def setUp(self):
""" Create setup for making sure that meta-data are
transfered to the status of payments """
account = a.BankAccount(amount = 1000, interest = 0.001, name = 'Main account', date=datetime(2016,9, 1))
savings = a.BankAccount(amount = 5000, interest = 0.013, name = 'Savings', date=datetime(2016,9, 1))
loan = a.Loan(amount = 100000, interest = 0.01, name = 'House Credit', date=datetime(2016,9, 1))
simulation = a.Simulation(account, savings, loan, name = 'Testsimulation', date=datetime(2016,9, 1))
simulation.add_regular(from_acc = 'Income',
to_acc = account,
payment = 2000,
interval = 'monthly',
date_start = datetime(2016,9,15),
day = 15,
name = 'Income')
simulation.add_regular(from_acc = account,
to_acc = savings,
payment = 500,
interval = 'monthly',
date_start = datetime(2016,9,30),
day = 30,
name = 'Savings',
meta = {'tax': 100})
simulation.simulate(delta=timedelta(days=2000))
self.simulation = simulation
def example_meta_controller(print_it=True):
""" This example shows, how meta-information for payments and account data could
be used to calculate annual tax-return """
account = a.BankAccount(amount=1000,
interest=0.001,
name='Main account',
date="01.09.2016")
# define meta-data for accounts. here: some fields that are relevant for
# tax calculations
loan = a.Loan(amount=100000,
interest=0.01,
name='House Credit',
date="01.09.2016",
meta={'tax': {
'outcome': 'yearly_interests'
}})
# add these accounts to the simulation
simulation = a.Simulation(account, loan, date='01.09.2016')
# our employee receives monthly 2000 netto, coming from 2500 brutto,
# 310 are subtracted directly from the loan, which is less than she
# needs to pay. 190 are paid for insurance
simulation.add_regular('Income',
account,
2000,
interval='monthly',
date_start="01.09.2016",
meta={
'type': 'income',
'tax': {
'brutto': 2500,
'paid': 310,
'insurance': 190
}
})
simulation.add_regular(account,
loan,
lambda: min(1500, -loan.account),
interval='monthly',
date_start="01.09.2016")
simulation.add_controller(controller_tax)
# simulate for ten years
simulation.simulate(delta=timedelta(days=365 * 10))
# this function is also part of a unittest. Therefore, we want to be able to
# control, whether we print some information or not
if print_it:
# print reports summarized in years
print(account.report.with_meta())
#print(loan.report.with_meta())
return simulation
def example3():
account = a.BankAccount(amount=1000, interest=0.001, name='Main account')
savings = a.BankAccount(amount=5000, interest=0.013, name='Savings')
loan = a.Loan(amount=100000, interest=0.01, name='House Credit')
simulation = a.Simulation(account, savings, loan, name='Testsimulation')
simulation.add_regular(from_acc='Income',
to_acc=account,
payment=2000,
interval='monthly',
date_start=datetime(2016, 9, 15),
day=15,
name='Income')
simulation.add_regular(from_acc=account,
to_acc=savings,
payment=500,
interval='monthly',
date_start=datetime(2016, 9, 30),
day=30,
name='Savings')
simulation.add_regular(from_acc=account,
to_acc=loan,
payment=1000,
interval='monthly',
date_start=datetime(2016, 9, 15),
day=15,
name='Debts',
fixed=False,
date_stop=lambda cdate: loan.is_finished())
simulation.add_regular(
from_acc=account,
to_acc=loan,
payment=lambda: min(8000, max(0,
account.get_account() - 4000)),
interval='yearly',
date_start=datetime(2016, 11, 20),
day=20,
name='Debts',
fixed=False,
date_stop=lambda cdate: loan.is_finished())
simulation.simulate(delta=timedelta(days=2000))
simulation.plt_summary()
show()
print(account.report)
print(loan.report)
def dependencies():
loan = a.Loan(200000, 0.0185, name='Credit')
# the class property defines a dependency on loan. When loan
# decreases, the house-property increases
house = a.Property(200000, 0, loan, name='House')
simulation = a.Simulation(loan, house)
simulation.add_regular('Income', loan, 1000, interval='monthly')
simulation.simulate(delta=timedelta(days=365 * 20))
simulation.plt_summary()
show(block=True)
def example2():
# create a private bank account and a loan
account = a.BankAccount(amount=1000, interest=0.001, name='Main account')
savings = a.BankAccount(amount=5000, interest=0.007, name='Savings')
loan = a.Loan(amount=100000, interest=0.01, name='House Credit')
# add these accounts to the simulation
simulation = a.Simulation(account, savings, loan)
# describe single or regular payments between accounts. note, that
# a string can be used for external accounts that you don't want to model.
# also note the lambda function for the payments to the loan.
simulation.add_regular('Income', account, 2000, interval='monthly')
simulation.add_regular(account, savings, 500, interval='monthly')
simulation.add_regular(account,
loan,
lambda: min(1500, -loan.account),
interval='monthly')
simulation.add_unique(savings, 'Vendor for car', 10000, '17.03.2019')
# simulate for ten years
simulation.simulate(delta=timedelta(days=365 * 10))
# plot the data
simulation.plt_summary()
# print reports summarized in years
print(account.report.yearly().as_df())
print(loan.report.yearly().as_df())
# analyze data
print("Bank account: %.2f" % (account.account + savings.account))
cwd = os.path.dirname(os.path.realpath(__file__))
result_folder = cwd + '/example2'
html.report(simulation, style="standard", output_dir=result_folder)
show()
def example1():
# create a private bank account and a loan
account = a.BankAccount(amount=1000, interest=0.001, name='Main account')
loan = a.Loan(amount=100000, interest=0.01, name='House Credit')
# add these accounts to the simulation
simulation = a.Simulation(account, loan)
# describe single or regular payments between accounts. note, that
# a string can be used for external accounts that you don't want to model.
# also note the lambda function for the payments to the loan.
simulation.add_regular('Income', account, 2000, interval='monthly')
# you can also use lambda function to dynamically decide how much money
# you would like to transfer
simulation.add_regular(account,
loan,
lambda: min(1500, -loan.account),
interval='monthly')
# simulate for ten years
simulation.simulate(delta=timedelta(days=365 * 10))
# plot the data
simulation.plt_summary()
show()
# print reports summarized in years
print(account.report.yearly().as_df())
print(loan.report.yearly().as_df())
# analyze data
print("Interests on bank account: %.2f" %
sum(account.report.yearly().interest))
print("Interests on loan account: %.2f" %
sum(loan.report.yearly().interest))
return simulation
def setUp(self):
""" Mostly taken from examples/simple_example.py """
account = a.BankAccount(amount=1000,
interest=0.001,
name='Main account',
date=datetime(2016, 9, 1))
savings = a.BankAccount(amount=5000,
interest=0.013,
name='Savings',
date=datetime(2016, 9, 1))
loan = a.Loan(amount=100000,
interest=0.01,
name='House Credit',
date=datetime(2016, 9, 1))
simulation = a.Simulation(account,
savings,
loan,
name='Testsimulation',
date=datetime(2016, 9, 1))
simulation.add_regular(from_acc='Income',
to_acc=account,
payment=2000,
interval='monthly',
date_start=datetime(2016, 9, 15),
day=15,
name='Income')
simulation.add_regular(from_acc=account,
to_acc=savings,
payment=500,
interval='monthly',
date_start=datetime(2016, 9, 30),
day=30,
name='Savings')
simulation.add_regular(from_acc=account,
to_acc=loan,
payment=1000,
interval='monthly',
date_start=datetime(2016, 9, 15),
day=15,
name='Debts',
fixed=False,
date_stop=lambda cdate: loan.is_finished())
simulation.add_regular(
from_acc=account,
to_acc=loan,
payment=lambda: min(8000, max(0,
account.get_account() - 4000)),
interval='yearly',
date_start=datetime(2016, 11, 20),
day=20,
name='Debts',
fixed=False,
date_stop=lambda cdate: loan.is_finished())
simulation.simulate(delta=timedelta(days=2000))
self.simulation = simulation
self.account = account
self.loan = loan