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cryspy
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public |
PNPD data analysis
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2025-09-24 |
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r-fail
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public |
More comfortable interface to work with R data or source files in a key-value fashion.
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2025-09-24 |
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r-datacomparer
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public |
Easy comparison of two tabular data objects in R. Specifically designed to show differences between two sets of data in a useful way that should make it easier to understand the differences, and if necessary, help you work out how to remedy them. Aims to offer a more useful output than all.equal() when your two data sets do not match, but isn't intended to replace all.equal() as a way to test for equality.
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2025-09-24 |
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r-bwstools
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public |
Tools to design best-worst scaling designs (i.e., balanced incomplete block designs) and to analyze data from these designs, using aggregate and individual methods such as: difference scores, Louviere, Lings, Islam, Gudergan, & Flynn (2013) <doi:10.1016/j.ijresmar.2012.10.002>; analytical estimation, Lipovetsky & Conklin (2014) <doi:10.1016/j.jocm.2014.02.001>; empirical Bayes, Lipovetsky & Conklin (2015) <doi:10.1142/S1793536915500028>; Elo, Hollis (2018) <doi:10.3758/s13428-017-0898-2>; and network-based measures.
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2025-09-24 |
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r-lvm4net
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public |
Latent variable models for network data using fast inferential procedures. For more information please visit: <http://igollini.github.io/lvm4net/>.
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2025-09-24 |
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r-ggdag
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public |
Tidy, analyze, and plot directed acyclic graphs (DAGs). 'ggdag' is built on top of 'dagitty', an R package that uses the 'DAGitty' web tool (<http://dagitty.net>) for creating and analyzing DAGs. 'ggdag' makes it easy to tidy and plot 'dagitty' objects using 'ggplot2' and 'ggraph', as well as common analytic and graphical functions, such as determining adjustment sets and node relationships.
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2025-09-24 |
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r-clustree
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public |
Deciding what resolution to use can be a difficult question when approaching a clustering analysis. One way to approach this problem is to look at how samples move as the number of clusters increases. This package allows you to produce clustering trees, a visualisation for interrogating clusterings as resolution increases.
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2025-09-24 |
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injective-py
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public |
Injective Python SDK, with Exchange API client
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2025-09-24 |
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r-plnmodels
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public |
The Poisson-lognormal model and variants can be used for a variety of multivariate problems when count data are at play, including principal component analysis for count data (Chiquet, Mariadassou and Robin, 2018 <doi:10.1214/18-AOAS1177>), discriminant analysis and network inference (Chiquet, Mariadassou and Robin, 2018 <http://proceedings.mlr.press/v97/chiquet19a.html>). Implements variational algorithms to fit such models accompanied with a set of functions for visualization and diagnostic.
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2025-09-24 |
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libmetatensor-torch
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public |
TorchScript/C++ bindings to metatensor
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2025-09-24 |
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neomodel
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public |
An object mapper for the neo4j graph database.
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2025-09-24 |
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r-polynomf
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public |
Implements univariate polynomial operations in R, including polynomial arithmetic, finding zeros, plotting, and some operations on lists of polynomials.
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2025-09-24 |
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fake-factory
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public |
Faker is a Python package that generates fake data for you.
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2025-09-24 |
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epoxy
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public |
A library for handling OpenGL function pointer management for you.
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2025-09-24 |
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adwaita-icon-theme
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public |
The default icon theme used by the GNOME desktop
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2025-09-24 |
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r-ggtangle
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public |
Extends the 'ggplot2' plotting system to support network visualization. Inspired by the 'Method 1' in 'ggtree' (G Yu (2018) <doi:10.1093/molbev/msy194>), 'ggtangle' is designed to work with network associated data.
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2025-09-24 |
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aiida-quantumespresso.meta
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public |
The official AiiDA plugin for Quantum ESPRESSO
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2025-09-24 |
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aiida-quantumespresso.code
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public |
The official AiiDA plugin for Quantum ESPRESSO
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2025-09-24 |
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aiida-quantumespresso
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public |
The official AiiDA plugin for Quantum ESPRESSO
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2025-09-24 |
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r-tsstudio
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public |
Provides a set of tools for descriptive and predictive analysis of time series data. That includes functions for interactive visualization of time series objects and as well utility functions for automation time series forecasting.
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2025-09-24 |
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r-waterfalls
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public |
A not uncommon task for quants is to create 'waterfall charts'. There seems to be no simple way to do this in 'ggplot2' currently. This package contains a single function (waterfall) that simply draws a waterfall chart in a 'ggplot2' object. Some flexibility is provided, though often the object created will need to be modified through a theme.
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2025-09-24 |
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r-marmap
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public |
Import xyz data from the NOAA (National Oceanic and Atmospheric Administration, <https://www.noaa.gov>), GEBCO (General Bathymetric Chart of the Oceans, <https://www.gebco.net>) and other sources, plot xyz data to prepare publication-ready figures, analyze xyz data to extract transects, get depth / altitude based on geographical coordinates, or calculate z-constrained least-cost paths.
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2025-09-24 |
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r-tpea
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public |
We described a novel Topology-based pathway enrichment analysis, which integrated the global position of the nodes and the topological property of the pathways in Kyoto Encyclopedia of Genes and Genomes Database. We also provide some functions to obtain the latest information about pathways to finish pathway enrichment analysis using this method.
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2025-09-24 |
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r-graddescent
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public |
An implementation of various learning algorithms based on Gradient Descent for dealing with regression tasks. The variants of gradient descent algorithm are : Mini-Batch Gradient Descent (MBGD), which is an optimization to use training data partially to reduce the computation load. Stochastic Gradient Descent (SGD), which is an optimization to use a random data in learning to reduce the computation load drastically. Stochastic Average Gradient (SAG), which is a SGD-based algorithm to minimize stochastic step to average. Momentum Gradient Descent (MGD), which is an optimization to speed-up gradient descent learning. Accelerated Gradient Descent (AGD), which is an optimization to accelerate gradient descent learning. Adagrad, which is a gradient-descent-based algorithm that accumulate previous cost to do adaptive learning. Adadelta, which is a gradient-descent-based algorithm that use hessian approximation to do adaptive learning. RMSprop, which is a gradient-descent-based algorithm that combine Adagrad and Adadelta adaptive learning ability. Adam, which is a gradient-descent-based algorithm that mean and variance moment to do adaptive learning. Stochastic Variance Reduce Gradient (SVRG), which is an optimization SGD-based algorithm to accelerates the process toward converging by reducing the gradient. Semi Stochastic Gradient Descent (SSGD),which is a SGD-based algorithm that combine GD and SGD to accelerates the process toward converging by choosing one of the gradients at a time. Stochastic Recursive Gradient Algorithm (SARAH), which is an optimization algorithm similarly SVRG to accelerates the process toward converging by accumulated stochastic information. Stochastic Recursive Gradient Algorithm+ (SARAHPlus), which is a SARAH practical variant algorithm to accelerates the process toward converging provides a possibility of earlier termination.
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2025-09-24 |
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r-tfdatasets
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public |
Interface to 'TensorFlow' Datasets, a high-level library for building complex input pipelines from simple, re-usable pieces. See <https://www.tensorflow.org/programmers_guide/datasets> for additional details.
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2025-09-24 |
