Logical Vectors and Logical Indexing

Return to List of Lectures

Previous Lecture

• Misc
  • MLC hours when math 230 specialists available
    • Monday 10:30 - 1:30pm, 8:30 - 10:00pm
    • Tuesday 12:30 - 1:30pm, 2:30 - 3:30pm, 7:00 - 10:00pm
    • Wednesday 10:30 - 1:30pm, 7:00 - 10:00pm
    • Thursday 11:30 - 3:30pm, 7:00 - 10:00pm
    • Friday 10:30 - 1:30pm
  • “Flatland” movie
    • This afternoon (Feb. 10), 2:30, Newton 201
• Questions?
• Logical Indexing and Logical Values
  • Sections 5.10 - 5.13
    • Logical arrays (elements are true/false logical values) and indexing
      • Accesses elements where indexing vector is true
    • Relational operators (e.g., >, >=, <=, <, ==, ~=)
    • Logical operators (& (and), | (or), ~ (not), xor (exclusive or))
  • Examples / practice
    

    >> % Find elements less than 0.5 in vector of random numbers
    >> v = rand( 1, 6 )
    v =
        0.2785    0.5469    0.9575    0.9649    0.1576    0.9706
    >> smallPositions = v < 0.5
    smallPositions =
         1     0     0     0     1     0
    >> v( smallPositions )
    ans =
        0.2785    0.1576
    >> % How many of those small numbers were there?
    >> length( v( smallPositions ) )
    ans =
         2
    >> sum( smallPositions )
    ans =
         2
    >> % Pick out the elements that aren’t less than 0.5
    >> newV = v( [false true true true false true ] )
    newV =
        0.5469    0.9575    0.9649    0.9706
    >> newV = v( v >= 0.5 )
    newV =
        0.5469    0.9575    0.9649    0.9706
    >> newV = v( ~ smallPositions )
    newV =
        0.5469    0.9575    0.9649    0.9706
    >> % Literally remove the elements less than 0.5 from the vector
    >> v
    v =
        0.2785    0.5469    0.9575    0.9649    0.1576    0.9706
    >> v(smallPositions) = []
    v =
        0.5469    0.9575    0.9649    0.9706
    >> % Pick out elements between -0.1 and +0.1 in another random vector
    >> v2 = rand( 1, 6 ) - 0.5
    v2 =
        0.4572   -0.0146    0.3003   -0.3581   -0.0782    0.4157
    >> v2( -0.1 <= v2 & v2 <= 0.1 )
    ans =
       -0.0146   -0.0782

• Vector Lab
  • Do you need a findPeaks function?
    • If help findpeaks produces something, or typing findp and then pressing the tab key in the command window offers findpeaks as a completion, then your Matlab has it
  • How to use it?
    • Calling it without using the result opens a graph of the argument as a wave, but assigning the result to a variable suppresses that graph and yields a vector of peak values you can use elsewhere
      

      >> wave = sin( 6 * linspace(0,2*pi,100) );
      >> findpeaks( wave )
      >> peaks = findpeaks( wave )
      peaks =
          0.9989    0.9898    0.9989    0.9898    0.9989    0.9898

• Next
  • Nyquist’s Theorem
  • Watch video lecture on digital signals, sampling, and Nyquist’s Theorem at https://www.youtube.com/watch?v=yWqrx08UeUs

Next Lecture