QtIPy is a simple GUI-based automator for IPython notebooks. It allows you to attach triggers to files, folders, or timers to automatically run notebooks. IPython notebooks are great for interactively working through analysis problems, so why would you want to automatically run them? To get a record of how you ran your analysis! By running a notebook through QtIPy you get the output, figures, and a step by step log of how the analysis was performed all in the same folder.
iNA is a computational tool for quantitative analysis of fluctuations in biochemical reaction networks. Such fluctuations, also known as intrinsic noise, arise due to the stochastic nature of chemical reactions and cannot be ignored for when some molecules are present only in very low copy numbers as is the case in living cells. The SBML-based software computes statistical measures such as means and standard deviations of concentrations within a given accuracy using the analytical system size expansion. The result of iNA’s analysis can be tested against the computationally much more expensive stochastic simulation algorithm.
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.
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.
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,
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.