Octave Cheat Sheet
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Concert Pitch and TranspositionHEY!!! What's this Concert Bb or Concert C major scale stuff, anyway!? Did you know that not all instruments sound like a C on the piano when you play a C on the instrument?? With instruments in so many different keys (meaning what note does it sound like if you play the instrument's C), it is helpful to have one place from which to start. So, we use the piano's notes as 'concert pitch'. Flutes, oboes, bassoons, trombones, tubas, baritones reading bass clef and all string instruments are concert pitch instruments: when they play a C it sounds like a C on the piano. They don't have to transpose. (All instruments that mostly read bass clef are in C, but some - like bass guitar and string bass - are written an octave higher to keep the music in the staff). Clarinets, bass clarinets, trumpets, tenor saxes and baritones playing treble clef are Bb instruments: when they play a C it sounds like a Bb on the piano. So, if they want to play a concert Bb scale, they start on a C (they have to think up a whole step). Concert C is their D, Concert Ab is their Bb. Alto and baritone saxes, alto clarinet and most alto horns are Eb instruments: when they play a C it sounds like a Eb on the piano. So, if they want to play a concert Bb scale, they start on a G (they have to think up a six steps in the scale - or down a minor third). Concert C is their A, Concert Ab is their F. French horns and some alto horns and the English horn (that's the one related to the oboe) are F instruments: when they play a C it sounds like a F on the piano. So, if they want to play a concert Bb scale, they start on a F (they have to think up five scale steps). Concert C is their G, Concert Ab is their Eb. By the time you are an eighth grader, you should know your scales (right off, no hesitation and without looking up key signatures or asking what note you start on or anything!) for the following concert pitches :
Click here if you need a cheat sheet to double check to see if you have your transpositions correct. And.. you should be able to find your scale for any other concert pitch that a conductor may request. You might want to print out some of this info for reference or you can get hard copies from MsM. |
- CHEAT SHEET - WRITTEN MANUAL - INTRODUCTION. Note an octave higher on the G string E and D strings any note on the E down and 2 frets over and you have.
- Fiddle trio: Devil Among the Tailors (score) Traditional tune, Arr. Julie Tebbs I always seem to need arrangements that include varying levels of playing ability. This one has violin 1 and 2 at an intermediate level and violin 3 at a beginning level.
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Introduction to Octave Dr. Long Department of Engineering University of Cambridge Based on the Tutorial Guide to Matlab written by Dr. Paul Smith September 2005 This document provides an introduction to computing using Octave. It will teach you howto use Octave to perform calculations, plot graphs, and write simple programs. For Linux, easy way is apt-get install octave. Might want to do apt-get autoremove before. 3 How to install additional packages? On octave 3.8, I found an install file called buildpackages.m in the folder C: Octave Octave-3.8.0 src which is where octave 3.8 was installed using the window installer mentioned above. May 30, 2020 An octave above 100Hz is 200Hz. But an octave above 1kHz is 2kHz. In the first case one octave is 100Hz, but in the second case one octave is 1,000Hz. That’s ten times larger! A 100Hz difference in the low end is HUGE. But 100Hz in the top end is nothing. 100Hz and 200Hz sound very different. But 1kHz (1,000Hz) and 1.1kHz (1,100Hz) sound very.
Visit the Wayland Public Schools site http://www.wayland.k12.ma.us | |||
At its core, this article is about a simple cheat sheet for basicoperations on numeric matrices, which can be very useful if you workingand experimenting with some of the most popular languages that are usedfor scientific computing, statistics, and data analysis.
Sections
- Introduction
- MATLAB/Octave
- Cheat sheet
Introduction
Matrices (or multidimensional arrays) are not only presenting thefundamental elements of many algebraic equations that are used in manypopular fields, such as pattern classification, machine learning, datamining, and math and engineering in general. But in context ofscientific computing, they also come in very handy for managing andstoring data in an more organized tabular form.
Such multidimensional data structures are also very powerfulperformance-wise thanks to the concept of automatic vectorization:instead of the individual and sequential processing of operations onscalars in loop-structures, the whole computation can be parallelized inorder to make optimal use of modern computer architectures.
Language overview
Before we jump to the actual cheat sheet, I wanted togive you at least a brief overview of the different languages that weare dealing with.
All four languages, MATLAB/Octave, Python, R, and Julia are dynamicallytyped, have a command line interface for the interpreter, and come withgreat number of additional and useful libraries to support scientificand technical computing. Conveniently, these languages also offer greatsolutions for easy plotting and visualizations.
Combined with interactive notebook interfaces or dynamic reportgeneration engines(MuPAD for MATLAB,IPython Notebook for Python,knitr for R, andIJulia for Julia based onIPython Notebook) data analysis and documentation has never been easier.
MATLAB (stands for MATrixLABoratory) is the name of an application and language that wasdeveloped byMathWorks back in
- One of its strengths is the variety of different and highlyoptimized “toolboxes” (including very powerful functions for image andother signal processing task), which makes suitable for tacklingbasically every possible science and engineering task.
Like the other languages, which will be covered in this article, it hascross-platform support and is using dynamic types, which allows for aconvenient interface, but can also be quite “memory hungry” forcomputations on large data sets.
Typescript cheat sheet pdf. Even today, MATLAB is probably (still) the most popular language fornumeric computation used for engineering tasks in academia as well as inindustry.
GNU Octave
It is also worth mentioning that MATLAB is the only language in thischeat sheet which is not free and open-sourced. But since it is soimmensely popular, I want to mention it nonetheless. And as analternative there is also the free GNU Octavere-implementation that follows thesame syntactic rules so that the code is compatible to MATLAB (exceptfor very specialized libraries).
This imageis a freely usable media under public domain and represents the firsteigenfunction of the L-shaped membrane, resembling (but not identicalto) MATLAB’s logo trademarked by MathWorks Inc.
Initially, the NumPy project started out underthe name “Numeric” in 1995 (renamed to NumPy in 2006) as a Pythonlibrary for numeric computations based on multi-dimensional datastructures, such as arrays and matrices. Since it makes use ofpre-compiled C code for operations on its “ndarray” objects, it isconsiderably faster than using equivalent approaches in (C)Python.
Python NumPy is my personal favorite since I am a big fan of the Pythonprogramming language. Although similar tools exist for other languages,I found myself to be most productive doing my research and data analysesin IPython notebooks.
It allows me to easily combine Python code (sometimes optimized bycompiling it via the Cython C-Extension or thejust-in-time (JIT) Numba compiler if speed isa concern) with different libraries from the Scipystack includingmatplotlib for inline data visualization (youcan find some of my example benchmarks in this GitHubrepository).
The R programming language was developed in1993 and is a modern GNU implementation of an older statisticalprogramming language called S, which wasdeveloped in the Bell Laboratories in 1976.Since its release, it has a fast-growing user base and is particularlypopular among statisticians.
R was also the first language which kindled my fascination forstatistics and computing. I have used it quite extensively a couple ofyears ago before I discovered Python as my new favorite language fordata analysis.
Although R has great in-built functions for performing all sortsstatistics, as well as a plethora of freely available librariesdeveloped by the large R community, I often hear people complainingabout its rather unintuitive syntax.
With its first release in 2012, Julia is by farthe youngest of the programming languages mentioned in this article. aWhile Julia can also be used as an interpreted language with dynamictypes from the command line, it aims for high-performance in scientificcomputing that is superior to the other dynamic programming languagesfor technical computing thanks to its LLVM-based just-in-time (JIT)compiler.
Personally, I haven’t used Julia that extensively, yet, but there aresome exciting benchmarks that look very promising:
Octave Cheat Sheet Printable
C compiled by gcc 4.8.1, taking best timing from all optimization levels(-O0 through -O3). C, Fortran and Julia use OpenBLAS v0.2.8. The Pythonimplementations of rand_mat_stat and rand_mat_mul use NumPy (v1.6.1)functions; the rest are pure Python implementations.
Octave Cheat Sheet Download
Bezanson, J., Karpinski, S., Shah, V.B. and Edelman, A. (2012), “Julia:A fast dynamic language for technical computing”.
(Source: http://julialang.org/benchmarks/, with permission from thecopyright holder)
KeroVee is a Pitch Correction plugin that works as a VST effect. KeroVee is focused to so-called 'Autotune effect', that is robotic but different from the vocoder. KeroVee can mix two independent transposed outputs of pitch-corrector and bypassed output. Apr 09, 2013 KeroVee is a Pitch-Correction plug-in that works as a VST effect. It can pitch-detect and retune to specified scales or MIDI notes. 'Bypass' and 'SubTone' mix are also available. KeroVee is a Pitch Correction plugin that works as a VST effect. KeroVee is focused to so-called ‘Autotune effect’, that is robotic but different from the vocoder. KeroVee can mix two independent transposed outputs of pitch-corrector and bypassed output. Kerovee153 (0.84.MB). KeroVee is a Pitch Correction plugin that works as a VST effect. It can pitch detect and retune to specified scales or MIDI notes. 'Bypass'and 'SubTone' mix are also available. Audacity vst enabler. Jan 20, 2021 KeroVee by g200kg is a Virtual Effect Audio Plugin for Windows. It functions as a VST Plugin.
Alternative data structures: NumPy matrices vs. NumPy arrays
Cheat Sheet Recipes
Python’s NumPy library also has a dedicated “matrix” type with a syntaxthat is a little bit closer to the MATLAB matrix: For example, the“ * ” operator would perform a matrix-matrix multiplication of NumPymatrices - same operator performs element-wise multiplication on NumPyarrays.
Vice versa, the “.dot()” method is used for element-wisemultiplication of NumPy matrices, wheras the equivalent operation wouldfor NumPy arrays would be achieved via the “ * “-operator.
Most people recommend the usage of the NumPy array type over NumPymatrices, since arrays are what most of the NumPy functions return.
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