symmetrical logarithmic (positive only) x axis

Hello!

I'm trying to plot flux values on the Y axis versus cumulative probability on the X axis. I've figured out the following code:

xdata = probability; %data I've entered as a variable
ydata = flux; %data I've entered as a variable
scatter(xdata,ydata);
set(gca,'xscale','log','yscale','log');
xticks([0.01 0.5 2 10 30 50 70 90 98 99.5 99.99]);
xlim([0 120]);
xlabel('cumulative probability') 
ylabel('flux CO2')

which produces this graph:

but the issue is, I would like to recreate the following X axis (ignore the Y axis below) where there is more space between intervals at lower and higher probabilities:

Any help in doing this would be greatly appreciated!

[Walter Roberson]

Do you want to do that by filtering out some of your existing data to make it more sparse at the upper end?

[Kristen Rahilly]

Thanks for your comment, Walter. I would like to just change the X axis (this is to follow practices in my field using what's called the Sinclair Method or Graphical Statistical Approach to find the inflection point between different populations within a geochemical dataset based on a log-normal probability plot). For some reason I just cannot figure out how to get the X axis scaled in this manner. An example of this type of plot is seen here: https://doi.org/10.1016/j.jvolgeores.2019.03.002 in Figure 7.

[dpb]

If have Statistics Toolbox, use probplot

The axis scaling for a probability plot is dependent upon the chosen distribution which isn't given in the above Q? and it takes access to get to the reference that most won't have.

[Kristen Rahilly]

Thanks so much for the suggestion to use probplot, I will definitely try that. Sorry about the reference access but thank you again for your help!

[dpb]

Oh, I see you did say a lognormal distribution above...missed it on the first reading.

BTW, with probplot default puts y on x-axis, to put the probability axis on x, use

view(90,90)

to rotate the view.

[Kristen Rahilly]

Hi dpb,

That works perfectly! Thank you very much for all your help.