Zoom in on a logarithmic axes

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Eric Kappel
Eric Kappel il 5 Nov 2022
Commentato: Eric Kappel il 5 Nov 2022
Good day everyone,
I aim to have the standard axes response (in linear values) when zooming in on
a logarithmic distributed frequency axes, but, ... with linkaxes functionality
coupling 2 adjacent figures in the y- (Frequency) direction. How can I acheive this?
My tries are shown in the code below.
close all; clear clc;
%% Mathworks question
n_timepnts = 500 ; % Number of time points
n_freqs = 100 ; % Number of frequency points
Freq = logspace(0,3,n_freqs) ; % Logarithmic distribution
DataArray = rand(n_freqs,n_timepnts) ; % Some arbitrary data array
Spectrum = rand(n_freqs,1).*max(DataArray,[],2) ; % Arbitrary spectrum
time = linspace(0,365,n_timepnts); % Arbitrary time array in days
%% imagesc approach
figure(1);clf
set(1,'Position',[ 28 250 1187 420],'Name','');
ax(1) = subplot(1,9,1:2);
plot(Spectrum,log10(Freq))
xlabel('Spectral max.')
ylabel(' Frequency [Hz]')
title('Arbitrary Spectrum')
grid on;
%---
ax(2) = subplot(1,9,4:9);
imagesc(time,log10(Freq),DataArray)
set(gca,'YDir','normal');
xlabel('Day of Year')
ylabel(' Frequency [Hz]')
title('Spectral data over time')
%---
linkaxes(ax,'y')
Using the contourf approach (not preferred due to slow response)
%% contourf approach
figure(2);clf
set(2,'Position',[ 48 250 1187 420],'Name','');
ax(1) = subplot(1,9,1:2);
semilogy(Spectrum,Freq)
xlabel('Spectral max.')
ylabel(' Frequency [Hz]')
title('Arbitrary Spectrum')
grid on;
%---
[X,Y] = meshgrid(time,log10(Freq));
ax(2) = subplot(1,9,4:9);
contourf(X,Y,DataArray,'LineColor','none')
% contourf(time,Freq,DataArray,'LineColor','none')
set(gca,'YDir','normal');
xlabel('Day of Year')
ylabel(' Frequency [Hz]')
title('Spectral data over time')
%---
% linkaxes(ax,'y')
yields.
Help please!
Kind regards,
Eric

Risposta accettata

Kevin Holly
Kevin Holly il 5 Nov 2022
You can add Listeners as shown below.
%% Parameters
n_timepnts = 500 ; % Number of time points
n_freqs = 100 ; % Number of frequency points
Freq = logspace(0,3,n_freqs) ; % Logarithmic distribution
DataArray = rand(n_freqs,n_timepnts) ; % Some arbitrary data array
Spectrum = rand(n_freqs,1).*max(DataArray,[],2) ; % Arbitrary spectrum
time = linspace(0,365,n_timepnts); % Arbitrary time array in days
%% contourf approach
figure(2);clf
set(2,'Position',[ 48 250 1187 420],'Name','');
ax(1) = subplot(1,9,1:2);
semilogy(Spectrum,Freq)
xlabel('Spectral max.')
ylabel(' Frequency [Hz]')
title('Arbitrary Spectrum')
grid on;
%---
[X,Y] = meshgrid(time,log10(Freq));
ax(2) = subplot(1,9,4:9);
contourf(X,Y,DataArray,'LineColor','none')
% contourf(time,Freq,DataArray,'LineColor','none')
set(gca,'YDir','normal');
xlabel('Day of Year')
ylabel(' Frequency [Hz]')
title('Spectral data over time')
%---
% Add Listeners
addlistener(ax(1),'YLim', 'PostSet',@(~,events)set(ax(2),'YLim',log10(ax(1).YLim)))
addlistener(ax(2),'YLim', 'PostSet',@(~,events)set(ax(1),'YLim',10.^(ax(2).YLim)))
  1 Commento
Eric Kappel
Eric Kappel il 5 Nov 2022
I certainly would not have come up with such an elegant solution!!! I think I can exploit this feature a lot more!
Thank you!!!
Kind regards,
Eric

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