Package Name | Access | Summary | Updated |
---|---|---|---|

pybind11 | public | Seamless operability between C++11 and Python | 2020-01-18 |

gidgethub | public | An async GitHub API library for Python | 2020-01-18 |

cymetric | public | Cyclus Metrics | 2020-01-18 |

awscli | public | Universal Command Line Environment for AWS. | 2020-01-18 |

boto3 | public | Amazon Web Services SDK for Python | 2020-01-18 |

botocore | public | Low-level, data-driven core of boto 3. | 2020-01-18 |

pivy | public | python bindings to coin3d. | 2020-01-17 |

r-factominer | public | Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017). | 2020-01-17 |

pyfmmlib | public | Python wrappers for FMMLIB2D and FMMLIB3D | 2020-01-17 |

pyside2 | public | Python bindings for Qt | 2020-01-17 |

gmp | public | The GNU multiprecision library. | 2020-01-17 |

soqt | public | SoQt library needed by Coin3d. | 2020-01-17 |

dynesty | public | A dynamic nested sampling package for computing Bayesian posteriors and evidences. | 2020-01-17 |

coin3d | public | Coin3D is a c++ high-level 3D graphics toolkit. | 2020-01-17 |

googleapis-common-protos | public | Common protobufs used in Google APIs | 2020-01-17 |

orekit | public | An accurate and efficient core layer for space flight dynamics applications | 2020-01-17 |

python-jsonrpc-server | public | A Python 2.7 and 3.4+ server implementation of the JSON RPC 2.0 protocol. | 2020-01-17 |

pycsw | public | OGC Catalogue Service for the Web (CSW) server implementation written in Python. | 2020-01-17 |

django-ajax-selects | public | Edit ForeignKey, ManyToManyField and CharField in Django Admin using jQuery UI AutoComplete. | 2020-01-17 |

r-sjlabelled | public | Collection of functions dealing with labelled data, like reading and writing data between R and other statistical software packages like 'SPSS', 'SAS' or 'Stata', and working with labelled data. This includes easy ways to get, set or change value and variable label attributes, to convert labelled vectors into factors or numeric (and vice versa), or to deal with multiple declared missing values. | 2020-01-17 |

libsemigroups | public | C++ library for semigroups and monoids | 2020-01-17 |

alpenglow | public | Open Source Recommender Framework with Time-aware Learning and Evaluation | 2020-01-17 |

pytest | public | Simple and powerful testing with Python. | 2020-01-17 |

orange3 | public | component-based data mining framework | 2020-01-17 |

r-rhpcblasctl | public | Control the number of threads on 'BLAS' (Aka 'GotoBLAS', 'OpenBLAS', 'ACML', 'BLIS' and 'MKL'). And possible to control the number of threads in 'OpenMP'. Get a number of logical cores and physical cores if feasible. | 2020-01-17 |

r-fpc | public | Various methods for clustering and cluster validation. Fixed point clustering. Linear regression clustering. Clustering by merging Gaussian mixture components. Symmetric and asymmetric discriminant projections for visualisation of the separation of groupings. Cluster validation statistics for distance based clustering including corrected Rand index. Standardisation of cluster validation statistics by random clusterings and comparison between many clustering methods and numbers of clusters based on this. Cluster-wise cluster stability assessment. Methods for estimation of the number of clusters: Calinski-Harabasz, Tibshirani and Walther's prediction strength, Fang and Wang's bootstrap stability. Gaussian/multinomial mixture fitting for mixed continuous/categorical variables. Variable-wise statistics for cluster interpretation. DBSCAN clustering. Interface functions for many clustering methods implemented in R, including estimating the number of clusters with kmeans, pam and clara. Modality diagnosis for Gaussian mixtures. For an overview see package?fpc. | 2020-01-17 |

assimulo | public | A package for solving ordinary differential equations and differential algebraic equations. | 2020-01-17 |

r-bridgesampling | public | Provides functions for estimating marginal likelihoods, Bayes factors, posterior model probabilities, and normalizing constants in general, via different versions of bridge sampling (Meng & Wong, 1996, <http://www3.stat.sinica.edu.tw/statistica/j6n4/j6n43/j6n43.htm>). | 2020-01-17 |

r-bit | public | True boolean datatype (no NAs), coercion from and to logicals, integers and integer subscripts; fast boolean operators and fast summary statistics. With 'bit' vectors you can store true binary booleans {FALSE,TRUE} at the expense of 1 bit only, on a 32 bit architecture this means factor 32 less RAM and ~ factor 32 more speed on boolean operations. Due to overhead of R calls, actual speed gain depends on the size of the vector: expect gains for vectors of size > 10000 elements. Even for one-time boolean operations it can pay-off to convert to bit, the pay-off is obvious, when such components are used more than once. Reading from and writing to bit is approximately as fast as accessing standard logicals - mostly due to R's time for memory allocation. The package allows to work with pre-allocated memory for return values by calling .Call() directly: when evaluating the speed of C-access with pre-allocated vector memory, coping from bit to logical requires only 70% of the time for copying from logical to logical; and copying from logical to bit comes at a performance penalty of 150%. the package now contains further classes for representing logical selections: 'bitwhich' for very skewed selections and 'ri' for selecting ranges of values for chunked processing. All three index classes can be used for subsetting 'ff' objects (ff-2.1-0 and higher). | 2020-01-17 |

glymur | public | Tools for accessing JPEG2000 files | 2020-01-17 |

dask | public | Parallel PyData with Task Scheduling | 2020-01-17 |

dask-core | public | Parallel Python with task scheduling | 2020-01-17 |

r-origami | public | A general framework for the application of cross-validation schemes to particular functions. By allowing arbitrary lists of results, origami accommodates a range of cross-validation applications. | 2020-01-16 |

metsim | public | Meteorology Simulator for Python | 2020-01-16 |

xpdconf | public | Configuration for XPD beamlines | 2020-01-16 |

r-rrcov | public | Robust Location and Scatter Estimation and Robust Multivariate Analysis with High Breakdown Point. | 2020-01-16 |

r-leaps | public | Regression subset selection, including exhaustive search. | 2020-01-16 |

impactutils | public | Utility library for USGS earthquake applications. | 2020-01-16 |

autobahn | public | WebSocket and WAMP in Python for Twisted and asyncio | 2020-01-16 |

r-knitr | public | Provides a general-purpose tool for dynamic report generation in R using Literate Programming techniques. | 2020-01-16 |

fastcluster | public | Fast hierarchical clustering routines for R and Python. | 2020-01-16 |

django-extensions | public | Extensions for Django. | 2020-01-16 |

r-shinycssloaders | public | Automatically show loader animations while a Shiny output is (re)calculating. This is mostly a wrapper around the css-loaders created by Luke Hass <https://github.com/lukehaas/css-loaders>. | 2020-01-16 |

r-diagrammer | public | Build graph/network structures using functions for stepwise addition and deletion of nodes and edges. Work with data available in tables for bulk addition of nodes, edges, and associated metadata. Use graph selections and traversals to apply changes to specific nodes or edges. A wide selection of graph algorithms allow for the analysis of graphs. Visualize the graphs and take advantage of any aesthetic properties assigned to nodes and edges. | 2020-01-16 |

r-ggspectra | public | Additional annotations, stats, geoms and scales for plotting "light" spectra with 'ggplot2', together with specializations of ggplot() and autoplot() methods for spectral data and waveband definitions stored in objects of classes defined in package 'photobiology'. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>. | 2020-01-16 |

python-lalsimulation | public | LSC Algorithm Simulation Library | 2020-01-16 |

lalsimulation | public | LSC Algorithm Simulation Library | 2020-01-16 |

r-future | public | The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use `x %<-% { expression }` with `plan(multiprocess)`. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implement additional backends for processing futures via compute cluster schedulers etc. Because of its unified API, there is no need to modify any code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures. | 2020-01-16 |

r-farver | public | The encoding of colour can be handled in many different ways, using different colour spaces. As different colour spaces have different uses, efficient conversion between these representations are important. The 'farver' package provides a set of functions that gives access to very fast colour space conversion and comparisons implemented in C++, and offers speed improvements over the 'convertColor' function in the 'grDevices' package. | 2020-01-16 |

pygmo | public | A C++ / Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model | 2020-01-16 |

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