import streamlit as st
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import math

st.title("Калькулятор Toyota📄")

st.markdown("Тут данные ввести")

Buying_an_autopilot = st.number_input('Покупка автопилота, руб.', value=2000000)
Purchase_of_peripheral_equipment = st.number_input('Покупка перефирийного оборудования, руб.', value=40000)
Purchase_by = st.number_input('Покупка ПО, руб.', value=10000)
Introduction_of_autopilot = st.number_input('Внедрение автопилота, руб.', value=20000)
Maintenance = st.number_input('Обслуживание (месяц), руб.', value=100000)
The_cost_of_repairing_one_car = st.number_input('Стоимость ремонта одной машины, руб.', value=10000)
Inflation_rate = st.number_input('Уровень инфляции', value=0.04)
Monthly_salary_rate = st.number_input('Заработная ставка, руб. в месяц', value=40000)
Number_of_months = st.number_input('Количество месяцев', value=12)
Equipment_breakdown_rate = st.number_input('Коэффициент поломки оборудования', value=0.1)
Price_for_processing_ont_pallet = st.number_input('Цена за обработку 1 паллета, руб.', value=300)
Cargo_flow = st.number_input('Грузопоток, шт/месяц', value=10000)
Efficiency = st.number_input('Производительность, шт в час', value=5)
Number_of_working_hours = st.number_input('Количество рабочих часов', value=8)
Shift_of_one_employee = st.number_input('Смена 1 работника, ч.', value=8)
Number_of_working_days_month = st.number_input('Количество рабочих дней в месяц, дн.', value=20)
Social_benefits_for_one_employee = st.number_input('Социальные выплаты 1 сотруднику, руб.', value=10000)
Insurance_rate = st.number_input('Ставка страхования', value=0.005)
Income_tax_rate = st.number_input('Ставка налога на прибыль', value=0.2)
Number_of_autopilots_serviced_by_one_employee = st.number_input('Количество автопилотов, обслуживаемых 1 работником', value=10)
discounting = st.number_input('Ставка дисконтирования в месяц', value=0.028)

Rate_CPI = 1.1


def get_number_pallets_and_machines_employees():
    Number_pallets = Efficiency * Number_of_working_hours * Number_of_working_days_month
    Number_machines = math.ceil(Cargo_flow / Number_pallets)
    Number_employees = math.ceil((Number_machines * Number_of_working_hours / Shift_of_one_employee) / Number_of_autopilots_serviced_by_one_employee)
    
    return Number_pallets, Number_machines, Number_employees


def get_revenue(idx):
    indexation = math.floor(idx / 12)
    Price = Price_for_processing_ont_pallet * math.pow(Rate_CPI, indexation)
    revenue = Number_machines * Number_pallets * Price
    
    return revenue


def get_costs(idx):
    indexation = math.floor(idx / 12)
    wage_fund_with_indexation = math.pow((Social_benefits_for_one_employee + Monthly_salary_rate), indexation)
    
    Expected_repair_costs_per_month = Number_machines * Equipment_breakdown_rate * The_cost_of_repairing_one_car
    Wage_Fund = Number_employees * wage_fund_with_indexation
    The_cost_of_insurance = Number_machines * Insurance_rate * (Buying_an_autopilot + Purchase_of_peripheral_equipment)
    
    return Purchase_by + Number_machines * Maintenance + Expected_repair_costs_per_month + Wage_Fund + The_cost_of_insurance


def get_profit(amortization, idx):
    profit = get_revenue(idx) - get_costs(idx) - amortization
    if profit > 0:
        return profit
    else:
        return profit * 0.8
    
    
def get_PV(profit, discounting):
    return profit * discounting


def get_array_discounting():
    array_discounting = [1]
    for idx in range(Number_of_months):
        array_discounting.append(array_discounting[-1] / (1 + discounting))
    return array_discounting


def get_amortization(value):
    array_amortization = [0]
    value = value / 60
    for idx in range(Number_of_months):
        array_amortization.append(value)
    return array_amortization


def get_array_CF_PV():
    I_0 = Buying_an_autopilot * Number_machines + Purchase_of_peripheral_equipment + Introduction_of_autopilot
    
    array_discounting = get_array_discounting()
    array_amortization = get_amortization(I_0)
    
    array_PV = [-I_0]
    array_CF = [-I_0]
    
    for idx in range(1, Number_of_months + 1, 1):
        
        profit = get_profit(array_amortization[idx], idx)
        
        array_CF.append(profit)
        
        cur_PV = get_PV(profit, array_discounting[idx])
        
        array_PV.append(cur_PV)
        
    return array_CF, array_PV


def get_array_NPV():
    array_NPV = [array_PV[0]]
    for idx in range(1, Number_of_months + 1, 1):
        array_NPV.append(array_NPV[-1] + array_PV[idx])
    return array_NPV


if st.button('Сюда кликнуть чтобы посчитать'):
    Number_pallets, Number_machines, Number_employees = get_number_pallets_and_machines_employees()
    array_CF, array_PV = get_array_PV()
    array_NPV =  get_array_NPV()
    
    IRR = np.irr(array_CF)
    
    st.write(f'NPV за {Number_of_months} месяцев:', array_NPV[-1])
    st.write(f'IRR на {Number_of_months} месяцев:', IRR)
    
    chart_data = pd.DataFrame(columns=['PV', 'NPV'])
    chart_data['PV'] = array_PV
    chart_data['NPV'] = array_NPV

    st.area_chart(chart_data)