deploy: 0f0f9b6

.gitmodules

@@ -0,0 +1,9 @@
+[submodule "modules/MCcubed"]
+	path = lisa/modules/MCcubed
+	url = https://github.com/mdhimes/mc3
+[submodule "modules/PolyChordLite"]
+	path = lisa/modules/PolyChordLite
+	url = https://github.com/PolyChord/PolyChordLite
+[submodule "lisa/modules/PyDREAM"]
+	path = lisa/modules/PyDREAM
+	url = https://github.com/mdhimes/PyDREAM

LICENSE

@@ -0,0 +1,38 @@
+The Large-selection Interface for Sampling Algorithms (LISA), a Python 
+interface for Markov chain and nested sampling algorithms.
+
+This project was completed with the support of the NASA Fellowship Activity, 
+grant 80NSSC20K0682, held by Principal Investigator Joseph Harrington in 
+support of Michael Himes, the principal developer of LISA.  
+
+Copyright (C) 2020 - 2021 University of Central Florida.
+All rights reserved.
+
+This is a test version only, and may not be redistributed to any third
+party.  Please refer such requests to us.  This program is distributed
+in the hope that it will be useful, but WITHOUT ANY WARRANTY; without
+even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
+PURPOSE.
+
+LISA is under a reproducible-research license.  Until LISA's first 
+publication, we do not permit others to redistribute the code in either 
+original or modified form, nor to publish work based in whole or in part on 
+the output of this code.  By downloading, running, or modifying this code, 
+you agree to these conditions.  We do encourage sharing any modifications 
+with us and discussing them openly.
+For more details, see 
+https://planets.ucf.edu/resources/reproducible-research/software-license/
+
+We welcome your feedback, but do not guarantee support.  Please send
+feedback or inquiries to:
+Michael Himes <[email protected]>  
+Joseph Harrington <[email protected]>   
+
+or alternatively,
+Joseph Harrington and Michael Himes
+UCF PSB 441
+4111 Libra Drive
+Orlando, FL 32816-2385
+USA
+
+Thank you for using LISA!

MANIFEST.in

@@ -0,0 +1,2 @@
+recursive-include doc/ *
+recursive-include lisa/modules/ *

Makefile

@@ -0,0 +1,13 @@
+all: mc3 polychord pydream
+
+mc3:
+	@cd ./lisa/modules/MCcubed && make
+	@echo "Finished compiling MCcubed.\n"
+
+polychord:
+	@cd ./lisa/modules/PolyChordLite && python setup.py --no-mpi install
+	@echo "Finished installing pypolychord.\n"
+
+pydream:
+	@cd ./lisa/modules/PyDREAM && python setup.py install
+	@echo "Finished installing PyDREAM.\n"

README

@@ -0,0 +1,175 @@
+                                LISA
+             Large-selection Interface for Sampling Algorithms
+===============================================================================
+
+
+Author :       Michael D. Himes    University of Central Florida
+Contact:       [email protected]
+
+Advisor:       Joseph Harrington   University of Central Florida
+
+Contributors:  
+
+
+Acknowledgements
+----------------
+This research was supported by the NASA Fellowship Activity under NASA Grant 
+80NSSC20K0682.  We gratefully thank Nvidia Corporation for the Titan Xp GPU 
+that was used throughout development of the software.
+
+
+Summary
+=======
+LISA provides an interface for a variety of sampling algorithms.  Currently, 
+the following sampling methods are available:
+    DE-MC (ter Braak 2006), via a fork (https://github.com/mdhimes/mc3/tree/mpi)
+                            of MC3 (https://github.com/pcubillos/mc3)
+    DE-MC with snooker updates (ter Braak & Vrugt 2008), via MC3 fork
+    DNest4 (Brewer & Foreman-Mackey 2018)
+    DREAM with snooker updates and multi-try (Laloy & Vrugt 2012), via PyDREAM 
+                                           (https://github.com/LoLab-VU/PyDREAM)
+    dynesty (Speagle 2019; https://github.com/joshspeagle/dynesty)
+    MULTINEST (Feroz et al. 2009), via PyMultiNest (Buchner et al. 2014; 
+                                 https://github.com/JohannesBuchner/PyMultiNest)
+    PolyChord (Handley et al. 2015a, 2015b; 
+               https://github.com/PolyChord/PolyChordLite)
+    UltraNest (Buchner 2014, 2019; https://github.com/JohannesBuchner/UltraNest)
+
+LISA comes with complete documentation as well as a user manual to assist 
+in its usage.  Users can find the latest LISA User Manual at 
+https://exosports.github.io/LISA/doc/LISA_User_Manual.html.
+
+LISA is an open-source project that welcomes improvements from the community 
+to be submitted via pull requests on Github.  To be accepted, such improvements 
+must be generally consistent with the existing coding style, and all changes 
+must be updated in associated documentation.
+
+LISA is released under the Reproducible Research Software License.  Users are 
+free to use the software for personal reasons.  Users publishing results from 
+LISA or modified versions of it in a peer-reviewed journal are required to 
+publicly release all necessary code/data to reproduce the published work.  
+Modified versions of LISA are required to also be released open source under 
+the same Reproducible Research License.  For more details, see the text of the 
+license.
+
+
+Files & Directories
+===================
+LISA contains various files and directories, described here.
+
+doc/            - Contains documentation for LISA.  The User Manual contains 
+                  the information in the README with more detail, as well as a 
+                  walkthrough for setup and running an example.
+environment.yml - Contains the required packages for LISA.
+example/        - Contains examples of executing LISA.
+LICENSE         - Contains the text of the sfotware's license.
+lisa/           - Contains the LISA package.
+  __init__.py   - Contains the main functions to use LISA.
+  modules/      - Contains submodules for some sampling algorithms.
+    MCcubed     - MC3 package.
+    PolyChordLite - polychord's public release on Github.
+  _version.py   - Tracks the code's version.
+  wrappers/     - Contains wrappers for the sampling algorithms.
+    helper.py   - Contains the parent class for samplers.
+Makefile        - Handles building MC3.
+README          - This file!
+setup.py        - Used to install the package.
+
+
+Note that all .py files have complete documentation; consult a specific file 
+for more details.
+
+
+Installation
+============
+To build the supplied conda environment, enter 
+    conda env create -f environment.yml
+and activate it:
+    conda activate lisa
+
+On some systems, this approach may fail.  For a more robust approach that 
+requires additional steps, enter
+    conda create -n lisa python=3.7.2
+    conda activate lisa
+    conda env update --file environment.yml
+This will build a base Python 3.7.2 environment, activate it, and then update 
+it with the packages necessary to run LISA.
+
+Mac users may need to install additional tools:
+    xcode-select --install
+This installs make, gcc, git, and other utilities needed.
+
+Now, install LISA:
+    python setup.py install
+This will compile required submodules and build an importable package.
+
+To check that everything installed properly, start up a Python session and try 
+    import lisa
+If it succeeds without warnings about missing MultiNest files, 
+you are now ready to use LISA!
+
+
+Executing LISA
+===============
+LISA is designed to be imported into existing projects.  LISA provides two 
+functions for usage: setup instantiates a sampler, while run performs setup, 
+runs the inference, and produces posterior plots.  For example,
+    import lisa
+    sampler = lisa.setup('demc')
+will set up a DEMC sampler object.  Users would then need to specify required 
+parameters, such as the data, uncertainties, phase space, etc.  For a list of 
+the required parameters,
+    print(sampler.reqpar)
+These parameters are attributes of the sampler object, and must be set to 
+execute the inference.  For example, if my data were y = x from 0 through 9, 
+    sampler.data = np.arange(10)
+Optional parameters are also available.  View those via
+    print(sampler.optpar)
+To get more information about some parameter P, there are two options:
+    sampler.help('P')
+    print(sampler.helpinfo['P'])
+
+Once all required parameters are specified, execute the inference via
+    sampler.run()
+If the sampler object is not properly set up, LISA will print to terminal 
+the issues that must be corrected, provided that the `verb` parameter is at 
+least 1.  After fixing them, call the run() method as before.
+
+To make plots of the posterior, enter
+    sampler.make_plots()
+
+Alternatively, if users already know what parameters to include, 
+    sampler = lisa.run(algorithm, keyword1=parameter1, keyword2=parameter2, ...)
+If a required parameter is missing, users can follow the above instructions 
+for adding the required parameters, run it, and produce plots.
+
+For more examples of how to incorporate LISA into your project, see the 
+example/ directory.
+
+
+Versions
+========
+LISA was developed on a Unix/Linux machine using the following 
+versions of packages:
+ - Python 3.7.2
+ - Numpy 1.16.2
+ - Matplotlib 3.0.2
+ - mpi4py 3.0.3
+ - Scipy 1.5.3
+ - h5py 2.9.0
+ - MULTINEST 3.10
+ - PyMultiNest 2.10
+ - UltraNest 2.2.2
+ - dynesty 1.0.1
+ - dnest4 0.2.4
+ - PyDREAM 2.0.0
+
+
+Be kind
+=======
+Please note that this software has not been officially released yet; see the 
+license for some restrictions on its usage prior to release.  Upon release, 
+we will add the relevant citation here, with a Bibtex entry.
+
+Thanks!
+

doc/LISA_User_Manual.html

@@ -0,0 +1,10 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
+<html lang="en" style="width:100%; height:100%;">
+<head>
+  <meta http-equiv="content-type" content="text/html; charset=utf-8">
+  <title>LISA User Manual</title>
+</head>
+  <body style="width:100%; height:100%; margin:0;">
+    <iframe src="https://docs.google.com/gview?url=https://github.com/exosports/LISA/raw/gh-pages/doc/LISA_user_manual/LISA_user_manual.pdf&embedded=true" style="width:100%; height:100%;" frameborder="0"></iframe>
+  </body>
+</html>

doc/LISA_user_manual/LISA_user_manual.aux

@@ -0,0 +1,52 @@
+\relax 
+\providecommand\hyper@newdestlabel[2]{}
+\providecommand\HyperFirstAtBeginDocument{\AtBeginDocument}
+\HyperFirstAtBeginDocument{\ifx\hyper@anchor\@undefined
+\global\let\oldnewlabel\newlabel
+\gdef\newlabel#1#2{\newlabelxx{#1}#2}
+\gdef\newlabelxx#1#2#3#4#5#6{\oldnewlabel{#1}{{#2}{#3}}}
+\AtEndDocument{\ifx\hyper@anchor\@undefined
+\let\newlabel\oldnewlabel
+\fi}
+\fi}
+\global\let\hyper@last\relax 
+\gdef\HyperFirstAtBeginDocument#1{#1}
+\providecommand\HyField@AuxAddToFields[1]{}
+\providecommand\HyField@AuxAddToCoFields[2]{}
+\bibstyle{apj_hyperref}
+\@writefile{toc}{\contentsline {section}{\numberline {1}Team Members}{2}{section.1}\protected@file@percent }
+\newlabel{sec:team}{{1}{2}{Team Members}{section.1}{}}
+\@writefile{toc}{\contentsline {section}{\numberline {2}Introduction}{2}{section.2}\protected@file@percent }
+\newlabel{sec:theory}{{2}{2}{Introduction}{section.2}{}}
+\@writefile{toc}{\contentsline {section}{\numberline {3}Installation}{2}{section.3}\protected@file@percent }
+\newlabel{sec:installation}{{3}{2}{Installation}{section.3}{}}
+\@writefile{toc}{\contentsline {subsection}{\numberline {3.1}System Requirements}{2}{subsection.3.1}\protected@file@percent }
+\newlabel{sec:requirements}{{3.1}{2}{System Requirements}{subsection.3.1}{}}
+\@writefile{toc}{\contentsline {subsection}{\numberline {3.2}Install and Compile}{3}{subsection.3.2}\protected@file@percent }
+\newlabel{sec:install}{{3.2}{3}{Install and Compile}{subsection.3.2}{}}
+\@writefile{toc}{\contentsline {section}{\numberline {4}Example}{4}{section.4}\protected@file@percent }
+\newlabel{sec:example}{{4}{4}{Example}{section.4}{}}
+\@writefile{toc}{\contentsline {section}{\numberline {5}Program Inputs}{4}{section.5}\protected@file@percent }
+\newlabel{sec:inputs}{{5}{4}{Program Inputs}{section.5}{}}
+\@writefile{toc}{\contentsline {subsection}{\numberline {5.1}Sampling Algorithm}{5}{subsection.5.1}\protected@file@percent }
+\@writefile{toc}{\contentsline {subsubsection}{\numberline {5.1.1}demc \& snooker}{5}{subsubsection.5.1.1}\protected@file@percent }
+\newlabel{sec:mcmc-inputs}{{5.1.1}{5}{demc \& snooker}{subsubsection.5.1.1}{}}
+\@writefile{toc}{\contentsline {subsubsection}{\numberline {5.1.2}dream}{6}{subsubsection.5.1.2}\protected@file@percent }
+\@writefile{toc}{\contentsline {subsubsection}{\numberline {5.1.3}dnest4}{7}{subsubsection.5.1.3}\protected@file@percent }
+\@writefile{toc}{\contentsline {subsubsection}{\numberline {5.1.4}dynesty, multinest, polychord, \& ultranest}{8}{subsubsection.5.1.4}\protected@file@percent }
+\newlabel{sec:ns-inputs}{{5.1.4}{8}{dynesty, multinest, polychord, \& ultranest}{subsubsection.5.1.4}{}}
+\@writefile{toc}{\contentsline {subsection}{\numberline {5.2}Parameter Dictionary}{9}{subsection.5.2}\protected@file@percent }
+\newlabel{sec:param-desc}{{5.2}{9}{Parameter Dictionary}{subsection.5.2}{}}
+\@writefile{toc}{\contentsline {section}{\numberline {6}Program Outputs}{12}{section.6}\protected@file@percent }
+\newlabel{sec:outputs}{{6}{12}{Program Outputs}{section.6}{}}
+\@writefile{toc}{\contentsline {subsection}{\numberline {6.1}Returns}{12}{subsection.6.1}\protected@file@percent }
+\@writefile{toc}{\contentsline {subsection}{\numberline {6.2}Output Files}{12}{subsection.6.2}\protected@file@percent }
+\@writefile{toc}{\contentsline {subsection}{\numberline {6.3}demc \& snooker}{12}{subsection.6.3}\protected@file@percent }
+\@writefile{toc}{\contentsline {subsection}{\numberline {6.4}dnest4}{13}{subsection.6.4}\protected@file@percent }
+\@writefile{toc}{\contentsline {subsection}{\numberline {6.5}multinest}{13}{subsection.6.5}\protected@file@percent }
+\@writefile{toc}{\contentsline {subsection}{\numberline {6.6}polychord}{13}{subsection.6.6}\protected@file@percent }
+\@writefile{toc}{\contentsline {subsection}{\numberline {6.7}ultranest}{13}{subsection.6.7}\protected@file@percent }
+\@writefile{toc}{\contentsline {section}{\numberline {7}FAQ}{13}{section.7}\protected@file@percent }
+\@writefile{toc}{\contentsline {section}{\numberline {8}Be Kind}{14}{section.8}\protected@file@percent }
+\newlabel{sec:bekind}{{8}{14}{Be Kind}{section.8}{}}
+\gdef \@abspage@last{15}