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Abstract: This paper examines the feasibility of high-level Python based utilities for numerically intensive applications via an example of a multidimensional integration for the evaluation of the statistical characteristics of a random variable. We discuss the approaches to the implementation of mathematically formulated incremental expressions using high-level scripting code and low-level compiled code. Due to the dynamic typing of the Python language, components of the algorithm can be easily coded in a generic way as algorithmic templates. Using the Enthought Development Suite they can be effectively assembled into a flexible computational framework that can be configured to execute the code for arbitrary combinations of integration schemes and versions of instantiated code. The paper describes the development cycle using a simple running example involving averaging of a random two-parametric function that includes discontinuity. This example is also used to compare the performance of the available algorithmic and executional features. The implemented package including further examples and the results of performance studies have been made available via the free repository [1] and CPCP library. Program summary: Program title: spirrid Catalogue identifier: AENL_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AENL_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Special licence provided by the author No. of lines in distributed program, including test data, etc.: 10722 No. of bytes in distributed program, including test data, etc.: 157099 Distribution format: tar.gz Programming language: Python and C. Computer: PC. Operating system: LINUX, UNIX, Windows. Classification: 4.13, 6.2. External routines: NumPy (http://numpy.scipy.org/), SciPy (http://www.scipy.com) Nature of problem: Evaluation of the statistical moments of a function of random variables. Solution method: Direct multidimensional integration. Running time: Depending on the number of random variables the time needed for the numerical estimation of the mean value of a function with a sufficiently low level of numerical error varies. For orientation, the time needed for two included examples: examples/fiber_tt_2p/fiber_tt_2p.py with 2 random variables: few milliseconds examples/fiber_po_8p/fiber_po_8p.py with 8 random variables: few seconds [Copyright &y& Elsevier]

UnDiFi-2D , an open source (free software) Un structured-grid, Di scontinuity Fi tting code, is presented. The aim of UnDiFi-2D is to model gas-dynamic discontinuities in two-dimensional (2D) flows as if they were true discontinuities of null thickness that bound regions of the flow-field where a smooth solution to the governing PDEs exists. UnDiFi-2D therefore needs to be coupled with an unstructured CFD solver that is used to discretize the governing PDEs within the smooth regions of the flow-field. Two different, in-house developed, CFD solvers are also included in the current distribution. The main features of the UnDiFi-2D software can be summarized as follows: Programming language UnDiFi-2D is written in standard Fortran 77/95; its design is highly modular in order to enhance simplicity of use, maintenance and allow coupling with virtually any existing CFD solver; Usability, maintenance and enhancement In order to improve the usability, maintenance and enhancement of the code also the documentation has been carefully taken into account. The git distributed versioning system has been adopted to facilitate collaborative maintenance and code development; Copyrights UnDiFi-2D is a free software that anyone can use, copy, distribute, change and improve under the GNU Public License version 3. The present paper is a manifesto of the first public release of the UnDiFi-2D code. It describes the currently implemented features, which are the result of more than a decade of still ongoing CFD developments. This work is focused on the computational techniques adopted and a detailed description of the main characteristics is reported. UnDiFi-2D capabilities are demonstrated by means of examples test cases. The design of the code allows to easily include existing CFD codes and is aimed at ease code reuse and readability. Program title: UnDiFi-2D CPC Library link to program files: https://doi.org/10.17632/5hwssmc2mx.1 Licensing provisions: GNU General Public License, version 3 Programming language: Fortran; developed and tested with Intel Fortran Compiler v. 18.0.3 and GNU gfortran. External routines: The code depends on several libraries and third-party packages which are detailed in the corpus of the text. Nature of problem: Numerical computation of flows with discontinuities. Solution method: Shock-fitting technique. Additional comments including restrictions and unusual features: • At present, UnDiFi-2D is validated for inviscid steady and unsteady two-dimensional flows without changes in the number of discontinuity lines and interaction points. • UnDiFi-2D implements a shock-fitting algorithm and can be coupled with unstructured cell-vertex solvers, with an Arbitrary Lagrangian-Eulerian (ALE) formulation. • UnDiFi-2D project adopts git [1], a free and open source distributed version control system. A public repository dedicated to UnDiFi-2D project [2] has been created on github [3], a web-based hosting service for software development projects using git versioning system. Finally, a comprehensive documentation is provided in the form of user manual developed in Pandoc [4]. [1] Git, a free and open source distributed version control system, http://git-scm.com. [2] UnDiFi-2D documentation, https://github.com/UnDiFi/UnDiFi-2D. [3] Github, a web-based hosting service for software development projects using git versioning system, https://github.com. [4] M. Dominici, TUGboat 35(1) (2014) 44-50. [ABSTRACT FROM AUTHOR]