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2be7272 3cb5cd5 b48512c 3cb5cd5 bcc6329 3cb5cd5 bcc6329 3cb5cd5 2be7272 3cb5cd5 d571752 3cb5cd5 d571752 3cb5cd5 bcc6329 3cb5cd5 d571752 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 | from portfolio import np, pretty_num, portfolio, INFLATION_RATE, set_INIT_AGE
import gradio as gr
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
def net_worth_calculator(Annual_Spending,Current_Income,Current_Age,Retirement_Age,
Current_Checking,Current_Savings,Current_Brokerage,
Current_Roth_401k,Current_Pretax_401k,Current_Roth_IRA,Current_Pretax_IRA):
INIT_SPENDING = Annual_Spending
INIT_SALARY = Current_Income
INIT_AGE = Current_Age
INIT_RETIREAGE = Retirement_Age
init_checkings = Current_Checking
init_savings = Current_Savings
init_brokerage = Current_Brokerage
init_roth_401k = Current_Roth_401k
init_pretax_401k = Current_Pretax_401k
init_roth_IRA = Current_Roth_IRA
init_pretax_IRA = Current_Pretax_IRA
set_INIT_AGE(INIT_AGE)
def career_model(i):
age = INIT_AGE + i
if age < INIT_RETIREAGE:
salary = INIT_SALARY*(1.02 + INFLATION_RATE)**i
elif age < 65:
salary = 0
else:
# social security
salary = 12*2e3* (1.0 + INFLATION_RATE)**i
# Hoping for a 0.25% increase in lifestype per year over inflation
spending = INIT_SPENDING*(1.0025 + INFLATION_RATE)**i
return spending, salary
p = portfolio(
retirement_age=INIT_RETIREAGE,
init_checkings=init_checkings,
init_savings=init_savings,
init_brokerage=init_brokerage,
init_roth_401k=init_roth_401k,
init_pretax_401k=init_pretax_401k,
init_roth_IRA=init_roth_IRA,
init_pretax_IRA=0.0
)
ages = []
spendings = []
salaries = []
nets = []
message = ""
do_i_win = True
while p.net_worth() > 0 and p.age < 100:
spending, salary = career_model(p.age - INIT_AGE)
ages.append(p.age)
spendings.append(spending)
salaries.append(salary)
nets.append(p.net_worth())
try:
msg = p.increment_year(pay=salary, spending=spending, verbose=False)
if p.age % 5 == 0:
message += "\n" + msg#print(msg)
except:
do_i_win = False
if p.age % 5 == 0:
message += "\nOUT OF MONEY, SO NO MORE LIVING"
#print("OUT OF MONEY, SO NO MORE LIVING")
fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.gca()
width, height = fig.get_size_inches() * fig.get_dpi()
if do_i_win:
ax.plot(ages, nets, 'g')
else:
ax.plot(ages, nets, 'r')
ax.set_xlabel("Age")
ax.set_ylabel("Net Worth")
canvas.draw()
image = np.frombuffer(canvas.tostring_rgb(),dtype='uint8').reshape(int(height),int(width), 3)
return image,message
gr.Interface(fn=net_worth_calculator,
inputs = [gr.Slider(minimum=0, maximum=1000e3, value=100e3, step=10e3),
gr.Slider(minimum=0, maximum=1000e3, value=100e3, step=10e3),
gr.Slider(minimum=31, maximum=100, value=30, step=1),
gr.Slider(minimum=31, maximum=100, value=65, step=1),
gr.Slider(minimum=0, maximum=1000e3, value=100e3, step=10e3),
gr.Slider(minimum=0, maximum=1000e3, value=100e3, step=10e3),
gr.Slider(minimum=0, maximum=1000e3, value=100e3, step=10e3),
gr.Slider(minimum=0, maximum=1000e3, value=100e3, step=10e3),
gr.Slider(minimum=0, maximum=1000e3, value=100e3, step=10e3),
gr.Slider(minimum=0, maximum=1000e3, value=100e3, step=10e3),
gr.Slider(minimum=0, maximum=1000e3, value=100e3, step=10e3),
],
outputs=['image','text']).launch() |