make vectors same length using min function
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A-Rod
am 17 Jun. 2024
Kommentiert: dpb
am 18 Jun. 2024
dear community let me ask your support.
my data:
x = [2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016];
y = [0, 0.05, 0.1, 0.15, 0.2];
a = [2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017,2018,2019];
b = [0, 0.05, 0.1, 0.15, 0.2, 0.4];
I'm trying to make x & a vector lenght same as y & b vector length so Im using min fucntion
minlen = min(length(y), length(x));
minlen = min(length(b), length(a));
I'm trying to get x & a vector updated instead of getting this ans
x(1:minlen);

how can I make x & a equal to ans respectively? like this:
x = [2008, 2009, 2010, 2011, 2012];
a = [2008, 2009, 2010, 2011, 2012, 2013];
any feedback will be highly appreciated
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Akzeptierte Antwort
Image Analyst
am 17 Jun. 2024
How about
x = [2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016];
y = [0, 0.05, 0.1, 0.15, 0.2];
a = [2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017,2018,2019];
b = [0, 0.05, 0.1, 0.15, 0.2, 0.4];
x = x(1 : length(y))
a = a(1 : length(b))
4 Kommentare
Image Analyst
am 17 Jun. 2024
Yeah, I don't know the whole situation and just did what was asked for. It's possible that it might not work for other situations (such as y being shorter than x) and this is certainly not a robust solution for all possible caes. Originally I thought of using linspace to go from the min x to the max x
x = linspace(min(x), max(x), numel(y))
but then I saw he wanted it truncated instead of interpolated/rescaled, so then I just went with indexing to basically crop the x.
Weitere Antworten (1)
Steven Lord
am 17 Jun. 2024
x = [2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016];
y = [0, 0.05, 0.1, 0.15, 0.2];
a = [2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017,2018,2019];
b = [0, 0.05, 0.1, 0.15, 0.2, 0.4];
minlen = min(length(y), length(x));
You could use indexing and assignment:
xbackup = x; % for use in the next block of code
x = x(1:minlen) % Note the added "x = " to assign the indexing result back to x
x = xbackup % restoring the original x since the previous line overwrote it
x = trimdata(x, minlen)
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