Gsharp, Un Éditeur De Partitions De Musique Interactif Et Personnalisable
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Objects, Time and Constraints in Openmusic
OBJECTS, TIME AND CONSTRAINTS IN OPENMUSIC Carlos Agon, Gérard Assayag, Olivier Delerue, Camilo Rueda. {agonc,assayag,delerue,crueda}@ircam.fr IRCAM - 1 Pl. Stravinsky. F-75004 Paris, France. 1. Abstract OpenMusic is a object oriented visual programming environment for music composers. It is based on Macintosh CommonLisp and Common Lisp Object System. It shows several original features, such as reflexivity, metaprogrammation capacities, handling of the duality between musical time and computational time, and provides with a framework of predefined musical objects for handling sound, midi and musical notation. Common Music Notation in OpenMusic is an extension of CMN, a public domain notation package by Bill Schottstaedt [SCO98]. 2. Objects 2.1. Underlying Object Model. Broadly speaking, basic calculus for object-oriented programming inherited the approach imposed by the precursory language Simula and its followers. The tentatives to formalize this family of object models used the concepts of parametric polymorphism or true polymorphism [CaWe85]. More recently, languages based on multiple-dispatching (methods that dispatch on a product of types rather than a single type) such as CLOS [Steel90] were also formalized [Cast98], using concepts of overloading or ad-hoc polymorphism. As OpenMusic, based on CLOS, may very well be formally described in this way, we will give here a brief summary of the λ&− calculus used by [Cast98]. We restrain to the extension of λ−calculus by the concept of generic functions which is at the base of λ&−calculus. A generic function is simply a collection of simple functions (λ−abstractions), which we will call methods. We must also distinguish the simple application indicated by «.» from the application of generic functions indicated by the operator . -
The Copyright Law of the United States (Title 17, U.S
NOTICE WARNING CONCERNING COPYRIGHT RESTRICTIONS: The copyright law of the United States (title 17, U.S. Code) governs the making of photocopies or other reproductions of copyrighted material. Any copying of this document without permission of its author may be prohibited by law. CMU Common Lisp User's Manual Mach/IBM RT PC Edition David B. McDonald, Editor April 1989 CMU-CS-89-132 . School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 This is a revised version of Technical Report CMU-CS-87-156. Companion to Common Lisp: The Language Abstract CMU Common Lisp is an implementation of Common Lisp that currently runs on the IBM RT PC under Mach, a Berkeley Unix 4.3 binary compatible operating system. This document describes the implementation dependent choices made in developing this implementation of Common Lisp. Also, several extensions have been added, including the proposed error system, a stack crawling debugger, a stepper, an interface to Mach system calls, a foreign function call interface, the ability to write assembler language routines, and other features that provide a good environment for developing Lisp code. This research was sponsored by the Defense Advanced Research Projects Agency (DOD), ARPA Order No. 4976 under contract F33615-87-C-1499 and monitored by the Avionics Laboratory, Air Force Wright Aeronautical Laboratories, Aeronautical Systems Division (AFSC), Wright-Patterson AFB, OHIO 45433-6543. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the U.S. -
Processing Sound and Music Description Data Using Openmusic
PROCESSING SOUND AND MUSIC DESCRIPTION DATA USING OPENMUSIC Jean Bresson, Carlos Agon IRCAM – CNRS UMR STMS Paris, France fbresson,[email protected] ABSTRACT graphs corresponding to functional expressions. The lan- guage provides a set of graphical control structures, such as This paper deals with the processing and manipulation of iterations and conditional controls, as well as the possibility music and sound description data using functional programs to carry out other programming concepts like abstraction, in the OpenMusic visual programming environment. We go higher-order functions or recursion [4]. through several general features and present some toolkits OM includes specialized functions and data structures created in this environment for the manipulation of different designed for musical applications. The different musical or data formats (audio, MIDI, SDIF). extra-musical objects are represented by classes (as meant by object-oriented programming) and used in the visual 1. INTRODUCTION programs by means of factory boxes, i.e. boxes generating instances of these classes and allowing to access their dif- Musical information processing often requires manipulating ferent attributes (called slots). large musical or sound description data bases. Ordering, Compared to most existing visual programming envi- sorting, renaming files, automatic indexing, contents brows- ronments, OM has the particularity to run a demand-driven ing or transformations are basic operations in compositional, execution model. In this model, the user triggers execution analytical, or other experimental applications. by evaluating a box somewhere in the visual program graph, Visual music programming environments make it possi- which recursively evaluates the upstream connected boxes ble to define specialized and personalized programs and to and returns a value. -
The Machine That Builds Itself: How the Strengths of Lisp Family
Khomtchouk et al. OPINION NOTE The Machine that Builds Itself: How the Strengths of Lisp Family Languages Facilitate Building Complex and Flexible Bioinformatic Models Bohdan B. Khomtchouk1*, Edmund Weitz2 and Claes Wahlestedt1 *Correspondence: [email protected] Abstract 1Center for Therapeutic Innovation and Department of We address the need for expanding the presence of the Lisp family of Psychiatry and Behavioral programming languages in bioinformatics and computational biology research. Sciences, University of Miami Languages of this family, like Common Lisp, Scheme, or Clojure, facilitate the Miller School of Medicine, 1120 NW 14th ST, Miami, FL, USA creation of powerful and flexible software models that are required for complex 33136 and rapidly evolving domains like biology. We will point out several important key Full list of author information is features that distinguish languages of the Lisp family from other programming available at the end of the article languages and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSL): languages which are specialized to a particular area and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the “programmable programming language.” We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and AI research in bioinformatics and computational biology. -
Omnipresent and Low-Overhead Application Debugging
Omnipresent and low-overhead application debugging Robert Strandh [email protected] LaBRI, University of Bordeaux Talence, France ABSTRACT application programmers as opposed to system programmers. The state of the art in application debugging in free Common The difference, in the context of this paper, is that the tech- Lisp implementations leaves much to be desired. In many niques that we suggest are not adapted to debugging the cases, only a backtrace inspector is provided, allowing the system itself, such as the compiler. Instead, throughout this application programmer to examine the control stack when paper, we assume that, as far as the application programmer an unhandled error is signaled. Most such implementations do is concerned, the semantics of the code generated by the not allow the programmer to set breakpoints (unconditional compiler corresponds to that of the source code. or conditional), nor to step the program after it has stopped. In this paper, we are mainly concerned with Common Furthermore, even debugging tools such as tracing or man- Lisp [1] implementations distributed as so-called FLOSS, i.e., ually calling break are typically very limited in that they do \Free, Libre, and Open Source Software". While some such not allow the programmer to trace or break in important sys- implementations are excellent in terms of the quality of the tem functions such as make-instance or shared-initialize, code that the compiler generates, most leave much to be simply because these tools impact all callers, including those desired when it comes to debugging tools available to the of the system itself, such as the compiler. -
Introduo Computao Musical (Minicurso Cbcomp 2004)
IV Congresso Brasileiro de Computação CBComp 2004 Brasil Introdução à Computação Musical E. M. Miletto, L. L. Costalonga, L. V. Flores, E. F. Fritsch, M. S. Pimenta e R. M. Vicari Instituto de Informática - Laboratório de Computação & Música Universidade Federal do Rio Grande do Sul Av. Bento Gonçalves, 9500 Bloco IV - Campus do Vale - Bairro Agronomia - CEP 91501-970 Porto Alegre - RS - Brasil {miletto, llcostalonga, lvf, fritsch, mpimenta, rosa}@inf.ufrgs.br RESUMO E. M. Miletto, L. L. Costalonga, L. V. Flores, E. F. Fritsch, M. S. Pimenta e R. M. Vicari. 2004. Introdução à Computação Musical. Congresso Brasileiro de Ciência da Computação, S Itajaí, 2004, 883 – 902. Itajaí, SC – Brasil, ISSN 1677-2822 A idéia deste minicurso é propiciar aos alunos conhecer alguns conceitos introdutórios de Computação Musical, uma área eminentemente interdisciplinar e que engloba problemas computacionais interessantes e relevantes (por exemplo, de representação de conhecimento musical, de controle a tempo-real de dispositivos, de interação com usuários possivelmente leigos em informática, para enumerar apenas alguns) subjacentes ao universo musical, que já é fascinante por si só. É uma área emergente no Brasil, mas já possui um reconhecimento da comunidade acadêmica de informática, uma vez que a SBC possui uma Comissão Especial de Computação Musical, que organiza um evento periódico (Simpósio Brasileiro de Computação Musical – SBCM). Ano passado, o IX SBCM aconteceu em Campinas em conjunto com o Congresso da SBC (ver http://www.nics.unicamp.br/nucom/portugues). As características interdisciplinares do tema têm sido, nos últimos anos, objeto de trabalho quotidiano do Grupo de Computação Musical da Universidade Federal do Rio Grande do Sul (UFRGS), que conta com a participação e interação efetivas de professores, alunos e pesquisadores tanto do Instituto de Informática quanto do Instituto de Artes da UFRGS (ver http://www.musicaeletronica.ufrgs.br). -
Macaque – a Tool for Spectral Processing and Transcription
MACAQUE – A TOOL FOR SPECTRAL PROCESSING AND TRANSCRIPTION Georg Hajdu Center for Microtonal Music and Multimedia (ZM4) Hamburg University of Music and Theater (HfMT) Harvestehuder Weg 12 20148 Hamburg [email protected] ABSTRACT act of my opera Der Sprung – Beschreibung einer Oper [7] I used the MIDI velocity information of the transcribed note This paper describes Macaque, a tool for spectral process- events to alter the size of their note heads so that the sight- ing and transcription, in development since 1996. Macaque reading musicians had instantaneous visual feedback per- was programmed in Max and, in 2013, embedded into the taining to the dynamics of the music to be performed. In MaxScore ecosystem. Its GUI offers several choices for the other instances, I have used a technique called “velocoding” processing and transcription of SDIF partial-track files into to encode microtonal pitch deviation in eighth-tone resolu- standard music notation. At the core of partial-track tran- tion into the velocity part of a MIDI note-on message to scription is an algorithm capable of “attracting” partial modify the Enigma file in such ways that the resulting score tracks (and fragments thereof) into single staves, thereby displayed the corresponding pitch alterations. Another early performing an important aspect of “spectral orchestration.” example of using Macaque is my piece Herzstück for two player pianos from 1999 which premiered at the Cologne 1. INTRODUCTION Triennale in 2000. This piece was written for two of Jürgen Hocker’s instruments which he also used to tour Conlon Macaque is a component of the MaxScore notation soft- Nancarrow’s compositions for player piano [8]. -
Musical Notation Codes Index
Music Notation - www.music-notation.info - Copyright 1997-2019, Gerd Castan Musical notation codes Index xml ascii binary 1. MidiXML 1. PDF used as music notation 1. General information format 2. Apple GarageBand Format 2. MIDI (.band) 2. DARMS 3. QuickScore Elite file format 3. SMDL 3. GUIDO Music Notation (.qsd) Language 4. MPEG4-SMR 4. WAV audio file format (.wav) 4. abc 5. MNML - The Musical Notation 5. MP3 audio file format (.mp3) Markup Language 5. MusiXTeX, MusicTeX, MuTeX... 6. WMA audio file format (.wma) 6. MusicML 6. **kern (.krn) 7. MusicWrite file format (.mwk) 7. MHTML 7. **Hildegard 8. Overture file format (.ove) 8. MML: Music Markup Language 8. **koto 9. ScoreWriter file format (.scw) 9. Theta: Tonal Harmony 9. **bol Exploration and Tutorial Assistent 10. Copyist file format (.CP6 and 10. Musedata format (.md) .CP4) 10. ScoreML 11. LilyPond 11. Rich MIDI Tablature format - 11. JScoreML RMTF 12. Philip's Music Writer (PMW) 12. eXtensible Score Language 12. Creative Music File Format (XScore) 13. TexTab 13. Sibelius Plugin Interface 13. MusiXML: My own format 14. Mup music publication program 14. Finale Plugin Interface 14. MusicXML (.mxl, .xml) 15. NoteEdit 15. Internal format of Finale (.mus) 15. MusiqueXML 16. Liszt: The SharpEye OMR 16. XMF - eXtensible Music 16. GUIDO XML engine output file format Format 17. WEDELMUSIC 17. Drum Tab 17. NIFF 18. ChordML 18. Enigma Transportable Format 18. Internal format of Capella (ETF) (.cap) 19. ChordQL 19. CMN: Common Music 19. SASL: Simple Audio Score 20. NeumesXML Notation Language 21. MEI 20. OMNL: Open Music Notation 20. -
Allegro CL User Guide
Allegro CL User Guide Volume 1 (of 2) version 4.3 March, 1996 Copyright and other notices: This is revision 6 of this manual. This manual has Franz Inc. document number D-U-00-000-01-60320-1-6. Copyright 1985-1996 by Franz Inc. All rights reserved. No part of this pub- lication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means electronic, mechanical, by photocopying or recording, or otherwise, without the prior and explicit written permission of Franz incorpo- rated. Restricted rights legend: Use, duplication, and disclosure by the United States Government are subject to Restricted Rights for Commercial Software devel- oped at private expense as specified in DOD FAR 52.227-7013 (c) (1) (ii). Allegro CL and Allegro Composer are registered trademarks of Franz Inc. Allegro Common Windows, Allegro Presto, Allegro Runtime, and Allegro Matrix are trademarks of Franz inc. Unix is a trademark of AT&T. The Allegro CL software as provided may contain material copyright Xerox Corp. and the Open Systems Foundation. All such material is used and distrib- uted with permission. Other, uncopyrighted material originally developed at MIT and at CMU is also included. Appendix B is a reproduction of chapters 5 and 6 of The Art of the Metaobject Protocol by G. Kiczales, J. des Rivieres, and D. Bobrow. All this material is used with permission and we thank the authors and their publishers for letting us reproduce their material. Contents Volume 1 Preface 1 Introduction 1.1 The language 1-1 1.2 History 1-1 1.3 Format -
Composição Assistida Por Computador: – Escolha De Estrutura Musical , Partes Computador • P.Ex
Composição não é Edição de Partituras • Ex: Musescore Computação Musical http://www.musescore.org/en Composição Assistida por • Composição Assistida por Computador: – Escolha de estrutura musical , partes Computador • p.ex. Concerto (3 movm: 'allegro-adagio-allegro') – Escolha de ritmos Prof. Marcelo Soares Pimenta – Escolha de sons, timbres, notas e sua serialização (melodia) e verticalização (harmonia, acordes) [email protected] – Edição, (re)arranjo, (re)organização, experimentação (audição) 2 Porto Alegre , 2009-2 Foundations of CAC Foundations of CAC the concept of Compositional Modeling Otto Laske, Composition Theory in Koenig's Project One and Project Two . Computer Music Journal (1981): Study, simulation, explicitation of an object (concept, concrete object, phenomenon, situation, "We may view composer-program interaction along a trajectory leading from purely manual etc.) control to control exercised by some compositional algorithm (composing machine). The zone "Modeling aims at gathering in a common coherent discourse a number of experiences and of greatest interest for composition theory is the midd le zone of the trajectory, since it allow a observations related by a means which is to determine during the modeling process itself" D. Berthier. Le great flexibility of approach. The powers of intuition and machine computation may be savoir et l’ordinateur combined." (2002) . Jean-Claude Risset, Musique, un calcul secret ? (1977) Computer model => abstract representation focusing on particular ⇒ The musician must be able to communicate with the computer in order to control and aspects of an object and supporting effective expermients and organize the details and global aspects of his musical works, and eventually to build his own operations on this object musical universe in it. -
S Allegro Common Lisp Foreign Function Interface
Please do not remove this page Extensions to the Franz, Inc.'s Allegro Common Lisp foreign function interface Keane, John https://scholarship.libraries.rutgers.edu/discovery/delivery/01RUT_INST:ResearchRepository/12643408560004646?l#13643533500004646 Keane, J. (1996). Extensions to the Franz, Inc.’s Allegro Common Lisp foreign function interface. Rutgers University. https://doi.org/10.7282/t3-pqns-7h57 This work is protected by copyright. You are free to use this resource, with proper attribution, for research and educational purposes. Other uses, such as reproduction or publication, may require the permission of the copyright holder. Downloaded On 2021/09/29 22:58:32 -0400 Extensions to the Franz Incs Allegro Common Lisp Foreign Function Interface John Keane Department of Computer Science Rutgers University New Brunswick NJ keanecsrutgersedu January Abstract As provided by Franz Inc the foreign function interface of Allegro Com mon Lisp has a number of limitations This pap er describ es extensions to the interface that facilitate the inclusion of C and Fortran co de into Common Lisp systems In particular these extensions make it easy to utilize libraries of numerical subroutines such as those from Numerical Recip es in C from within ACL including those routines that take functions as arguments A mechanism for creating Lisplike dynamic runtime closures for C routines is also describ ed Acknowledgments The research presented in this do cument is supp orted in part by NASA grants NCC and NAG This research is also part of the Rutgers based -
Threading and GUI Issues for R
Threading and GUI Issues for R Luke Tierney School of Statistics University of Minnesota March 5, 2001 Contents 1 Introduction 2 2 Concurrency and Parallelism 2 3 Concurrency and Dynamic State 3 3.1 Options Settings . 3 3.2 User Defined Options . 5 3.3 Devices and Par Settings . 5 3.4 Standard Connections . 6 3.5 The Context Stack . 6 3.5.1 Synchronization . 6 4 GUI Events And Blocking IO 6 4.1 UNIX Issues . 7 4.2 Win32 Issues . 7 4.3 Classic MacOS Issues . 8 4.4 Implementations To Consider . 8 4.5 A Note On Java . 8 4.6 A Strategy for GUI/IO Management . 9 4.7 A Sample Implementation . 9 5 Threads and GUI’s 10 6 Threading Design Space 11 6.1 Parallelism Through HL Threads: The MXM Options . 12 6.2 Light-Weight Threads: The XMX Options . 12 6.3 Multiple OS Threads Running One At A Time: MSS . 14 6.4 Variations on OS Threads . 14 6.5 SMS or MXS: Which To Choose? . 14 7 Light-Weight Thread Implementation 14 1 March 5, 2001 2 8 Other Issues 15 8.1 High-Level GUI Interfaces . 16 8.2 High-Level Thread Interfaces . 16 8.3 High-Level Streams Interfaces . 16 8.4 Completely Random Stuff . 16 1 Introduction This document collects some random thoughts on runtime issues relating to concurrency, threads, GUI’s and the like. Some of this is extracted from recent R-core email threads. I’ve tried to provide lots of references that might be of use.