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Nemerle is a general-purpose, high-level, statically typed programming language designed for platforms using the Common Language Infrastructure (.NET/Mono). It offers functional, object-oriented, aspect-oriented, reflective and imperative features. It has a simple C#-like syntax and a powerful metaprogramming system. In June 2012, the core developers of Nemerle were hired by the Czech software development company JetBrains. The team was focusing on developing Nitra, a framework to implement extant and new programming languages. Both the Nemerle language and Nitra have seemingly been abandoned or discontinued by JetBrains; Nitra has not been updated by its original creators since 2017 and Nemerle is now maintained entirely by the Russian Software Development Network, independently from JetBrains, although no major updates have been released yet and development is progressing very slowly. Neither Nemerle, nor Nitra have been mentioned or referenced by JetBrains for years. Nemerle is named after the Archmage Nemmerle, a character in the fantasy novel A Wizard of Earthsea by Ursula K. Le Guin. Nemerle's most notable feature is the ability to mix styles of programming that are object-oriented and functional. Programs may be structured using object-oriented concepts such as classes and namespaces, while methods can (optionally) be written in a functional style. Other notable features include: strong type inference a flexible metaprogramming subsystem (using macros) full support for object-oriented programming (OOP), in the style of C#, Java, and C++ full support for functional programming, in the style of ML, OCaml, and Haskell, with these features: higher-order functions pattern matching algebraic types local functions tuples and anonymous types partial application of functions The metaprogramming system allows for great compiler extensibility, embedding domain-specific languages, partial evaluation, and aspect-oriented programming, taking a high-level approach to lift as much of the burden as possible from programmers.
Martin Odersky, Nicolas Alexander Stucki
[2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will implement a simple fractional resampler that
uses local Lagrange interpolation. The resampler can be used to perform
any rational sampling rate change (but beware of aliasing when
downsampling!)
In [1]:
import numpy as np
import IPython
from scipy.io import wavfile
Local Lagrange interpolation[4]¶
To perform resampling we will need to compute subsample values and, in [2]Paolo Prandoni, [3]LCAV, EPFL
This notebook shows a simple way to process audio files (in WAV format)
in a block-by-block fashion; this is useful in two cases
1. when you want to process a data stream in real time but you can
accept a small processing delay; in this case a buffered approach
can yield computational gains
2. when you need to process a large file that does not fit entirely
into