Struggle with logical indexing

Hey,

I'm wokring on some data for a research project and I'm still pretty new to matlab. I would like to extract information from an array given specific conditions.

% Find incorrect answers (incorrect answer = 0) that were given with high confidence (high confidence = > 0.5)

c = find((temp_data_bundle.data_falt(:,21) > 0.5) & (temp_data_bundle.data_falt(:,13) == 0))

% Find the corresponding question

question = temp_data_bundle.data_falt(c,8) 

% Find the run in which the answer was given (there are 6 runs in total)

run = temp_data_bundle.data_falt(c,3)

To explain it more clearly:

The participant gave an erroneous response (but with high confidence that the response is correct) regarding question 6. Each question (1-10) will be repeated 4 times. In this case the participant will have 3 chances left to correct his answer regarding question 6. Now I would like to extract these 3 trials that are left and their responses regarding that specific question.

I would be very pleased if someone could give me a hint. Have a nice day!

Answer 1

[Steven Lord]

You're not actually using logical indexing, you're using subscripted indexing. If you omitted the find call where you defined c you would be using logical indexing (in one of the dimensions.)

A = magic(5)

A = 5×5

17 24 1 8 15 23 5 7 14 16 4 6 13 20 22 10 12 19 21 3 11 18 25 2 9

logicalIndices = A(:, 3) > 10

logicalIndices = 5×1 logical array
   0
   0
   1
   1
   1

subscriptIndices = find(logicalIndices)

subscriptIndices = 3×1

3 4 5

useLogicalIndices = A(logicalIndices, :)

useLogicalIndices = 3×5

4 6 13 20 22 10 12 19 21 3 11 18 25 2 9

useSubscriptIndices = A(subscriptIndices, :)

useSubscriptIndices = 3×5

4 6 13 20 22 10 12 19 21 3 11 18 25 2 9

Given that clarification, I'm not quite sure what your question means, "Now I would like to extract these 3 trials that are left and their responses regarding that specific question." Perhaps if you showed a few representative rows of your data in temp_data_bundle.data_falt and explained the meanings of each column (do some of them represent the 'trials' aka chances for a user to answer a question?) we might be able to offer some guidance.

As a suggestion I might consider storing the data in a table array and giving each variable in the table a descriptive name, something like:

% Random / arbitrary sample data
questionNumber = [1; 1; 2; 3; 4];
trialNumber = [1; 2; 1; 1; 1];
rng default
answer = randi(4, 5, 1);
confidence = rand(5, 1);
correct = answer == 3;

% The table
T = table(questionNumber, trialNumber, answer, confidence, correct)

T = 5×5 table
    questionNumber    trialNumber    answer    confidence    correct
    ______________    ___________    ______    __________    _______

          1                1           4        0.09754       false 
          1                2           4         0.2785       false 
          2                1           1        0.54688       false 
          3                1           4        0.95751       false 
          4                1           3        0.96489       true  

With this you can write more descriptive code.

wasWrongAnswerWithHighConfidence = (~T.correct) & (T.confidence > 0.9)

wasWrongAnswerWithHighConfidence = 5×1 logical array
   0
   0
   0
   1
   0

wrongAnswers = T.answer(wasWrongAnswerWithHighConfidence) % or

wrongAnswers = 4

subtable = T(wasWrongAnswerWithHighConfidence, :)

subtable = 1×5 table
    questionNumber    trialNumber    answer    confidence    correct
    ______________    ___________    ______    __________    _______

          3                1           4        0.95751       false