MatLab (MATrix LABoratory)

MATLAB is a high-level language and interactive environment built for numerical computing, matrix operations, data analysis, visualization, and algorithm development.

It is widely used in engineering, research, AI/ML, signal processing, control systems, and finance.

Learning Path

• MATLAB On Ramp
• Deep Learning On Ramp
• Machine Learning on Ramp
• Reinforced Lerning on Ramp
• Fundamental Of Programming

Finding Help

doc fn = document for function

% To add comment

• pwd :to get current directory
• cd : change directory
• ls : list directory
• who : view variable in current scope
• whos : Detailed view of variable sin scope
• clear: clear variables in current workspace

Data Types

Numeric Types

Integer and floating-point data

• unsigned Int: uint8/16/32/64
• signed Int: int8/16/32/64
• single : 4 byte float
• double : 8 byte double precision

Characters and Strings

Text in character arrays and string arrays

Dates and Time

Arrays of date and time values that can be displayed in different formats

Categorical Arrays

Arrays of qualitative data with values from a finite set of discrete, nonnumeric data

Tables

Arrays in tabular form whose named columns can have different types

Timetables

Time-stamped data in tabular form

Structures

Arrays with named fields that can contain data of varying types and sizes

Cell Arrays

Arrays that can contain data of varying types and sizes

Function Handles

Variables that allow you to invoke a function indirectly

Map Containers

Objects with keys that index to values, where keys need not be integers

Time Series

Data vectors sampled over time

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Precision of Variables in Workspace

format long // Upto 10+ decimal places

format short // Upto 4 decimal places

Variable:

• starts with alphabets
• contain a_z, A_Z , 0..9, & _
• MatLab automatically show suggestion for incorrect variables
• Can see data value by entering variable name

Saving & Loading Variables

Save all Variables in MAT File

save <filename>.mat

Save Single variable in MAT file

save <filename>.mat <variableName>

Save all Variables in Readable File format

save <filename>.txt -ascii

Load Saved Variables

load <filename>.mat
load <filename>.dat

Load Single Saved Variables

load <filename>.mat <variableName>

Empty WorkSpace

clear

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Creating Arrays & Matrix

    magic(n,m)  sum of rows, column , diagonal is same


   x = [7 9]      // row array or row vector [element  element]
   x= x'          // Transpose into column vector
   ( A')'==A        // Double transpose is same
  
    x = start:end          // Shortcut create Row Vector [1,2,3,4]
    x=  start: step: step    // shortcut create Row Vector 1 to 5 step 0.5 [1,1.5,2,2.5, 3,3.5,4,4.5 5]
    x= (start: step: step)' // shortcut create Column Vector 1 to 5 step 0.5 

    x = linspace(start ,end ,space)   // equidistance  rowvector 
    x = linspace(start ,end ,space)'  //  equidistance columnn vector

• , Rows
• ; Column

    x = [7,9]       // row array [element , element]
    x = [7;9]       // column array [element ; element]
    x = [4,5 ; 7,9] // 2d Matrix [ROW; ROW]
    
    x = rand(n)    // Generate  nxn matrix with random number
    x = rand(n,m)  // Generate  nxm matrix with random number
    
    x = zeros(n,m) // Generate  nXm matrix with zero elements
    x = ones(n,m) // Generate nxm unit matrix   
    
    x= eye(n,m) // GenerateIdentity Matrix
    x= eye(n)   // Generate nxn Identity Matrix

Tricks

A.*eye(n) = diagonal matrix of A

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Reading Values from Matrix

• Indexing starts with 1

     length(V)              // Length of Vector
     size(A)                // size of matrix
     [dr, dc] = size(A)     // Size in dr,dc
     [vMax, ivMax]= max(A)   // Max Value and its Index
     
     A(:)   // convert Matrix into single column Vector
    
     A(i)     // ith element of Vector
     A(n:m)   // All elements from n to m index of Vector

     A(i,j)    // ith row, jth column of Matrix 
     A(end,j)  // last row j column 
     A(n, :)  // Get all elements of nth Row
     A(:, n)   // Get all elements of nth Column
     A(:, end-1:end) // all elements of last 2 column
     A([a,b], :) // all elements of a, b rows

Tricks

     [vMax, ivMax]= max(A)   // Max Value and its Index
     max(A,[],1)             // return max per column
     max(A,[],2)             // return max per row

     max(A(:))  // max eleemnt in A
     
     sum(A,1)  // per column sum
     sum(A,1)  // per row sum
     
     A.*eye(n)  = diagonal matrix of A
     
     sum(sum(A.*eye(n))) = sum of all diagonal elements of A

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Update Values in Matrix

    
    A(i) = b      // modify A(i)th element  to b
    A(i,j) = b    // modify A(i,j)th element to b 
    
    C =[A,B] = [A B]  // concate B after last column of A
    C =[A;B]          // concate B below last row of A
    
    A =[A,[a;b;c]]  // append a,b,c  as last column in A

• Operation on Matrix applies on all elements of matrix

     A + b        // Add Scaler b to all elements of Matrix A
     A / b        // Divide Scaler b to all elements of Matrix A
       
     A<3        // element wise compare and return binary Matrix
     [r,c] = find(A<3) // return row and column index matrix(r & c) satisfying
     
      A + B        // Add A+ B
      A.*B         // Multiply A.*B

Functions

    fn(A)        // Math fn on all elements of Matrix A eg sqrt, abs, log
    
    sum(A)    //  Add up all elemnts
    prod(A)    // Return product of all elements
    
    floor(A)  // floor (0,5-> 0)
    ceil(A)   // round (0,5->1)

Inverse

    pinv(A)     //Inverse of Matrix
    pinv(A)*A  // Identity Matrix of A

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