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_HOME: ../index.html
#+HTML_LINK_UP: ../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="https://research.tdehaeze.xyz/css/style.css"/>
#+HTML_HEAD: <link rel="stylesheet" type="text/css" href="./css/readtheorg.css"/> #+HTML_HEAD: <script type="text/javascript" src="https://research.tdehaeze.xyz/js/script.js"></script>
#+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>
#+PROPERTY: header-args:latex :headers '("\\usepackage{tikz}" "\\usepackage{import}" "\\import{$HOME/Cloud/tikz/org/}{config.tex}") #+PROPERTY: header-args:latex :headers '("\\usepackage{tikz}" "\\usepackage{import}" "\\import{$HOME/Cloud/tikz/org/}{config.tex}")
#+PROPERTY: header-args:latex+ :imagemagick t :fit yes #+PROPERTY: header-args:latex+ :imagemagick t :fit yes
@ -22,6 +18,7 @@
#+PROPERTY: header-args:latex+ :eval no-export #+PROPERTY: header-args:latex+ :eval no-export
#+PROPERTY: header-args:latex+ :exports both #+PROPERTY: header-args:latex+ :exports both
#+PROPERTY: header-args:latex+ :mkdirp yes #+PROPERTY: header-args:latex+ :mkdirp yes
#+PROPERTY: header-args:latex+ :tangle no
#+PROPERTY: header-args:latex+ :output-dir figs #+PROPERTY: header-args:latex+ :output-dir figs
#+PROPERTY: header-args:latex+ :post pdf2svg(file=*this*, ext="png") #+PROPERTY: header-args:latex+ :post pdf2svg(file=*this*, ext="png")
@ -55,22 +52,7 @@ Finally, some notes are done on how to compute the noise level and signal level
:END: :END:
<<sec:spectral_analysis_basics>> <<sec:spectral_analysis_basics>>
** ZIP file containing the data and matlab files :ignore: ** Introduction :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. In this section, the basics of spectral analysis is presented with the associated Matlab commands.
This include: This include:
@ -87,6 +69,14 @@ This include:
<<matlab-init>> <<matlab-init>>
#+end_src #+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 ** 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. 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. The geophone has some dynamics that we represent with $G_g(s)$, its output a voltage.
@ -483,22 +473,7 @@ With Matlab, the Cumulative Power Spectrum can be computed with the below formul
:END: :END:
<<sec:approximate_tf>> <<sec:approximate_tf>>
** ZIP file containing the data and matlab files :ignore: ** Introduction :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: ** Matlab Init :noexport:ignore:
#+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name) #+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name)
@ -509,6 +484,14 @@ With Matlab, the Cumulative Power Spectrum can be computed with the below formul
<<matlab-init>> <<matlab-init>>
#+end_src #+end_src
#+begin_src matlab :tangle no
addpath('./matlab/mat/');
#+end_src
#+begin_src matlab :eval no
addpath('./mat/');
#+end_src
** Signal's PSD ** Signal's PSD
We load the PSD of the signal we wish to replicate. We load the PSD of the signal we wish to replicate.
#+begin_src matlab #+begin_src matlab
@ -703,22 +686,7 @@ Finally, we compare the PSD of the generated signal with the original PSD in fig
:END: :END:
<<sec:approximate_ifft>> <<sec:approximate_ifft>>
** ZIP file containing the data and matlab files :ignore: ** Introduction :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). 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. It is used to compute a periodic signal that has any Power Spectral Density defined.
It makes used of the Unversed Fast Fourier Transform (IFFT). It makes used of the Unversed Fast Fourier Transform (IFFT).
@ -732,6 +700,14 @@ It makes used of the Unversed Fast Fourier Transform (IFFT).
<<matlab-init>> <<matlab-init>>
#+end_src #+end_src
#+begin_src matlab :tangle no
addpath('./matlab/mat/');
#+end_src
#+begin_src matlab :eval no
addpath('./mat/');
#+end_src
** Signal's PSD ** Signal's PSD
We load the PSD of the signal we wish to replicate. We load the PSD of the signal we wish to replicate.
#+begin_src matlab #+begin_src matlab
@ -867,21 +843,7 @@ Finally, we compare the PSD of the original signal and the obtained signal on fi
:END: :END:
<<sec:compute_psd_levels>> <<sec:compute_psd_levels>>
** ZIP file containing the data and matlab files :ignore: ** Introduction :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. 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. 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>> <<matlab-init>>
#+end_src #+end_src
#+begin_src matlab :tangle no
addpath('./matlab/mat/');
#+end_src
#+begin_src matlab :eval no
addpath('./mat/');
#+end_src
** Time Domain Signal ** Time Domain Signal
Let's first define the number of sample and the sampling time. Let's first define the number of sample and the sampling time.
#+begin_src matlab #+begin_src matlab

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

View File

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

View File

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

View File

@ -4,10 +4,9 @@ clear; close all; clc;
%% Intialize Laplace variable %% Intialize Laplace variable
s = zpk('s'); s = zpk('s');
addpath('./mat/');
% #+RESULTS:
% [[file:figs/velocity_to_voltage.png]]
% #+NAME: fig:velocity_to_voltage % #+NAME: fig:velocity_to_voltage
% #+CAPTION: Schematic of the instrumentation used for the measurement % #+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. % 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 % #+end_quote
% We now have the velocity $v$ in the time domain: % We now have the velocity $v(t)\ [m/s]$ in the time domain.
% \[ v(t)\ [m/s] \]
% The Power Spectral Density (PSD) $S_v(f)$ of the time domain $v(t)$ can be computed using the following equation: % The Power Spectral Density (PSD) $S_v(f)$ of the time domain $v(t)$ can be computed using the following equation:
% \[ S_v(f) = \frac{1}{f_s} \sum_{m=-\infty}^{\infty} R_{xx}(m) e^{-j 2 \pi m f / f_s} \ \left[\frac{(m/s)^2}{Hz}\right] \] % \[ S_v(f) = \frac{1}{f_s} \sum_{m=-\infty}^{\infty} R_{xx}(m) e^{-j 2 \pi m f / f_s} \ \left[\frac{(m/s)^2}{Hz}\right] \]
@ -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]]). % 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: % The use of the =pwelch= function is:
% =[pxx,w] = pwelch(x,window,noverlap,nfft, fs)= % =[pxx,w] = pwelch(x,window,noverlap,nfft, fs)=
% With: % with:
% - =x= is the discrete time signal % - =x= is the discrete time signal
% - =window= is a window that is used to smooth the obtained PSD % - =window= is a window that is used to smooth the obtained PSD
% - =overlap= can be used to have some overlap from section to section % - =overlap= can be used to have some overlap from section to section