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    Random thoughts and bits of codes compiled along the way

    © 2021. SB.

    Access sampled ESP in TephraProb

      21 Feb 2018     tephraprob     codes tips

    This note shows how to access the ESPs sampled during Monte Carlo simulations and how to link them to a given output. This note has been updated on 2020-02-12 to work with v1.7.1 of TephraProb. Two files are needed:

    • The file located in RUNS/runName/runNb/ named runName_runNb.mat. This contains a structure called data, which contains a field named stor where all the ESPs are stored. data.stor contains sub-fields for the different parameter (e.g. plume height, duration, mass, MER, TGSD). These parameters are stored as vectors that can have different sizes. If the duration of each simulated eruption is <6 h, the size of all vectors should equal the number of simulated eruptions. If durations are >6 h, the size of those parameters that change at each 6 h increment (e.g. plume height, MER) represents the number of times each was sampled. For instance, in the case of a 15 h-long eruption, 3 plume heights are sampled. However, other parameters (e.g. TGSD) are constant over the entire duration of the eruption, so the resulting vectors will have a size equal to the number of simulated eruptions.
    • The file located in RUNS/runName/runNb/DATA/ named dataT2_all.mat, which contains two variables:
      • dataT2 is a m by n matrix, where m is the number of points over which accumulations are computed and n is the number of runs. This variable contains all the summed Tephra2 outputs in kg/m2;
      • runNb is a m by 1 vector, where m is the number of runs.

    Now, there is something to keep in mind. Let’s say we have 10 text files named sequentially from 01.txt to 10.txt. Matlab reads sequential files as 01.txt, 10.txt, 02.txt … 09.txt, and not as 01.txt, 02.txt … 10.txt. In TephraProb post-processing, this means that:

    • ESPs in the variable data.stor are ordered in increasing run number
    • Runs outputs in dataT2 are ordered in the way Matlab reads the files

    It is therefore necessary to re-index dataT2 to the order of the ESPs contained in data.stor.

    Examples

    Re-index ESPs with outputs

    % Load the second sampling attempt of the run called Sakurajima
load RUNS/Sakurajima/2/Sakurajima_2 

% Load the isomass output
load RUNS/Sakurajima/2/DATA/dataT2_all.mat 

% Show the loaded variables
data.stor
dataT2
runNb

% Retrieve the selected ESPs
esp = [[data.stor.ht]'./1e3,log10([data.stor.mass]'),[data.stor.dur]'./3600,[data.stor.gs_med]',date(:,2)];

% Reorder the run numbers in ascending order and save their indices
[~,id] = sort(runNb);
% Reorder the isomass outputs
dataT2 = dataT2(:,id);

% dataT2 and data.stor are now indexed
random_run = 10;
run_output = dataT2(:,random_run);
run_ESPs = esp(random_run, :);

    Plot a histogram of the plume height:

    toPlot = [data.stor.ht]; % Need to vectorize the data

figure;
histogram(toPlot)
xlabel('Plume height')
ylabel('Frequency')
title([num2str(numel(toPlot)), ' occurrences'])

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