Bindings for numeric::kdtree namespace

Classes
		builtins.object CompareKDPoints HyperRectangle KDNode KDPoint KDPointList KDPoint_MinDist KDTree   class CompareKDPoints(builtins.object)       Methods defined here: __call__(...) from builtins.PyCapsule __call__(self : rosetta.numeric.kdtree.CompareKDPoints, x : rosetta.numeric.kdtree.KDPoint, y : rosetta.numeric.kdtree.KDPoint) -> bool __init__(...) from builtins.PyCapsule __init__(*args, **kwargs) Overloaded function.   1. __init__(rosetta.numeric.kdtree.CompareKDPoints) -> NoneType   2. __init__(self : rosetta.numeric.kdtree.CompareKDPoints, new_idx : int) -> NoneType __new__(*args, **kwargs) from builtins.type Create and return a new object.  See help(type) for accurate signature.   class HyperRectangle(builtins.object)       Methods defined here: __init__(...) from builtins.PyCapsule __init__(*args, **kwargs) Overloaded function.   1. __init__(rosetta.numeric.kdtree.HyperRectangle) -> NoneType   2. __init__(self : rosetta.numeric.kdtree.HyperRectangle, upper : rosetta.utility.vector1_double, lower : rosetta.utility.vector1_double) -> NoneType   3. __init__(self : rosetta.numeric.kdtree.HyperRectangle, pts : rosetta.utility.vector1_utility_vector1_double_std_allocator_double_t) -> NoneType __new__(*args, **kwargs) from builtins.type Create and return a new object.  See help(type) for accurate signature. assign(...) from builtins.PyCapsule assign(self : rosetta.numeric.kdtree.HyperRectangle, src : rosetta.numeric.kdtree.HyperRectangle) -> rosetta.numeric.kdtree.HyperRectangle extend(...) from builtins.PyCapsule extend(self : rosetta.numeric.kdtree.HyperRectangle, pt : rosetta.utility.vector1_double) -> NoneType lower(...) from builtins.PyCapsule lower(rosetta.numeric.kdtree.HyperRectangle) -> rosetta.utility.vector1_double ndim(...) from builtins.PyCapsule ndim(rosetta.numeric.kdtree.HyperRectangle) -> int upper(...) from builtins.PyCapsule upper(rosetta.numeric.kdtree.HyperRectangle) -> rosetta.utility.vector1_double   class KDNode(builtins.object)       Methods defined here: __init__(...) from builtins.PyCapsule __init__(self : rosetta.numeric.kdtree.KDNode, tree : rosetta.numeric.kdtree.KDTree) -> NoneType __new__(*args, **kwargs) from builtins.type Create and return a new object.  See help(type) for accurate signature. distance(...) from builtins.PyCapsule distance(*args, **kwargs) Overloaded function.   1. distance(rosetta.numeric.kdtree.KDNode) -> float   2. distance(self : rosetta.numeric.kdtree.KDNode, new_dist : float) -> NoneType is_leaf(...) from builtins.PyCapsule is_leaf(rosetta.numeric.kdtree.KDNode) -> bool   Returns true if this node has no children, false otherwise. is_root(...) from builtins.PyCapsule is_root(rosetta.numeric.kdtree.KDNode) -> bool   Returns true if this node has no parent, false otherwise. left_child(...) from builtins.PyCapsule left_child(*args, **kwargs) Overloaded function.   1. left_child(rosetta.numeric.kdtree.KDNode) -> rosetta.numeric.kdtree.KDNode   Returns the left child of this KDNode in the tree,  or NULL if there is no left child.   2. left_child(self : rosetta.numeric.kdtree.KDNode, new_left_child : rosetta.numeric.kdtree.KDNode) -> NoneType   Sets the left child for this node. location(...) from builtins.PyCapsule location(*args, **kwargs) Overloaded function.   1. location(rosetta.numeric.kdtree.KDNode) -> rosetta.utility.vector1_double   Returns the location of this node in k-space.   2. location(self : rosetta.numeric.kdtree.KDNode, new_location : rosetta.utility.vector1_double) -> NoneType   Sets the location of this node in k-space. parent(...) from builtins.PyCapsule parent(*args, **kwargs) Overloaded function.   1. parent(rosetta.numeric.kdtree.KDNode) -> rosetta.numeric.kdtree.KDNode   Returns the parent of this KDNode in the tree,  or NULL if there is no parent.   2. parent(self : rosetta.numeric.kdtree.KDNode, new_parent : rosetta.numeric.kdtree.KDNode) -> NoneType   Sets the parent for this node. point(...) from builtins.PyCapsule point(*args, **kwargs) Overloaded function.   1. point(rosetta.numeric.kdtree.KDNode) -> rosetta.numeric.kdtree.KDPoint   2. point(self : rosetta.numeric.kdtree.KDNode, new_point : rosetta.numeric.kdtree.KDPoint) -> NoneType right_child(...) from builtins.PyCapsule right_child(*args, **kwargs) Overloaded function.   1. right_child(rosetta.numeric.kdtree.KDNode) -> rosetta.numeric.kdtree.KDNode   Returns the right child of this KDNode in the tree,  or NULL if there is no right child.   2. right_child(self : rosetta.numeric.kdtree.KDNode, new_right_child : rosetta.numeric.kdtree.KDNode) -> NoneType   Sets the right child for this node. split_axis(...) from builtins.PyCapsule split_axis(*args, **kwargs) Overloaded function.   1. split_axis(rosetta.numeric.kdtree.KDNode) -> int   Returns the dimension along which this node splits points.   2. split_axis(self : rosetta.numeric.kdtree.KDNode, axis : int) -> NoneType   Sets the dimension along which this node splits points. tree(...) from builtins.PyCapsule tree(rosetta.numeric.kdtree.KDNode) -> rosetta.numeric.kdtree.KDTree   Returns a const reference to the Tree that contains  this KDNode.   class KDPoint(builtins.object)       Methods defined here: __eq__(...) from builtins.PyCapsule __eq__(self : rosetta.numeric.kdtree.KDPoint, other : rosetta.numeric.kdtree.KDPoint) -> bool   Equality operator. Compares location() and distance(),  ignores data(). __init__(...) from builtins.PyCapsule __init__(*args, **kwargs) Overloaded function.   1. __init__(rosetta.numeric.kdtree.KDPoint) -> NoneType   2. __init__(self : rosetta.numeric.kdtree.KDPoint, location : rosetta.utility.vector1_double) -> NoneType   3. __init__(self : rosetta.numeric.kdtree.KDPoint, location : rosetta.utility.vector1_double, data : utility::pointer::ReferenceCount) -> NoneType   4. __init__(self : rosetta.numeric.kdtree.KDPoint, location : rosetta.utility.vector1_double, distance : float) -> NoneType   5. __init__(self : rosetta.numeric.kdtree.KDPoint, location : rosetta.utility.vector1_double, data : utility::pointer::ReferenceCount, distance : float) -> NoneType   6. __init__(self : rosetta.numeric.kdtree.KDPoint, src : rosetta.numeric.kdtree.KDPoint) -> NoneType __new__(*args, **kwargs) from builtins.type Create and return a new object.  See help(type) for accurate signature. assign(...) from builtins.PyCapsule assign(self : rosetta.numeric.kdtree.KDPoint, src : rosetta.numeric.kdtree.KDPoint) -> rosetta.numeric.kdtree.KDPoint   Assignment operator for KDPoint class. const_location(...) from builtins.PyCapsule const_location(rosetta.numeric.kdtree.KDPoint) -> rosetta.utility.vector1_double   Returns a const reference to the location of this point in  k-space. distance(...) from builtins.PyCapsule distance(*args, **kwargs) Overloaded function.   1. distance(rosetta.numeric.kdtree.KDPoint) -> float   getter for distance() from this point to an arbitrary point  in kd-space.   2. distance(self : rosetta.numeric.kdtree.KDPoint, dist : float) -> NoneType   Sets the distance to an arbitrary point. location(...) from builtins.PyCapsule location(*args, **kwargs) Overloaded function.   1. location(rosetta.numeric.kdtree.KDPoint) -> rosetta.utility.vector1_double   Returns to the location of this point in k-space.   2. location(self : rosetta.numeric.kdtree.KDPoint, dat : rosetta.utility.vector1_double) -> NoneType   sets the location of this point in k-space. size(...) from builtins.PyCapsule size(rosetta.numeric.kdtree.KDPoint) -> int   Returns the number of dimensions for the space in which this point  lives. to_string(...) from builtins.PyCapsule to_string(rosetta.numeric.kdtree.KDPoint) -> str   Returns a stringified version of this object.   class KDPointList(builtins.object)     Class for keeping track of the closest N KDPoint objects by distance.     Methods defined here: __getitem__(...) from builtins.PyCapsule __getitem__(self : rosetta.numeric.kdtree.KDPointList, pos : int) -> rosetta.numeric.kdtree.KDPoint __init__(...) from builtins.PyCapsule __init__(self : rosetta.numeric.kdtree.KDPointList, n_to_keep : int) -> NoneType __new__(*args, **kwargs) from builtins.type Create and return a new object.  See help(type) for accurate signature. assign(...) from builtins.PyCapsule assign(self : rosetta.numeric.kdtree.KDPointList,  : rosetta.numeric.kdtree.KDPointList) -> rosetta.numeric.kdtree.KDPointList begin(...) from builtins.PyCapsule begin(*args, **kwargs) Overloaded function.   1. begin(rosetta.numeric.kdtree.KDPointList) -> __gnu_cxx::__normal_iterator<std::shared_ptr<numeric::kdtree::KDPoint> const*, std::vector<std::shared_ptr<numeric::kdtree::KDPoint>, std::allocator<std::shared_ptr<numeric::kdtree::KDPoint> > > >   2. begin(rosetta.numeric.kdtree.KDPointList) -> __gnu_cxx::__normal_iterator<std::shared_ptr<numeric::kdtree::KDPoint>*, std::vector<std::shared_ptr<numeric::kdtree::KDPoint>, std::allocator<std::shared_ptr<numeric::kdtree::KDPoint> > > > distance_cutoff(...) from builtins.PyCapsule distance_cutoff(*args, **kwargs) Overloaded function.   1. distance_cutoff(rosetta.numeric.kdtree.KDPointList) -> float   2. distance_cutoff(self : rosetta.numeric.kdtree.KDPointList, cutoff : float) -> NoneType end(...) from builtins.PyCapsule end(*args, **kwargs) Overloaded function.   1. end(rosetta.numeric.kdtree.KDPointList) -> __gnu_cxx::__normal_iterator<std::shared_ptr<numeric::kdtree::KDPoint> const*, std::vector<std::shared_ptr<numeric::kdtree::KDPoint>, std::allocator<std::shared_ptr<numeric::kdtree::KDPoint> > > >   2. end(rosetta.numeric.kdtree.KDPointList) -> __gnu_cxx::__normal_iterator<std::shared_ptr<numeric::kdtree::KDPoint>*, std::vector<std::shared_ptr<numeric::kdtree::KDPoint>, std::allocator<std::shared_ptr<numeric::kdtree::KDPoint> > > > insert(...) from builtins.PyCapsule insert(self : rosetta.numeric.kdtree.KDPointList, pt : rosetta.numeric.kdtree.KDPoint) -> NoneType max_values(...) from builtins.PyCapsule max_values(rosetta.numeric.kdtree.KDPointList) -> int merge(...) from builtins.PyCapsule merge(self : rosetta.numeric.kdtree.KDPointList, other : rosetta.numeric.kdtree.KDPointList) -> NoneType   merge another KDPointList with this KDPointList.  This calls insert which is a little slow, and is a candidate for  optimization if the insert() method shows up in profiling. size(...) from builtins.PyCapsule size(rosetta.numeric.kdtree.KDPointList) -> int sorted_values(...) from builtins.PyCapsule sorted_values(rosetta.numeric.kdtree.KDPointList) -> rosetta.utility.vector1_std_shared_ptr_numeric_kdtree_KDPoint_t worst_distance(...) from builtins.PyCapsule worst_distance(rosetta.numeric.kdtree.KDPointList) -> float   class KDPoint_MinDist(builtins.object)       Methods defined here: __call__(...) from builtins.PyCapsule __call__(self : rosetta.numeric.kdtree.KDPoint_MinDist, a : rosetta.numeric.kdtree.KDPoint, b : rosetta.numeric.kdtree.KDPoint) -> bool __init__(...) from builtins.PyCapsule __init__(rosetta.numeric.kdtree.KDPoint_MinDist) -> NoneType __new__(*args, **kwargs) from builtins.type Create and return a new object.  See help(type) for accurate signature.   class KDTree(builtins.object)       Methods defined here: __init__(...) from builtins.PyCapsule __init__(*args, **kwargs) Overloaded function.   1. __init__(rosetta.numeric.kdtree.KDTree) -> NoneType   2. __init__(self : rosetta.numeric.kdtree.KDTree, pts : rosetta.utility.vector1_utility_vector1_double_std_allocator_double_t) -> NoneType __new__(*args, **kwargs) from builtins.type Create and return a new object.  See help(type) for accurate signature. assign(...) from builtins.PyCapsule assign(self : rosetta.numeric.kdtree.KDTree,  : rosetta.numeric.kdtree.KDTree) -> rosetta.numeric.kdtree.KDTree bounds(...) from builtins.PyCapsule bounds(rosetta.numeric.kdtree.KDTree) -> rosetta.numeric.kdtree.HyperRectangle   Returns the HyperRectangle that bounds all of the points in the  kd-tree.      A HyperRectangle is defined as two vectors upper and lower, with  each dimension of lower having the minimum value seen in each dimension,  and each dimension of higher having the maximum value seen in each  dimension. extend_bounds(...) from builtins.PyCapsule extend_bounds(self : rosetta.numeric.kdtree.KDTree, pt : rosetta.utility.vector1_double) -> NoneType   Pushes out the bounds of the HyperRectangle bounding this kd-tree  if necessary. ndim(...) from builtins.PyCapsule ndim(rosetta.numeric.kdtree.KDTree) -> int   Number of dimensions in the kd-tree. This is the "k" in kd. root(...) from builtins.PyCapsule root(*args, **kwargs) Overloaded function.   1. root(rosetta.numeric.kdtree.KDTree) -> numeric::kdtree::KDNode   Returns the KDNodeOP that is the root of the balanced kd-tree.   2. root(self : rosetta.numeric.kdtree.KDTree, new_root : numeric::kdtree::KDNode) -> NoneType   Sets the root of the kd-tree. size(...) from builtins.PyCapsule size(*args, **kwargs) Overloaded function.   1. size(rosetta.numeric.kdtree.KDTree) -> int   Number of points in the kd-tree.   2. size(self : rosetta.numeric.kdtree.KDTree, new_size : int) -> NoneType   Sets the number of points in this kd-tree.

Functions
		construct_kd_tree(...) method of builtins.PyCapsule instance construct_kd_tree(points : rosetta.utility.vector1_std_shared_ptr_numeric_kdtree_KDPoint_t, depth : int, tree : rosetta.numeric.kdtree.KDTree) -> rosetta.numeric.kdtree.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. get_percentile_bounds(...) method of builtins.PyCapsule instance get_percentile_bounds(points : rosetta.utility.vector1_utility_vector1_double_std_allocator_double_t) -> rosetta.numeric.kdtree.HyperRectangle hr_intersects_hs(...) method of builtins.PyCapsule instance hr_intersects_hs(hr : rosetta.numeric.kdtree.HyperRectangle, pt : rosetta.utility.vector1_double, r : float) -> bool   returns true if the given hyper-rectangle intersects with the given  hypersphere. is_legal_greater_than(...) method of builtins.PyCapsule instance is_legal_greater_than(current : rosetta.numeric.kdtree.KDNode, split_axis : int, split_value : float) -> bool is_legal_kdtree_below_node(...) method of builtins.PyCapsule instance is_legal_kdtree_below_node(current : rosetta.numeric.kdtree.KDNode) -> bool is_legal_less_than(...) method of builtins.PyCapsule instance is_legal_less_than(current : rosetta.numeric.kdtree.KDNode, split_axis : int, split_value : float) -> bool make_points(...) method of builtins.PyCapsule instance make_points(points : rosetta.utility.vector1_utility_vector1_double_std_allocator_double_t) -> rosetta.utility.vector1_std_shared_ptr_numeric_kdtree_KDPoint_t   Makes a vector of KDPoints. nearest_neighbor(...) method of builtins.PyCapsule instance nearest_neighbor(*args, **kwargs) Overloaded function.   1. nearest_neighbor(tree : rosetta.numeric.kdtree.KDTree, pt : rosetta.utility.vector1_double, nearest : rosetta.numeric.kdtree.KDNode, dist_sq : float) -> NoneType   Searches the KDtree for the nearest neigbor to a given input point,  returns nearest neighbor and distance-squared to nearest neigbor by  reference.   2. nearest_neighbor(current : rosetta.numeric.kdtree.KDNode, pt : rosetta.utility.vector1_double, bounds : rosetta.numeric.kdtree.HyperRectangle, max_dist_sq : float, nearest : rosetta.numeric.kdtree.KDNode, dist_sq : float) -> NoneType   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 nearest_neighbors(...) method of builtins.PyCapsule instance nearest_neighbors(*args, **kwargs) Overloaded function.   1. nearest_neighbors(tree : rosetta.numeric.kdtree.KDTree, pt : rosetta.utility.vector1_double, wanted : int) -> rosetta.numeric.kdtree.KDPointList   Returns a KDPointList of the N nearest neighbors from the KDTree to  the given input point.   2. nearest_neighbors(tree : rosetta.numeric.kdtree.KDTree, pt : rosetta.utility.vector1_double, wanted : int, max_dist_allowed : float) -> rosetta.numeric.kdtree.KDPointList   3. nearest_neighbors(current : rosetta.numeric.kdtree.KDNode, pt : rosetta.utility.vector1_double, bounds : rosetta.numeric.kdtree.HyperRectangle, max_dist_sq : float, neighbors : rosetta.numeric.kdtree.KDPointList) -> NoneType   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. sq_vec_distance(...) method of builtins.PyCapsule instance sq_vec_distance(vec1 : rosetta.utility.vector1_double, vec2 : rosetta.utility.vector1_double) -> float   Returns the square of the Euclidean distance between the two points  vec1 and vec2. transform_percentile(...) method of builtins.PyCapsule instance transform_percentile(*args, **kwargs) Overloaded function.   1. transform_percentile(points : rosetta.utility.vector1_utility_vector1_double_std_allocator_double_t) -> NoneType   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.   2. transform_percentile(points : rosetta.utility.vector1_utility_vector1_double_std_allocator_double_t, bounds : rosetta.numeric.kdtree.HyperRectangle) -> NoneType transform_percentile_single_pt(...) method of builtins.PyCapsule instance transform_percentile_single_pt(point : rosetta.utility.vector1_double, bounds : rosetta.numeric.kdtree.HyperRectangle) -> NoneType vec_distance(...) method of builtins.PyCapsule instance vec_distance(vec1 : rosetta.utility.vector1_double, vec2 : rosetta.utility.vector1_double) -> float   Returns the Euclidean distance between the two points vec1 and vec2.