qml-module-qzxing

QZXing QML/QtQuick module

Qt wrapper for the ZXing 1D/2D barcode image decoder.

casacore-data-jpl-de405

Jet Propulsion Laboratory Development Ephemeris DE405 for casacore

The name Jet Propulsion Laboratory Development Ephemeris are a series of models of the Solar System produced at the Jet Propulsion Laboratory in Pasadena, California, primarily for purposes of spacecraft navigation and astronomy.

libgnatvsn5-mipsel-cross

GNU Ada compiler selected components (shared library)

GNAT is a compiler for the Ada programming language. It produces optimized code on platforms supported by the GNU Compiler Collection (GCC).

gnat-5-sjlj-aarch64-linux-gnu

GNU Ada compiler (setjump/longjump runtime library)

GNAT is a compiler for the Ada programming language. It produces optimized code on platforms supported by the GNU Compiler Collection (GCC).

libstopt4

library for stochastic optimization problems (shared library)

The STochastic OPTimization library (StOpt) aims at providing tools in C++ for solving some stochastic optimization problems encountered in finance or in the industry. Different methods are available: - dynamic programming methods based on Monte Carlo with regressions (global, local, kernel and sparse regressors), for underlying states following some uncontrolled Stochastic Differential Equations; - dynamic programming with a representation of uncertainties with a tree: transition problems are here solved by some discretizations of the commands, resolution of LP with cut representation of the Bellman values; - Semi-Lagrangian methods for Hamilton Jacobi Bellman general equations for underlying states following some controlled Stochastic Differential Equations; - Stochastic Dual Dynamic Programming methods to deal with stochastic stock management problems in high dimension. Uncertainties can be given by Monte Carlo and can be represented by a state with a finite number of values (tree); - Some branching nesting methods to solve very high dimensional non linear PDEs and some appearing in HJB problems. Besides some methods are provided to solve by Monte Carlo some problems where the underlying stochastic state is controlled. For each method, a framework is provided to optimize the problem and then simulate it out of the sample using the optimal commands previously computed. Parallelization methods based on OpenMP and MPI are provided in this framework permitting to solve high dimensional problems on clusters. The library should be flexible enough to be used at different levels depending on the user's willingness.

python-pep8-naming

check for PEP 8 naming conventions (flake8 plugin for Python2)

The PEP 8 recommendation is a style guide for Python code. This plugin for flake8 checks whether the naming conventions of PEP 8 have been commplied with. However written as plugin for flake8, some tools make independent use of the module.