Difference between revisions of "TISEAN package"
(→Porting TISEAN: added link to "Table of functions") 
(moved "Procedure" to TISEAN_package:Procedure; added noise reduction tutorial.) 

Line 1:  Line 1:  
== Porting TISEAN ==  == Porting TISEAN ==  
−  This section  +  This section will focus on demonstrating the capabilities of the TISEAN package. The previous information about the porting procedure has been moved [[TISEAN_package:Procedurehere]]. 
−  
−  +  == Tutorials ==  
−  +  These tutorials are based on examples, tutorials and the articles located on the TISEAN website:<br/> [http://www.mpipksdresden.mpg.de/~tisean/Tisean_3.0.1/ http://www.mpipksdresden.mpg.de/~tisean/Tisean_3.0.1/].<br/>  
−  +  This tutorial will utilize the following dataset:  
−  +  * [http://www.mpipksdresden.mpg.de/~tisean/Tisean_3.0.1/docs/tutorial/amplitude.dat amplitude.dat]  
−  [  +  Please download it as the tutorial functions will reference it. 
−  +  === Noise Reduction ===  
−  +  This tutorial show different methods of the 'Noise Reduction' section of the TISEAN documentation (located [http://www.mpipksdresden.mpg.de/~tisean/Tisean_3.0.1/docs/chaospaper/node22.html#SECTION00060000000000000000 here]). It shows the use of simple nonlinear noise reduction (function {{Codelinelazy}}) and locally projective nonlinear noise reduction (function {{Codelineghkss}}). To start let's create noisy data to work with.  
−  +  {{CodeCreating a noisy henon map<syntaxhighlight lang="octave" style="fontsize:13px">  
−  +  hen = henon (10000);  
−  +  hen = hen(:,1); # We only need the first column  
−  +  hen_noisy = hen + std (hen) * 0.02 .* (6 + sum (rand ([size(hen), 12]), 3));  
−  +  </syntaxhighlight>}}  
−  +  This created a Henon map contaminated by 2% Gaussian noise à la TISEAN. In the tutorials and exercises on the TISEAN website this would be equivalent to calling {{Codelinemakenoise %2}} on the Henon map.<br/>  
+  Next we will reduce the noise using simple nonlinear noise reduction {{Codelinelazy}}.  
+  {{CodeSimple nonlinear noise reduction<syntaxhighlight lang="octave" style="fontsize:13px">  
+  clean = lazy (hen_noisy,7,0.06,3);  
+  # Create delay vectors for both the clean and noisy data  
+  delay_clean = delay (clean);  
+  delay_noisy = delay (hen_noisy);  
+  # Plot both on one chart  
+  plot (delay_noisy(:,1), delay_noisy(:,2), 'b.;Noisy Data;','markersize,3,...  
+  delay_clean(:,1), delay_clean(:,2), 'r.;Clean Data;','markersize,3)  
+  </syntaxhighlight>}}  
+  On the chart created the red dots represent cleaned up data. It is much closer to the original than the noisy set.<br/>  
+  Now we will do the same, only with {{Codelineghkss}}.  
+  {{CodeLocally projective nonlinear noise reduction<syntaxhighlight lang="octave" style="fontsize:13px">  
+  clean = ghkss (hen(:,1),'m',7,'q',2,'r',0.05,'k',20,'i',2);  
+  # Create delay vectors for both the clean and noisy data  
+  delay_clean = delay (clean);  
+  delay_noisy = delay (hen_noisy);  
+  # Plot both on one chart  
+  plot (delay_noisy(:,1), delay_noisy(:,2), 'b.;Noisy Data;','markersize,3,...  
+  delay_clean(:,1), delay_clean(:,2), 'r.;Clean Data;','markersize,3)  
+  </syntaxhighlight>}}  
[[Category:OctaveForge]]  [[Category:OctaveForge]] 
Revision as of 10:35, 1 June 2015
Porting TISEAN
This section will focus on demonstrating the capabilities of the TISEAN package. The previous information about the porting procedure has been moved here.
Tutorials
These tutorials are based on examples, tutorials and the articles located on the TISEAN website:
http://www.mpipksdresden.mpg.de/~tisean/Tisean_3.0.1/.
This tutorial will utilize the following dataset:
Please download it as the tutorial functions will reference it.
Noise Reduction
This tutorial show different methods of the 'Noise Reduction' section of the TISEAN documentation (located here). It shows the use of simple nonlinear noise reduction (function lazy
) and locally projective nonlinear noise reduction (function ghkss
). To start let's create noisy data to work with.
Code: Creating a noisy henon map 
hen = henon (10000);
hen = hen(:,1); # We only need the first column
hen_noisy = hen + std (hen) * 0.02 .* (6 + sum (rand ([size(hen), 12]), 3));

This created a Henon map contaminated by 2% Gaussian noise à la TISEAN. In the tutorials and exercises on the TISEAN website this would be equivalent to calling makenoise %2
on the Henon map.
Next we will reduce the noise using simple nonlinear noise reduction lazy
.
Code: Simple nonlinear noise reduction 
clean = lazy (hen_noisy,7,0.06,3);
# Create delay vectors for both the clean and noisy data
delay_clean = delay (clean);
delay_noisy = delay (hen_noisy);
# Plot both on one chart
plot (delay_noisy(:,1), delay_noisy(:,2), 'b.;Noisy Data;','markersize,3,...
delay_clean(:,1), delay_clean(:,2), 'r.;Clean Data;','markersize,3)

On the chart created the red dots represent cleaned up data. It is much closer to the original than the noisy set.
Now we will do the same, only with ghkss
.
Code: Locally projective nonlinear noise reduction 
clean = ghkss (hen(:,1),'m',7,'q',2,'r',0.05,'k',20,'i',2);
# Create delay vectors for both the clean and noisy data
delay_clean = delay (clean);
delay_noisy = delay (hen_noisy);
# Plot both on one chart
plot (delay_noisy(:,1), delay_noisy(:,2), 'b.;Noisy Data;','markersize,3,...
delay_clean(:,1), delay_clean(:,2), 'r.;Clean Data;','markersize,3)

External links
 Bitbucket repository where the porting is taking place.