import pandas as pd
import matplotlib.pyplot as plt
import tabulate

# it = 0

def compounding_interest(balances, rate=0.05, terms=3):
    if terms <= 0:
        print("Number of terms must be >0!")
        return
    global it 
    balances_over_time = []
    current_balances = balances
    for i in range(0, terms):
        new_bal = []
        for balance in current_balances:
            b = balance + (balance * rate)
            new_bal.append(b)
            # it += 1
        assert(len(new_bal) == len(balances))
        balances_over_time.append(new_bal)
        current_balances = new_bal
    return balances_over_time

def calc_share_of_wealth(balances):
    total_money = sum(balances)
    shares = []
    for balance in balances:
        shares.append(balance/total_money)
    return shares

def ubi(balances, rate=10, terms=3):
    dividend = rate
    balances_over_time = []
    current_balances = balances
    for i in range(0, terms):
        new_bal = []
        for balance in current_balances:
            b = balance + dividend
            new_bal.append(b)
        assert(len(new_bal) == len(balances))
        balances_over_time.append(new_bal)
        current_balances = new_bal
    return balances_over_time

def mining(balances, halving_frequency=1, reward=10, terms=3):
    balances_over_time = []
    current_balances = balances
    for i in range(0, terms):
        new_bal = []
        for balance in current_balances:
            b = balance + reward
            new_bal.append(b)
        assert(len(new_bal) == len(balances))
        if i % halving_frequency == 0:
            reward = reward/2
        balances_over_time.append(new_bal)
        current_balances = new_bal
    return balances_over_time

def get_balances_over_time(names, balances, func, terms=4, param=0):
    if func is None:
        print("Need a function!")
        return
    if len(names) != len(balances):
        print("Every person needs a balance.")
        return
    data = {
        'name' : names,
        'initial' : balances
    }
    df = pd.DataFrame(data)
    frame_data = []
    if param == 0:
        frame_data = func(balances, terms=terms)
    else:
        frame_data = func(balances, terms=terms, rate=param)
    assert(len(frame_data) == terms)
    for i in range(0, terms):
        key = str(i)
        df[key] = frame_data[i]
    return df

# -------------

def illustrate_share_of_wealth():

    participants = ["Alice", "Bob", "Charlie"]
    balances = [100,40,20]

    print("In this demo, we have three participants.\n", participants)
    print("They respectively have ", balances)

    print("\nThe initial distribution of wealth is ")
    print(calc_share_of_wealth(balances))
    print("\n")

    df = get_balances_over_time (
        participants, balances, compounding_interest
    )
    # print(it)
    df["share"] = [val * 100 for val in calc_share_of_wealth(df["3"]) ]
    
    print(df.to_html())

    terms = 222
    print(f"How much money exists after {terms} terms?")
    #### In 222 terms, even C becomes a millionaire.
    nb = compounding_interest(balances, terms=terms)
    print(nb[-1])
    print("\n")

    df = get_balances_over_time (
        participants, balances, ubi
    )
    print(df.to_html())

    print("How much money exists after 999 terms?")
    u = ubi(balances, terms=999)
    print(u[-1])

    print("What is the share of wealth in a UBI economy?")
    print(calc_share_of_wealth(u[-1]))



def visualize_ubi(terms=25):

    participants = ["Alice", "Bob", "Charlie"]
    balances = [100,40,20]

    df = get_balances_over_time (
        participants, balances, ubi,
        terms = terms
    )
    # print(df.keys)
    shares = []
    for key, data in df.items():
        if key == "name":
            continue
        if key == "initial":
            continue
        shares.append(calc_share_of_wealth(data))
    sow = pd.DataFrame(shares)
    # print(sow.keys())
    x = [i for i in range(1,terms)]
    assert(len(x) == len(shares))

    plt.style.use('dark_background')
    plt.plot(
        x, sow[0], color="red", label=participants[0]
    )
    plt.plot(
        x, sow[1], color="lightgreen", label=participants[1]
    )
    plt.plot(
        x, sow[2], color="cyan", label=participants[2]
    )
    plt.axhline(
        y=0.33, color='violet', linestyle='--', label="0.33"
    )

    plt.title("Change in Wealth Distribution With a Constant Dividend")
    plt.legend()
    plt.xlabel("Terms")
    plt.ylabel("Share of Wealth")
    plt.savefig("ubi-wealth-distribution.png")
    plt.close()
    # plt.show()
    return

def calc_total_supply(df):
    total = []
    for key, data in df.items():
        if key == "name":
            continue
        total.append(sum(data))
    return total

def draw_specific_chart1(terms=50, linear_label="? (linear)"):
    participants = ["Alice", "Bob", "Charlie"]
    balances = [100,40,20]

    df = get_balances_over_time (
        participants, balances, ubi,
        terms = terms
    )
    total_supply_ubi = calc_total_supply(df)

    df_si = get_balances_over_time (
        participants, balances, compounding_interest,
        terms = terms
    )
    total_supply_si = calc_total_supply(df_si)
    # + 1 because the initial frame is included this time
    x = [i for i in range(1,terms+1)]
    assert(len(x) == len(total_supply_si))

    plt.style.use('dark_background')
    plt.plot(
        x, total_supply_si, color="red", label="apy = 0.05"
    )
    plt.plot(
        x,
        calc_total_supply(get_balances_over_time(
            participants, 
            balances, 
            compounding_interest,
            terms=terms,
            param=0.04
        )),
        color="orange", label="apy = 0.04"
    )
    plt.plot(
        x,
        calc_total_supply(get_balances_over_time(
            participants, 
            balances, 
            compounding_interest,
            terms=terms,
            param=0.03
        )),
        color="yellow", label="apy = 0.03"
    )
    plt.title("Supply of Money Over Time")
    plt.legend()
    plt.xlabel("Terms")
    plt.ylabel("Total Currency")
    plt.savefig("inflation-ubi-vs-5apy.png")
    plt.close()
    # plt.show()

def draw_specific_chart2(terms=50):
    participants = ["Alice", "Bob", "Charlie"]
    balances = [100,40,20]

    df = get_balances_over_time (
        participants, balances, ubi,
        terms = terms
    )
    total_supply_ubi = calc_total_supply(df)

    df_si = get_balances_over_time (
        participants, balances, compounding_interest,
        terms = terms
    )
    total_supply_si = calc_total_supply(df_si)
    # + 1 because the initial frame is included this time
    x = [i for i in range(1,terms+1)]
    assert(len(x) == len(total_supply_si))

    plt.style.use('dark_background')
    plt.plot(
        x, total_supply_ubi, color="cyan", label="dividend = 10"
    )
    plt.plot(
        x,
        calc_total_supply(get_balances_over_time(
            participants, 
            balances, 
            ubi,
            terms=terms,
            param=5
        )),
        color="violet", label="dividend = 5"
    )
    plt.plot(
        x,
        calc_total_supply(get_balances_over_time(
            participants, 
            balances, 
            ubi,
            terms=terms,
            param=15
        )),
        color="lightgreen", label="dividend = 15"
    )
    plt.plot(
        x, total_supply_si, color="red", label="apy = 0.05"
    )
    plt.plot(
        x,
        calc_total_supply(get_balances_over_time(
            participants, 
            balances, 
            compounding_interest,
            terms=terms,
            param=0.04
        )),
        color="orange", label="apy = 0.04"
    )
    plt.plot(
        x,
        calc_total_supply(get_balances_over_time(
            participants, 
            balances, 
            compounding_interest,
            terms=terms,
            param=0.03
        )),
        color="yellow", label="apy = 0.03"
    )
    plt.title("Supply of Money Over Time")
    plt.legend()
    plt.xlabel("Terms")
    plt.ylabel("Total Currency")
    plt.savefig("inflation-ubi-vs-apy2.png")
    plt.close()
    # plt.show()

def visualize_inflation(df, title="Inflation", filename="inflation.png"):
    supply_over_time = calc_total_supply(df)
    time_span = len(supply_over_time)
    x = [i for i in range(time_span)]
    assert(len(x) == time_span)

    plt.style.use('dark_background')
    plt.plot(
        x, supply_over_time, color="red")
    plt.title(title)
    plt.legend()
    plt.xlabel("Terms")
    plt.ylabel("Total Currency")
    plt.savefig(filename)
    plt.close()

def visualize_wealth_dist(df, title="Wealth Distribution", filename="wealth-distribution.png"):
    participants = df["name"]
    shares = []
    for key, data in df.items():
        if key == "name":
            continue
        if key == "initial":
            continue
        shares.append(calc_share_of_wealth(data))
    sow = pd.DataFrame(shares)
    # print(sow.keys())
    terms = sow.shape[0] + 1
    x = [i for i in range(1,terms)]
    print(len(x))
    print(len(shares))
    assert(len(x) == len(shares))

    plt.style.use('dark_background')
    plt.plot(
        x, sow[0], color="red", label=participants[0]
    )
    plt.plot(
        x, sow[1], color="lightgreen", label=participants[1]
    )
    plt.plot(
        x, sow[2], color="cyan", label=participants[2]
    )
    plt.axhline(
        y=0.33, color='violet', linestyle='--', label="0.33"
    )

    plt.title(title)
    plt.legend()
    plt.xlabel("Terms")
    plt.ylabel("Share of Wealth")
    plt.savefig(filename)
    plt.close()

if __name__ == "__main__":

    illustrate_share_of_wealth()
    visualize_ubi(terms=50)
    draw_specific_chart1(terms=75)
    draw_specific_chart1(terms=75, linear_label="dividend = 10")
    draw_specific_chart2(terms=75)

    participants = ["Alice", "Bob", "Charlie"]
    balances = [100,40,20]
    m = get_balances_over_time(participants, balances, mining, terms=10)
    print(m)
    print(m.shape[1])
    visualize_inflation(m, title="Inflation Given block_reward = 10 and Halving Every Term", filename="inflation-pow.png")
    # print(m.iloc[:,:5].to_markdown())
    visualize_wealth_dist(m, filename="wealth-distribution-pow.png")