relax is a program designed for the study of the dynamics of proteins or other macromolecules though the analysis of NMR relaxation experiments. It supports exponential curve fitting for the calculation of the R1 and R2 relaxation rates, calculation of the NOE, reduced spectral density mapping, the Lipari and Szabo model-free analysis, study of domain motions via the N-state model and frame order dynamics theories using anisotropic NMR parameters such as RDCs and PCSs, and the investigation of stereochemistry.
Rocket Propulsion Analysis (RPA) is a tool for the performance prediction of rocket engines. By providing a few engine parameters such as combustion chamber pressure, used propellant components, and nozzle parameters, the program obtains chemical equilibrium composition of combustion products, determines its thermodynamic properties, and predicts the theoretical rocket performance. A robust, proven, and industry-accepted Gibbs free energy minimization approach is used to obtain the combustion composition. It can perform analysis of nozzle flows with shifting and frozen chemical equilibrium, optimization of propellant components mixture ratio for maximum specific impulse of bipropellant systems, altitude performance analysis, analysis of nozzle performance with respect to overexpansion and flow separation, throttled engine performance analysis, estimation of test (actual) nozzle performance, and nested analysis: stepping of up to four independent variables (component ratio, chamber pressure, nozzle inlet conditions, and nozzle exit conditions).
HOPSPACK solves derivative-free optimization problems in a C++ software framework. The framework enables parallel operation using MPI (for distributed machine architectures) and multithreading (for single machines with multiple processors or cores). Optimization problems can be very general: functions can be noisy, nonsmooth, and nonconvex, linear and nonlinear constraints are supported, and variables may be continuous or integer-valued.
Kst is a fast real-time large-dataset viewing and plotting tool with built-in data analysis functionality. It contains many powerful built-in features and is expandable with plugins and extensions. It features powerful keyboard and mouse plot manipulation, a large selection of built-in plotting and data manipulation functions (such as histograms, equations, and power spectra), built-in filtering and curve fitting capabilities, a convenient command-line interface, a powerful graphical user interface with non-modal dialogs for an optimized workflow, support for several popular data formats, extended annotation objects similar to vector graphics applications, and high-quality export to bitmap or vector formats,
scikits.statsmodels is a Python package which provides a complement to scipy for statistical computations, including descriptive statistics and estimation of statistical models. The main included model categories are linear, discrete, generalized linear, and robust linear models, and, in time series analysis, AR, ARMA, and VAR. It also includes statistical tests mainly for regression diagnostics.
statsmodels is a Python package which provides a complement to scipy for statistical computations, including descriptive statistics and estimation of statistical models. The main included model categories are linear, discrete, generalized linear, and robust linear, and, in time series analysis, AR, ARMA, and VAR. It also includes statistical tests mainly for regression diagnostics. statsmodels was renamed from scikits.statsmodels.