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

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 |

pyglet | public | Cross-platform windowing and multimedia library | 2020-01-17 |

climlab | public | Python package for process-oriented climate modeling | 2020-01-17 |

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

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

jupyterlab | public | An extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture. | 2020-01-17 |

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

s3transfer | public | An Amazon S3 Transfer Manager | 2020-01-17 |

itkwidgets | public | Interactive Jupyter widgets to visualize images in 2D and 3D | 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 |

mysql-connector-c | public | MySQL Connector/C, the C interface for communicating with MySQL servers. | 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 |

magics | public | ECMWF's Meteorological plotting software. | 2020-01-16 |

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

abydos | public | Abydos is a python library of phonetic algorithms, string distance measures & metrics, stemmers, and string fingerprinters | 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 |

lalsuite | public | LSC Algorithm Library Suite | 2020-01-16 |

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

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

orange3-network | public | Networks add-on for Orange 3 data mining software package. | 2020-01-16 |

r-gdalutils | public | Wrappers for the Geospatial Data Abstraction Library (GDAL) Utilities. | 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 |

cudatoolkit-dev | public | Develop, Optimize and Deploy GPU-accelerated Apps | 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 |

astroid | public | A abstract syntax tree for Python with inference support. | 2020-01-16 |

orange3-timeseries | public | Orange3 add-on for exploring time series and sequential data. | 2020-01-16 |

scikit-allel | public | A Python package for exploring and analysing genetic variation data. | 2020-01-16 |

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

opencv | public | Computer vision and machine learning software library. | 2020-01-16 |

xeus-python | public | Jupyter kernel for the Python programming language based on xeus | 2020-01-16 |

gwpy | public | A python package for gravitational-wave astrophysics | 2020-01-16 |

adaptive | public | Adaptive parallel sampling of mathematical functions | 2020-01-16 |

jcc | public | a C++ code generator for calling Java from C++/Python | 2020-01-16 |

r-modelmetrics | public | Collection of metrics for evaluating models written in C++ using 'Rcpp'. Popular metrics include area under the curve, log loss, root mean square error, etc. | 2020-01-16 |

r-afex | public | Convenience functions for analyzing factorial experiments using ANOVA or mixed models. aov_ez(), aov_car(), and aov_4() allow specification of between, within (i.e., repeated-measures), or mixed (i.e., split-plot) ANOVAs for data in long format (i.e., one observation per row), automatically aggregating multiple observations per individual and cell of the design. mixed() fits mixed models using lme4::lmer() and computes p-values for all fixed effects using either Kenward-Roger or Satterthwaite approximation for degrees of freedom (LMM only), parametric bootstrap (LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs). afex_plot() provides a high-level interface for interaction or one-way plots using ggplot2, combining raw data and model estimates. afex uses type 3 sums of squares as default (imitating commercial statistical software). | 2020-01-16 |

conda-gitenv | public | Track environment specifications using a git repo. | 2020-01-16 |

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