Use online CSS and JS

This commit is contained in:
Thomas Dehaeze 2020-11-12 10:21:37 +01:00
parent 14b54fb912
commit 9c1d16e11a
13 changed files with 48 additions and 1474 deletions

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index.org
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@ -7,12 +7,8 @@
#+HTML_LINK_HOME: ../index.html
#+HTML_LINK_UP: ../index.html
#+HTML_HEAD: <link rel="stylesheet" type="text/css" href="./css/htmlize.css"/>
#+HTML_HEAD: <link rel="stylesheet" type="text/css" href="./css/readtheorg.css"/>
#+HTML_HEAD: <link rel="stylesheet" type="text/css" href="./css/custom.css"/>
#+HTML_HEAD: <script type="text/javascript" src="./js/jquery.min.js"></script>
#+HTML_HEAD: <script type="text/javascript" src="./js/bootstrap.min.js"></script>
#+HTML_HEAD: <script type="text/javascript" src="./js/readtheorg.js"></script>
#+HTML_HEAD: <link rel="stylesheet" type="text/css" href="https://research.tdehaeze.xyz/css/style.css"/>
#+HTML_HEAD: <script type="text/javascript" src="https://research.tdehaeze.xyz/js/script.js"></script>
#+PROPERTY: header-args:latex :headers '("\\usepackage{tikz}" "\\usepackage{import}" "\\import{$HOME/Cloud/tikz/org/}{config.tex}")
#+PROPERTY: header-args:latex+ :imagemagick t :fit yes
@ -22,6 +18,7 @@
#+PROPERTY: header-args:latex+ :eval no-export
#+PROPERTY: header-args:latex+ :exports both
#+PROPERTY: header-args:latex+ :mkdirp yes
#+PROPERTY: header-args:latex+ :tangle no
#+PROPERTY: header-args:latex+ :output-dir figs
#+PROPERTY: header-args:latex+ :post pdf2svg(file=*this*, ext="png")
@ -55,21 +52,6 @@ Finally, some notes are done on how to compute the noise level and signal level
:END:
<<sec:spectral_analysis_basics>>
** ZIP file containing the data and matlab files :ignore:
#+begin_src bash :exports none :results none
if [ matlab/spectral_analysis_basics.m -nt data/spectral_analysis_basics.zip ]; then
cp matlab/spectral_analysis_basics.m spectral_analysis_basics.m;
zip data/spectral_analysis_basics \
mat/data_028.mat \
spectral_analysis_basics.m
rm spectral_analysis_basics.m;
fi
#+end_src
#+begin_note
All the files (data and Matlab scripts) are accessible [[file:data/spectral_analysis_basics.zip][here]].
#+end_note
** Introduction :ignore:
In this section, the basics of spectral analysis is presented with the associated Matlab commands.
@ -87,6 +69,14 @@ This include:
<<matlab-init>>
#+end_src
#+begin_src matlab :tangle no
addpath('./matlab/mat/');
#+end_src
#+begin_src matlab :eval no
addpath('./mat/');
#+end_src
** Sensitivity of the instrumentation
A typical measurement setup is shown in figure [[fig:velocity_to_voltage]] where we measure a physical signal which is here a velocity $v(t)$ using a geophone.
The geophone has some dynamics that we represent with $G_g(s)$, its output a voltage.
@ -483,21 +473,6 @@ With Matlab, the Cumulative Power Spectrum can be computed with the below formul
:END:
<<sec:approximate_tf>>
** ZIP file containing the data and matlab files :ignore:
#+begin_src bash :exports none :results none
if [ matlab/approximate_psd_tf.m -nt data/approximate_psd_tf.zip ]; then
cp matlab/approximate_psd_tf.m approximate_psd_tf.m;
zip data/approximate_psd_tf \
mat/dist_psd.mat \
approximate_psd_tf.m
rm approximate_psd_tf.m;
fi
#+end_src
#+begin_note
All the files (data and Matlab scripts) are accessible [[file:data/approximate_psd_tf.zip][here]].
#+end_note
** Introduction :ignore:
** Matlab Init :noexport:ignore:
@ -509,6 +484,14 @@ With Matlab, the Cumulative Power Spectrum can be computed with the below formul
<<matlab-init>>
#+end_src
#+begin_src matlab :tangle no
addpath('./matlab/mat/');
#+end_src
#+begin_src matlab :eval no
addpath('./mat/');
#+end_src
** Signal's PSD
We load the PSD of the signal we wish to replicate.
#+begin_src matlab
@ -703,21 +686,6 @@ Finally, we compare the PSD of the generated signal with the original PSD in fig
:END:
<<sec:approximate_ifft>>
** ZIP file containing the data and matlab files :ignore:
#+begin_src bash :exports none :results none
if [ matlab/approximate_psd_ifft.m -nt data/approximate_psd_ifft.zip ]; then
cp matlab/approximate_psd_ifft.m approximate_psd_ifft.m;
zip data/approximate_psd_ifft \
mat/dist_psd.mat \
approximate_psd_ifft.m
rm approximate_psd_ifft.m;
fi
#+end_src
#+begin_note
All the files (data and Matlab scripts) are accessible [[file:data/approximate_psd_ifft.zip][here]].
#+end_note
** Introduction :ignore:
The technique comes from cite:preumont94_random_vibrat_spect_analy (section 12.11).
It is used to compute a periodic signal that has any Power Spectral Density defined.
@ -732,6 +700,14 @@ It makes used of the Unversed Fast Fourier Transform (IFFT).
<<matlab-init>>
#+end_src
#+begin_src matlab :tangle no
addpath('./matlab/mat/');
#+end_src
#+begin_src matlab :eval no
addpath('./mat/');
#+end_src
** Signal's PSD
We load the PSD of the signal we wish to replicate.
#+begin_src matlab
@ -867,20 +843,6 @@ Finally, we compare the PSD of the original signal and the obtained signal on fi
:END:
<<sec:compute_psd_levels>>
** ZIP file containing the data and matlab files :ignore:
#+begin_src bash :exports none :results none
if [ matlab/compute_psd_levels.m -nt data/compute_psd_levels.zip ]; then
cp matlab/compute_psd_levels.m compute_psd_levels.m;
zip data/compute_psd_levels \
compute_psd_levels.m
rm compute_psd_levels.m;
fi
#+end_src
#+begin_note
All the files (data and Matlab scripts) are accessible [[file:data/compute_psd_levels.zip][here]].
#+end_note
** Introduction :ignore:
We here make use of the Power Spectral Density to estimate either the noise level or the amplitude of a deterministic signal.
Everything is explained in cite:schmid12_how_to_use_fft_matlab sections 5 and 6.
@ -894,6 +856,14 @@ Everything is explained in cite:schmid12_how_to_use_fft_matlab sections 5 and 6.
<<matlab-init>>
#+end_src
#+begin_src matlab :tangle no
addpath('./matlab/mat/');
#+end_src
#+begin_src matlab :eval no
addpath('./mat/');
#+end_src
** Time Domain Signal
Let's first define the number of sample and the sampling time.
#+begin_src matlab

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@ -1,87 +0,0 @@
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$(document).on('click', ".wy-menu-vertical .current ul li a", function() {
$("[data-toggle='wy-nav-shift']").removeClass("shift");
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});
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});
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});
$( document ).ready(function() {
$('#text-table-of-contents ul').first().addClass('nav');
// ScrollSpy also requires that we use
// a Bootstrap nav component.
$('body').scrollspy({target: '#text-table-of-contents'});
// add sticky table headers
$('table').stickyTableHeaders();
// set the height of tableOfContents
var $postamble = $('#postamble');
var $tableOfContents = $('#table-of-contents');
$tableOfContents.css({paddingBottom: $postamble.outerHeight()});
// add TOC button
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$('#content').prepend(toggleSidebar);
// add close button when sidebar showed in mobile screen
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var tocTitle = $('#table-of-contents').find('h2');
tocTitle.append(closeBtn);
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var navBar,
win,
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@ -4,6 +4,8 @@ clear; close all; clc;
%% Intialize Laplace variable
s = zpk('s');
addpath('./mat/');
% Signal's PSD
% We load the PSD of the signal we wish to replicate.

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@ -4,6 +4,8 @@ clear; close all; clc;
%% Intialize Laplace variable
s = zpk('s');
addpath('./mat/');
% Signal's PSD
% We load the PSD of the signal we wish to replicate.

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@ -4,6 +4,8 @@ clear; close all; clc;
%% Intialize Laplace variable
s = zpk('s');
addpath('./mat/');
% Time Domain Signal
% Let's first define the number of sample and the sampling time.

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@ -4,10 +4,9 @@ clear; close all; clc;
%% Intialize Laplace variable
s = zpk('s');
addpath('./mat/');
% #+RESULTS:
% [[file:figs/velocity_to_voltage.png]]
% #+NAME: fig:velocity_to_voltage
% #+CAPTION: Schematic of the instrumentation used for the measurement
@ -69,8 +68,7 @@ ylabel("Velocity [m/s]");
% The goal of spectral estimation is to describe the distribution (over frequency) of the power contained in a signal, based on a finite set of data.
% #+end_quote
% We now have the velocity $v$ in the time domain:
% \[ v(t)\ [m/s] \]
% We now have the velocity $v(t)\ [m/s]$ in the time domain.
% The Power Spectral Density (PSD) $S_v(f)$ of the time domain $v(t)$ can be computed using the following equation:
% \[ S_v(f) = \frac{1}{f_s} \sum_{m=-\infty}^{\infty} R_{xx}(m) e^{-j 2 \pi m f / f_s} \ \left[\frac{(m/s)^2}{Hz}\right] \]
@ -85,7 +83,7 @@ ylabel("Velocity [m/s]");
% To compute the Power Spectral Density with matlab, we use the =pwelch= function ([[https://fr.mathworks.com/help/signal/ref/pwelch.html?s_tid=doc_ta][documentation]]).
% The use of the =pwelch= function is:
% =[pxx,w] = pwelch(x,window,noverlap,nfft, fs)=
% With:
% with:
% - =x= is the discrete time signal
% - =window= is a window that is used to smooth the obtained PSD
% - =overlap= can be used to have some overlap from section to section