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PypeIt is a Python package for semi-automated reduction of astronomical, spectroscopic data. Its algorithms build on decades-long development of previous data reduction pipelines by the developers (Bernstein, Burles, & Prochaska, 2015;…

Instrumentation and Methods for Astrophysics · Physics 2020-05-20 J. Xavier Prochaska , Joseph F. Hennawi , Kyle B. Westfall , Ryan J. Cooke , Feige Wang , Tiffany Hsyu , Frederick B. Davies , Emanuele Paolo Farina

TextDescriptives is a Python package for calculating a large variety of metrics from text. It is built on top of spaCy and can be easily integrated into existing workflows. The package has already been used for analysing the linguistic…

Computation and Language · Computer Science 2023-10-30 Lasse Hansen , Ludvig Renbo Olsen , Kenneth Enevoldsen

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a…

I present a fast Python tool, SpectRes, for carrying out the resampling of spectral flux densities and their associated uncertainties onto different wavelength grids. The function works with any grid of wavelength values, including…

Instrumentation and Methods for Astrophysics · Physics 2017-05-16 A. C. Carnall

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…

Synthcity is an open-source software package for innovative use cases of synthetic data in ML fairness, privacy and augmentation across diverse tabular data modalities, including static data, regular and irregular time series, data with…

Machine Learning · Computer Science 2023-01-19 Zhaozhi Qian , Bogdan-Constantin Cebere , Mihaela van der Schaar

Python has emerged as one of the most popular programming languages, extensively utilized in domains such as machine learning, data analysis, and web applications. Python's dynamic nature and extensive usage make it an attractive candidate…

Software Engineering · Computer Science 2024-03-04 Islem Bouzenia , Bajaj Piyush Krishan , Michael Pradel

Distributed, large-scale quantum computing will need architectures that combine matter-based qubits with photonic links, but today's software stacks target either gate-based chips or linear-optical devices in isolation. We introduce Optyx,…

Computational materials science produces large quantities of data, both in terms of high-throughput calculations and individual studies. Extracting knowledge from this large and heterogeneous pool of data is challenging due to the wide…

Materials Science · Physics 2024-10-23 Martin Kuban , Santiago Rigamonti , Claudia Draxl

In this paper, we present pomdp_py, a general purpose Partially Observable Markov Decision Process (POMDP) library written in Python and Cython. Existing POMDP libraries often hinder accessibility and efficient prototyping due to the…

Artificial Intelligence · Computer Science 2020-04-22 Kaiyu Zheng , Stefanie Tellex

This paper presents a Python software package, Ph3pyWF, providing a more convenient platform to realize high-throughput analysis of lattice thermal conductivity for ceramic materials. The interface of Ph3pyWF is friendly for users with…

Materials Science · Physics 2023-02-24 Kerui Lai , Yuxuan Wang

Software vulnerabilities are a fundamental cause of cyber attacks. Effectively identifying these vulnerabilities is essential for robust cybersecurity, yet it remains a complex and challenging task. In this paper, we present SafePyScript, a…

Software Engineering · Computer Science 2024-11-04 Talaya Farasat , Atiqullah Ahmadzai , Aleena Elsa George , Sayed Alisina Qaderi , Dusan Dordevic , Joachim Posegga

Ordinary Differential Equations (ODE) are used throughout science where the capture of rates of change in states is sought. While both pieces of commercial and open software exist to study such systems, their efficient and accurate usage…

Mathematical Software · Computer Science 2018-03-20 Edwin Tye , Tom Finnie , Ian Hall , Steve Leach

The online data reduction service reductus transforms measurements in experimental science from laboratory coordinates into physically meaningful quantities with accurate estimation of uncertainties based on instrumental settings and…

Data Analysis, Statistics and Probability · Physics 2018-11-15 Brian Maranville , William Ratcliff , Paul Kienzle

We introduce Diddy, a collection of Python scripts for analyzing infinite discrete dynamical systems. The main focus is on generalized multidimensional shifts of finite type (SFTs). We show how Diddy can be used to easily define SFTs and…

Mathematical Software · Computer Science 2023-05-03 Ville Salo , Ilkka Törmä

`scores` is a Python package containing mathematical functions for the verification, evaluation and optimisation of forecasts, predictions or models. It supports labelled n-dimensional (multidimensional) data, which is used in many…

Haydi (http://haydi.readthedocs.io) is a framework for generating discrete structures. It provides a way to define a structure from basic building blocks and then enumerate all elements, all non-isomorphic elements, or generate random…

Formal Languages and Automata Theory · Computer Science 2020-10-22 Stanislav Böhm , Jakub Beránek , Martin Šurkovský

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…

Instrumentation and Methods for Astrophysics · Physics 2022-06-01 Adam Ginsburg , Vlas Sokolov , Miguel de Val-Borro , Erik Rosolowsky , Jaime E. Pineda , Brigitta M. Sipőcz , Jonathan D. Henshaw

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…

Computational Physics · Physics 2025-03-18 Patrick Müller , Wilfried Nörtershäuser

Dealing with uncertainty in applications of machine learning to real-life data critically depends on the knowledge of intrinsic dimensionality (ID). A number of methods have been suggested for the purpose of estimating ID, but no standard…

Machine Learning · Computer Science 2023-12-07 Jonathan Bac , Evgeny M. Mirkes , Alexander N. Gorban , Ivan Tyukin , Andrei Zinovyev