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Operating Systems OS X (Apple) Simple symmetrical wave RMS DEMO using awk. Post 303002987 by wisecracker on Wednesday 6th of September 2017 09:04:12 AM
Old 09-06-2017
Hi JM...
(Thanks for the reply.)
Apologies for any typos, and hope it is lucid enough.
Quote:
Originally Posted by jim mcnamara
It looks to me like you have a granularity problem. Four dots as a sample can fit a lot of functions, with intermediate datapoints from increased sampling rates you could then use fft to get good sine waves, for example.

You can code fft.c then call it using the system() function in awk. I think your awk supports that call.

A google for 'fft.c' got me 10 first page hits that looked respectably good. There are sites with an array of algorithmic variants to meet differing needs.

fft is gold standard for fitting data sampling output.
Apologies for the delay, I have not been around for a while. My triangle wave is more or less hypothetical as sampling a real time random triangle wave that......
1) starts at the 0 point,
2) is initially positive going,
3) has 4 samples, or any number of the same 4 samples,
......is close to impossible.
But a file CAN be so easily be created as shown in the single cycle version in the code.
Although I was aware of the errors that creep in when creating the RMS values I was NOT aware of this one off bizarre situation, (and could find nothing on the WWW about it), so after creating the simple code I made a point of there being a reference to this anomaly.

As the RMS value(s) are near the exact value(s) for that of a sinewave hence my point.

In the days of Debian 6 and PCLinuxOS 2009, (my two main OSes in those days), when '/dev/dsp' was available, recreating the waveforms through '/dev/dsp' would result in a triangle wave as the sound system interpolation was Linear, this was also true for some Windows machines of bygone days. I am not sure what interpolations are used in current OSes and sound systems but it sure looks trigonometric to me, so I would guess that a sinewave would be recreated as a result.

I am happy with the idea of the RMS code at this point but looking more towards True RMS but would probably need to rethink my approach.

But to re-iterate for others, be aware of this anomaly.

LBNL, for any FFT work needed, I would do it through Python and SciPy as the heavy lifting is done already, see previous uploads of AudioScope.sh for the AF Spectrum display...

Bazza...

Last edited by wisecracker; 09-06-2017 at 12:18 PM.. Reason: Modify for error...
 

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FFT(3pm)						User Contributed Perl Documentation						  FFT(3pm)

NAME
PDL::FFT - FFTs for PDL DESCRIPTION
FFTs for PDL. These work for arrays of any dimension, although ones with small prime factors are likely to be the quickest. For historical reasons, these routines work in-place and do not recognize the in-place flag. That should be fixed. SYNOPSIS
use PDL::FFT qw/:Func/; fft($real, $imag); ifft($real, $imag); realfft($real); realifft($real); fftnd($real,$imag); ifftnd($real,$imag); $kernel = kernctr($image,$smallk); fftconvolve($image,$kernel); DATA TYPES
The underlying C library upon which this module is based performs FFTs on both single precision and double precision floating point piddles. Performing FFTs on integer data types is not reliable. Consider the following FFT on piddles of type 'double': $r = pdl(0,1,0,1); $i = zeroes($r); fft($r,$i); print $r,$i; [2 0 -2 0] [0 0 0 0] But if $r and $i are unsigned short integers (ushorts): $r = pdl(ushort,0,1,0,1); $i = zeroes($r); fft($r,$i); print $r,$i; [2 0 65534 0] [0 0 0 0] This used to occur because PDL::PP converts the ushort piddles to floats or doubles, performs the FFT on them, and then converts them back to ushort, causing the overflow where the amplitude of the frequency should be -2. Therefore, if you pass in a piddle of integer datatype (byte, short, ushort, long) to any of the routines in PDL::FFT, your data will be promoted to a double-precision piddle. If you pass in a float, the single-precision FFT will be performed. FREQUENCIES
For even-sized input arrays, the frequencies are packed like normal for FFTs (where N is the size of the array and D is the physical step size between elements): 0, 1/ND, 2/ND, ..., (N/2-1)/ND, 1/2D, -(N/2-1)/ND, ..., -1/ND. which can easily be obtained (taking the Nyquist frequency to be positive) using "$kx = $real->xlinvals(-($N/2-1)/$N/$D,1/2/$D)->rotate(-($N/2 -1));" For odd-sized input arrays the Nyquist frequency is not directly acessible, and the frequencies are 0, 1/ND, 2/ND, ..., (N/2-0.5)/ND, -(N/2-0.5)/ND, ..., -1/ND. which can easily be obtained using "$kx = $real->xlinvals(-($N/2-0.5)/$N/$D,($N/2-0.5)/$N/$D)->rotate(-($N-1)/2);" ALTERNATIVE FFT PACKAGES
Various other modules - such as PDL::FFTW and PDL::Slatec - contain FFT routines. However, unlike PDL::FFT, these modules are optional, and so may not be installed. FUNCTIONS
fft() Complex FFT of the "real" and "imag" arrays [inplace]. fft($real,$imag); ifft() Complex inverse FFT of the "real" and "imag" arrays [inplace]. ifft($real,$imag); realfft() One-dimensional FFT of real function [inplace]. The real part of the transform ends up in the first half of the array and the imaginary part of the transform ends up in the second half of the array. realfft($real); realifft() Inverse of one-dimensional realfft routine [inplace]. realifft($real); fftnd() N-dimensional FFT (inplace) fftnd($real,$imag); ifftnd() N-dimensional inverse FFT ifftnd($real,$imag); fftconvolve() N-dimensional convolution with periodic boundaries (FFT method) $kernel = kernctr($image,$smallk); fftconvolve($image,$kernel); fftconvolve works inplace, and returns an error array in kernel as an accuracy check -- all the values in it should be negligible. See also PDL::ImageND::convolveND, which performs speed-optimized convolution with a variety of boundary conditions. The sizes of the image and the kernel must be the same. kernctr centres a small kernel to emulate the behaviour of the direct convolution routines. The speed cross-over between using straight convolution (PDL::Image2D::conv2d()) and these fft routines is for kernel sizes roughly 7x7. convmath Signature: ([o,nc]a(m); [o,nc]b(m)) Internal routine doing maths for convolution convmath does not process bad values. It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles. cmul Signature: (ar(); ai(); br(); bi(); [o]cr(); [o]ci()) Complex multiplication cmul does not process bad values. It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles. cdiv Signature: (ar(); ai(); br(); bi(); [o]cr(); [o]ci()) Complex division cdiv does not process bad values. It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles. BUGS
Where the source is marked `FIX', could re-implement using phase-shift factors on the transforms and some real-space bookkeeping, to save some temporary space and redundant transforms. AUTHOR
This file copyright (C) 1997, 1998 R.J.R. Williams (rjrw@ast.leeds.ac.uk), Karl Glazebrook (kgb@aaoepp.aao.gov.au), Tuomas J. Lukka, (lukka@husc.harvard.edu). All rights reserved. There is no warranty. You are allowed to redistribute this software / documentation under certain conditions. For details, see the file COPYING in the PDL distribution. If this file is separated from the PDL distribution, the copyright notice should be included in the file. perl v5.14.2 2012-05-30 FFT(3pm)
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