Plot a table and generate legend from values from the table

Question

Nazar Adamchuk 2021-9-1

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1444729-plot-a-table-and-generate-legend-from-values-from-the-table

回答： Star Strider 2021-9-1

采纳的回答： Star Strider

raw_data.xlsx

在 MATLAB Online 中打开

I have following table (you can find the file in the attachment):

I am reading this table in MATLAB and creating a plot of three lines (I am interested in the lines for the stress ratio "-1") as follows:

imported = readtable('raw_data.xlsx');
plot([imported{1, {'a','c'}}], imported{1,{'b', 'd'}},...
[imported{3, {'a','c'}}], imported{3,{'b', 'd'}},...
[imported{4, {'a','c'}}], imported{4,{'b', 'd'}});

Then I recieve such result:

While plotting I know that the ''-1" stress ratio data are in the lines 1, 3 and 4 in the table "imported". But what if I don't know where are the lines with stress ratio "-1" and I have, for example, stress ratios "1" and "0". Moreover, let es assume I have more then 1000 data.

I would like to have a script be created that founds data for "-1" stress ratio and adds a following legend:

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Answer 1

Star Strider 2021-9-1

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1444729-plot-a-table-and-generate-legend-from-values-from-the-table#answer_778824

在 MATLAB Online 中打开

Try this —

imported = readtable('https://www.mathworks.com/matlabcentral/answers/uploaded_files/726854/raw_data.xlsx');

imported = 4×7 table

a b c d StressRatio Microstructure1 Microstructure2 _ _ _ _ ___________ _______________ _______________ 1 2 2 5 -1 77 23 2 3 4 5 0 70 30 3 3 4 7 -1 74 26 7 4 6 1 -1 71 29

lgdtbl = imported(imported{:,5}<0,[6 7]);

lgdvn = join(lgdtbl.Properties.VariableNames, ' ');

lgdnum = compose('%2d %2d', table2array(lgdtbl));

figure

plot([imported{1, {'a','c'}}], imported{1,{'b', 'd'}},...

[imported{3, {'a','c'}}], imported{3,{'b', 'd'}},...

[imported{4, {'a','c'}}], imported{4,{'b', 'd'}});

hlgd = legend(lgdnum, 'Location','S');

title(hlgd, lgdvn)

This is likely as close as it is possible to get to what you want.

Experiment to get different results.

.