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trollsift
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public |
String parser/formatter for PyTroll packages
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2025-04-22 |
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python-geotiepoints
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public |
Interpolation of geographic tiepoints in Python
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2025-04-22 |
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pycoast
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public |
Writing of coastlines, borders and rivers to images in Python
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2025-04-22 |
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cgroupspy
|
public |
Python library for managing cgroups
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2025-04-22 |
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r-mice
|
public |
Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in Van Buuren and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.
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2025-04-22 |
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cppheaderparser
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public |
Parse C++ header files and generate a data structure representing the class
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2025-04-22 |
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bisonpp
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public |
The original bison++ project, brought up to date with modern compilers
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2025-04-22 |
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datacache
|
public |
Helpers for transparently downloading datasets
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2025-04-22 |
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r-paco
|
public |
Procrustes analyses to infer co-phylogenetic matching between pairs of (ultrametric) phylogenetic trees.
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2025-04-22 |
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python_http_client
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public |
SendGrid's Python HTTP Client for calling APIs
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2025-04-22 |
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w3g
|
public |
Access Warcraft 3 replay files from Python 2 or 3
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2025-04-22 |
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trollimage
|
public |
Pytroll imaging library
|
2025-04-22 |
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memoized-property
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public |
A simple python decorator for defining properties that only run their fget function once
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2025-04-22 |
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aggdraw
|
public |
High quality drawing interface for PIL.
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2025-04-22 |
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cykdtree
|
public |
Cython based KD-Tree
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2025-04-22 |
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grove
|
public |
A collection of quantum algorithms built using pyQuil and Forest
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2025-04-22 |
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bamnostic
|
public |
a pure Python, OS-agnositic Binary Alignment Map (BAM) file parser and random access tool.
|
2025-04-22 |
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chemdataextractor
|
public |
Automatically extract chemical information from scientific documents.
|
2025-04-22 |
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sexpdata
|
public |
S-expression parser for Python
|
2025-04-22 |
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unittest2
|
public |
Recent features of the unittest package backported to Python <= 3.4.
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2025-04-22 |
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typechecks
|
public |
Helper functions for runtime type checking
|
2025-04-22 |
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tinytimer
|
public |
Tiny Python benchmarking library
|
2025-04-22 |
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sphinx-releases
|
public |
A powerful Sphinx changelog-generating extension
|
2025-04-22 |
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tensorly
|
public |
Tensor learning in Python
|
2025-04-22 |
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r-brms
|
public |
Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include non-linear and smooth terms, auto-correlation structures, censored data, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed and compared with posterior predictive checks and leave-one-out cross-validation. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; Bürkner (2018) <doi:10.32614/RJ-2018-017>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
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2025-04-22 |
