fibonacci_dynamic used O(n) time and O(n) space. Design a version that uses O(n) time but only O(1) space. (Hint: Create A with exactly 3 elements.)

Please do not give solution in image format thanku

i dont know what im missing, project is due in a couple of hours and my output is just a blinking cursor. please help me. below is my source code and attatched is my project. please please help!   source code:   import random def powMod_sm(base, exp, n):    exp_b=bin(exp)    value=base    for i in range(3, len(exp_b)):        value=(value**2)%n        if exp_b[i:i+1]=='1: ':            value = (value * base)% n        return value# using the euclidean Algorithmdef computeGCD(x, y):    while y:        x, y = y, x % y    return x#Extended euclidean Algorithm method to calculate gcd and get the coefficientdef extendedGCD(a, b):    if a == 0:        return b, 0, 1    gcd, x1, y1 = extendedGCD(b % a, a)    x = y1 - (b // a)* x1    y = x1    return gcd, x, y# calculating the modular inverse using EEAdef mod_Inv(b, n):    gcd, _, t = extendedGCD(n, b)    if gcd==1:        i = t % n    elif gcd!=1:        print("Inverse is undefined")    return i#miller-rabin Primality testdef mrt(p):    if p…

1. Create a script that will take 4 vertices (total 8 numbers) then make decision whether those vertices form a square, a rectangular, a diamond (A.K.A Rhombus), a parallelogram, or just a quadrilateral. Also, the area of the shapes if the shape is a square or rectangular. [CREATE AN ARRAY FOR 4 VERTICES (TOTAL 8 NUMBERS, THEN REPEAT THE SAME PROCEDURE. The WHOLE COMPUTATION NEEDS TO BE DONE BY ACCESSING ELEMENTS IN THE ARRAY .) Taking values for the ARRAY has to be done within main(). But computation and displaying the result should be done with the USER DEFINED FUNCTION!)

The interchange implementation was supposed to be better than the transpose implementation as it implements the same algorithm without the need of copying the 640,000 elements. However, it is not. How do you explain this inconsistency?

Describe the benefits of using the merge sort in Java. What are the key steps that must be taken to ensure an efficient sorting of objects? Also, specifically think of and give a real-life scenario where Merge sort may be used Merge sort may be a better fit than Quick and Radix sorts

1. Modify the code of ElemSort.java (discussed in last class) and incorporate the merge sort code into it. You can take help from the code given in the slides. Call the mergeSort method and let your program sort your hundred element arrays. Run your code, take a screenshot and upload.

To determine the number of times each day appears in our data, slice the 'day' column from our forestfire_df feature and execute the value_counts() function on that slice. Save the results to the variable day counts.   # TODO 1.2 day_counts = display(day_counts) todo_check([ (np.all(day_counts.values == np.array([95,85,84,74,64,61,54])),'Month values did not match!') ])