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To reduce and analyze astronomical images, astronomers can rely on a wide range of libraries providing low-level implementations of legacy algorithms. However, combining these routines into robust and functional pipelines requires a major…
The absorption and emission of light by exoplanet atmospheres encode details of atmospheric composition, temperature, and dynamics. Fundamentally, simulating these processes requires detailed knowledge of the opacity of gases within an…
We introduce cosmocnc, a Python package for computing the number count likelihood of galaxy cluster catalogues in a fast, flexible and accurate way. cosmocnc offers three types of likelihoods: an unbinned, a binned, and an extreme value…
iSpec is an integrated spectroscopic software framework suitable for the creation of spectral libraries such as the Benchmark Stars library and the determination of atmospheric parameters (i.e. effective temperature, surface gravity,…
Classification is a fundamental task in machine learning and data mining. Existing classification methods are designed to classify unknown instances within a set of previously known training classes. Such a classification takes the form of…
HiClass is an open-source Python library for local hierarchical classification entirely compatible with scikit-learn. It contains implementations of the most common design patterns for hierarchical machine learning models found in the…
SWIFTGalaxy is an open-source astrophysics module that extends SWIFTSimIO to analyses of particles belonging to individual galaxies simulated with SWIFT. It inherits from and extends the functionality of SWIFTSimIO's SWIFTDataset class. It…
Pyxel is a novel python tool for end-to-end detection chain simulation i.e. from detector optical effects to readout electronics effects. It is an easy-to-use framework to host and pipeline any detector effect model. It is suited for…
Many synoptic surveys are observing large parts of the sky multiple times. The resulting lightcurves provide a wonderful window to the dynamic nature of the universe. However, there are many significant challenges in analyzing these light…
Gravitational microlensing is a robust tool to detect and directly measure the abundance and mass of any kind of compact objects, either in our galaxy or in the extragalatic domain. On basis to generic, broadly applicable arguments, it is…
Instance Space Analysis is a methodology to evaluate algorithm performance across diverse problem fields. Through visualisation and exploratory data analysis techniques, Instance Space Analysis offers objective, data-driven insights into…
We describe a novel, interdisciplinary, computational methods course that uses Python and associated numerical and visualization libraries to enable students to implement simulations for a number of different course modules. Problems in…
pyspeckit is a toolkit and library for spectroscopic analysis in Python. We describe the pyspeckit package and highlight some of its capabilities, such as interactively fitting a model to data, akin to the historically widely-used splot…
A major trend in academia and data science is the rapid adoption of Bayesian statistics for data analysis and modeling, leading to the development of probabilistic programming languages (PPL). A PPL provides a framework that allows users to…
The analysis of experimental results with Python often requires writing many code scripts which all need access to the same set of functions. In a common field of research, this set will be nearly the same for many users. The qspec Python…
Gravitational microlensing is a key probe of the nature of dark matter and its distribution on the smallest scales. For many practical purposes, confronting theory to observation requires to model the probability that a light source is…
Probabilistic cross-identification has been successfully applied to a number of problems in astronomy from matching simple point sources to associating stars with unknown proper motions and even radio observations with realistic morphology.…
Powerbox is a pure-Python package for creating and measuring structured fields with homogeneous and isotropic power spectra.
We present Artificial Stellar Populations (ArtPop), an open-source Python package for synthesizing stellar populations and generating artificial images of fully populated stellar systems. The code is designed to be intuitive to use and as…
Probabilistic programming (PP) allows flexible specification of Bayesian statistical models in code. PyMC3 is a new, open-source PP framework with an intutive and readable, yet powerful, syntax that is close to the natural syntax…