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Gyselalib++ is a collection of C++ components for writing gyrokinetic semi-lagrangian codes and similar as well as a collection of such codes.
Davix aims to make the task of managing files overHTTP-based protocols simple. It is being developed by the IT-SDC-ID section at CERN, and while the project’s purpose is its use on the CERN grid, the functionality offered is generic.
This package provides a small and thin Python interface to read Les Houches Event (LHE) files.
distinctipy is a lightweight python package providing functions to generate colours that are visually distinct from one another.
Confit is a complete and easy-to-use configuration framework aimed at improving the reproducibility of experiments by relying on the Python typing system, minimal configuration files and command line interfaces.
Envisage is a Python-based framework for building extensible applications, that is, applications whose functionality can be extended by adding 'plug-ins. Envisage provides a standard mechanism for features to be added to an application, whether by the original developer or by someone else. In fact, when you build an application using Envisage, the entire application consists primarily of plug-ins. In this respect, it is similar to the Eclipse and Netbeans frameworks for Java applications.
The pyjson-tricks package brings several pieces of functionality to python handling of JSON files:
Store and load numpy arrays in human-readable format.
Store and load class instances both generic and customized.
Store and load date/times as a dictionary (including timezone).
Preserve map order using OrderedDict.
Allow for comments in json files by starting lines with #.
Sets, complex numbers, Decimal, Fraction, enums, compression, duplicate keys, pathlib Paths, bytes, ...
As well as compression and disallowing duplicate keys.
This package provides a hierarchical data modeling framework for modern science data standards.
dask-jobqueue makes it easy to deploy Dask on common job queuing systems typically found in high performance supercomputers, academic research institutions, and other clusters, like PBS, Slurm, MOAB, SGE, LSF, and HTCondor.
This package provides a pure Python library to create SVG drawings.
Mayavi is a general purpose, cross-platform tool for 2-D and 3-D scientific data visualization.
Python Bindings for the NVIDIA Management Library.
Chaco is a Python package for building interactive and custom 2-D plots and visualizations. Chaco facilitates writing plotting applications at all levels of complexity, from simple scripts with hard-coded data to large plotting programs with complex data interrelationships and a multitude of interactive tools. While Chaco generates attractive static plots for publication and presentation, Chaco differs from tools like Matplotlib in that it also works well for dynamic interactive data visualization and exploration.
This package provides classes and functions for performing customizable robust ICA.
Tools and utilities shared by Deisa backends.
This package provides tools for automated download of UMLS data.
This package provides functions for 3D coordinate transformations.
Compute a single hash of the file contents of a directory.
Bracex is a brace expanding library (à la Bash) for Python. Brace expanding is used to generate arbitrary strings.
h5io is a package designed to facilitate saving some standard Python objects into the forward-compatible HDF5 format. It is a higher-level package than h5py.
Wildcard Match provides an enhanced fnmatch, glob, and pathlib library in order to provide file matching and globbing that more closely follows the features found in Bash.
A Python module to read Matlab files. This module works with both the old (< 7.3) and the new (>= 7.3) HDF5 based format. The output should be the same for both kinds of files.
Discrete Fourier Transform with xarray.
Table logger using Rich, aimed at PyTorch Lightning logging.
Features
display your training logs with pretty rich tables
describe your fields with goal, format and name
a field descriptor can be matched with any regex
a field name can be computed as a regex substitution
works in Jupyter notebooks as well as in a command line
integrates easily with Pytorch Lightning