conda-forge / packages

Package Name Access Summary Updated
dmf-chip public Digital microfluidic chip tools 2019-04-22
mpl_sample_data public Publication quality figures in Python 2019-04-22
matplotlib public Publication quality figures in Python 2019-04-22
matplotlib-base public Publication quality figures in Python 2019-04-22
latlon23 public Methods for representing geographic coordinates 2019-04-22
gsw public Gibbs SeaWater Oceanographic Package of TEOS-10 2019-04-22
mkl-service public Python hooks for Intel(R) Math Kernel Library runtime control settings. 2019-04-22
ipypublish public A workflow for creating and editing publication ready scientific reports, from one or more Jupyter Notebooks 2019-04-22
geocube public Tool to convert geopandas vector data into rasterized xarray data 2019-04-22
rope public A python refactoring library 2019-04-22
click_config_file public Configuration file support for click applications. 2019-04-22
yews public Yews: Your Earthquake Waveform Solutions. 2019-04-22
urllib3 public HTTP library with thread-safe connection pooling, file post, and more. 2019-04-22
xpdsim public A simulation environment for experiments at the XPD beamline at NSLS-II 2019-04-22
xpdan public Analysis Tools for XPD 2019-04-22
xpdtools public Analysis Tools for XPD 2019-04-22
xpdconf public Configuration for XPD beamlines 2019-04-22
postgresql-plpython public The plpythonu postgresql extension 2019-04-22
postgresql public PostgreSQL is a powerful, open source object-relational database system. 2019-04-22
libpq public The postgres runtime libraries and utilities (not the server itself) 2019-04-22
conda public OS-agnostic, system-level binary package and environment manager. 2019-04-22
numpy public Array processing for numbers, strings, records, and objects. 2019-04-22
pycoalescence public Spatially-explicit neutral ecology simulator using coalescence methods 2019-04-22
r-mpmi public Uses a kernel smoothing approach to calculate Mutual Information for comparisons between all types of variables including continuous vs continuous, continuous vs discrete and discrete vs discrete. Uses a nonparametric bias correction giving Bias Corrected Mutual Information (BCMI). Implemented efficiently in Fortran 95 with OpenMP and suited to large genomic datasets. 2019-04-22
r-genetics public Classes and methods for handling genetic data. Includes classes to represent genotypes and haplotypes at single markers up to multiple markers on multiple chromosomes. Function include allele frequencies, flagging homo/heterozygotes, flagging carriers of certain alleles, estimating and testing for Hardy-Weinberg disequilibrium, estimating and testing for linkage disequilibrium, ... 2019-04-22
jsonextended public Extending the python json package functionality 2019-04-22
r-fields public For curve, surface and function fitting with an emphasis on splines, spatial data and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions for large data sets. The splines and Kriging methods are supported by functions that can determine the smoothing parameter (nugget and sill variance) and other covariance function parameters by cross validation and also by restricted maximum likelihood. For Kriging there is an easy to use function that also estimates the correlation scale (range parameter). A major feature is that any covariance function implemented in R and following a simple format can be used for spatial prediction. There are also many useful functions for plotting and working with spatial data as images. This package also contains an implementation of sparse matrix methods for large spatial data sets and currently requires the sparse matrix (spam) package. Use help(fields) to get started and for an overview. The fields source code is deliberately commented and provides useful explanations of numerical details as a companion to the manual pages. The commented source code can be viewed by expanding source code version and looking in the R subdirectory. The reference for fields can be generated by the citation function in R and has DOI <doi:10.5065/D6W957CT>. 2019-04-22
r-copula public Classes (S4) of commonly used elliptical, Archimedean, extreme value and some more copula families. Methods for density, distribution, random number generation, bivariate dependence measures, perspective and contour plots. Fitting copula models including variance estimates. 2019-04-22
camelot-py public PDF Table Extraction for Humans. 2019-04-22
r-jmv public A suite of common statistical methods such as descriptives, t-tests, ANOVAs, regression, correlation matrices, proportion tests, contingency tables, and factor analysis. This package is also useable from the 'jamovi' statistical spreadsheet (see <> for more information). 2019-04-22
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. 2019-04-22
r-igraph public Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more. 2019-04-22
r-infer public The objective of this package is to perform inference using an expressive statistical grammar that coheres with the tidy design framework. 2019-04-22
rioxarray public rasterio xarray extension. 2019-04-22
cms-md5 public Independent implementation of MD5 (RFC 1321). 2019-04-22
python-clang public Python bindings for clang 2019-04-22
r-rfpermute public Estimate significance of importance metrics for a Random Forest model by permuting the response variable. Produces null distribution of importance metrics for each predictor variable and p-value of observed. Provides summary and visualization functions for 'randomForest' results. 2019-04-22
cppzmq public C++ bindings for 0MQ 2019-04-22
xeus-cling public Cling-based C++ kernel for Jupyter based on xeus 2019-04-22
xeus-python public Jupyter kernel for the Python programming language based on xeus 2019-04-22
django-simple-history public Store model history and view/revert changes from admin site. 2019-04-22
pymeasure public Scientific measurement library for instruments, experiments, and live-plotting. 2019-04-21
ruamel.yaml public A YAML package for Python. It is a derivative of Kirill Simonov's PyYAML 3.11 which supports YAML1.1 2019-04-21
r-emmeans public Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and compact letter displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>. 2019-04-21
r-splitstackshape public Online data collection tools like Google Forms often export multiple-response questions with data concatenated in cells. The concat.split (cSplit) family of functions splits such data into separate cells. The package also includes functions to stack groups of columns and to reshape wide data, even when the data are "unbalanced"---something which reshape (from base R) does not handle, and which melt and dcast from reshape2 do not easily handle. 2019-04-21
numpydoc public Numpy's Sphinx extensions 2019-04-21
grpcio-gcp public gRPC extensions for Google Cloud Platform 2019-04-21
flask-appbuilder public Simple and rapid application development framework, built on top of Flask. includes detailed security, auto CRUD generation for your models, google charts and much more. 2019-04-21
r-randtoolbox public Provides (1) pseudo random generators - general linear congruential generators, multiple recursive generators and generalized feedback shift register (SF-Mersenne Twister algorithm and WELL generators); (2) quasi random generators - the Torus algorithm, the Sobol sequence, the Halton sequence (including the Van der Corput sequence) and (3) some generator tests - the gap test, the serial test, the poker test. See e.g. Gentle (2003) <doi:10.1007/b97336>. The package can be provided without the rngWELL dependency on demand. Take a look at the Distribution task view of types and tests of random number generators. Version in Memoriam of Diethelm and Barbara Wuertz. 2019-04-21
brial public Brial - successor to PolyBoRi 2019-04-21
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