Pratik Bhadane
131 lines
3.0 KiB
Python
131 lines
3.0 KiB
Python
"""
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Price Transformations — Helper functions to synthesize OHLC arrays into single arrays.
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Functions
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---------
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AVGPRICE — Average Price: (Open + High + Low + Close) / 4
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MEDPRICE — Median Price: (High + Low) / 2
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TYPPRICE — Typical Price: (High + Low + Close) / 3
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WCLPRICE — Weighted Close Price: (High + Low + Close * 2) / 4
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"""
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from __future__ import annotations
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import numpy as np
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from numpy.typing import ArrayLike
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from ferro_ta._ferro_ta import (
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avgprice as _avgprice,
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)
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from ferro_ta._ferro_ta import (
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medprice as _medprice,
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)
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from ferro_ta._ferro_ta import (
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typprice as _typprice,
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)
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from ferro_ta._ferro_ta import (
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wclprice as _wclprice,
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)
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from ferro_ta._utils import _to_f64
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from ferro_ta.core.exceptions import _normalize_rust_error
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def AVGPRICE(
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open: ArrayLike,
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high: ArrayLike,
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low: ArrayLike,
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close: ArrayLike,
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) -> np.ndarray:
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"""Average Price: (Open + High + Low + Close) / 4.
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Parameters
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----------
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open : array-like
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Sequence of open prices.
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high : array-like
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Sequence of high prices.
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low : array-like
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Sequence of low prices.
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close : array-like
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Sequence of closing prices.
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Returns
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-------
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numpy.ndarray
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Array of AVGPRICE values.
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"""
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try:
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return _avgprice(_to_f64(open), _to_f64(high), _to_f64(low), _to_f64(close))
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except ValueError as e:
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_normalize_rust_error(e)
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def MEDPRICE(high: ArrayLike, low: ArrayLike) -> np.ndarray:
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"""Median Price: (High + Low) / 2.
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Parameters
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----------
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high : array-like
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Sequence of high prices.
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low : array-like
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Sequence of low prices.
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Returns
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-------
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numpy.ndarray
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Array of MEDPRICE values.
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"""
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try:
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return _medprice(_to_f64(high), _to_f64(low))
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except ValueError as e:
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_normalize_rust_error(e)
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def TYPPRICE(high: ArrayLike, low: ArrayLike, close: ArrayLike) -> np.ndarray:
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"""Typical Price: (High + Low + Close) / 3.
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Parameters
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----------
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high : array-like
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Sequence of high prices.
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low : array-like
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Sequence of low prices.
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close : array-like
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Sequence of closing prices.
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Returns
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-------
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numpy.ndarray
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Array of TYPPRICE values.
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"""
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try:
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return _typprice(_to_f64(high), _to_f64(low), _to_f64(close))
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except ValueError as e:
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_normalize_rust_error(e)
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def WCLPRICE(high: ArrayLike, low: ArrayLike, close: ArrayLike) -> np.ndarray:
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"""Weighted Close Price: (High + Low + Close * 2) / 4.
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Parameters
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----------
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high : array-like
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Sequence of high prices.
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low : array-like
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Sequence of low prices.
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close : array-like
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Sequence of closing prices.
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Returns
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-------
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numpy.ndarray
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Array of WCLPRICE values.
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"""
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try:
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return _wclprice(_to_f64(high), _to_f64(low), _to_f64(close))
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except ValueError as e:
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_normalize_rust_error(e)
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__all__ = ["AVGPRICE", "MEDPRICE", "TYPPRICE", "WCLPRICE"]
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