# Bumps 0.8.1 documentation

## bumps.dream.bounds

# Source code for bumps.dream.bounds

    """
    Bounds handling.

    Use bounds(low, high, style) to create a bounds handling object.  This
    function operates on a point x, transforming it so that all dimensions
    are within the bounds.  Options are available, including reflecting,
    wrapping, clipping or randomizing the point, or ignoring the bounds.

    The returned bounds object should have an apply(x) method which
    transforms the point *x*.
    """
    __all__ = ["make_bounds_handler", "Bounds", "ReflectBounds", "ClipBounds",
               "FoldBounds", "RandomBounds", "IgnoreBounds"]

    import numpy as np
    from numpy import inf, isinf
    from . import util
    from .compiled import dll

    def make_bounds_handler(bounds, style='reflect'):
        """
        Return a bounds object which can update the bounds.

        Bounds handling *style* name is one of::

            reflect:   reflect off the boundary
            clip:      stop at the boundary
            fold:      wrap values to the other side of the boundary
            randomize: move to a random point in the bounds
            none:      ignore the bounds

        With semi-infinite intervals folding and randomizing aren't well
        defined, and reflection is used instead.

        With finite intervals the the reflected or folded point may still be
        outside the bounds (which can happen if the step size is too large),
        and a random uniform value is used instead.
        """
        if bounds is None:
            return IgnoreBounds()

        low, high = bounds

        # Do boundary handling -- what to do when points fall outside bound
        style = style.lower()
        if style == 'reflect':
            f = ReflectBounds(low, high)
        elif style == 'clip':
            f = ClipBounds(low, high)
        elif style == 'fold':
            f = FoldBounds(low, high)
        elif style == 'randomize':
            f = RandomBounds(low, high)
        elif style == 'none' or style is None:
            f = IgnoreBounds()
        else:
            raise ValueError("bounds style %s is not valid" % style)
        return f

    class Bounds(object):
        """
        Base class for all times of bounds objects.
        """
        c_interface = None # type: Callable[[int, int, Any, Any, Any], None]
        low = None # type: np.ndarray
        high = None # type: np.ndarray
        def apply(self, x):
            """Force x values within bounds"""
            raise NotImplementedError

        def __call__(self, pop):
            """Force x values within bounds for each member of the population"""
            if self.c_interface is not None:
                self.c_interface(len(pop), len(self.low), pop.ctypes,
                                 self.low.ctypes, self.high.ctypes)
            else:
                for x in pop:
                    self.apply(x)
            return pop

    class ReflectBounds(Bounds):
        """
        Reflect parameter values into bounded region
        """
        c_interface = dll.bounds_reflect if dll else None
        def __init__(self, low, high):
            self.low, self.high = [np.ascontiguousarray(v, 'd') for v in (low, high)]

        def apply(self, y):
            """
            Update x so all values lie within bounds

            Returns x for convenience.  E.g., y = bounds.apply(x+0)
            """
            minn, maxn = self.low, self.high

            # Reflect points which are out of bounds
            idx = y < minn
            y[idx] = 2*minn[idx] - y[idx]
            idx = y > maxn
            y[idx] = 2*maxn[idx] - y[idx]

            # Randomize points which are still out of bounds
            idx = (y < minn) | (y > maxn)
            y[idx] = minn[idx] + util.rng.rand(sum(idx))*(maxn[idx]-minn[idx])
            return y

    class ClipBounds(Bounds):
        """
        Clip values to bounded region
        """
        c_interface = dll.bounds_clip if dll else None
        def __init__(self, low, high):
            self.low, self.high = [np.ascontiguousarray(v, 'd') for v in (low, high)]

        def apply(self, y):
            minn, maxn = self.low, self.high
            idx = y < minn
            y[idx] = minn[idx]
            idx = y > maxn
            y[idx] = maxn[idx]

            return y

    class FoldBounds(Bounds):
        """
        Wrap values into the bounded region
        """
        c_interface = dll.bounds_fold if dll else None
        def __init__(self, low, high):
            self.low, self.high = [np.ascontiguousarray(v, 'd') for v in (low, high)]

        def apply(self, y):
            minn, maxn = self.low, self.high

            # Deal with semi-infinite cases using reflection
            idx = (y < minn) & isinf(maxn)
            y[idx] = 2*minn[idx] - y[idx]
            idx = (y > maxn) & isinf(minn)
            y[idx] = 2*maxn[idx] - y[idx]

            # Wrap points which are out of bounds
            idx = y < minn
            y[idx] = maxn[idx] - (minn[idx] - y[idx])
            idx = y > maxn
            y[idx] = minn[idx] + (y[idx] - maxn[idx])

            # Randomize points which are still out of bounds
            idx = (y < minn) | (y > maxn)
            y[idx] = minn[idx] + util.rng.rand(sum(idx))*(maxn[idx]-minn[idx])

            return y

    class RandomBounds(Bounds):
        """
        Randomize values into the bounded region
        """
        c_interface = dll.bounds_random if dll else None
        def __init__(self, low, high):
            self.low, self.high = [np.ascontiguousarray(v, 'd') for v in (low, high)]

        def apply(self, y):
            minn, maxn = self.low, self.high

            # Deal with semi-infinite cases using reflection
            idx = (y < minn) & isinf(maxn)
            y[idx] = 2*minn[idx] - y[idx]
            idx = (y > maxn) & isinf(minn)
            y[idx] = 2*maxn[idx] - y[idx]

            # The remainder are selected uniformly from the bounded region
            idx = (y < minn) | (y > maxn)
            y[idx] = minn[idx] + util.rng.rand(sum(idx))*(maxn[idx]-minn[idx])

            return y

    class IgnoreBounds(Bounds):
        """
        Leave values outside the bounded region
        """
        c_interface = dll.bounds_ignore if dll else None
        def __init__(self, low=None, high=None):
            self.low, self.high = [np.ascontiguousarray(v, 'd') for v in (low, high)]

        def apply(self, y):
            return y

    def test():
        """bounds handlers test"""
        from numpy.linalg import norm
        from numpy import array

        bounds = list(zip([5, 10], [-inf, -10], [-5, inf], [-inf, inf]))
        v = np.ascontiguousarray([6, -12, 6, -12], 'd')
        for t in 'none', 'reflect', 'clip', 'fold', 'randomize':
            assert norm(make_bounds_handler(bounds, t).apply(v+0) - v) == 0
        v = np.ascontiguousarray([12, 12, -12, -12], 'd')
        for t in 'none', 'reflect', 'clip', 'fold':
            w = make_bounds_handler(bounds, t)
            assert norm(w(array([v, v, v])) - w.apply(v+0)) == 0
        assert norm(make_bounds_handler(bounds, 'none').apply(v+0) - v) == 0
        assert norm(make_bounds_handler(bounds, 'reflect').apply(v+0)
                    - [8, -32, 2, -12]) == 0
        assert norm(make_bounds_handler(bounds, 'clip').apply(v+0)
                    - [10, -10, -5, -12]) == 0
        assert norm(make_bounds_handler(bounds, 'fold').apply(v+0)
                    - [7, -32, 2, -12]) == 0
        w = make_bounds_handler(bounds, 'randomize').apply(v+0)
        assert 5 <= w[0] <= 10 and w[1] == -32 and w[2] == 2 and w[3] == -12
        v = np.ascontiguousarray([20, 1, 1, 1], 'd')
        w = make_bounds_handler(bounds, 'reflect').apply(v+0)
        assert 5 <= w[0] <= 10
        v = np.ascontiguousarray([20, 1, 1, 1], 'd')
        w = make_bounds_handler(bounds, 'fold').apply(v+0)
        assert 5 <= w[0] <= 10

    if __name__ == "__main__":
        test()