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There is an array with positive, negative and NaN values, find the first negative number’s index, and the last positive number index. Use the find function.
for it_array=1:1:2
% Construct Array
if (it_array == 1)
ar_alpha_sum_devi_one = [0.1, 0.7, -0.001, NaN, NaN];
elseif (it_array ==2)
ar_alpha_sum_devi_one = [0.1, 0.7, 0.001, NaN, NaN];
end
% Find last positive
it_last_pos_idx = find(ar_alpha_sum_devi_one > 0, 1, 'last');
% Find first negative
it_first_neg_idx = find(ar_alpha_sum_devi_one < 0, 1, 'first');
if (isempty(it_first_neg_idx))
it_first_neg_idx = NaN;
end
disp(['it_last_pos_idx=' num2str(it_last_pos_idx) ...
', it_first_neg_idx=' num2str(it_first_neg_idx)])
end
it_last_pos_idx=2, it_first_neg_idx=3
it_last_pos_idx=3, it_first_neg_idx=NaNThere is an array with some negative numbers, then some positive numbers, then some negative numbers again. Find the first element of the final segment of negative numbers.
for it_array=1:5
% Construct Array
if (it_array == 1)
ar_alpha_sum_devi_one = [0.1, 0.7, -0.001, NaN, NaN];
elseif (it_array ==2)
ar_alpha_sum_devi_one = [0.1, 0.7, 0.001, NaN, NaN];
elseif (it_array ==3)
ar_alpha_sum_devi_one = [-0.001, 0.1, 0.7, 0.001, NaN, NaN];
elseif (it_array ==4)
ar_alpha_sum_devi_one = [-0.001, 0.1, 0.7, 0.001, -0.0002, -0.05, NaN, NaN];
elseif (it_array ==5)
ar_alpha_sum_devi_one = [NaN, NaN, -0.001, 0.1, 0.7, 0.001, -0.0002, NaN];
end
% Find last positive
it_last_pos_idx = find(ar_alpha_sum_devi_one > 0, 1, 'last');
% Find first negative
it_first_neg_idx = find(ar_alpha_sum_devi_one < 0, 1, 'first');
% Find first negative of last negative segment
ar_alpha_sum_after_last_pos = ...
ar_alpha_sum_devi_one(it_last_pos_idx:length(ar_alpha_sum_devi_one));
it_first_neg_last_neg_seg_idx = it_last_pos_idx - 1 + ...
find(ar_alpha_sum_after_last_pos < 0, 1, 'first');
if (isempty(it_first_neg_idx))
it_first_neg_idx = NaN;
end
if (isempty(it_first_neg_last_neg_seg_idx))
it_first_neg_last_neg_seg_idx = NaN;
end
disp(['it_last_pos_idx=' num2str(it_last_pos_idx) ...
', it_first_neg_idx=' num2str(it_first_neg_idx)...
', it_first_neg_last_neg_seg_idx=' num2str(it_first_neg_last_neg_seg_idx)])
end
it_last_pos_idx=2, it_first_neg_idx=3, it_first_neg_last_neg_seg_idx=3
it_last_pos_idx=3, it_first_neg_idx=NaN, it_first_neg_last_neg_seg_idx=NaN
it_last_pos_idx=4, it_first_neg_idx=1, it_first_neg_last_neg_seg_idx=NaN
it_last_pos_idx=4, it_first_neg_idx=1, it_first_neg_last_neg_seg_idx=5
it_last_pos_idx=6, it_first_neg_idx=3, it_first_neg_last_neg_seg_idx=7In the example below, select by entire rows and columns:
% There is a 2D Matrix
rng(123);
randMatZ = rand(3,6);
disp(randMatZ);
0.6965 0.5513 0.9808 0.3921 0.4386 0.7380
0.2861 0.7195 0.6848 0.3432 0.0597 0.1825
0.2269 0.4231 0.4809 0.7290 0.3980 0.1755
% Duplicate Select Row sand Columns of Elements
disp(randMatZ([1,2,3,3,3,2], [1,1,2,2,2,1]))
0.6965 0.6965 0.5513 0.5513 0.5513 0.6965
0.2861 0.2861 0.7195 0.7195 0.7195 0.2861
0.2269 0.2269 0.4231 0.4231 0.4231 0.2269
0.2269 0.2269 0.4231 0.4231 0.4231 0.2269
0.2269 0.2269 0.4231 0.4231 0.4231 0.2269
0.2861 0.2861 0.7195 0.7195 0.7195 0.2861Rather than selecting entire rows and columns, suppose we want to select only one element at row 1 col 2, the element at row 2 col 4, element at row 5 col 1, etc.
% Select Subset of Elements
it_row_idx = [1,2,3,1,3,2];
it_col_idx = [1,1,5,4,2,3];
% Select sub2idx
ar_lin_idx = sub2ind(size(randMatZ), it_row_idx, it_col_idx);
ar_sel_val = randMatZ(ar_lin_idx);
disp(ar_sel_val');
0.6965
0.2861
0.3980
0.3921
0.4231
0.6848Given scalar value, find the cloest value in array:
fl_a = 3.4;
ar_bb = [1,2,3,4];
[fl_min, it_min_idx] = min(abs(ar_bb-fl_a));
disp(it_min_idx);
3Given a scalar value and an array, find the closest smaller value in the array to the scalar value:
fl_a = 2.1;
ar_bb = [1,2,3,4];
disp(sum(ar_bb<fl_a));
2Array A is between 0 and 1, on some grid. Array B is also between 0 and 1, but scattered. Find for each element of B the index of the cloest value on A that is smaller than the element in B.
rng(1234);
ar_a = linspace(0,10,5);
ar_b = rand([5,1])*10;
mt_a_less_b = ar_a<ar_b;
mt_a_less_b_idx = sum(ar_a<ar_b, 2);
disp(ar_a);
0 2.5000 5.0000 7.5000 10.0000
disp(ar_b);
1.9152
6.2211
4.3773
7.8536
7.7998
disp(mt_a_less_b);
1 0 0 0 0
1 1 1 0 0
1 1 0 0 0
1 1 1 1 0
1 1 1 1 0
disp(mt_a_less_b_idx);
1
3
2
4
4rng(123);
randMatZ = rand(3,6)+1;
randMat = rand(3,6)-0.5;
output = max(-randMat,0);
randMatZ(output==0) = 999;
min(randMatZ,[],2);
randMatZ((max(-randMat,0))==0) = 999;
disp(randMatZ);
999.0000 999.0000 999.0000 1.3921 1.4386 1.7380
999.0000 999.0000 1.6848 1.3432 1.0597 1.1825
999.0000 999.0000 1.4809 999.0000 1.3980 1.1755
disp(min(randMatZ,[],2));
1.3921
1.0597
1.1755In the example below, we start with a 4 by 2 matrix, than we expand specific rows and columns of the matrix. Specifically, we expand the matrix such that the result matrix repeats the 1st, 2nd, 1st, 2nd, then 3rd, than 1st, 1st, and 1st rows. And repeats column 1, then 2nd, then 2nd, then 2nd, and finally the first column.
% Original Matrix
Z = 2;
N = 2;
Q = 2;
base_mat = reshape(1:(Z*N*Q),Z*N,Q);
disp(base_mat);
1 5
2 6
3 7
4 8
% Expanded Matrix
base_expand = base_mat([1,2,1,2,3,1,1,1],[1,2,2,2,1]);
disp(base_expand);
1 5 5 5 1
2 6 6 6 2
1 5 5 5 1
2 6 6 6 2
3 7 7 7 3
1 5 5 5 1
1 5 5 5 1
1 5 5 5 1The example here has the same idea, but we do the operations above in a more automated way. This could be done using alternative methods.
% Original Matrix
Z = 2;
N = 2;
Q = 2;
base_mat = reshape(1:(Z*N*Q),Z*N,Q);
disp(base_mat);
1 5
2 6
3 7
4 8
% Generate row Index many times automatically depending on how many times
% to replicate
vmat_repeat_count = 3;
vmat_reindex_rows_repeat = [1:(Z*N)]'* ones(1,vmat_repeat_count);
vmat_reindex_rows_repeat = vmat_reindex_rows_repeat(:);
disp(vmat_reindex_rows_repeat');
1 2 3 4 1 2 3 4 1 2 3 4
% Duplicate Matrix by the Rows specified above, and using the same number
% of columns.
mat_repdown = base_mat(vmat_reindex_rows_repeat(:), 1:Q);
disp(mat_repdown');
1 2 3 4 1 2 3 4 1 2 3 4
5 6 7 8 5 6 7 8 5 6 7 8There is a matrix where some values are equal to 1 (based on some prior selection), get the row and column index of the matrix.
% Some matrix with 1s
rng(123);
mt_some_ones = rand(3,3);
disp(mt_some_ones);
0.6965 0.5513 0.9808
0.2861 0.7195 0.6848
0.2269 0.4231 0.4809
% find the location of the ones
[r_idx, c_idx] = find(mt_some_ones<0.5);
% the set of locations
disp([r_idx,c_idx]);
2 1
3 1
3 2
3 3Now do the same three with a three dimensional array:
% Some matrix with 1s
rng(123);
mn3_some_ones = rand(3,3,3);
disp(mn3_some_ones);
(:,:,1) =
0.6965 0.5513 0.9808
0.2861 0.7195 0.6848
0.2269 0.4231 0.4809
(:,:,2) =
0.3921 0.4386 0.7380
0.3432 0.0597 0.1825
0.7290 0.3980 0.1755
(:,:,3) =
0.5316 0.8494 0.7224
0.5318 0.7245 0.3230
0.6344 0.6110 0.3618
% find the location of the ones
[d1_idx, d2_idx, d3_idx] = ind2sub(size(mn3_some_ones), find(mn3_some_ones<0.5));
% the set of locations
disp([d1_idx, d2_idx, d3_idx]);
2 1 1
3 1 1
3 2 1
3 3 1
1 1 2
2 1 2
1 2 2
2 2 2
3 2 2
2 3 2
3 3 2
2 3 3
3 3 3Finding max of matrix column by column, then obtain the linear index associated with the max values.
randMat = rand(5,3);
disp(randMat);
0.2283 0.4309 0.8934
0.2937 0.4937 0.9442
0.6310 0.4258 0.5018
0.0921 0.3123 0.6240
0.4337 0.4264 0.1156
[maxVal maxIndex] = max(randMat);
linearIndex = sub2ind(size(randMat),maxIndex,(1:1:size(randMat,2)))
linearIndex = 1x3
3 7 12
randMat(linearIndex)
ans = 1x3
0.6310 0.4937 0.9442
t_pV = [1,2;3,4;5,6];
t_pV_Ind = [1,1;0,0;1,1];
[maxVal maxIndex] = max(t_pV(t_pV_Ind==1))
maxVal = 6
maxIndex = 4% Subset count
it_n = 5;
% Example 1, long array
ar_fl_a = 1:1.1:100;
ar_it_subset_idx = unique(round(((0:1:(it_n-1))/(it_n-1))*(length(ar_fl_a)-1)+1));
ar_fl_a_subset = ar_fl_a(ar_it_subset_idx);
disp(ar_fl_a_subset);
1.0000 26.3000 50.5000 75.8000 100.0000
% Example 2, Short Array
ar_fl_a = 1:1.1:3;
ar_it_subset_idx = unique(round(((0:1:(it_n-1))/(it_n-1))*(length(ar_fl_a)-1)+1));
ar_fl_a_subset = ar_fl_a(ar_it_subset_idx);
disp(ar_fl_a_subset);
1.0000 2.1000
% Write As function
f_subset = @(it_subset_n, it_ar_n) unique(round(((0:1:(it_subset_n-1))/(it_subset_n-1))*(it_ar_n-1)+1));
% Select 5 out of 10
disp(f_subset(5, 10));
1 3 6 8 10
% Select 10 out of 5
disp(f_subset(10, 5));
1 2 3 4 5
% Select 5 out of 5
disp(f_subset(5, 5));
1 2 3 4 5