Source code for ferro_ta.indicators.price_transform

"""
Price Transformations — Helper functions to synthesize OHLC arrays into single arrays.

Functions
---------
AVGPRICE — Average Price: (Open + High + Low + Close) / 4
MEDPRICE — Median Price: (High + Low) / 2
TYPPRICE — Typical Price: (High + Low + Close) / 3
WCLPRICE — Weighted Close Price: (High + Low + Close * 2) / 4
"""

from __future__ import annotations

import numpy as np
from numpy.typing import ArrayLike

from ferro_ta._ferro_ta import (
    avgprice as _avgprice,
)
from ferro_ta._ferro_ta import (
    medprice as _medprice,
)
from ferro_ta._ferro_ta import (
    typprice as _typprice,
)
from ferro_ta._ferro_ta import (
    wclprice as _wclprice,
)
from ferro_ta._utils import _to_f64
from ferro_ta.core.exceptions import _normalize_rust_error


[docs] def AVGPRICE( open: ArrayLike, high: ArrayLike, low: ArrayLike, close: ArrayLike, ) -> np.ndarray: """Average Price: (Open + High + Low + Close) / 4. Parameters ---------- open : array-like Sequence of open prices. high : array-like Sequence of high prices. low : array-like Sequence of low prices. close : array-like Sequence of closing prices. Returns ------- numpy.ndarray Array of AVGPRICE values. """ try: return _avgprice(_to_f64(open), _to_f64(high), _to_f64(low), _to_f64(close)) except ValueError as e: _normalize_rust_error(e)
[docs] def MEDPRICE(high: ArrayLike, low: ArrayLike) -> np.ndarray: """Median Price: (High + Low) / 2. Parameters ---------- high : array-like Sequence of high prices. low : array-like Sequence of low prices. Returns ------- numpy.ndarray Array of MEDPRICE values. """ try: return _medprice(_to_f64(high), _to_f64(low)) except ValueError as e: _normalize_rust_error(e)
[docs] def TYPPRICE(high: ArrayLike, low: ArrayLike, close: ArrayLike) -> np.ndarray: """Typical Price: (High + Low + Close) / 3. Parameters ---------- high : array-like Sequence of high prices. low : array-like Sequence of low prices. close : array-like Sequence of closing prices. Returns ------- numpy.ndarray Array of TYPPRICE values. """ try: return _typprice(_to_f64(high), _to_f64(low), _to_f64(close)) except ValueError as e: _normalize_rust_error(e)
[docs] def WCLPRICE(high: ArrayLike, low: ArrayLike, close: ArrayLike) -> np.ndarray: """Weighted Close Price: (High + Low + Close * 2) / 4. Parameters ---------- high : array-like Sequence of high prices. low : array-like Sequence of low prices. close : array-like Sequence of closing prices. Returns ------- numpy.ndarray Array of WCLPRICE values. """ try: return _wclprice(_to_f64(high), _to_f64(low), _to_f64(close)) except ValueError as e: _normalize_rust_error(e)
__all__ = ["AVGPRICE", "MEDPRICE", "TYPPRICE", "WCLPRICE"]