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scikit-learn/sklearn/ball_tree.c

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/* Generated by Cython 0.13 on Fri Sep 2 11:24:58 2011 */
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typedef __pyx_t_5numpy_float64_t __pyx_t_7sklearn_9ball_tree_DTYPE_t;
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":323
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* ITYPE_t idx_end
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__pyx_t_7sklearn_9ball_tree_ITYPE_t idx_start;
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__pyx_t_7sklearn_9ball_tree_ITYPE_t is_leaf;
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};
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":333
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struct __pyx_t_7sklearn_9ball_tree_stack_item {
__pyx_t_7sklearn_9ball_tree_ITYPE_t i_node;
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struct __pyx_t_7sklearn_9ball_tree_stack_item *heap;
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PyObject_HEAD
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__pyx_t_7sklearn_9ball_tree_ITYPE_t (*query_radius_count_)(struct __pyx_obj_7sklearn_9ball_tree_BallTree *, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_DTYPE_t, struct __pyx_t_7sklearn_9ball_tree_stack *);
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__pyx_t_7sklearn_9ball_tree_ITYPE_t (*query_radius_distances_)(struct __pyx_obj_7sklearn_9ball_tree_BallTree *, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_DTYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t *, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, struct __pyx_t_7sklearn_9ball_tree_stack *);
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static void __Pyx_WriteUnraisable(const char *name); /*proto*/
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/* Module declarations from cpython.buffer */
/* Module declarations from cpython.ref */
/* Module declarations from libc.stdio */
/* Module declarations from cpython.object */
/* Module declarations from libc.stdlib */
/* Module declarations from numpy */
/* Module declarations from numpy */
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static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0;
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static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew2(PyObject *, PyObject *); /*proto*/
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew3(PyObject *, PyObject *, PyObject *); /*proto*/
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew4(PyObject *, PyObject *, PyObject *, PyObject *); /*proto*/
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew5(PyObject *, PyObject *, PyObject *, PyObject *, PyObject *); /*proto*/
static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/
static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *, PyObject *); /*proto*/
static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *); /*proto*/
/* Module declarations from cython */
/* Module declarations from libc */
/* Module declarations from sklearn.ball_tree */
static PyTypeObject *__pyx_ptype_7sklearn_9ball_tree_BallTree = 0;
static __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_7sklearn_9ball_tree_infinity;
static CYTHON_INLINE __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_f_7sklearn_9ball_tree_dmax(__pyx_t_7sklearn_9ball_tree_DTYPE_t, __pyx_t_7sklearn_9ball_tree_DTYPE_t); /*proto*/
static CYTHON_INLINE __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_f_7sklearn_9ball_tree_dmin(__pyx_t_7sklearn_9ball_tree_DTYPE_t, __pyx_t_7sklearn_9ball_tree_DTYPE_t); /*proto*/
static CYTHON_INLINE __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_f_7sklearn_9ball_tree_dabs(__pyx_t_7sklearn_9ball_tree_DTYPE_t); /*proto*/
static __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_f_7sklearn_9ball_tree_dist(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_DTYPE_t); /*proto*/
static __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_f_7sklearn_9ball_tree_dist_p(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_DTYPE_t); /*proto*/
static __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_f_7sklearn_9ball_tree_dist_from_dist_p(__pyx_t_7sklearn_9ball_tree_DTYPE_t, __pyx_t_7sklearn_9ball_tree_DTYPE_t); /*proto*/
static __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_f_7sklearn_9ball_tree_dist_p_from_dist(__pyx_t_7sklearn_9ball_tree_DTYPE_t, __pyx_t_7sklearn_9ball_tree_DTYPE_t); /*proto*/
static CYTHON_INLINE void __pyx_f_7sklearn_9ball_tree_stack_create(struct __pyx_t_7sklearn_9ball_tree_stack *, int); /*proto*/
static CYTHON_INLINE void __pyx_f_7sklearn_9ball_tree_stack_destroy(struct __pyx_t_7sklearn_9ball_tree_stack *); /*proto*/
static CYTHON_INLINE void __pyx_f_7sklearn_9ball_tree_stack_resize(struct __pyx_t_7sklearn_9ball_tree_stack *, int); /*proto*/
static CYTHON_INLINE void __pyx_f_7sklearn_9ball_tree_stack_push(struct __pyx_t_7sklearn_9ball_tree_stack *, struct __pyx_t_7sklearn_9ball_tree_stack_item); /*proto*/
static CYTHON_INLINE struct __pyx_t_7sklearn_9ball_tree_stack_item __pyx_f_7sklearn_9ball_tree_stack_pop(struct __pyx_t_7sklearn_9ball_tree_stack *); /*proto*/
static CYTHON_INLINE void __pyx_f_7sklearn_9ball_tree_copy_array(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
static void __pyx_f_7sklearn_9ball_tree_compute_centroid(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
static __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_f_7sklearn_9ball_tree_find_split_dim(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
static CYTHON_INLINE void __pyx_f_7sklearn_9ball_tree_iswap(__pyx_t_7sklearn_9ball_tree_ITYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
static CYTHON_INLINE void __pyx_f_7sklearn_9ball_tree_dswap(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
static void __pyx_f_7sklearn_9ball_tree_partition_indices(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
static CYTHON_INLINE __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_f_7sklearn_9ball_tree_calc_dist_LB(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_DTYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_DTYPE_t); /*proto*/
static CYTHON_INLINE __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_f_7sklearn_9ball_tree_calc_dist_p_LB(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_DTYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_DTYPE_t); /*proto*/
static CYTHON_INLINE __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_f_7sklearn_9ball_tree_pqueue_largest(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
static CYTHON_INLINE void __pyx_f_7sklearn_9ball_tree_pqueue_insert(__pyx_t_7sklearn_9ball_tree_DTYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
static CYTHON_INLINE __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_f_7sklearn_9ball_tree_max_heap_largest(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
static void __pyx_f_7sklearn_9ball_tree_max_heap_insert(__pyx_t_7sklearn_9ball_tree_DTYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
static void __pyx_f_7sklearn_9ball_tree_sort_dist_idx(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
static __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_f_7sklearn_9ball_tree_partition_dist_idx(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t); /*proto*/
#define __Pyx_MODULE_NAME "sklearn.ball_tree"
int __pyx_module_is_main_sklearn__ball_tree = 0;
/* Implementation of sklearn.ball_tree */
static PyObject *__pyx_builtin_ValueError;
static PyObject *__pyx_builtin_enumerate;
static PyObject *__pyx_builtin_range;
static PyObject *__pyx_builtin_RuntimeError;
static char __pyx_k_1[] = "new_size smaller than current";
static char __pyx_k_2[] = "popping empty stack";
static char __pyx_k_3[] = "X is an empty array";
static char __pyx_k_4[] = "X should have two dimensions";
static char __pyx_k_5[] = "p must be greater than or equal to 1";
static char __pyx_k_6[] = "leaf_size must be greater than or equal to 1";
static char __pyx_k_8[] = "query data dimension must match BallTree data dimension";
static char __pyx_k_9[] = "k must be less than or equal to the number of training points";
static char __pyx_k_13[] = "count_only and return_distance cannot both be true";
static char __pyx_k_14[] = "return_distance must be True if sort_distances is True";
static char __pyx_k_15[] = "r must be broadcastable to X.shape";
static char __pyx_k_16[] = "query_radius_idx_only_";
static char __pyx_k_17[] = "query_radius_distances_";
static char __pyx_k_18[] = "Fatal: parent is a leaf. Memory allocation is flawed";
static char __pyx_k_19[] = "zero-sized node";
static char __pyx_k_20[] = "ndarray is not C contiguous";
static char __pyx_k_21[] = "ndarray is not Fortran contiguous";
static char __pyx_k_22[] = "Non-native byte order not supported";
static char __pyx_k_23[] = "unknown dtype code in numpy.pxd (%d)";
static char __pyx_k_24[] = "Format string allocated too short, see comment in numpy.pxd";
static char __pyx_k_25[] = "Format string allocated too short.";
static char __pyx_k_26[] = "\n=========\nBall Tree\n=========\nA ball tree is a data object which speeds up nearest neighbor\nsearches in high dimensions (see scikit-learn neighbors module\ndocumentation for an overview of neighbor trees). There are many\ntypes of ball trees. This package provides a basic implementation\nin cython.\n\nImplementation Notes\n--------------------\n\nA ball tree can be thought of as a collection of nodes. Each node\nstores a centroid, a radius, and the pointers to two child nodes.\n\n* centroid : the centroid of a node is the mean of all the locations\n of points within the node\n* radius : the radius of a node is the distance from the centroid\n to the furthest point in the node.\n* subnodes : each node has a maximum of 2 child nodes. The data within\n the parent node is divided between the two child nodes.\n\nIn a typical tree implementation, nodes may be classes or structures which\nare dynamically allocated as needed. This offers flexibility in the number\nof nodes, and leads to very straightforward and readable code. It also means\nthat the tree can be dynamically augmented or pruned with new data, in an\nin-line fashion. This approach generally leads to recursive code: upon\nconstruction, the head node constructs its child nodes, the child nodes\nconstruct their child nodes, and so-on.\n\nThe current package uses a different approach: all node data is stored in\na set of numpy arrays which are pre-allocated. The main advantage of this\napproach is that the whole object can be quickly and easily saved to disk\nand reconstructed from disk. This also allows for an iterative interface\nwhich gives more control over the heap, and leads to speed. There are a\nfew disadvantages, however: once the tree is built, augmenting or pruning it\nis not as straightforward. Also, the size of the tree must be known from the\nstart, so there is not as much flexibility in building it.\n\nBallTree Pseudo-code\n~~~~~~~~~~~~~~~~~~~~\nBecause understanding a ball ""tree is simpler with recursive code, here is some\npseudo-code to show the structure of the main functionality\n\n # Ball Tree pseudo code\n\n class Node:\n #class data:\n centroid\n radius\n child1, child2\n\n #class methods:\n def construct(data):\n centroid = compute_centroid(data)\n radius = compute_radius(centroid, data)\n\n # Divide the data into two approximately equal sets.\n # This is often done by splitting along a single dimension.\n data1, data2 = divide(data)\n\n if number_of_points(data1) > 0:\n child1.construct(data1)\n\n if number_of_points(data2) > 0:\n child2.construct(data2)\n\n def query(pt, neighbors_heap):\n # compute the minimum distance from pt to any point in this node\n d = distance(point, centroid)\n if d < radius:\n min_distance = 0\n else:\n min_distance = d - radius\n\n if min_distance > max_distance_in(neighbors_heap):\n # all these points are too far away. cut off the search here\n return\n elif node_size > 1:\n child1.query(pt, neighbors_heap)\n child2.query(pt, neighbors_heap)\n\n\n object BallTree:\n #class data:\n data\n root_node\n\n #class methods\n def construct(data, num_leaves):\n root_node.construct(data)\n\n def query(point, num_neighbors):\n neighbors_heap = empty_heap_of_size(num_neighbors)\n root_node.query(point, neighbors_heap)\n\nThis certainly is not a complete description, but should give the basic idea\nof the form of the algorithm. The implementation below is much faster than\nanything mirroring the pseudo-code above, but for that reason is much more\nopaque. Here's the basic idea:\n\nBallTree Storage\n~~~~~~~~~~~~~~~~\nTh""e BallTree information is stored using a combination of\n\"Array of Structures\" and \"Structure of Arrays\" to maximize speed.\nGiven input data of size ``(n_samples, n_features)``, BallTree computes the\nexpected number of nodes ``n_nodes`` (see below), and allocates the\nfollowing arrays:\n\n* ``data`` : a float array of shape ``(n_samples, n_features)``\n This is simply the input data. If the input matrix is well-formed\n (contiguous, c-ordered, correct data type) then no copy is needed\n* ``idx_array`` : an integer array of size ``n_samples``\n This can be thought of as an array of pointers to the data in ``data``.\n Rather than shuffling around the data itself, we shuffle around pointers\n to the rows in data.\n* ``node_centroid_arr`` : a float array of shape ``(n_nodes, n_features)``\n This stores the centroid of the data in each node.\n* ``node_info_arr`` : a size-``n_nodes`` array of ``NodeInfo`` structures.\n This stores information associated with each node. Each ``NodeInfo``\n instance has the following attributes:\n - ``idx_start``\n - ``idx_end`` : ``idx_start`` and ``idx_end`` reference the part of\n ``idx_array`` which point to the data associated with the node.\n The data in node with index ``i_node`` is given by\n ``data[idx_array[idx_start:idx_end]]``\n - ``is_leaf`` : a boolean value which tells whether this node is a leaf:\n that is, whether or not it has children.\n - ``radius`` : a floating-point value which gives the distance from\n the node centroid to the furthest point in the node.\n\nOne feature here is that there are no stored pointers from parent nodes to\nchild nodes and vice-versa. These pointers are implemented implicitly:\nFor a node with index ``i``, the two children are found at indices\n``2 * i + 1`` and ``2 * i + 2``, while the parent is found at index\n``floor((i - 1) / 2)``. The root node has no parent.\n\nWith this data structure in place, the functionality of t""he above BallTree\npseudo-code can be implemented in a much more efficient manner.\nMost of the data passing done in this code uses raw data pointers.\nUsing numpy arrays would be preferable for safety, but the\noverhead of array slicing and sub-array construction leads to execution\ntime which is several orders of magnitude slower than the current\nimplementation.\n\nPriority Queue vs Max-heap\n~~~~~~~~~~~~~~~~~~~~~~~~~~\nWhen querying for more than one neighbor, the code must maintain a list of\nthe current k nearest points. The BallTree code implements this in two ways.\n\n- A priority queue: this is just a sorted list. When an item is added,\n it is inserted in the appropriate location. The cost of the search plus\n insert averages O[k].\n- A max-heap: this is a binary tree structure arranged such that each node is\n greater than its children. The cost of adding an item is O[log(k)].\n At the end of the iterations, the results must be sorted: a quicksort is\n used, which averages O[k log(k)]. Quicksort has worst-case O[k^2]\n performance, but because the input is already structured in a max-heap,\n the worst case will not be realized. Thus the sort is a one-time operation\n with cost O[k log(k)].\n\nEach insert is performed an average of log(N) times per query, where N is\nthe number of training points. Because of this, for a single query, the\npriority-queue approach costs O[k log(N)], and the max-heap approach costs\nO[log(k)log(N)] + O[k log(k)]. Tests show that for sufficiently large k,\nthe max-heap approach out-performs the priority queue approach by a factor\nof a few. In light of these tests, the code uses a priority queue for\nk < 5, and a max-heap otherwise.\n\nMemory Allocation\n~~~~~~~~~~~~~~~~~\nIt is desirable to construct a tree in as balanced a way as possible.\nGiven a training set with n_samples and a user-supplied leaf_size, if\nthe points in each node are divided as evenly as possible between the\ntwo children, the maximum de""pth needed so that leaf nodes satisfy\n``leaf_size <= n_points <= 2 * leaf_size`` is given by\n``n_levels = 1 + max(0, floor(log2((n_samples - 1) / leaf_size)))``\n(with the exception of the special case where ``n_samples < leaf_size``)\nFor a given number of levels, the number of points in a tree is given by\n``n_nodes = 2 ** n_levels - 1``. Both of these results can be shown\nby induction. Using them, the correct amount of memory can be pre-allocated\nfor a given ``n_samples`` and ``leaf_size``.\n";
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":810
*
* cdef DTYPE_t* centroid = node_centroid_arr
* cdef NodeInfo* node_info = node_info_arr # <<<<<<<<<<<<<<
* cdef NodeInfo* parent_info
* cdef DTYPE_t* point
*/
__pyx_v_node_info = __pyx_v_node_info_arr;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":816
* #------------------------------------------------------------
* # take care of the root node
* node_info.idx_start = 0 # <<<<<<<<<<<<<<
* node_info.idx_end = n_samples
* n_points = n_samples
*/
__pyx_v_node_info->idx_start = 0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":817
* # take care of the root node
* node_info.idx_start = 0
* node_info.idx_end = n_samples # <<<<<<<<<<<<<<
* n_points = n_samples
*
*/
__pyx_v_node_info->idx_end = __pyx_v_n_samples;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":818
* node_info.idx_start = 0
* node_info.idx_end = n_samples
* n_points = n_samples # <<<<<<<<<<<<<<
*
* # determine Node centroid
*/
__pyx_v_n_points = __pyx_v_n_samples;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":822
* # determine Node centroid
* compute_centroid(centroid, data, idx_array,
* n_features, n_samples) # <<<<<<<<<<<<<<
*
* # determine Node radius
*/
__pyx_f_7sklearn_9ball_tree_compute_centroid(__pyx_v_centroid, __pyx_v_data, __pyx_v_idx_array, __pyx_v_n_features, __pyx_v_n_samples);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":825
*
* # determine Node radius
* radius = 0 # <<<<<<<<<<<<<<
* for i from node_info.idx_start <= i < node_info.idx_end:
* radius = dmax(radius,
*/
__pyx_v_radius = 0.0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":826
* # determine Node radius
* radius = 0
* for i from node_info.idx_start <= i < node_info.idx_end: # <<<<<<<<<<<<<<
* radius = dmax(radius,
* dist_p(centroid, data + n_features * idx_array[i],
*/
__pyx_t_1 = __pyx_v_node_info->idx_end;
for (__pyx_v_i = __pyx_v_node_info->idx_start; __pyx_v_i < __pyx_t_1; __pyx_v_i++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":829
* radius = dmax(radius,
* dist_p(centroid, data + n_features * idx_array[i],
* n_features, p)) # <<<<<<<<<<<<<<
* node_info.radius = dist_from_dist_p(radius, p)
*
*/
__pyx_v_radius = __pyx_f_7sklearn_9ball_tree_dmax(__pyx_v_radius, __pyx_f_7sklearn_9ball_tree_dist_p(__pyx_v_centroid, (__pyx_v_data + (__pyx_v_n_features * (__pyx_v_idx_array[__pyx_v_i]))), __pyx_v_n_features, __pyx_v_p));
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":830
* dist_p(centroid, data + n_features * idx_array[i],
* n_features, p))
* node_info.radius = dist_from_dist_p(radius, p) # <<<<<<<<<<<<<<
*
* # check if this is a leaf
*/
__pyx_v_node_info->radius = __pyx_f_7sklearn_9ball_tree_dist_from_dist_p(__pyx_v_radius, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":833
*
* # check if this is a leaf
* if self.n_nodes == 1: # <<<<<<<<<<<<<<
* node_info.is_leaf = 1
*
*/
__pyx_t_2 = (__pyx_v_self->n_nodes == 1);
if (__pyx_t_2) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":834
* # check if this is a leaf
* if self.n_nodes == 1:
* node_info.is_leaf = 1 # <<<<<<<<<<<<<<
*
* else:
*/
__pyx_v_node_info->is_leaf = 1;
goto __pyx_L5;
}
/*else*/ {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":837
*
* else:
* node_info.is_leaf = 0 # <<<<<<<<<<<<<<
*
* # find dimension with largest spread
*/
__pyx_v_node_info->is_leaf = 0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":841
* # find dimension with largest spread
* i_max = find_split_dim(data, idx_array + node_info.idx_start,
* n_features, n_points) # <<<<<<<<<<<<<<
*
* # sort idx_array along this dimension
*/
__pyx_v_i_max = __pyx_f_7sklearn_9ball_tree_find_split_dim(__pyx_v_data, (__pyx_v_idx_array + __pyx_v_node_info->idx_start), __pyx_v_n_features, __pyx_v_n_points);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":849
* n_points / 2,
* n_features,
* n_points) # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_f_7sklearn_9ball_tree_partition_indices(__pyx_v_data, (__pyx_v_idx_array + __pyx_v_node_info->idx_start), __pyx_v_i_max, (__pyx_v_n_points / 2), __pyx_v_n_features, __pyx_v_n_points);
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__pyx_L5:;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":853
* #------------------------------------------------------------
* # cycle through all child nodes
* for i_node from 1 <= i_node < self.n_nodes: # <<<<<<<<<<<<<<
* i_parent = (i_node - 1) / 2
* parent_info = node_info_arr + i_parent
*/
__pyx_t_1 = __pyx_v_self->n_nodes;
for (__pyx_v_i_node = 1; __pyx_v_i_node < __pyx_t_1; __pyx_v_i_node++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":854
* # cycle through all child nodes
* for i_node from 1 <= i_node < self.n_nodes:
* i_parent = (i_node - 1) / 2 # <<<<<<<<<<<<<<
* parent_info = node_info_arr + i_parent
*
*/
__pyx_v_i_parent = ((__pyx_v_i_node - 1) / 2);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":855
* for i_node from 1 <= i_node < self.n_nodes:
* i_parent = (i_node - 1) / 2
* parent_info = node_info_arr + i_parent # <<<<<<<<<<<<<<
*
* node_info = node_info_arr + i_node
*/
__pyx_v_parent_info = (__pyx_v_node_info_arr + __pyx_v_i_parent);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":857
* parent_info = node_info_arr + i_parent
*
* node_info = node_info_arr + i_node # <<<<<<<<<<<<<<
*
* if parent_info.is_leaf:
*/
__pyx_v_node_info = (__pyx_v_node_info_arr + __pyx_v_i_node);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":859
* node_info = node_info_arr + i_node
*
* if parent_info.is_leaf: # <<<<<<<<<<<<<<
* raise ValueError("Fatal: parent is a leaf. Memory "
* "allocation is flawed")
*/
if (__pyx_v_parent_info->is_leaf) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":860
*
* if parent_info.is_leaf:
* raise ValueError("Fatal: parent is a leaf. Memory " # <<<<<<<<<<<<<<
* "allocation is flawed")
*
*/
__pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 860; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_INCREF(((PyObject *)__pyx_kp_s_18));
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__Pyx_GIVEREF(((PyObject *)__pyx_kp_s_18));
__pyx_t_4 = PyObject_Call(__pyx_builtin_ValueError, __pyx_t_3, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 860; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__Pyx_Raise(__pyx_t_4, 0, 0);
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
{__pyx_filename = __pyx_f[0]; __pyx_lineno = 860; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
goto __pyx_L8;
}
__pyx_L8:;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":863
* "allocation is flawed")
*
* if i_node < self.n_nodes / 2: # <<<<<<<<<<<<<<
* node_info.is_leaf = 0
* else:
*/
__pyx_t_2 = (__pyx_v_i_node < (__pyx_v_self->n_nodes / 2));
if (__pyx_t_2) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":864
*
* if i_node < self.n_nodes / 2:
* node_info.is_leaf = 0 # <<<<<<<<<<<<<<
* else:
* node_info.is_leaf = 1
*/
__pyx_v_node_info->is_leaf = 0;
goto __pyx_L9;
}
/*else*/ {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":866
* node_info.is_leaf = 0
* else:
* node_info.is_leaf = 1 # <<<<<<<<<<<<<<
*
* centroid = node_centroid_arr + i_node * n_features
*/
__pyx_v_node_info->is_leaf = 1;
}
__pyx_L9:;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":868
* node_info.is_leaf = 1
*
* centroid = node_centroid_arr + i_node * n_features # <<<<<<<<<<<<<<
*
* # find indices for this node
*/
__pyx_v_centroid = (__pyx_v_node_centroid_arr + (__pyx_v_i_node * __pyx_v_n_features));
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":871
*
* # find indices for this node
* idx_start = parent_info.idx_start # <<<<<<<<<<<<<<
* idx_end = parent_info.idx_end
*
*/
__pyx_v_idx_start = __pyx_v_parent_info->idx_start;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":872
* # find indices for this node
* idx_start = parent_info.idx_start
* idx_end = parent_info.idx_end # <<<<<<<<<<<<<<
*
* if i_node % 2 == 1:
*/
__pyx_v_idx_end = __pyx_v_parent_info->idx_end;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":874
* idx_end = parent_info.idx_end
*
* if i_node % 2 == 1: # <<<<<<<<<<<<<<
* idx_start = (idx_start + idx_end) / 2
* else:
*/
__pyx_t_2 = ((__pyx_v_i_node % 2) == 1);
if (__pyx_t_2) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":875
*
* if i_node % 2 == 1:
* idx_start = (idx_start + idx_end) / 2 # <<<<<<<<<<<<<<
* else:
* idx_end = (idx_start + idx_end) / 2
*/
__pyx_v_idx_start = ((__pyx_v_idx_start + __pyx_v_idx_end) / 2);
goto __pyx_L10;
}
/*else*/ {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":877
* idx_start = (idx_start + idx_end) / 2
* else:
* idx_end = (idx_start + idx_end) / 2 # <<<<<<<<<<<<<<
*
* node_info.idx_start = idx_start
*/
__pyx_v_idx_end = ((__pyx_v_idx_start + __pyx_v_idx_end) / 2);
}
__pyx_L10:;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":879
* idx_end = (idx_start + idx_end) / 2
*
* node_info.idx_start = idx_start # <<<<<<<<<<<<<<
* node_info.idx_end = idx_end
*
*/
__pyx_v_node_info->idx_start = __pyx_v_idx_start;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":880
*
* node_info.idx_start = idx_start
* node_info.idx_end = idx_end # <<<<<<<<<<<<<<
*
* n_points = idx_end - idx_start
*/
__pyx_v_node_info->idx_end = __pyx_v_idx_end;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":882
* node_info.idx_end = idx_end
*
* n_points = idx_end - idx_start # <<<<<<<<<<<<<<
*
* if n_points == 0:
*/
__pyx_v_n_points = (__pyx_v_idx_end - __pyx_v_idx_start);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":884
* n_points = idx_end - idx_start
*
* if n_points == 0: # <<<<<<<<<<<<<<
* raise ValueError("zero-sized node")
*
*/
switch (__pyx_v_n_points) {
case 0:
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":885
*
* if n_points == 0:
* raise ValueError("zero-sized node") # <<<<<<<<<<<<<<
*
* elif n_points == 1:
*/
__pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
__Pyx_INCREF(((PyObject *)__pyx_kp_s_19));
PyTuple_SET_ITEM(__pyx_t_4, 0, ((PyObject *)__pyx_kp_s_19));
__Pyx_GIVEREF(((PyObject *)__pyx_kp_s_19));
__pyx_t_3 = PyObject_Call(__pyx_builtin_ValueError, __pyx_t_4, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
__Pyx_Raise(__pyx_t_3, 0, 0);
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
{__pyx_filename = __pyx_f[0]; __pyx_lineno = 885; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
break;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":887
* raise ValueError("zero-sized node")
*
* elif n_points == 1: # <<<<<<<<<<<<<<
* #copy this point to centroid
* copy_array(centroid,
*/
case 1:
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":891
* copy_array(centroid,
* data + idx_array[idx_start] * n_features,
* n_features) # <<<<<<<<<<<<<<
*
* #store radius in array
*/
__pyx_f_7sklearn_9ball_tree_copy_array(__pyx_v_centroid, (__pyx_v_data + ((__pyx_v_idx_array[__pyx_v_idx_start]) * __pyx_v_n_features)), __pyx_v_n_features);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":894
*
* #store radius in array
* node_info.radius = 0 # <<<<<<<<<<<<<<
*
* #is a leaf
*/
__pyx_v_node_info->radius = 0.0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":897
*
* #is a leaf
* node_info.is_leaf = 1 # <<<<<<<<<<<<<<
*
* else:
*/
__pyx_v_node_info->is_leaf = 1;
break;
default:
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":902
* # determine Node centroid
* compute_centroid(centroid, data, idx_array + idx_start,
* n_features, n_points) # <<<<<<<<<<<<<<
*
* # determine Node radius
*/
__pyx_f_7sklearn_9ball_tree_compute_centroid(__pyx_v_centroid, __pyx_v_data, (__pyx_v_idx_array + __pyx_v_idx_start), __pyx_v_n_features, __pyx_v_n_points);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":905
*
* # determine Node radius
* radius = 0 # <<<<<<<<<<<<<<
* for i from idx_start <= i < idx_end:
* radius = dmax(radius,
*/
__pyx_v_radius = 0.0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":906
* # determine Node radius
* radius = 0
* for i from idx_start <= i < idx_end: # <<<<<<<<<<<<<<
* radius = dmax(radius,
* dist_p(centroid,
*/
__pyx_t_5 = __pyx_v_idx_end;
for (__pyx_v_i = __pyx_v_idx_start; __pyx_v_i < __pyx_t_5; __pyx_v_i++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":910
* dist_p(centroid,
* data + n_features * idx_array[i],
* n_features, p)) # <<<<<<<<<<<<<<
* node_info.radius = dist_from_dist_p(radius, p)
*
*/
__pyx_v_radius = __pyx_f_7sklearn_9ball_tree_dmax(__pyx_v_radius, __pyx_f_7sklearn_9ball_tree_dist_p(__pyx_v_centroid, (__pyx_v_data + (__pyx_v_n_features * (__pyx_v_idx_array[__pyx_v_i]))), __pyx_v_n_features, __pyx_v_p));
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":911
* data + n_features * idx_array[i],
* n_features, p))
* node_info.radius = dist_from_dist_p(radius, p) # <<<<<<<<<<<<<<
*
* if not node_info.is_leaf:
*/
__pyx_v_node_info->radius = __pyx_f_7sklearn_9ball_tree_dist_from_dist_p(__pyx_v_radius, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":913
* node_info.radius = dist_from_dist_p(radius, p)
*
* if not node_info.is_leaf: # <<<<<<<<<<<<<<
* # find dimension with largest spread
* i_max = find_split_dim(data, idx_array + idx_start,
*/
__pyx_t_2 = (!__pyx_v_node_info->is_leaf);
if (__pyx_t_2) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":916
* # find dimension with largest spread
* i_max = find_split_dim(data, idx_array + idx_start,
* n_features, n_points) # <<<<<<<<<<<<<<
*
* # sort indices along this dimension
*/
__pyx_v_i_max = __pyx_f_7sklearn_9ball_tree_find_split_dim(__pyx_v_data, (__pyx_v_idx_array + __pyx_v_idx_start), __pyx_v_n_features, __pyx_v_n_points);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":924
* n_points / 2,
* n_features,
* n_points) # <<<<<<<<<<<<<<
*
* cdef void query_one_(BallTree self,
*/
__pyx_f_7sklearn_9ball_tree_partition_indices(__pyx_v_data, (__pyx_v_idx_array + __pyx_v_idx_start), __pyx_v_i_max, (__pyx_v_n_points / 2), __pyx_v_n_features, __pyx_v_n_points);
goto __pyx_L13;
}
__pyx_L13:;
break;
}
}
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.ball_tree.BallTree.build_tree_");
__pyx_L0:;
__Pyx_RefNannyFinishContext();
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":926
* n_points)
*
* cdef void query_one_(BallTree self, # <<<<<<<<<<<<<<
* DTYPE_t* pt,
* ITYPE_t k,
*/
static void __pyx_f_7sklearn_9ball_tree_8BallTree_query_one_(struct __pyx_obj_7sklearn_9ball_tree_BallTree *__pyx_v_self, __pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_pt, __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_k, __pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_near_set_dist, __pyx_t_7sklearn_9ball_tree_ITYPE_t *__pyx_v_near_set_indx, struct __pyx_t_7sklearn_9ball_tree_stack *__pyx_v_node_stack, __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_use_max_heap) {
__pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_data;
__pyx_t_7sklearn_9ball_tree_ITYPE_t *__pyx_v_idx_array;
__pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_node_centroid_arr;
struct __pyx_t_7sklearn_9ball_tree_NodeInfo *__pyx_v_node_info_arr;
struct __pyx_t_7sklearn_9ball_tree_NodeInfo *__pyx_v_node_info;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_p;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_n_features;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_dist_pt;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_dist_p_LB;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_dist_p_LB_1;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_dist_p_LB_2;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i1;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i2;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i_node;
struct __pyx_t_7sklearn_9ball_tree_stack_item __pyx_v_item;
__pyx_t_7sklearn_9ball_tree_DTYPE_t (*__pyx_v_heapqueue_largest)(__pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t);
void (*__pyx_v_heapqueue_insert)(__pyx_t_7sklearn_9ball_tree_DTYPE_t, __pyx_t_7sklearn_9ball_tree_ITYPE_t, __pyx_t_7sklearn_9ball_tree_DTYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t *, __pyx_t_7sklearn_9ball_tree_ITYPE_t);
int __pyx_t_1;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_t_2;
__Pyx_RefNannySetupContext("query_one_");
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":933
* stack* node_stack,
* ITYPE_t use_max_heap):
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data # <<<<<<<<<<<<<<
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
*/
__pyx_v_data = ((__pyx_t_7sklearn_9ball_tree_DTYPE_t *)__pyx_v_self->data->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":934
* ITYPE_t use_max_heap):
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data # <<<<<<<<<<<<<<
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
*/
__pyx_v_idx_array = ((__pyx_t_7sklearn_9ball_tree_ITYPE_t *)__pyx_v_self->idx_array->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":935
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data # <<<<<<<<<<<<<<
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
* cdef NodeInfo* node_info = node_info_arr
*/
__pyx_v_node_centroid_arr = ((__pyx_t_7sklearn_9ball_tree_DTYPE_t *)__pyx_v_self->node_centroid_arr->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":936
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data # <<<<<<<<<<<<<<
* cdef NodeInfo* node_info = node_info_arr
*
*/
__pyx_v_node_info_arr = ((struct __pyx_t_7sklearn_9ball_tree_NodeInfo *)__pyx_v_self->node_info_arr->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":937
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
* cdef NodeInfo* node_info = node_info_arr # <<<<<<<<<<<<<<
*
* cdef DTYPE_t p = self.p
*/
__pyx_v_node_info = __pyx_v_node_info_arr;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":939
* cdef NodeInfo* node_info = node_info_arr
*
* cdef DTYPE_t p = self.p # <<<<<<<<<<<<<<
* cdef ITYPE_t n_features = self.data.shape[1]
*
*/
__pyx_v_p = __pyx_v_self->p;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":940
*
* cdef DTYPE_t p = self.p
* cdef ITYPE_t n_features = self.data.shape[1] # <<<<<<<<<<<<<<
*
* cdef DTYPE_t dist_pt, dist_p_LB, dist_p_LB_1, dist_p_LB_2
*/
__pyx_v_n_features = (__pyx_v_self->data->dimensions[1]);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":947
* cdef stack_item item
*
* item.i_node = 0 # <<<<<<<<<<<<<<
* item.dist_p_LB = calc_dist_p_LB(pt, node_centroid_arr,
* node_info.radius,
*/
__pyx_v_item.i_node = 0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":948
*
* item.i_node = 0
* item.dist_p_LB = calc_dist_p_LB(pt, node_centroid_arr, # <<<<<<<<<<<<<<
* node_info.radius,
* n_features, p)
*/
__pyx_v_item.dist_p_LB = __pyx_f_7sklearn_9ball_tree_calc_dist_p_LB(__pyx_v_pt, __pyx_v_node_centroid_arr, __pyx_v_node_info->radius, __pyx_v_n_features, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":951
* node_info.radius,
* n_features, p)
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* # create pointers to the priority-queue/max-heap functions.
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":959
* ITYPE_t*, ITYPE_t)
*
* if use_max_heap: # <<<<<<<<<<<<<<
* heapqueue_largest = &max_heap_largest
* heapqueue_insert = &max_heap_insert
*/
if (__pyx_v_use_max_heap) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":960
*
* if use_max_heap:
* heapqueue_largest = &max_heap_largest # <<<<<<<<<<<<<<
* heapqueue_insert = &max_heap_insert
* else:
*/
__pyx_v_heapqueue_largest = (&__pyx_f_7sklearn_9ball_tree_max_heap_largest);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":961
* if use_max_heap:
* heapqueue_largest = &max_heap_largest
* heapqueue_insert = &max_heap_insert # <<<<<<<<<<<<<<
* else:
* heapqueue_largest = &pqueue_largest
*/
__pyx_v_heapqueue_insert = (&__pyx_f_7sklearn_9ball_tree_max_heap_insert);
goto __pyx_L3;
}
/*else*/ {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":963
* heapqueue_insert = &max_heap_insert
* else:
* heapqueue_largest = &pqueue_largest # <<<<<<<<<<<<<<
* heapqueue_insert = &pqueue_insert
*
*/
__pyx_v_heapqueue_largest = (&__pyx_f_7sklearn_9ball_tree_pqueue_largest);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":964
* else:
* heapqueue_largest = &pqueue_largest
* heapqueue_insert = &pqueue_insert # <<<<<<<<<<<<<<
*
* while(node_stack.n > 0):
*/
__pyx_v_heapqueue_insert = (&__pyx_f_7sklearn_9ball_tree_pqueue_insert);
}
__pyx_L3:;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":966
* heapqueue_insert = &pqueue_insert
*
* while(node_stack.n > 0): # <<<<<<<<<<<<<<
* item = stack_pop(node_stack)
* i_node = item.i_node
*/
while (1) {
__pyx_t_1 = (__pyx_v_node_stack->n > 0);
if (!__pyx_t_1) break;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":967
*
* while(node_stack.n > 0):
* item = stack_pop(node_stack) # <<<<<<<<<<<<<<
* i_node = item.i_node
* dist_p_LB = item.dist_p_LB
*/
__pyx_v_item = __pyx_f_7sklearn_9ball_tree_stack_pop(__pyx_v_node_stack);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":968
* while(node_stack.n > 0):
* item = stack_pop(node_stack)
* i_node = item.i_node # <<<<<<<<<<<<<<
* dist_p_LB = item.dist_p_LB
*
*/
__pyx_v_i_node = __pyx_v_item.i_node;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":969
* item = stack_pop(node_stack)
* i_node = item.i_node
* dist_p_LB = item.dist_p_LB # <<<<<<<<<<<<<<
*
* node_info = node_info_arr + i_node
*/
__pyx_v_dist_p_LB = __pyx_v_item.dist_p_LB;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":971
* dist_p_LB = item.dist_p_LB
*
* node_info = node_info_arr + i_node # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_v_node_info = (__pyx_v_node_info_arr + __pyx_v_i_node);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":975
* #------------------------------------------------------------
* # Case 1: query point is outside node radius
* if dist_p_LB >= heapqueue_largest(near_set_dist, k): # <<<<<<<<<<<<<<
* continue
*
*/
__pyx_t_1 = (__pyx_v_dist_p_LB >= __pyx_v_heapqueue_largest(__pyx_v_near_set_dist, __pyx_v_k));
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":976
* # Case 1: query point is outside node radius
* if dist_p_LB >= heapqueue_largest(near_set_dist, k):
* continue # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
goto __pyx_L4_continue;
goto __pyx_L6;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":980
* #------------------------------------------------------------
* # Case 2: this is a leaf node. Update set of nearby points
* elif node_info.is_leaf: # <<<<<<<<<<<<<<
* for i from node_info.idx_start <= i < node_info.idx_end:
* dist_pt = dist_p(pt,
*/
if (__pyx_v_node_info->is_leaf) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":981
* # Case 2: this is a leaf node. Update set of nearby points
* elif node_info.is_leaf:
* for i from node_info.idx_start <= i < node_info.idx_end: # <<<<<<<<<<<<<<
* dist_pt = dist_p(pt,
* data + n_features * idx_array[i],
*/
__pyx_t_2 = __pyx_v_node_info->idx_end;
for (__pyx_v_i = __pyx_v_node_info->idx_start; __pyx_v_i < __pyx_t_2; __pyx_v_i++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":984
* dist_pt = dist_p(pt,
* data + n_features * idx_array[i],
* n_features, p) # <<<<<<<<<<<<<<
*
* if dist_pt < heapqueue_largest(near_set_dist, k):
*/
__pyx_v_dist_pt = __pyx_f_7sklearn_9ball_tree_dist_p(__pyx_v_pt, (__pyx_v_data + (__pyx_v_n_features * (__pyx_v_idx_array[__pyx_v_i]))), __pyx_v_n_features, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":986
* n_features, p)
*
* if dist_pt < heapqueue_largest(near_set_dist, k): # <<<<<<<<<<<<<<
* heapqueue_insert(dist_pt, idx_array[i],
* near_set_dist, near_set_indx, k)
*/
__pyx_t_1 = (__pyx_v_dist_pt < __pyx_v_heapqueue_largest(__pyx_v_near_set_dist, __pyx_v_k));
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":988
* if dist_pt < heapqueue_largest(near_set_dist, k):
* heapqueue_insert(dist_pt, idx_array[i],
* near_set_dist, near_set_indx, k) # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_v_heapqueue_insert(__pyx_v_dist_pt, (__pyx_v_idx_array[__pyx_v_i]), __pyx_v_near_set_dist, __pyx_v_near_set_indx, __pyx_v_k);
goto __pyx_L9;
}
__pyx_L9:;
}
goto __pyx_L6;
}
/*else*/ {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":994
* # starting with the one whose centroid is closest
* else:
* i1 = 2 * i_node + 1 # <<<<<<<<<<<<<<
* i2 = i1 + 1
* dist_p_LB_1 = calc_dist_p_LB(pt, (node_centroid_arr
*/
__pyx_v_i1 = ((2 * __pyx_v_i_node) + 1);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":995
* else:
* i1 = 2 * i_node + 1
* i2 = i1 + 1 # <<<<<<<<<<<<<<
* dist_p_LB_1 = calc_dist_p_LB(pt, (node_centroid_arr
* + i1 * n_features),
*/
__pyx_v_i2 = (__pyx_v_i1 + 1);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":999
* + i1 * n_features),
* node_info_arr[i1].radius,
* n_features, p) # <<<<<<<<<<<<<<
* dist_p_LB_2 = calc_dist_p_LB(pt, (node_centroid_arr
* + i2 * n_features),
*/
__pyx_v_dist_p_LB_1 = __pyx_f_7sklearn_9ball_tree_calc_dist_p_LB(__pyx_v_pt, (__pyx_v_node_centroid_arr + (__pyx_v_i1 * __pyx_v_n_features)), (__pyx_v_node_info_arr[__pyx_v_i1]).radius, __pyx_v_n_features, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1003
* + i2 * n_features),
* node_info_arr[i2].radius,
* n_features, p) # <<<<<<<<<<<<<<
*
* # append children to stack: last-in-first-out
*/
__pyx_v_dist_p_LB_2 = __pyx_f_7sklearn_9ball_tree_calc_dist_p_LB(__pyx_v_pt, (__pyx_v_node_centroid_arr + (__pyx_v_i2 * __pyx_v_n_features)), (__pyx_v_node_info_arr[__pyx_v_i2]).radius, __pyx_v_n_features, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1006
*
* # append children to stack: last-in-first-out
* if dist_p_LB_2 <= dist_p_LB_1: # <<<<<<<<<<<<<<
* item.i_node = i1
* item.dist_p_LB = dist_p_LB_1
*/
__pyx_t_1 = (__pyx_v_dist_p_LB_2 <= __pyx_v_dist_p_LB_1);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1007
* # append children to stack: last-in-first-out
* if dist_p_LB_2 <= dist_p_LB_1:
* item.i_node = i1 # <<<<<<<<<<<<<<
* item.dist_p_LB = dist_p_LB_1
* stack_push(node_stack, item)
*/
__pyx_v_item.i_node = __pyx_v_i1;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1008
* if dist_p_LB_2 <= dist_p_LB_1:
* item.i_node = i1
* item.dist_p_LB = dist_p_LB_1 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_v_item.dist_p_LB = __pyx_v_dist_p_LB_1;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1009
* item.i_node = i1
* item.dist_p_LB = dist_p_LB_1
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* item.i_node = i2
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1011
* stack_push(node_stack, item)
*
* item.i_node = i2 # <<<<<<<<<<<<<<
* item.dist_p_LB = dist_p_LB_2
* stack_push(node_stack, item)
*/
__pyx_v_item.i_node = __pyx_v_i2;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1012
*
* item.i_node = i2
* item.dist_p_LB = dist_p_LB_2 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_v_item.dist_p_LB = __pyx_v_dist_p_LB_2;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1013
* item.i_node = i2
* item.dist_p_LB = dist_p_LB_2
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* else:
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
goto __pyx_L10;
}
/*else*/ {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1016
*
* else:
* item.i_node = i2 # <<<<<<<<<<<<<<
* item.dist_p_LB = dist_p_LB_2
* stack_push(node_stack, item)
*/
__pyx_v_item.i_node = __pyx_v_i2;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1017
* else:
* item.i_node = i2
* item.dist_p_LB = dist_p_LB_2 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_v_item.dist_p_LB = __pyx_v_dist_p_LB_2;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1018
* item.i_node = i2
* item.dist_p_LB = dist_p_LB_2
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* item.i_node = i1
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1020
* stack_push(node_stack, item)
*
* item.i_node = i1 # <<<<<<<<<<<<<<
* item.dist_p_LB = dist_p_LB_1
* stack_push(node_stack, item)
*/
__pyx_v_item.i_node = __pyx_v_i1;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1021
*
* item.i_node = i1
* item.dist_p_LB = dist_p_LB_1 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_v_item.dist_p_LB = __pyx_v_dist_p_LB_1;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1022
* item.i_node = i1
* item.dist_p_LB = dist_p_LB_1
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* for i from 0 <= i < k:
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
}
__pyx_L10:;
}
__pyx_L6:;
__pyx_L4_continue:;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1024
* stack_push(node_stack, item)
*
* for i from 0 <= i < k: # <<<<<<<<<<<<<<
* near_set_dist[i] = dist_from_dist_p(near_set_dist[i], p)
*
*/
__pyx_t_2 = __pyx_v_k;
for (__pyx_v_i = 0; __pyx_v_i < __pyx_t_2; __pyx_v_i++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1025
*
* for i from 0 <= i < k:
* near_set_dist[i] = dist_from_dist_p(near_set_dist[i], p) # <<<<<<<<<<<<<<
*
* cdef ITYPE_t query_radius_count_(BallTree self,
*/
(__pyx_v_near_set_dist[__pyx_v_i]) = __pyx_f_7sklearn_9ball_tree_dist_from_dist_p((__pyx_v_near_set_dist[__pyx_v_i]), __pyx_v_p);
}
__Pyx_RefNannyFinishContext();
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1027
* near_set_dist[i] = dist_from_dist_p(near_set_dist[i], p)
*
* cdef ITYPE_t query_radius_count_(BallTree self, # <<<<<<<<<<<<<<
* DTYPE_t* pt, DTYPE_t r,
* stack* node_stack):
*/
static __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_f_7sklearn_9ball_tree_8BallTree_query_radius_count_(struct __pyx_obj_7sklearn_9ball_tree_BallTree *__pyx_v_self, __pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_pt, __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_r, struct __pyx_t_7sklearn_9ball_tree_stack *__pyx_v_node_stack) {
__pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_data;
__pyx_t_7sklearn_9ball_tree_ITYPE_t *__pyx_v_idx_array;
__pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_node_centroid_arr;
struct __pyx_t_7sklearn_9ball_tree_NodeInfo *__pyx_v_node_info_arr;
struct __pyx_t_7sklearn_9ball_tree_NodeInfo *__pyx_v_node_info;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_p;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_n_features;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i_node;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_count;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_r_p;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_dist_pt;
struct __pyx_t_7sklearn_9ball_tree_stack_item __pyx_v_item;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_r;
int __pyx_t_1;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_t_2;
long __pyx_t_3;
__Pyx_RefNannySetupContext("query_radius_count_");
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1030
* DTYPE_t* pt, DTYPE_t r,
* stack* node_stack):
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data # <<<<<<<<<<<<<<
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
*/
__pyx_v_data = ((__pyx_t_7sklearn_9ball_tree_DTYPE_t *)__pyx_v_self->data->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1031
* stack* node_stack):
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data # <<<<<<<<<<<<<<
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
*/
__pyx_v_idx_array = ((__pyx_t_7sklearn_9ball_tree_ITYPE_t *)__pyx_v_self->idx_array->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1032
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data # <<<<<<<<<<<<<<
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
* cdef NodeInfo* node_info = node_info_arr
*/
__pyx_v_node_centroid_arr = ((__pyx_t_7sklearn_9ball_tree_DTYPE_t *)__pyx_v_self->node_centroid_arr->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1033
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data # <<<<<<<<<<<<<<
* cdef NodeInfo* node_info = node_info_arr
*
*/
__pyx_v_node_info_arr = ((struct __pyx_t_7sklearn_9ball_tree_NodeInfo *)__pyx_v_self->node_info_arr->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1034
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
* cdef NodeInfo* node_info = node_info_arr # <<<<<<<<<<<<<<
*
* cdef DTYPE_t p = self.p
*/
__pyx_v_node_info = __pyx_v_node_info_arr;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1036
* cdef NodeInfo* node_info = node_info_arr
*
* cdef DTYPE_t p = self.p # <<<<<<<<<<<<<<
* cdef ITYPE_t n_features = self.data.shape[1]
* cdef ITYPE_t i, i_node
*/
__pyx_v_p = __pyx_v_self->p;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1037
*
* cdef DTYPE_t p = self.p
* cdef ITYPE_t n_features = self.data.shape[1] # <<<<<<<<<<<<<<
* cdef ITYPE_t i, i_node
* cdef ITYPE_t count = 0
*/
__pyx_v_n_features = (__pyx_v_self->data->dimensions[1]);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1039
* cdef ITYPE_t n_features = self.data.shape[1]
* cdef ITYPE_t i, i_node
* cdef ITYPE_t count = 0 # <<<<<<<<<<<<<<
* cdef DTYPE_t r_p = dist_p_from_dist(r, p)
* cdef DTYPE_t dist_pt
*/
__pyx_v_count = 0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1040
* cdef ITYPE_t i, i_node
* cdef ITYPE_t count = 0
* cdef DTYPE_t r_p = dist_p_from_dist(r, p) # <<<<<<<<<<<<<<
* cdef DTYPE_t dist_pt
*
*/
__pyx_v_r_p = __pyx_f_7sklearn_9ball_tree_dist_p_from_dist(__pyx_v_r, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1045
* cdef stack_item item
*
* item.i_node = 0 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_v_item.i_node = 0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1046
*
* item.i_node = 0
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* while(node_stack.n > 0):
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1048
* stack_push(node_stack, item)
*
* while(node_stack.n > 0): # <<<<<<<<<<<<<<
* item = stack_pop(node_stack)
* i_node = item.i_node
*/
while (1) {
__pyx_t_1 = (__pyx_v_node_stack->n > 0);
if (!__pyx_t_1) break;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1049
*
* while(node_stack.n > 0):
* item = stack_pop(node_stack) # <<<<<<<<<<<<<<
* i_node = item.i_node
* node_info = node_info_arr + i_node
*/
__pyx_v_item = __pyx_f_7sklearn_9ball_tree_stack_pop(__pyx_v_node_stack);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1050
* while(node_stack.n > 0):
* item = stack_pop(node_stack)
* i_node = item.i_node # <<<<<<<<<<<<<<
* node_info = node_info_arr + i_node
*
*/
__pyx_v_i_node = __pyx_v_item.i_node;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1051
* item = stack_pop(node_stack)
* i_node = item.i_node
* node_info = node_info_arr + i_node # <<<<<<<<<<<<<<
*
* dist_pt = dist(pt, node_centroid_arr + n_features * i_node,
*/
__pyx_v_node_info = (__pyx_v_node_info_arr + __pyx_v_i_node);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1054
*
* dist_pt = dist(pt, node_centroid_arr + n_features * i_node,
* n_features, p) # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_v_dist_pt = __pyx_f_7sklearn_9ball_tree_dist(__pyx_v_pt, (__pyx_v_node_centroid_arr + (__pyx_v_n_features * __pyx_v_i_node)), __pyx_v_n_features, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1059
* # Case 1: all node points are outside distance r.
* # prune this branch.
* if dist_pt - node_info.radius > r: # <<<<<<<<<<<<<<
* continue
*
*/
__pyx_t_1 = ((__pyx_v_dist_pt - __pyx_v_node_info->radius) > __pyx_v_r);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1060
* # prune this branch.
* if dist_pt - node_info.radius > r:
* continue # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
goto __pyx_L3_continue;
goto __pyx_L5;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1065
* # Case 2: all node points are within distance r
* # add all points
* elif dist_pt + node_info.radius < r: # <<<<<<<<<<<<<<
* count += (node_info.idx_end - node_info.idx_start)
*
*/
__pyx_t_1 = ((__pyx_v_dist_pt + __pyx_v_node_info->radius) < __pyx_v_r);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1066
* # add all points
* elif dist_pt + node_info.radius < r:
* count += (node_info.idx_end - node_info.idx_start) # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_v_count += (__pyx_v_node_info->idx_end - __pyx_v_node_info->idx_start);
goto __pyx_L5;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1071
* # Case 3: this is a leaf node. Go through all points to
* # determine if they fall within radius
* elif node_info.is_leaf: # <<<<<<<<<<<<<<
* for i from node_info.idx_start <= i < node_info.idx_end:
* dist_pt = dist_p(pt,
*/
if (__pyx_v_node_info->is_leaf) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1072
* # determine if they fall within radius
* elif node_info.is_leaf:
* for i from node_info.idx_start <= i < node_info.idx_end: # <<<<<<<<<<<<<<
* dist_pt = dist_p(pt,
* data + idx_array[i] * n_features,
*/
__pyx_t_2 = __pyx_v_node_info->idx_end;
for (__pyx_v_i = __pyx_v_node_info->idx_start; __pyx_v_i < __pyx_t_2; __pyx_v_i++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1075
* dist_pt = dist_p(pt,
* data + idx_array[i] * n_features,
* n_features, p) # <<<<<<<<<<<<<<
* if dist_pt <= r_p:
* count += 1
*/
__pyx_v_dist_pt = __pyx_f_7sklearn_9ball_tree_dist_p(__pyx_v_pt, (__pyx_v_data + ((__pyx_v_idx_array[__pyx_v_i]) * __pyx_v_n_features)), __pyx_v_n_features, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1076
* data + idx_array[i] * n_features,
* n_features, p)
* if dist_pt <= r_p: # <<<<<<<<<<<<<<
* count += 1
*
*/
__pyx_t_1 = (__pyx_v_dist_pt <= __pyx_v_r_p);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1077
* n_features, p)
* if dist_pt <= r_p:
* count += 1 # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_v_count += 1;
goto __pyx_L8;
}
__pyx_L8:;
}
goto __pyx_L5;
}
/*else*/ {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1082
* # Case 4: Node is not a leaf. Recursively query subnodes
* else:
* item.i_node = 2 * i_node + 1 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_v_item.i_node = ((2 * __pyx_v_i_node) + 1);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1083
* else:
* item.i_node = 2 * i_node + 1
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* item.i_node = i = 2 * i_node + 2
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1085
* stack_push(node_stack, item)
*
* item.i_node = i = 2 * i_node + 2 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_t_3 = ((2 * __pyx_v_i_node) + 2);
__pyx_v_item.i_node = __pyx_t_3;
__pyx_v_i = __pyx_t_3;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1086
*
* item.i_node = i = 2 * i_node + 2
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* return count
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
}
__pyx_L5:;
__pyx_L3_continue:;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1088
* stack_push(node_stack, item)
*
* return count # <<<<<<<<<<<<<<
*
* cdef ITYPE_t query_radius_idx_only_(BallTree self,
*/
__pyx_r = __pyx_v_count;
goto __pyx_L0;
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1090
* return count
*
* cdef ITYPE_t query_radius_idx_only_(BallTree self, # <<<<<<<<<<<<<<
* DTYPE_t* pt, DTYPE_t r,
* ITYPE_t* indices,
*/
static __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_f_7sklearn_9ball_tree_8BallTree_query_radius_idx_only_(struct __pyx_obj_7sklearn_9ball_tree_BallTree *__pyx_v_self, __pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_pt, __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_r, __pyx_t_7sklearn_9ball_tree_ITYPE_t *__pyx_v_indices, struct __pyx_t_7sklearn_9ball_tree_stack *__pyx_v_node_stack) {
__pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_data;
__pyx_t_7sklearn_9ball_tree_ITYPE_t *__pyx_v_idx_array;
__pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_node_centroid_arr;
struct __pyx_t_7sklearn_9ball_tree_NodeInfo *__pyx_v_node_info_arr;
struct __pyx_t_7sklearn_9ball_tree_NodeInfo *__pyx_v_node_info;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_p;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_n_features;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i_node;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_idx_i;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_r_p;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_dist_pt;
struct __pyx_t_7sklearn_9ball_tree_stack_item __pyx_v_item;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_r;
int __pyx_t_1;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_t_2;
long __pyx_t_3;
__Pyx_RefNannySetupContext("query_radius_idx_only_");
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1094
* ITYPE_t* indices,
* stack* node_stack):
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data # <<<<<<<<<<<<<<
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
*/
__pyx_v_data = ((__pyx_t_7sklearn_9ball_tree_DTYPE_t *)__pyx_v_self->data->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1095
* stack* node_stack):
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data # <<<<<<<<<<<<<<
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
*/
__pyx_v_idx_array = ((__pyx_t_7sklearn_9ball_tree_ITYPE_t *)__pyx_v_self->idx_array->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1096
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data # <<<<<<<<<<<<<<
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
* cdef NodeInfo* node_info = node_info_arr
*/
__pyx_v_node_centroid_arr = ((__pyx_t_7sklearn_9ball_tree_DTYPE_t *)__pyx_v_self->node_centroid_arr->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1097
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data # <<<<<<<<<<<<<<
* cdef NodeInfo* node_info = node_info_arr
*
*/
__pyx_v_node_info_arr = ((struct __pyx_t_7sklearn_9ball_tree_NodeInfo *)__pyx_v_self->node_info_arr->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1098
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
* cdef NodeInfo* node_info = node_info_arr # <<<<<<<<<<<<<<
*
* cdef DTYPE_t p = self.p
*/
__pyx_v_node_info = __pyx_v_node_info_arr;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1100
* cdef NodeInfo* node_info = node_info_arr
*
* cdef DTYPE_t p = self.p # <<<<<<<<<<<<<<
* cdef ITYPE_t n_features = self.data.shape[1]
* cdef ITYPE_t i, i_node
*/
__pyx_v_p = __pyx_v_self->p;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1101
*
* cdef DTYPE_t p = self.p
* cdef ITYPE_t n_features = self.data.shape[1] # <<<<<<<<<<<<<<
* cdef ITYPE_t i, i_node
* cdef ITYPE_t idx_i = 0
*/
__pyx_v_n_features = (__pyx_v_self->data->dimensions[1]);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1103
* cdef ITYPE_t n_features = self.data.shape[1]
* cdef ITYPE_t i, i_node
* cdef ITYPE_t idx_i = 0 # <<<<<<<<<<<<<<
* cdef DTYPE_t r_p = dist_p_from_dist(r, p)
* cdef DTYPE_t dist_pt
*/
__pyx_v_idx_i = 0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1104
* cdef ITYPE_t i, i_node
* cdef ITYPE_t idx_i = 0
* cdef DTYPE_t r_p = dist_p_from_dist(r, p) # <<<<<<<<<<<<<<
* cdef DTYPE_t dist_pt
*
*/
__pyx_v_r_p = __pyx_f_7sklearn_9ball_tree_dist_p_from_dist(__pyx_v_r, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1109
* cdef stack_item item
*
* item.i_node = 0 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_v_item.i_node = 0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1110
*
* item.i_node = 0
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* while(node_stack.n > 0):
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1112
* stack_push(node_stack, item)
*
* while(node_stack.n > 0): # <<<<<<<<<<<<<<
* item = stack_pop(node_stack)
* i_node = item.i_node
*/
while (1) {
__pyx_t_1 = (__pyx_v_node_stack->n > 0);
if (!__pyx_t_1) break;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1113
*
* while(node_stack.n > 0):
* item = stack_pop(node_stack) # <<<<<<<<<<<<<<
* i_node = item.i_node
* node_info = node_info_arr + i_node
*/
__pyx_v_item = __pyx_f_7sklearn_9ball_tree_stack_pop(__pyx_v_node_stack);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1114
* while(node_stack.n > 0):
* item = stack_pop(node_stack)
* i_node = item.i_node # <<<<<<<<<<<<<<
* node_info = node_info_arr + i_node
*
*/
__pyx_v_i_node = __pyx_v_item.i_node;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1115
* item = stack_pop(node_stack)
* i_node = item.i_node
* node_info = node_info_arr + i_node # <<<<<<<<<<<<<<
*
* dist_pt = dist(pt, node_centroid_arr + n_features * i_node,
*/
__pyx_v_node_info = (__pyx_v_node_info_arr + __pyx_v_i_node);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1118
*
* dist_pt = dist(pt, node_centroid_arr + n_features * i_node,
* n_features, p) # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_v_dist_pt = __pyx_f_7sklearn_9ball_tree_dist(__pyx_v_pt, (__pyx_v_node_centroid_arr + (__pyx_v_n_features * __pyx_v_i_node)), __pyx_v_n_features, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1123
* # Case 1: all node points are outside distance r.
* # prune this branch.
* if dist_pt - node_info.radius > r: # <<<<<<<<<<<<<<
* continue
*
*/
__pyx_t_1 = ((__pyx_v_dist_pt - __pyx_v_node_info->radius) > __pyx_v_r);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1124
* # prune this branch.
* if dist_pt - node_info.radius > r:
* continue # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
goto __pyx_L3_continue;
goto __pyx_L5;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1129
* # Case 2: all node points are within distance r
* # add all points
* elif dist_pt + node_info.radius < r: # <<<<<<<<<<<<<<
* for i from node_info.idx_start <= i < node_info.idx_end:
* indices[idx_i] = idx_array[i]
*/
__pyx_t_1 = ((__pyx_v_dist_pt + __pyx_v_node_info->radius) < __pyx_v_r);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1130
* # add all points
* elif dist_pt + node_info.radius < r:
* for i from node_info.idx_start <= i < node_info.idx_end: # <<<<<<<<<<<<<<
* indices[idx_i] = idx_array[i]
* idx_i += 1
*/
__pyx_t_2 = __pyx_v_node_info->idx_end;
for (__pyx_v_i = __pyx_v_node_info->idx_start; __pyx_v_i < __pyx_t_2; __pyx_v_i++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1131
* elif dist_pt + node_info.radius < r:
* for i from node_info.idx_start <= i < node_info.idx_end:
* indices[idx_i] = idx_array[i] # <<<<<<<<<<<<<<
* idx_i += 1
*
*/
(__pyx_v_indices[__pyx_v_idx_i]) = (__pyx_v_idx_array[__pyx_v_i]);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1132
* for i from node_info.idx_start <= i < node_info.idx_end:
* indices[idx_i] = idx_array[i]
* idx_i += 1 # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_v_idx_i += 1;
}
goto __pyx_L5;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1137
* # Case 3: this is a leaf node. Go through all points to
* # determine if they fall within radius
* elif node_info.is_leaf: # <<<<<<<<<<<<<<
* for i from node_info.idx_start <= i < node_info.idx_end:
* dist_pt = dist_p(pt,
*/
if (__pyx_v_node_info->is_leaf) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1138
* # determine if they fall within radius
* elif node_info.is_leaf:
* for i from node_info.idx_start <= i < node_info.idx_end: # <<<<<<<<<<<<<<
* dist_pt = dist_p(pt,
* data + idx_array[i] * n_features,
*/
__pyx_t_2 = __pyx_v_node_info->idx_end;
for (__pyx_v_i = __pyx_v_node_info->idx_start; __pyx_v_i < __pyx_t_2; __pyx_v_i++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1141
* dist_pt = dist_p(pt,
* data + idx_array[i] * n_features,
* n_features, p) # <<<<<<<<<<<<<<
* if dist_pt <= r_p:
* indices[idx_i] = idx_array[i]
*/
__pyx_v_dist_pt = __pyx_f_7sklearn_9ball_tree_dist_p(__pyx_v_pt, (__pyx_v_data + ((__pyx_v_idx_array[__pyx_v_i]) * __pyx_v_n_features)), __pyx_v_n_features, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1142
* data + idx_array[i] * n_features,
* n_features, p)
* if dist_pt <= r_p: # <<<<<<<<<<<<<<
* indices[idx_i] = idx_array[i]
* idx_i += 1
*/
__pyx_t_1 = (__pyx_v_dist_pt <= __pyx_v_r_p);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1143
* n_features, p)
* if dist_pt <= r_p:
* indices[idx_i] = idx_array[i] # <<<<<<<<<<<<<<
* idx_i += 1
*
*/
(__pyx_v_indices[__pyx_v_idx_i]) = (__pyx_v_idx_array[__pyx_v_i]);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1144
* if dist_pt <= r_p:
* indices[idx_i] = idx_array[i]
* idx_i += 1 # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_v_idx_i += 1;
goto __pyx_L10;
}
__pyx_L10:;
}
goto __pyx_L5;
}
/*else*/ {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1149
* # Case 4: Node is not a leaf. Recursively query subnodes
* else:
* item.i_node = 2 * i_node + 1 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_v_item.i_node = ((2 * __pyx_v_i_node) + 1);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1150
* else:
* item.i_node = 2 * i_node + 1
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* item.i_node = i = 2 * i_node + 2
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1152
* stack_push(node_stack, item)
*
* item.i_node = i = 2 * i_node + 2 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_t_3 = ((2 * __pyx_v_i_node) + 2);
__pyx_v_item.i_node = __pyx_t_3;
__pyx_v_i = __pyx_t_3;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1153
*
* item.i_node = i = 2 * i_node + 2
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* return idx_i
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
}
__pyx_L5:;
__pyx_L3_continue:;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1155
* stack_push(node_stack, item)
*
* return idx_i # <<<<<<<<<<<<<<
*
* cdef ITYPE_t query_radius_distances_(BallTree self,
*/
__pyx_r = __pyx_v_idx_i;
goto __pyx_L0;
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1157
* return idx_i
*
* cdef ITYPE_t query_radius_distances_(BallTree self, # <<<<<<<<<<<<<<
* DTYPE_t* pt, DTYPE_t r,
* ITYPE_t* indices,
*/
static __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_f_7sklearn_9ball_tree_8BallTree_query_radius_distances_(struct __pyx_obj_7sklearn_9ball_tree_BallTree *__pyx_v_self, __pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_pt, __pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_r, __pyx_t_7sklearn_9ball_tree_ITYPE_t *__pyx_v_indices, __pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_distances, struct __pyx_t_7sklearn_9ball_tree_stack *__pyx_v_node_stack) {
__pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_data;
__pyx_t_7sklearn_9ball_tree_ITYPE_t *__pyx_v_idx_array;
__pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_node_centroid_arr;
struct __pyx_t_7sklearn_9ball_tree_NodeInfo *__pyx_v_node_info_arr;
struct __pyx_t_7sklearn_9ball_tree_NodeInfo *__pyx_v_node_info;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_p;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_n_features;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i_node;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_idx_i;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_r_p;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_dist_pt;
struct __pyx_t_7sklearn_9ball_tree_stack_item __pyx_v_item;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_r;
int __pyx_t_1;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_t_2;
long __pyx_t_3;
__Pyx_RefNannySetupContext("query_radius_distances_");
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1162
* DTYPE_t* distances,
* stack* node_stack):
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data # <<<<<<<<<<<<<<
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
*/
__pyx_v_data = ((__pyx_t_7sklearn_9ball_tree_DTYPE_t *)__pyx_v_self->data->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1163
* stack* node_stack):
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data # <<<<<<<<<<<<<<
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
*/
__pyx_v_idx_array = ((__pyx_t_7sklearn_9ball_tree_ITYPE_t *)__pyx_v_self->idx_array->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1164
* cdef DTYPE_t* data = <DTYPE_t*> self.data.data
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data # <<<<<<<<<<<<<<
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
* cdef NodeInfo* node_info = node_info_arr
*/
__pyx_v_node_centroid_arr = ((__pyx_t_7sklearn_9ball_tree_DTYPE_t *)__pyx_v_self->node_centroid_arr->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1165
* cdef ITYPE_t* idx_array = <ITYPE_t*> self.idx_array.data
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data # <<<<<<<<<<<<<<
* cdef NodeInfo* node_info = node_info_arr
*
*/
__pyx_v_node_info_arr = ((struct __pyx_t_7sklearn_9ball_tree_NodeInfo *)__pyx_v_self->node_info_arr->data);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1166
* cdef DTYPE_t* node_centroid_arr = <DTYPE_t*>self.node_centroid_arr.data
* cdef NodeInfo* node_info_arr = <NodeInfo*> self.node_info_arr.data
* cdef NodeInfo* node_info = node_info_arr # <<<<<<<<<<<<<<
*
* cdef DTYPE_t p = self.p
*/
__pyx_v_node_info = __pyx_v_node_info_arr;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1168
* cdef NodeInfo* node_info = node_info_arr
*
* cdef DTYPE_t p = self.p # <<<<<<<<<<<<<<
* cdef ITYPE_t n_features = self.data.shape[1]
* cdef ITYPE_t i, i_node
*/
__pyx_v_p = __pyx_v_self->p;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1169
*
* cdef DTYPE_t p = self.p
* cdef ITYPE_t n_features = self.data.shape[1] # <<<<<<<<<<<<<<
* cdef ITYPE_t i, i_node
* cdef ITYPE_t idx_i = 0
*/
__pyx_v_n_features = (__pyx_v_self->data->dimensions[1]);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1171
* cdef ITYPE_t n_features = self.data.shape[1]
* cdef ITYPE_t i, i_node
* cdef ITYPE_t idx_i = 0 # <<<<<<<<<<<<<<
* cdef DTYPE_t r_p = dist_p_from_dist(r, p)
* cdef DTYPE_t dist_pt
*/
__pyx_v_idx_i = 0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1172
* cdef ITYPE_t i, i_node
* cdef ITYPE_t idx_i = 0
* cdef DTYPE_t r_p = dist_p_from_dist(r, p) # <<<<<<<<<<<<<<
* cdef DTYPE_t dist_pt
*
*/
__pyx_v_r_p = __pyx_f_7sklearn_9ball_tree_dist_p_from_dist(__pyx_v_r, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1177
* cdef stack_item item
*
* item.i_node = 0 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_v_item.i_node = 0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1178
*
* item.i_node = 0
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* while(node_stack.n > 0):
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1180
* stack_push(node_stack, item)
*
* while(node_stack.n > 0): # <<<<<<<<<<<<<<
* item = stack_pop(node_stack)
* i_node = item.i_node
*/
while (1) {
__pyx_t_1 = (__pyx_v_node_stack->n > 0);
if (!__pyx_t_1) break;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1181
*
* while(node_stack.n > 0):
* item = stack_pop(node_stack) # <<<<<<<<<<<<<<
* i_node = item.i_node
* node_info = node_info_arr + i_node
*/
__pyx_v_item = __pyx_f_7sklearn_9ball_tree_stack_pop(__pyx_v_node_stack);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1182
* while(node_stack.n > 0):
* item = stack_pop(node_stack)
* i_node = item.i_node # <<<<<<<<<<<<<<
* node_info = node_info_arr + i_node
*
*/
__pyx_v_i_node = __pyx_v_item.i_node;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1183
* item = stack_pop(node_stack)
* i_node = item.i_node
* node_info = node_info_arr + i_node # <<<<<<<<<<<<<<
*
* dist_pt = dist(pt, node_centroid_arr + n_features * i_node,
*/
__pyx_v_node_info = (__pyx_v_node_info_arr + __pyx_v_i_node);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1186
*
* dist_pt = dist(pt, node_centroid_arr + n_features * i_node,
* n_features, p) # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_v_dist_pt = __pyx_f_7sklearn_9ball_tree_dist(__pyx_v_pt, (__pyx_v_node_centroid_arr + (__pyx_v_n_features * __pyx_v_i_node)), __pyx_v_n_features, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1191
* # Case 1: all node points are outside distance r.
* # prune this branch.
* if dist_pt - node_info.radius > r: # <<<<<<<<<<<<<<
* continue
*
*/
__pyx_t_1 = ((__pyx_v_dist_pt - __pyx_v_node_info->radius) > __pyx_v_r);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1192
* # prune this branch.
* if dist_pt - node_info.radius > r:
* continue # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
goto __pyx_L3_continue;
goto __pyx_L5;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1197
* # Case 2: all node points are within distance r
* # add all points
* elif dist_pt + node_info.radius < r: # <<<<<<<<<<<<<<
* for i from node_info.idx_start <= i < node_info.idx_end:
* dist_pt = dist(pt,
*/
__pyx_t_1 = ((__pyx_v_dist_pt + __pyx_v_node_info->radius) < __pyx_v_r);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1198
* # add all points
* elif dist_pt + node_info.radius < r:
* for i from node_info.idx_start <= i < node_info.idx_end: # <<<<<<<<<<<<<<
* dist_pt = dist(pt,
* data + idx_array[i] * n_features,
*/
__pyx_t_2 = __pyx_v_node_info->idx_end;
for (__pyx_v_i = __pyx_v_node_info->idx_start; __pyx_v_i < __pyx_t_2; __pyx_v_i++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1201
* dist_pt = dist(pt,
* data + idx_array[i] * n_features,
* n_features, p) # <<<<<<<<<<<<<<
* indices[idx_i] = idx_array[i]
* distances[idx_i] = dist_pt
*/
__pyx_v_dist_pt = __pyx_f_7sklearn_9ball_tree_dist(__pyx_v_pt, (__pyx_v_data + ((__pyx_v_idx_array[__pyx_v_i]) * __pyx_v_n_features)), __pyx_v_n_features, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1202
* data + idx_array[i] * n_features,
* n_features, p)
* indices[idx_i] = idx_array[i] # <<<<<<<<<<<<<<
* distances[idx_i] = dist_pt
* idx_i += 1
*/
(__pyx_v_indices[__pyx_v_idx_i]) = (__pyx_v_idx_array[__pyx_v_i]);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1203
* n_features, p)
* indices[idx_i] = idx_array[i]
* distances[idx_i] = dist_pt # <<<<<<<<<<<<<<
* idx_i += 1
*
*/
(__pyx_v_distances[__pyx_v_idx_i]) = __pyx_v_dist_pt;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1204
* indices[idx_i] = idx_array[i]
* distances[idx_i] = dist_pt
* idx_i += 1 # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_v_idx_i += 1;
}
goto __pyx_L5;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1209
* # Case 3: this is a leaf node. Go through all points to
* # determine if they fall within radius
* elif node_info.is_leaf: # <<<<<<<<<<<<<<
* for i from node_info.idx_start <= i < node_info.idx_end:
* dist_pt = dist_p(pt,
*/
if (__pyx_v_node_info->is_leaf) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1210
* # determine if they fall within radius
* elif node_info.is_leaf:
* for i from node_info.idx_start <= i < node_info.idx_end: # <<<<<<<<<<<<<<
* dist_pt = dist_p(pt,
* data + idx_array[i] * n_features,
*/
__pyx_t_2 = __pyx_v_node_info->idx_end;
for (__pyx_v_i = __pyx_v_node_info->idx_start; __pyx_v_i < __pyx_t_2; __pyx_v_i++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1213
* dist_pt = dist_p(pt,
* data + idx_array[i] * n_features,
* n_features, p) # <<<<<<<<<<<<<<
* if dist_pt <= r_p:
* indices[idx_i] = idx_array[i]
*/
__pyx_v_dist_pt = __pyx_f_7sklearn_9ball_tree_dist_p(__pyx_v_pt, (__pyx_v_data + ((__pyx_v_idx_array[__pyx_v_i]) * __pyx_v_n_features)), __pyx_v_n_features, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1214
* data + idx_array[i] * n_features,
* n_features, p)
* if dist_pt <= r_p: # <<<<<<<<<<<<<<
* indices[idx_i] = idx_array[i]
* distances[idx_i] = dist_from_dist_p(dist_pt, p)
*/
__pyx_t_1 = (__pyx_v_dist_pt <= __pyx_v_r_p);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1215
* n_features, p)
* if dist_pt <= r_p:
* indices[idx_i] = idx_array[i] # <<<<<<<<<<<<<<
* distances[idx_i] = dist_from_dist_p(dist_pt, p)
* idx_i += 1
*/
(__pyx_v_indices[__pyx_v_idx_i]) = (__pyx_v_idx_array[__pyx_v_i]);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1216
* if dist_pt <= r_p:
* indices[idx_i] = idx_array[i]
* distances[idx_i] = dist_from_dist_p(dist_pt, p) # <<<<<<<<<<<<<<
* idx_i += 1
*
*/
(__pyx_v_distances[__pyx_v_idx_i]) = __pyx_f_7sklearn_9ball_tree_dist_from_dist_p(__pyx_v_dist_pt, __pyx_v_p);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1217
* indices[idx_i] = idx_array[i]
* distances[idx_i] = dist_from_dist_p(dist_pt, p)
* idx_i += 1 # <<<<<<<<<<<<<<
*
* #------------------------------------------------------------
*/
__pyx_v_idx_i += 1;
goto __pyx_L10;
}
__pyx_L10:;
}
goto __pyx_L5;
}
/*else*/ {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1222
* # Case 4: Node is not a leaf. Recursively query subnodes
* else:
* item.i_node = 2 * i_node + 1 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_v_item.i_node = ((2 * __pyx_v_i_node) + 1);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1223
* else:
* item.i_node = 2 * i_node + 1
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* item.i_node = i = 2 * i_node + 2
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1225
* stack_push(node_stack, item)
*
* item.i_node = i = 2 * i_node + 2 # <<<<<<<<<<<<<<
* stack_push(node_stack, item)
*
*/
__pyx_t_3 = ((2 * __pyx_v_i_node) + 2);
__pyx_v_item.i_node = __pyx_t_3;
__pyx_v_i = __pyx_t_3;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1226
*
* item.i_node = i = 2 * i_node + 2
* stack_push(node_stack, item) # <<<<<<<<<<<<<<
*
* return idx_i
*/
__pyx_f_7sklearn_9ball_tree_stack_push(__pyx_v_node_stack, __pyx_v_item);
}
__pyx_L5:;
__pyx_L3_continue:;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1228
* stack_push(node_stack, item)
*
* return idx_i # <<<<<<<<<<<<<<
*
*
*/
__pyx_r = __pyx_v_idx_i;
goto __pyx_L0;
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1235
* #
* @cython.profile(False)
* cdef inline void copy_array(DTYPE_t* x, DTYPE_t* y, ITYPE_t n): # <<<<<<<<<<<<<<
* # copy array y into array x
* cdef ITYPE_t i
*/
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__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i;
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1239
* cdef ITYPE_t i
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1243
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* DTYPE_t* data,
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__pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_this_pt;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_j;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_t_1;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_t_2;
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1254
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1255
*
* for j from 0 <= j < n_features:
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*
* for i from 0 <= i < n_points:
*/
(__pyx_v_centroid[__pyx_v_j]) = 0.0;
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1257
* centroid[j] = 0
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* for i from 0 <= i < n_points: # <<<<<<<<<<<<<<
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* for j from 0 <= j < n_features:
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1258
*
* for i from 0 <= i < n_points:
* this_pt = data + n_features * node_indices[i] # <<<<<<<<<<<<<<
* for j from 0 <= j < n_features:
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1259
* for i from 0 <= i < n_points:
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* for j from 0 <= j < n_features: # <<<<<<<<<<<<<<
* centroid[j] += this_pt[j]
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1260
* this_pt = data + n_features * node_indices[i]
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* for j from 0 <= j < n_features:
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1262
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1263
*
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1266
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* ITYPE_t* node_indices,
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static __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_f_7sklearn_9ball_tree_find_split_dim(__pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_data, __pyx_t_7sklearn_9ball_tree_ITYPE_t *__pyx_v_node_indices, __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_n_features, __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_n_points) {
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_min_val;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_max_val;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_val;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_spread;
__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_max_spread;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_j;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_j_max;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_r;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_t_1;
__pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_t_2;
int __pyx_t_3;
__Pyx_RefNannySetupContext("find_split_dim");
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1275
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__pyx_v_j_max = 0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1276
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* for j from 0 <= j < n_features:
*/
__pyx_v_max_spread = 0.0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1278
* max_spread = 0
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* for j from 0 <= j < n_features: # <<<<<<<<<<<<<<
* max_val = data[node_indices[0] * n_features + j]
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for (__pyx_v_j = 0; __pyx_v_j < __pyx_t_1; __pyx_v_j++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1279
*
* for j from 0 <= j < n_features:
* max_val = data[node_indices[0] * n_features + j] # <<<<<<<<<<<<<<
* min_val = max_val
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1280
* for j from 0 <= j < n_features:
* max_val = data[node_indices[0] * n_features + j]
* min_val = max_val # <<<<<<<<<<<<<<
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1281
* max_val = data[node_indices[0] * n_features + j]
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* for i from 1 <= i < n_points: # <<<<<<<<<<<<<<
* val = data[node_indices[i] * n_features + j]
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__pyx_t_2 = __pyx_v_n_points;
for (__pyx_v_i = 1; __pyx_v_i < __pyx_t_2; __pyx_v_i++) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1282
* min_val = max_val
* for i from 1 <= i < n_points:
* val = data[node_indices[i] * n_features + j] # <<<<<<<<<<<<<<
* max_val = dmax(max_val, val)
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1283
* for i from 1 <= i < n_points:
* val = data[node_indices[i] * n_features + j]
* max_val = dmax(max_val, val) # <<<<<<<<<<<<<<
* min_val = dmin(min_val, val)
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1284
* val = data[node_indices[i] * n_features + j]
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1285
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1286
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__pyx_L7:;
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1289
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1295
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1296
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1303
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1306
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1322
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1323
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*
* while True:
*/
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1325
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*/
while (1) {
if (!1) break;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1326
*
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1327
* while True:
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* for i from left <= i < right: # <<<<<<<<<<<<<<
* d1 = data[node_indices[i] * n_features + split_dim]
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1328
* midindex = left
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* d2 = data[node_indices[right] * n_features + split_dim]
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1329
* for i from left <= i < right:
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* d2 = data[node_indices[right] * n_features + split_dim] # <<<<<<<<<<<<<<
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1330
* d1 = data[node_indices[i] * n_features + split_dim]
* d2 = data[node_indices[right] * n_features + split_dim]
* if d1 < d2: # <<<<<<<<<<<<<<
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1331
* d2 = data[node_indices[right] * n_features + split_dim]
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__pyx_f_7sklearn_9ball_tree_iswap(__pyx_v_node_indices, __pyx_v_i, __pyx_v_midindex);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1332
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*/
__pyx_v_midindex += 1;
goto __pyx_L7;
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__pyx_L7:;
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1333
* iswap(node_indices, i, midindex)
* midindex += 1
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* if midindex == split_index:
* break
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__pyx_f_7sklearn_9ball_tree_iswap(__pyx_v_node_indices, __pyx_v_midindex, __pyx_v_right);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1334
* midindex += 1
* iswap(node_indices, midindex, right)
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* break
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1336
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1377
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1388
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1390
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1391
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__pyx_t_1 = ((__pyx_v_i_upper - __pyx_v_i_lower) < 2);
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1392
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1393
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goto __pyx_L6;
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1395
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__pyx_L6:;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1397
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* break
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__pyx_t_1 = (__pyx_v_i_mid == __pyx_v_i_lower);
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1398
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__pyx_v_i_mid += 1;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1399
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goto __pyx_L5_break;
goto __pyx_L7;
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__pyx_L7:;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1401
* break
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__pyx_t_1 = (__pyx_v_val >= (__pyx_v_queue[__pyx_v_i_mid]));
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1402
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1404
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1406
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1407
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1411
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1438
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1441
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static void __pyx_f_7sklearn_9ball_tree_max_heap_insert(__pyx_t_7sklearn_9ball_tree_DTYPE_t __pyx_v_val, __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_i_val, __pyx_t_7sklearn_9ball_tree_DTYPE_t *__pyx_v_heap, __pyx_t_7sklearn_9ball_tree_ITYPE_t *__pyx_v_idx_array, __pyx_t_7sklearn_9ball_tree_ITYPE_t __pyx_v_heap_size) {
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1450
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__pyx_L3:;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1453
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1457
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__pyx_v_i = 0;
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1458
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* while 1: # <<<<<<<<<<<<<<
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1459
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* ic2 = ic1 + 1
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1460
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__pyx_v_ic2 = (__pyx_v_ic1 + 1);
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1462
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__pyx_t_1 = (__pyx_v_ic1 >= __pyx_v_heap_size);
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1463
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goto __pyx_L6;
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1464
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__pyx_t_1 = (__pyx_v_ic2 >= __pyx_v_heap_size);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1465
* break
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__pyx_t_1 = ((__pyx_v_heap[__pyx_v_ic1]) > __pyx_v_val);
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1466
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__pyx_v_i_swap = __pyx_v_ic1;
goto __pyx_L7;
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/*else*/ {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1468
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goto __pyx_L5_break;
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__pyx_L7:;
goto __pyx_L6;
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1469
* else:
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* elif heap[ic1] >= heap[ic2]: # <<<<<<<<<<<<<<
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__pyx_t_1 = ((__pyx_v_heap[__pyx_v_ic1]) >= (__pyx_v_heap[__pyx_v_ic2]));
if (__pyx_t_1) {
/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1470
* break
* elif heap[ic1] >= heap[ic2]:
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* i_swap = ic1
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__pyx_t_1 = (__pyx_v_val < (__pyx_v_heap[__pyx_v_ic1]));
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/* "/home/fabian/dev/scikit-learn/sklearn/ball_tree.pyx":1471
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/*else*/ {
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":219
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":220
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":221
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":223
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":224
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__pyx_L8:;
/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":225
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":226
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":227
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":230
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":242
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":244
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":245
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":246
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__pyx_L13:;
/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":249
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":250
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goto __pyx_L14;
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":251
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__pyx_v_f = __pyx_k__h;
goto __pyx_L14;
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":252
* elif t == NPY_UBYTE: f = "B"
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if (__pyx_t_1) {
__pyx_v_f = __pyx_k__H;
goto __pyx_L14;
}
/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":253
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if (__pyx_t_1) {
__pyx_v_f = __pyx_k__i;
goto __pyx_L14;
}
/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":254
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if (__pyx_t_1) {
__pyx_v_f = __pyx_k__I;
goto __pyx_L14;
}
/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":255
* elif t == NPY_INT: f = "i"
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__pyx_v_f = __pyx_k__l;
goto __pyx_L14;
}
/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":256
* elif t == NPY_UINT: f = "I"
* elif t == NPY_LONG: f = "l"
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__pyx_t_1 = (__pyx_v_t == NPY_ULONG);
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__pyx_v_f = __pyx_k__L;
goto __pyx_L14;
}
/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":257
* elif t == NPY_LONG: f = "l"
* elif t == NPY_ULONG: f = "L"
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*/
__pyx_t_1 = (__pyx_v_t == NPY_LONGLONG);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__q;
goto __pyx_L14;
}
/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":258
* elif t == NPY_ULONG: f = "L"
* elif t == NPY_LONGLONG: f = "q"
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*/
__pyx_t_1 = (__pyx_v_t == NPY_ULONGLONG);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__Q;
goto __pyx_L14;
}
/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":259
* elif t == NPY_LONGLONG: f = "q"
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*/
__pyx_t_1 = (__pyx_v_t == NPY_FLOAT);
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__pyx_v_f = __pyx_k__f;
goto __pyx_L14;
}
/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":260
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*/
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__pyx_v_f = __pyx_k__d;
goto __pyx_L14;
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":261
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__pyx_v_f = __pyx_k__g;
goto __pyx_L14;
}
/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":262
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goto __pyx_L14;
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/* "/home/fabian/envs/p27/lib/python2.7/site-packages/Cython-0.13-py2.7-linux-x86_64.egg/Cython/Includes/numpy.pxd":263
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"need more than %d value%s to unpack", (int)index,
#else
"need more than %zd value%s to unpack", index,
#endif
(index == 1) ? "" : "s");
}
static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
PyErr_Format(PyExc_ValueError,
#if PY_VERSION_HEX < 0x02050000
"too many values to unpack (expected %d)", (int)expected);
#else
"too many values to unpack (expected %zd)", expected);
#endif
}
static void __Pyx_UnpackTupleError(PyObject *t, Py_ssize_t index) {
if (t == Py_None) {
__Pyx_RaiseNoneNotIterableError();
} else if (PyTuple_GET_SIZE(t) < index) {
__Pyx_RaiseNeedMoreValuesError(PyTuple_GET_SIZE(t));
} else {
__Pyx_RaiseTooManyValuesError(index);
}
}
static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list) {
PyObject *py_import = 0;
PyObject *empty_list = 0;
PyObject *module = 0;
PyObject *global_dict = 0;
PyObject *empty_dict = 0;
PyObject *list;
py_import = __Pyx_GetAttrString(__pyx_b, "__import__");
if (!py_import)
goto bad;
if (from_list)
list = from_list;
else {
empty_list = PyList_New(0);
if (!empty_list)
goto bad;
list = empty_list;
}
global_dict = PyModule_GetDict(__pyx_m);
if (!global_dict)
goto bad;
empty_dict = PyDict_New();
if (!empty_dict)
goto bad;
module = PyObject_CallFunctionObjArgs(py_import,
name, global_dict, empty_dict, list, NULL);
bad:
Py_XDECREF(empty_list);
Py_XDECREF(py_import);
Py_XDECREF(empty_dict);
return module;
}
static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
PyThreadState *tstate = PyThreadState_GET();
tmp_type = tstate->curexc_type;
tmp_value = tstate->curexc_value;
tmp_tb = tstate->curexc_traceback;
tstate->curexc_type = type;
tstate->curexc_value = value;
tstate->curexc_traceback = tb;
Py_XDECREF(tmp_type);
Py_XDECREF(tmp_value);
Py_XDECREF(tmp_tb);
}
static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb) {
PyThreadState *tstate = PyThreadState_GET();
*type = tstate->curexc_type;
*value = tstate->curexc_value;
*tb = tstate->curexc_traceback;
tstate->curexc_type = 0;
tstate->curexc_value = 0;
tstate->curexc_traceback = 0;
}
#if PY_MAJOR_VERSION < 3
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb) {
Py_XINCREF(type);
Py_XINCREF(value);
Py_XINCREF(tb);
/* First, check the traceback argument, replacing None with NULL. */
if (tb == Py_None) {
Py_DECREF(tb);
tb = 0;
}
else if (tb != NULL && !PyTraceBack_Check(tb)) {
PyErr_SetString(PyExc_TypeError,
"raise: arg 3 must be a traceback or None");
goto raise_error;
}
/* Next, replace a missing value with None */
if (value == NULL) {
value = Py_None;
Py_INCREF(value);
}
#if PY_VERSION_HEX < 0x02050000
if (!PyClass_Check(type))
#else
if (!PyType_Check(type))
#endif
{
/* Raising an instance. The value should be a dummy. */
if (value != Py_None) {
PyErr_SetString(PyExc_TypeError,
"instance exception may not have a separate value");
goto raise_error;
}
/* Normalize to raise <class>, <instance> */
Py_DECREF(value);
value = type;
#if PY_VERSION_HEX < 0x02050000
if (PyInstance_Check(type)) {
type = (PyObject*) ((PyInstanceObject*)type)->in_class;
Py_INCREF(type);
}
else {
type = 0;
PyErr_SetString(PyExc_TypeError,
"raise: exception must be an old-style class or instance");
goto raise_error;
}
#else
type = (PyObject*) Py_TYPE(type);
Py_INCREF(type);
if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) {
PyErr_SetString(PyExc_TypeError,
"raise: exception class must be a subclass of BaseException");
goto raise_error;
}
#endif
}
__Pyx_ErrRestore(type, value, tb);
return;
raise_error:
Py_XDECREF(value);
Py_XDECREF(type);
Py_XDECREF(tb);
return;
}
#else /* Python 3+ */
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb) {
if (tb == Py_None) {
tb = 0;
} else if (tb && !PyTraceBack_Check(tb)) {
PyErr_SetString(PyExc_TypeError,
"raise: arg 3 must be a traceback or None");
goto bad;
}
if (value == Py_None)
value = 0;
if (PyExceptionInstance_Check(type)) {
if (value) {
PyErr_SetString(PyExc_TypeError,
"instance exception may not have a separate value");
goto bad;
}
value = type;
type = (PyObject*) Py_TYPE(value);
} else if (!PyExceptionClass_Check(type)) {
PyErr_SetString(PyExc_TypeError,
"raise: exception class must be a subclass of BaseException");
goto bad;
}
PyErr_SetObject(type, value);
if (tb) {
PyThreadState *tstate = PyThreadState_GET();
PyObject* tmp_tb = tstate->curexc_traceback;
if (tb != tmp_tb) {
Py_INCREF(tb);
tstate->curexc_traceback = tb;
Py_XDECREF(tmp_tb);
}
}
bad:
return;
}
#endif
static CYTHON_INLINE npy_int32 __Pyx_PyInt_from_py_npy_int32(PyObject* x) {
const npy_int32 neg_one = (npy_int32)-1, const_zero = (npy_int32)0;
const int is_unsigned = const_zero < neg_one;
if (sizeof(npy_int32) == sizeof(char)) {
if (is_unsigned)
return (npy_int32)__Pyx_PyInt_AsUnsignedChar(x);
else
return (npy_int32)__Pyx_PyInt_AsSignedChar(x);
} else if (sizeof(npy_int32) == sizeof(short)) {
if (is_unsigned)
return (npy_int32)__Pyx_PyInt_AsUnsignedShort(x);
else
return (npy_int32)__Pyx_PyInt_AsSignedShort(x);
} else if (sizeof(npy_int32) == sizeof(int)) {
if (is_unsigned)
return (npy_int32)__Pyx_PyInt_AsUnsignedInt(x);
else
return (npy_int32)__Pyx_PyInt_AsSignedInt(x);
} else if (sizeof(npy_int32) == sizeof(long)) {
if (is_unsigned)
return (npy_int32)__Pyx_PyInt_AsUnsignedLong(x);
else
return (npy_int32)__Pyx_PyInt_AsSignedLong(x);
} else if (sizeof(npy_int32) == sizeof(PY_LONG_LONG)) {
if (is_unsigned)
return (npy_int32)__Pyx_PyInt_AsUnsignedLongLong(x);
else
return (npy_int32)__Pyx_PyInt_AsSignedLongLong(x);
} else {
npy_int32 val;
PyObject *v = __Pyx_PyNumber_Int(x);
#if PY_VERSION_HEX < 0x03000000
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
return (npy_int32)-1;
}
}
static CYTHON_INLINE long __Pyx_pow_long(long b, long e) {
long t = b;
switch (e) {
case 3:
t *= b;
case 2:
t *= b;
case 1:
return t;
case 0:
return 1;
}
if (unlikely(e<0)) return 0;
t = 1;
while (likely(e)) {
t *= (b * (e&1)) | ((~e)&1); /* 1 or b */
b *= b;
e >>= 1;
}
return t;
}
static CYTHON_INLINE PyObject *__Pyx_PyInt_to_py_npy_int32(npy_int32 val) {
const npy_int32 neg_one = (npy_int32)-1, const_zero = (npy_int32)0;
const int is_unsigned = const_zero < neg_one;
if ((sizeof(npy_int32) == sizeof(char)) ||
(sizeof(npy_int32) == sizeof(short))) {
return PyInt_FromLong((long)val);
} else if ((sizeof(npy_int32) == sizeof(int)) ||
(sizeof(npy_int32) == sizeof(long))) {
if (is_unsigned)
return PyLong_FromUnsignedLong((unsigned long)val);
else
return PyInt_FromLong((long)val);
} else if (sizeof(npy_int32) == sizeof(PY_LONG_LONG)) {
if (is_unsigned)
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG)val);
else
return PyLong_FromLongLong((PY_LONG_LONG)val);
} else {
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
return _PyLong_FromByteArray(bytes, sizeof(npy_int32),
little, !is_unsigned);
}
}
static CYTHON_INLINE PyObject *__Pyx_PyInt_to_py_Py_intptr_t(Py_intptr_t val) {
const Py_intptr_t neg_one = (Py_intptr_t)-1, const_zero = (Py_intptr_t)0;
const int is_unsigned = const_zero < neg_one;
if ((sizeof(Py_intptr_t) == sizeof(char)) ||
(sizeof(Py_intptr_t) == sizeof(short))) {
return PyInt_FromLong((long)val);
} else if ((sizeof(Py_intptr_t) == sizeof(int)) ||
(sizeof(Py_intptr_t) == sizeof(long))) {
if (is_unsigned)
return PyLong_FromUnsignedLong((unsigned long)val);
else
return PyInt_FromLong((long)val);
} else if (sizeof(Py_intptr_t) == sizeof(PY_LONG_LONG)) {
if (is_unsigned)
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG)val);
else
return PyLong_FromLongLong((PY_LONG_LONG)val);
} else {
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
return _PyLong_FromByteArray(bytes, sizeof(Py_intptr_t),
little, !is_unsigned);
}
}
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
return ::std::complex< float >(x, y);
}
#else
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
return x + y*(__pyx_t_float_complex)_Complex_I;
}
#endif
#else
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
__pyx_t_float_complex z;
z.real = x;
z.imag = y;
return z;
}
#endif
#if CYTHON_CCOMPLEX
#else
static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
return (a.real == b.real) && (a.imag == b.imag);
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
z.real = a.real + b.real;
z.imag = a.imag + b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
z.real = a.real - b.real;
z.imag = a.imag - b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
z.real = a.real * b.real - a.imag * b.imag;
z.imag = a.real * b.imag + a.imag * b.real;
return z;
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
float denom = b.real * b.real + b.imag * b.imag;
z.real = (a.real * b.real + a.imag * b.imag) / denom;
z.imag = (a.imag * b.real - a.real * b.imag) / denom;
return z;
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex a) {
__pyx_t_float_complex z;
z.real = -a.real;
z.imag = -a.imag;
return z;
}
static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex a) {
return (a.real == 0) && (a.imag == 0);
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex a) {
__pyx_t_float_complex z;
z.real = a.real;
z.imag = -a.imag;
return z;
}
/*
static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex z) {
#if HAVE_HYPOT
return hypotf(z.real, z.imag);
#else
return sqrtf(z.real*z.real + z.imag*z.imag);
#endif
}
*/
#endif
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
return ::std::complex< double >(x, y);
}
#else
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
return x + y*(__pyx_t_double_complex)_Complex_I;
}
#endif
#else
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
__pyx_t_double_complex z;
z.real = x;
z.imag = y;
return z;
}
#endif
#if CYTHON_CCOMPLEX
#else
static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex a, __pyx_t_double_complex b) {
return (a.real == b.real) && (a.imag == b.imag);
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
z.real = a.real + b.real;
z.imag = a.imag + b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
z.real = a.real - b.real;
z.imag = a.imag - b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
z.real = a.real * b.real - a.imag * b.imag;
z.imag = a.real * b.imag + a.imag * b.real;
return z;
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
double denom = b.real * b.real + b.imag * b.imag;
z.real = (a.real * b.real + a.imag * b.imag) / denom;
z.imag = (a.imag * b.real - a.real * b.imag) / denom;
return z;
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex a) {
__pyx_t_double_complex z;
z.real = -a.real;
z.imag = -a.imag;
return z;
}
static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex a) {
return (a.real == 0) && (a.imag == 0);
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex a) {
__pyx_t_double_complex z;
z.real = a.real;
z.imag = -a.imag;
return z;
}
/*
static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex z) {
#if HAVE_HYPOT
return hypot(z.real, z.imag);
#else
return sqrt(z.real*z.real + z.imag*z.imag);
#endif
}
*/
#endif
static CYTHON_INLINE unsigned char __Pyx_PyInt_AsUnsignedChar(PyObject* x) {
const unsigned char neg_one = (unsigned char)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(unsigned char) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(unsigned char)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to unsigned char" :
"value too large to convert to unsigned char");
}
return (unsigned char)-1;
}
return (unsigned char)val;
}
return (unsigned char)__Pyx_PyInt_AsUnsignedLong(x);
}
static CYTHON_INLINE unsigned short __Pyx_PyInt_AsUnsignedShort(PyObject* x) {
const unsigned short neg_one = (unsigned short)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(unsigned short) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(unsigned short)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to unsigned short" :
"value too large to convert to unsigned short");
}
return (unsigned short)-1;
}
return (unsigned short)val;
}
return (unsigned short)__Pyx_PyInt_AsUnsignedLong(x);
}
static CYTHON_INLINE unsigned int __Pyx_PyInt_AsUnsignedInt(PyObject* x) {
const unsigned int neg_one = (unsigned int)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(unsigned int) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(unsigned int)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to unsigned int" :
"value too large to convert to unsigned int");
}
return (unsigned int)-1;
}
return (unsigned int)val;
}
return (unsigned int)__Pyx_PyInt_AsUnsignedLong(x);
}
static CYTHON_INLINE char __Pyx_PyInt_AsChar(PyObject* x) {
const char neg_one = (char)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(char) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(char)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to char" :
"value too large to convert to char");
}
return (char)-1;
}
return (char)val;
}
return (char)__Pyx_PyInt_AsLong(x);
}
static CYTHON_INLINE short __Pyx_PyInt_AsShort(PyObject* x) {
const short neg_one = (short)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(short) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(short)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to short" :
"value too large to convert to short");
}
return (short)-1;
}
return (short)val;
}
return (short)__Pyx_PyInt_AsLong(x);
}
static CYTHON_INLINE int __Pyx_PyInt_AsInt(PyObject* x) {
const int neg_one = (int)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(int) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(int)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to int" :
"value too large to convert to int");
}
return (int)-1;
}
return (int)val;
}
return (int)__Pyx_PyInt_AsLong(x);
}
static CYTHON_INLINE signed char __Pyx_PyInt_AsSignedChar(PyObject* x) {
const signed char neg_one = (signed char)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(signed char) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(signed char)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to signed char" :
"value too large to convert to signed char");
}
return (signed char)-1;
}
return (signed char)val;
}
return (signed char)__Pyx_PyInt_AsSignedLong(x);
}
static CYTHON_INLINE signed short __Pyx_PyInt_AsSignedShort(PyObject* x) {
const signed short neg_one = (signed short)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(signed short) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(signed short)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to signed short" :
"value too large to convert to signed short");
}
return (signed short)-1;
}
return (signed short)val;
}
return (signed short)__Pyx_PyInt_AsSignedLong(x);
}
static CYTHON_INLINE signed int __Pyx_PyInt_AsSignedInt(PyObject* x) {
const signed int neg_one = (signed int)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(signed int) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(signed int)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to signed int" :
"value too large to convert to signed int");
}
return (signed int)-1;
}
return (signed int)val;
}
return (signed int)__Pyx_PyInt_AsSignedLong(x);
}
static CYTHON_INLINE int __Pyx_PyInt_AsLongDouble(PyObject* x) {
const int neg_one = (int)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(int) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(int)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to int" :
"value too large to convert to int");
}
return (int)-1;
}
return (int)val;
}
return (int)__Pyx_PyInt_AsLong(x);
}
static CYTHON_INLINE unsigned long __Pyx_PyInt_AsUnsignedLong(PyObject* x) {
const unsigned long neg_one = (unsigned long)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to unsigned long");
return (unsigned long)-1;
}
return (unsigned long)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to unsigned long");
return (unsigned long)-1;
}
return PyLong_AsUnsignedLong(x);
} else {
return PyLong_AsLong(x);
}
} else {
unsigned long val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (unsigned long)-1;
val = __Pyx_PyInt_AsUnsignedLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static CYTHON_INLINE unsigned PY_LONG_LONG __Pyx_PyInt_AsUnsignedLongLong(PyObject* x) {
const unsigned PY_LONG_LONG neg_one = (unsigned PY_LONG_LONG)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to unsigned PY_LONG_LONG");
return (unsigned PY_LONG_LONG)-1;
}
return (unsigned PY_LONG_LONG)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to unsigned PY_LONG_LONG");
return (unsigned PY_LONG_LONG)-1;
}
return PyLong_AsUnsignedLongLong(x);
} else {
return PyLong_AsLongLong(x);
}
} else {
unsigned PY_LONG_LONG val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (unsigned PY_LONG_LONG)-1;
val = __Pyx_PyInt_AsUnsignedLongLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static CYTHON_INLINE long __Pyx_PyInt_AsLong(PyObject* x) {
const long neg_one = (long)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to long");
return (long)-1;
}
return (long)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to long");
return (long)-1;
}
return PyLong_AsUnsignedLong(x);
} else {
return PyLong_AsLong(x);
}
} else {
long val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (long)-1;
val = __Pyx_PyInt_AsLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static CYTHON_INLINE PY_LONG_LONG __Pyx_PyInt_AsLongLong(PyObject* x) {
const PY_LONG_LONG neg_one = (PY_LONG_LONG)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to PY_LONG_LONG");
return (PY_LONG_LONG)-1;
}
return (PY_LONG_LONG)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to PY_LONG_LONG");
return (PY_LONG_LONG)-1;
}
return PyLong_AsUnsignedLongLong(x);
} else {
return PyLong_AsLongLong(x);
}
} else {
PY_LONG_LONG val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (PY_LONG_LONG)-1;
val = __Pyx_PyInt_AsLongLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static CYTHON_INLINE signed long __Pyx_PyInt_AsSignedLong(PyObject* x) {
const signed long neg_one = (signed long)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to signed long");
return (signed long)-1;
}
return (signed long)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to signed long");
return (signed long)-1;
}
return PyLong_AsUnsignedLong(x);
} else {
return PyLong_AsLong(x);
}
} else {
signed long val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (signed long)-1;
val = __Pyx_PyInt_AsSignedLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static CYTHON_INLINE signed PY_LONG_LONG __Pyx_PyInt_AsSignedLongLong(PyObject* x) {
const signed PY_LONG_LONG neg_one = (signed PY_LONG_LONG)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to signed PY_LONG_LONG");
return (signed PY_LONG_LONG)-1;
}
return (signed PY_LONG_LONG)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to signed PY_LONG_LONG");
return (signed PY_LONG_LONG)-1;
}
return PyLong_AsUnsignedLongLong(x);
} else {
return PyLong_AsLongLong(x);
}
} else {
signed PY_LONG_LONG val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (signed PY_LONG_LONG)-1;
val = __Pyx_PyInt_AsSignedLongLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static void __Pyx_WriteUnraisable(const char *name) {
PyObject *old_exc, *old_val, *old_tb;
PyObject *ctx;
__Pyx_ErrFetch(&old_exc, &old_val, &old_tb);
#if PY_MAJOR_VERSION < 3
ctx = PyString_FromString(name);
#else
ctx = PyUnicode_FromString(name);
#endif
__Pyx_ErrRestore(old_exc, old_val, old_tb);
if (!ctx) {
PyErr_WriteUnraisable(Py_None);
} else {
PyErr_WriteUnraisable(ctx);
Py_DECREF(ctx);
}
}
static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
#if PY_VERSION_HEX >= 0x02070000 && !(PY_MAJOR_VERSION==3&&PY_MINOR_VERSION==0)
PyObject *ob = PyCapsule_New(vtable, 0, 0);
#else
PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
#endif
if (!ob)
goto bad;
if (PyDict_SetItemString(dict, "__pyx_vtable__", ob) < 0)
goto bad;
Py_DECREF(ob);
return 0;
bad:
Py_XDECREF(ob);
return -1;
}
#ifndef __PYX_HAVE_RT_ImportType
#define __PYX_HAVE_RT_ImportType
static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name,
long size, int strict)
{
PyObject *py_module = 0;
PyObject *result = 0;
PyObject *py_name = 0;
char warning[200];
py_module = __Pyx_ImportModule(module_name);
if (!py_module)
goto bad;
#if PY_MAJOR_VERSION < 3
py_name = PyString_FromString(class_name);
#else
py_name = PyUnicode_FromString(class_name);
#endif
if (!py_name)
goto bad;
result = PyObject_GetAttr(py_module, py_name);
Py_DECREF(py_name);
py_name = 0;
Py_DECREF(py_module);
py_module = 0;
if (!result)
goto bad;
if (!PyType_Check(result)) {
PyErr_Format(PyExc_TypeError,
"%s.%s is not a type object",
module_name, class_name);
goto bad;
}
if (!strict && ((PyTypeObject *)result)->tp_basicsize > size) {
PyOS_snprintf(warning, sizeof(warning),
"%s.%s size changed, may indicate binary incompatibility",
module_name, class_name);
#if PY_VERSION_HEX < 0x02050000
PyErr_Warn(NULL, warning);
#else
PyErr_WarnEx(NULL, warning, 0);
#endif
}
else if (((PyTypeObject *)result)->tp_basicsize != size) {
PyErr_Format(PyExc_ValueError,
"%s.%s has the wrong size, try recompiling",
module_name, class_name);
goto bad;
}
return (PyTypeObject *)result;
bad:
Py_XDECREF(py_module);
Py_XDECREF(result);
return 0;
}
#endif
#ifndef __PYX_HAVE_RT_ImportModule
#define __PYX_HAVE_RT_ImportModule
static PyObject *__Pyx_ImportModule(const char *name) {
PyObject *py_name = 0;
PyObject *py_module = 0;
#if PY_MAJOR_VERSION < 3
py_name = PyString_FromString(name);
#else
py_name = PyUnicode_FromString(name);
#endif
if (!py_name)
goto bad;
py_module = PyImport_Import(py_name);
Py_DECREF(py_name);
return py_module;
bad:
Py_XDECREF(py_name);
return 0;
}
#endif
#include "compile.h"
#include "frameobject.h"
#include "traceback.h"
static void __Pyx_AddTraceback(const char *funcname) {
PyObject *py_srcfile = 0;
PyObject *py_funcname = 0;
PyObject *py_globals = 0;
PyCodeObject *py_code = 0;
PyFrameObject *py_frame = 0;
#if PY_MAJOR_VERSION < 3
py_srcfile = PyString_FromString(__pyx_filename);
#else
py_srcfile = PyUnicode_FromString(__pyx_filename);
#endif
if (!py_srcfile) goto bad;
if (__pyx_clineno) {
#if PY_MAJOR_VERSION < 3
py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, __pyx_clineno);
#else
py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, __pyx_clineno);
#endif
}
else {
#if PY_MAJOR_VERSION < 3
py_funcname = PyString_FromString(funcname);
#else
py_funcname = PyUnicode_FromString(funcname);
#endif
}
if (!py_funcname) goto bad;
py_globals = PyModule_GetDict(__pyx_m);
if (!py_globals) goto bad;
py_code = PyCode_New(
0, /*int argcount,*/
#if PY_MAJOR_VERSION >= 3
0, /*int kwonlyargcount,*/
#endif
0, /*int nlocals,*/
0, /*int stacksize,*/
0, /*int flags,*/
__pyx_empty_bytes, /*PyObject *code,*/
__pyx_empty_tuple, /*PyObject *consts,*/
__pyx_empty_tuple, /*PyObject *names,*/
__pyx_empty_tuple, /*PyObject *varnames,*/
__pyx_empty_tuple, /*PyObject *freevars,*/
__pyx_empty_tuple, /*PyObject *cellvars,*/
py_srcfile, /*PyObject *filename,*/
py_funcname, /*PyObject *name,*/
__pyx_lineno, /*int firstlineno,*/
__pyx_empty_bytes /*PyObject *lnotab*/
);
if (!py_code) goto bad;
py_frame = PyFrame_New(
PyThreadState_GET(), /*PyThreadState *tstate,*/
py_code, /*PyCodeObject *code,*/
py_globals, /*PyObject *globals,*/
0 /*PyObject *locals*/
);
if (!py_frame) goto bad;
py_frame->f_lineno = __pyx_lineno;
PyTraceBack_Here(py_frame);
bad:
Py_XDECREF(py_srcfile);
Py_XDECREF(py_funcname);
Py_XDECREF(py_code);
Py_XDECREF(py_frame);
}
static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
while (t->p) {
#if PY_MAJOR_VERSION < 3
if (t->is_unicode) {
*t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
} else if (t->intern) {
*t->p = PyString_InternFromString(t->s);
} else {
*t->p = PyString_FromStringAndSize(t->s, t->n - 1);
}
#else /* Python 3+ has unicode identifiers */
if (t->is_unicode | t->is_str) {
if (t->intern) {
*t->p = PyUnicode_InternFromString(t->s);
} else if (t->encoding) {
*t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
} else {
*t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
}
} else {
*t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
}
#endif
if (!*t->p)
return -1;
++t;
}
return 0;
}
/* Type Conversion Functions */
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
int is_true = x == Py_True;
if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
else return PyObject_IsTrue(x);
}
static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) {
PyNumberMethods *m;
const char *name = NULL;
PyObject *res = NULL;
#if PY_VERSION_HEX < 0x03000000
if (PyInt_Check(x) || PyLong_Check(x))
#else
if (PyLong_Check(x))
#endif
return Py_INCREF(x), x;
m = Py_TYPE(x)->tp_as_number;
#if PY_VERSION_HEX < 0x03000000
if (m && m->nb_int) {
name = "int";
res = PyNumber_Int(x);
}
else if (m && m->nb_long) {
name = "long";
res = PyNumber_Long(x);
}
#else
if (m && m->nb_int) {
name = "int";
res = PyNumber_Long(x);
}
#endif
if (res) {
#if PY_VERSION_HEX < 0x03000000
if (!PyInt_Check(res) && !PyLong_Check(res)) {
#else
if (!PyLong_Check(res)) {
#endif
PyErr_Format(PyExc_TypeError,
"__%s__ returned non-%s (type %.200s)",
name, name, Py_TYPE(res)->tp_name);
Py_DECREF(res);
return NULL;
}
}
else if (!PyErr_Occurred()) {
PyErr_SetString(PyExc_TypeError,
"an integer is required");
}
return res;
}
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
Py_ssize_t ival;
PyObject* x = PyNumber_Index(b);
if (!x) return -1;
ival = PyInt_AsSsize_t(x);
Py_DECREF(x);
return ival;
}
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
#if PY_VERSION_HEX < 0x02050000
if (ival <= LONG_MAX)
return PyInt_FromLong((long)ival);
else {
unsigned char *bytes = (unsigned char *) &ival;
int one = 1; int little = (int)*(unsigned char*)&one;
return _PyLong_FromByteArray(bytes, sizeof(size_t), little, 0);
}
#else
return PyInt_FromSize_t(ival);
#endif
}
static CYTHON_INLINE size_t __Pyx_PyInt_AsSize_t(PyObject* x) {
unsigned PY_LONG_LONG val = __Pyx_PyInt_AsUnsignedLongLong(x);
if (unlikely(val == (unsigned PY_LONG_LONG)-1 && PyErr_Occurred())) {
return (size_t)-1;
} else if (unlikely(val != (unsigned PY_LONG_LONG)(size_t)val)) {
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to size_t");
return (size_t)-1;
}
return (size_t)val;
}
#endif /* Py_PYTHON_H */
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