- Discussion of numerical stability
- Binary decimal structure. Is it possible to represent every number exactly?
>>> a = 3.1 >>> a 3.1000000000000001 >>> a = 35.95 >>> a 35.950000000000003

- Numpy's
*round*allows you to choose the number of decimal places, but how can you floor a decimal to two places?a = floor(a * 100.0)/100.0

- In lab problem
- The plot of Office Space and Superman 3.
- Write a function named
**create_accounts**that, given input length*n*, will generate a pseudo-random list of*n*bank accounts between $0.01 and $10000.00 (inclusive). - Write a function named
**real_interest**that, given a list of account balances as input and a percentage of interest*p*, will calculate the yearly interest, compounded monthly, and update the balance of each account. Note that interest is always rounded to the nearest cent (2 decimal places). - Write a function named
**evil_interest**that, given a list of transactions as input and a percentage of interest*p*, will calculate the yearly interest, and implement the malicious plot as in the movie Office Space, where the interest is always rounded down, and the remainder is dropped into a personal account. The function should return as the amount that you were able to steal with this diabolical plot in one year. - Use
**__main__**and provide a function that will create accounts, and then run the evil interest for 25 years. Use VPython to graph the amount of money you have skimmed into your account, making one plot every year.

from numpy import round, floor from random import uniform def create_accounts(n): accounts = [] for i in xrange(n): accounts.append(round(uniform(0.01, 10000.0), 2)) return accounts def real_interest(accounts, p): for i in xrange(len(accounts)): for j in xrange(12): accounts[i] += round(accounts[i] * p/12.0, 2) def evil_interest(accounts, p): my_account = 0.0 for i in xrange(len(accounts)): for j in xrange(12): real_interest = accounts[i] * p/12.0 interest_floor = floor(real_interest * 100.0)/100.0 my_share = real_interest - interest_floor accounts[i] += interest_floor my_account += my_share return round(my_account, 2) if __name__ == "__main__": from visual import rate, color from visual.graph import gdisplay, gcurve scene = display( title="How to succeed at business without really trying", autocenter=True gdisplay( # 2D graph window parameters title="Money Illegally Earned", # Window title xtitle="Years", # Label on x-axis ytitle="Dollars", # Label on y-axis background=color.white, foreground=color.black ) green_line = gcurve(color=(0,1,0)) # Set up a green curve accounts = create_accounts(100000) my_account = 0.0 for i in xrange(25): my_account += evil_interest(accounts, 0.03) print "$", my_account green_line.plot(pos=(i, my_account))

- Discuss Part 2 of Project 2: What plots to create and what data to analyze.
- show the example plot
- generate the corresponding plots for the other two forms of percolation
- two setup questions
- study on impact of grid size is only done for unrestricted percolation
- mention possible problem with recursion limit
- point them to needed set of plot formats

- Answer questions over Part 1 and provide time to work.