Predicting COVID cases

A researcher at UC San Diego Health now wants to predict COVID-19 cases in the next few days!

She has a list cases which contains the current number of cases in San Francisco, Santa Barbara, Los Angeles, and San Diego.

cases = [12508, 9969, 310595, 57409]

She also has a list predicted_growths which contains the predicted number of new cases for every city in the next few days.

For example:

Suppose today is 11/02/2020,

predicted_growths = [100, 200, 300]

which means that the predicted number of new cases on 11/03/2020 is 100 for every city, the predicted number of new cases on 11/04/2020 is 200 and the predicted number of new cases on 11/05/2020 is 300.

Your job: Define a function predict(cases, predicted_growths) using nested for-loops, help the researcher print out the predicted number of all cases for each city in the next k days, where k is the length of predicted_growths. Note: you can assume that cases and predicted_growths are lists, and that k == len(predicted_growths) > 0. It’s okay to update cases.

Sample 1:

cases = [12508, 9969, 310595, 57409]
predicted_growths = [100, 200, 300]

You should print:

[12608, 10069, 310695, 57509]
[12808, 10269, 310895, 57709]
[13108, 10569, 311195, 58009]

Sample 2:

cases = [12508, 9969, 310595, 57409]
predicted_growths = [1000, 2000, 3000, 4000]

You should print:

[13508, 10969, 311595, 58409]
[15508, 12969, 313595, 60409]
[18508, 15969, 316595, 63409]
[22508, 19969, 320595, 67409]

Sample 3:

cases = [12508, 9969, 310595, 57409]
predicted_growths = [10000]

You should print:

[22508, 19969, 320595, 67409]