pymrm.solve.clip_approach

def clip_approach(values, dummy, lower_bounds=0, upper_bounds=None, factor=0):
    """Project values onto bounds, optionally with a relaxed approach rule.

    Parameters
    ----------
    values : numpy.ndarray
        Values to modify in place.
    dummy : Any
        Placeholder argument kept for API compatibility.
    lower_bounds, upper_bounds : float or numpy.ndarray, optional
        Lower and upper bounds. Scalars and broadcastable arrays are supported.
    factor : float, optional
        Relaxation factor for out-of-bound entries. ``0`` applies strict clipping.
        Non-zero values apply a linear approach update toward the violated bound.
    """
    if factor == 0:
        np.clip(values, lower_bounds, upper_bounds, out=values)
    else:
        if lower_bounds is not None:
            below_lower = values < lower_bounds
            if np.any(below_lower):
                broadcasted_lower_bounds = np.broadcast_to(lower_bounds, values.shape)
                values[below_lower] = (1.0 + factor) * broadcasted_lower_bounds[
                    below_lower
                ] - factor * values[below_lower]
        if upper_bounds is not None:
            above_upper = values > upper_bounds
            if np.any(above_upper):
                broadcasted_upper_bounds = np.broadcast_to(upper_bounds, values.shape)
                values[above_upper] = (1.0 + factor) * broadcasted_upper_bounds[
                    above_upper
                ] - factor * values[above_upper]