The Python Papers Anthology
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Modeling and Markov chains
Get PDFArtificial intelligence and simulation are now topics with major interest for researchers and practitioners. Markov chain is a powerful approach of simulation that could be used in multiple area. For example, in management this approach can give numerous opportunities to better understand phenomena. Thus we ask the question: “How can Markov chains be useful to simulate processes? “. This paper is our answer. With Markov chains we show the possibilities to better understand management project. We also propose two programs which explain how to implement these simulations based on Markov chains. The results show that Markov chains approach of simulation can be useful for teaching and explaining processes. Simulation gives data to analyse what can be compared with empirical data or tested for coherence. Simulation with Markov chain can be interpreted and give insights on real causes of complex phenomena
Handing Over the Baton
Get PDFAfter co-founding and running The Python Papers Anthology, which is the umbrella for The Python Paper, for the last 12 years including pre-inaugural issue; I felt that it is time to hand over the baton and reins of the anthology to a new co-Editor-in-Chief
Forecasting Nord Pool day-ahead prices with Python
Get PDFThis paper presents a Nord Pool forecast model for hourly day-ahead prices, utilizing the Python software. The model is an autoregressive model based on [1] and the data spans the period from 2004 to 2011. The targets (i.e. dependent variables) are the hourly day-ahead prices for a certain hour during the day while the features (i.e. independent variables) are the prices for the same hour the previous two days and the previous week, the minimum price for the previous day, four weekday dummy variables, including the demand and wind for the actual hour. We test the model in a simple linear regression framework with cross-validation. Next, we utilize regularized regressions including Ridge and Lasso. Finally, we utilize a Keras neural network. The models are evaluated with the mean absolute percentage error (MAPE) criterion, R-square and scatterplots. The results demonstrate that the models perform well and could add value for a market player
Editor’s Comments
Get PDFThe twelfth issue of The Python Papers.Since 2006, python papers proposed twelve issues of the journal. Python is now one of the most used programming languages and the interest of researchers and practitioners stay strong.This issue consists of two articles. The first article is about Modeling and Markov chains.The second article is entitled: Forecasting Nord Pool day-ahead prices with Python
Creating a Python-based Portable Media Player with Enhanced Parental Control Capabilities
Get PDFWith the rapid development in information technology, children and adolescents have unprecedented access to digital media. Given the double-edged sword digital media has become, parents, teachers and policymakers have concerns about the negative impact that digital media exerts on children and adolescents. This leads to a growing need for digital media content regulation and censorship. However, current suppression of content in Singapore is mild and insufficient. Only a small number of films or TV shows that have explicit sensitive or offensive content were censored. A vast amount of inappropriate media content is still accessible to children and adolescents. Parents are encouraged by the MCI (Ministry of Communications and Information) to guide their children on digital media consumption. Some companies have developed computer programmes that cleanse movies containing offensive scenes. However, existing computer programmes have limited ability in allowing users to adjust the filtering levels, or generating seamless cutting results. Motivated by the above observations, we had developed a novel media player to facilitate home users, content providers and service providers to suppress content, rate and classify digital media. The software permits its user to select various degrees of content suppression according to the user’s level of acumen and discretion. Based on the properties of the sub-file objects pre-set by the user, the software will make use of its dynamic sub-file filter to examine the data set at the sub-file level for scrutiny before the substantiated content is consented for screening. With this software, user can sanitize the digital media content by skipping over specific scenes that may contain nudity, sexual situations and excessive violence, muting potentially objectionable audio words, and blurring out unsavoury objects in the scenes to preserve the integrity of the storyline. The software is also capable of preserving different categories of media classification from an unimpeded multimedia file. Unlike existing movie sanitizing tools, the software does not physically alter the original videos or make replicated copies. By applying pre-set restrictions to the video during playback, it keeps the original video unscathed
Processing Integrated Circuit Layouts Using Python: A Case Study On Rapid Prototyping
Get PDFThis paper narrates our experience developing, in a relatively short time, an application to rasterize layers of integrated circuit (IC) layout definitions specified in the Calma Graphic Data System (GDS) II file format. We developed software to parse GDS-II IC layouts to generate a bitmap of regions of the chip that are filled with material such as metal, poly-silicon, etc. Such bitmaps are useful for analyzing the geometry of IC design and implementation. We developed the software in the Python programming language, reputed for use in rapid application development environments. Our experience developing and validating the application provides useful insights into the general methodology of iterative development, and the suitability of Python in non-traditional, rapid prototyping environments. Our experience shows that the choice of a versatile programming language can greatly improve productivity in a rapid application development environment where there is incomplete information at the outset
Weighted graph algorithms with Python
Get PDFPython implementation of selected weighted graph data structures and algorithms is presented. The minimal graph interface is defined together with several classes implementing this interface. Graph nodes can be any hashable Python objects. Directed edges are instances of the Edge class. Graphs are instances of the Graph class. It is based on the adjacency-list representation, but with fast lookup of nodes and neighbors (dict-of-dict structure). Other implementations of this class are also included, for instance, the adjacency matrix representation (list-of-list structure). Multigraphs are instances of the Multigraph class.In this work, many algorithms are implemented using a unified approach. There are separate classes and modules devoted to different algorithms. Three algorithms for finding a minimum spanning tree are implemented: the Boruvka's algorithm, the Prim's algorithm (three implementations), and the Kruskal's algorithm. Three algorithms for solving the single-source shortest path problem are implemented: the dag shortest path algorithm, the Bellman-Ford algorithm, and the Dijkstra's algorithm (two implementations). Two algorithms for solving all-pairs shortest path problem are implemented: the Floyd-Warshall algorithm and the Johnson's algorithm.All algorithms were tested by means of the unittest module, the Python unit testing framework. Additional computer experiments were done in order to compare real and theoretical computational complexity. The source code is available from the public GitHub graphs-dict repository
Bactome III: OLIgonucleotide Variable Expression Ranker (OLIVER) 1.0, Tool for Identifying Suitable Reference (Invariant) Genes from Large Microarray Datasets
Get PDFReference genes are crucial in gene expression analysis where varying gene expressions are reported as changes with respect to the expression of reference genes. Hence, reference genes are assumed to be stably expressed under most circumstances. Previous studies have shown that common algorithms for identifying of potential reference genes are not suitable for large microarray-sized datasets. Our previous work had derived methods for identification of reference genes from large microarray-sized datasets and the performances of these methods are linear to sample size. These methods had been implemented as a tool, OLIgonucleotide Variable Expression Ranker (OLIVER), which can be downloaded from http://sourceforge. net/projects/bactome/files/OLIVER/OLIVER_1.zip. This manuscript documents the implementation of OLIVER, which had been incorporated as part of Bactome project (http://www.sf.net/projects/bactome). These codes are licensed under GNU General Public License version 3 for academic and non-for-profit use
