Author Archives: Alice Allen

June 2016 additions to the ASCL

Fifteen codes were added to the ASCL in June 2016:

COMB: Compact embedded object simulations
Companion-Finder: Planets and binary companions in time series spectra
Cygrid: Cython-powered convolution-based gridding module for Python
FDIPS: Finite Difference Iterative Potential-field Solver
FLASK: Full-sky Lognormal Astro-fields Simulation Kit

HIBAYES: Global 21-cm Bayesian Monte-Carlo Model Fitting
KMDWARFPARAM: Parameters estimator for K and M dwarf stars
Lmfit: Non-Linear Least-Square Minimization and Curve-Fitting for Python
PAL: Positional Astronomy Library
Pulse Portraiture: Pulsar timing

PyMultiNest: Python interface for MultiNest
s2: Object oriented wrapper for functions on the sphere
SimpLens: Interactive gravitational lensing simulator
SWOC: Spectral Wavelength Optimization Code
uvmcmcfit: Parametric models to interferometric data fitter

Engineering Academic Software, Schloss Dagstuhl Day 4

The morning of Day 4 of the Engineering Academic Software workshop opened with the mighty James Howison talking about the outputs expected from our work this week; these include a report of the meeting, the manifesto mentioned in my previous blog post, a draft document offering guidance for tenure committees on evaluating software contributions, a draft workplan for writing a proposal to establish an award for software contributions, a table of contents for a research software engineering handbook, and a sustainability debt use case, these last four from breakout session work.

The two talks on this morning might well be billed the Battle of Cool Places to Work. First up was Cecilia Aragon from the University of Washington on eScience Institute Initiatives. This work grew out of the realization that people were drowning in data, leading to the Moore/Sloan Data Science Environment, a $37.8M initiative at UCB, NYU, and UW. Tweet: ""Big data is two orders of magnitudes larger than you are used to dealing with now" - @craragon"The eScience Institute has a multi-pronged approach set up around science theme areas with bridges to data science methodologies; this sets up a cycle wherein research needs generate new methodologies, which enable more science. Two new roles were established, Data Science Fellows and Data Scientists. They also set up education and training, including workshops and bootcamps for data science, such as Software Carpentry and Astro Hack Week and a seminar series. They offer a new MS in data science that is interdisciplinary, involving six departments, and innovative, with a social science component that includes a human-centered viewpoints and ethics. This MS program is designed for working professionals, provides a rigorous technical program in statistics and computer science, and has evening courses and allows full or part time attendance. Tweet: "UW's MSc in Data Science includes training in "software hygiene" and pragmatic parts of Soft Eng"They have set up guidelines for reproducibility and offer help to people to improve this aspect of their work; eScience institute data scientists and others participate in a “drop-in” office hours program. They foster working relations with their working space and culture; people sit side-by-side to work on a problem. They see sharing a physical space as essential for data science and growing research software collaborations.

Aragon discussed the integration of ethnography (a qualitative field-based technique originally from anthropology that enables study of underlying patterns and themes) and evaluation into a wide range of the data science environment. Ethnography research tries to answer questions such as Who does data science?, How are they networked?, and What forms of social interaction do they use? Ethnographers at UW work with members of the community to interpret observations and to provide feedback on what works and what doesn’t. She reports they have had a lot of  success with “applied ethnography”.

She also discussed their data science incubator program, which was the precursor to the Data Science for Social Good program. They looked for high-impact data-intensive science projects that would benefit from quarter-long sprints of expertise, and had projects outlive the incubator, getting advances in both the science and the software and generating publishable "Human centered data science" initiative by @craragon impressive in its interdisciplinary diversity. Great stuff to learn fromresults for both. One project was to try to solve problem of homelessness in Seattle. It involved bringing data about homelessness into more manageable form and analyzing it to see what worked, conducting analysis to identify predictors of permanent housing, and looking for successful outcomes. Another project, Open Sidewalks, created sidewalk maps for low-mobility citizens to show the curb cuts are.

Aragon discussed the marketing that they do; they talk to a lot of people, and this has helped with engagement. They actively look for ways to build relationships and collaboration.
factors contributing to collaborative dynamicsAs with all the talks, participants in the room were very engaged, asked questions, and discussed various points. Aragon was asked about career paths and the backgrounds of those in the MS data science program; she said there were forty students in the first cohort and that it was a very heterogenous class, with people from many disciplines. The ethnography work has been discussed in a paper by Tanweer, Fiore, and Aragon. I hope the slides for this talk are released! There was a lot in it that I have not captured here. Screen Shot 2016-06-27 at 6.32.45 PMWhen someone gives a talk about their organisation and you want to quit your job, leave the country and go join them.
The “organization envy,” as one person in the room put it, continued with Rob van Nieuwpoort‘s talk on the Netherlands eScience Center. The Netherlands eScience center receives 5.4M€/year in permanent funding.
Screen Shot 2016-06-27 at 6.34.54 PMTheir responsibilities is demand-driven for all sciences; competition for funding and services is within disciplines, not between disciplines. They fund path-finding projects; this program is similar to UW’s incubator projects program. They also receive in-kind funding for eScience research engineers; these are broadly oriented scientists.

The eScience Center recognized early on that they wanted to give research engineers career paths; they offer three different paths: managerial, technical, and research. Asked by Katz whether research engineers have to have academic appointments, van Nieuwpoort stated that some researcher engineers do have academic appointments, but not all do. Vinju asked about educational opportunities, to which the answer was that yes, there are educational opportunities, including workshop and other training; this topic came up again a bit later.

They foster a collaborative rather than a competitive environment, with their engineers fully integrated into the scientific work, and domain scientists recognized for their contributions to software development. Research software engineers are coauthors on science papers to which they have contributed, and when software methods published, domain scientists are recognized with coauthorship.

Returning to education, van Nieuwpoort stated that research software engineers like learn, so the eScience Center keeps them challenged and learning with courses, hackathons, and sprints, and by switching disciplines and technologies.

Through eStep, an eScience technology platform, the eScience Center serves the 99% of Rob action shotscientists in the Netherlands that aren’t at the eScience Center. eSTEP goals are to prevent fragmentation and duplication; to promote exchange and reuse of best practices; to represent NLeSC’s expertise and knowledge, and to improve the science state of art with fundamental science research. There are key expertises used in many projects and projects use number of methodologies. NLeSC generalizes software for use in eSTEP; they find or develop state of the art and “best of breed” technologies and software matching their expertise areas that can be made generic and overarching and integrate that technology into eSTEP.

Sustainability is important to them, as is preventing duplication and fragmentation; they seek to build software that is worth sustaining and enforce software engineering best practicesTweet: OH sustainability only matters for things that are worth sustaining :-). They use Software Carpentry and Data Carpentry to educate their partners, maintain a knowledge base, and (be still, my heart!) offer a searchable software repository. And more! Slides (PDF)

Tweet: lots of cool projects and ideas at esciencecenter.nl :)

Of course there was discussion (and funding envy, too); Kevin Crowston pointed out that permanent funding, as Rob’s eScience center has, solves a lot of issues. After a short break, we worked together (all of us in the same Google document, which was a little wild) on the Manifesto, sometimes tweeting out comments and questions, up until lunch.

Tweet: Has anyone got any stories about researchers who shared their code and got publicly mocked because of low quality?Tweet: Trying to "look far into future" as @dagstuhl manifestos are meant to do. What will research software be in 10, 20 years?Tweet: "Just became aware of #CodeMeta “a Rosetta stone of software metadata” http://codemeta.github.io"After lunch, we went into breakout sessions; these included sessions on future research questions, the research software engineering handbook, and the Force11 software citation suggestions. After working in these breakouts, we reconvened to share and discuss the progress that was made, breaking only for dinner at 6:00 PM because we had to.

A very busy, exciting, interesting, informative, and productive day!

Engineering Academic Software, Schloss Dagstuhl Day 3

The day started with a quick discussion about the afternoon; it is traditional for Schloss Dagstuhl seminars that Wednesday afternoons involve a social activity. It was determined on Tuesday that the activity was to be a hike some distance away from Dagstuhl with dinner after in another town, but several changes to these plans had to be ironed out and announced. After a few minutes spent on that, the morning session got underway and was furiously fast! This was an Open Mic, with participants having signed up while here to give short talks (ten minutes or less).

First up was Daniel Garijo on Software Metadata: Describing “dark software” in Geosciences. By “dark software,” he means that which is often hidden from view. He described the current state of the art for software description in geosciences and demonstrated Ontosoft.org, a semantic registry for scientific software, which currently includes information from several geosciences resources. As Ontosoft is not domain-specific, it has the capacity to expand into other fields as well. This is a very attractive and capable site. It uses a distributed approach to software registries and depends on crowdsourcing for metadata maintenance. The resource organizes software metadata using the OntoSoft ontology along six dimensions: identify software, understand and assess software, execute software, get support for the software, do research with the software, and update the software. Slideshare

Jurgen Vinju was next with Organising a research team around the research software around the research team in software engineering: Motivation, experiences, lessons. He talked about his experiences as the group leader of the SWAT (Software Analysis and Transformation) team at Centrum Wiskunde and Informatica (CWI), the national research institute for math and computer science in the Netherlands. tweet showing image of Jurgen presenting his Open Mic talkSWAT is all about the source code and supporting programmers to create more efficient, maintainable software. They work to understand and control software complexity to enable more and better tools. He made the point that research teams “prioritise for academic output which is not software.” He showed UseTheSource, a resource developed by CWI with contributions from other institutes and housing open-source projects related to software language engineering and metaprogramming. This allows more efficient programming by automating tasks that are cumbersome or hard, and allows synergies between software engineers, researchers, and industry. PDF
Tweet: A research team s not a software team. We have fewer resources. We need more investment in efficiency.

Dan Katz gave an overview of work done by the Force11 Software Citation Working Group; his presentation was titled Software Citation: Principles, Discussion, and Metadata. He provided Tweet: "Check out force 11 for progress in software citation"rationales for citing software, information on the WSSSPE and Force11 groups involved in developing software citation principles and the process used to develop them, and then the six principles, which focus on the importance of software, the need to credit and attribute the contributions software makes to research and to be able to uniquely identify software in a persistent and specific way, and that citations should enable access to the software and associated information about the software that informs its use. Katz brought up many of the discussions the WSSSPE and Force11 working groups had and their determinations, such as what software to cite, how to uniquely identify software, that peer-review of software is important but not required for citation, and how publishers can help.
Tweet: "It's more important to cite the software directly rather than a software paper"Each of the Open Mic sessions generated immediate discussion during the sessions and while the next presenter was setting up, and this session was no exception. When Katz pointed out that a common practice is to publish and cite papers about software (“software papers”), but that the Importance principle of the Force11 Working Group calls for the citation of the software itself, “on the same basis as any other research product”, this was countered with a comment that people should cite software papers if the software authors have requested that method of citation. Katz stated that could be done in addition to citing to the software, as one of his slides stated. The presentation concluded with information on the next steps for the Force11 Software Citation Working Group — to finalize the principles, and publish and circulate them for endorsement — and the likelihood of a Software Citation Implementation Group being formed to work with institutions, researchers, publishers, and other interested parties to put the principles into practice. PDF

Tweet: ""Software advisors are elected. It's a role people create when ask you questions" Katie Kuksenok"The fourth Open Mic talk was by Katerena Kuksenok on Best Practices (by any other name). This interesting talk looked atTweet: "User resistance: “I don’t want to use version control because I don’t want the world to see my terrible code.”" intersections of the technical, social, and cognitive aspects of software engineering in research, and asked how the available community and skill resources could be leveraged. brought together various elements brought up through the workshop so far, including different roles that had been identified, the need for software engineers to learn from scientists just as we hope researchers learn software engineering practices, Tweet: Mike Croucher "is s/w therapist/coach, helping scientists improve code...carefully; doesn't throw computer science at them!"and overcoming communications barriers. She referred back to a comment Mike Croucher had made in his talk on Monday, agreeing that software engineers should “do CS/SE with people not at them!” PowerPoint

After Kuksenok’s talk, I presented Restoring reproducibility: Making scientist software discoverable. This presentation was a quick overview of the ASCL, its history and a few of the changes to our infrastructure, the lessons we learned from Tweet: astrophysics source code library since 1999looking at what other astro code registries and repositories had done and what we did with those lessons, and some of the impact we have on the community. As with every other session, there was intermittent discussion, questions asked and answered, and conversation on the topic as I headed back to my chair and the next speaker set up. PowerPoint PDF

Robert Haines was up next with A Short* History of Research Software Engineers in the UK (*and probably incomplete). Before there were Research Software Engineers (RSE), there were RSEs going by other names, such as Post Doc and Research Assistant. These were the people in the lab who could code, andTweet" "#dagsRobert Haines reports on the coming to life of the job of “Research Software Engineer”, with jobs, a union, etc." fell “foul of publish or perish” because they were writing code rather than papers. RSEs might also have been hiding as those working in high performance computing or as a research group admin. He is an example of someone who has always done RSE work, though was not called an RSE until fairly recently. It was at a Software Sustainability Institute Collaborations Workshop in 2012 that there was a call to arm to recognize the Screen Shot 2016-06-26 at 12.34.52 PM contributions of those who write code rather than papers and are not purely researchers. They decided they needed a name, to unionize, and a policy campaign. He described the current environment, both the challenges and the positives, and shared that many people want to work in this field. Yes, discussion broke out in this session, too! It was remarkable how engaged everyone at the workshop was, and how often and easily discussion took place. PDF

Ralf presentingDan Katz made a very brief presentation and instigated more discussion on career paths when Robert Haines was finished, then after a brief coffee break, the morning Open Mic session continued with Ralf Lämmel‘s presentation intriguingly called Making a failing project succeed?! about the 101Companies project. He called 101Companies a software chrestomathyfrom chresto, meaning “useful” and mathein, meaning “to learn.” He shared other chrestomathies, such as the Hello World Collection and the Evolution of a Haskell programmer. (One of the previous links will lead you to a song about a popular beverage.) 101Companies is a resource for learning Tweet: "101 is a knowledge resource for technological space travel (between all kinds of online spaces)"more about software, for comparing technologies, for programming education, and can serve as “a playground for student projects.” He discussed some of the challenges the project is having and some of the ways in which it is succeeding. PDF

The last Open Mic talk of the morning was by Ashish Gehani giving a quick overview of his work on software, including software to make data more manageable, particularly the OCCAM: Object Culling and Concretization for Assurance Maximization project.

The last agenda item for the morning was to discuss the manifesto that is one of the required Tweets: "we discussed the #manifesto as genre in http://dx.doi.org/10.1109/ICSE.2015.179 … section III. http://press.princeton.edu/titles/8066.html … is a great #longread"outputs for this workshop. This discussion was led by James Howison, who shared the link for the Google Doc that was to become the manifesto, and which was discussed and created in tandem (and wild abandon) by many in the room duTweet: "I was, uh, one of the authors of the EAS manifesto. The original EAS manifesto. Not the compromised second draft."ring the time remaining before lunch. The manifesto is our public declaration, our own call to action. Our work is only beginning at Schloss Dagstuhl; we must put what we have discussed here into practice. We shared other manifestos (manifesti!), determined authorship as opt-in (by adding our names to the author list), and talked about but did not determine where this might be published. I found the creation of this document interesting and inspiring, very much in line with the philosophy of “be the change you want to see in the world.”
Tweet: "According to James Howison software as communication between people should be studied."
After getting a good start on the manifesto, we broke for a longer than usual lunch period, after which some took a long hike with a lakeside stop for a refreshing beverage, and some did other things. I took a much-needed nap and then noodled around for a bit in the music room, view of the music room looking toward the piano from the far end a lovely large, long room with wonderful acoustics and a recently-tuned grand piano, two guitars, a cello, and a violin available. (I discovered later in the week that the violin case also holds a kazoo.) small ornate doorway decorated with naked cherubs and a shield with 1743 on itScores for solo and ensemble music are stocked in a room at one end of the music room, the (small) door to which is watched over by cherubs. Most of the Schloss is modern in appearance; this is one of the few rooms that reveals the building’s history. I found plenty of music to amuse myself with, including a collection of Bach preludes and fugues from the WTC apparently edited by Bartók and in what to me was a confusing order, and Beethoven sonatas that at one time I knew how to butcher. Others reported having taken shorter walks than the one that was organized, listening to podcasts, trying out the bicycles available for guests, and also napping.

As you have likely surmised by now, the Twitter hashtag for this event was , and the Twitter feed offers more pictures and information about this workshop.

Engineering Academic Software, Schloss Dagstuhl Day 2

Tuesday started with Jeffrey Carver from the University of Alabama presenting What we have learned about using software engineering practices in scientific software. They took a multi-pronged approach to studying scientific software, from conducting surveys and workshop to direct interactions and case studies. From survey work, his team was able to group problems scientists were having with their own software into four main areas: rework, performance, regression (testing), and forgetting bugs. From this, they could see what software engineering practices might help with solving the problems.

Case studies brought numerous lessons to light; they found that the use of higher-level languages was low, performance competes with other goals, and external software use can be seen as risky. Workshops highlighted some of the differences between scientist programmers and software engineers and their domains. Scientist developers often lack formal software engineering expertise but have deep knowledge of their domains and are often the main users of their software. Quality goals are different, too; scientists would rather software not run than return an incorrect result. This project demonstrated that there is a need to eliminate the stigma associated with software engineering and that software engineers need to understand domain constraints and specific problems. PDF

Every presentation sparked lively Q&A and discussion, often throughout the presentation, and this one was no exception. User stories beat data even for scientistsScreen Shot 2016-06-22 at 7.49.08 PM

The next presentation was Engineering yt by Matthew Turk from NCSA at the University of Illinois at Urbana Champaign. He provided context and information on this well-cited community-developed project, discussed how the community was built, and its adoption of a code of conduct. YTEP, yt Enhancement Proposals, provide a method to manage suggestions for improving yt. Communication methods within the community are well thought out. The challenges of creating and managing the community sparked a lot of discussion; large software projects can have many things go wrong. tweet about change
Failure Modes

Discussion among the group made Matt’s presentation run long, making it necessary to break for coffee before Matt’s talk was done and then return to it after the break. The group was very engaged throughout the day; fortunately, the schedule accommodated the frequent discussions in every presention very well.

After Matt’s talk, Caroline Jay (University of Manchester) and Robert Haines (Software Sustainability Institute) presented Software as academic output. They discussed software’s role in research, when it can be a tool that enables research or the actual research itself, and how this is different depending on the discipline and the functionality of the software within the discipline and the role of the person using the software. They made the point that “Software isn’t a separate thing — software could exist without the paper; the paper couldn’t exist without the software.”
Daniel's tweetChristoph's tweetOh, there was much more goodness in this presentation, which was interrupted by lunch, than I have time to report, including The Horror, as it was termed — the steps necessary for someone to replicate the computational work on one of the research projects this presentation covered — and Robert’s work on making this computational work software available in Docker. It also touched on the FAIR principles for computational research and academic software, and like the other presentations, generated lots of discussion, including conversations in the group on ethical considerations. PDFDan Katz's tweetOscar's tweet

The last formal presentation of the day, before the breakout workgroups, was by Claude Kirchner (INRIA) on the Software Heritage Project. He covered the rationale for this project, which includes the inconsiderate or malicious loss of code and the desire to preserve “our technical and scientific knowledge.” The Software Heritage Project has set out to preserve all the software. Yes, you read that correctly: All the software. Fortunately, a version of the slides for this presentation are online so you can see them for yourself! The site is scheduled to go live next week and I look forward to seeing it.

After Claude’s presentation, we went into breakout sessions.
Christoph's tweet re breakout groupsI joined a breakout session on getting a standing award for scientific contributions through software created. The other breakout sessions were on creating a research software engineering handbook and academic software project typology. All groups reported back before the day’s session ended for dinner. Quite an informative, exciting, and productive day!

Engineering Academic Software at Schloss Dagstuhl

I’m at Schloss Dagstuhl – Leibniz Center for Informatics for a week-long workshop on Engineering Academic Software. Some of the questions we are tackling have been discussed elsewhere, which we are taking into consideration as we talk about them here, and new questions were not only part of the seminar’s original description, but are arising throughout the general and break-out sessions. I would say we’re at the end of the first day but it continues on though it is past 10 PM, with a planned open and vibrant discussion on dogmas past and present. First up for discussion tonight was Agile project management; how do you feel about it? Is this a dogma that needs to be shot or embraced?

The hashtag to follow on Twitter is #dagstuhleas for the full-group discussions; the breakout sessions so far have been too intense for tweeting!

April and May 2016 additions to the ASCL

Twenty-eight codes were added to the ASCL in April and May 2016:

2-DUST: Dust radiative transfer code
ASTRiDE: Automated Streak Detection for Astronomical Images
BACCHUS: Brussels Automatic Stellar Parameter
CAMELOT: Cloud Archive for MEtadata, Library and Online Toolkit
CCSNMultivar: Core-Collapse Supernova Gravitational Waves

cluster-lensing: Tools for calculating properties and weak lensing profiles of galaxy clusters
DISCO: 3-D moving-mesh magnetohydrodynamics package
DNest3: Diffusive Nested Sampling
DUO: Spectra of diatomic molecules
FDPS: Framework for Developing Particle Simulators

grtrans: Polarized general relativistic radiative transfer via ray tracing
Halotools: Galaxy-Halo connection models
K2SC: K2 Systematics Correction
LAMBDAR: Lambda Adaptive Multi-Band Deblending Algorithm in R
libpolycomp: Compression/decompression library

magicaxis: Pretty scientific plotting with minor-tick and log minor-tick support
MARZ: Redshifting Program
MUSCLE: MUltiscale Spherical-ColLapse Evolution
OpenMHD: Godunov-type code for ideal/resistive magnetohydrodynamics (MHD)
PDT: Photometric DeTrending Algorithm Using Machine Learning

SAND: Automated VLBI imaging and analyzing pipeline
Shadowfax: Moving mesh hydrodynamical integration code
Surprise Calculator: Estimating relative entropy and Surprise between samples
The Tractor: Probabilistic astronomical source detection and measurement
TMBIDL: Single dish radio astronomy data reduction package

TRIPPy: Python-based Trailed Source Photometry
TTVFaster: First order eccentricity transit timing variations (TTVs)
zeldovich-PLT: Zel’dovich approximation initial conditions generator

Engineering Academic Software

I’ll be heading to Schloss Dahstuhl in June for a Perspectives Workshop on Engineering Academic Software. Questions the workshop will seek to address include:

  • How is academic software different from other software? What are its most pressing dimensions of quality?
  • Is the software we use and produce in an academic context sustainable? How can we ensure that the software continues to evolve and offer value after serving its initial purpose?
  • How can we adapt software engineering methods for the unique academic context without losing quality?
  • How can we balance domain knowledge and expertise with software engineering knowledge and expertise in an academic research team?
  • Do quality aspects of academic software apply to open data as well? How can well-engineered academic software together with open data make science more reproducible?

I look forward to tackling these and other questions with the other participants, and thank Carole Goble, James Howison, Claude Kirchner, and Oscar M. Nierstrasz for organizing the workshop.

March 2016 additions to the ASCL

Eighteen codes were added to the ASCL in March, 2016:

Asfgrid: Asteroseismic parameters for a star
CORBITS: Efficient Geometric Probabilities of Multi-Transiting Exoplanetary Systems
Dedalus: Flexible framework for spectrally solving differential equations
DiskJockey: Protoplanetary disk modeling for dynamical mass derivation
ellc: Light curve model for eclipsing binary stars and transiting exoplanets

EQUIB: Atomic level populations and line emissivities calculator
ExoPriors: Accounting for observational bias of transiting exoplanets
FAST-PT: Convolution integrals in cosmological perturbation theory calculator
fibmeasure: Python/Cython module to find the center of back-illuminated optical fibers in metrology images
gPhoton: Time-tagged GALEX photon events analysis tools

HIIexplorer: Detect and extract integrated spectra of HII regions
PyGSM: Python interface to the Global Sky Model
PolRadTran: Polarized Radiative Transfer Model Distribution
ROBAST: ROOT-based ray-tracing library for cosmic-ray telescopes
SILSS: SPHERE/IRDIS Long-Slit Spectroscopy pipeline

SMARTIES: Spheroids Modelled Accurately with a Robust T-matrix Implementation for Electromagnetic Scattering
tpipe: Searching radio interferometry data for fast, dispersed transients
VIP: Vortex Image Processing pipeline for high-contrast direct imaging of exoplanets

February 2016 additions to the ASCL

Twenty-one codes were added to the ASCL in February, 2016:

Automark: Automatic marking of marked Poisson process in astronomical high-dimensional datasets
Celestial: Common astronomical conversion routines and functions
CHIP: Caltech High-res IRS Pipeline
CLOC: Cluster Luminosity Order-Statistic Code
COLAcode: COmoving Lagrangian Acceleration code

DELightcurveSimulation: Light curve simulation code
DUSTYWAVE: Linear waves in gas and dust
FilTER: Filament Trait-Evalutated Reconstruction
GANDALF: Graphical Astrophysics code for N-body Dynamics And Lagrangian Fluids
IRSFRINGE: Interactive tool for fringe removal from Spitzer IRS spectra

k2photometry: Read, reduce and detrend K2 photometry
LensTools: Weak Lensing computing tools
LIRA: LInear Regression in Astronomy
LRGS: Linear Regression by Gibbs Sampling
mbb_emcee: Modified Blackbody MCMC

NuCraft: Oscillation probabilities for atmospheric neutrinos calculator
POPPY: Physical Optics Propagation in PYthon
pyraf-dbsp: Reduction pipeline for the Palomar Double Beam Spectrograph
TailZ: Redshift distributions estimator of photometric samples of galaxies
The Cannon: Data-driven method for determining stellar parameters and abundances from stellar spectra

ZAP: Zurich Atmosphere Purge