Adding text from calculated functions and line of best fit to scatter plot

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I have calculated three statistic values for observed vs simulated data. I want to add these defined output values (i.e. the cor_Manual_Urbano, bias_da_Manoel_Urbano, NASH_Manoel_Urbano) to the scatter plot of oberserved vs simulated. There is the additional problem that the output result for cor_Manual_Urbano produces a matrix but I only want to display the correlation value between the two variables. I also want to add a line of best fit to the scatter plot. Here is my code so far:
%pearsons%
cor_Manoel_Urbano = corrcoef(combined_data.Observed_Manoel_Urbano,combined_data.Simulated_Manoel_Urbano, 'Rows', 'pairwise')
%bias%
just_Manoel_Urbano = combined_data(:, [11,22]);
cleaned_Manoel_Urbano = rmmissing(just_Manoel_Urbano);
observedmean_Manoel_Urbano = mean(cleaned_Manoel_Urbano.Observed_Manoel_Urbano);
simulatedmean_Manoel_Urbano = mean(cleaned_Manoel_Urbano.Simulated_Manoel_Urbano);
bias_da_Manoel_Urbano = 100*((observedmean_Manoel_Urbano-simulatedmean_Manoel_Urbano)/observedmean_Manoel_Urbano)
%NASH%
DATA_NASH_Manoel_Urbano = [combined_data.Observed_Manoel_Urbano,combined_data.Simulated_Manoel_Urbano];
DATA_NASH_Manoel_Urbano(any(isnan(DATA_NASH_Manoel_Urbano), 2), :) = [];
NASH_Manoel_Urbano = NSE(DATA_NASH_Manoel_Urbano(:,1), DATA_NASH_Manoel_Urbano(:,2))
%scatter%
figure22 = figure('Name','Scatter Manoel Urbano','Color',[1 1 1]);
scatter(cleaned_Manoel_Urbano.Observed_Manoel_Urbano, cleaned_Manoel_Urbano.Simulated_Manoel_Urbano, 'k')
xlabel('Observed','FontName','Calibri','FontSize',12)
ylabel('Simulated', 'FontName','Calibri','FontSize',12)
title('Manoel Urbano','FontName','Calibri','FontSize',14);
set(gcf,'Position',[100 100 400 400])

Akzeptierte Antwort

Star Strider
Star Strider am 26 Mär. 2021
To display the information on the plot, use the text function.
The sprintf or compose functions can also be helpful, depending on what you want to do.
  10 Kommentare
Elizabeth Lees
Elizabeth Lees am 28 Mär. 2021
lsline function works brilliantly! thank you so much all for your help!

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R2018a

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