conda-forge / packages

Package Name Access Summary Updated
python public General purpose programming language. 2019-02-24
configparser public This library brings the updated configparser from Python 3.5 to Python 2.6-3.5 2019-02-24
elementpath public XPath 1.0/2.0 parsers and selectors for ElementTree 2019-02-24
openbabel public A chemical toolbox designed to speak the many languages of chemical data 2019-02-24
enum34 public No Summary 2019-02-24
gwdetchar public A python package for gravitational-wave detector characterisation 2019-02-24
pycraf public A Python package for spectrum-management compatibility studies 2019-02-24
xlwings public Interact with Excel from Python and vice versa 2019-02-23
hypothesis public A library for property based testing 2019-02-23
subprocess32 public A backport of the subprocess module from Python 3.2/3.3 for use on 2.x. 2019-02-23
xpdan public Analysis Tools for XPD 2019-02-23
aiozmq public ZeroMQ integration with asyncio. 2019-02-23
shed public Streaming Heterogeneous Event Data 2019-02-23
socat public No Summary 2019-02-23
nginx public Nginx is an HTTP and reverse proxy server 2019-02-23
orca_test public Assertions for testing the characteristics of orca tables and columns 2019-02-23
lscsoft-glue public Grid LSC User Engine 2019-02-23
xlsxwriter public A Python module for creating Excel XLSX files 2019-02-23
khronos-opencl-icd-loader public A driver loader for OpenCL 2019-02-23
python-lalinspiral public LSC Algorithm Inspiral Library 2019-02-23
lalinspiral public LSC Algorithm Inspiral Library 2019-02-23
python-lalburst public LSC Algorithm Burst Library 2019-02-23
lalburst public LSC Algorithm Burst Library 2019-02-23
pycondor public Python utility for HTCondor 2019-02-23
tableone public Create Table 1 for research papers in Python 2019-02-23
vmtouch public Portable file system cache diagnostics and control 2019-02-23
websocket-client public WebSocket client for python. hybi13 is supported. 2019-02-23
coincbc public Cbc (Coin-or branch and cut) is an open-source mixed integer programming solver written in C++. 2019-02-23
xonda public This is a thin wrapper around conda for use with xonsh 2019-02-23
r-ergm.count public A set of extensions for the 'ergm' package to fit weighted networks whose edge weights are counts. 2019-02-23
r-tergm public An integrated set of extensions to the 'ergm' package to analyze and simulate network evolution based on exponential-family random graph models (ERGM). 'tergm' is a part of the 'statnet' suite of packages for network analysis. 2019-02-23
pyexcel public Single API for reading, manipulating and writing data in csv, ods, xls, xlsx and xlsm files 2019-02-23
fs public Filesystem abstraction layer for Python 2019-02-23
r-xtensor public R bindings for xtensor, the C++ tensor algebra library 2019-02-23
testfixtures public A collection of helpers and mock objects for unit tests and doc tests. 2019-02-23
responder public A familiar HTTP Service Framework for Python 2019-02-23
trimesh public Import, export, process, analyze and view triangular meshes. 2019-02-23
shap public A unified approach to explain the output of any machine learning model. 2019-02-23
cdutil public A set of tools to manipulate climate data 2019-02-23
libgfortran public Fortran compiler and libraries from the GNU Compiler Collection 2019-02-23
awscli public Universal Command Line Environment for AWS. 2019-02-23
ngmix public Gaussian mixtures and image processing implemented in python and C 2019-02-23
animatplot public Animating plots with matplotlib made easy 2019-02-23
jupytext public Jupyter notebooks as Markdown documents, Julia, Python or R scripts 2019-02-23
boto3 public Amazon Web Services SDK for Python 2019-02-23
genutil public General Utitilites for the Community Data Analysys Tools 2019-02-23
uproot public ROOT I/O in pure Python and Numpy. 2019-02-22
uproot-base public ROOT I/O in pure Python and Numpy. 2019-02-22
r-ergm public An integrated set of tools to analyze and simulate networks based on exponential-family random graph models (ERGMs). 'ergm' is a part of the Statnet suite of packages for network analysis. 2019-02-22
r-huge public Provides a general framework for high-dimensional undirected graph estimation. It integrates data preprocessing, neighborhood screening, graph estimation, and model selection techniques into a pipeline. In preprocessing stage, the nonparanormal(npn) transformation is applied to help relax the normality assumption. In the graph estimation stage, the graph structure is estimated by Meinshausen-Buhlmann graph estimation or the graphical lasso, and both methods can be further accelerated by the lossy screening rule preselecting the neighborhood of each variable by correlation thresholding. We target on high-dimensional data analysis usually d >> n, and the computation is memory-optimized using the sparse matrix output. We also provide a computationally efficient approach, correlation thresholding graph estimation. Three regularization/thresholding parameter selection methods are included in this package: (1)stability approach for regularization selection (2) rotation information criterion (3) extended Bayesian information criterion which is only available for the graphical lasso. 2019-02-22
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