LANGUAGE IS PYTHON 9. 14 LAB: Brute force equation solver

Numerous engineering and scientific applications require finding solutions to a set of equations. Ex: 8x + 7y = 38 and 3x - 5y = -1 have a solution x = 3, y = 2. Given integer coefficients of two linear equations with variables x and y, use brute force to find an integer solution for x and y in the range -10 to 10.

Ex: If the input is:

8

7

38

3

-5

-1

Then the output is:

x = 3 , y = 2

Use this brute force approach:

For every value of x from -10 to 10

For every value of y from -10 to 10

Check if the current x and y satisfy both equations. If so, output the solution, and finish.

Ex: If no solution is found, output:

There is no solution

Fast sportcars the top speeds of sportscars, given in miles per hour, are: 155 mph bmw m5 217 mph lamborghini aventador spyder 205 mph ferrari 488 205 mph nissan gtr 197 mph chevrolet corvette stingray zr1 258 mph bugatti veyron supersport 195 mph dodge viper 270 mph hennessey venom 155 mph bmw m3 195 mph mercedes sl given: topspeeds=[155; 217; 205; 205; 197; 258; 195; 270; 155; 195]; carnames=string(["bmw m5" "lamborghini aventador spyder" "ferrari 488" "nissan gtr" "chevrolet corvette stingray zr1" "bugatti veyron supersport" "dodge viper" "hennessey venom" "bmw m3" "mercedes sl"]); the variable is a rectangular array. write a function called selectcars to identify cars with the top speed within a given range, and display the identified names. the selected cars speed will be in a range given by lowerbound < speed < upperbound. inputs to the function selectcars are: a column array os all car top speeds named topspeeds, the corresponding chara

17. implement the jvm dload instruction for the mic-2. it has a 1-byte index and pushes the local variable at this position onto the stack. then it pushes the next higher word onto the stack as well

1. package newton’s method for approximating square roots (case study 3.6) in a function named newton. this function expects the input number as an argument and returns the estimate of its square root. the script should also include a main function that allows the user to compute square roots of inputs until she presses the enter/return key. 2. convert newton’s method for approximating square roots in project 1 to a recursive function named newton. (hint: the estimate of the square root should be passed as a second argument to the function.) 3. elena complains that the recursive newton function in project 2 includes an extra argument for the estimate. the function’s users should not have to provide this value, which is always the same, when they call this function. modify the definition of the function so that it uses a keyword parameter with the appropriate default value for this argument, and call the function without a second argument to demonstrate that it solves this problem. 4. restructure newton’s method (case study 3.6) by decomposing it into three cooperating functions. the newton function can use either the recursive strategy of project 1 or the iterative strategy of case study 3.6. the task of testing for the limit is assigned to a function named limitreached, whereas the task of computing a new approximation is assigned to a function named improveestimate. each function expects the relevant arguments and returns an appropriate value. 5. a list is sorted in ascending order if it is empty or each item except the last one is less than or equal to its successor. define a predicate issorted that expects a list as an argument and returns true if the list is sorted, or returns false otherwise. (hint: for a list of length 2 or greater, loop through the list and compare pairs of items, from left to right, and return false if the first item in a pair is greater.)