Delete items from array and split it up into new arrays

1 view (last 30 days)
Hi,
I have a long array consisting of a long section of negative values, then a long section of positive values, then a long section of negative values and so on. I would like to remove all the negative values from my array, but at the same time split up the array into the individual long sections of positive values.
Simplified example:
array = [-0.0016 -0.0017 0.1746 0.1834 -0.0017 -0.0018 0.1567 0.1456 0.1744 -0.0018 -0.0017 0.1243 0.1456]
And then I would like this:
answer = {0.1746 0.1834} {0.1567 0.1456 0.1744} {0.1243 0.1456}
So the negative values has been removed, and the array is split up into new arrays containing the positive values from each section.
I hope it makes sense!

Accepted Answer

Image Analyst
Image Analyst on 10 Nov 2022
You can easily do it if you have the Image Processing Toolbox.
array = [-0.0016 -0.0017 0.1746 0.1834 -0.0017 -0.0018 0.1567 0.1456 0.1744 -0.0018 -0.0017 0.1243 0.1456];
% Identify positive indexes
mask = array >= 0;
% Measure values at those indexes.
positiveRegions = regionprops(mask, array, 'PixelValues');
% Identify negative indexes
mask = array < 0;
% Measure values at those indexes.
negativeRegions = regionprops(mask, array, 'PixelValues');
positiveRegions and negativeRegions are structure arrays (rather than cell arrays). To extract the numbers for a particular region, say the 2nd region you can do
values = positiveRegions(2).PixelValues
values = 1×3
0.1567 0.1456 0.1744
You can also get them in a table if you want:
array = [-0.0016 -0.0017 0.1746 0.1834 -0.0017 -0.0018 0.1567 0.1456 0.1744 -0.0018 -0.0017 0.1243 0.1456];
% Identify positive indexes
mask = array >= 0;
% Measure values at those indexes.
positiveRegions = regionprops('table', mask, array, 'PixelValues')
positiveRegions = 3×1 table
PixelValues ________________________ {[ 0.1746 0.1834]} {[0.1567 0.1456 0.1744]} {[ 0.1243 0.1456]}
% Identify negative indexes
mask = array < 0;
% Measure values at those indexes.
negativeRegions = regionprops('table', mask, array, 'PixelValues')
negativeRegions = 3×1 table
PixelValues __________________ -0.0016 -0.0017 -0.0017 -0.0018 -0.0018 -0.0017

More Answers (2)

Voss
Voss on 10 Nov 2022
array = [-0.0016 -0.0017 0.1746 0.1834 -0.0017 -0.0018 0.1567 0.1456 0.1744 -0.0018 -0.0017 0.1243 0.1456];
is_negative = array < 0
is_negative = 1×13 logical array
1 1 0 0 1 1 0 0 0 1 1 0 0
start_idx = strfind([true is_negative],[true false])
start_idx = 1×3
3 7 12
end_idx = strfind([is_negative true],[false true])
end_idx = 1×3
4 9 13
answer = arrayfun(@(s,e)array(s:e),start_idx,end_idx,'UniformOutput',false)
answer = 1×3 cell array
{[0.1746 0.1834]} {[0.1567 0.1456 0.1744]} {[0.1243 0.1456]}

AH
AH on 10 Nov 2022
You may find the code below doing the desired task
array = [-0.0016 -0.0017 0.1746 0.1834 -0.0017 -0.0018 0.1567 0.1456 0.1744 -0.0018 -0.0017 0.1243 0.1456]'
array = 13×1
-0.0016 -0.0017 0.1746 0.1834 -0.0017 -0.0018 0.1567 0.1456 0.1744 -0.0018
% find the mask where the array is non-negative
binMask = array >= 0;
% Find the start and end index of each region of interest
sidx = find(diff(binMask) == 1)+1
sidx = 3×1
3 7 12
eidx = find(diff(binMask) == -1)
eidx = 2×1
4 9
if (binMask(1) == 1)
sidx = [1;sidx];
end
if (binMask(end) == 1)
eidx = [eidx; length(array)];
end
% Split it into cells
ncell = min(length(sidx),length(eidx));
A = cell(ncell,1);
for i = 1:ncell
A{i} = array(sidx(i):eidx(i));
end
A
A = 3×1 cell array
{2×1 double} {3×1 double} {2×1 double}
You can also achieve this task using the functions sigrangebinmask and binmask2sigroi.
  3 Comments
Image Analyst
Image Analyst on 10 Nov 2022
@AH, what toolbox is sigrangebinmask in? It's not in the Signal Processing Toolbox.

Sign in to comment.

Categories

Find more on Matrices and Arrays in Help Center and File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!