Differential D133 Diff 470 source/blender/python/generic/kdtree_py_api.c

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source/blender/python/generic/kdtree_py_api.c

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				/*
				* *** BEGIN GPL LICENSE BLOCK ***
				*
				* This program is free software; you can redistribute it and/or
				* modify it under the terms of the GNU General Public License
				* as published by the Free Software Foundation; either version 2
				* of the License, or (at your option) any later version.
				*
				* This program is distributed in the hope that it will be useful,
				* but WITHOUT ANY WARRANTY; without even the implied warranty of
				* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
				* GNU General Public License for more details.
				*
				* You should have received a copy of the GNU General Public License
				* along with this program; if not, write to the Free Software Foundation,
				* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
				*
				* Contributor(s): Dan Eicher
				*
				* *** END GPL LICENSE BLOCK ***
				*/


				#include <Python.h>

				#include "kdtree_py_api.h"
				#include "../mathutils/mathutils.h"

				#include "BLI_kdtree.h"
				#include "MEM_guardedalloc.h"

				typedef struct {
				PyObject_HEAD
				KDTree *obj;
				unsigned int maxsize;
				unsigned int count;
				unsigned int balanced;
				} PyKDTree;

				static int
				py_seq_to_vec3(PyObject seq, void vec)
				{
				if (mathutils_array_parse((float*)vec, 3, 3, seq, "KDTree") == -1)
				return 0;

				return 1;
				}

				static PyObject *
				kdtree_nearest_to_py_tuple(KDTreeNearest *nearest)
				{
				PyObject *py_retval;

				if (nearest->index == -1) {
				return PyTuple_Pack(3, Py_None, Py_None, Py_None); /* new references */
				}

				py_retval = PyTuple_New(3);

				PyTuple_SET_ITEM(py_retval, 0, PyLong_FromLong(nearest->index));
				PyTuple_SET_ITEM(py_retval, 1, PyFloat_FromDouble(nearest->dist));
				PyTuple_SET_ITEM(py_retval, 2, Vector_CreatePyObject(&(*nearest->co), 3, Py_NEW, NULL));

				campbellbartonAuthorUnsubmitted Not Done Inline Actions prefer PyTuple_New(), SET_ITEM, means no need to decref after. campbellbarton: prefer PyTuple_New(), SET_ITEM, means no need to decref after.
				return py_retval;
				}

				static int
				PyKDTree__tp_init(PyKDTree self, PyObject args, PyObject *kwargs)
				{
				unsigned int maxsize;
				const char *keywords[] = {"size", NULL};

				if (!PyArg_ParseTupleAndKeywords(args, kwargs, (char ) "I", (char *) keywords, &maxsize)) {
				campbellbartonAuthorUnsubmitted Not Done Inline Actions Passing negative values crashes. campbellbarton: Passing negative values crashes.
				return -1;
				}

				self->obj = BLI_kdtree_new(maxsize);
				campbellbartonAuthorUnsubmitted Not Done Inline Actions just pass `nearest->co` campbellbarton: just pass `nearest->co`
				dnaUnsubmitted Not Done Inline Actions For some odd reason just passing nearest->co was failing. Tested with: for v in bm.verts: i, d, co = tree.find_nearest(v.co) v.co == co dna: For some odd reason just passing nearest->co was failing. Tested with: for v in bm.verts…
				self->maxsize = maxsize;
				self->count = 0;
				self->balanced = 0;

				return 0;
				}

				static void
				PyKDTree__tp_dealloc(PyKDTree *self)
				{
				BLI_kdtree_free(self->obj);
				Py_TYPE(self)->tp_free((PyObject*)self);
				}

				PyDoc_STRVAR(py_kdtree_insert_doc,
				".. method:: insert(index, co)\n"
				"\n"
				" Insert a point into the KDTree.\n"
				"\n"
				" :arg index: The index of the point.\n"
				" :type index: unsigned int\n"
				" :arg co: Point 3d position.\n"
				" :type co: Sequence of three floats\n"
				);
				static PyObject *
				py_kdtree_insert(PyKDTree self, PyObject args, PyObject *kwargs)
				{
				int index;
				float co[3];
				const char *keywords[] = {"index", "co", NULL};

				if (!PyArg_ParseTupleAndKeywords(args, kwargs, (char ) "iO&:insert", (char *) keywords,
				&index, &py_seq_to_vec3, &co)) {
				return NULL;
				}

				campbellbartonAuthorUnsubmitted Not Done Inline Actions `"iO&" -> "iO&:insert"` will give better exception messages, goes for other uses of `PyArg_ParseTupleAndKeywords` campbellbarton: `"iO&" -> "iO&:insert"` will give better exception messages, goes for other uses of…
				if (self->count >= self->maxsize) {
				PyErr_SetString(PyExc_RuntimeError, "Trying to insert more items than KDTree has room for");
				return NULL;
				}

				BLI_kdtree_insert(self->obj, index, co, NULL);
				self->count++;
				self->balanced = 0;

				Py_RETURN_NONE;
				}

				PyDoc_STRVAR(py_kdtree_balance_doc,
				".. method:: balance()\n"
				"\n"
				" Balance the tree.\n"
				);
				static PyObject *
				py_kdtree_balance(PyKDTree *self)
				{
				BLI_kdtree_balance(self->obj);
				self->balanced = 1;
				Py_RETURN_NONE;
				}

				PyDoc_STRVAR(py_kdtree_find_nearest_doc,
				".. method:: find_nearest(co)\n"
				"\n"
				" Find nearest point to `co'.\n"
				"\n"
				campbellbartonAuthorUnsubmitted Not Done Inline Actions Not sure theres a good reason to allow passing a None arg, the caller can just ommit the arg in this case. campbellbarton: Not sure theres a good reason to allow passing a None arg, the caller can just ommit the arg in…
				" KdTree.balance() must have been called before using this method.\n"
				"\n"
				" :arg co: 3d coordinates.\n"
				" :type co: Sequence of three floats\n"
				" :return: Returns index, distance, :class:`Vector`.\n"
				" :rtype: :class:`tuple`\n"
				);
				static PyObject *
				py_kdtree_find_nearest(PyKDTree self, PyObject args, PyObject *kwargs)
				{
				float co[3];
				KDTreeNearest nearest;
				const char *keywords[] = {"co", NULL};

				if (!PyArg_ParseTupleAndKeywords(args, kwargs, (char ) "O&:find_nearest", (char *) keywords,
				&py_seq_to_vec3, &co)) {
				return NULL;
				}

				if (self->balanced == 0) {
				PyErr_SetString(PyExc_RuntimeError, "KDTree must be balanced before calling find_nearest()");
				return NULL;
				}

				BLI_kdtree_find_nearest(self->obj, co, NULL, &nearest);

				return kdtree_nearest_to_py_tuple(&nearest);
				}

				PyDoc_STRVAR(py_kdtree_find_nearest_n_doc,
				".. method:: find_nearest_n(n, co)\n"
				"\n"
				" Find nearest `n' points to `co'.\n"
				"\n"
				" KdTree.balance() must have been called before using this method.\n"
				"\n"
				" :arg n: Number of points to find.\n"
				" :type n: unsigned int\n"
				" :arg co: 3d coordinates.\n"
				" :type co: Sequence of three floats\n"
				" :return: Returns a list of index, distance, :class:`Vector`.\n"
				" :rtype: :class:`tuple`\n"
				);
				static PyObject *
				py_kdtree_find_nearest_n(PyKDTree self, PyObject args, PyObject *kwargs)
				{
				PyObject *py_list;
				float co[3];
				KDTreeNearest *nearest;
				unsigned int n;
				int i, found;
				campbellbartonAuthorUnsubmitted Not Done Inline Actions again, seems odd to support. campbellbarton: again, seems odd to support.
				const char *keywords[] = {"n", "co", NULL};

				if (!PyArg_ParseTupleAndKeywords(args, kwargs, (char ) "IO&:find_nearest_n", (char *) keywords,
				&n, &py_seq_to_vec3, &co)) {
				return NULL;
				}

				if (self->balanced == 0) {
				PyErr_SetString(PyExc_RuntimeError, "KDTree must be balanced before calling find_nearest_n()");
				return NULL;
				}

				nearest = MEM_mallocN(sizeof(KDTreeNearest) * n, "PyKDTree nearest");

				found = BLI_kdtree_find_nearest_n(self->obj, co, NULL, nearest, n);

				campbellbartonAuthorUnsubmitted Not Done Inline Actions The python API could ensure this fairly easily, (just store bool flag)... OR the C api could ensure and assert if it fails. campbellbarton: The python API could ensure this fairly easily, (just store bool flag)... OR the C api could…
				py_list = PyList_New(found);

				for (i = 0; i < found; i++) {
				PyList_SET_ITEM(py_list, i, kdtree_nearest_to_py_tuple(&nearest[i]));
				}

				MEM_freeN(nearest);

				return py_list;
				}

				PyDoc_STRVAR(py_kdtree_range_search_doc,
				".. method:: range_search(range, co)\n"
				"\n"
				" Find all points within `range' of `co'.\n"
				"\n"
				" KdTree.balance() must have been called before using this method.\n"
				"\n"
				" :arg range: Distance to search for points.\n"
				" :type range: float\n"
				" :arg co: 3d coordinates.\n"
				" :type co: Sequence of three floats\n"
				" :return: Returns a list of index, distance, :class:`Vector`.\n"
				" :rtype: :class:`tuple`\n"
				);
				static PyObject *
				campbellbartonAuthorUnsubmitted Not Done Inline Actions again... wouldnt bother with this. campbellbarton: again... wouldnt bother with this.
				py_kdtree_range_search(PyKDTree self, PyObject args, PyObject *kwargs)
				{
				PyObject *py_list;
				float co[3];
				KDTreeNearest *nearest = NULL;
				float range;
				int i, found;

				const char *keywords[] = {"range", "co", NULL};

				if (!PyArg_ParseTupleAndKeywords(args, kwargs, (char ) "fO&:range_search", (char *) keywords,
				&range, &py_seq_to_vec3, &co)) {
				return NULL;
				}

				if (self->balanced == 0) {
				PyErr_SetString(PyExc_RuntimeError, "KDTree must be balanced before calling range_search()");
				return NULL;
				}

				found = BLI_kdtree_range_search(self->obj, co, NULL, &nearest, range);

				py_list = PyList_New(found);

				for (i = 0; i < found; i++) {
				PyList_SET_ITEM(py_list, i, kdtree_nearest_to_py_tuple(&nearest[i]));
				}

				MEM_freeN(nearest);

				return py_list;
				}


				static PyMethodDef PyKDTree_methods[] = {
				{"insert", (PyCFunction)py_kdtree_insert, METH_KEYWORDS\|METH_VARARGS, py_kdtree_insert_doc},
				{"balance", (PyCFunction)py_kdtree_balance, METH_NOARGS, py_kdtree_balance_doc},
				{"find_nearest", (PyCFunction)py_kdtree_find_nearest, METH_KEYWORDS\|METH_VARARGS, py_kdtree_find_nearest_doc},
				{"find_nearest_n", (PyCFunction)py_kdtree_find_nearest_n, METH_KEYWORDS\|METH_VARARGS, py_kdtree_find_nearest_n_doc},
				{"range_search", (PyCFunction)py_kdtree_range_search, METH_KEYWORDS\|METH_VARARGS, py_kdtree_range_search_doc},
				{NULL, NULL, 0, NULL}
				};

				PyDoc_STRVAR(py_kdtree_doc,
				"Generic 3-dimentional kd-tree.\n"
				"\n"
				"KdTree(size) -> new kd-tree initialized to hold `size' items.\n"
				);
				PyTypeObject PyKDTree_Type = {
				PyVarObject_HEAD_INIT(NULL, 0)
				(char ) "KDTree", / tp_name */
				sizeof(PyKDTree), /* tp_basicsize */
				0, /* tp_itemsize */
				/* methods */
				(destructor)PyKDTree__tp_dealloc, /* tp_dealloc */
				(printfunc)0, /* tp_print */
				(getattrfunc)NULL, /* tp_getattr */
				(setattrfunc)NULL, /* tp_setattr */
				NULL, /* tp_compare */
				(reprfunc)NULL, /* tp_repr */
				(PyNumberMethods)NULL, / tp_as_number */
				(PySequenceMethods)NULL, / tp_as_sequence */
				(PyMappingMethods)NULL, / tp_as_mapping */
				(hashfunc)NULL, /* tp_hash */
				(ternaryfunc)NULL, /* tp_call */
				(reprfunc)NULL, /* tp_str */
				(getattrofunc)NULL, /* tp_getattro */
				(setattrofunc)NULL, /* tp_setattro */
				(PyBufferProcs)NULL, / tp_as_buffer */
				Py_TPFLAGS_DEFAULT, /* tp_flags */
				py_kdtree_doc, /* Documentation string */
				(traverseproc)NULL, /* tp_traverse */
				(inquiry)NULL, /* tp_clear */
				(richcmpfunc)NULL, /* tp_richcompare */
				0, /* tp_weaklistoffset */
				(getiterfunc)NULL, /* tp_iter */
				(iternextfunc)NULL, /* tp_iternext */
				(struct PyMethodDef)PyKDTree_methods, / tp_methods */
				(struct PyMemberDef)0, / tp_members */
				0, /* tp_getset */
				NULL, /* tp_base */
				NULL, /* tp_dict */
				(descrgetfunc)NULL, /* tp_descr_get */
				(descrsetfunc)NULL, /* tp_descr_set */
				0, /* tp_dictoffset */
				(initproc)PyKDTree__tp_init, /* tp_init */
				(allocfunc)PyType_GenericAlloc, /* tp_alloc */
				(newfunc)PyType_GenericNew, /* tp_new */
				(freefunc)0, /* tp_free */
				(inquiry)NULL, /* tp_is_gc */
				NULL, /* tp_bases */
				NULL, /* tp_mro */
				NULL, /* tp_cache */
				NULL, /* tp_subclasses */
				NULL, /* tp_weaklist */
				(destructor) NULL /* tp_del */
				};

				static struct PyModuleDef kdtree_moduledef = {
				PyModuleDef_HEAD_INIT,
				"kdtree", /* m_name */
				NULL, /* m_doc */
				0, /* m_size */
				NULL, /* m_methods */
				NULL, /* m_reload */
				NULL, /* m_traverse */
				NULL, /* m_clear */
				NULL /* m_free */
				};

				PyObject *
				BPyInit_kdtree(void)
				{
				PyObject *m = PyModule_Create(&kdtree_moduledef);

				if (m == NULL) {
				return NULL;
				}

				/* Register the 'KDTree' class */
				if (PyType_Ready(&PyKDTree_Type)) {
				return NULL;
				}
				PyModule_AddObject(m, (char ) "KDTree", (PyObject ) &PyKDTree_Type);

				return m;
				}