)`,
  ///                             \code{.F90}
  ///                                 REAL getLogFunc(REAL[] state, int32_t ndim);
  ///                             \endcode
  ///                             where `REAL` can be a floating-point type of kind \C_RKALL for the corresponding varying-precision sampler interfaces:<br>
  ///                             <ol>
  ///                                 <li>    [runParaDRAMF](@ref runParaDRAMF),
  ///                                 <li>    [runParaDRAMD](@ref runParaDRAMD),
  ///                                 <li>    [runParaDRAML](@ref runParaDRAML).
  ///                             </ol>
  /// \param[in]  ndim        :   The input scalar constant of type `int32_t` representing the number of dimensions of the domain of the objective function.
  /// \param[in]  input       :   The input scalar pointer of type `char` representing the null-terminated C string
  ///                             that contains either,
  ///                             <ol>
  ///                                 <li>    the path to an external input file containing the namelist group of ParaDRAM sampler specifications
  ///                                         as outlined in the corresponding page of [ParaMonte library generic documentation website](\pmdoc_usage_sampling/paradram/specifications/).<br>
  ///                                 <li>    the namelist group of ParaDRAM sampler specifications as the can appear in an external input specification file.<br>
  ///                             </ol>
  ///                             While all input simulation specifications are optional, it is highly recommended to pay
  ///                             attention to the default settings of the domain boundaries and sampler starting point.<br>
  ///                             (**optional**. It is considered as missing if set to `NULL`.)
  ///
  /// \return
  /// `stat`                  :   The output scalar of type `int32_t` that is `0` **if and only if**
  ///                             the sampler succeeds in sampling the specified density function.<br>
  ///
  /// \interface{runParaDRAM}
  /// \code{.cpp}
  ///
  ///     include "pm_sampling.hpp"
  ///
  ///     stat = runParaDRAMF(getLogFunc, ndim, input)
  ///     stat = runParaDRAMD(getLogFunc, ndim, input)
  ///     stat = runParaDRAML(getLogFunc, ndim, input)
  ///
  /// \endcode
  ///
  /// \warning
  /// Beware that the definition of extended precision real type `long double` is compiler and platform dependent
  /// making the use of `long double` with precompiled ParaMonte libraries problematic and non-functional.<br>
  ///
  /// \warning
  /// The condition `0 < ndim` must hold for the corresponding input arguments.<br>
  /// \vericon
  ///
  /// \example{mvn}
  /// \include{lineno} example/pm_sampling/mvn/main.cpp
  /// \inputfile{mvn, input.nml, example specifications namelist input file}
  /// \include{lineno} example/pm_sampling/mvn/input.nml
  /// \cmakefile{mvn}
  /// \include{lineno} example/pm_sampling/mvn/CMakeLists.txt
  /// \cmakerun{mvn}
  /// \postproc{mvn}
  /// \include{lineno} example/pm_sampling/mvn/main.py
  /// \vis{mvn}
  /// \image html example/pm_sampling/mvn/mvn.traceplot.png width=700
  /// \image html example/pm_sampling/mvn/mvn.scatterplot.png width=700
  /// \image html example/pm_sampling/mvn/mvn.adaptationMeasure.png width=700
  ///
  /// \example{himmelblau}
  /// \include{lineno} example/pm_sampling/himmelblau/main.cpp
  /// \inputfile{himmelblau, input.nml, example specifications namelist input file}
  /// \include{lineno} example/pm_sampling/himmelblau/input.nml
  /// \cmakefile{himmelblau}
  /// \include{lineno} example/pm_sampling/himmelblau/CMakeLists.txt
  /// \cmakerun{himmelblau}
  /// \postproc{himmelblau}
  /// \include{lineno} example/pm_sampling/himmelblau/main.py
  /// \vis{himmelblau}
  /// \image html example/pm_sampling/himmelblau/himmelblau.traceplot.png width=700
  /// \image html example/pm_sampling/himmelblau/himmelblau.scatterplot.png width=700
  /// \image html example/pm_sampling/himmelblau/himmelblau.adaptationMeasure.png width=700
  ///
  /// \test
  /// [test_pm_sampling](@ref test_pm_sampling)
  ///
  /// \bug
  /// \status \unresolved
  /// \source \ifx{2024.0.0 20231017}
  /// \desc
  /// \ifx This interface yields a segmentation fault error for all `real` types supported when linked with the ParaMonte library built with \ifx.
  /// \remedy
  /// For now, only \ifort will be used.<br>
  ///
  /// \bug
  /// \status \unresolved
  /// \source \ifort{2021.11.0 20231010}
  /// \desc
  /// The `runParaDRAML` interface for `long double` yields a segmentation fault error.
  /// \remedy
  /// None as of today.<br>
  ///
  /// \todo
  /// \pvhigh
  /// The current tests for `long double` interface fail with \ifx and \icx compilers.<br>
  /// Apparently, there is a mismatch between `long double` and `c_long_double` storage.<br>
  /// This issue does not exist with GNU compilers, although the GNU definition of `long double`
  /// appears to yield incorrect values in some calculations, e.g., in `isFailedGeomCyclicFit()` of the ParaMonte library.<br>
  ///
  /// \todo
  /// \pmed
  /// This C-style interface should be ideally wrapped in a C++ template.
  ///
  /// \finminc{runParaDRAM}
  ///
  /// \author
  /// \AmirShahmoradi, May 16 2016, 9:03 AM, Oden Institute for Computational Engineering and Sciences (ICES), UT Austin
  ///
  ///     

  
  The above example documentation snippet will generate an HTML similar to this documentation.
  Note the lack of an empty line among the commands that immediately follow \example.
  This is essential to keep the entire example section in the same paragraph.

  
  

⛓

ParaMonte C++ Language Examples

The ParaMonte C++ library ships with tens of thousands of example usage that are available in the example/cpp folder in the root directory of the project repository.
These examples are also available and discussed in the documentations of individual modules and procedures of this this documentation website.

⛓

ParaMonte C++ Language Benchmarks

The ParaMonte C++ library currently does not ship with any benchmarks.
If you would like to see a relevant benchmark currently not included, discuss it here or raise an issue here for consideration or volunteer to implement it!

⛓

ParaMonte C++ Documentation Troubleshooting

1. Side navigation pane disappears in some documentation pages.
   This issue most likely originates from the interference of browser addons with the documentation.
   This issue is mostly observed on Firefox browsers.
   If it occurs, open the page in browser private mode or use other (e.g., chrome-based) browsers.