DSA Part 2: Mathematics | ahampriyanshu

Number System

Types of number

Types of number system

Number system consists values from 0 to N-1

Number Series

Number Sequences

Arithmetic progression

$2, 4, 6, 8, \ldots$

$\rightarrow a_{1} = a + 0.d $

$\rightarrow a_{2} = a + 1.d $

$\rightarrow a_{3} = a + 2.d $

$ \vdots $

$\rightarrow T_{n} = a + (n-1) \cdot d $

We know that

$\rightarrow avg = \frac{sum}{n}$

$\rightarrow sum = avg \times n$

And in case of evenly distributed numbers

$\rightarrow avg = \frac{first + last}{2}$

$\rightarrow sum = \frac{(a + a + (n-1).d)n}{2}$

$\rightarrow S_n = \frac{n(2a + (n-1)*d)}{2}$

Geometric progression

2, 4, 16, 32, 64 ……

a, $a.r^{1}$, $a.r^{2}$, $a.r^{3}$, … $r^{n-1}$

Nth term $\rightarrow$ $T_{n} = a*r^{n-1}$

Sum till N terms $\rightarrow$ $S_{n} = a*(r^{n} - 1)/ r-1$

Sum of infinite terms $\rightarrow$ $S_{\infty} = \frac{a}{1-r}$

Harmonic Progression

Harmonic progression (or harmonic sequence) is a progression formed by taking the reciprocals of an arithmetic progression. $\rightarrow \frac{1}{5}, \frac{1}{10}, \frac{1}{15}, \ldots$

Nth term $\rightarrow$ $T_{n} = \frac{1}{a + (n-1) \cdot d}$

Average

Mean

The central of middle value in a set of data. Commons ways to calculate average are mean, median, mode.

Suppose

$a_{1}, a_{2}, a_{3}, …. , a_{n}$

Mean is the arithmetic average of a given data.

$\rightarrow mean = \frac{a_{1} + a_{2} + a_{3} + …. + a_{n}}{n}$

Types of Mean

$\rightarrow GM^2 = AM \times GM $

Median

Median is the middle value

$\rightarrow median = A[\frac{n+1}{2}] if n is odd else \frac{A[\frac{n}{2}] + A[\frac{n+1}{2} + 1]}{2} $

Mode

Mode is the number with the maximum frequency

$\rightarrow 3 Median = 2 Mean + Mode $

Quadratic formula

Roots of quad eq.

$ax^{2} + by + c = 0$

$x=\frac{-b\pm\sqrt{b^2-4ac}}{2a}$.

$D = b^{2} - 4ac$

• D < 0 : Imaginary roots
• D = 0 : Two equal roots
• D > 0 : Two distinct roots

Prime numbers

2,3,5,7,11, ….

All the numbers having exactly two factors.

Can be represented as 6n+1 or 6n-1, except 2 and 3.

2 and 3 are only consecutive prime numbers.

Test Of Divisibility

HCF and LCM

There are three ways to find HCM and LCM

1. Listing factors/multiple
2. Prime fractorization
3. Division method

$\rightarrow a\times b = HCF(a,b) \times LCM(a,b)$

HCF of co-primes is 1.

For fractions

$ HCF = \frac{HCF(Numerators)}{LCM(Denominators)} $

$ LCM = \frac{LCM(Numerators)}{HCF(Denominators)} $

Area

Rectangle

$\rightarrow area = length \times bread$

$\rightarrow perimeter = 2 ( length + bread)$

Square

$\rightarrow area = side^{2} $

$\rightarrow perimeter = 4 \times side$

Rhombus

$\rightarrow area = \frac{product of diagonals}{2} $

Equilateral Triangle

$\rightarrow area = \frac{ \sqrt{n} \times side^{2}}{4} $

$\rightarrow radius of incircle = \frac{side}{2 \times \sqrt{3}} $

$\rightarrow radius of circle = \frac{side}{\sqrt{3}} $

Isosceles Triangle

$\rightarrow area = \frac{base \times length}{2} $

Heron’s Formula

$\rightarrow area = \sqrt{s(s-a)(s-b)(s-c)} $

where s is semi-perimeter

$\rightarrow s = \frac{a + b + c}{2}$

Circle

$\rightarrow area = \pi \times R^{2} $

$\rightarrow circumference = 2 \times \pi \times R $

Parallelogram

$\rightarrow area = base \times height $

Volume

Cuboid

$\rightarrow Volume = L \ast B \ast H $

$\rightarrow Surface area = 2 \cdot (LB + BH + LH) $

$\rightarrow Diagonal = \sqrt{L^2 + B^2 + H^2} $

Cube

$\rightarrow Volume = a^3 $

$\rightarrow Surface area = 6 \cdot a^2 $

$\rightarrow Diagonal = \sqrt{3}a $

Cylinder

$\rightarrow Volume = \pi r^2h $

$\rightarrow Curved surface area = 2 \pi rh $

$\rightarrow Total surface area = 2 \pi rh + 2 \pi r^2 $

Cone

$\rightarrow Slant height = \sqrt{h^2 + r^2} $

$\rightarrow Volume = \frac{\pi r^2 h}{3} $

$\rightarrow Curved surface area = \pi rL $

$\rightarrow Total surface area = \pi rL + \pi r^2 $

Sphere

$\rightarrow Volume = \frac{4 \pi r^3}{3} $

$\rightarrow Surface area = 4 \pi r^2 $

Trignometry

$Radian = \frac{\pi}{180} \times θ$

Trignometric Ratios

$ sin θ = \frac{Perpendicular}{Hypotenuse} $

$ cos θ = \frac{Base}{Hypotenuse} $

$ tan θ = \frac{Perpendicular}{Base} $

$ sec θ = \frac{Hypotenuse}{Base} $

$ cosec θ = \frac{Hypotenuse}{Perpendicular} $

$ cot θ = \frac{Base}{Perpendicular} $

Fundamental Trignometric identities

1. $sin^2 A + cos^2 A = 1$
2. $1 + tan^2 A = sec^2 A$
3. $1 + cot^2 A = cosce^2 A$

Reciprocal Identities

$sin θ = \frac{1}{cosec θ} $

$cos θ = \frac{1}{sec θ} $

$tan θ = \frac{1}{cot θ} $

Trigonometry Table

Periodicity Identities

First Quadrant:

• $sin (π/2 – θ) = cos θ$
• $cos (π/2 – θ) = sin θ$
• $sin (π/2 + θ) = cos θ$
• $cos (π/2 + θ) = – sin θ$

Second Quadrant:

• $sin (3π/2 – θ) = – cos θ$
• $cos (3π/2 – θ) = – sin θ$
• $sin (3π/2 + θ) = – cos θ$
• $cos (3π/2 + θ) = sin θ$

Third Quadrant:

• $sin (π – θ) = sin θ$
• $cos (π – θ) = – cos θ$
• $sin (π + θ) = – sin θ$
• $cos (π + θ) = – cos θ$

Fourth Quadrant:

• $sin (2π – θ) = – sin θ$
• $cos (2π – θ) = cos θ$
• $sin (2π + θ) = sin θ$
• $cos (2π + θ) = cos θ$

Co-function Identities

• sin(90° − x) = cos x
• cos(90° − x) = sin x
• tan(90° − x) = cot x
• cot(90° − x) = tan x
• sec(90° − x) = cosec x
• cosec(90° − x) = sec x

Inverse Formulas

• $sin^{-1} (-x) = -sin^{-1} x$

• $cos^{-1} (-x) = π - cos^{-1} x$

• $tan^{-1} (-x) = -tan^{-1} x$

• $cosec^{-1} (-x) = -cosec^{-1} x$

• $sec^{-1} (-x) = π - sec^{-1} x$

• $cot^{-1} (-x) = π - cot^{-1} x$

Logarithm

Logarithm is the inverse function to exponentiation.

$ \log_a{b} = c \implies a^c = b $

$ \log_2{8} = 3 \implies 2^3 = 8 $

Types of logs

• Common log $\rightarrow$ base 10 $\rightarrow log_10{x} $
• Natural log $\rightarrow$ base e $\rightarrow log_e{x}$ or $ lnx $
• Binary log $\rightarrow$ base 2 $\rightarrow log_2{x} $

Laws of logarithms

Addition Property

$\log_ab + \log_ac = \log_a{bc}$

Subtraction Property

$\log_ab - \log_ac = \log_a{\frac{b}{c}}$

Argument-Power Property

$\log_ab^n = n\log_ab$

Inverse Property

$\log_ab = \frac{1}{\log_ba}$

$\log_a{\frac{1}{b}} = - \log_ab$

Power Property

$\log_{a^n}b^n = \log_ab$

Change-of-Base

$\frac{\log_cb}{\log_ca} = \log_ab$

• $log_a{1} = 0$
• $log_aa = 1$

Problems

Number of digits in an integer

Iterative

count(n){
    int cnt = 0;
    while(n){
        cnt += n%10;
        n /= 10;
    }

    return cnt;
}

Recursive

count(n){
    if(!n) return n;
    return 1+count(n)l
}

Logarithmic

count(n){
    return floor(log(n) + 1);
}

Check if the given integer is a palindrome or not.

bool isPal(int n){
  int rev = 0;
  int tmp = n;

  while(tmp){
    int ones = tmp % 10;
    rev = rev * 10 + ones;
    tmp /= rmp;
  }

  return rev == n;
}

Factorial of a number

Iterative

int fact(int n);

int res = 1;

for(int i=2; i<=n; i++)
  res *= i;

return res;
}

Recursive

int fact(int n){
  if(!n) return 1;
  return n * fact(n-1);
}

Count trailing zeros in the factorial of a number

int ctz(int n){
  int res = 0;
  for(int i=5; i<=n; i *= 5)
    res += n/i;
  return res;
}

TC : O(log5n)

GCD of two numbers

Naive

int gcd(int a, int b){
  int res = min(a, b);

  while(res){
    if(a%res == 0 and b%res == 0)
      break;
    res--;
  }

  return res;
}

Time Complexity: O(min(a,b))

Euclidean Algorithm

int gcd(int a, int b){
  while(a != b)
    if(a>b)
      a = a-b;
    else
      b = b-a;
  return a;
}

Optimized Euclidean Algorithm

int gcd(int a, int b){
  if(b==0)
  return a;
  return gcd(b, a%b);
}

Time Complexity: O(log max(a,b))

Extended Euclidean Algorithm

int gcd(int a, int b, int *x, int *y)
{
    if (a == 0)
    {
        *x = 0;
        *y = 1;
        return b;
    }

    int res = gcd(b%a, a, &x1, &y1);

    *x = y1 - (b/a) * x1;
    *y = x1;

    return res;
}

LCM of two numbers

Naive

int gcd(int a, int b){
  int res = max(a, b);

  while(res){
    if(res%a == 0 and res%a == 0)
      break;
    res++;
  }

  return res;
}

Time Complexity: O(a*b - max(a,b))

Efficient Approach

$\rightarrow a\times b = gcd(a,b) \times lcm(a,b)$

$\rightarrow lcm(a,b) = \frac{a\times b}{gcd(a,b)}$

Time Complexity: O(log max(a,b))

Prime number

Naive approach

bool isPrime(int n)
{
    if (n <= 1)
        return false;

    for (int i = 2; i < n; i++)
        if (n % i == 0)
            return false;

    return true;
}

Time Complexity: O(n)

Efficient approach

bool isPrime(int n)
{
    if (n <= 1)
        return false;

    for (int i = 2; i*i <= n; i++)
        if (n % i == 0)
            return false;

    return true;
}

Time Complexity: O($\sqrt{n}$)

Optimized approach

bool isPrime(int n)
{
    if (n <= 1)
        return false;
    if (n <= 3)
        return true;

    if (n % 2 == 0 || n % 3 == 0)
        return false;

    for (int i = 5; i * i <= n; i = i + 6)
        if (n % i == 0 || n % (i + 2) == 0)
            return false;

    return true;
}

Prime factorization of a number

Naive

bool isPrime(int n)
{
    if (n <= 1)
        return false;
    if (n <= 3)
        return true;

    if (n % 2 == 0 || n % 3 == 0)
        return false;

    for (int i = 5; i * i <= n; i = i + 6)
        if (n % i == 0 || n % (i + 2) == 0)
            return false;

    return true;
}

void primeFactors(int n)
{
    for (int i = 2; i <= n; i = i + 2)
    {

      if(isPrime(i))

      int x = i;

      while (n % x == 0)
      {
      cout << i << " ";
      x = x*i;
      }
    }

}

Time Complexity: O($nlogn $)

Efficient

void primeFactors(int n)
{
    if (n <= 1) return;

    for (int i = 2; i*i <= n; i = i + 2)
    {
        while (n % i == 0)
        {
            cout << i << " ";
            n = n/i;
        }
    }

    if (n > 1)
        cout << n << " ";
}

Time Complexity: O($\sqrt{n} logn $)

Using Sieve

void primeFactors(int n)
{
    int c=2;
    while(n>1)
    {
        if(n%c==0){
        cout<<c<<" ";
        n/=c;
        }
        else c++;
    }
}

Time Complexity: O(n)

Print all divisors in ascending order

Naive

void printDivisors(int n)
{
    for (int i = 1; i <= n; i++)
        if (n % i == 0)
            cout <<" " << i;
}

Time Complexity: O(n)

Efficient

void printDivisors(int n)
{
    for (int i=1; i*i<=n; i++)
    {
        if (n%i == 0)
          cout << i << " ";
    }

        for (; i>=1; i--)
    {
        if (n%i == 0)
          cout << n/i << " ";
    }
}

Time Complexity: O($\sqrt{n}$)

N Prime Numbers

Naive

void nPrimes(){
  for(int i=2; i<=n; i++)
    if(isPrime(i))
      cout << i << " ";
}

Time Complexity: O($n \times \sqrt{n}$)

Sieve of Eratosthenes

void manipulated_seive(int n)
{

  vector<bool> isPrime(n+1, true);


  for (int i=2; i*i<=n ; i++)
  {
    if (isprime[i])
    {
      cout << i << " "
      for(int j=i*i; j<=n; j+= i)
        isPrime[j] = false;
    }
  }
}

Time Complexity: O($ log log n $)

Computating Pow(x,n)

Naive

FOR(1->n) : x = x*x;

Time Complexity: O(n)

Optimized

double myPow(double x, int n) {
        if(n==0) return 1.0;
        double y = myPow(x, n/2);

        if(n % 2 == 0)
            return y*y;
        else return n < 0 ? (y*y)/x : x*y*y;
}

Time Complexity: O(logn)

Constant Space

$\rightarrow $ Every natural number can be written as the sum of distinct powers of 2.

double myPow(long long int x, long long int n) {
  long long int res = 1;
  while(n>0){

    if(n&1)
    res = res * x;

    x *= x;
    n = n >> 1;
  }
  return res;
}

Time Complexity: O(logn)