syphh

function dynamicSumSubmatrices(mat){
    // n and m represent dimensions of the matrix
    let n = mat.length;
    let m = mat[0].length;
  
    // declaring a (n*m) matrix
    let sumMat = [...new Array(n)].map(row => [...new Array(m)]);
  
    // part 1
    sumMat[0][0] = mat[0][0];

syphh

function sumSubmatrices(mat){
    // n and m represent dimensions of the matrix
    let n = mat.length;
    let m = mat[0].length;
  
    // declaring a (n*m) matrix
    let sumMat = [...new Array(n)].map(row => [...new Array(m)]);
  
    for(let i = 0; i < n; i++){
        for(let j = 0; j < m; j++){

syphh

let randomMat = [...new Array(100)].map(row => [...new Array(100)].map(cell => Math.floor(Math.random() * 10)));

syphh

function foo(){
  console.time();
  // function code
  console.timeEnd();
}

syphh

function isLowerTriangular(mat){
  let matSize = mat.length;
  for(let i = 0; i < matSize; i++){
    for(let j = i+1; j < matSize; j++){
      if(mat[i][j] != 0)
        return false;
    }
  }
  return true;
}

syphh

class Node:
    def __init__(self, val=0, neighbors=None):
        self.val = val
        self.neighbors = neighbors if neighbors is not None else []


def dfs(node, node_map):
    clone = Node(node.val)
    node_map[node.val] = clone
    for neighbor in node.neighbors:

syphh

def is_safe(board, i, j):
    n = len(board)
    j_left = j
    j_right = j
    while i >= 0:
        if (j_left >= 0 and board[i][j_left] == 1) or board[i][j] == 1 or (j_right < n and board[i][j_right] == 1):
            return False
        i -= 1
        j_left -= 1
        j_right += 1

syphh

import numpy as np

def approximate_pi(n):
    points = np.random.uniform(-1, 1, (n, 2))
    inside = np.sum(points[:,0]**2+points[:,1]**2 <= 1)
    k = inside/n
    return 4*k


n = 1000000

syphh

from typing import List, Any

class Node:
    def __init__(self, key, value, nxt=None):
        self.key: str = key
        self.value: Any = value
        self.nxt: Node = nxt
        

class LinkedList:

syphh

import numpy as np
import matplotlib.pyplot as plt


def midpoint(p1, p2):
    x1, y1 = p1
    x2, y2 = p2
    return (x1+x2)/2, (y1+y2)/2