"""Halving calendar and position within the halving cycle."""

import numpy as np
import pandas as pd

GENESIS = pd.Timestamp("2009-01-03")

# Block heights 210k, 420k, 630k, 840k (UTC dates).
HALVINGS = pd.DatetimeIndex(["2012-11-28", "2016-07-09", "2020-05-11", "2024-04-20"])

# Later halvings are projected at the length of the last cycle. Block times drift
# by weeks per cycle, which is noise at the resolution this is used.
_LAST_CYCLE = HALVINGS[-1] - HALVINGS[-2]
_PROJECTED = pd.DatetimeIndex([HALVINGS[-1] + k * _LAST_CYCLE for k in range(1, 6)])

# Genesis starts cycle 0.
CYCLE_STARTS = pd.DatetimeIndex([GENESIS]).append(HALVINGS).append(_PROJECTED)


def cycle_position(dates) -> tuple[np.ndarray, np.ndarray]:
    """
    For each date, return (cycle index, days since that cycle began).

    Cycle 0 runs from genesis to the first halving; a halving day is day 0 of
    the cycle it starts.
    """
    dates = pd.DatetimeIndex(dates)
    if (dates < GENESIS).any():
        raise ValueError("date before genesis")
    if (dates >= CYCLE_STARTS[-1]).any():
        raise ValueError("date beyond projected halvings")
    index = CYCLE_STARTS.searchsorted(dates, side="right") - 1
    days = (dates - CYCLE_STARTS[index]).days
    return np.asarray(index), np.asarray(days)


def cycle_fraction(dates) -> tuple[np.ndarray, np.ndarray]:
    """For each date, return (cycle index, fraction of that cycle elapsed, in [0, 1))."""
    index, days = cycle_position(dates)
    lengths = (CYCLE_STARTS[index + 1] - CYCLE_STARTS[index]).days
    return index, days / np.asarray(lengths)