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from datetime import date
from math import exp, log

Iterations, Epsilon = 20, 1.0e-5

# Requires amounts and times already converted from dates
class Transactions:
    def __init__(self):
        self.amounts, self.times = [], []
    
    def add(self, amount, time):
        self.amounts.append(amount)
        self.times.append(time)

# Requires amounts and dates. Dates then get converted to times, i.e. days
class Date_Transactions:
    def __init__(self):
        self.amounts, self.times, self.the_dates = [], [], []
    
    def add_amount_and_date(self, amount, a_date):
        self.amounts.append(amount)
        self.the_dates.append(a_date)
    
    # dates_2_times requires a second parameter, the separator in the dates.
    def dates_2_times(self, sep):
        ds = []
        for a_date in self.the_dates:
            y, m, d =[int(x) for x in a_date.split(sep)]
            ds.append(date(y, m, d))

        for a_date in ds:
            self.times.append((a_date - ds[0]).days / 365.25)
            # print('{0:.2f}'.format(self.times[-1]))

# Uses a Date_Transactions class which needs conversion to times
# irrcc requires a second parameter, the separator in the dates.
def irrcc(date_transactions, sep):
    global Iterations, Epsilon
    have_pos, have_neg = False, False
    
    # Dates haved been entered. Convert to times, i.e., days after
    # first date.
    date_transactions.dates_2_times(sep)
    
    for amount in date_transactions.amounts:
        if amount > 0.0:
            have_pos = True
            if have_neg:
                break
        elif amount < 0.0:
            have_neg = True
            if have_pos:
                break

    if have_neg and have_pos:
        u, converged = 0.0, False
        
        for i in range(Iterations):
            pos, d_pos, neg, d_neg = 0.0, 0.0, 0.0, 0.0
            # dd_pos, dd_neg = 0.0, 0.0
            # print(i)
            for j in range(len(date_transactions.amounts)):
                an_amount, a_time = date_transactions.amounts[j], date_transactions.times[j]
                tmp = an_amount * exp(u * a_time)
            
                if an_amount > 0.0:
                    pos += tmp
                    d_pos += tmp * a_time
                    # dd_pos += tmp * a_time * a_time
                else:
                    neg -= tmp;
                    d_neg -= tmp * a_time
                    # dd_neg -= tmp * a_time * a_time

            # Haley's 2nd order Newton's method
            f = log(neg / pos)
            fp = (d_neg / neg) - (d_pos / pos)
            # tmp = (neg * dd_neg - d_neg * d_neg) / neg / neg
            # fpp = tmp - ((pos * dd_pos - d_pos * d_pos) / pos /pos)
            # h_inv = -fp / f + fpp / (2 * fp)
            # delta = -1 / h_inv
            
            # First order Newton's method
            # delta = log(neg / pos) / (d_neg / neg - d_pos / pos)
            delta = f / fp
            
            u -= delta
            if abs(delta) < Epsilon:
                converged = True
                break
        if converged:
            result = -u
        else:
            result = 'No convergence'
    else:
        result = 'Bad Data!'
    
    return result

# Uses a Transactions class which already has times
def jns_irr(transactions):
    global Iterations, Epsilon
    have_pos, have_neg = False, False
    
    for amount in transactions.amounts:
        if amount > 0.0:
            have_pos = True
            if have_neg:
                break
        elif amount < 0.0:
            have_neg = True
            if have_pos:
                break

    if have_neg and have_pos:
        u, converged = 0.0, False
        
        for i in range(Iterations):
            pos, d_pos, neg, d_neg = 0.0, 0.0, 0.0, 0.0
            # print(i)
            for j in range(len(transactions.amounts)):
                an_amount, a_time = transactions.amounts[j], transactions.times[j]
                tmp = an_amount * exp(u * a_time)
            
                if an_amount > 0.0:
                    pos += tmp
                    d_pos += tmp * a_time
                else:
                    neg -= tmp;
                    d_neg -= tmp * a_time

            delta = log(neg / pos) / (d_neg / neg - d_pos / pos)
            u -= delta
            if abs(delta) < Epsilon:
                converged = True
                break
        if converged:
            result = -u
        else:
            result = 'No convergence'
    else:
        result = 'Bad Data!'
    
    return result

    
if __name__ == "__main__":
    amounts = [-1000.00, 500.00, -2000.00, -2000.00, 1500.00, 4000.00]
    dates = ['2016-03-16', '2017-09-26', '2018-01-15', '2020-04-05', '2019-05-1', '2021-01-01']

    dts = Date_Transactions()
    for i in range(len(amounts)):
        dts.add_amount_and_date(amounts[i], dates[i])

    # irrcc requires a second parameter, the separator in the dates.
    irr = irrcc(dts, '-')
    print('The internal rate of return with continuous compounding is {0:.2f}%.'.format(100 * irr))