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use math::interpolate;
use noise_fns::NoiseFn;

/// Noise function that outputs the value selected from one of two source
/// functions chosen by the output value from a control function.
pub struct Select<'a, T: 'a> {
    /// Outputs a value.
    pub source1: &'a dyn NoiseFn<T>,

    /// Outputs a value.
    pub source2: &'a dyn NoiseFn<T>,

    /// Determines the value to select. If the output value from
    /// the control function is within a range of values know as the _selection
    /// range_, this noise function outputs the value from `source2`.
    /// Otherwise, this noise function outputs the value from `source1`.
    pub control: &'a dyn NoiseFn<T>,

    /// Bounds of the selection range. Default is 0.0 to 1.0.
    pub bounds: (f64, f64),

    /// Edge falloff value. Default is 0.0.
    pub falloff: f64,
}

impl<'a, T> Select<'a, T> {
    pub fn new(
        source1: &'a dyn NoiseFn<T>,
        source2: &'a dyn NoiseFn<T>,
        control: &'a dyn NoiseFn<T>,
    ) -> Self {
        Select {
            source1,
            source2,
            control,
            bounds: (0.0, 1.0),
            falloff: 0.0,
        }
    }

    pub fn set_bounds(self, lower_bound: f64, upper_bound: f64) -> Self {
        Select {
            bounds: (lower_bound, upper_bound),
            ..self
        }
    }

    pub fn set_falloff(self, falloff: f64) -> Self {
        Select { falloff, ..self }
    }
}

impl<'a, T> NoiseFn<T> for Select<'a, T>
where
    T: Copy,
{
    fn get(&self, point: T) -> f64 {
        let control_value = self.control.get(point);
        let (lower, upper) = self.bounds;

        if self.falloff > 0.0 {
            match () {
                _ if control_value < (lower - self.falloff) => self.source1.get(point),
                _ if control_value < (lower + self.falloff) => {
                    let lower_curve = lower - self.falloff;
                    let upper_curve = lower + self.falloff;
                    let alpha = interpolate::s_curve3(
                        (control_value - lower_curve) / (upper_curve - lower_curve),
                    );

                    interpolate::linear(self.source1.get(point), self.source2.get(point), alpha)
                }
                _ if control_value < (upper - self.falloff) => self.source2.get(point),
                _ if control_value < (upper + self.falloff) => {
                    let lower_curve = upper - self.falloff;
                    let upper_curve = upper + self.falloff;
                    let alpha = interpolate::s_curve3(
                        (control_value - lower_curve) / (upper_curve - lower_curve),
                    );

                    interpolate::linear(self.source2.get(point), self.source1.get(point), alpha)
                }
                _ => self.source1.get(point),
            }
        } else if control_value < lower || control_value > upper {
            self.source1.get(point)
        } else {
            self.source2.get(point)
        }
    }
}