"""Offline teaching calculations for Litecoin.watch, 22 October 2026.
All hashrates, prices, costs, pool outcomes and yields below are synthetic.
No network access, wallet operations, mining jobs, transfers or file writes.
Python 3 standard library only. Save this file as calculations.py and run it.
"""
from decimal import Decimal as D, getcontext
from math import exp, sqrt
import json
getcontext().prec = 40

def calculate():
    fraction = D(16) / D(3000000)  # GH/s divided by GH/s, each modeled chain
    ltc = fraction * D(576) * D("6.25")
    doge = fraction * D(1440) * D(10000)
    net_ltc, net_doge = ltc * D(".98"), doge * D(".98")
    gross_value = ltc * 60 + doge * D(".10")
    net_value = net_ltc * 60 + net_doge * D(".10")
    electricity = D("3.36") * 24 * D(".10")
    gross_after_halving = ltc / 2 * 60 + doge * D(".10")
    pplns = {str(blocks): D(blocks) * D("6.25") * D(16) / D(300000) * D(".98") for blocks in [40, 58, 75]}
    pool_lambda = 576 * .10
    solo_lambda = float(fraction * 576)
    interest = D(10) * D(".05") * 90 / 365
    net_interest = interest - D(".02")
    final_ltc = 10 + net_interest
    lp_x = (D(6000) / 120).sqrt()
    lp_y = D(6000) / lp_x
    lp_value = lp_x * 120 + lp_y
    hold_value = D(10) * 120 + 600
    return {
        "kind": "SYNTHETIC_TEACHING_CALCULATIONS_NOT_LIVE_QUOTES",
        "gross_ltc_per_day": ltc,
        "gross_doge_per_day": doge,
        "net_ltc_per_day_after_assumed_2pct": net_ltc,
        "net_doge_per_day_after_assumed_2pct": net_doge,
        "gross_value_usd_per_day": gross_value,
        "net_coin_revenue_usd_per_day": net_value,
        "electricity_usd_per_day": electricity,
        "margin_before_other_costs_usd_per_day": net_value - electricity,
        "gross_value_after_only_ltc_halving_usd": gross_after_halving,
        "gross_value_drop_percent": (1-gross_after_halving/gross_value)*100,
        "idealized_pplns_ltc_by_pool_blocks": pplns,
        "pool_ltc_blocks_expected_per_day": pool_lambda,
        "pool_ltc_block_count_cv_day": 1/sqrt(pool_lambda),
        "pool_ltc_block_count_cv_30days": 1/sqrt(pool_lambda*30),
        "solo_ltc_blocks_expected_per_day": solo_lambda,
        "solo_ltc_mean_interval_days": 1/solo_lambda,
        "solo_ltc_probability_zero_blocks_365days": exp(-solo_lambda*365),
        "yield_simple_5pct_apr_90days_gross_ltc": interest,
        "yield_costs_ltc": D(".02"),
        "yield_90days_net_ltc": net_interest,
        "yield_final_ltc": final_ltc,
        "yield_net_period_return_percent": net_interest/10*100,
        "yield_simple_annualized_net_percent": net_interest/10*365/90*100,
        "yield_ending_usd_at_assumed_40": final_ltc*40,
        "apy_5pct_apr_compounded_monthly_percent": ((1+D(".05")/12)**12-1)*100,
        "one_percent_daily_year_balance_multiplier": D("1.01")**365,
        "constant_product_ltc_units_at_price_120": lp_x,
        "constant_product_stable_units_at_price_120": lp_y,
        "constant_product_value_usd": lp_value,
        "hold_original_pair_value_usd": hold_value,
        "constant_product_difference_vs_holding_percent": (lp_value/hold_value-1)*100,
        "target_cases": [{"work":n,"parent_target":100,"aux_target":400,"meets_parent":n<=100,"meets_aux":n<=400} for n in [80,250,500]]
    }

def check(r):
    assert r["gross_ltc_per_day"] == D(".0192")
    assert r["gross_doge_per_day"] == D("76.8")
    assert r["net_ltc_per_day_after_assumed_2pct"] == D(".018816")
    assert r["net_doge_per_day_after_assumed_2pct"] == D("75.264")
    assert r["net_coin_revenue_usd_per_day"] == D("8.65536")
    assert r["electricity_usd_per_day"] == D("8.064")
    assert r["margin_before_other_costs_usd_per_day"] == D(".59136")
    assert r["gross_value_after_only_ltc_halving_usd"] == D("8.256")
    assert round(r["gross_value_drop_percent"],2) == D("6.52")
    assert r["idealized_pplns_ltc_by_pool_blocks"]["75"] == D(".0245")
    assert round(r["idealized_pplns_ltc_by_pool_blocks"]["40"],8) == D(".01306667")
    assert round(r["idealized_pplns_ltc_by_pool_blocks"]["58"],8) == D(".01894667")
    assert abs(r["solo_ltc_probability_zero_blocks_365days"]-.32586242366032314) < 1e-14
    assert round(r["yield_final_ltc"],8) == D("10.10328767")
    assert round(r["yield_simple_annualized_net_percent"],4) == D("4.1889")
    assert round(r["apy_5pct_apr_compounded_monthly_percent"],4) == D("5.1162")
    assert round(r["one_percent_daily_year_balance_multiplier"],2) == D("37.78")
    assert round(r["constant_product_value_usd"],2) == D("1697.06")
    assert round(r["constant_product_difference_vs_holding_percent"],2) == D("-5.72")
    assert r["target_cases"][1]["meets_aux"] and not r["target_cases"][1]["meets_parent"]
    assert D(".00002000") * 100000 == 2
    assert 200*2 == 400
    assert D("1")-D(1410)/100000000 == D(".99998590")
    assert D(".01")+D(".018816")-D(".02") == D(".008816")
    return 24

if __name__ == "__main__":
    results=calculate()
    checks=check(results)
    print(json.dumps({"arithmetic_assertions":checks,"results":results},default=str,indent=2))