use nautilus_model::data::Bar;
use pyo3::prelude::*;
use crate::{
average::MovingAverageType,
indicator::Indicator,
momentum::stochastics::{Stochastics, StochasticsDMethod},
};
#[pymethods]
#[pyo3_stub_gen::derive::gen_stub_pymethods]
impl Stochastics {
#[new]
#[pyo3(signature = (period_k, period_d, slowing=None, ma_type=None, d_method=None))]
#[must_use]
pub fn py_new(
period_k: usize,
period_d: usize,
slowing: Option<usize>,
ma_type: Option<MovingAverageType>,
d_method: Option<StochasticsDMethod>,
) -> Self {
Self::new_with_params(
period_k,
period_d,
slowing.unwrap_or(1),
ma_type.unwrap_or(MovingAverageType::Exponential),
d_method.unwrap_or(StochasticsDMethod::Ratio),
)
}
fn __repr__(&self) -> String {
format!(
"Stochastics({},{},{},{:?},{:?})",
self.period_k, self.period_d, self.slowing, self.ma_type, self.d_method
)
}
#[getter]
#[pyo3(name = "name")]
fn py_name(&self) -> String {
self.name()
}
#[getter]
#[pyo3(name = "period_k")]
const fn py_period_k(&self) -> usize {
self.period_k
}
#[getter]
#[pyo3(name = "period_d")]
const fn py_period_d(&self) -> usize {
self.period_d
}
#[getter]
#[pyo3(name = "slowing")]
const fn py_slowing(&self) -> usize {
self.slowing
}
#[getter]
#[pyo3(name = "ma_type")]
const fn py_ma_type(&self) -> MovingAverageType {
self.ma_type
}
#[getter]
#[pyo3(name = "d_method")]
const fn py_d_method(&self) -> StochasticsDMethod {
self.d_method
}
#[getter]
#[pyo3(name = "has_inputs")]
fn py_has_inputs(&self) -> bool {
self.has_inputs()
}
#[getter]
#[pyo3(name = "value_k")]
const fn py_value_k(&self) -> f64 {
self.value_k
}
#[getter]
#[pyo3(name = "value_d")]
const fn py_value_d(&self) -> f64 {
self.value_d
}
#[getter]
#[pyo3(name = "initialized")]
const fn py_initialized(&self) -> bool {
self.initialized
}
#[pyo3(name = "update_raw")]
fn py_update_raw(&mut self, high: f64, low: f64, close: f64) {
self.update_raw(high, low, close);
}
#[pyo3(name = "handle_bar")]
fn py_handle_bar(&mut self, bar: &Bar) {
self.handle_bar(bar);
}
#[pyo3(name = "reset")]
fn py_reset(&mut self) {
self.reset();
}
}