This document discusses data structures and abstract data types. It covers one-dimensional and multi-dimensional arrays in C++. Arrays allow storing a collection of elements of the same type that can be accessed via an index. The document provides examples of declaring, initializing, accessing, and passing arrays. It also discusses how arrays are stored contiguously in memory. Multidimensional arrays generalize this to store elements accessed by multiple indices.
Below are the lists of available Webi 3.1 report functions and will describe each & every functions along with example. Webi 4.0 reports are also having some functions with some additional futures.
The Ring programming language version 1.5.2 book - Part 34 of 181Mahmoud Samir Fayed
This document provides documentation on various functions available in the Ring standard library (stdlib) for tasks like string manipulation, mathematical operations, date/time functions, and more. It describes the syntax and examples of usage for over 40 functions, including endsWith(), gcd(), sumlist(), factors(), binarydigits(), and ListAllFiles(). The functions cover a wide range of common use cases and data types like strings, lists, matrices, files.
Crushing the Head of the Snake by Robert Brewer PyData SV 2014PyData
Big Data brings with it particular challenges in any language, mostly in performance. This talk will explain how to get immediate speedups in your Python code by exploiting both timeless programming techniques and fixes specific to Python. We will cover: I. Amongst Our Weaponry 1. How to Time and Profile Python 2. Extracting Loop invariants: constants, lookup tables, even methods! 3. Caching: memoization and heavier things II Gunfight at the O.K. Corral in Morse Code 1. Python functions vs C functions 2. Vector operations: NumPy 3. Reducing calls: loops, generators, recursion III. The Semaphore Version of Wuthering Heights 1. Using select instead of Queue 2. Serialization overhead 3. Parallelizing work
Martin Fowler's Refactoring Techniques Quick ReferenceSeung-Bum Lee
The document discusses various refactoring techniques for restructuring code to improve design, readability, and extensibility without changing external behavior. It provides examples of techniques like extracting methods, replacing temporary variables, simplifying conditional expressions, and dealing with generalization through inheritance/polymorphism. The techniques are organized into categories like composing methods, organizing data, simplifying method calls, and dealing with generalization.
Python lambda functions with filter, map & reduce functionARVIND PANDE
Lambda functions allow the creation of small anonymous functions and can be passed as arguments to other functions. The map() function applies a lambda function to each element of a list and returns a new list. The filter() function filters a list based on the return value of a lambda function. The reduce() function iteratively applies a lambda function to consecutive pairs in a list and returns a single value. User-defined functions in Python can perform tasks like converting between temperature scales, finding max/min/average of lists, generating Fibonacci series, reversing strings, summing digits in numbers, and calculating powers using recursion.
This document provides an overview of basic data structures in Python including stacks, queues, deques, and linked lists. It describes each data structure as an abstract data type with common operations. Implementations of each data structure are provided using Python classes. The stack, queue, and deque classes implement the respective data structures using Python lists. The linked list class implements nodes to link elements and allow for traversal. Examples are given demonstrating usage of each data structure implementation.
Dynamic memory allocation involves allocating memory at runtime using functions like malloc(), calloc(), and realloc(). Malloc() allocates a block of memory of a specified size and returns a pointer to it. Calloc() allocates memory for an array and initializes it to zero. Realloc() changes the size of a previously allocated memory block. The examples demonstrate allocating 2D arrays dynamically and performing operations like transpose and multiplication on them before freeing the allocated memory.
Spark 4th Meetup Londond - Building a Product with Sparksamthemonad
This document discusses common technical problems encountered when building products with Spark and provides solutions. It covers Spark exceptions like out of memory errors and shuffle file problems. It recommends increasing partitions and memory configurations. The document also discusses optimizing Spark code using functional programming principles like strong and weak pipelining, and leveraging monoid structures to reduce shuffling. Overall it provides tips to debug issues, optimize performance, and productize Spark applications.
Below are the lists of available Webi 3.1 report functions and will describe each & every functions along with example. Webi 4.0 reports are also having some functions with some additional futures.
The Ring programming language version 1.5.2 book - Part 34 of 181Mahmoud Samir Fayed
This document provides documentation on various functions available in the Ring standard library (stdlib) for tasks like string manipulation, mathematical operations, date/time functions, and more. It describes the syntax and examples of usage for over 40 functions, including endsWith(), gcd(), sumlist(), factors(), binarydigits(), and ListAllFiles(). The functions cover a wide range of common use cases and data types like strings, lists, matrices, files.
Crushing the Head of the Snake by Robert Brewer PyData SV 2014PyData
Big Data brings with it particular challenges in any language, mostly in performance. This talk will explain how to get immediate speedups in your Python code by exploiting both timeless programming techniques and fixes specific to Python. We will cover: I. Amongst Our Weaponry 1. How to Time and Profile Python 2. Extracting Loop invariants: constants, lookup tables, even methods! 3. Caching: memoization and heavier things II Gunfight at the O.K. Corral in Morse Code 1. Python functions vs C functions 2. Vector operations: NumPy 3. Reducing calls: loops, generators, recursion III. The Semaphore Version of Wuthering Heights 1. Using select instead of Queue 2. Serialization overhead 3. Parallelizing work
Martin Fowler's Refactoring Techniques Quick ReferenceSeung-Bum Lee
The document discusses various refactoring techniques for restructuring code to improve design, readability, and extensibility without changing external behavior. It provides examples of techniques like extracting methods, replacing temporary variables, simplifying conditional expressions, and dealing with generalization through inheritance/polymorphism. The techniques are organized into categories like composing methods, organizing data, simplifying method calls, and dealing with generalization.
Python lambda functions with filter, map & reduce functionARVIND PANDE
Lambda functions allow the creation of small anonymous functions and can be passed as arguments to other functions. The map() function applies a lambda function to each element of a list and returns a new list. The filter() function filters a list based on the return value of a lambda function. The reduce() function iteratively applies a lambda function to consecutive pairs in a list and returns a single value. User-defined functions in Python can perform tasks like converting between temperature scales, finding max/min/average of lists, generating Fibonacci series, reversing strings, summing digits in numbers, and calculating powers using recursion.
This document provides an overview of basic data structures in Python including stacks, queues, deques, and linked lists. It describes each data structure as an abstract data type with common operations. Implementations of each data structure are provided using Python classes. The stack, queue, and deque classes implement the respective data structures using Python lists. The linked list class implements nodes to link elements and allow for traversal. Examples are given demonstrating usage of each data structure implementation.
Dynamic memory allocation involves allocating memory at runtime using functions like malloc(), calloc(), and realloc(). Malloc() allocates a block of memory of a specified size and returns a pointer to it. Calloc() allocates memory for an array and initializes it to zero. Realloc() changes the size of a previously allocated memory block. The examples demonstrate allocating 2D arrays dynamically and performing operations like transpose and multiplication on them before freeing the allocated memory.
Spark 4th Meetup Londond - Building a Product with Sparksamthemonad
This document discusses common technical problems encountered when building products with Spark and provides solutions. It covers Spark exceptions like out of memory errors and shuffle file problems. It recommends increasing partitions and memory configurations. The document also discusses optimizing Spark code using functional programming principles like strong and weak pipelining, and leveraging monoid structures to reduce shuffling. Overall it provides tips to debug issues, optimize performance, and productize Spark applications.
The Ring programming language version 1.10 book - Part 45 of 212Mahmoud Samir Fayed
The document provides documentation on various functions available in the Ring programming language. It describes functions for string manipulation like TrimLeft(), TrimRight(), functions for file and directory operations like ListAllFiles(), OSCopyFile(), OSDeleteFolder(), functions for executing system commands like SystemCmd(), SystemSilent(), and functions for date/time, math, lists, and more. Syntax and examples are provided for many of the functions.
The Ring programming language version 1.5.3 book - Part 35 of 184Mahmoud Samir Fayed
The document provides documentation on various functions available in the Ring programming language standard library (stdlib). It describes functions for generating permutations, reading lines from a file, finding substrings, changing substrings, sleeping, checking if a file is the main source file, checking if a directory exists, making directories, getting file sizes, trimming strings, getting the epoch time, executing system commands, listing all files in a folder, and more. It also provides details on classes in the stdlib like the String, List, Stack, Queue, HashTable, Tree, Math, DateTime, File, and other classes along with their methods.
Simple, fast, and scalable torch7 tutorialJin-Hwa Kim
A tutorial based on basic information of Torch7. It covers installation, simple runable codes, tensor manipulations, sweep out key-packages and post-hoc audience q&a.
How to make hash functions go fast inside snarks, aka a guided tour through arithmetisation friendly hash functions (useful for all cryptographic protocols where cost is dominated by multiplications -- e.g. anything using R1CS; secret sharing based multiparty computation protocols; etc)
The Ring programming language version 1.5.3 book - Part 23 of 184Mahmoud Samir Fayed
The document discusses various string and date/time functions in Ring programming language. It describes how to create and manipulate strings, get string length, convert case, access characters, trim strings, compare strings, and convert between strings and lists. It also explains functions to work with dates and times, like getting the current date/time, adding/subtracting days, and converting between dates and epoch seconds.
How To Crack RSA Netrek Binary Verification SystemJay Corrales
The document describes how to crack the RSA encryption used in the Netrek binary verification system. It explains the RSA algorithm, gives an example, and then describes how to factor the public key to obtain the private key. It provides code to factor the global key for a specific Netrek server, modify an RSA key generation program to use the known private factors, and generate custom key files that can be used to bypass the verification check.
Arrays in Python can be used to store collections of homogeneous data elements. There are two main ways to work with arrays in Python: using the array module or using NumPy. The array module allows users to create arrays of basic data types like integers while NumPy provides a more powerful N-dimensional array object and tools for scientific computing. Both support common array operations like accessing elements, slicing, concatenation, and more. NumPy arrays can also represent matrices and support linear algebra operations.
The document contains summaries of code snippets and explanations of technical concepts. It discusses:
1) How a code snippet with post-increment operator i++ would output a garbage value.
2) Why a code snippet multiplying two ints and storing in a long int variable would not give the desired output.
3) Why a code snippet attempting to concatenate a character to a string would not work.
4) How to determine the maximum number of elements an array can hold based on its data type and memory model.
5) How to read data from specific memory locations using the peekb() function in C.
Scientific Computing with Python - NumPy | WeiYuanWei-Yuan Chang
This document provides an overview of NumPy, the fundamental package for scientific computing in Python. It discusses NumPy's powerful N-dimensional array object and sophisticated broadcasting functions. The document outlines topics including Ndarray, creating and manipulating arrays, array properties, basic operations, matrices, and advanced usages like boolean indexing and masking. NumPy allows efficient storage and manipulation of multi-dimensional data, and integration with languages like C/C++ and Fortran.
Python- Creating Dictionary,
Accessing and Modifying key: value Pairs in Dictionaries
Built-In Functions used on Dictionaries,
Dictionary Methods
Removing items from dictionary
The Ring programming language version 1.8 book - Part 94 of 202Mahmoud Samir Fayed
This document provides code examples for common GUI tasks in Ring using the Qt library:
1. It shows how to close a window and display another by connecting a button's click event to call the close() method on the first window and show() on the second.
2. It demonstrates how to create a modal window in Ring/Qt by setting the window modality to true and parent to the main window.
3. Methods like setWindowFlags() and removing the maximize flag can disable resizing and maximize buttons on a window.
Google interviewer asked for an algorithm to extract the k smallest elements from a set of ordered arrays. I suggested a vectorised bucket sort and merge sort approach. I took the problem offline and produced this analysis and C++.
This document provides an overview of basic commands and functions for constructing, sending, receiving, and analyzing packets using Scapy. It summarizes key Scapy commands for listing available protocols and functions, configuring parameters, building packets by specifying addresses, ports, and layer values, sending and receiving packets on different interfaces, capturing live packets, and fuzzing packet fields. The document is a quick reference for common Scapy tasks.
This week, Luke Pearson (Polychain Capital) and Joshua Fitzgerald (Anoma) present their work on Plonkup, a protocol that combines Plookup and PLONK into a single, efficient protocol. The protocol relies on a new hash function, called Reinforced Concrete, written by Dmitry Khovratovich. The three of them will present their work together at this week's edition of zkStudyClub!
Slides:
---
To Follow the Zero Knowledge Podcast us at https://www.zeroknowledge.fm
To the listeners of Zero Knowledge Podcast, if you like what we do:
- Follow us on Twitter - @zeroknowledgefm
- Join us on Telegram - https://t.me/joinchat/TORo7aknkYNLHmCM
- Support our Gitcoin Grant - https://gitcoin.co/grants/329/zero-knowledge-podcast-2
- Support us on Patreon - https://www.patreon.com/zeroknowledge
This document discusses functions in C++. It covers:
- The definition of a function as a subprogram that can act on data and return a value.
- Functions come in two varieties: user-defined and built-in.
- Functions must be declared before use with a prototype specifying the return type and parameters.
- A function is defined by providing the body of code that performs the task.
- Functions can interact through calls where parameters are passed by value or by reference.
The document discusses functions in Python. It describes built-in functions like input(), print(), and eval(). It also discusses user-defined functions, including defining functions with parameters, return values, and different scopes. Functions can take arbitrary arguments and keyword arguments. Additionally, the document discusses calling functions from the command line and passing arguments.
This document discusses role models and provides examples of positive role models from New Zealand and other countries that could inspire students. It notes that role models can motivate students to work and study for the future or limit their potential. The document also notes some differences in role models between Maori and Pakeha families in New Zealand, with Maori families often able to trace ancestry back further.
El informe presenta los resultados académicos del tercer periodo de 32 estudiantes de octavo grado. Incluye sus nombres, las notas de cada uno de los cuatro periodos evaluados, el promedio de notas y el promedio general del grado. La mayoría de estudiantes obtuvieron un promedio entre 2.9 y 4.1, con algunos destacándose por encima de 4.5.
The Ring programming language version 1.10 book - Part 45 of 212Mahmoud Samir Fayed
The document provides documentation on various functions available in the Ring programming language. It describes functions for string manipulation like TrimLeft(), TrimRight(), functions for file and directory operations like ListAllFiles(), OSCopyFile(), OSDeleteFolder(), functions for executing system commands like SystemCmd(), SystemSilent(), and functions for date/time, math, lists, and more. Syntax and examples are provided for many of the functions.
The Ring programming language version 1.5.3 book - Part 35 of 184Mahmoud Samir Fayed
The document provides documentation on various functions available in the Ring programming language standard library (stdlib). It describes functions for generating permutations, reading lines from a file, finding substrings, changing substrings, sleeping, checking if a file is the main source file, checking if a directory exists, making directories, getting file sizes, trimming strings, getting the epoch time, executing system commands, listing all files in a folder, and more. It also provides details on classes in the stdlib like the String, List, Stack, Queue, HashTable, Tree, Math, DateTime, File, and other classes along with their methods.
Simple, fast, and scalable torch7 tutorialJin-Hwa Kim
A tutorial based on basic information of Torch7. It covers installation, simple runable codes, tensor manipulations, sweep out key-packages and post-hoc audience q&a.
How to make hash functions go fast inside snarks, aka a guided tour through arithmetisation friendly hash functions (useful for all cryptographic protocols where cost is dominated by multiplications -- e.g. anything using R1CS; secret sharing based multiparty computation protocols; etc)
The Ring programming language version 1.5.3 book - Part 23 of 184Mahmoud Samir Fayed
The document discusses various string and date/time functions in Ring programming language. It describes how to create and manipulate strings, get string length, convert case, access characters, trim strings, compare strings, and convert between strings and lists. It also explains functions to work with dates and times, like getting the current date/time, adding/subtracting days, and converting between dates and epoch seconds.
How To Crack RSA Netrek Binary Verification SystemJay Corrales
The document describes how to crack the RSA encryption used in the Netrek binary verification system. It explains the RSA algorithm, gives an example, and then describes how to factor the public key to obtain the private key. It provides code to factor the global key for a specific Netrek server, modify an RSA key generation program to use the known private factors, and generate custom key files that can be used to bypass the verification check.
Arrays in Python can be used to store collections of homogeneous data elements. There are two main ways to work with arrays in Python: using the array module or using NumPy. The array module allows users to create arrays of basic data types like integers while NumPy provides a more powerful N-dimensional array object and tools for scientific computing. Both support common array operations like accessing elements, slicing, concatenation, and more. NumPy arrays can also represent matrices and support linear algebra operations.
The document contains summaries of code snippets and explanations of technical concepts. It discusses:
1) How a code snippet with post-increment operator i++ would output a garbage value.
2) Why a code snippet multiplying two ints and storing in a long int variable would not give the desired output.
3) Why a code snippet attempting to concatenate a character to a string would not work.
4) How to determine the maximum number of elements an array can hold based on its data type and memory model.
5) How to read data from specific memory locations using the peekb() function in C.
Scientific Computing with Python - NumPy | WeiYuanWei-Yuan Chang
This document provides an overview of NumPy, the fundamental package for scientific computing in Python. It discusses NumPy's powerful N-dimensional array object and sophisticated broadcasting functions. The document outlines topics including Ndarray, creating and manipulating arrays, array properties, basic operations, matrices, and advanced usages like boolean indexing and masking. NumPy allows efficient storage and manipulation of multi-dimensional data, and integration with languages like C/C++ and Fortran.
Python- Creating Dictionary,
Accessing and Modifying key: value Pairs in Dictionaries
Built-In Functions used on Dictionaries,
Dictionary Methods
Removing items from dictionary
The Ring programming language version 1.8 book - Part 94 of 202Mahmoud Samir Fayed
This document provides code examples for common GUI tasks in Ring using the Qt library:
1. It shows how to close a window and display another by connecting a button's click event to call the close() method on the first window and show() on the second.
2. It demonstrates how to create a modal window in Ring/Qt by setting the window modality to true and parent to the main window.
3. Methods like setWindowFlags() and removing the maximize flag can disable resizing and maximize buttons on a window.
Google interviewer asked for an algorithm to extract the k smallest elements from a set of ordered arrays. I suggested a vectorised bucket sort and merge sort approach. I took the problem offline and produced this analysis and C++.
This document provides an overview of basic commands and functions for constructing, sending, receiving, and analyzing packets using Scapy. It summarizes key Scapy commands for listing available protocols and functions, configuring parameters, building packets by specifying addresses, ports, and layer values, sending and receiving packets on different interfaces, capturing live packets, and fuzzing packet fields. The document is a quick reference for common Scapy tasks.
This week, Luke Pearson (Polychain Capital) and Joshua Fitzgerald (Anoma) present their work on Plonkup, a protocol that combines Plookup and PLONK into a single, efficient protocol. The protocol relies on a new hash function, called Reinforced Concrete, written by Dmitry Khovratovich. The three of them will present their work together at this week's edition of zkStudyClub!
Slides:
---
To Follow the Zero Knowledge Podcast us at https://www.zeroknowledge.fm
To the listeners of Zero Knowledge Podcast, if you like what we do:
- Follow us on Twitter - @zeroknowledgefm
- Join us on Telegram - https://t.me/joinchat/TORo7aknkYNLHmCM
- Support our Gitcoin Grant - https://gitcoin.co/grants/329/zero-knowledge-podcast-2
- Support us on Patreon - https://www.patreon.com/zeroknowledge
This document discusses functions in C++. It covers:
- The definition of a function as a subprogram that can act on data and return a value.
- Functions come in two varieties: user-defined and built-in.
- Functions must be declared before use with a prototype specifying the return type and parameters.
- A function is defined by providing the body of code that performs the task.
- Functions can interact through calls where parameters are passed by value or by reference.
The document discusses functions in Python. It describes built-in functions like input(), print(), and eval(). It also discusses user-defined functions, including defining functions with parameters, return values, and different scopes. Functions can take arbitrary arguments and keyword arguments. Additionally, the document discusses calling functions from the command line and passing arguments.
This document discusses role models and provides examples of positive role models from New Zealand and other countries that could inspire students. It notes that role models can motivate students to work and study for the future or limit their potential. The document also notes some differences in role models between Maori and Pakeha families in New Zealand, with Maori families often able to trace ancestry back further.
El informe presenta los resultados académicos del tercer periodo de 32 estudiantes de octavo grado. Incluye sus nombres, las notas de cada uno de los cuatro periodos evaluados, el promedio de notas y el promedio general del grado. La mayoría de estudiantes obtuvieron un promedio entre 2.9 y 4.1, con algunos destacándose por encima de 4.5.
Este documento proporciona instrucciones en 4 pasos para construir una casa de cartón. Primero, se trazan las medidas de las piezas de cartón necesarias como paredes, techo y suelo. Luego, se recortan las piezas y se asegura que encajen. Después, se barniza la casa para protegerla y se pinta de colores. Por último, se añade iluminación básica con un circuito eléctrico de cable, pila, interruptor y bombilla.
This document discusses strategies for optimizing search engine results for time-sensitive queries around holidays. It uses a case study of optimizing for Father's Day searches on Google to illustrate how search engine result pages (SERPs) change over time as the holiday approaches and passes. Key factors that can affect SERP placement include knowledge graphs, news listings, image optimization, and in-depth article content. The document also provides recommendations for identifying peak search times for holidays and creating relevant content to target those periods in order to achieve high SERP rankings.
Back-analysis of the collapse of a metal truss structureFranco Bontempi
This paper is organized in two parts. The first one describes a case history of few collapses of metal truss structures designed to be used as entertainment structures for which the structural safety gains therefore much more importance due to the people that can be involved in the collapse. In the second part, a specific case of the collapse of an entertainment structure made by aluminum is taken under study. A back analysis of the collapse of this metal truss structure is developed and produces a flowchart that points out the possible causes that led the structure to the collapse. By means of non linear analyses by Finite Element Model (FEM) the failure sequence of this particular structure is shown and forensic investigation concerning the whole phase of the construction phase is performed, starting from the design one, through the assembling and ending with the rigging phase.
The document analyzes marketing strategies of selected travel agents in Ludhiana, India. It finds that Thomas Cook and SOTC are the most preferred brands, competing on both quality and price while Pan Express competes primarily on price. Customer surveys found that while online travel has grown, most people in Ludhiana still prefer visiting travel agents to plan trips. Thomas Cook and SOTC were found to have the leading and most stable market positions over the past 5 years.
Dokumen ini membahas tentang tiga teknik utama dari pemrograman berorientasi objek yaitu enkapsulasi, inheritance, dan polymorphism. Enkapsulasi berfungsi untuk mengisolasi data dan instruksi untuk memanipulasi data tersebut ke dalam objek. Inheritance dan polymorphism memungkinkan pembentukan hierarki kelas dan pendefinisian kembali metode kelas. Visual Basic tidak sepenuhnya dapat memanfaatkan fitur-fitur pemrograman berorientasi objek.
CTA 2013 Robustezza Strutturale e Resilienza di Sistemi Strutturali e Infrast...Franco Bontempi
1. The document discusses the concepts of structural robustness and resilience for structural and infrastructure systems.
2. It examines attributes like reliability, availability, safety, and integrity and threats like failure, error, and faults that can impact system performance.
3. The document presents approaches for improving dependability, including fault tolerant design, fault detection and diagnosis, and structural health monitoring to assess damage and remaining capacity.
The document provides guidelines for youth participation and chaperoning at an American Cancer Society Relay For Life event. It requires one chaperone over age 25 for every five youth team members under age 18. Both youth participants and chaperones must complete registration forms and agree to guidelines regarding behavior, safety, respecting others, and not using alcohol or drugs at the event. Disciplinary actions for violations may include being sent home or barred from future activities.
The document discusses best practices for email marketing. It recommends determining the purpose and objective of the email, crafting the subject line and content to match expectations and optimize delivery and results. It also suggests targeting the right audience at the right time, testing elements, and ensuring the user experience is simple, direct and smooth. The overall message is to send targeted, relevant, timely communications that deliver on promises to get email marketing right.
The document provides a step-by-step guide to using social media marketing to generate profits. It discusses setting up profiles and pages on Facebook, Twitter, YouTube, MySpace, and Digg to build a large fan base and drive traffic to one's website. Specific tips are given for each platform on content to share, ways to interact, and how to promote one's brand and business. The goal is to build relationships and a targeted audience first before promoting products or services.
The document discusses data structures and abstract data types, specifically arrays. It defines arrays as structured data types that store a collection of elements of the same type that can be accessed by their position. It describes how arrays are implemented in C++ using static allocation, with elements accessed using an index. It provides examples of declaring, initializing, accessing, and passing arrays to functions.
The document discusses data structures and abstract data types. It introduces arrays as a data structure and abstract data type. Arrays allow storing a collection of data elements of the same type that can be accessed via an index. The document covers declaring, initializing, accessing, and passing single-dimensional arrays to functions in C++. It also briefly mentions multidimensional arrays.
The document discusses data structures and abstract data types, specifically arrays. It defines arrays as structured data types that store a collection of elements of the same type that can be accessed by their position. It provides examples of declaring and initializing single-dimensional arrays in C++ and passing arrays as arguments to functions. It also briefly discusses multidimensional arrays.
This document provides information on arrays, structures, and pointers in C++. It defines an array as a collection of data storage locations that hold the same type of data. Arrays can be one-dimensional or multi-dimensional. Structures are collections of variables of different data types grouped together under a single name. Pointers are variables that store the address of another variable in memory. Pointers can be used to access elements in an array using pointer arithmetic and to dynamically allocate memory using operators like new and delete.
Classes allow programmers to create new types that model real-world objects. A class defines both data attributes and built-in operations that can operate on that data. C++ provides built-in classes like string and iostream that add powerful functionality to the language. The string class allows easy storage and manipulation of strings, while the iostream classes (istream and ostream) define objects like cin and cout for input/output. These classes provide many useful built-in operations that make input/output powerful yet easy to use.
The document discusses arrays in C++. It explains one-dimensional and two-dimensional arrays, how to declare, initialize, and access elements of arrays. Key points include arrays storing a collection of like-typed data, being indexed starting from 0, initializing during declaration, and accessing two-dimensional array elements requiring row and column indices. Examples are provided to demonstrate array concepts.
- Arrays allow storing multiple values of the same type sequentially in memory. They have a fixed size or dimension.
- To declare an integer array of size 4, we write "int arr[4]". Individual elements can be accessed using indexes from 0 to dimension-1.
- Strings in C++ are arrays of characters that end with a null character. Common string functions like strcpy(), strcat(), strlen() allow manipulating strings.
Arrry structure Stacks in data structurelodhran-hayat
There are two types of arrays in C++: single dimensional and multidimensional arrays. The document then provides examples of using single dimensional arrays, traversing arrays using for loops and foreach loops, using structs with constructors and methods, pointers including declaring, assigning, and dereferencing pointers, and dynamic memory allocation using new and delete operators for built-in types, arrays, objects, and multidimensional arrays.
The document discusses arrays in C++. It defines an array as a group of consecutive memory locations with the same name and type. Arrays allow storing multiple values using a single name. The document covers one-dimensional and two-dimensional arrays, including how to declare, initialize, access elements, and write programs to input and output array values. It provides examples of programs that input values into arrays, find the maximum/minimum values, and store/display 2D arrays.
This document discusses arrays and pointers in C++. It begins by explaining that arrays allow storing multiple values of the same type, and that arrays have a fixed size and type after declaration. It then covers how to declare, initialize, access elements of, and iterate through arrays using indexes and loops. Multidimensional arrays are also explained, including how they can be thought of as tables with rows and columns. The document concludes by introducing pointers as variables that store the memory addresses of other variables.
The document provides information about arrays and pointers in C++. It discusses how to declare, initialize, access elements of arrays including multi-dimensional arrays. It also covers pointers, how they store memory addresses rather than values, and how to declare and assign addresses to pointers. Key topics include declaring arrays with syntax like dataType arrayName[size]; initializing arrays; accessing elements using indices; multi-dimensional arrays of different sizes; declaring pointers with syntax like int* pointer; and assigning addresses to pointers using &operator.
Arrays allow storing multiple values of the same type sequentially in memory. An array is declared with the type, name, and size. Elements are accessed using indexes from 0 to size-1. Strings are represented as character arrays terminated with a null character. Arrays can be passed to and returned from functions, and multidimensional arrays store arrays within arrays. Standard libraries provide functions for string and character manipulation.
An array is a container that holds a fixed number of values of the same type. Arrays in Java are created in three steps: 1) declare the array name and type, 2) create the array using new, and 3) initialize the array values. The length of an array is fixed at creation. Arrays can be one-dimensional, containing a list of values, or multi-dimensional, containing other arrays. Elements in arrays are accessed via an index with the first element at index 0.
This document discusses references and dynamic memory allocation in C++. It covers passing references as function parameters, returning references from functions, and advantages over pointers. It also explains static versus dynamic memory allocation, allocating and deallocating single and multi-dimensional dynamic arrays, and avoiding memory leaks when using dynamic allocation.
Arrays are ordered sets of elements of the same type that allow direct access to each element through an index. In C++, arrays have a fixed size that is declared, with elements accessed using square brackets and integers representing their position. Multidimensional arrays arrange data in tables and can be thought of as arrays of arrays. Elements are accessed using multiple indices separated by commas within the brackets.
The document discusses arrays in Java, including how to declare and initialize one-dimensional and two-dimensional arrays, access array elements, pass arrays as parameters, and sort and search arrays. It also covers arrays of objects and examples of using arrays to store student data and daily temperature readings from multiple cities over multiple days.
The document discusses how to tune a query for better performance. It begins by explaining that the algorithm and approach are most important for performance and scalability. Writing procedural code should be avoided when possible in favor of set-based operations using SQL. Examples are provided of poorly written procedural code that could be improved by using SQL constructs instead. The document then demonstrates how to tune a sample query by adding relevant indexes and constraints based on the schema. Overall, the key points are to think in sets rather than procedurally, leverage SQL over procedural code, and understand how the schema and metadata impact query optimization.
The document discusses pointers and dynamic memory allocation in C++. It explains that pointers store memory addresses and can be used to indirectly access variables. The new operator allocates dynamic memory from the heap at runtime and returns the memory address, which must be assigned to a pointer. The delete operator deallocates memory previously allocated with new. Dynamic arrays can be created at runtime using new[] and require delete[] to avoid memory leaks. Classes with dynamic memory need constructors to allocate memory and destructors to deallocate it.
This document provides instructions for a learning exercise on linked lists. It contains 8 parts that teach what linked lists are, how to define the data structure for a linked list, and how to perform operations like adding and removing nodes from the list. The tasks are meant to be completed during a 25 minute lecture, with the goal of learning how to handle linked lists and practice working with pointers and dynamically allocated data objects. The document provides code snippets and explanations for creating a linked list and performing operations like adding nodes, displaying the list, and deleting nodes from different positions within the list. It also discusses using additional pointers to navigate through the list.
The document discusses one-dimensional arrays in C++, including how to define and initialize arrays, pass arrays to functions as parameters, and use pointers and references to access array elements. It provides examples of declaring and initializing arrays, passing arrays to a function that prints out the elements, using the reference operator (&) to get the address of a variable and assign it to a pointer, using the dereference operator (*) to access the value at a pointer's address, and how changing a value through a pointer changes the original variable.
The document discusses various topics related to dynamic linked lists including their meaning, traversal, insertion, and deletion operations. It describes implementing a list abstract data type using either an array or linked list as the underlying data structure. Key points covered include traversing a linked list using pointers, inserting and deleting nodes by allocating and deallocating memory dynamically, and the additional operations needed for a sorted linked list such as insert as first and remove first elements.
This document discusses lists as an abstract data type and various implementations of lists in C++. It covers array-based and linked list implementations. For array-based lists, it describes static and dynamic allocation approaches. For linked lists, it explains how to implement them using nodes with pointer links between elements and the operations needed for insertion, deletion and traversal. It also discusses the advantages and disadvantages of the different list implementations.
The document discusses abstract data types (ADTs) and data structures in C++. It covers arrays as ADTs implemented as static and dynamic arrays using pointers. Dynamic arrays use new and delete operators to allocate and free memory at runtime. Structures are introduced as a way to create new data types that have multiple attributes and can model objects. An example shows an array of structures to store information about animals in a zoo.
This document discusses data structures and abstract data types. It covers one-dimensional and multidimensional arrays in C++. Arrays allow storing a collection of elements of the same type that can be accessed via an index. The document provides examples of declaring, initializing, accessing, and passing arrays. It also discusses how arrays are stored contiguously in memory. Functions are demonstrated that take arrays as arguments to operate on the elements. Multidimensional arrays generalize this to multiple indices.
This document discusses data structures and their role in organizing data efficiently for computer programs. It defines key concepts like abstract data types, algorithms, and problems. It also provides examples to illustrate selecting the appropriate data structure based on the operations and constraints of a problem. A banking application is used to demonstrate how hash tables are suitable because they allow extremely fast searching by account numbers while also supporting efficient insertion and deletion. B-trees are shown to be better than hash tables for a city database because they enable fast range queries in addition to exact searches. Overall, the document emphasizes that each data structure has costs and benefits, and a careful analysis is needed to determine the best structure for a given problem.
This chapter discusses object-oriented programming (OOP) and abstract data types (ADTs) using C++ classes. It contrasts procedural with object-oriented programming, explaining how classes are used in C++ to define new types. The chapter then covers class constructors, overloaded operators, and pointers to class objects. It provides an example of a Time class that implements a time ADT as an illustration.
The document contains examples of Boolean algebra expressions and their simplification using sum of products and product of sums.
In the first example, the expression (A'B' + C)(B + CD) is simplified using both methods. The sum of products results in 9 terms, while the product of sums results in 8 terms.
The second example simplifies the expression X(X + Y’)(Y’Z’) using sum of products, resulting in 5 terms.
This document contains 12 differential equations with varying levels of complexity. The equations include functions such as sine, cosine, tangent, secant, exponentials, logarithms, and inverse trigonometric functions. The differential equations relate the rate of change of y with respect to x (y') to expressions involving x and previously defined functions.
This document provides solutions to finding derivatives of various functions:
1) The derivatives of functions involving inverse trigonometric, exponential, logarithmic, and composite functions are presented.
2) Rules for evaluating derivatives of functions of the form F(X) are reviewed, including the derivatives of F(X)n and ln(F(X)).
3) Examples of applying these rules to evaluate definite integrals are shown.
The document discusses data structures and their importance in organizing data efficiently for computer programs. It defines what a data structure is and how choosing the right one can improve a program's performance. Several examples are provided to illustrate how analyzing a problem's specific needs guides the selection of an optimal data structure.
This document outlines the syllabus for MST 103 - Introduction to Statistics and Probability, a 3-credit course taught on Sundays from 9-11 am by Professor Ahmed HassenYoussef. The textbook is Statistical Techniques in Business and Economics with Global Data sets. The goals of the course are to understand descriptive and inferential statistics, distinguish between variable types, and understand the four levels of measurement. Statistics is defined as the science of collecting, organizing, analyzing, and interpreting numerical data to assist with decision making.
2. 2
Chapter Contents
1 Data Structures, Abstract Data Types and
Implementations
2 Static Arrays
3 Multidimensional Arrays (optional)
4 Dynamic Arrays
5 C-Style Structs (optional)
6 Procedural Programming
3. 3
Chapter Objectives
• Look at ADTs, implementations in detail
• Introduce arrays as ADTs
• See arrays implemented as C++ static arrays
• (Optional) Describe multidimensional arrays
• Extend pointers to use in dynamic arrays
• (Optional) Show use of C++ structs to model
objects with multiple attributes
• Show example of procedural programming
paradigm
4. 4
Data Structures, Abstract Data
Types, and Implementations
• Consider example of an airplane flight with
10 seats to be assigned
• Tasks
– List available seats
– Reserve a seat
• How to store, access data?
– 10 individual variables
– An array of variables
5. 5
Data Structures, Abstract Data
Types, and Implementations
• Implementation consists of
– Storage (data) structures
– Algorithms for basic operations
• Note following figure
– C++ provides large collection of data types and
structures
6. 6
C++ Data TypesC++ Data Types
structured
array struct union class
address
pointer reference
simple
integral enum
char short int long bool
floating
float double long double
7. Structured Data Type
7
A structured data type is a type that
– Stores a collection of individual
components with one variable name
– And allows individual components
to be stored and retrieved by their
position within the collection
8. 8
Arrays
• Collection of data elements
– All of same type
– Each accessed by specifying position
• Static array
– Compiler determines how memory allocated
• Dynamic array
– Allocation takes place at run time
9. 9
Single Dimension Arrays
• Syntax:
ElementType arrayName [CAPACITY];
ElementType arrayName [CAPACITY] =
{ initializer_list };
• Example:
int b [10];
• Elements accessed by
– name and [ ] operation b[5]
10. 10
Character Arrays
• Elements of an array may be of any type
– Including characters
• Example:
char name [NAME_CAPACITY] =
"John Doe";
• If array initialized shorter than specs
– extra locations filled with null character
11. 11
Subscript Operation
• We have said elements
accessed by name and [ ]
numList[5]
• Consider the [ ] to be an
operator
– The subscript operator
– Performs address
translation
• Name of the array is a
pointer constant
– The base address
12. Declare variables to
store and total 3 blood pressures
12
int bp1, bp2, bp3;
int total;
40024000 4004
bp2bp1 bp3
cin >> bp1 >> bp2 >> bp3;
total = bp1 + bp2 + bp3;
13. What if you wanted to store and
total 1000 blood pressures?
13
int bp[1000];
// Declares an array of 1000 int values
bp[0] bp[1] bp[2] . . . . bp[999]
5000 5002 5004 5006
. . . .
14. One-Dimensional Array
Definition
14
An array is a structured collection of components
(called array elements), all of the same data type,
given a single name, and stored in adjacent
memory locations
The individual components are accessed by using
the array name together with an integral valued
index in square brackets
The index indicates the position of the component
within the collection
15. Another Example
15
• Declare an array called temps which will
hold up to 5 individual float values
float temps[5]; // Declaration allocates memory
temps[0] temps[1] temps[2] temps[3] temps[4]
7000 7004 7008 7012 7016
number of elements in the array
indexes or subscripts
Base Address
16. Declaration of an Array
16
• The index is also called the subscript
• In C++, the first array element always has
subscript 0, the second array element has
subscript 1, etc.
• The base address of an array is its
beginning address in memory
SYNTAX
DataType ArrayName[ConstIntExpression];
17. Yet Another Example
17
• Declare an array called name which will hold
up to 10 individual char values
char name[10]; // Declaration allocates memory
number of elements in the array
name[0] name[1] name[2] name[3] name[4] . . . . . name[9]
6000 6001 6002 6003 6004 6005 6006 6007 6008 6009
Base Address
18. Assigning Values to
Individual Array Elements
18
float temps[5]; int m = 4; // Allocates memory
temps[2] = 98.6;
temps[3] = 101.2;
temps[0] = 99.4;
temps[m] = temps[3] / 2.0;
temps[1] = temps[3] - 1.2;
// What value is assigned?
temps[0] temps[1] temps[2] temps[3] temps[4]
7000 7004 7008 7012 7016
99.4 ? 98.6 101.2 50.6
19. What values are assigned?
19
float temps[5]; // Allocates memory
int m;
for (m = 0; m < 5; m++)
{
temps[m] = 100.0 + m * 0.2 ;
}
temps[0] temps[1] temps[2] temps[3] temps[4]
7000 7004 7008 7012 7016
? ? ? ? ?
20. Now what values are printed?
20
float temps[5]; // Allocates memory
Int m;
. . . . .
for (m = 4; m >= 0; m--)
{
cout << temps[m] << endl;
}
temps[0] temps[1] temps[2] temps[3] temps[4]
7000 7004 7008 7012 7016
100.0 100.2 100.4 100.6 100.8
21. Variable Subscripts
21
float temps[5]; // Allocates memory
int m = 3;
. . . . . .
What is temps[m + 1] ?
What is temps[m] + 1 ?
temps[0] temps[1] temps[2] temps[3] temps[4]
7000 7004 7008 7012 7016
100.0 100.2 100.4 100.6 100.8
22. A Closer Look at the Compiler
22
float temps[5]; // Allocates memory
To the compiler, the value of the identifier temps is
the base address of the array
We say temps is a pointer (because its value is an
address); it “points” to a memory location
temps[0] temps[1] temps[2] temps[3] temps[4]
7000 7004 7008 7012 7016
100.0 100.2 100.4 100.6 100.8
23. Initializing in a Declaration
23
int ages[5] ={ 40, 13, 20, 19, 36 };
for (int m = 0; m < 5; m++)
{
cout << ages[m];
}
ages[0] ages[1] ages[2] ages[3] ages[4]
6000 6002 6004 6006 6008
40 13 20 19 36
24. Passing Arrays as Arguments
24
• In C++, arrays are always
passed by reference
• Whenever an array is passed as
an argument, its base address is
sent to the called function
25. In C++,
No Aggregate Array Operations
25
• The only thing you can do with an
entire array as a whole (aggregate)
is to pass it as an argument to a
function
• Exception: aggregate I/O is
permitted for C strings (special
kinds of char arrays)
26. Using Arrays as
Arguments to Functions
26
Generally, functions that work with
arrays require 2 items of information
– The beginning memory address of the
array (base address)
– The number of elements to process in the
array
27. Example with Array Parameters
27
#include <iomanip>
#include <iostream>
void Obtain (int[], int); // Prototypes here
void FindWarmest (const int[], int , int&);
void FindAverage (const int[], int , int&);
void Print (const int[], int);
using namespace std;
int main ( )
{
// Array to hold up to 31 temperatures
int temp[31]
int numDays;
int average;
int hottest;
int m;
27
28. Example continued
28
cout << “How many daily temperatures? ”;
cin >> numDays;
Obtain(temp, numDays);
// Call passes value of numDays and address temp
cout << numDays << “ temperatures“ << endl;
Print (temp, numDays);
FindAverage (temp, numDays, average);
FindWarmest (temp, numDays, hottest);
cout << endl << “Average was: “ << average
<< endl;
cout << “Highest was: “ << hottest << endl;
return 0;
}
28
29. Memory Allocated for Array
29
temp[0] temp[1] temp[2] temp[3] temp[4] . . . . . temp[30]
6000
Base Address
50 65 70 62 68 . . . . . .
int temp[31];// Array to hold up to 31 temperatures
30. 30
void Obtain ( /* out */ int temp[] ,
/* in */ int number )
// User enters number temperatures at keyboard
// Precondition:
// number is assigned && number > 0
// Postcondition:
// temp[0 . . number -1] are assigned
{
int m;
for (m = 0; m < number; m++)
{
cout << “Enter a temperature : “;
cin >> temp[m];
}
} 30
31. 31
void Print ( /* in */ const int temp[],
/* in */ int number )
// Prints number temperature values to screen
// Precondition:
// number is assigned && number > 0
// temp[0 . . number -1] are assigned
// Postcondition:
// temp[0 . . number -1] printed 5 per line
{
int m;
cout << “You entered: “;
for (m = 0; m < number; m++)
{
if (m % 5 == 0)
cout << endl;
cout << setw(7) << temp[m];
}
}
31
32. 32
Using Arrays
• Accessing array for output
– See Fig. 1
• Accessing array for input from keyboard
– See Fig. 2
• Note use of arrays as parameters
– Must specify number of elements of array being
used
33. Figure1:Array Output
Function
void display(int theArray[], int numValues)
/*-----------------------------------------------------------------
Display values in an array of integers. Precondition: 0 <=
numValues < capacity of theArray. Postcondition: The
first numValues integers stored in theArray have been
output to cout.
-------------------------------------------------------------------------*/
{
for (int i = 0; i < numValues; i++)
cout « theArray[i] « 00 " .
cout « endl;
} 33
34. Figure 2: Array Input Function
#include <cassert>
void read(IntArray theArray, int capacity, int numValues)
/*-------------------------------------------------------------------------
Input values into an array of integers from the keyboard.
Preconditions: 0 <= numValues < capacity, which is the capacity
of theArray. Postcondition: numValues integers entered from the
keyboard have been stored in the first NumValues positions of
theArray
-------------------------------------------------------------------------/*
{
assert (numValues >= 0 && numValues <= capacity);
for (int i = 0; i < numValues; i++)
cin » theArray[i] ;
}
34
35. 35
#include <iostream>
using namespace std;
void main()
{
int Nums[4];
int Sum=0;
cout<<"Enter 4 Numbers :n";
for(int i=0;i<4;i++)
cin>>Nums[i];
for(int j=0;j<4;j++)
Sum+=Nums[j];
cout<<"Sum = "<<Sum<<endl;
}
36. 36
Multidimensional Arrays
• Consider multiple pages of the student grade
book
const int NUM_ROWS = 10, NUM_COLS = 5,
NUM_RANKS = 10;
typedef double
ThreeDimArray[NUM_ROWS][NUM_COLS][NUM_RANKS];
. . .
37. Example on Multidimensional Arrays
• #include <iostream> using namespace std;
• int main()
• {
• // A 2-Dimensional array
• double distance[2][4] = {44.14, 720.52, 96.08, 468.78, 6.28, 68.04, 364.55, 6234.12};
• // Scan the array from the 3rd to the 7th member
• cout << "Members of the array";
• cout << "nDistance [0][0]" << ": " << distance[0][0];
• cout << "nDistance [0][1]" << ": " << distance[0][1];
• cout << "nDistance [0][2]" << ": " << distance[0][2];
• cout << "nDistance [0][3]" << ": " << distance[0][3];
• cout << "nDistance [1][0]" << ": " << distance[1][0];
• cout << "nDistance [1][1]" << ": " << distance[1][1];
• cout << "nDistance [1][2]" << ": " << distance[1][2];
• cout << "nDistance [1][3]" << ": " << distance[1][3];
• cout << endl; return 0;
• }
• This would produce: Members of the array
• Distance [0][0]: 44.14 Distance [0][1]: 720.52
• Distance [0][2]: 96.08 Distance [0][3]: 468.78
• Distance [1][0]: 6.28 Distance [1][1]: 68.04
• Distance [1][2]: 364.55 Distance [1][3]: 6234.12 37
38. 38
Array of Array Declarations
• An array of arrays
– An array whose elements are other arrays
39. 39
Array of Array Declarations
• Each of the rows is itself a one dimensional
array of values
scoresTable[2]
is the whole row numbered 2
scoresTable[2]
is the whole row numbered 2
scoresTable [1][3]scoresTable [1][3]
40. 40
Memory Allocation in
2-Dimensional Arrays
• Elements
stored in
rowwise order
• Also called
column major
order
location [0][4] is followed in
memory by location [1][0]
location [0][4] is followed in
memory by location [1][0]