Question

Pycharm

Write a function to make a new list

1. if original_samples is [1,2,3], then this should return a new list [3,2,1]. Don't use the reversed function or original_samples[::-1]

def make_reserved_samples (original_samples):

new_samples[ ]

  

return new_samples

2. multiplied by volume. If original_samples is [1,2,3] and volume is 2, the new list is [2,4,6]

def make_louder_samples(original_samples, volume):

return [ ]

3. If the original list is [1,2,3,4,5,6,7,8] and skip is 3, the new liat should be [1,4,7]. Don't use original_list[::skip]. you must use a loop to find the desired elements.

def make_reduced_samples(original_samples, skip):

return[ ]

4. if original samples is [-5,-1,2,5,10] and clip level is 4, then new liat would be [-4,-1,2,4,4]

def make clipped_samples(original_samples, clip_level):

return [ ]

5. if the original list is [10,20,30] and noise_level is 2, the a new list is [8,21,29] if the random ints picked happened to be -2,-1,-1 return the new list

def make_noisy_samples(origianl_samples, noise_level):

return [ ]

6. write a function to make a tone. Each "sawtooth" should be valus going from -10000 to 10000 counting by 1000. So the elements should be -10000,-9000,-8000,-7000,-6000, .........., 7000,8000,9000,10000. Then there should be 1000 sawtooths.

def make_tone( ):

return [ ]

Answer 1

1.)

def make_reserved_samples (original_samples):
    c = len(original_samples)-1
    while c >= 0:
        new_samples.append(original_samples[c])
        c = c - 1
    return new_samples
original_samples=[1,2,3]
new_samples=[]
print(make_reserved_samples (original_samples))

2.)

def make_louder_samples(original_samples, volume):
    for o in original_samples:
        new_samples.append(o*volume)
    return new_samples
original_samples=[1,2,3]
new_samples=[]
print(make_louder_samples(original_samples,2))

3.)

def make_reduced_samples(original_samples, skip):
    new_list = []
    i = 0
    for a in original_samples:
        if i <= len(original_samples):
            new_list.append(original_samples[i])
            i += skip

    return new_list
original_samples=[1,2,3,4,5,6,7,8]
print(make_reduced_samples(original_samples,3))

4.)

import numpy as np 
def make_clipped_samples(original_samples, clip_level):
    new_list = np.clip(original_samples, a_min = - clip_level , a_max = clip_level) 

    return new_list
original_samples=[-5,-1,2,5,10] 
print(make_clipped_samples(original_samples,4))

I have provided solution for 4 questions.Hope it helps you