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Armadillo C++ Library
Armadillo: a template-based C++ library for linear algebra Conrad Sanderson and Ryan Curtin Abstract The C++ language is often used for implementing functionality that is performance and/or resource sensitive. While the standard C++ library provides many useful algorithms (such as sorting), in its current form it does not provide direct handling of linear algebra (matrix maths). Armadillo is an open source linear algebra library for the C++ language, aiming towards a good balance between speed and ease of use. Its high-level application programming interface (function syntax) is deliberately similar to the widely used Matlab and Octave languages [4], so that mathematical operations can be expressed in a familiar and natural manner. The library is useful for algorithm development directly in C++, or relatively quick conversion of research code into production environments. Armadillo provides efficient objects for vectors, matrices and cubes (third order tensors), as well as over 200 associated functions for manipulating data stored in the objects. Integer, floating point and complex numbers are supported, as well as dense and sparse storage formats. Various matrix factorisations are provided through integration with LAPACK [3], or one of its high performance drop-in replacements such as Intel MKL [6] or OpenBLAS [9]. It is also possible to use Armadillo in conjunction with NVBLAS to obtain GPU-accelerated matrix multiplication [7]. Armadillo is used as a base for other open source projects, such as MLPACK, a C++ library for machine learning and pattern recognition [2], and RcppArmadillo, a bridge between the R language and C++ in order to speed up computations [5]. -
A Polymorphic Type System for Extensible Records and Variants
A Polymorphic Typ e System for Extensible Records and Variants Benedict R. Gaster and Mark P. Jones Technical rep ort NOTTCS-TR-96-3, November 1996 Department of Computer Science, University of Nottingham, University Park, Nottingham NG7 2RD, England. fbrg,[email protected] Abstract b oard, and another indicating a mouse click at a par- ticular p oint on the screen: Records and variants provide exible ways to construct Event = Char + Point : datatyp es, but the restrictions imp osed by practical typ e systems can prevent them from b eing used in ex- These de nitions are adequate, but they are not par- ible ways. These limitations are often the result of con- ticularly easy to work with in practice. For example, it cerns ab out eciency or typ e inference, or of the di- is easy to confuse datatyp e comp onents when they are culty in providing accurate typ es for key op erations. accessed by their p osition within a pro duct or sum, and This pap er describ es a new typ e system that reme- programs written in this way can b e hard to maintain. dies these problems: it supp orts extensible records and To avoid these problems, many programming lan- variants, with a full complement of p olymorphic op era- guages allow the comp onents of pro ducts, and the al- tions on each; and it o ers an e ective type inference al- ternatives of sums, to b e identi ed using names drawn gorithm and a simple compilation metho d. -
J1939 Data Mapping Explained
J1939 Data Mapping Explained Part No. BW2031 Revision: 1.05 May 18, 2018 Pyramid Solutions, Inc. 30200 Telegraph Road, Suite 440 Bingham Farms, MI 48025 www.pyramidsolutions.com | P: 248.549.1200 | F: 248.549.1400 © Pyramid Solutions 1 PUB-BW4031-001 Table of Contents Overview ......................................................................................................................... 2 J1939 Message Terminology ............................................................................................ 2 J1939 PGN Message Definitions ....................................................................................... 3 PGN and Parameter Documentation Examples ........................................................................ 3 J1939 Specification Example ........................................................................................................ 3 Parameter Table Example ............................................................................................................ 5 Determining the BridgeWay Data Table Layout ................................................................ 6 Data Table Layout for Modbus RTU and Modbus TCP (Big Endian) ........................................... 6 Data Table Layout for EtherNet/IP (Little Endian) .................................................................... 7 Configuring the BridgeWay I/O Mapping ......................................................................... 8 Configuration Attributes ........................................................................................................ -
Advanced Software Engineering with C++ Templates Lecture 4: Separate Compilation and Templates III
Advanced Software Engineering with C++ Templates Lecture 4: Separate Compilation and Templates III Thomas Gschwind <thgatzurichdotibmdotcom> Agenda . Separate Compilation • Introduction (C++ versus Java) • Variables • Routines (Functions & Operators) • Types (Structures, Classes) • Makefiles . Templates III • Design and Implementation (C++ versus Java versus C#) • “Dynamic” Static Algorithm Selection • Binders Th. Gschwind. Fortgeschrittene Programmierung in C++. 2 Separate Compilation . Why? • Having only one source file is unrealistic • Break the code up into its logical structure • Reduction of compile time - Only changed parts need to be recompiled . How? • Use multiple source files • Need to know what information about functions and variables “used” from other files Th. Gschwind. Fortgeschrittene Programmierung in C++. 3 Separate Compilation in Java . Each Java file is compiled into a class file . If a Java class invokes a method of another class, the compiler consults that other class file to • Determine whether the class provides the requested method • Determine whether a class file implements a given interface • etc. • Hence, the .class file contains the entire interface . That’s why in Java, the compiler needs the class path . Finally, all class files are loaded by the Java Virtual Machine (and “linked”) . Java source code can be relatively well reconstructed from .class file (see Java Decompiler: jd, jad) Th. Gschwind. Fortgeschrittene Programmierung in C++. 4 Some Java Trivia . Let us write Hello World in Java . In order to simplify the reconfiguration (e.g., translation) • Put all the constants into one Java file • Put the complex application code into another public class Const { public static final String msg="Hello World!"; } public class Cool { public static void main(String[] args) { System.out.println(Const.msg); } } Th. -
P2356R0 Date 2021-04-09 Reply-To Matus Chochlik [email protected] Audience SG7 Overview Details
Overview Details Implementing Factory builder on top of P2320 Document Number P2356R0 Date 2021-04-09 Reply-to Matus Chochlik [email protected] Audience SG7 Overview Details The goal (Semi-)automate the implementation of the Factory design pattern Overview Details What is meant by \Factory" here? • Class that constructs instances of a \Product" type. • From some external representation: • XML, • JSON, • YAML, • a GUI, • a scripting language, • a relational database, • ... Overview Details Factory builder • Framework combining the following parts • Meta-data • obtained from reflection. • Traits • units of code that handle various stages of construction, • specific to a particular external representation, • provided by user. Overview Details Factory builder • Used meta-data • type name strings, • list of meta-objects reflecting constructors, • list of meta-objects reflecting constructor parameters, • parameter type, • parameter name, • ... Overview Details Factory builder • Units handling the stages of construction • selecting the \best" constructor, • invoking the selected constructor, • conversion of parameter values from the external representation, • may recursively use factories for composite parameter types. Overview Details Used reflection features • ^T • [: :]1 • meta::name_of • meta::type_of • meta::members_of • meta::is_constructor • meta::is_default_constructor • meta::is_move_constructor • meta::is_copy_constructor • meta::parameters_of • size(Range) • range iterators 1to get back the reflected type Overview Details Reflection review • The good2 • How extensive and powerful the API is • The bad • Didn't find much3 • The ugly • Some of the syntax4 2great actually! 3some details follow 4but then this is a matter of personal preference Overview Details What is missing • The ability to easily unpack meta-objects from a range into a template, without un-reflecting them. • I used the following workaround + make_index_sequence: template <typename Iterator > consteval auto advance(Iterator it, size_t n) { while (n-- > 0) { ++ it; } return it; } • Details follow. -
New Inheritance Models That Facilitate Source Code Reuse in Object-Oriented Programming
NEW INHERITANCE MODELS THAT FACILITATE SOURCE CODE REUSE IN OBJECT- ORIENTED PROGRAMMING By HISHAM M. AL-HADDAD Bachelor of Science Yarmouk University lrbid, Jordan 1986 Master of Science Northrop University Los Angeles, California 1988 Submitted to the Faculty of the Graduate College of the Oklahoma State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY July, 1992 Oklahoma Statt.' Ur1iv. Library NEW INHERITANCE MODELS THAT FACILITATE SOURCE CODE REUSE IN OBJECT- ORIENTED PROGRAMMING C/ wU::r-~ B I A~c;p .... _.-~ Dean of the Graduate CoUege ii PREFACE Code reusability is a primary objective in the development of software systems. The object-oriented programming methodology is one of the areas that facilitate the development of software systems by allowing and promoting code reuse and modular designs. Object-oriented programming languages (OOPLs) provide different facilities to attain efficient reuse and reliable extension of existing software components. Inheritance is an important language feature that is conducive to reusability and extensibility. Various OOPLs provide different inheritance models based on different interpretations of the inheritance notion. Therefore, OOPLs have different characteristics derived from their respective inheritance models. This dissertation is concerned with solutions for three major problems that limit the utilization of inheritance for code reusability. The range of object-oriented applications and thus the usage of object-oriented programming in general is also discussed. The three major problems are: 1) the relationship between inheritance and other related issues such as encapsulation, access techniques, visibility of inheritance, and subtyping; 2) the hierarchical structure imposed by inheritance among classes; and 3) the accessibility of previous versions of the modified methods defmed in classes located at higher levels of the inheritance structure than the parent classes. -
Abstract Data Types
Chapter 2 Abstract Data Types The second idea at the core of computer science, along with algorithms, is data. In a modern computer, data consists fundamentally of binary bits, but meaningful data is organized into primitive data types such as integer, real, and boolean and into more complex data structures such as arrays and binary trees. These data types and data structures always come along with associated operations that can be done on the data. For example, the 32-bit int data type is defined both by the fact that a value of type int consists of 32 binary bits but also by the fact that two int values can be added, subtracted, multiplied, compared, and so on. An array is defined both by the fact that it is a sequence of data items of the same basic type, but also by the fact that it is possible to directly access each of the positions in the list based on its numerical index. So the idea of a data type includes a specification of the possible values of that type together with the operations that can be performed on those values. An algorithm is an abstract idea, and a program is an implementation of an algorithm. Similarly, it is useful to be able to work with the abstract idea behind a data type or data structure, without getting bogged down in the implementation details. The abstraction in this case is called an \abstract data type." An abstract data type specifies the values of the type, but not how those values are represented as collections of bits, and it specifies operations on those values in terms of their inputs, outputs, and effects rather than as particular algorithms or program code. -
Scala Tutorial
Scala Tutorial SCALA TUTORIAL Simply Easy Learning by tutorialspoint.com tutorialspoint.com i ABOUT THE TUTORIAL Scala Tutorial Scala is a modern multi-paradigm programming language designed to express common programming patterns in a concise, elegant, and type-safe way. Scala has been created by Martin Odersky and he released the first version in 2003. Scala smoothly integrates features of object-oriented and functional languages. This tutorial gives a great understanding on Scala. Audience This tutorial has been prepared for the beginners to help them understand programming Language Scala in simple and easy steps. After completing this tutorial, you will find yourself at a moderate level of expertise in using Scala from where you can take yourself to next levels. Prerequisites Scala Programming is based on Java, so if you are aware of Java syntax, then it's pretty easy to learn Scala. Further if you do not have expertise in Java but you know any other programming language like C, C++ or Python, then it will also help in grasping Scala concepts very quickly. Copyright & Disclaimer Notice All the content and graphics on this tutorial are the property of tutorialspoint.com. Any content from tutorialspoint.com or this tutorial may not be redistributed or reproduced in any way, shape, or form without the written permission of tutorialspoint.com. Failure to do so is a violation of copyright laws. This tutorial may contain inaccuracies or errors and tutorialspoint provides no guarantee regarding the accuracy of the site or its contents including this tutorial. If you discover that the tutorialspoint.com site or this tutorial content contains some errors, please contact us at [email protected] TUTORIALS POINT Simply Easy Learning Table of Content Scala Tutorial .......................................................................... -
5. Data Types
IEEE FOR THE FUNCTIONAL VERIFICATION LANGUAGE e Std 1647-2011 5. Data types The e language has a number of predefined data types, including the integer and Boolean scalar types common to most programming languages. In addition, new scalar data types (enumerated types) that are appropriate for programming, modeling hardware, and interfacing with hardware simulators can be created. The e language also provides a powerful mechanism for defining OO hierarchical data structures (structs) and ordered collections of elements of the same type (lists). The following subclauses provide a basic explanation of e data types. 5.1 e data types Most e expressions have an explicit data type, as follows: — Scalar types — Scalar subtypes — Enumerated scalar types — Casting of enumerated types in comparisons — Struct types — Struct subtypes — Referencing fields in when constructs — List types — The set type — The string type — The real type — The external_pointer type — The “untyped” pseudo type Certain expressions, such as HDL objects, have no explicit data type. See 5.2 for information on how these expressions are handled. 5.1.1 Scalar types Scalar types in e are one of the following: numeric, Boolean, or enumerated. Table 17 shows the predefined numeric and Boolean types. Both signed and unsigned integers can be of any size and, thus, of any range. See 5.1.2 for information on how to specify the size and range of a scalar field or variable explicitly. See also Clause 4. 5.1.2 Scalar subtypes A scalar subtype can be named and created by using a scalar modifier to specify the range or bit width of a scalar type. -
Lecture 2: Variables and Primitive Data Types
Lecture 2: Variables and Primitive Data Types MIT-AITI Kenya 2005 1 In this lecture, you will learn… • What a variable is – Types of variables – Naming of variables – Variable assignment • What a primitive data type is • Other data types (ex. String) MIT-Africa Internet Technology Initiative 2 ©2005 What is a Variable? • In basic algebra, variables are symbols that can represent values in formulas. • For example the variable x in the formula f(x)=x2+2 can represent any number value. • Similarly, variables in computer program are symbols for arbitrary data. MIT-Africa Internet Technology Initiative 3 ©2005 A Variable Analogy • Think of variables as an empty box that you can put values in. • We can label the box with a name like “Box X” and re-use it many times. • Can perform tasks on the box without caring about what’s inside: – “Move Box X to Shelf A” – “Put item Z in box” – “Open Box X” – “Remove contents from Box X” MIT-Africa Internet Technology Initiative 4 ©2005 Variables Types in Java • Variables in Java have a type. • The type defines what kinds of values a variable is allowed to store. • Think of a variable’s type as the size or shape of the empty box. • The variable x in f(x)=x2+2 is implicitly a number. • If x is a symbol representing the word “Fish”, the formula doesn’t make sense. MIT-Africa Internet Technology Initiative 5 ©2005 Java Types • Integer Types: – int: Most numbers you’ll deal with. – long: Big integers; science, finance, computing. – short: Small integers. -
Csci 658-01: Software Language Engineering Python 3 Reflexive
CSci 658-01: Software Language Engineering Python 3 Reflexive Metaprogramming Chapter 3 H. Conrad Cunningham 4 May 2018 Contents 3 Decorators and Metaclasses 2 3.1 Basic Function-Level Debugging . .2 3.1.1 Motivating example . .2 3.1.2 Abstraction Principle, staying DRY . .3 3.1.3 Function decorators . .3 3.1.4 Constructing a debug decorator . .4 3.1.5 Using the debug decorator . .6 3.1.6 Case study review . .7 3.1.7 Variations . .7 3.1.7.1 Logging . .7 3.1.7.2 Optional disable . .8 3.2 Extended Function-Level Debugging . .8 3.2.1 Motivating example . .8 3.2.2 Decorators with arguments . .9 3.2.3 Prefix decorator . .9 3.2.4 Reformulated prefix decorator . 10 3.3 Class-Level Debugging . 12 3.3.1 Motivating example . 12 3.3.2 Class-level debugger . 12 3.3.3 Variation: Attribute access debugging . 14 3.4 Class Hierarchy Debugging . 16 3.4.1 Motivating example . 16 3.4.2 Review of objects and types . 17 3.4.3 Class definition process . 18 3.4.4 Changing the metaclass . 20 3.4.5 Debugging using a metaclass . 21 3.4.6 Why metaclasses? . 22 3.5 Chapter Summary . 23 1 3.6 Exercises . 23 3.7 Acknowledgements . 23 3.8 References . 24 3.9 Terms and Concepts . 24 Copyright (C) 2018, H. Conrad Cunningham Professor of Computer and Information Science University of Mississippi 211 Weir Hall P.O. Box 1848 University, MS 38677 (662) 915-5358 Note: This chapter adapts David Beazley’s debugly example presentation from his Python 3 Metaprogramming tutorial at PyCon’2013 [Beazley 2013a]. -
Metaclasses: Generative C++
Metaclasses: Generative C++ Document Number: P0707 R3 Date: 2018-02-11 Reply-to: Herb Sutter ([email protected]) Audience: SG7, EWG Contents 1 Overview .............................................................................................................................................................2 2 Language: Metaclasses .......................................................................................................................................7 3 Library: Example metaclasses .......................................................................................................................... 18 4 Applying metaclasses: Qt moc and C++/WinRT .............................................................................................. 35 5 Alternatives for sourcedefinition transform syntax .................................................................................... 41 6 Alternatives for applying the transform .......................................................................................................... 43 7 FAQs ................................................................................................................................................................. 46 8 Revision history ............................................................................................................................................... 51 Major changes in R3: Switched to function-style declaration syntax per SG7 direction in Albuquerque (old: $class M new: constexpr void M(meta::type target,