Projects tagged ‘nonlinear’

OpenShot Video Editor is a non-linear video editor for Linux, built with Python, GTK, and the MLT Framework. Our goal is to create an easy-to-use, powerful, non-linear video editor, with a focus on "User Interface", "Work flow", and "Stability".

ASCEND is an interactive environment for modeling, debugging, and solving large systems of nonlinear algebraic or differential equations. Its interactive design allows users to inspect and solve ... [More] very difficult nonlinear systems. It includes plotting abilities and is scriptable. [Less]

nemesis consists of two parts: a C++ core, embedding the Python interpreter, capable of undertaking a wide variety of static/transient/eigenvalue problems accounting for material and/or geometrical ... [More] nonlinearities, and extras, a set of Python scripts that access the core and exploit usability in simple or more complicated tasks, including pre- and post-processing. Some of the available features in nemesis are: bar/beam/triangle/quad/brick elements, uniaxial elastic/hardening/cyclic/viscoplastic materials, von Mises/Mohr-Coulomb multiaxial elasto-viscoplastic materials, initial/modified/full Newton-Raphson and BFGS algorithms, load/displacement/arc-lenght/Newmark controls and connection to sql databases. nemesis. an experimental finite element code. Copyright (C) 2004-2007 F.E. Karaoulanis. [Less]

OTK++OTK++ (Optimization Toolkit) is a nonlinear optimization library written in C++. It also has a Python-based interface for testing and comparing algorithms and a Qt-based GUI for demonstration ... [More] purposes. Linear algebra operations and Python interfaces are written by using uBLAS and Boost.Python. Implemented algorithmsThe currently implemented algorithms are for minimization of functions of the form f:R^n->R. Some algorithms also support imposing constraints. The following algorithms are implemented by the author of this package: Line search algorithms: More and Thuente Fletcher Trust region algorithms: Steihaug Dogleg Multidimensional solvers: Hooke-Jeeves PARTAN Steihaug-SR1 Dogleg-BFGS Fletcher-Reeves and Polak-Ribiere conjugate gradient algorithms BFGS and L-BFGS algorithms Modified Newton Other algorithms included in this library: Algorithms implemented in the GSL multimin package (version 1.11) L-BFGS-B for bound-constrained large-scale optimization [3] LMBM algorithm for nonsmooth large-scale optimization [4] Algorithms to be implemented (either by rewriting from scratch or by using existing Fortran implementations): Powell's NEWUOA algorithm RequirementsRequired dependencies: uBLAS >= 1.34 g++ >= 4.2 CMake >= 2.6 Optional dependencies: Library/program Version CMake flag Enables GSL >= 1.11 -DWITH_GSL=ON/OFF GSL minimization algorithms GNU libmatheval >= 1.1.3 -DWITH_LIBMATHEVAL=ON/OFF symbolic function evaluation gfortran >= 4.2 -DWITH_FORTRAN=ON/OFF algorithms implemented in Fortran (e.g. LMBM) Qt >= 4.3 -DWITH_QT=ON/OFF Qt-based GUI Qwt >= 5.1 -DWITH_QT=ON/OFF 2d plotting widgets QwtPlot3D >= 0.2 -DWITH_QT=ON/OFF 3d plotting widgets InstallationOTK++ uses CMake as its build system. To install the C++ libraries, extract the otkpp tarball and type the following commands: cmake . By default, headers will be installed in /usr/local/include/otkpp, libraries in /usr/local/lib and binaries in /usr/local/bin. You can change the install prefix by appending -DCMAKE_INSTALL_PREFIX= to the list of CMake flags. PyOTKPyOTK is a Python extension for OTK++. It uses Boost.Python for exposing the OTK++ classes into Python. Several classes and functions for analyzing and visualizing the behaviour of minimization algorithms are implemented in PyOTK. RequirementsAs PyOTK is an extension of OTK++, it requires that the OTK++ libraries, and they must be installed with either the prefix /usr or /usr/local. PyOTK has been tested to compile with Python 2.5/2.6 and Boost.Python 1.34. Python 3.0 and newer are not currently supported. PyOTK also requires the following Python libraries: Matplotlib >= 0.98 NumPy >= 1.1.0 SciPy >= 0.6.0 InstallationPyOTK uses distutils for compiling the C++ interface libraries and copying the Python scripts to appropriate directories in the system path. To install PyOTK, extract the pyotk tarball and type the following command: python setup.py installNOTE: The functionality of the Python interface depends on the flags the OTK++ library was compiled with. The setup.py script automatically parses the configuration file generated by the OTK++ install script and reads the variables it was configured with. ReferencesThe algorithms implemented in OTK++ are based on the following references: [1] J. Nocedal and S.J. Wright, Numerical Optimization, 1999 [2] C.T. Kelley, Iterative Methods for Optimization, 1999 [3] C. Zhu, R.H. Byrd and J. Nocedal, L-BFGS-B: Algorithm 778: L-BFGS-B, FORTRAN routines for large scale bound constrained optimization (1997), ACM Transactions on Mathematical Software, Vol 23, Num. 4, pp. 550-560 [4] N. Karmitsa, "LMBM - FORTRAN Subroutines for Large-Scale Nonsmooth Minimization: User's Manual", TUCS Technical Report, No. 856, Turku Centre for Computer Science, Turku, 2007. [Less]

Non linear propagation of a high intensity laser

A collection of tools for modeling nonlinear optical phenomena. Software is available for: basic gaussian beams counterpropagating beam nonlinearities optical pattern formation in 3D systems

A minimalist interface representing an open end nonlinear essay. The text has one beginning and many ends as the contributor (or the group of contributors) can open a new line of thought which in turn ... [More] can alse split in many paths. Navigation within the tree structure of the nonlinear text is available through the arrow keys as well as a through placemarking in a dynamically updated map of all the possible lines of thought. The project includes an administration panel of the group of readers and authors. [Less]

KARMA is a multi-physics, transient, nonlinear solver for reactor core analysis problems, written entirely in C++. It uses linear algebra data-structures provided by PETSc (Vec, Mat, KSP, SNES) ... [More] which ensures fast, reliable and scalable execution. The spatial discretization of the different physics are performed using a Finite Element (FE) library, libMesh, which provides interfaces also to work with standard libraries like PETSc, SLEPc, ParMetis and packages like Gmsh, VISIT for mesh generation and visualization respectively; The temporal integration can be performed using arbitrary DIRK schemes to accurately resolve the nonlinearities in the different physics, even in a stiff setting; Different representative physics in a reactor core are given by coarse grain models currently; Future versions will include detailed physics. Several numerical and physics-based Preconditioners will be available for each of the different physics to improve overall execution efficiency. [Less]

An extensible Python framework for visualizing dynamical systems.

OverviewMotivationThe goal of the Python Optical Fiber Toolkit is to provide a group of optical fiber related Python/Numpy functions and class in one coherent package in such a way that undergraduates ... [More] student can explore and make simple calculation about optical fiber. This project has been moved to GitHub: http://github.com/mlaprise/PyOFTK/tree/master [Less]