Module _numeric_kdtree_

construct_kd_tree( (object)points, (int)depth, (KDTree)tree) -> KDNode :
    Function for constructing a KDTree. Returns a KDNodeOP that
    represents the root of the tree. Points need to be sorted as the
    tree is being constructed, so the reference to the points is non-const.
    

    C++ signature :
        boost::shared_ptr<numeric::kdtree::KDNode> construct_kd_tree(utility::vector1<boost::shared_ptr<numeric::kdtree::KDPoint>, std::allocator<boost::shared_ptr<numeric::kdtree::KDPoint> > > {lvalue},unsigned long,numeric::kdtree::KDTree {lvalue})

get_percentile_bounds( (vec1_vec1_Real)points) -> HyperRectangle :
    numeric/kdtree/util.hh:85

    C++ signature :
        boost::shared_ptr<numeric::kdtree::HyperRectangle> get_percentile_bounds(utility::vector1<utility::vector1<double, std::allocator<double> >, std::allocator<utility::vector1<double, std::allocator<double> > > > {lvalue})

hr_intersects_hs( (HyperRectangle)hr, (vector1_Real)pt, (float)r) -> bool :
    returns true if the given hyper-rectangle intersects with the given
    hypersphere.
    

    C++ signature :
        bool hr_intersects_hs(numeric::kdtree::HyperRectangle,utility::vector1<double, std::allocator<double> >,double)

is_legal_greater_than( (KDNode)current, (int)split_axis, (float)split_value) -> bool :
    numeric/kdtree/util.hh:125

    C++ signature :
        bool is_legal_greater_than(boost::shared_ptr<numeric::kdtree::KDNode>,unsigned long,double)

is_legal_kdtree_below_node( (KDNode)current) -> bool :
    numeric/kdtree/util.hh:129

    C++ signature :
        bool is_legal_kdtree_below_node(boost::shared_ptr<numeric::kdtree::KDNode>)

is_legal_less_than( (KDNode)current, (int)split_axis, (float)split_value) -> bool :
    numeric/kdtree/util.hh:119

    C++ signature :
        bool is_legal_less_than(boost::shared_ptr<numeric::kdtree::KDNode>,unsigned long,double)

make_points( (vec1_vec1_Real)points, (object)data) -> object :
    Makes a vector1 of KDPoints, associating the nth entry in data
    with the nth entry in points.
    

    C++ signature :
        utility::vector1<boost::shared_ptr<numeric::kdtree::KDPoint>, std::allocator<boost::shared_ptr<numeric::kdtree::KDPoint> > > make_points(utility::vector1<utility::vector1<double, std::allocator<double> >, std::allocator<utility::vector1<double, std::allocator<double> > > >,utility::vector1<boost::shared_ptr<utility::pointer::ReferenceCount>, std::allocator<boost::shared_ptr<utility::pointer::ReferenceCount> > >)

make_points( (vec1_vec1_Real)points) -> object :
    Makes a vector of KDPoints.
    

    C++ signature :
        utility::vector1<boost::shared_ptr<numeric::kdtree::KDPoint>, std::allocator<boost::shared_ptr<numeric::kdtree::KDPoint> > > make_points(utility::vector1<utility::vector1<double, std::allocator<double> >, std::allocator<utility::vector1<double, std::allocator<double> > > >)

nearest_neighbor( (KDNode)current, (vector1_Real)pt, (HyperRectangle)bounds, (float)max_dist_sq, (KDNode)nearest, (float)dist_sq) -> None :
    returns the nearest neighbor to the given point.
    Parameters are (in order):
    - current: the base of the tree
    - pt: the point that is being searched against the tree
    - bounds: hyper-rectangle in k-space that bounds all points in the tree
    - max_dist_sq: maximum squared distance that we care about.
    - nearest neighbor (returned by reference)
    - squared distance to the nearest neighbor
    

    C++ signature :
        void nearest_neighbor(boost::shared_ptr<numeric::kdtree::KDNode> {lvalue},utility::vector1<double, std::allocator<double> >,numeric::kdtree::HyperRectangle {lvalue},double,boost::shared_ptr<numeric::kdtree::KDNode> {lvalue},double {lvalue})

nearest_neighbor( (KDTree)tree, (vector1_Real)pt, (KDNode)nearest, (float)dist_sq) -> None :
    Searches the KDtree for the nearest neigbor to a given input point,
    returns nearest neighbor and distance-squared to nearest neigbor by
    reference.
    

    C++ signature :
        void nearest_neighbor(numeric::kdtree::KDTree {lvalue},utility::vector1<double, std::allocator<double> >,boost::shared_ptr<numeric::kdtree::KDNode> {lvalue},double {lvalue})

nearest_neighbors( (KDNode)current, (vector1_Real)pt, (HyperRectangle)bounds, (float)max_dist_sq, (KDPointList)neighbors) -> None :
    Recursive function definition for search for a list of the N nearest
    neighbors, where N is defined as a member variable of the KDPointList
    object.
    

    C++ signature :
        void nearest_neighbors(boost::shared_ptr<numeric::kdtree::KDNode> {lvalue},utility::vector1<double, std::allocator<double> >,numeric::kdtree::HyperRectangle {lvalue},double,numeric::kdtree::KDPointList {lvalue})

nearest_neighbors( (KDTree)tree, (vector1_Real)pt, (int)wanted, (float)max_dist_allowed) -> KDPointList :
    numeric/kdtree/nearest_neighbors.hh:48

    C++ signature :
        numeric::kdtree::KDPointList nearest_neighbors(numeric::kdtree::KDTree {lvalue},utility::vector1<double, std::allocator<double> >,unsigned long,double)

nearest_neighbors( (KDTree)tree, (vector1_Real)pt, (int)wanted) -> KDPointList :
    Returns a KDPointList of the N nearest neighbors from the KDTree to
    the given input point.
    

    C++ signature :
        numeric::kdtree::KDPointList nearest_neighbors(numeric::kdtree::KDTree {lvalue},utility::vector1<double, std::allocator<double> >,unsigned long)

print_point( (OStream)out, (vector1_Real)point) -> None :
    numeric/kdtree/util.hh:81

    C++ signature :
        void print_point(std::ostream {lvalue},utility::vector1<double, std::allocator<double> >)

print_points( (OStream)out, (vec1_vec1_Real)points) -> None :
    numeric/kdtree/util.hh:76

    C++ signature :
        void print_points(std::ostream {lvalue},utility::vector1<utility::vector1<double, std::allocator<double> >, std::allocator<utility::vector1<double, std::allocator<double> > > >)

print_tree( (OStream)out, (KDNode)current, (int)current_depth [, (int)width=3]) -> None :
    numeric/kdtree/util.hh:113

    C++ signature :
        void print_tree(std::ostream {lvalue},boost::shared_ptr<numeric::kdtree::KDNode>,unsigned long [,unsigned long=3])

sq_vec_distance( (vector1_Real)vec1, (vector1_Real)vec2) -> float :
    distance metrics for real-valued points
    Returns the square of the Euclidean distance between the two points
    vec1 and vec2.
    

    C++ signature :
        double sq_vec_distance(utility::vector1<double, std::allocator<double> >,utility::vector1<double, std::allocator<double> >)

transform_percentile( (vec1_vec1_Real)points, (HyperRectangle)bounds) -> None :
    numeric/kdtree/util.hh:61

    C++ signature :
        void transform_percentile(utility::vector1<utility::vector1<double, std::allocator<double> >, std::allocator<utility::vector1<double, std::allocator<double> > > > {lvalue},boost::shared_ptr<numeric::kdtree::HyperRectangle>)

transform_percentile( (vec1_vec1_Real)points) -> None :
    distance metrics for real-valued points
    Transforms the list of points given into percentiles using
    a linear mapping from the input space to percentile-space for each
    variable.
    For each variable X in row R, replaces X with the quantity
    ( X - min(R) ) / ( max(R) - min(R) ). Runs in O(N) time.
    

    C++ signature :
        void transform_percentile(utility::vector1<utility::vector1<double, std::allocator<double> >, std::allocator<utility::vector1<double, std::allocator<double> > > > {lvalue})

transform_percentile_single_pt( (vector1_Real)point, (HyperRectangle)bounds) -> None :
    numeric/kdtree/util.hh:66

    C++ signature :
        void transform_percentile_single_pt(utility::vector1<double, std::allocator<double> > {lvalue},boost::shared_ptr<numeric::kdtree::HyperRectangle>)

vec_distance( (vector1_Real)vec1, (vector1_Real)vec2) -> float :
    Returns the Euclidean distance between the two points vec1 and vec2.
    

    C++ signature :
        double vec_distance(utility::vector1<double, std::allocator<double> >,utility::vector1<double, std::allocator<double> >)