Handling of Complex Nmnbers in the CH Progrannning Language
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Datatypes (Pdf Format)
Basic Scripting, Syntax, and Data Types in Python Mteor 227 – Fall 2020 Basic Shell Scripting/Programming with Python • Shell: a user interface for access to an operating system’s services. – The outer layer between the user and the operating system. • The first line in your program needs to be: #!/usr/bin/python • This line tells the computer what python interpreter to use. Comments • Comments in Python are indicated with a pound sign, #. • Any text following a # and the end of the line is ignored by the interpreter. • For multiple-line comments, a # must be used at the beginning of each line. Continuation Line • The \ character at the end of a line of Python code signifies that the next line is a continuation of the current line. Variable Names and Assignments • Valid characters for variable, function, module, and object names are any letter or number. The underscore character can also be used. • Numbers cannot be used as the first character. • The underscore should not be used as either the first or last character, unless you know what you are doing. – There are special rules concerning leading and trailing underscore characters. Variable Names and Assignments • Python is case sensitive! Capitalization matters. – The variable f is not the same as the variable F. • Python supports parallel assignment >>> a, b = 5, 'hi' >>> a 5 >>> b 'hi' Data Types • Examples of data types are integers, floating-point numbers, complex numbers, strings, etc. • Python uses dynamic typing, which means that the variable type is determined by its input. – The same variable name can be used as an integer at one point, and then if a string is assigned to it, it then becomes a string or character variable. -
Think Python
Think Python How to Think Like a Computer Scientist 2nd Edition, Version 2.2.18 Think Python How to Think Like a Computer Scientist 2nd Edition, Version 2.2.18 Allen Downey Green Tea Press Needham, Massachusetts Copyright © 2015 Allen Downey. Green Tea Press 9 Washburn Ave Needham MA 02492 Permission is granted to copy, distribute, and/or modify this document under the terms of the Creative Commons Attribution-NonCommercial 3.0 Unported License, which is available at http: //creativecommons.org/licenses/by-nc/3.0/. The original form of this book is LATEX source code. Compiling this LATEX source has the effect of gen- erating a device-independent representation of a textbook, which can be converted to other formats and printed. http://www.thinkpython2.com The LATEX source for this book is available from Preface The strange history of this book In January 1999 I was preparing to teach an introductory programming class in Java. I had taught it three times and I was getting frustrated. The failure rate in the class was too high and, even for students who succeeded, the overall level of achievement was too low. One of the problems I saw was the books. They were too big, with too much unnecessary detail about Java, and not enough high-level guidance about how to program. And they all suffered from the trap door effect: they would start out easy, proceed gradually, and then somewhere around Chapter 5 the bottom would fall out. The students would get too much new material, too fast, and I would spend the rest of the semester picking up the pieces. -
Natural Domain of a Function • Range Calculations Table of Contents (Continued)
~ THE UNIVERSITY OF AKRON w Mathematics and Computer Science calculus Article: Functions menu Directory • Table of Contents • Begin tutorial on Functions • Index Copyright c 1995{1998 D. P. Story Last Revision Date: 11/6/1998 Functions Table of Contents 1. Introduction 2. The Concept of a Function 2.1. Constructing Functions • The Use of Algebraic Expressions • Piecewise Definitions • Descriptive or Conceptual Methods 2.2. Evaluation Issues • Numerical Evaluation • Symbolic Evalulation 2.3. What's in a Name • The \Standard" Way • Functions Named by the Depen- dent Variable • Descriptive Naming • Famous Functions 2.4. Models for Functions • A Function as a Mapping • Venn Diagram of a Function • A Function as a Black Box 2.5. Calculating the Domain and Range • The Natural Domain of a Function • Range Calculations Table of Contents (continued) 2.6. Recognizing Functions • Interpreting the Terminology • The Vertical Line Test 3. Graphing: First Principles 4. Methods of Combining Functions 4.1. The Algebra of Functions 4.2. The Composition of Functions 4.3. Shifting and Rescaling • Horizontal Shifting • Vertical Shifting • Rescaling 5. Classification of Functions • Polynomial Functions • Rational Functions • Algebraic Functions 1. Introduction In the world of Mathematics one of the most common creatures en- countered is the function. It is important to understand the idea of a function if you want to gain a thorough understanding of Calculus. Science concerns itself with the discovery of physical or scientific truth. In a portion of these investigations, researchers (or engineers) attempt to discern relationships between physical quantities of interest. There are many ways of interpreting the meaning of the word \relation- ships," but in Calculus we are most often concerned with functional relationships. -
MPLAB C Compiler for PIC24 Mcus and Dspic Dscs User's Guide
MPLAB® C Compiler for PIC24 MCUs and dsPIC® DSCs User’s Guide 2002-2011 Microchip Technology Inc. DS51284K Note the following details of the code protection feature on Microchip devices: • Microchip products meet the specification contained in their particular Microchip Data Sheet. • Microchip believes that its family of products is one of the most secure families of its kind on the market today, when used in the intended manner and under normal conditions. • There are dishonest and possibly illegal methods used to breach the code protection feature. All of these methods, to our knowledge, require using the Microchip products in a manner outside the operating specifications contained in Microchip’s Data Sheets. Most likely, the person doing so is engaged in theft of intellectual property. • Microchip is willing to work with the customer who is concerned about the integrity of their code. • Neither Microchip nor any other semiconductor manufacturer can guarantee the security of their code. Code protection does not mean that we are guaranteeing the product as “unbreakable.” Code protection is constantly evolving. We at Microchip are committed to continuously improving the code protection features of our products. Attempts to break Microchip’s code protection feature may be a violation of the Digital Millennium Copyright Act. If such acts allow unauthorized access to your software or other copyrighted work, you may have a right to sue for relief under that Act. Information contained in this publication regarding device Trademarks applications and the like is provided only for your convenience The Microchip name and logo, the Microchip logo, dsPIC, and may be superseded by updates. -
False Dilemma Wikipedia Contents
False dilemma Wikipedia Contents 1 False dilemma 1 1.1 Examples ............................................... 1 1.1.1 Morton's fork ......................................... 1 1.1.2 False choice .......................................... 2 1.1.3 Black-and-white thinking ................................... 2 1.2 See also ................................................ 2 1.3 References ............................................... 3 1.4 External links ............................................. 3 2 Affirmative action 4 2.1 Origins ................................................. 4 2.2 Women ................................................ 4 2.3 Quotas ................................................. 5 2.4 National approaches .......................................... 5 2.4.1 Africa ............................................ 5 2.4.2 Asia .............................................. 7 2.4.3 Europe ............................................ 8 2.4.4 North America ........................................ 10 2.4.5 Oceania ............................................ 11 2.4.6 South America ........................................ 11 2.5 International organizations ...................................... 11 2.5.1 United Nations ........................................ 12 2.6 Support ................................................ 12 2.6.1 Polls .............................................. 12 2.7 Criticism ............................................... 12 2.7.1 Mismatching ......................................... 13 2.8 See also -
Pivotal Decompositions of Functions
PIVOTAL DECOMPOSITIONS OF FUNCTIONS JEAN-LUC MARICHAL AND BRUNO TEHEUX Abstract. We extend the well-known Shannon decomposition of Boolean functions to more general classes of functions. Such decompositions, which we call pivotal decompositions, express the fact that every unary section of a function only depends upon its values at two given elements. Pivotal decom- positions appear to hold for various function classes, such as the class of lattice polynomial functions or the class of multilinear polynomial functions. We also define function classes characterized by pivotal decompositions and function classes characterized by their unary members and investigate links between these two concepts. 1. Introduction A remarkable (though immediate) property of Boolean functions is the so-called Shannon decomposition, or Shannon expansion (see [20]), also called pivotal decom- position [2]. This property states that, for every Boolean function f : {0, 1}n → {0, 1} and every k ∈ [n]= {1,...,n}, the following decomposition formula holds: 1 0 n (1) f(x) = xk f(xk)+ xk f(xk) , x = (x1,...,xn) ∈{0, 1} , a where xk = 1 − xk and xk is the n-tuple whose i-th coordinate is a, if i = k, and xi, otherwise. Here the ‘+’ sign represents the classical addition for real numbers. Decomposition formula (1) means that we can precompute the function values for xk = 0 and xk = 1 and then select the appropriate value depending on the value of xk. By analogy with the cofactor expansion formula for determinants, here 1 0 f(xk) (resp. f(xk)) is called the cofactor of xk (resp. xk) for f and is derived by setting xk = 1 (resp. -
Functional C
Functional C Pieter Hartel Henk Muller January 3, 1999 i Functional C Pieter Hartel Henk Muller University of Southampton University of Bristol Revision: 6.7 ii To Marijke Pieter To my family and other sources of inspiration Henk Revision: 6.7 c 1995,1996 Pieter Hartel & Henk Muller, all rights reserved. Preface The Computer Science Departments of many universities teach a functional lan- guage as the first programming language. Using a functional language with its high level of abstraction helps to emphasize the principles of programming. Func- tional programming is only one of the paradigms with which a student should be acquainted. Imperative, Concurrent, Object-Oriented, and Logic programming are also important. Depending on the problem to be solved, one of the paradigms will be chosen as the most natural paradigm for that problem. This book is the course material to teach a second paradigm: imperative pro- gramming, using C as the programming language. The book has been written so that it builds on the knowledge that the students have acquired during their first course on functional programming, using SML. The prerequisite of this book is that the principles of programming are already understood; this book does not specifically aim to teach `problem solving' or `programming'. This book aims to: ¡ Familiarise the reader with imperative programming as another way of imple- menting programs. The aim is to preserve the programming style, that is, the programmer thinks functionally while implementing an imperative pro- gram. ¡ Provide understanding of the differences between functional and imperative pro- gramming. Functional programming is a high level activity. -
Notes on Functional Programming with Haskell
Notes on Functional Programming with Haskell H. Conrad Cunningham [email protected] Multiparadigm Software Architecture Group Department of Computer and Information Science University of Mississippi 201 Weir Hall University, Mississippi 38677 USA Fall Semester 2014 Copyright c 1994, 1995, 1997, 2003, 2007, 2010, 2014 by H. Conrad Cunningham Permission to copy and use this document for educational or research purposes of a non-commercial nature is hereby granted provided that this copyright notice is retained on all copies. All other rights are reserved by the author. H. Conrad Cunningham, D.Sc. Professor and Chair Department of Computer and Information Science University of Mississippi 201 Weir Hall University, Mississippi 38677 USA [email protected] PREFACE TO 1995 EDITION I wrote this set of lecture notes for use in the course Functional Programming (CSCI 555) that I teach in the Department of Computer and Information Science at the Uni- versity of Mississippi. The course is open to advanced undergraduates and beginning graduate students. The first version of these notes were written as a part of my preparation for the fall semester 1993 offering of the course. This version reflects some restructuring and revision done for the fall 1994 offering of the course|or after completion of the class. For these classes, I used the following resources: Textbook { Richard Bird and Philip Wadler. Introduction to Functional Program- ming, Prentice Hall International, 1988 [2]. These notes more or less cover the material from chapters 1 through 6 plus selected material from chapters 7 through 9. Software { Gofer interpreter version 2.30 (2.28 in 1993) written by Mark P. -
Software II: Principles of Programming Languages
Software II: Principles of Programming Languages Lecture 6 – Data Types Some Basic Definitions • A data type defines a collection of data objects and a set of predefined operations on those objects • A descriptor is the collection of the attributes of a variable • An object represents an instance of a user- defined (abstract data) type • One design issue for all data types: What operations are defined and how are they specified? Primitive Data Types • Almost all programming languages provide a set of primitive data types • Primitive data types: Those not defined in terms of other data types • Some primitive data types are merely reflections of the hardware • Others require only a little non-hardware support for their implementation The Integer Data Type • Almost always an exact reflection of the hardware so the mapping is trivial • There may be as many as eight different integer types in a language • Java’s signed integer sizes: byte , short , int , long The Floating Point Data Type • Model real numbers, but only as approximations • Languages for scientific use support at least two floating-point types (e.g., float and double ; sometimes more • Usually exactly like the hardware, but not always • IEEE Floating-Point Standard 754 Complex Data Type • Some languages support a complex type, e.g., C99, Fortran, and Python • Each value consists of two floats, the real part and the imaginary part • Literal form real component – (in Fortran: (7, 3) imaginary – (in Python): (7 + 3j) component The Decimal Data Type • For business applications (money) -
Vivado Design Suite User Guide: High-Level Synthesis (UG902)
Vivado Design Suite User Guide High-Level Synthesis UG902 (v2018.3) December 20, 2018 Revision History Revision History The following table shows the revision history for this document. Section Revision Summary 12/20/2018 Version 2018.3 Schedule Viewer Updated information on the schedule viewer. Optimizing the Design Clarified information on dataflow and loops throughout section. C++ Arbitrary Precision Fixed-Point Types: Reference Added note on using header files. Information HLS Math Library Updated information on how hls_math.h is used. The HLS Math Library, Fixed-Point Math Functions Updated functions. HLS Video Library, HLS Video Functions Library Moved the HLS video library to the Xilinx GitHub (https:// github.com/Xilinx/xfopencv) HLS SQL Library, HLS SQL Library Functions Updated hls::db to hls::alg functions. System Calls Added information on using the __SYNTHESIS__ macro. Arrays Added information on array sizing behavior. Command Reference Updated commands. config_dataflow, config_rtl Added the option -disable_start_propagation Class Methods, Operators, and Data Members Added guidance on specifying data width. UG902 (v2018.3) December 20, 2018Send Feedback www.xilinx.com High-Level Synthesis 2 Table of Contents Revision History...............................................................................................................2 Chapter 1: High-Level Synthesis............................................................................ 5 High-Level Synthesis Benefits....................................................................................................5 -
Should C Replace FORTRAN As the Language of Scientific Programming?
Should C Replace FORTRAN as the Language of Scientific Programming? Linda Wharton CSCI 5535 Fall 1995 Abstract Anti-FORTRAN sentiment has recently become more prevalent. Where does the attitude originate? The most probable source is academia, where C and C++ are the languages of choice. Is there a fact based justification for the attitude? FORTRAN and C are evaluated to determine whether C is a better language than FORTRAN for scientific programming. The features of FORTRAN 77, FORTRAN 90, C and C++ are compared, and evaluated as to how well they meet the requirements of the scientific programming domain. FORTRAN was designed specifically for numerical programming, and thus better meets the requirements. Three algorithms in the scientific domain are coded in both FORTRAN and C. They are evaluated on performance, readability of the code and optimization potential. In all cases the FORTRAN implementations proved superior. Is there evidence to mandate that all upgrades and new development should be done in C, rather than FORTRAN? A good computer programmer can solve any given problem in any language, however it is best to code in the language specifically designed for the problem domain. In the case of scientific programming, that language is FORTRAN. 1 Introduction In the computer arena related to scientific programming, a prevalent attitude seems to be that FORTRAN is obsolete, and C should be used as a replacement language. I am employed as a programmer that supports meteorological research. Most of the programming code I work with is written in FORTRAN. Within the course of my work, I continually encounter prejudice against FORTRAN. -
Stable/Src/Hdmf
HD HierarchicalM DataF Modeling Framework HDMF Release 3.1.1 Aug 13, 2021 Getting Started 1 Installing HDMF 3 1.1 Option 1: Using pip...........................................3 1.2 Option 2: Using conda..........................................3 2 Tutorials 5 2.1 DynamicTable Tutorial..........................................5 2.2 MultiContainerInterface.........................................9 2.3 AlignedDynamicTable.......................................... 13 2.4 ExternalResources............................................ 19 2.5 DynamicTable How-To Guide...................................... 24 3 Introduction 39 4 Software Architecture 41 4.1 Main Concepts.............................................. 44 4.2 Additional Concepts........................................... 46 5 Citing HDMF 49 5.1 BibTeX entry............................................... 49 5.2 Using RRID............................................... 49 5.3 Using duecredit.............................................. 49 6 API Documentation 51 6.1 hdmf.common package.......................................... 51 6.2 hdmf.container module.......................................... 73 6.3 hdmf.build package........................................... 76 6.4 hdmf.spec package............................................ 91 6.5 hdmf.backends package......................................... 108 6.6 hdmf.data_utils module......................................... 120 6.7 hdmf.utils module............................................ 124 6.8 hdmf.validate package.........................................