Cleanup: use BLI_kdtree_3d prefix

Use prefix now there isn't only the 3d version.
This commit is contained in:
2019-03-20 00:46:33 +11:00
parent e8777a7290
commit 109cbdf2e1
30 changed files with 236 additions and 232 deletions

View File

@@ -655,7 +655,7 @@ PyMODINIT_FUNC PyInit_mathutils(void)
PyModule_AddObject(mod, "bvhtree", (submodule = PyInit_mathutils_bvhtree()));
PyDict_SetItem(sys_modules, PyModule_GetNameObject(submodule), submodule);
/* KDTree submodule */
/* KDTree_3d submodule */
PyModule_AddObject(mod, "kdtree", (submodule = PyInit_mathutils_kdtree()));
PyDict_SetItem(sys_modules, PyModule_GetNameObject(submodule), submodule);
#endif

View File

@@ -38,7 +38,7 @@
typedef struct {
PyObject_HEAD
KDTree *obj;
KDTree_3d *obj;
unsigned int maxsize;
unsigned int count;
unsigned int count_balance; /* size when we last balanced */
@@ -48,7 +48,7 @@ typedef struct {
/* -------------------------------------------------------------------- */
/* Utility helper functions */
static void kdtree_nearest_to_py_tuple(const KDTreeNearest *nearest, PyObject *py_retval)
static void kdtree_nearest_to_py_tuple(const KDTreeNearest_3d *nearest, PyObject *py_retval)
{
BLI_assert(nearest->index >= 0);
BLI_assert(PyTuple_GET_SIZE(py_retval) == 3);
@@ -59,7 +59,7 @@ static void kdtree_nearest_to_py_tuple(const KDTreeNearest *nearest, PyObject *p
PyFloat_FromDouble(nearest->dist));
}
static PyObject *kdtree_nearest_to_py(const KDTreeNearest *nearest)
static PyObject *kdtree_nearest_to_py(const KDTreeNearest_3d *nearest)
{
PyObject *py_retval;
@@ -70,7 +70,7 @@ static PyObject *kdtree_nearest_to_py(const KDTreeNearest *nearest)
return py_retval;
}
static PyObject *kdtree_nearest_to_py_and_check(const KDTreeNearest *nearest)
static PyObject *kdtree_nearest_to_py_and_check(const KDTreeNearest_3d *nearest)
{
PyObject *py_retval;
@@ -110,7 +110,7 @@ static int PyKDTree__tp_init(PyKDTree *self, PyObject *args, PyObject *kwargs)
return -1;
}
self->obj = BLI_kdtree_new(maxsize);
self->obj = BLI_kdtree_3d_new(maxsize);
self->maxsize = maxsize;
self->count = 0;
self->count_balance = 0;
@@ -120,7 +120,7 @@ static int PyKDTree__tp_init(PyKDTree *self, PyObject *args, PyObject *kwargs)
static void PyKDTree__tp_dealloc(PyKDTree *self)
{
BLI_kdtree_free(self->obj);
BLI_kdtree_3d_free(self->obj);
Py_TYPE(self)->tp_free((PyObject *)self);
}
@@ -161,7 +161,7 @@ static PyObject *py_kdtree_insert(PyKDTree *self, PyObject *args, PyObject *kwar
return NULL;
}
BLI_kdtree_insert(self->obj, index, co);
BLI_kdtree_3d_insert(self->obj, index, co);
self->count++;
Py_RETURN_NONE;
@@ -178,7 +178,7 @@ PyDoc_STRVAR(py_kdtree_balance_doc,
);
static PyObject *py_kdtree_balance(PyKDTree *self)
{
BLI_kdtree_balance(self->obj);
BLI_kdtree_3d_balance(self->obj);
self->count_balance = self->count;
Py_RETURN_NONE;
}
@@ -228,7 +228,7 @@ static PyObject *py_kdtree_find(PyKDTree *self, PyObject *args, PyObject *kwargs
{
PyObject *py_co, *py_filter = NULL;
float co[3];
KDTreeNearest nearest;
KDTreeNearest_3d nearest;
const char *keywords[] = {"co", "filter", NULL};
if (!PyArg_ParseTupleAndKeywords(
@@ -249,7 +249,7 @@ static PyObject *py_kdtree_find(PyKDTree *self, PyObject *args, PyObject *kwargs
nearest.index = -1;
if (py_filter == NULL) {
BLI_kdtree_find_nearest(self->obj, co, &nearest);
BLI_kdtree_3d_find_nearest(self->obj, co, &nearest);
}
else {
struct PyKDTree_NearestData data = {0};
@@ -257,7 +257,7 @@ static PyObject *py_kdtree_find(PyKDTree *self, PyObject *args, PyObject *kwargs
data.py_filter = py_filter;
data.is_error = false;
BLI_kdtree_find_nearest_cb(
BLI_kdtree_3d_find_nearest_cb(
self->obj, co,
py_find_nearest_cb, &data,
&nearest);
@@ -287,7 +287,7 @@ static PyObject *py_kdtree_find_n(PyKDTree *self, PyObject *args, PyObject *kwar
PyObject *py_list;
PyObject *py_co;
float co[3];
KDTreeNearest *nearest;
KDTreeNearest_3d *nearest;
unsigned int n;
int i, found;
const char *keywords[] = {"co", "n", NULL};
@@ -312,9 +312,9 @@ static PyObject *py_kdtree_find_n(PyKDTree *self, PyObject *args, PyObject *kwar
return NULL;
}
nearest = MEM_mallocN(sizeof(KDTreeNearest) * n, __func__);
nearest = MEM_mallocN(sizeof(KDTreeNearest_3d) * n, __func__);
found = BLI_kdtree_find_nearest_n(self->obj, co, nearest, n);
found = BLI_kdtree_3d_find_nearest_n(self->obj, co, nearest, n);
py_list = PyList_New(found);
@@ -344,7 +344,7 @@ static PyObject *py_kdtree_find_range(PyKDTree *self, PyObject *args, PyObject *
PyObject *py_list;
PyObject *py_co;
float co[3];
KDTreeNearest *nearest = NULL;
KDTreeNearest_3d *nearest = NULL;
float radius;
int i, found;
@@ -370,7 +370,7 @@ static PyObject *py_kdtree_find_range(PyKDTree *self, PyObject *args, PyObject *
return NULL;
}
found = BLI_kdtree_range_search(self->obj, co, &nearest, radius);
found = BLI_kdtree_3d_range_search(self->obj, co, &nearest, radius);
py_list = PyList_New(found);