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Commit 18c2bcddd4fbb36ebbef13006c804f4ce661476a

Authored by Thiago Franco de Moraes
1 parent 73ddbb08
Exists in master

Moved all cython codes to invesalius_cy

Showing 20 changed files with 1731 additions and 1731 deletions   Show diff stats
invesalius/data/cy_mesh.pyx
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1   -# distutils: language = c++
2   -#cython: boundscheck=False
3   -#cython: wraparound=False
4   -#cython: initializedcheck=False
5   -#cython: cdivision=True
6   -#cython: nonecheck=False
7   -
8   -import sys
9   -import time
10   -cimport numpy as np
11   -
12   -from libc.math cimport sin, cos, acos, exp, sqrt, fabs, M_PI
13   -from libc.stdlib cimport abs as cabs
14   -from cython.operator cimport dereference as deref, preincrement as inc
15   -from libcpp.map cimport map
16   -from libcpp.unordered_map cimport unordered_map
17   -from libcpp.set cimport set
18   -from libcpp.vector cimport vector
19   -from libcpp.pair cimport pair
20   -from libcpp cimport bool
21   -from libcpp.deque cimport deque as cdeque
22   -from cython.parallel import prange
23   -
24   -from cy_my_types cimport vertex_t, normal_t, vertex_id_t
25   -
26   -import numpy as np
27   -import vtk
28   -
29   -from vtk.util import numpy_support
30   -
31   -ctypedef float weight_t
32   -
33   -cdef struct Point:
34   - vertex_t x
35   - vertex_t y
36   - vertex_t z
37   -
38   -ctypedef pair[vertex_id_t, vertex_id_t] key
39   -
40   -
41   -cdef class Mesh:
42   - cdef vertex_t[:, :] vertices
43   - cdef vertex_id_t[:, :] faces
44   - cdef normal_t[:, :] normals
45   -
46   - cdef unordered_map[int, vector[vertex_id_t]] map_vface
47   - cdef unordered_map[vertex_id_t, int] border_vertices
48   -
49   - cdef bool _initialized
50   -
51   - def __cinit__(self, pd=None, other=None):
52   - cdef int i
53   - cdef map[key, int] edge_nfaces
54   - cdef map[key, int].iterator it
55   - if pd:
56   - self._initialized = True
57   - _vertices = numpy_support.vtk_to_numpy(pd.GetPoints().GetData())
58   - _vertices.shape = -1, 3
59   -
60   - _faces = numpy_support.vtk_to_numpy(pd.GetPolys().GetData())
61   - _faces.shape = -1, 4
62   -
63   - _normals = numpy_support.vtk_to_numpy(pd.GetCellData().GetArray("Normals"))
64   - _normals.shape = -1, 3
65   -
66   - self.vertices = _vertices
67   - self.faces = _faces
68   - self.normals = _normals
69   -
70   - for i in xrange(_faces.shape[0]):
71   - self.map_vface[self.faces[i, 1]].push_back(i)
72   - self.map_vface[self.faces[i, 2]].push_back(i)
73   - self.map_vface[self.faces[i, 3]].push_back(i)
74   -
75   - edge_nfaces[key(min(self.faces[i, 1], self.faces[i, 2]), max(self.faces[i, 1], self.faces[i, 2]))] += 1
76   - edge_nfaces[key(min(self.faces[i, 2], self.faces[i, 3]), max(self.faces[i, 2], self.faces[i, 3]))] += 1
77   - edge_nfaces[key(min(self.faces[i, 1], self.faces[i, 3]), max(self.faces[i, 1], self.faces[i, 3]))] += 1
78   -
79   - it = edge_nfaces.begin()
80   -
81   - while it != edge_nfaces.end():
82   - if deref(it).second == 1:
83   - self.border_vertices[deref(it).first.first] = 1
84   - self.border_vertices[deref(it).first.second] = 1
85   -
86   - inc(it)
87   -
88   - elif other:
89   - _other = <Mesh>other
90   - self._initialized = True
91   - self.vertices = _other.vertices.copy()
92   - self.faces = _other.faces.copy()
93   - self.normals = _other.normals.copy()
94   - self.map_vface = unordered_map[int, vector[vertex_id_t]](_other.map_vface)
95   - self.border_vertices = unordered_map[vertex_id_t, int](_other.border_vertices)
96   - else:
97   - self._initialized = False
98   -
99   - cdef void copy_to(self, Mesh other):
100   - """
101   - Copies self content to other.
102   - """
103   - if self._initialized:
104   - other.vertices[:] = self.vertices
105   - other.faces[:] = self.faces
106   - other.normals[:] = self.normals
107   - other.map_vface = unordered_map[int, vector[vertex_id_t]](self.map_vface)
108   - other.border_vertices = unordered_map[vertex_id_t, int](self.border_vertices)
109   - else:
110   - other.vertices = self.vertices.copy()
111   - other.faces = self.faces.copy()
112   - other.normals = self.normals.copy()
113   -
114   - other.map_vface = self.map_vface
115   - other.border_vertices = self.border_vertices
116   -
117   - def to_vtk(self):
118   - """
119   - Converts Mesh to vtkPolyData.
120   - """
121   - vertices = np.asarray(self.vertices)
122   - faces = np.asarray(self.faces)
123   - normals = np.asarray(self.normals)
124   -
125   - points = vtk.vtkPoints()
126   - points.SetData(numpy_support.numpy_to_vtk(vertices))
127   -
128   - id_triangles = numpy_support.numpy_to_vtkIdTypeArray(faces)
129   - triangles = vtk.vtkCellArray()
130   - triangles.SetCells(faces.shape[0], id_triangles)
131   -
132   - pd = vtk.vtkPolyData()
133   - pd.SetPoints(points)
134   - pd.SetPolys(triangles)
135   -
136   - return pd
137   -
138   - cdef vector[vertex_id_t]* get_faces_by_vertex(self, int v_id) nogil:
139   - """
140   - Returns the faces whose vertex `v_id' is part.
141   - """
142   - return &self.map_vface[v_id]
143   -
144   - cdef set[vertex_id_t]* get_ring1(self, vertex_id_t v_id) nogil:
145   - """
146   - Returns the ring1 of vertex `v_id'
147   - """
148   - cdef vertex_id_t f_id
149   - cdef set[vertex_id_t]* ring1 = new set[vertex_id_t]()
150   - cdef vector[vertex_id_t].iterator it = self.map_vface[v_id].begin()
151   -
152   - while it != self.map_vface[v_id].end():
153   - f_id = deref(it)
154   - inc(it)
155   - if self.faces[f_id, 1] != v_id:
156   - ring1.insert(self.faces[f_id, 1])
157   - if self.faces[f_id, 2] != v_id:
158   - ring1.insert(self.faces[f_id, 2])
159   - if self.faces[f_id, 3] != v_id:
160   - ring1.insert(self.faces[f_id, 3])
161   -
162   - return ring1
163   -
164   - cdef bool is_border(self, vertex_id_t v_id) nogil:
165   - """
166   - Check if vertex `v_id' is a vertex border.
167   - """
168   - return self.border_vertices.find(v_id) != self.border_vertices.end()
169   -
170   - cdef vector[vertex_id_t]* get_near_vertices_to_v(self, vertex_id_t v_id, float dmax) nogil:
171   - """
172   - Returns all vertices with distance at most `d' to the vertex `v_id'
173   -
174   - Params:
175   - v_id: id of the vertex
176   - dmax: the maximum distance.
177   - """
178   - cdef vector[vertex_id_t]* idfaces
179   - cdef vector[vertex_id_t]* near_vertices = new vector[vertex_id_t]()
180   -
181   - cdef cdeque[vertex_id_t] to_visit
182   - cdef unordered_map[vertex_id_t, bool] status_v
183   - cdef unordered_map[vertex_id_t, bool] status_f
184   -
185   - cdef vertex_t *vip
186   - cdef vertex_t *vjp
187   -
188   - cdef float distance
189   - cdef int nf, nid, j
190   - cdef vertex_id_t f_id, vj
191   -
192   - vip = &self.vertices[v_id, 0]
193   - to_visit.push_back(v_id)
194   - while(not to_visit.empty()):
195   - v_id = to_visit.front()
196   - to_visit.pop_front()
197   -
198   - status_v[v_id] = True
199   -
200   - idfaces = self.get_faces_by_vertex(v_id)
201   - nf = idfaces.size()
202   -
203   - for nid in xrange(nf):
204   - f_id = deref(idfaces)[nid]
205   - if status_f.find(f_id) == status_f.end():
206   - status_f[f_id] = True
207   -
208   - for j in xrange(3):
209   - vj = self.faces[f_id, j+1]
210   - if status_v.find(vj) == status_v.end():
211   - status_v[vj] = True
212   - vjp = &self.vertices[vj, 0]
213   - distance = sqrt((vip[0] - vjp[0]) * (vip[0] - vjp[0]) \
214   - + (vip[1] - vjp[1]) * (vip[1] - vjp[1]) \
215   - + (vip[2] - vjp[2]) * (vip[2] - vjp[2]))
216   - if distance <= dmax:
217   - near_vertices.push_back(vj)
218   - to_visit.push_back(vj)
219   -
220   - return near_vertices
221   -
222   -
223   -cdef vector[weight_t]* calc_artifacts_weight(Mesh mesh, vector[vertex_id_t]& vertices_staircase, float tmax, float bmin) nogil:
224   - """
225   - Calculate the artifact weight based on distance of each vertex to its
226   - nearest staircase artifact vertex.
227   -
228   - Params:
229   - mesh: Mesh
230   - vertices_staircase: the identified staircase artifact vertices
231   - tmax: max distance the vertex must be to its nearest artifact vertex
232   - to considered to calculate the weight
233   - bmin: The minimum weight.
234   - """
235   - cdef int vi_id, vj_id, nnv, n_ids, i, j
236   - cdef vector[vertex_id_t]* near_vertices
237   - cdef weight_t value
238   - cdef float d
239   - n_ids = vertices_staircase.size()
240   -
241   - cdef vertex_t* vi
242   - cdef vertex_t* vj
243   - cdef size_t msize
244   -
245   - msize = mesh.vertices.shape[0]
246   - cdef vector[weight_t]* weights = new vector[weight_t](msize)
247   - weights.assign(msize, bmin)
248   -
249   - for i in prange(n_ids, nogil=True):
250   - vi_id = vertices_staircase[i]
251   - deref(weights)[vi_id] = 1.0
252   -
253   - vi = &mesh.vertices[vi_id, 0]
254   - near_vertices = mesh.get_near_vertices_to_v(vi_id, tmax)
255   - nnv = near_vertices.size()
256   -
257   - for j in xrange(nnv):
258   - vj_id = deref(near_vertices)[j]
259   - vj = &mesh.vertices[vj_id, 0]
260   -
261   - d = sqrt((vi[0] - vj[0]) * (vi[0] - vj[0])\
262   - + (vi[1] - vj[1]) * (vi[1] - vj[1])\
263   - + (vi[2] - vj[2]) * (vi[2] - vj[2]))
264   - value = (1.0 - d/tmax) * (1.0 - bmin) + bmin
265   -
266   - if value > deref(weights)[vj_id]:
267   - deref(weights)[vj_id] = value
268   -
269   - del near_vertices
270   -
271   - # for i in xrange(msize):
272   - # if mesh.is_border(i):
273   - # deref(weights)[i] = 0.0
274   -
275   - # cdef vertex_id_t v0, v1, v2
276   - # for i in xrange(mesh.faces.shape[0]):
277   - # for j in xrange(1, 4):
278   - # v0 = mesh.faces[i, j]
279   - # vi = &mesh.vertices[v0, 0]
280   - # if mesh.is_border(v0):
281   - # deref(weights)[v0] = 0.0
282   - # v1 = mesh.faces[i, (j + 1) % 3 + 1]
283   - # if mesh.is_border(v1):
284   - # vi = &mesh.vertices[v1, 0]
285   - # deref(weights)[v0] = 0.0
286   -
287   - return weights
288   -
289   -
290   -cdef inline Point calc_d(Mesh mesh, vertex_id_t v_id) nogil:
291   - cdef Point D
292   - cdef int nf, f_id, nid
293   - cdef float n=0
294   - cdef int i
295   - cdef vertex_t* vi
296   - cdef vertex_t* vj
297   - cdef set[vertex_id_t]* vertices
298   - cdef set[vertex_id_t].iterator it
299   - cdef vertex_id_t vj_id
300   -
301   - D.x = 0.0
302   - D.y = 0.0
303   - D.z = 0.0
304   -
305   - vertices = mesh.get_ring1(v_id)
306   - vi = &mesh.vertices[v_id, 0]
307   -
308   - if mesh.is_border(v_id):
309   - it = vertices.begin()
310   - while it != vertices.end():
311   - vj_id = deref(it)
312   - if mesh.is_border(vj_id):
313   - vj = &mesh.vertices[vj_id, 0]
314   -
315   - D.x = D.x + (vi[0] - vj[0])
316   - D.y = D.y + (vi[1] - vj[1])
317   - D.z = D.z + (vi[2] - vj[2])
318   - n += 1.0
319   -
320   - inc(it)
321   - else:
322   - it = vertices.begin()
323   - while it != vertices.end():
324   - vj_id = deref(it)
325   - vj = &mesh.vertices[vj_id, 0]
326   -
327   - D.x = D.x + (vi[0] - vj[0])
328   - D.y = D.y + (vi[1] - vj[1])
329   - D.z = D.z + (vi[2] - vj[2])
330   - n += 1.0
331   -
332   - inc(it)
333   -
334   - del vertices
335   -
336   - D.x = D.x / n
337   - D.y = D.y / n
338   - D.z = D.z / n
339   - return D
340   -
341   -cdef vector[vertex_id_t]* find_staircase_artifacts(Mesh mesh, double[3] stack_orientation, double T) nogil:
342   - """
343   - This function is used to find vertices at staircase artifacts, which are
344   - those vertices whose incident faces' orientation differences are
345   - greater than T.
346   -
347   - Params:
348   - mesh: Mesh
349   - stack_orientation: orientation of slice stacking
350   - T: Min angle (between vertex faces and stack_orientation) to consider a
351   - vertex a staircase artifact.
352   - """
353   - cdef int nv, nf, f_id, v_id
354   - cdef double of_z, of_y, of_x, min_z, max_z, min_y, max_y, min_x, max_x;
355   - cdef vector[vertex_id_t]* f_ids
356   - cdef normal_t* normal
357   -
358   - cdef vector[vertex_id_t]* output = new vector[vertex_id_t]()
359   - cdef int i
360   -
361   - nv = mesh.vertices.shape[0]
362   -
363   - for v_id in xrange(nv):
364   - max_z = -10000
365   - min_z = 10000
366   - max_y = -10000
367   - min_y = 10000
368   - max_x = -10000
369   - min_x = 10000
370   -
371   - f_ids = mesh.get_faces_by_vertex(v_id)
372   - nf = deref(f_ids).size()
373   -
374   - for i in xrange(nf):
375   - f_id = deref(f_ids)[i]
376   - normal = &mesh.normals[f_id, 0]
377   -
378   - of_z = 1 - fabs(normal[0]*stack_orientation[0] + normal[1]*stack_orientation[1] + normal[2]*stack_orientation[2]);
379   - of_y = 1 - fabs(normal[0]*0 + normal[1]*1 + normal[2]*0);
380   - of_x = 1 - fabs(normal[0]*1 + normal[1]*0 + normal[2]*0);
381   -
382   - if (of_z > max_z):
383   - max_z = of_z
384   -
385   - if (of_z < min_z):
386   - min_z = of_z
387   -
388   - if (of_y > max_y):
389   - max_y = of_y
390   -
391   - if (of_y < min_y):
392   - min_y = of_y
393   -
394   - if (of_x > max_x):
395   - max_x = of_x
396   -
397   - if (of_x < min_x):
398   - min_x = of_x
399   -
400   -
401   - if ((fabs(max_z - min_z) >= T) or (fabs(max_y - min_y) >= T) or (fabs(max_x - min_x) >= T)):
402   - output.push_back(v_id)
403   - break
404   - return output
405   -
406   -
407   -cdef void taubin_smooth(Mesh mesh, vector[weight_t]& weights, float l, float m, int steps):
408   - """
409   - Implementation of Taubin's smooth algorithm described in the paper "A
410   - Signal Processing Approach To Fair Surface Design". His benefeat is it
411   - avoids surface shrinking.
412   - """
413   - cdef int s, i, nvertices
414   - nvertices = mesh.vertices.shape[0]
415   - cdef vector[Point] D = vector[Point](nvertices)
416   - cdef vertex_t* vi
417   - for s in xrange(steps):
418   - for i in prange(nvertices, nogil=True):
419   - D[i] = calc_d(mesh, i)
420   -
421   - for i in prange(nvertices, nogil=True):
422   - mesh.vertices[i, 0] += weights[i]*l*D[i].x;
423   - mesh.vertices[i, 1] += weights[i]*l*D[i].y;
424   - mesh.vertices[i, 2] += weights[i]*l*D[i].z;
425   -
426   - for i in prange(nvertices, nogil=True):
427   - D[i] = calc_d(mesh, i)
428   -
429   - for i in prange(nvertices, nogil=True):
430   - mesh.vertices[i, 0] += weights[i]*m*D[i].x;
431   - mesh.vertices[i, 1] += weights[i]*m*D[i].y;
432   - mesh.vertices[i, 2] += weights[i]*m*D[i].z;
433   -
434   -
435   -def ca_smoothing(Mesh mesh, double T, double tmax, double bmin, int n_iters):
436   - """
437   - This is a implementation of the paper "Context-aware mesh smoothing for
438   - biomedical applications". It can be used to smooth meshes generated by
439   - binary images to remove its staircase artifacts and keep the fine features.
440   -
441   - Params:
442   - mesh: Mesh
443   - T: Min angle (between vertex faces and stack_orientation) to consider a
444   - vertex a staircase artifact
445   - tmax: max distance the vertex must be to its nearest artifact vertex
446   - to considered to calculate the weight
447   - bmin: The minimum weight
448   - n_iters: Number of iterations.
449   - """
450   - cdef double[3] stack_orientation = [0.0, 0.0, 1.0]
451   -
452   - t0 = time.time()
453   - cdef vector[vertex_id_t]* vertices_staircase = find_staircase_artifacts(mesh, stack_orientation, T)
454   - print "vertices staircase", time.time() - t0
455   -
456   - t0 = time.time()
457   - cdef vector[weight_t]* weights = calc_artifacts_weight(mesh, deref(vertices_staircase), tmax, bmin)
458   - print "Weights", time.time() - t0
459   -
460   - del vertices_staircase
461   -
462   - t0 = time.time()
463   - taubin_smooth(mesh, deref(weights), 0.5, -0.53, n_iters)
464   - print "taubin", time.time() - t0
465   -
466   - del weights
invesalius/data/cy_my_types.pxd
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1   -import numpy as np
2   -cimport numpy as np
3   -cimport cython
4   -
5   -# ctypedef np.uint16_t image_t
6   -
7   -ctypedef fused image_t:
8   - np.float64_t
9   - np.int16_t
10   - np.uint8_t
11   -
12   -ctypedef np.uint8_t mask_t
13   -
14   -ctypedef np.float32_t vertex_t
15   -ctypedef np.float32_t normal_t
16   -
17   -# To compile in windows 64
18   -IF UNAME_MACHINE == 'AMD64':
19   - ctypedef np.int64_t vertex_id_t
20   -ELSE:
21   - ctypedef np.int_t vertex_id_t
invesalius/data/floodfill.pyx
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1   -import numpy as np
2   -cimport numpy as np
3   -cimport cython
4   -
5   -from collections import deque
6   -
7   -from cython.parallel import prange
8   -from libc.math cimport floor, ceil
9   -from libcpp cimport bool
10   -from libcpp.deque cimport deque as cdeque
11   -from libcpp.vector cimport vector
12   -
13   -from cy_my_types cimport image_t, mask_t
14   -
15   -cdef struct s_coord:
16   - int x
17   - int y
18   - int z
19   -
20   -ctypedef s_coord coord
21   -
22   -
23   -@cython.boundscheck(False) # turn of bounds-checking for entire function
24   -@cython.wraparound(False)
25   -@cython.nonecheck(False)
26   -@cython.cdivision(True)
27   -cdef inline void append_queue(cdeque[int]& stack, int x, int y, int z, int d, int h, int w) nogil:
28   - stack.push_back(z*h*w + y*w + x)
29   -
30   -
31   -@cython.boundscheck(False) # turn of bounds-checking for entire function
32   -@cython.wraparound(False)
33   -@cython.nonecheck(False)
34   -@cython.cdivision(True)
35   -cdef inline void pop_queue(cdeque[int]& stack, int* x, int* y, int* z, int d, int h, int w) nogil:
36   - cdef int i = stack.front()
37   - stack.pop_front()
38   - x[0] = i % w
39   - y[0] = (i / w) % h
40   - z[0] = i / (h * w)
41   -
42   -
43   -@cython.boundscheck(False) # turn of bounds-checking for entire function
44   -def floodfill(np.ndarray[image_t, ndim=3] data, int i, int j, int k, int v, int fill, np.ndarray[mask_t, ndim=3] out):
45   -
46   - cdef int to_return = 0
47   - if out is None:
48   - out = np.zeros_like(data)
49   - to_return = 1
50   -
51   - cdef int x, y, z
52   - cdef int w, h, d
53   -
54   - d = data.shape[0]
55   - h = data.shape[1]
56   - w = data.shape[2]
57   -
58   - stack = [(i, j, k), ]
59   - out[k, j, i] = fill
60   -
61   - while stack:
62   - x, y, z = stack.pop()
63   -
64   - if z + 1 < d and data[z + 1, y, x] == v and out[z + 1, y, x] != fill:
65   - out[z + 1, y, x] = fill
66   - stack.append((x, y, z + 1))
67   -
68   - if z - 1 >= 0 and data[z - 1, y, x] == v and out[z - 1, y, x] != fill:
69   - out[z - 1, y, x] = fill
70   - stack.append((x, y, z - 1))
71   -
72   - if y + 1 < h and data[z, y + 1, x] == v and out[z, y + 1, x] != fill:
73   - out[z, y + 1, x] = fill
74   - stack.append((x, y + 1, z))
75   -
76   - if y - 1 >= 0 and data[z, y - 1, x] == v and out[z, y - 1, x] != fill:
77   - out[z, y - 1, x] = fill
78   - stack.append((x, y - 1, z))
79   -
80   - if x + 1 < w and data[z, y, x + 1] == v and out[z, y, x + 1] != fill:
81   - out[z, y, x + 1] = fill
82   - stack.append((x + 1, y, z))
83   -
84   - if x - 1 >= 0 and data[z, y, x - 1] == v and out[z, y, x - 1] != fill:
85   - out[z, y, x - 1] = fill
86   - stack.append((x - 1, y, z))
87   -
88   - if to_return:
89   - return out
90   -
91   -
92   -@cython.boundscheck(False) # turn of bounds-checking for entire function
93   -@cython.wraparound(False)
94   -@cython.nonecheck(False)
95   -def floodfill_threshold(np.ndarray[image_t, ndim=3] data, list seeds, int t0, int t1, int fill, np.ndarray[mask_t, ndim=3] strct, np.ndarray[mask_t, ndim=3] out):
96   -
97   - cdef int to_return = 0
98   - if out is None:
99   - out = np.zeros_like(data)
100   - to_return = 1
101   -
102   - cdef int x, y, z
103   - cdef int dx, dy, dz
104   - cdef int odx, ody, odz
105   - cdef int xo, yo, zo
106   - cdef int i, j, k
107   - cdef int offset_x, offset_y, offset_z
108   -
109   - dz = data.shape[0]
110   - dy = data.shape[1]
111   - dx = data.shape[2]
112   -
113   - odz = strct.shape[0]
114   - ody = strct.shape[1]
115   - odx = strct.shape[2]
116   -
117   - cdef cdeque[coord] stack
118   - cdef coord c
119   -
120   - offset_z = odz / 2
121   - offset_y = ody / 2
122   - offset_x = odx / 2
123   -
124   - for i, j, k in seeds:
125   - if data[k, j, i] >= t0 and data[k, j, i] <= t1:
126   - c.x = i
127   - c.y = j
128   - c.z = k
129   - stack.push_back(c)
130   - out[k, j, i] = fill
131   -
132   - with nogil:
133   - while stack.size():
134   - c = stack.back()
135   - stack.pop_back()
136   -
137   - x = c.x
138   - y = c.y
139   - z = c.z
140   -
141   - out[z, y, x] = fill
142   -
143   - for k in xrange(odz):
144   - zo = z + k - offset_z
145   - for j in xrange(ody):
146   - yo = y + j - offset_y
147   - for i in xrange(odx):
148   - if strct[k, j, i]:
149   - xo = x + i - offset_x
150   - if 0 <= xo < dx and 0 <= yo < dy and 0 <= zo < dz and out[zo, yo, xo] != fill and t0 <= data[zo, yo, xo] <= t1:
151   - out[zo, yo, xo] = fill
152   - c.x = xo
153   - c.y = yo
154   - c.z = zo
155   - stack.push_back(c)
156   -
157   - if to_return:
158   - return out
159   -
160   -
161   -@cython.boundscheck(False) # turn of bounds-checking for entire function
162   -@cython.wraparound(False)
163   -@cython.nonecheck(False)
164   -def floodfill_auto_threshold(np.ndarray[image_t, ndim=3] data, list seeds, float p, int fill, np.ndarray[mask_t, ndim=3] out):
165   -
166   - cdef int to_return = 0
167   - if out is None:
168   - out = np.zeros_like(data)
169   - to_return = 1
170   -
171   - cdef cdeque[int] stack
172   - cdef int x, y, z
173   - cdef int w, h, d
174   - cdef int xo, yo, zo
175   - cdef int t0, t1
176   -
177   - cdef int i, j, k
178   -
179   - d = data.shape[0]
180   - h = data.shape[1]
181   - w = data.shape[2]
182   -
183   -
184   - # stack = deque()
185   -
186   - x = 0
187   - y = 0
188   - z = 0
189   -
190   -
191   - for i, j, k in seeds:
192   - append_queue(stack, i, j, k, d, h, w)
193   - out[k, j, i] = fill
194   - print i, j, k, d, h, w
195   -
196   - with nogil:
197   - while stack.size():
198   - pop_queue(stack, &x, &y, &z, d, h, w)
199   -
200   - # print x, y, z, d, h, w
201   -
202   - xo = x
203   - yo = y
204   - zo = z
205   -
206   - t0 = <int>ceil(data[z, y, x] * (1 - p))
207   - t1 = <int>floor(data[z, y, x] * (1 + p))
208   -
209   - if z + 1 < d and data[z + 1, y, x] >= t0 and data[z + 1, y, x] <= t1 and out[zo + 1, yo, xo] != fill:
210   - out[zo + 1, yo, xo] = fill
211   - append_queue(stack, x, y, z+1, d, h, w)
212   -
213   - if z - 1 >= 0 and data[z - 1, y, x] >= t0 and data[z - 1, y, x] <= t1 and out[zo - 1, yo, xo] != fill:
214   - out[zo - 1, yo, xo] = fill
215   - append_queue(stack, x, y, z-1, d, h, w)
216   -
217   - if y + 1 < h and data[z, y + 1, x] >= t0 and data[z, y + 1, x] <= t1 and out[zo, yo + 1, xo] != fill:
218   - out[zo, yo + 1, xo] = fill
219   - append_queue(stack, x, y+1, z, d, h, w)
220   -
221   - if y - 1 >= 0 and data[z, y - 1, x] >= t0 and data[z, y - 1, x] <= t1 and out[zo, yo - 1, xo] != fill:
222   - out[zo, yo - 1, xo] = fill
223   - append_queue(stack, x, y-1, z, d, h, w)
224   -
225   - if x + 1 < w and data[z, y, x + 1] >= t0 and data[z, y, x + 1] <= t1 and out[zo, yo, xo + 1] != fill:
226   - out[zo, yo, xo + 1] = fill
227   - append_queue(stack, x+1, y, z, d, h, w)
228   -
229   - if x - 1 >= 0 and data[z, y, x - 1] >= t0 and data[z, y, x - 1] <= t1 and out[zo, yo, xo - 1] != fill:
230   - out[zo, yo, xo - 1] = fill
231   - append_queue(stack, x-1, y, z, d, h, w)
232   -
233   - if to_return:
234   - return out
235   -
236   -
237   -@cython.boundscheck(False)
238   -@cython.wraparound(False)
239   -@cython.nonecheck(False)
240   -def fill_holes_automatically(np.ndarray[mask_t, ndim=3] mask, np.ndarray[np.uint16_t, ndim=3] labels, unsigned int nlabels, unsigned int max_size):
241   - """
242   - Fill mask holes automatically. The hole must <= max_size. Return True if any hole were filled.
243   - """
244   - cdef np.ndarray[np.uint32_t, ndim=1] sizes = np.zeros(shape=(nlabels + 1), dtype=np.uint32)
245   - cdef int x, y, z
246   - cdef int dx, dy, dz
247   - cdef int i
248   -
249   - cdef bool modified = False
250   -
251   - dz = mask.shape[0]
252   - dy = mask.shape[1]
253   - dx = mask.shape[2]
254   -
255   - for z in xrange(dz):
256   - for y in xrange(dy):
257   - for x in xrange(dx):
258   - sizes[labels[z, y, x]] += 1
259   -
260   - #Checking if any hole will be filled
261   - for i in xrange(nlabels + 1):
262   - if sizes[i] <= max_size:
263   - modified = True
264   -
265   - if not modified:
266   - return 0
267   -
268   - for z in prange(dz, nogil=True):
269   - for y in xrange(dy):
270   - for x in xrange(dx):
271   - if sizes[labels[z, y, x]] <= max_size:
272   - mask[z, y, x] = 254
273   -
274   - return modified
invesalius/data/interpolation.pxd
View file @73ddbb0
... ... @@ -1,8 +0,0 @@
1   -from .cy_my_types cimport image_t
2   -
3   -cdef double interpolate(image_t[:, :, :], double, double, double) nogil
4   -cdef double tricub_interpolate(image_t[:, :, :], double, double, double) nogil
5   -cdef double tricubicInterpolate (image_t[:, :, :], double, double, double) nogil
6   -cdef double lanczos3 (image_t[:, :, :], double, double, double) nogil
7   -
8   -cdef double nearest_neighbour_interp(image_t[:, :, :], double, double, double) nogil
invesalius/data/interpolation.pyx
View file @73ddbb0
... ... @@ -1,392 +0,0 @@
1   -# from interpolation cimport interpolate
2   -
3   -import numpy as np
4   -cimport numpy as np
5   -cimport cython
6   -
7   -from libc.math cimport floor, ceil, sqrt, fabs, sin, M_PI
8   -from cython.parallel import prange
9   -
10   -DEF LANCZOS_A = 4
11   -DEF SIZE_LANCZOS_TMP = LANCZOS_A * 2 - 1
12   -
13   -cdef double[64][64] temp = [
14   - [ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
15   - [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
16   - [-3, 3, 0, 0, 0, 0, 0, 0,-2,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
17   - [ 2, -2, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
18   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
19   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
20   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
21   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
22   - [-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
23   - [ 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
24   - [ 9, -9,-9, 9, 0, 0, 0, 0, 6, 3,-6,-3, 0, 0, 0, 0, 6,-6, 3,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 2, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
25   - [-6, 6, 6,-6, 0, 0, 0, 0,-3,-3, 3, 3, 0, 0, 0, 0,-4, 4,-2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-2,-1,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
26   - [ 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
27   - [ 0, 0, 0, 0, 0, 0, 0, 0, 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
28   - [-6, 6, 6,-6, 0, 0, 0, 0,-4,-2, 4, 2, 0, 0, 0, 0,-3, 3,-3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-1,-2,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
29   - [ 4, -4,-4, 4, 0, 0, 0, 0, 2, 2,-2,-2, 0, 0, 0, 0, 2,-2, 2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
30   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
31   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
32   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
33   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
34   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
35   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
36   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 3, 0, 0, 0, 0, 0, 0,-2,-1, 0, 0, 0, 0, 0, 0],
37   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0],
38   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
39   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0, 0, 0, 0, 0],
40   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9,-9,-9, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 3,-6,-3, 0, 0, 0, 0, 6,-6, 3,-3, 0, 0, 0, 0, 4, 2, 2, 1, 0, 0, 0, 0],
41   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-6, 6, 6,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3,-3, 3, 3, 0, 0, 0, 0,-4, 4,-2, 2, 0, 0, 0, 0,-2,-2,-1,-1, 0, 0, 0, 0],
42   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
43   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0],
44   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-6, 6, 6,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4,-2, 4, 2, 0, 0, 0, 0,-3, 3,-3, 3, 0, 0, 0, 0,-2,-1,-2,-1, 0, 0, 0, 0],
45   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4,-4,-4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2,-2,-2, 0, 0, 0, 0, 2,-2, 2,-2, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0],
46   - [-3, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0, 0, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
47   - [ 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0, 0, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
48   - [ 9, -9, 0, 0,-9, 9, 0, 0, 6, 3, 0, 0,-6,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6,-6, 0, 0, 3,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 2, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
49   - [-6, 6, 0, 0, 6,-6, 0, 0,-3,-3, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4, 4, 0, 0,-2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-2, 0, 0,-1,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
50   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0, 0, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
51   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0, 0, 0,-1, 0, 0, 0],
52   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9,-9, 0, 0,-9, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 3, 0, 0,-6,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6,-6, 0, 0, 3,-3, 0, 0, 4, 2, 0, 0, 2, 1, 0, 0],
53   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-6, 6, 0, 0, 6,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3,-3, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4, 4, 0, 0,-2, 2, 0, 0,-2,-2, 0, 0,-1,-1, 0, 0],
54   - [ 9, 0,-9, 0,-9, 0, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 3, 0,-6, 0,-3, 0, 6, 0,-6, 0, 3, 0,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 2, 0, 2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
55   - [ 0, 0, 0, 0, 0, 0, 0, 0, 9, 0,-9, 0,-9, 0, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 3, 0,-6, 0,-3, 0, 6, 0,-6, 0, 3, 0,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 2, 0, 2, 0, 1, 0],
56   - [-27, 27,27,-27,27,-27,-27,27,-18,-9,18, 9,18, 9,-18,-9,-18,18,-9, 9,18,-18, 9,-9,-18,18,18,-18,-9, 9, 9,-9,-12,-6,-6,-3,12, 6, 6, 3,-12,-6,12, 6,-6,-3, 6, 3,-12,12,-6, 6,-6, 6,-3, 3,-8,-4,-4,-2,-4,-2,-2,-1],
57   - [18, -18,-18,18,-18,18,18,-18, 9, 9,-9,-9,-9,-9, 9, 9,12,-12, 6,-6,-12,12,-6, 6,12,-12,-12,12, 6,-6,-6, 6, 6, 6, 3, 3,-6,-6,-3,-3, 6, 6,-6,-6, 3, 3,-3,-3, 8,-8, 4,-4, 4,-4, 2,-2, 4, 4, 2, 2, 2, 2, 1, 1],
58   - [-6, 0, 6, 0, 6, 0,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0,-3, 0, 3, 0, 3, 0,-4, 0, 4, 0,-2, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-2, 0,-1, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
59   - [ 0, 0, 0, 0, 0, 0, 0, 0,-6, 0, 6, 0, 6, 0,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0,-3, 0, 3, 0, 3, 0,-4, 0, 4, 0,-2, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-2, 0,-1, 0,-1, 0],
60   - [18, -18,-18,18,-18,18,18,-18,12, 6,-12,-6,-12,-6,12, 6, 9,-9, 9,-9,-9, 9,-9, 9,12,-12,-12,12, 6,-6,-6, 6, 6, 3, 6, 3,-6,-3,-6,-3, 8, 4,-8,-4, 4, 2,-4,-2, 6,-6, 6,-6, 3,-3, 3,-3, 4, 2, 4, 2, 2, 1, 2, 1],
61   - [-12, 12,12,-12,12,-12,-12,12,-6,-6, 6, 6, 6, 6,-6,-6,-6, 6,-6, 6, 6,-6, 6,-6,-8, 8, 8,-8,-4, 4, 4,-4,-3,-3,-3,-3, 3, 3, 3, 3,-4,-4, 4, 4,-2,-2, 2, 2,-4, 4,-4, 4,-2, 2,-2, 2,-2,-2,-2,-2,-1,-1,-1,-1],
62   - [ 2, 0, 0, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
63   - [ 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
64   - [-6, 6, 0, 0, 6,-6, 0, 0,-4,-2, 0, 0, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 3, 0, 0,-3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-1, 0, 0,-2,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
65   - [ 4, -4, 0, 0,-4, 4, 0, 0, 2, 2, 0, 0,-2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0, 2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
66   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
67   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0],
68   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-6, 6, 0, 0, 6,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4,-2, 0, 0, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 3, 0, 0,-3, 3, 0, 0,-2,-1, 0, 0,-2,-1, 0, 0],
69   - [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4,-4, 0, 0,-4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 0, 0,-2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0, 2,-2, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0],
70   - [-6, 0, 6, 0, 6, 0,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4, 0,-2, 0, 4, 0, 2, 0,-3, 0, 3, 0,-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0,-2, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
71   - [ 0, 0, 0, 0, 0, 0, 0, 0,-6, 0, 6, 0, 6, 0,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4, 0,-2, 0, 4, 0, 2, 0,-3, 0, 3, 0,-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0,-2, 0,-1, 0],
72   - [18, -18,-18,18,-18,18,18,-18,12, 6,-12,-6,-12,-6,12, 6,12,-12, 6,-6,-12,12,-6, 6, 9,-9,-9, 9, 9,-9,-9, 9, 8, 4, 4, 2,-8,-4,-4,-2, 6, 3,-6,-3, 6, 3,-6,-3, 6,-6, 3,-3, 6,-6, 3,-3, 4, 2, 2, 1, 4, 2, 2, 1],
73   - [-12, 12,12,-12,12,-12,-12,12,-6,-6, 6, 6, 6, 6,-6,-6,-8, 8,-4, 4, 8,-8, 4,-4,-6, 6, 6,-6,-6, 6, 6,-6,-4,-4,-2,-2, 4, 4, 2, 2,-3,-3, 3, 3,-3,-3, 3, 3,-4, 4,-2, 2,-4, 4,-2, 2,-2,-2,-1,-1,-2,-2,-1,-1],
74   - [ 4, 0,-4, 0,-4, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 2, 0,-2, 0,-2, 0, 2, 0,-2, 0, 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
75   - [ 0, 0, 0, 0, 0, 0, 0, 0, 4, 0,-4, 0,-4, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 2, 0,-2, 0,-2, 0, 2, 0,-2, 0, 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0],
76   - [-12, 12,12,-12,12,-12,-12,12,-8,-4, 8, 4, 8, 4,-8,-4,-6, 6,-6, 6, 6,-6, 6,-6,-6, 6, 6,-6,-6, 6, 6,-6,-4,-2,-4,-2, 4, 2, 4, 2,-4,-2, 4, 2,-4,-2, 4, 2,-3, 3,-3, 3,-3, 3,-3, 3,-2,-1,-2,-1,-2,-1,-2,-1],
77   - [ 8, -8,-8, 8,-8, 8, 8,-8, 4, 4,-4,-4,-4,-4, 4, 4, 4,-4, 4,-4,-4, 4,-4, 4, 4,-4,-4, 4, 4,-4,-4, 4, 2, 2, 2, 2,-2,-2,-2,-2, 2, 2,-2,-2, 2, 2,-2,-2, 2,-2, 2,-2, 2,-2, 2,-2, 1, 1, 1, 1, 1, 1, 1, 1]
78   -]
79   -
80   -@cython.boundscheck(False) # turn of bounds-checking for entire function
81   -@cython.cdivision(True)
82   -@cython.wraparound(False)
83   -cdef double nearest_neighbour_interp(image_t[:, :, :] V, double x, double y, double z) nogil:
84   - return V[<int>(z), <int>(y), <int>(x)]
85   -
86   -@cython.boundscheck(False) # turn of bounds-checking for entire function
87   -@cython.cdivision(True)
88   -@cython.wraparound(False)
89   -cdef double interpolate(image_t[:, :, :] V, double x, double y, double z) nogil:
90   - cdef double xd, yd, zd
91   - cdef double c00, c10, c01, c11
92   - cdef double c0, c1
93   - cdef double c
94   -
95   - cdef int x0 = <int>floor(x)
96   - cdef int x1 = x0 + 1
97   -
98   - cdef int y0 = <int>floor(y)
99   - cdef int y1 = y0 + 1
100   -
101   - cdef int z0 = <int>floor(z)
102   - cdef int z1 = z0 + 1
103   -
104   - if x0 == x1:
105   - xd = 1.0
106   - else:
107   - xd = (x - x0) / (x1 - x0)
108   -
109   - if y0 == y1:
110   - yd = 1.0
111   - else:
112   - yd = (y - y0) / (y1 - y0)
113   -
114   - if z0 == z1:
115   - zd = 1.0
116   - else:
117   - zd = (z - z0) / (z1 - z0)
118   -
119   - c00 = _G(V, x0, y0, z0)*(1 - xd) + _G(V, x1, y0, z0)*xd
120   - c10 = _G(V, x0, y1, z0)*(1 - xd) + _G(V, x1, y1, z0)*xd
121   - c01 = _G(V, x0, y0, z1)*(1 - xd) + _G(V, x1, y0, z1)*xd
122   - c11 = _G(V, x0, y1, z1)*(1 - xd) + _G(V, x1, y1, z1)*xd
123   -
124   - c0 = c00*(1 - yd) + c10*yd
125   - c1 = c01*(1 - yd) + c11*yd
126   -
127   - c = c0*(1 - zd) + c1*zd
128   -
129   - return c
130   -
131   -
132   -@cython.boundscheck(False) # turn of bounds-checking for entire function
133   -@cython.cdivision(True)
134   -@cython.wraparound(False)
135   -cdef inline double lanczos3_L(double x, int a) nogil:
136   - if x == 0:
137   - return 1.0
138   - elif -a <= x < a:
139   - return (a * sin(M_PI * x) * sin(M_PI * (x / a)))/(M_PI**2 * x**2)
140   - else:
141   - return 0.0
142   -
143   -
144   -@cython.boundscheck(False) # turn of bounds-checking for entire function
145   -@cython.cdivision(True)
146   -@cython.wraparound(False)
147   -cdef double lanczos3(image_t[:, :, :] V, double x, double y, double z) nogil:
148   - cdef int a = LANCZOS_A
149   -
150   - cdef int xd = <int>floor(x)
151   - cdef int yd = <int>floor(y)
152   - cdef int zd = <int>floor(z)
153   -
154   - cdef int xi = xd - a + 1
155   - cdef int xf = xd + a
156   -
157   - cdef int yi = yd - a + 1
158   - cdef int yf = yd + a
159   -
160   - cdef int zi = zd - a + 1
161   - cdef int zf = zd + a
162   -
163   - cdef double lx = 0.0
164   - cdef double ly = 0.0
165   - cdef double lz = 0.0
166   -
167   - cdef double[SIZE_LANCZOS_TMP][SIZE_LANCZOS_TMP] temp_x
168   - cdef double[SIZE_LANCZOS_TMP] temp_y
169   -
170   - cdef int i, j, k
171   - cdef int m, n, o
172   -
173   - m = 0
174   - for k in xrange(zi, zf):
175   - n = 0
176   - for j in xrange(yi, yf):
177   - lx = 0
178   - for i in xrange(xi, xf):
179   - lx += _G(V, i, j, k) * lanczos3_L(x - i, a)
180   - temp_x[m][n] = lx
181   - n += 1
182   - m += 1
183   -
184   - m = 0
185   - for k in xrange(zi, zf):
186   - n = 0
187   - ly = 0
188   - for j in xrange(yi, yf):
189   - ly += temp_x[m][n] * lanczos3_L(y - j, a)
190   - n += 1
191   - temp_y[m] = ly
192   - m += 1
193   -
194   - m = 0
195   - for k in xrange(zi, zf):
196   - lz += temp_y[m] * lanczos3_L(z - k, a)
197   - m += 1
198   -
199   - return lz
200   -
201   -
202   -@cython.boundscheck(False) # turn of bounds-checking for entire function
203   -@cython.cdivision(True)
204   -@cython.wraparound(False)
205   -cdef image_t _G(image_t[:, :, :] V, int x, int y, int z) nogil:
206   - cdef int dz, dy, dx
207   - dz = V.shape[0] - 1
208   - dy = V.shape[1] - 1
209   - dx = V.shape[2] - 1
210   -
211   - if x < 0:
212   - x = dx + x + 1
213   - elif x > dx:
214   - x = x - dx - 1
215   -
216   - if y < 0:
217   - y = dy + y + 1
218   - elif y > dy:
219   - y = y - dy - 1
220   -
221   - if z < 0:
222   - z = dz + z + 1
223   - elif z > dz:
224   - z = z - dz - 1
225   -
226   - return V[z, y, x]
227   -
228   -
229   -@cython.boundscheck(False) # turn of bounds-checking for entire function
230   -@cython.cdivision(True)
231   -@cython.wraparound(False)
232   -cdef void calc_coef_tricub(image_t[:, :, :] V, double x, double y, double z, double [64] coef) nogil:
233   - cdef int xi = <int>floor(x)
234   - cdef int yi = <int>floor(y)
235   - cdef int zi = <int>floor(z)
236   -
237   - cdef double[64] _x
238   -
239   - cdef int i, j
240   -
241   - _x[0] = _G(V, xi, yi, zi)
242   - _x[1] = _G(V, xi + 1, yi, zi)
243   - _x[2] = _G(V, xi, yi + 1, zi)
244   - _x[3] = _G(V, xi + 1, yi + 1, zi)
245   - _x[4] = _G(V, xi, yi, zi + 1)
246   - _x[5] = _G(V, xi + 1, yi, zi + 1)
247   - _x[6] = _G(V, xi, yi + 1, zi + 1)
248   - _x[7] = _G(V, xi + 1, yi + 1, zi + 1)
249   -
250   - _x[8] = 0.5*(_G(V, xi+1,yi,zi) - _G(V, xi-1, yi, zi))
251   - _x[9] = 0.5*(_G(V, xi+2,yi,zi) - _G(V, xi, yi, zi))
252   - _x[10] = 0.5*(_G(V, xi+1, yi+1,zi) - _G(V, xi-1, yi+1, zi))
253   - _x[11] = 0.5*(_G(V, xi+2, yi+1,zi) - _G(V, xi, yi+1, zi))
254   - _x[12] = 0.5*(_G(V, xi+1, yi,zi+1) - _G(V, xi-1, yi, zi+1))
255   - _x[13] = 0.5*(_G(V, xi+2, yi,zi+1) - _G(V, xi, yi, zi+1))
256   - _x[14] = 0.5*(_G(V, xi+1, yi+1,zi+1) - _G(V, xi-1, yi+1, zi+1))
257   - _x[15] = 0.5*(_G(V, xi+2, yi+1,zi+1) - _G(V, xi, yi+1, zi+1))
258   - _x[16] = 0.5*(_G(V, xi, yi+1,zi) - _G(V, xi, yi-1, zi))
259   - _x[17] = 0.5*(_G(V, xi+1, yi+1,zi) - _G(V, xi+1, yi-1, zi))
260   - _x[18] = 0.5*(_G(V, xi, yi+2,zi) - _G(V, xi, yi, zi))
261   - _x[19] = 0.5*(_G(V, xi+1, yi+2,zi) - _G(V, xi+1, yi, zi))
262   - _x[20] = 0.5*(_G(V, xi, yi+1,zi+1) - _G(V, xi, yi-1, zi+1))
263   - _x[21] = 0.5*(_G(V, xi+1, yi+1,zi+1) - _G(V, xi+1, yi-1, zi+1))
264   - _x[22] = 0.5*(_G(V, xi, yi+2,zi+1) - _G(V, xi, yi, zi+1))
265   - _x[23] = 0.5*(_G(V, xi+1, yi+2,zi+1) - _G(V, xi+1, yi, zi+1))
266   - _x[24] = 0.5*(_G(V, xi, yi,zi+1) - _G(V, xi, yi, zi-1))
267   - _x[25] = 0.5*(_G(V, xi+1, yi,zi+1) - _G(V, xi+1, yi, zi-1))
268   - _x[26] = 0.5*(_G(V, xi, yi+1,zi+1) - _G(V, xi, yi+1, zi-1))
269   - _x[27] = 0.5*(_G(V, xi+1, yi+1,zi+1) - _G(V, xi+1, yi+1, zi-1))
270   - _x[28] = 0.5*(_G(V, xi, yi,zi+2) - _G(V, xi, yi, zi))
271   - _x[29] = 0.5*(_G(V, xi+1, yi,zi+2) - _G(V, xi+1, yi, zi))
272   - _x[30] = 0.5*(_G(V, xi, yi+1,zi+2) - _G(V, xi, yi+1, zi))
273   - _x[31] = 0.5*(_G(V, xi+1, yi+1,zi+2) - _G(V, xi+1, yi+1, zi))
274   -
275   - _x [32] = 0.25*(_G(V, xi+1, yi+1, zi) - _G(V, xi-1, yi+1, zi) - _G(V, xi+1, yi-1, zi) + _G(V, xi-1, yi-1, zi))
276   - _x [33] = 0.25*(_G(V, xi+2, yi+1, zi) - _G(V, xi, yi+1, zi) - _G(V, xi+2, yi-1, zi) + _G(V, xi, yi-1, zi))
277   - _x [34] = 0.25*(_G(V, xi+1, yi+2, zi) - _G(V, xi-1, yi+2, zi) - _G(V, xi+1, yi, zi) + _G(V, xi-1, yi, zi))
278   - _x [35] = 0.25*(_G(V, xi+2, yi+2, zi) - _G(V, xi, yi+2, zi) - _G(V, xi+2, yi, zi) + _G(V, xi, yi, zi))
279   - _x [36] = 0.25*(_G(V, xi+1, yi+1, zi+1) - _G(V, xi-1, yi+1, zi+1) - _G(V, xi+1, yi-1, zi+1) + _G(V, xi-1, yi-1, zi+1))
280   - _x [37] = 0.25*(_G(V, xi+2, yi+1, zi+1) - _G(V, xi, yi+1, zi+1) - _G(V, xi+2, yi-1, zi+1) + _G(V, xi, yi-1, zi+1))
281   - _x [38] = 0.25*(_G(V, xi+1, yi+2, zi+1) - _G(V, xi-1, yi+2, zi+1) - _G(V, xi+1, yi, zi+1) + _G(V, xi-1, yi, zi+1))
282   - _x [39] = 0.25*(_G(V, xi+2, yi+2, zi+1) - _G(V, xi, yi+2, zi+1) - _G(V, xi+2, yi, zi+1) + _G(V, xi, yi, zi+1))
283   - _x [40] = 0.25*(_G(V, xi+1, yi, zi+1) - _G(V, xi-1, yi, zi+1) - _G(V, xi+1, yi, zi-1) + _G(V, xi-1, yi, zi-1))
284   - _x [41] = 0.25*(_G(V, xi+2, yi, zi+1) - _G(V, xi, yi, zi+1) - _G(V, xi+2, yi, zi-1) + _G(V, xi, yi, zi-1))
285   - _x [42] = 0.25*(_G(V, xi+1, yi+1, zi+1) - _G(V, xi-1, yi+1, zi+1) - _G(V, xi+1, yi+1, zi-1) + _G(V, xi-1, yi+1, zi-1))
286   - _x [43] = 0.25*(_G(V, xi+2, yi+1, zi+1) - _G(V, xi, yi+1, zi+1) - _G(V, xi+2, yi+1, zi-1) + _G(V, xi, yi+1, zi-1))
287   - _x [44] = 0.25*(_G(V, xi+1, yi, zi+2) - _G(V, xi-1, yi, zi+2) - _G(V, xi+1, yi, zi) + _G(V, xi-1, yi, zi))
288   - _x [45] = 0.25*(_G(V, xi+2, yi, zi+2) - _G(V, xi, yi, zi+2) - _G(V, xi+2, yi, zi) + _G(V, xi, yi, zi))
289   - _x [46] = 0.25*(_G(V, xi+1, yi+1, zi+2) - _G(V, xi-1, yi+1, zi+2) - _G(V, xi+1, yi+1, zi) + _G(V, xi-1, yi+1, zi))
290   - _x [47] = 0.25*(_G(V, xi+2, yi+1, zi+2) - _G(V, xi, yi+1, zi+2) - _G(V, xi+2, yi+1, zi) + _G(V, xi, yi+1, zi))
291   - _x [48] = 0.25*(_G(V, xi, yi+1, zi+1) - _G(V, xi, yi-1, zi+1) - _G(V, xi, yi+1, zi-1) + _G(V, xi, yi-1, zi-1))
292   - _x [49] = 0.25*(_G(V, xi+1, yi+1, zi+1) - _G(V, xi+1, yi-1, zi+1) - _G(V, xi+1, yi+1, zi-1) + _G(V, xi+1, yi-1, zi-1))
293   - _x [50] = 0.25*(_G(V, xi, yi+2, zi+1) - _G(V, xi, yi, zi+1) - _G(V, xi, yi+2, zi-1) + _G(V, xi, yi, zi-1))
294   - _x [51] = 0.25*(_G(V, xi+1, yi+2, zi+1) - _G(V, xi+1, yi, zi+1) - _G(V, xi+1, yi+2, zi-1) + _G(V, xi+1, yi, zi-1))
295   - _x [52] = 0.25*(_G(V, xi, yi+1, zi+2) - _G(V, xi, yi-1, zi+2) - _G(V, xi, yi+1, zi) + _G(V, xi, yi-1, zi))
296   - _x [53] = 0.25*(_G(V, xi+1, yi+1, zi+2) - _G(V, xi+1, yi-1, zi+2) - _G(V, xi+1, yi+1, zi) + _G(V, xi+1, yi-1, zi))
297   - _x [54] = 0.25*(_G(V, xi, yi+2, zi+2) - _G(V, xi, yi, zi+2) - _G(V, xi, yi+2, zi) + _G(V, xi, yi, zi))
298   - _x [55] = 0.25*(_G(V, xi+1, yi+2, zi+2) - _G(V, xi+1, yi, zi+2) - _G(V, xi+1, yi+2, zi) + _G(V, xi+1, yi, zi))
299   -
300   - _x[56] = 0.125*(_G(V, xi+1, yi+1, zi+1) - _G(V, xi-1, yi+1, zi+1) - _G(V, xi+1, yi-1, zi+1) + _G(V, xi-1, yi-1, zi+1) - _G(V, xi+1, yi+1, zi-1) + _G(V, xi-1,yi+1,zi-1)+_G(V, xi+1,yi-1,zi-1)-_G(V, xi-1,yi-1,zi-1))
301   - _x[57] = 0.125*(_G(V, xi+2, yi+1, zi+1) - _G(V, xi, yi+1, zi+1) - _G(V, xi+2, yi-1, zi+1) + _G(V, xi, yi-1, zi+1) - _G(V, xi+2, yi+1, zi-1) + _G(V, xi,yi+1,zi-1)+_G(V, xi+2,yi-1,zi-1)-_G(V, xi,yi-1,zi-1))
302   - _x[58] = 0.125*(_G(V, xi+1, yi+2, zi+1) - _G(V, xi-1, yi+2, zi+1) - _G(V, xi+1, yi, zi+1) + _G(V, xi-1, yi, zi+1) - _G(V, xi+1, yi+2, zi-1) + _G(V, xi-1,yi+2,zi-1)+_G(V, xi+1,yi,zi-1)-_G(V, xi-1,yi,zi-1))
303   - _x[59] = 0.125*(_G(V, xi+2, yi+2, zi+1) - _G(V, xi, yi+2, zi+1) - _G(V, xi+2, yi, zi+1) + _G(V, xi, yi, zi+1) - _G(V, xi+2, yi+2, zi-1) + _G(V, xi,yi+2,zi-1)+_G(V, xi+2,yi,zi-1)-_G(V, xi,yi,zi-1))
304   - _x[60] = 0.125*(_G(V, xi+1, yi+1, zi+2) - _G(V, xi-1, yi+1, zi+2) - _G(V, xi+1, yi-1, zi+2) + _G(V, xi-1, yi-1, zi+2) - _G(V, xi+1, yi+1, zi) + _G(V, xi-1,yi+1,zi)+_G(V, xi+1,yi-1,zi)-_G(V, xi-1,yi-1,zi))
305   - _x[61] = 0.125*(_G(V, xi+2, yi+1, zi+2) - _G(V, xi, yi+1, zi+2) - _G(V, xi+2, yi-1, zi+2) + _G(V, xi, yi-1, zi+2) - _G(V, xi+2, yi+1, zi) + _G(V, xi,yi+1,zi)+_G(V, xi+2,yi-1,zi)-_G(V, xi,yi-1,zi))
306   - _x[62] = 0.125*(_G(V, xi+1, yi+2, zi+2) - _G(V, xi-1, yi+2, zi+2) - _G(V, xi+1, yi, zi+2) + _G(V, xi-1, yi, zi+2) - _G(V, xi+1, yi+2, zi) + _G(V, xi-1,yi+2,zi)+_G(V, xi+1,yi,zi)-_G(V, xi-1,yi,zi))
307   - _x[63] = 0.125*(_G(V, xi+2, yi+2, zi+2) - _G(V, xi, yi+2, zi+2) - _G(V, xi+2, yi, zi+2) + _G(V, xi, yi, zi+2) - _G(V, xi+2, yi+2, zi) + _G(V, xi,yi+2,zi)+_G(V, xi+2,yi,zi)-_G(V, xi,yi,zi))
308   -
309   - for j in prange(64):
310   - coef[j] = 0.0
311   - for i in xrange(64):
312   - coef[j] += (temp[j][i] * _x[i])
313   -
314   -
315   -@cython.boundscheck(False) # turn of bounds-checking for entire function
316   -@cython.cdivision(True)
317   -@cython.wraparound(False)
318   -cdef double tricub_interpolate(image_t[:, :, :] V, double x, double y, double z) nogil:
319   - # From: Tricubic interpolation in three dimensions. Lekien and Marsden
320   - cdef double[64] coef
321   - cdef double result = 0.0
322   - calc_coef_tricub(V, x, y, z, coef)
323   -
324   - cdef int i, j, k
325   -
326   - cdef int xi = <int>floor(x)
327   - cdef int yi = <int>floor(y)
328   - cdef int zi = <int>floor(z)
329   -
330   - for i in xrange(4):
331   - for j in xrange(4):
332   - for k in xrange(4):
333   - result += (coef[i+4*j+16*k] * ((x-xi)**i) * ((y-yi)**j) * ((z-zi)**k))
334   - # return V[<int>z, <int>y, <int>x]
335   - # with gil:
336   - # print result
337   - return result
338   -
339   -
340   -@cython.boundscheck(False) # turn of bounds-checking for entire function
341   -@cython.cdivision(True)
342   -@cython.wraparound(False)
343   -cdef double cubicInterpolate(double p[4], double x) nogil:
344   - return p[1] + 0.5 * x*(p[2] - p[0] + x*(2.0*p[0] - 5.0*p[1] + 4.0*p[2] - p[3] + x*(3.0*(p[1] - p[2]) + p[3] - p[0])))
345   -
346   -
347   -@cython.boundscheck(False) # turn of bounds-checking for entire function
348   -@cython.cdivision(True)
349   -@cython.wraparound(False)
350   -cdef double bicubicInterpolate (double p[4][4], double x, double y) nogil:
351   - cdef double arr[4]
352   - arr[0] = cubicInterpolate(p[0], y)
353   - arr[1] = cubicInterpolate(p[1], y)
354   - arr[2] = cubicInterpolate(p[2], y)
355   - arr[3] = cubicInterpolate(p[3], y)
356   - return cubicInterpolate(arr, x)
357   -
358   -
359   -@cython.boundscheck(False) # turn of bounds-checking for entire function
360   -@cython.cdivision(True)
361   -@cython.wraparound(False)
362   -cdef double tricubicInterpolate(image_t[:, :, :] V, double x, double y, double z) nogil:
363   - # From http://www.paulinternet.nl/?page=bicubic
364   - cdef double p[4][4][4]
365   -
366   - cdef int xi = <int>floor(x)
367   - cdef int yi = <int>floor(y)
368   - cdef int zi = <int>floor(z)
369   -
370   - cdef int i, j, k
371   -
372   - for i in xrange(4):
373   - for j in xrange(4):
374   - for k in xrange(4):
375   - p[i][j][k] = _G(V, xi + i -1, yi + j -1, zi + k - 1)
376   -
377   - cdef double arr[4]
378   - arr[0] = bicubicInterpolate(p[0], y-yi, z-zi)
379   - arr[1] = bicubicInterpolate(p[1], y-yi, z-zi)
380   - arr[2] = bicubicInterpolate(p[2], y-yi, z-zi)
381   - arr[3] = bicubicInterpolate(p[3], y-yi, z-zi)
382   - return cubicInterpolate(arr, x-xi)
383   -
384   -
385   -def tricub_interpolate_py(image_t[:, :, :] V, double x, double y, double z):
386   - return tricub_interpolate(V, x, y, z)
387   -
388   -def tricub_interpolate2_py(image_t[:, :, :] V, double x, double y, double z):
389   - return tricubicInterpolate(V, x, y, z)
390   -
391   -def trilin_interpolate_py(image_t[:, :, :] V, double x, double y, double z):
392   - return interpolate(V, x, y, z)
invesalius/data/mask.py
  Diff comments   View file @18c2bcd
... ... @@ -30,7 +30,7 @@ import invesalius.constants as const
30 30 import invesalius.data.imagedata_utils as iu
31 31 import invesalius.session as ses
32 32  
33   -from . import floodfill
  33 +from invesalius_cy import floodfill
34 34  
35 35 from wx.lib.pubsub import pub as Publisher
36 36 from scipy import ndimage
... ...
invesalius/data/mips.pyx
View file @73ddbb0
... ... @@ -1,379 +0,0 @@
1   -#http://en.wikipedia.org/wiki/Local_maximum_intensity_projection
2   -import numpy as np
3   -cimport numpy as np
4   -cimport cython
5   -
6   -from libc.math cimport floor, ceil, sqrt, fabs
7   -from cython.parallel import prange
8   -
9   -DTYPE = np.uint8
10   -ctypedef np.uint8_t DTYPE_t
11   -
12   -DTYPE16 = np.int16
13   -ctypedef np.int16_t DTYPE16_t
14   -
15   -DTYPEF32 = np.float32
16   -ctypedef np.float32_t DTYPEF32_t
17   -
18   -@cython.boundscheck(False) # turn of bounds-checking for entire function
19   -def lmip(np.ndarray[DTYPE16_t, ndim=3] image, int axis, DTYPE16_t tmin,
20   - DTYPE16_t tmax, np.ndarray[DTYPE16_t, ndim=2] out):
21   - cdef DTYPE16_t max
22   - cdef int start
23   - cdef int sz = image.shape[0]
24   - cdef int sy = image.shape[1]
25   - cdef int sx = image.shape[2]
26   -
27   - # AXIAL
28   - if axis == 0:
29   - for x in xrange(sx):
30   - for y in xrange(sy):
31   - max = image[0, y, x]
32   - if max >= tmin and max <= tmax:
33   - start = 1
34   - else:
35   - start = 0
36   - for z in xrange(sz):
37   - if image[z, y, x] > max:
38   - max = image[z, y, x]
39   -
40   - elif image[z, y, x] < max and start:
41   - break
42   -
43   - if image[z, y, x] >= tmin and image[z, y, x] <= tmax:
44   - start = 1
45   -
46   - out[y, x] = max
47   -
48   - #CORONAL
49   - elif axis == 1:
50   - for z in xrange(sz):
51   - for x in xrange(sx):
52   - max = image[z, 0, x]
53   - if max >= tmin and max <= tmax:
54   - start = 1
55   - else:
56   - start = 0
57   - for y in xrange(sy):
58   - if image[z, y, x] > max:
59   - max = image[z, y, x]
60   -
61   - elif image[z, y, x] < max and start:
62   - break
63   -
64   - if image[z, y, x] >= tmin and image[z, y, x] <= tmax:
65   - start = 1
66   -
67   - out[z, x] = max
68   -
69   - #CORONAL
70   - elif axis == 2:
71   - for z in xrange(sz):
72   - for y in xrange(sy):
73   - max = image[z, y, 0]
74   - if max >= tmin and max <= tmax:
75   - start = 1
76   - else:
77   - start = 0
78   - for x in xrange(sx):
79   - if image[z, y, x] > max:
80   - max = image[z, y, x]
81   -
82   - elif image[z, y, x] < max and start:
83   - break
84   -
85   - if image[z, y, x] >= tmin and image[z, y, x] <= tmax:
86   - start = 1
87   -
88   - out[z, y] = max
89   -
90   -
91   -cdef DTYPE16_t get_colour(DTYPE16_t vl, DTYPE16_t wl, DTYPE16_t ww):
92   - cdef DTYPE16_t out_colour
93   - cdef DTYPE16_t min_value = wl - (ww / 2)
94   - cdef DTYPE16_t max_value = wl + (ww / 2)
95   - if vl < min_value:
96   - out_colour = min_value
97   - elif vl > max_value:
98   - out_colour = max_value
99   - else:
100   - out_colour = vl
101   -
102   - return out_colour
103   -
104   -@cython.boundscheck(False) # turn of bounds-checking for entire function
105   -@cython.cdivision(True)
106   -cdef float get_opacity(DTYPE16_t vl, DTYPE16_t wl, DTYPE16_t ww) nogil:
107   - cdef float out_opacity
108   - cdef DTYPE16_t min_value = wl - (ww / 2)
109   - cdef DTYPE16_t max_value = wl + (ww / 2)
110   - if vl < min_value:
111   - out_opacity = 0.0
112   - elif vl > max_value:
113   - out_opacity = 1.0
114   - else:
115   - out_opacity = 1.0/(max_value - min_value) * (vl - min_value)
116   -
117   - return out_opacity
118   -
119   -@cython.boundscheck(False) # turn of bounds-checking for entire function
120   -@cython.cdivision(True)
121   -cdef float get_opacity_f32(DTYPEF32_t vl, DTYPE16_t wl, DTYPE16_t ww) nogil:
122   - cdef float out_opacity
123   - cdef DTYPE16_t min_value = wl - (ww / 2)
124   - cdef DTYPE16_t max_value = wl + (ww / 2)
125   - if vl < min_value:
126   - out_opacity = 0.0
127   - elif vl > max_value:
128   - out_opacity = 1.0
129   - else:
130   - out_opacity = 1.0/(max_value - min_value) * (vl - min_value)
131   -
132   - return out_opacity
133   -
134   -
135   -@cython.boundscheck(False) # turn of bounds-checking for entire function
136   -@cython.cdivision(True)
137   -def mida(np.ndarray[DTYPE16_t, ndim=3] image, int axis, DTYPE16_t wl,
138   - DTYPE16_t ww, np.ndarray[DTYPE16_t, ndim=2] out):
139   - cdef int sz = image.shape[0]
140   - cdef int sy = image.shape[1]
141   - cdef int sx = image.shape[2]
142   -
143   - cdef DTYPE16_t min = image.min()
144   - cdef DTYPE16_t max = image.max()
145   - cdef DTYPE16_t vl
146   -
147   - cdef DTYPE16_t min_value = wl - (ww / 2)
148   - cdef DTYPE16_t max_value = wl + (ww / 2)
149   -
150   - cdef float fmax=0.0
151   - cdef float fpi
152   - cdef float dl
153   - cdef float bt
154   -
155   - cdef float alpha
156   - cdef float alpha_p = 0.0
157   - cdef float colour
158   - cdef float colour_p = 0
159   -
160   - cdef int x, y, z
161   -
162   - # AXIAL
163   - if axis == 0:
164   - for x in prange(sx, nogil=True):
165   - for y in xrange(sy):
166   - fmax = 0.0
167   - alpha_p = 0.0
168   - colour_p = 0.0
169   - for z in xrange(sz):
170   - vl = image[z, y, x]
171   - fpi = 1.0/(max - min) * (vl - min)
172   - if fpi > fmax:
173   - dl = fpi - fmax
174   - fmax = fpi
175   - else:
176   - dl = 0.0
177   -
178   - bt = 1.0 - dl
179   -
180   - colour = fpi
181   - alpha = get_opacity(vl, wl, ww)
182   - colour = (bt * colour_p) + (1 - bt * alpha_p) * colour * alpha
183   - alpha = (bt * alpha_p) + (1 - bt * alpha_p) * alpha
184   -
185   - colour_p = colour
186   - alpha_p = alpha
187   -
188   - if alpha >= 1.0:
189   - break
190   -
191   -
192   - #out[y, x] = <DTYPE16_t>((max_value - min_value) * colour + min_value)
193   - out[y, x] = <DTYPE16_t>((max - min) * colour + min)
194   -
195   -
196   - #CORONAL
197   - elif axis == 1:
198   - for z in prange(sz, nogil=True):
199   - for x in xrange(sx):
200   - fmax = 0.0
201   - alpha_p = 0.0
202   - colour_p = 0.0
203   - for y in xrange(sy):
204   - vl = image[z, y, x]
205   - fpi = 1.0/(max - min) * (vl - min)
206   - if fpi > fmax:
207   - dl = fpi - fmax
208   - fmax = fpi
209   - else:
210   - dl = 0.0
211   -
212   - bt = 1.0 - dl
213   -
214   - colour = fpi
215   - alpha = get_opacity(vl, wl, ww)
216   - colour = (bt * colour_p) + (1 - bt * alpha_p) * colour * alpha
217   - alpha = (bt * alpha_p) + (1 - bt * alpha_p) * alpha
218   -
219   - colour_p = colour
220   - alpha_p = alpha
221   -
222   - if alpha >= 1.0:
223   - break
224   -
225   - out[z, x] = <DTYPE16_t>((max - min) * colour + min)
226   -
227   - #AXIAL
228   - elif axis == 2:
229   - for z in prange(sz, nogil=True):
230   - for y in xrange(sy):
231   - fmax = 0.0
232   - alpha_p = 0.0
233   - colour_p = 0.0
234   - for x in xrange(sx):
235   - vl = image[z, y, x]
236   - fpi = 1.0/(max - min) * (vl - min)
237   - if fpi > fmax:
238   - dl = fpi - fmax
239   - fmax = fpi
240   - else:
241   - dl = 0.0
242   -
243   - bt = 1.0 - dl
244   -
245   - colour = fpi
246   - alpha = get_opacity(vl, wl, ww)
247   - colour = (bt * colour_p) + (1 - bt * alpha_p) * colour * alpha
248   - alpha = (bt * alpha_p) + (1 - bt * alpha_p) * alpha
249   -
250   - colour_p = colour
251   - alpha_p = alpha
252   -
253   - if alpha >= 1.0:
254   - break
255   -
256   - out[z, y] = <DTYPE16_t>((max - min) * colour + min)
257   -
258   -
259   -
260   -@cython.boundscheck(False) # turn of bounds-checking for entire function
261   -@cython.cdivision(True)
262   -cdef inline void finite_difference(DTYPE16_t[:, :, :] image,
263   - int x, int y, int z, float h, float *g) nogil:
264   - cdef int px, py, pz, fx, fy, fz
265   -
266   - cdef int sz = image.shape[0]
267   - cdef int sy = image.shape[1]
268   - cdef int sx = image.shape[2]
269   -
270   - cdef float gx, gy, gz
271   -
272   - if x == 0:
273   - px = 0
274   - fx = 1
275   - elif x == sx - 1:
276   - px = x - 1
277   - fx = x
278   - else:
279   - px = x - 1
280   - fx = x + 1
281   -
282   - if y == 0:
283   - py = 0
284   - fy = 1
285   - elif y == sy - 1:
286   - py = y - 1
287   - fy = y
288   - else:
289   - py = y - 1
290   - fy = y + 1
291   -
292   - if z == 0:
293   - pz = 0
294   - fz = 1
295   - elif z == sz - 1:
296   - pz = z - 1
297   - fz = z
298   - else:
299   - pz = z - 1
300   - fz = z + 1
301   -
302   - gx = (image[z, y, fx] - image[z, y, px]) / (2*h)
303   - gy = (image[z, fy, x] - image[z, py, x]) / (2*h)
304   - gz = (image[fz, y, x] - image[pz, y, x]) / (2*h)
305   -
306   - g[0] = gx
307   - g[1] = gy
308   - g[2] = gz
309   -
310   -
311   -
312   -@cython.boundscheck(False) # turn of bounds-checking for entire function
313   -@cython.cdivision(True)
314   -cdef inline float calc_fcm_itensity(DTYPE16_t[:, :, :] image,
315   - int x, int y, int z, float n, float* dir) nogil:
316   - cdef float g[3]
317   - finite_difference(image, x, y, z, 1.0, g)
318   - cdef float gm = sqrt(g[0]*g[0] + g[1]*g[1] + g[2]*g[2])
319   - cdef float d = g[0]*dir[0] + g[1]*dir[1] + g[2]*dir[2]
320   - cdef float sf = (1.0 - fabs(d/gm))**n
321   - #alpha = get_opacity_f32(gm, wl, ww)
322   - cdef float vl = gm * sf
323   - return vl
324   -
325   -@cython.boundscheck(False) # turn of bounds-checking for entire function
326   -@cython.cdivision(True)
327   -def fast_countour_mip(np.ndarray[DTYPE16_t, ndim=3] image,
328   - float n,
329   - int axis,
330   - DTYPE16_t wl, DTYPE16_t ww,
331   - int tmip,
332   - np.ndarray[DTYPE16_t, ndim=2] out):
333   - cdef int sz = image.shape[0]
334   - cdef int sy = image.shape[1]
335   - cdef int sx = image.shape[2]
336   - cdef float gm
337   - cdef float alpha
338   - cdef float sf
339   - cdef float d
340   -
341   - cdef float* g
342   - cdef float* dir = [ 0, 0, 0 ]
343   -
344   - cdef DTYPE16_t[:, :, :] vimage = image
345   - cdef np.ndarray[DTYPE16_t, ndim=3] tmp = np.empty_like(image)
346   -
347   - cdef DTYPE16_t min = image.min()
348   - cdef DTYPE16_t max = image.max()
349   - cdef float fmin = <float>min
350   - cdef float fmax = <float>max
351   - cdef float vl
352   - cdef DTYPE16_t V
353   -
354   - cdef int x, y, z
355   -
356   - if axis == 0:
357   - dir[2] = 1.0
358   - elif axis == 1:
359   - dir[1] = 1.0
360   - elif axis == 2:
361   - dir[0] = 1.0
362   -
363   - for z in prange(sz, nogil=True):
364   - for y in range(sy):
365   - for x in range(sx):
366   - vl = calc_fcm_itensity(vimage, x, y, z, n, dir)
367   - tmp[z, y, x] = <DTYPE16_t>vl
368   -
369   - cdef DTYPE16_t tmin = tmp.min()
370   - cdef DTYPE16_t tmax = tmp.max()
371   -
372   - #tmp = ((max - min)/<float>(tmax - tmin)) * (tmp - tmin) + min
373   -
374   - if tmip == 0:
375   - out[:] = tmp.max(axis)
376   - elif tmip == 1:
377   - lmip(tmp, axis, 700, 3033, out)
378   - elif tmip == 2:
379   - mida(tmp, axis, wl, ww, out)
invesalius/data/slice_.py
  Diff comments   View file @18c2bcd
... ... @@ -28,13 +28,13 @@ from wx.lib.pubsub import pub as Publisher
28 28 import invesalius.constants as const
29 29 import invesalius.data.converters as converters
30 30 import invesalius.data.imagedata_utils as iu
31   -import invesalius.data.transformations as transformations
32 31 import invesalius.session as ses
33 32 import invesalius.style as st
34 33 import invesalius.utils as utils
35   -from invesalius.data import mips, transforms
  34 +from invesalius.data import transformations
36 35 from invesalius.data.mask import Mask
37 36 from invesalius.project import Project
  37 +from invesalius_cy import mips, transforms
38 38  
39 39 OTHER = 0
40 40 PLIST = 1
... ...
invesalius/data/styles.py
  Diff comments   View file @18c2bcd
... ... @@ -46,7 +46,7 @@ import invesalius.utils as utils
46 46 from invesalius.data.measures import (CircleDensityMeasure, MeasureData,
47 47 PolygonDensityMeasure)
48 48  
49   -from . import floodfill
  49 +from invesalius_cy import floodfill
50 50  
51 51 ORIENTATIONS = {
52 52 "AXIAL": const.AXIAL,
... ...
invesalius/data/surface.py
  Diff comments   View file @18c2bcd
... ... @@ -59,9 +59,9 @@ import invesalius.utils as utl
59 59 import invesalius.data.vtk_utils as vu
60 60  
61 61 from invesalius.gui import dialogs
  62 +from invesalius_cy import cy_mesh
62 63  
63   -from invesalius.data import cy_mesh
64   -# TODO: Verificar ReleaseDataFlagOn and SetSource
  64 +# TODO: Verificar ReleaseDataFlagOn and SetSource
65 65  
66 66  
67 67 class Surface():
... ...
invesalius/data/surface_process.py
  Diff comments   View file @18c2bcd
... ... @@ -13,7 +13,7 @@ import vtk
13 13  
14 14 import invesalius.i18n as i18n
15 15 import invesalius.data.converters as converters
16   -from invesalius.data import cy_mesh
  16 +from invesalius_cy import cy_mesh
17 17  
18 18 import weakref
19 19 from scipy import ndimage
... ...
invesalius/data/transforms.pyx
View file @73ddbb0
... ... @@ -1,174 +0,0 @@
1   -import numpy as np
2   -cimport numpy as np
3   -cimport cython
4   -
5   -from .cy_my_types cimport image_t
6   -from .interpolation cimport interpolate, tricub_interpolate, tricubicInterpolate, lanczos3, nearest_neighbour_interp
7   -
8   -from libc.math cimport floor, ceil, sqrt, fabs, round
9   -from cython.parallel import prange
10   -
11   -ctypedef double (*interp_function)(image_t[:, :, :], double, double, double) nogil
12   -
13   -@cython.boundscheck(False) # turn of bounds-checking for entire function
14   -@cython.cdivision(True)
15   -@cython.wraparound(False)
16   -cdef void mul_mat4_vec4(double[:, :] M,
17   - double* coord,
18   - double* out) nogil:
19   -
20   - out[0] = coord[0] * M[0, 0] + coord[1] * M[0, 1] + coord[2] * M[0, 2] + coord[3] * M[0, 3]
21   - out[1] = coord[0] * M[1, 0] + coord[1] * M[1, 1] + coord[2] * M[1, 2] + coord[3] * M[1, 3]
22   - out[2] = coord[0] * M[2, 0] + coord[1] * M[2, 1] + coord[2] * M[2, 2] + coord[3] * M[2, 3]
23   - out[3] = coord[0] * M[3, 0] + coord[1] * M[3, 1] + coord[2] * M[3, 2] + coord[3] * M[3, 3]
24   -
25   -
26   -@cython.boundscheck(False) # turn of bounds-checking for entire function
27   -@cython.cdivision(True)
28   -@cython.wraparound(False)
29   -cdef image_t coord_transform(image_t[:, :, :] volume, double[:, :] M, int x, int y, int z, double sx, double sy, double sz, interp_function f_interp, image_t cval) nogil:
30   -
31   - cdef double coord[4]
32   - coord[0] = z*sz
33   - coord[1] = y*sy
34   - coord[2] = x*sx
35   - coord[3] = 1.0
36   -
37   - cdef double _ncoord[4]
38   - _ncoord[3] = 1
39   - # _ncoord[:] = [0.0, 0.0, 0.0, 1.0]
40   -
41   - cdef unsigned int dz, dy, dx
42   - dz = volume.shape[0]
43   - dy = volume.shape[1]
44   - dx = volume.shape[2]
45   -
46   -
47   - mul_mat4_vec4(M, coord, _ncoord)
48   -
49   - cdef double nz, ny, nx
50   - nz = (_ncoord[0]/_ncoord[3])/sz
51   - ny = (_ncoord[1]/_ncoord[3])/sy
52   - nx = (_ncoord[2]/_ncoord[3])/sx
53   -
54   - cdef double v
55   -
56   - if 0 <= nz <= (dz-1) and 0 <= ny <= (dy-1) and 0 <= nx <= (dx-1):
57   - return <image_t>f_interp(volume, nx, ny, nz)
58   - # if minterpol == 0:
59   - # return <image_t>nearest_neighbour_interp(volume, nx, ny, nz)
60   - # elif minterpol == 1:
61   - # return <image_t>interpolate(volume, nx, ny, nz)
62   - # elif minterpol == 2:
63   - # v = tricubicInterpolate(volume, nx, ny, nz)
64   - # if (v < cval):
65   - # v = cval
66   - # return <image_t>v
67   - # else:
68   - # v = lanczos3(volume, nx, ny, nz)
69   - # if (v < cval):
70   - # v = cval
71   - # return <image_t>v
72   - else:
73   - return cval
74   -
75   -
76   -@cython.boundscheck(False) # turn of bounds-checking for entire function
77   -@cython.cdivision(True)
78   -@cython.wraparound(False)
79   -def apply_view_matrix_transform(image_t[:, :, :] volume,
80   - spacing,
81   - double[:, :] M,
82   - unsigned int n, str orientation,
83   - int minterpol,
84   - image_t cval,
85   - image_t[:, :, :] out):
86   -
87   - cdef int dz, dy, dx
88   - cdef int z, y, x
89   - dz = volume.shape[0]
90   - dy = volume.shape[1]
91   - dx = volume.shape[2]
92   -
93   - cdef unsigned int odz, ody, odx
94   - odz = out.shape[0]
95   - ody = out.shape[1]
96   - odx = out.shape[2]
97   -
98   - cdef unsigned int count = 0
99   -
100   - cdef double sx, sy, sz
101   - sx = spacing[0]
102   - sy = spacing[1]
103   - sz = spacing[2]
104   -
105   - cdef interp_function f_interp
106   -
107   - if minterpol == 0:
108   - f_interp = nearest_neighbour_interp
109   - elif minterpol == 1:
110   - f_interp = interpolate
111   - elif minterpol == 2:
112   - f_interp = tricubicInterpolate
113   - else:
114   - f_interp = lanczos3
115   -
116   - if orientation == 'AXIAL':
117   - for z in xrange(n, n+odz):
118   - for y in prange(dy, nogil=True):
119   - for x in xrange(dx):
120   - out[count, y, x] = coord_transform(volume, M, x, y, z, sx, sy, sz, f_interp, cval)
121   - count += 1
122   -
123   - elif orientation == 'CORONAL':
124   - for y in xrange(n, n+ody):
125   - for z in prange(dz, nogil=True):
126   - for x in xrange(dx):
127   - out[z, count, x] = coord_transform(volume, M, x, y, z, sx, sy, sz, f_interp, cval)
128   - count += 1
129   -
130   - elif orientation == 'SAGITAL':
131   - for x in xrange(n, n+odx):
132   - for z in prange(dz, nogil=True):
133   - for y in xrange(dy):
134   - out[z, y, count] = coord_transform(volume, M, x, y, z, sx, sy, sz, f_interp, cval)
135   - count += 1
136   -
137   -
138   -@cython.boundscheck(False) # turn of bounds-checking for entire function
139   -@cython.cdivision(True)
140   -@cython.wraparound(False)
141   -def convolve_non_zero(image_t[:, :, :] volume,
142   - image_t[:, :, :] kernel,
143   - image_t cval):
144   - cdef Py_ssize_t x, y, z, sx, sy, sz, kx, ky, kz, skx, sky, skz, i, j, k
145   - cdef image_t v
146   -
147   - cdef image_t[:, :, :] out = np.zeros_like(volume)
148   -
149   - sz = volume.shape[0]
150   - sy = volume.shape[1]
151   - sx = volume.shape[2]
152   -
153   - skz = kernel.shape[0]
154   - sky = kernel.shape[1]
155   - skx = kernel.shape[2]
156   -
157   - for z in prange(sz, nogil=True):
158   - for y in xrange(sy):
159   - for x in xrange(sx):
160   - if volume[z, y, x] != 0:
161   - for k in xrange(skz):
162   - kz = z - skz // 2 + k
163   - for j in xrange(sky):
164   - ky = y - sky // 2 + j
165   - for i in xrange(skx):
166   - kx = x - skx // 2 + i
167   -
168   - if 0 <= kz < sz and 0 <= ky < sy and 0 <= kx < sx:
169   - v = volume[kz, ky, kx]
170   - else:
171   - v = cval
172   -
173   - out[z, y, x] += (v * kernel[k, j, i])
174   - return np.asarray(out)
invesalius_cy/cy_mesh.pyx 0 → 100644
  Diff comments   View file @18c2bcd
... ... @@ -0,0 +1,466 @@
  1 +# distutils: language = c++
  2 +#cython: boundscheck=False
  3 +#cython: wraparound=False
  4 +#cython: initializedcheck=False
  5 +#cython: cdivision=True
  6 +#cython: nonecheck=False
  7 +
  8 +import sys
  9 +import time
  10 +cimport numpy as np
  11 +
  12 +from libc.math cimport sin, cos, acos, exp, sqrt, fabs, M_PI
  13 +from libc.stdlib cimport abs as cabs
  14 +from cython.operator cimport dereference as deref, preincrement as inc
  15 +from libcpp.map cimport map
  16 +from libcpp.unordered_map cimport unordered_map
  17 +from libcpp.set cimport set
  18 +from libcpp.vector cimport vector
  19 +from libcpp.pair cimport pair
  20 +from libcpp cimport bool
  21 +from libcpp.deque cimport deque as cdeque
  22 +from cython.parallel import prange
  23 +
  24 +from cy_my_types cimport vertex_t, normal_t, vertex_id_t
  25 +
  26 +import numpy as np
  27 +import vtk
  28 +
  29 +from vtk.util import numpy_support
  30 +
  31 +ctypedef float weight_t
  32 +
  33 +cdef struct Point:
  34 + vertex_t x
  35 + vertex_t y
  36 + vertex_t z
  37 +
  38 +ctypedef pair[vertex_id_t, vertex_id_t] key
  39 +
  40 +
  41 +cdef class Mesh:
  42 + cdef vertex_t[:, :] vertices
  43 + cdef vertex_id_t[:, :] faces
  44 + cdef normal_t[:, :] normals
  45 +
  46 + cdef unordered_map[int, vector[vertex_id_t]] map_vface
  47 + cdef unordered_map[vertex_id_t, int] border_vertices
  48 +
  49 + cdef bool _initialized
  50 +
  51 + def __cinit__(self, pd=None, other=None):
  52 + cdef int i
  53 + cdef map[key, int] edge_nfaces
  54 + cdef map[key, int].iterator it
  55 + if pd:
  56 + self._initialized = True
  57 + _vertices = numpy_support.vtk_to_numpy(pd.GetPoints().GetData())
  58 + _vertices.shape = -1, 3
  59 +
  60 + _faces = numpy_support.vtk_to_numpy(pd.GetPolys().GetData())
  61 + _faces.shape = -1, 4
  62 +
  63 + _normals = numpy_support.vtk_to_numpy(pd.GetCellData().GetArray("Normals"))
  64 + _normals.shape = -1, 3
  65 +
  66 + self.vertices = _vertices
  67 + self.faces = _faces
  68 + self.normals = _normals
  69 +
  70 + for i in xrange(_faces.shape[0]):
  71 + self.map_vface[self.faces[i, 1]].push_back(i)
  72 + self.map_vface[self.faces[i, 2]].push_back(i)
  73 + self.map_vface[self.faces[i, 3]].push_back(i)
  74 +
  75 + edge_nfaces[key(min(self.faces[i, 1], self.faces[i, 2]), max(self.faces[i, 1], self.faces[i, 2]))] += 1
  76 + edge_nfaces[key(min(self.faces[i, 2], self.faces[i, 3]), max(self.faces[i, 2], self.faces[i, 3]))] += 1
  77 + edge_nfaces[key(min(self.faces[i, 1], self.faces[i, 3]), max(self.faces[i, 1], self.faces[i, 3]))] += 1
  78 +
  79 + it = edge_nfaces.begin()
  80 +
  81 + while it != edge_nfaces.end():
  82 + if deref(it).second == 1:
  83 + self.border_vertices[deref(it).first.first] = 1
  84 + self.border_vertices[deref(it).first.second] = 1
  85 +
  86 + inc(it)
  87 +
  88 + elif other:
  89 + _other = <Mesh>other
  90 + self._initialized = True
  91 + self.vertices = _other.vertices.copy()
  92 + self.faces = _other.faces.copy()
  93 + self.normals = _other.normals.copy()
  94 + self.map_vface = unordered_map[int, vector[vertex_id_t]](_other.map_vface)
  95 + self.border_vertices = unordered_map[vertex_id_t, int](_other.border_vertices)
  96 + else:
  97 + self._initialized = False
  98 +
  99 + cdef void copy_to(self, Mesh other):
  100 + """
  101 + Copies self content to other.
  102 + """
  103 + if self._initialized:
  104 + other.vertices[:] = self.vertices
  105 + other.faces[:] = self.faces
  106 + other.normals[:] = self.normals
  107 + other.map_vface = unordered_map[int, vector[vertex_id_t]](self.map_vface)
  108 + other.border_vertices = unordered_map[vertex_id_t, int](self.border_vertices)
  109 + else:
  110 + other.vertices = self.vertices.copy()
  111 + other.faces = self.faces.copy()
  112 + other.normals = self.normals.copy()
  113 +
  114 + other.map_vface = self.map_vface
  115 + other.border_vertices = self.border_vertices
  116 +
  117 + def to_vtk(self):
  118 + """
  119 + Converts Mesh to vtkPolyData.
  120 + """
  121 + vertices = np.asarray(self.vertices)
  122 + faces = np.asarray(self.faces)
  123 + normals = np.asarray(self.normals)
  124 +
  125 + points = vtk.vtkPoints()
  126 + points.SetData(numpy_support.numpy_to_vtk(vertices))
  127 +
  128 + id_triangles = numpy_support.numpy_to_vtkIdTypeArray(faces)
  129 + triangles = vtk.vtkCellArray()
  130 + triangles.SetCells(faces.shape[0], id_triangles)
  131 +
  132 + pd = vtk.vtkPolyData()
  133 + pd.SetPoints(points)
  134 + pd.SetPolys(triangles)
  135 +
  136 + return pd
  137 +
  138 + cdef vector[vertex_id_t]* get_faces_by_vertex(self, int v_id) nogil:
  139 + """
  140 + Returns the faces whose vertex `v_id' is part.
  141 + """
  142 + return &self.map_vface[v_id]
  143 +
  144 + cdef set[vertex_id_t]* get_ring1(self, vertex_id_t v_id) nogil:
  145 + """
  146 + Returns the ring1 of vertex `v_id'
  147 + """
  148 + cdef vertex_id_t f_id
  149 + cdef set[vertex_id_t]* ring1 = new set[vertex_id_t]()
  150 + cdef vector[vertex_id_t].iterator it = self.map_vface[v_id].begin()
  151 +
  152 + while it != self.map_vface[v_id].end():
  153 + f_id = deref(it)
  154 + inc(it)
  155 + if self.faces[f_id, 1] != v_id:
  156 + ring1.insert(self.faces[f_id, 1])
  157 + if self.faces[f_id, 2] != v_id:
  158 + ring1.insert(self.faces[f_id, 2])
  159 + if self.faces[f_id, 3] != v_id:
  160 + ring1.insert(self.faces[f_id, 3])
  161 +
  162 + return ring1
  163 +
  164 + cdef bool is_border(self, vertex_id_t v_id) nogil:
  165 + """
  166 + Check if vertex `v_id' is a vertex border.
  167 + """
  168 + return self.border_vertices.find(v_id) != self.border_vertices.end()
  169 +
  170 + cdef vector[vertex_id_t]* get_near_vertices_to_v(self, vertex_id_t v_id, float dmax) nogil:
  171 + """
  172 + Returns all vertices with distance at most `d' to the vertex `v_id'
  173 +
  174 + Params:
  175 + v_id: id of the vertex
  176 + dmax: the maximum distance.
  177 + """
  178 + cdef vector[vertex_id_t]* idfaces
  179 + cdef vector[vertex_id_t]* near_vertices = new vector[vertex_id_t]()
  180 +
  181 + cdef cdeque[vertex_id_t] to_visit
  182 + cdef unordered_map[vertex_id_t, bool] status_v
  183 + cdef unordered_map[vertex_id_t, bool] status_f
  184 +
  185 + cdef vertex_t *vip
  186 + cdef vertex_t *vjp
  187 +
  188 + cdef float distance
  189 + cdef int nf, nid, j
  190 + cdef vertex_id_t f_id, vj
  191 +
  192 + vip = &self.vertices[v_id, 0]
  193 + to_visit.push_back(v_id)
  194 + while(not to_visit.empty()):
  195 + v_id = to_visit.front()
  196 + to_visit.pop_front()
  197 +
  198 + status_v[v_id] = True
  199 +
  200 + idfaces = self.get_faces_by_vertex(v_id)
  201 + nf = idfaces.size()
  202 +
  203 + for nid in xrange(nf):
  204 + f_id = deref(idfaces)[nid]
  205 + if status_f.find(f_id) == status_f.end():
  206 + status_f[f_id] = True
  207 +
  208 + for j in xrange(3):
  209 + vj = self.faces[f_id, j+1]
  210 + if status_v.find(vj) == status_v.end():
  211 + status_v[vj] = True
  212 + vjp = &self.vertices[vj, 0]
  213 + distance = sqrt((vip[0] - vjp[0]) * (vip[0] - vjp[0]) \
  214 + + (vip[1] - vjp[1]) * (vip[1] - vjp[1]) \
  215 + + (vip[2] - vjp[2]) * (vip[2] - vjp[2]))
  216 + if distance <= dmax:
  217 + near_vertices.push_back(vj)
  218 + to_visit.push_back(vj)
  219 +
  220 + return near_vertices
  221 +
  222 +
  223 +cdef vector[weight_t]* calc_artifacts_weight(Mesh mesh, vector[vertex_id_t]& vertices_staircase, float tmax, float bmin) nogil:
  224 + """
  225 + Calculate the artifact weight based on distance of each vertex to its
  226 + nearest staircase artifact vertex.
  227 +
  228 + Params:
  229 + mesh: Mesh
  230 + vertices_staircase: the identified staircase artifact vertices
  231 + tmax: max distance the vertex must be to its nearest artifact vertex
  232 + to considered to calculate the weight
  233 + bmin: The minimum weight.
  234 + """
  235 + cdef int vi_id, vj_id, nnv, n_ids, i, j
  236 + cdef vector[vertex_id_t]* near_vertices
  237 + cdef weight_t value
  238 + cdef float d
  239 + n_ids = vertices_staircase.size()
  240 +
  241 + cdef vertex_t* vi
  242 + cdef vertex_t* vj
  243 + cdef size_t msize
  244 +
  245 + msize = mesh.vertices.shape[0]
  246 + cdef vector[weight_t]* weights = new vector[weight_t](msize)
  247 + weights.assign(msize, bmin)
  248 +
  249 + for i in prange(n_ids, nogil=True):
  250 + vi_id = vertices_staircase[i]
  251 + deref(weights)[vi_id] = 1.0
  252 +
  253 + vi = &mesh.vertices[vi_id, 0]
  254 + near_vertices = mesh.get_near_vertices_to_v(vi_id, tmax)
  255 + nnv = near_vertices.size()
  256 +
  257 + for j in xrange(nnv):
  258 + vj_id = deref(near_vertices)[j]
  259 + vj = &mesh.vertices[vj_id, 0]
  260 +
  261 + d = sqrt((vi[0] - vj[0]) * (vi[0] - vj[0])\
  262 + + (vi[1] - vj[1]) * (vi[1] - vj[1])\
  263 + + (vi[2] - vj[2]) * (vi[2] - vj[2]))
  264 + value = (1.0 - d/tmax) * (1.0 - bmin) + bmin
  265 +
  266 + if value > deref(weights)[vj_id]:
  267 + deref(weights)[vj_id] = value
  268 +
  269 + del near_vertices
  270 +
  271 + # for i in xrange(msize):
  272 + # if mesh.is_border(i):
  273 + # deref(weights)[i] = 0.0
  274 +
  275 + # cdef vertex_id_t v0, v1, v2
  276 + # for i in xrange(mesh.faces.shape[0]):
  277 + # for j in xrange(1, 4):
  278 + # v0 = mesh.faces[i, j]
  279 + # vi = &mesh.vertices[v0, 0]
  280 + # if mesh.is_border(v0):
  281 + # deref(weights)[v0] = 0.0
  282 + # v1 = mesh.faces[i, (j + 1) % 3 + 1]
  283 + # if mesh.is_border(v1):
  284 + # vi = &mesh.vertices[v1, 0]
  285 + # deref(weights)[v0] = 0.0
  286 +
  287 + return weights
  288 +
  289 +
  290 +cdef inline Point calc_d(Mesh mesh, vertex_id_t v_id) nogil:
  291 + cdef Point D
  292 + cdef int nf, f_id, nid
  293 + cdef float n=0
  294 + cdef int i
  295 + cdef vertex_t* vi
  296 + cdef vertex_t* vj
  297 + cdef set[vertex_id_t]* vertices
  298 + cdef set[vertex_id_t].iterator it
  299 + cdef vertex_id_t vj_id
  300 +
  301 + D.x = 0.0
  302 + D.y = 0.0
  303 + D.z = 0.0
  304 +
  305 + vertices = mesh.get_ring1(v_id)
  306 + vi = &mesh.vertices[v_id, 0]
  307 +
  308 + if mesh.is_border(v_id):
  309 + it = vertices.begin()
  310 + while it != vertices.end():
  311 + vj_id = deref(it)
  312 + if mesh.is_border(vj_id):
  313 + vj = &mesh.vertices[vj_id, 0]
  314 +
  315 + D.x = D.x + (vi[0] - vj[0])
  316 + D.y = D.y + (vi[1] - vj[1])
  317 + D.z = D.z + (vi[2] - vj[2])
  318 + n += 1.0
  319 +
  320 + inc(it)
  321 + else:
  322 + it = vertices.begin()
  323 + while it != vertices.end():
  324 + vj_id = deref(it)
  325 + vj = &mesh.vertices[vj_id, 0]
  326 +
  327 + D.x = D.x + (vi[0] - vj[0])
  328 + D.y = D.y + (vi[1] - vj[1])
  329 + D.z = D.z + (vi[2] - vj[2])
  330 + n += 1.0
  331 +
  332 + inc(it)
  333 +
  334 + del vertices
  335 +
  336 + D.x = D.x / n
  337 + D.y = D.y / n
  338 + D.z = D.z / n
  339 + return D
  340 +
  341 +cdef vector[vertex_id_t]* find_staircase_artifacts(Mesh mesh, double[3] stack_orientation, double T) nogil:
  342 + """
  343 + This function is used to find vertices at staircase artifacts, which are
  344 + those vertices whose incident faces' orientation differences are
  345 + greater than T.
  346 +
  347 + Params:
  348 + mesh: Mesh
  349 + stack_orientation: orientation of slice stacking
  350 + T: Min angle (between vertex faces and stack_orientation) to consider a
  351 + vertex a staircase artifact.
  352 + """
  353 + cdef int nv, nf, f_id, v_id
  354 + cdef double of_z, of_y, of_x, min_z, max_z, min_y, max_y, min_x, max_x;
  355 + cdef vector[vertex_id_t]* f_ids
  356 + cdef normal_t* normal
  357 +
  358 + cdef vector[vertex_id_t]* output = new vector[vertex_id_t]()
  359 + cdef int i
  360 +
  361 + nv = mesh.vertices.shape[0]
  362 +
  363 + for v_id in xrange(nv):
  364 + max_z = -10000
  365 + min_z = 10000
  366 + max_y = -10000
  367 + min_y = 10000
  368 + max_x = -10000
  369 + min_x = 10000
  370 +
  371 + f_ids = mesh.get_faces_by_vertex(v_id)
  372 + nf = deref(f_ids).size()
  373 +
  374 + for i in xrange(nf):
  375 + f_id = deref(f_ids)[i]
  376 + normal = &mesh.normals[f_id, 0]
  377 +
  378 + of_z = 1 - fabs(normal[0]*stack_orientation[0] + normal[1]*stack_orientation[1] + normal[2]*stack_orientation[2]);
  379 + of_y = 1 - fabs(normal[0]*0 + normal[1]*1 + normal[2]*0);
  380 + of_x = 1 - fabs(normal[0]*1 + normal[1]*0 + normal[2]*0);
  381 +
  382 + if (of_z > max_z):
  383 + max_z = of_z
  384 +
  385 + if (of_z < min_z):
  386 + min_z = of_z
  387 +
  388 + if (of_y > max_y):
  389 + max_y = of_y
  390 +
  391 + if (of_y < min_y):
  392 + min_y = of_y
  393 +
  394 + if (of_x > max_x):
  395 + max_x = of_x
  396 +
  397 + if (of_x < min_x):
  398 + min_x = of_x
  399 +
  400 +
  401 + if ((fabs(max_z - min_z) >= T) or (fabs(max_y - min_y) >= T) or (fabs(max_x - min_x) >= T)):
  402 + output.push_back(v_id)
  403 + break
  404 + return output
  405 +
  406 +
  407 +cdef void taubin_smooth(Mesh mesh, vector[weight_t]& weights, float l, float m, int steps):
  408 + """
  409 + Implementation of Taubin's smooth algorithm described in the paper "A
  410 + Signal Processing Approach To Fair Surface Design". His benefeat is it
  411 + avoids surface shrinking.
  412 + """
  413 + cdef int s, i, nvertices
  414 + nvertices = mesh.vertices.shape[0]
  415 + cdef vector[Point] D = vector[Point](nvertices)
  416 + cdef vertex_t* vi
  417 + for s in xrange(steps):
  418 + for i in prange(nvertices, nogil=True):
  419 + D[i] = calc_d(mesh, i)
  420 +
  421 + for i in prange(nvertices, nogil=True):
  422 + mesh.vertices[i, 0] += weights[i]*l*D[i].x;
  423 + mesh.vertices[i, 1] += weights[i]*l*D[i].y;
  424 + mesh.vertices[i, 2] += weights[i]*l*D[i].z;
  425 +
  426 + for i in prange(nvertices, nogil=True):
  427 + D[i] = calc_d(mesh, i)
  428 +
  429 + for i in prange(nvertices, nogil=True):
  430 + mesh.vertices[i, 0] += weights[i]*m*D[i].x;
  431 + mesh.vertices[i, 1] += weights[i]*m*D[i].y;
  432 + mesh.vertices[i, 2] += weights[i]*m*D[i].z;
  433 +
  434 +
  435 +def ca_smoothing(Mesh mesh, double T, double tmax, double bmin, int n_iters):
  436 + """
  437 + This is a implementation of the paper "Context-aware mesh smoothing for
  438 + biomedical applications". It can be used to smooth meshes generated by
  439 + binary images to remove its staircase artifacts and keep the fine features.
  440 +
  441 + Params:
  442 + mesh: Mesh
  443 + T: Min angle (between vertex faces and stack_orientation) to consider a
  444 + vertex a staircase artifact
  445 + tmax: max distance the vertex must be to its nearest artifact vertex
  446 + to considered to calculate the weight
  447 + bmin: The minimum weight
  448 + n_iters: Number of iterations.
  449 + """
  450 + cdef double[3] stack_orientation = [0.0, 0.0, 1.0]
  451 +
  452 + t0 = time.time()
  453 + cdef vector[vertex_id_t]* vertices_staircase = find_staircase_artifacts(mesh, stack_orientation, T)
  454 + print "vertices staircase", time.time() - t0
  455 +
  456 + t0 = time.time()
  457 + cdef vector[weight_t]* weights = calc_artifacts_weight(mesh, deref(vertices_staircase), tmax, bmin)
  458 + print "Weights", time.time() - t0
  459 +
  460 + del vertices_staircase
  461 +
  462 + t0 = time.time()
  463 + taubin_smooth(mesh, deref(weights), 0.5, -0.53, n_iters)
  464 + print "taubin", time.time() - t0
  465 +
  466 + del weights
... ...
invesalius_cy/cy_my_types.pxd 0 → 100644
  Diff comments   View file @18c2bcd
... ... @@ -0,0 +1,21 @@
  1 +import numpy as np
  2 +cimport numpy as np
  3 +cimport cython
  4 +
  5 +# ctypedef np.uint16_t image_t
  6 +
  7 +ctypedef fused image_t:
  8 + np.float64_t
  9 + np.int16_t
  10 + np.uint8_t
  11 +
  12 +ctypedef np.uint8_t mask_t
  13 +
  14 +ctypedef np.float32_t vertex_t
  15 +ctypedef np.float32_t normal_t
  16 +
  17 +# To compile in windows 64
  18 +IF UNAME_MACHINE == 'AMD64':
  19 + ctypedef np.int64_t vertex_id_t
  20 +ELSE:
  21 + ctypedef np.int_t vertex_id_t
... ...
invesalius_cy/floodfill.pyx 0 → 100644
  Diff comments   View file @18c2bcd
... ... @@ -0,0 +1,274 @@
  1 +import numpy as np
  2 +cimport numpy as np
  3 +cimport cython
  4 +
  5 +from collections import deque
  6 +
  7 +from cython.parallel import prange
  8 +from libc.math cimport floor, ceil
  9 +from libcpp cimport bool
  10 +from libcpp.deque cimport deque as cdeque
  11 +from libcpp.vector cimport vector
  12 +
  13 +from cy_my_types cimport image_t, mask_t
  14 +
  15 +cdef struct s_coord:
  16 + int x
  17 + int y
  18 + int z
  19 +
  20 +ctypedef s_coord coord
  21 +
  22 +
  23 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  24 +@cython.wraparound(False)
  25 +@cython.nonecheck(False)
  26 +@cython.cdivision(True)
  27 +cdef inline void append_queue(cdeque[int]& stack, int x, int y, int z, int d, int h, int w) nogil:
  28 + stack.push_back(z*h*w + y*w + x)
  29 +
  30 +
  31 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  32 +@cython.wraparound(False)
  33 +@cython.nonecheck(False)
  34 +@cython.cdivision(True)
  35 +cdef inline void pop_queue(cdeque[int]& stack, int* x, int* y, int* z, int d, int h, int w) nogil:
  36 + cdef int i = stack.front()
  37 + stack.pop_front()
  38 + x[0] = i % w
  39 + y[0] = (i / w) % h
  40 + z[0] = i / (h * w)
  41 +
  42 +
  43 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  44 +def floodfill(np.ndarray[image_t, ndim=3] data, int i, int j, int k, int v, int fill, np.ndarray[mask_t, ndim=3] out):
  45 +
  46 + cdef int to_return = 0
  47 + if out is None:
  48 + out = np.zeros_like(data)
  49 + to_return = 1
  50 +
  51 + cdef int x, y, z
  52 + cdef int w, h, d
  53 +
  54 + d = data.shape[0]
  55 + h = data.shape[1]
  56 + w = data.shape[2]
  57 +
  58 + stack = [(i, j, k), ]
  59 + out[k, j, i] = fill
  60 +
  61 + while stack:
  62 + x, y, z = stack.pop()
  63 +
  64 + if z + 1 < d and data[z + 1, y, x] == v and out[z + 1, y, x] != fill:
  65 + out[z + 1, y, x] = fill
  66 + stack.append((x, y, z + 1))
  67 +
  68 + if z - 1 >= 0 and data[z - 1, y, x] == v and out[z - 1, y, x] != fill:
  69 + out[z - 1, y, x] = fill
  70 + stack.append((x, y, z - 1))
  71 +
  72 + if y + 1 < h and data[z, y + 1, x] == v and out[z, y + 1, x] != fill:
  73 + out[z, y + 1, x] = fill
  74 + stack.append((x, y + 1, z))
  75 +
  76 + if y - 1 >= 0 and data[z, y - 1, x] == v and out[z, y - 1, x] != fill:
  77 + out[z, y - 1, x] = fill
  78 + stack.append((x, y - 1, z))
  79 +
  80 + if x + 1 < w and data[z, y, x + 1] == v and out[z, y, x + 1] != fill:
  81 + out[z, y, x + 1] = fill
  82 + stack.append((x + 1, y, z))
  83 +
  84 + if x - 1 >= 0 and data[z, y, x - 1] == v and out[z, y, x - 1] != fill:
  85 + out[z, y, x - 1] = fill
  86 + stack.append((x - 1, y, z))
  87 +
  88 + if to_return:
  89 + return out
  90 +
  91 +
  92 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  93 +@cython.wraparound(False)
  94 +@cython.nonecheck(False)
  95 +def floodfill_threshold(np.ndarray[image_t, ndim=3] data, list seeds, int t0, int t1, int fill, np.ndarray[mask_t, ndim=3] strct, np.ndarray[mask_t, ndim=3] out):
  96 +
  97 + cdef int to_return = 0
  98 + if out is None:
  99 + out = np.zeros_like(data)
  100 + to_return = 1
  101 +
  102 + cdef int x, y, z
  103 + cdef int dx, dy, dz
  104 + cdef int odx, ody, odz
  105 + cdef int xo, yo, zo
  106 + cdef int i, j, k
  107 + cdef int offset_x, offset_y, offset_z
  108 +
  109 + dz = data.shape[0]
  110 + dy = data.shape[1]
  111 + dx = data.shape[2]
  112 +
  113 + odz = strct.shape[0]
  114 + ody = strct.shape[1]
  115 + odx = strct.shape[2]
  116 +
  117 + cdef cdeque[coord] stack
  118 + cdef coord c
  119 +
  120 + offset_z = odz / 2
  121 + offset_y = ody / 2
  122 + offset_x = odx / 2
  123 +
  124 + for i, j, k in seeds:
  125 + if data[k, j, i] >= t0 and data[k, j, i] <= t1:
  126 + c.x = i
  127 + c.y = j
  128 + c.z = k
  129 + stack.push_back(c)
  130 + out[k, j, i] = fill
  131 +
  132 + with nogil:
  133 + while stack.size():
  134 + c = stack.back()
  135 + stack.pop_back()
  136 +
  137 + x = c.x
  138 + y = c.y
  139 + z = c.z
  140 +
  141 + out[z, y, x] = fill
  142 +
  143 + for k in xrange(odz):
  144 + zo = z + k - offset_z
  145 + for j in xrange(ody):
  146 + yo = y + j - offset_y
  147 + for i in xrange(odx):
  148 + if strct[k, j, i]:
  149 + xo = x + i - offset_x
  150 + if 0 <= xo < dx and 0 <= yo < dy and 0 <= zo < dz and out[zo, yo, xo] != fill and t0 <= data[zo, yo, xo] <= t1:
  151 + out[zo, yo, xo] = fill
  152 + c.x = xo
  153 + c.y = yo
  154 + c.z = zo
  155 + stack.push_back(c)
  156 +
  157 + if to_return:
  158 + return out
  159 +
  160 +
  161 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  162 +@cython.wraparound(False)
  163 +@cython.nonecheck(False)
  164 +def floodfill_auto_threshold(np.ndarray[image_t, ndim=3] data, list seeds, float p, int fill, np.ndarray[mask_t, ndim=3] out):
  165 +
  166 + cdef int to_return = 0
  167 + if out is None:
  168 + out = np.zeros_like(data)
  169 + to_return = 1
  170 +
  171 + cdef cdeque[int] stack
  172 + cdef int x, y, z
  173 + cdef int w, h, d
  174 + cdef int xo, yo, zo
  175 + cdef int t0, t1
  176 +
  177 + cdef int i, j, k
  178 +
  179 + d = data.shape[0]
  180 + h = data.shape[1]
  181 + w = data.shape[2]
  182 +
  183 +
  184 + # stack = deque()
  185 +
  186 + x = 0
  187 + y = 0
  188 + z = 0
  189 +
  190 +
  191 + for i, j, k in seeds:
  192 + append_queue(stack, i, j, k, d, h, w)
  193 + out[k, j, i] = fill
  194 + print i, j, k, d, h, w
  195 +
  196 + with nogil:
  197 + while stack.size():
  198 + pop_queue(stack, &x, &y, &z, d, h, w)
  199 +
  200 + # print x, y, z, d, h, w
  201 +
  202 + xo = x
  203 + yo = y
  204 + zo = z
  205 +
  206 + t0 = <int>ceil(data[z, y, x] * (1 - p))
  207 + t1 = <int>floor(data[z, y, x] * (1 + p))
  208 +
  209 + if z + 1 < d and data[z + 1, y, x] >= t0 and data[z + 1, y, x] <= t1 and out[zo + 1, yo, xo] != fill:
  210 + out[zo + 1, yo, xo] = fill
  211 + append_queue(stack, x, y, z+1, d, h, w)
  212 +
  213 + if z - 1 >= 0 and data[z - 1, y, x] >= t0 and data[z - 1, y, x] <= t1 and out[zo - 1, yo, xo] != fill:
  214 + out[zo - 1, yo, xo] = fill
  215 + append_queue(stack, x, y, z-1, d, h, w)
  216 +
  217 + if y + 1 < h and data[z, y + 1, x] >= t0 and data[z, y + 1, x] <= t1 and out[zo, yo + 1, xo] != fill:
  218 + out[zo, yo + 1, xo] = fill
  219 + append_queue(stack, x, y+1, z, d, h, w)
  220 +
  221 + if y - 1 >= 0 and data[z, y - 1, x] >= t0 and data[z, y - 1, x] <= t1 and out[zo, yo - 1, xo] != fill:
  222 + out[zo, yo - 1, xo] = fill
  223 + append_queue(stack, x, y-1, z, d, h, w)
  224 +
  225 + if x + 1 < w and data[z, y, x + 1] >= t0 and data[z, y, x + 1] <= t1 and out[zo, yo, xo + 1] != fill:
  226 + out[zo, yo, xo + 1] = fill
  227 + append_queue(stack, x+1, y, z, d, h, w)
  228 +
  229 + if x - 1 >= 0 and data[z, y, x - 1] >= t0 and data[z, y, x - 1] <= t1 and out[zo, yo, xo - 1] != fill:
  230 + out[zo, yo, xo - 1] = fill
  231 + append_queue(stack, x-1, y, z, d, h, w)
  232 +
  233 + if to_return:
  234 + return out
  235 +
  236 +
  237 +@cython.boundscheck(False)
  238 +@cython.wraparound(False)
  239 +@cython.nonecheck(False)
  240 +def fill_holes_automatically(np.ndarray[mask_t, ndim=3] mask, np.ndarray[np.uint16_t, ndim=3] labels, unsigned int nlabels, unsigned int max_size):
  241 + """
  242 + Fill mask holes automatically. The hole must <= max_size. Return True if any hole were filled.
  243 + """
  244 + cdef np.ndarray[np.uint32_t, ndim=1] sizes = np.zeros(shape=(nlabels + 1), dtype=np.uint32)
  245 + cdef int x, y, z
  246 + cdef int dx, dy, dz
  247 + cdef int i
  248 +
  249 + cdef bool modified = False
  250 +
  251 + dz = mask.shape[0]
  252 + dy = mask.shape[1]
  253 + dx = mask.shape[2]
  254 +
  255 + for z in xrange(dz):
  256 + for y in xrange(dy):
  257 + for x in xrange(dx):
  258 + sizes[labels[z, y, x]] += 1
  259 +
  260 + #Checking if any hole will be filled
  261 + for i in xrange(nlabels + 1):
  262 + if sizes[i] <= max_size:
  263 + modified = True
  264 +
  265 + if not modified:
  266 + return 0
  267 +
  268 + for z in prange(dz, nogil=True):
  269 + for y in xrange(dy):
  270 + for x in xrange(dx):
  271 + if sizes[labels[z, y, x]] <= max_size:
  272 + mask[z, y, x] = 254
  273 +
  274 + return modified
... ...
invesalius_cy/interpolation.pxd 0 → 100644
  Diff comments   View file @18c2bcd
... ... @@ -0,0 +1,8 @@
  1 +from .cy_my_types cimport image_t
  2 +
  3 +cdef double interpolate(image_t[:, :, :], double, double, double) nogil
  4 +cdef double tricub_interpolate(image_t[:, :, :], double, double, double) nogil
  5 +cdef double tricubicInterpolate (image_t[:, :, :], double, double, double) nogil
  6 +cdef double lanczos3 (image_t[:, :, :], double, double, double) nogil
  7 +
  8 +cdef double nearest_neighbour_interp(image_t[:, :, :], double, double, double) nogil
... ...
invesalius_cy/interpolation.pyx 0 → 100644
  Diff comments   View file @18c2bcd
... ... @@ -0,0 +1,392 @@
  1 +# from interpolation cimport interpolate
  2 +
  3 +import numpy as np
  4 +cimport numpy as np
  5 +cimport cython
  6 +
  7 +from libc.math cimport floor, ceil, sqrt, fabs, sin, M_PI
  8 +from cython.parallel import prange
  9 +
  10 +DEF LANCZOS_A = 4
  11 +DEF SIZE_LANCZOS_TMP = LANCZOS_A * 2 - 1
  12 +
  13 +cdef double[64][64] temp = [
  14 + [ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  15 + [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  16 + [-3, 3, 0, 0, 0, 0, 0, 0,-2,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  17 + [ 2, -2, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  18 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  19 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  20 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  21 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  22 + [-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  23 + [ 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  24 + [ 9, -9,-9, 9, 0, 0, 0, 0, 6, 3,-6,-3, 0, 0, 0, 0, 6,-6, 3,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 2, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  25 + [-6, 6, 6,-6, 0, 0, 0, 0,-3,-3, 3, 3, 0, 0, 0, 0,-4, 4,-2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-2,-1,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  26 + [ 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  27 + [ 0, 0, 0, 0, 0, 0, 0, 0, 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  28 + [-6, 6, 6,-6, 0, 0, 0, 0,-4,-2, 4, 2, 0, 0, 0, 0,-3, 3,-3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-1,-2,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  29 + [ 4, -4,-4, 4, 0, 0, 0, 0, 2, 2,-2,-2, 0, 0, 0, 0, 2,-2, 2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  30 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  31 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  32 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  33 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  34 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  35 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
  36 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 3, 0, 0, 0, 0, 0, 0,-2,-1, 0, 0, 0, 0, 0, 0],
  37 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0],
  38 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  39 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0, 0, 0, 0, 0],
  40 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9,-9,-9, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 3,-6,-3, 0, 0, 0, 0, 6,-6, 3,-3, 0, 0, 0, 0, 4, 2, 2, 1, 0, 0, 0, 0],
  41 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-6, 6, 6,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3,-3, 3, 3, 0, 0, 0, 0,-4, 4,-2, 2, 0, 0, 0, 0,-2,-2,-1,-1, 0, 0, 0, 0],
  42 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  43 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0],
  44 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-6, 6, 6,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4,-2, 4, 2, 0, 0, 0, 0,-3, 3,-3, 3, 0, 0, 0, 0,-2,-1,-2,-1, 0, 0, 0, 0],
  45 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4,-4,-4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2,-2,-2, 0, 0, 0, 0, 2,-2, 2,-2, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0],
  46 + [-3, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0, 0, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  47 + [ 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0, 0, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  48 + [ 9, -9, 0, 0,-9, 9, 0, 0, 6, 3, 0, 0,-6,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6,-6, 0, 0, 3,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 2, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  49 + [-6, 6, 0, 0, 6,-6, 0, 0,-3,-3, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4, 4, 0, 0,-2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-2, 0, 0,-1,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  50 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0, 0, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  51 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0, 0, 0,-1, 0, 0, 0],
  52 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9,-9, 0, 0,-9, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 3, 0, 0,-6,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6,-6, 0, 0, 3,-3, 0, 0, 4, 2, 0, 0, 2, 1, 0, 0],
  53 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-6, 6, 0, 0, 6,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3,-3, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4, 4, 0, 0,-2, 2, 0, 0,-2,-2, 0, 0,-1,-1, 0, 0],
  54 + [ 9, 0,-9, 0,-9, 0, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 3, 0,-6, 0,-3, 0, 6, 0,-6, 0, 3, 0,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 2, 0, 2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  55 + [ 0, 0, 0, 0, 0, 0, 0, 0, 9, 0,-9, 0,-9, 0, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 3, 0,-6, 0,-3, 0, 6, 0,-6, 0, 3, 0,-3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 2, 0, 2, 0, 1, 0],
  56 + [-27, 27,27,-27,27,-27,-27,27,-18,-9,18, 9,18, 9,-18,-9,-18,18,-9, 9,18,-18, 9,-9,-18,18,18,-18,-9, 9, 9,-9,-12,-6,-6,-3,12, 6, 6, 3,-12,-6,12, 6,-6,-3, 6, 3,-12,12,-6, 6,-6, 6,-3, 3,-8,-4,-4,-2,-4,-2,-2,-1],
  57 + [18, -18,-18,18,-18,18,18,-18, 9, 9,-9,-9,-9,-9, 9, 9,12,-12, 6,-6,-12,12,-6, 6,12,-12,-12,12, 6,-6,-6, 6, 6, 6, 3, 3,-6,-6,-3,-3, 6, 6,-6,-6, 3, 3,-3,-3, 8,-8, 4,-4, 4,-4, 2,-2, 4, 4, 2, 2, 2, 2, 1, 1],
  58 + [-6, 0, 6, 0, 6, 0,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0,-3, 0, 3, 0, 3, 0,-4, 0, 4, 0,-2, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-2, 0,-1, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  59 + [ 0, 0, 0, 0, 0, 0, 0, 0,-6, 0, 6, 0, 6, 0,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 0,-3, 0, 3, 0, 3, 0,-4, 0, 4, 0,-2, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-2, 0,-1, 0,-1, 0],
  60 + [18, -18,-18,18,-18,18,18,-18,12, 6,-12,-6,-12,-6,12, 6, 9,-9, 9,-9,-9, 9,-9, 9,12,-12,-12,12, 6,-6,-6, 6, 6, 3, 6, 3,-6,-3,-6,-3, 8, 4,-8,-4, 4, 2,-4,-2, 6,-6, 6,-6, 3,-3, 3,-3, 4, 2, 4, 2, 2, 1, 2, 1],
  61 + [-12, 12,12,-12,12,-12,-12,12,-6,-6, 6, 6, 6, 6,-6,-6,-6, 6,-6, 6, 6,-6, 6,-6,-8, 8, 8,-8,-4, 4, 4,-4,-3,-3,-3,-3, 3, 3, 3, 3,-4,-4, 4, 4,-2,-2, 2, 2,-4, 4,-4, 4,-2, 2,-2, 2,-2,-2,-2,-2,-1,-1,-1,-1],
  62 + [ 2, 0, 0, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  63 + [ 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  64 + [-6, 6, 0, 0, 6,-6, 0, 0,-4,-2, 0, 0, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 3, 0, 0,-3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2,-1, 0, 0,-2,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  65 + [ 4, -4, 0, 0,-4, 4, 0, 0, 2, 2, 0, 0,-2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0, 2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  66 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  67 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0],
  68 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-6, 6, 0, 0, 6,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4,-2, 0, 0, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-3, 3, 0, 0,-3, 3, 0, 0,-2,-1, 0, 0,-2,-1, 0, 0],
  69 + [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4,-4, 0, 0,-4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 0, 0,-2,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0, 2,-2, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0],
  70 + [-6, 0, 6, 0, 6, 0,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4, 0,-2, 0, 4, 0, 2, 0,-3, 0, 3, 0,-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0,-2, 0,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  71 + [ 0, 0, 0, 0, 0, 0, 0, 0,-6, 0, 6, 0, 6, 0,-6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-4, 0,-2, 0, 4, 0, 2, 0,-3, 0, 3, 0,-3, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0,-2, 0,-1, 0,-2, 0,-1, 0],
  72 + [18, -18,-18,18,-18,18,18,-18,12, 6,-12,-6,-12,-6,12, 6,12,-12, 6,-6,-12,12,-6, 6, 9,-9,-9, 9, 9,-9,-9, 9, 8, 4, 4, 2,-8,-4,-4,-2, 6, 3,-6,-3, 6, 3,-6,-3, 6,-6, 3,-3, 6,-6, 3,-3, 4, 2, 2, 1, 4, 2, 2, 1],
  73 + [-12, 12,12,-12,12,-12,-12,12,-6,-6, 6, 6, 6, 6,-6,-6,-8, 8,-4, 4, 8,-8, 4,-4,-6, 6, 6,-6,-6, 6, 6,-6,-4,-4,-2,-2, 4, 4, 2, 2,-3,-3, 3, 3,-3,-3, 3, 3,-4, 4,-2, 2,-4, 4,-2, 2,-2,-2,-1,-1,-2,-2,-1,-1],
  74 + [ 4, 0,-4, 0,-4, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 2, 0,-2, 0,-2, 0, 2, 0,-2, 0, 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
  75 + [ 0, 0, 0, 0, 0, 0, 0, 0, 4, 0,-4, 0,-4, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 2, 0,-2, 0,-2, 0, 2, 0,-2, 0, 2, 0,-2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0],
  76 + [-12, 12,12,-12,12,-12,-12,12,-8,-4, 8, 4, 8, 4,-8,-4,-6, 6,-6, 6, 6,-6, 6,-6,-6, 6, 6,-6,-6, 6, 6,-6,-4,-2,-4,-2, 4, 2, 4, 2,-4,-2, 4, 2,-4,-2, 4, 2,-3, 3,-3, 3,-3, 3,-3, 3,-2,-1,-2,-1,-2,-1,-2,-1],
  77 + [ 8, -8,-8, 8,-8, 8, 8,-8, 4, 4,-4,-4,-4,-4, 4, 4, 4,-4, 4,-4,-4, 4,-4, 4, 4,-4,-4, 4, 4,-4,-4, 4, 2, 2, 2, 2,-2,-2,-2,-2, 2, 2,-2,-2, 2, 2,-2,-2, 2,-2, 2,-2, 2,-2, 2,-2, 1, 1, 1, 1, 1, 1, 1, 1]
  78 +]
  79 +
  80 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  81 +@cython.cdivision(True)
  82 +@cython.wraparound(False)
  83 +cdef double nearest_neighbour_interp(image_t[:, :, :] V, double x, double y, double z) nogil:
  84 + return V[<int>(z), <int>(y), <int>(x)]
  85 +
  86 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  87 +@cython.cdivision(True)
  88 +@cython.wraparound(False)
  89 +cdef double interpolate(image_t[:, :, :] V, double x, double y, double z) nogil:
  90 + cdef double xd, yd, zd
  91 + cdef double c00, c10, c01, c11
  92 + cdef double c0, c1
  93 + cdef double c
  94 +
  95 + cdef int x0 = <int>floor(x)
  96 + cdef int x1 = x0 + 1
  97 +
  98 + cdef int y0 = <int>floor(y)
  99 + cdef int y1 = y0 + 1
  100 +
  101 + cdef int z0 = <int>floor(z)
  102 + cdef int z1 = z0 + 1
  103 +
  104 + if x0 == x1:
  105 + xd = 1.0
  106 + else:
  107 + xd = (x - x0) / (x1 - x0)
  108 +
  109 + if y0 == y1:
  110 + yd = 1.0
  111 + else:
  112 + yd = (y - y0) / (y1 - y0)
  113 +
  114 + if z0 == z1:
  115 + zd = 1.0
  116 + else:
  117 + zd = (z - z0) / (z1 - z0)
  118 +
  119 + c00 = _G(V, x0, y0, z0)*(1 - xd) + _G(V, x1, y0, z0)*xd
  120 + c10 = _G(V, x0, y1, z0)*(1 - xd) + _G(V, x1, y1, z0)*xd
  121 + c01 = _G(V, x0, y0, z1)*(1 - xd) + _G(V, x1, y0, z1)*xd
  122 + c11 = _G(V, x0, y1, z1)*(1 - xd) + _G(V, x1, y1, z1)*xd
  123 +
  124 + c0 = c00*(1 - yd) + c10*yd
  125 + c1 = c01*(1 - yd) + c11*yd
  126 +
  127 + c = c0*(1 - zd) + c1*zd
  128 +
  129 + return c
  130 +
  131 +
  132 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  133 +@cython.cdivision(True)
  134 +@cython.wraparound(False)
  135 +cdef inline double lanczos3_L(double x, int a) nogil:
  136 + if x == 0:
  137 + return 1.0
  138 + elif -a <= x < a:
  139 + return (a * sin(M_PI * x) * sin(M_PI * (x / a)))/(M_PI**2 * x**2)
  140 + else:
  141 + return 0.0
  142 +
  143 +
  144 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  145 +@cython.cdivision(True)
  146 +@cython.wraparound(False)
  147 +cdef double lanczos3(image_t[:, :, :] V, double x, double y, double z) nogil:
  148 + cdef int a = LANCZOS_A
  149 +
  150 + cdef int xd = <int>floor(x)
  151 + cdef int yd = <int>floor(y)
  152 + cdef int zd = <int>floor(z)
  153 +
  154 + cdef int xi = xd - a + 1
  155 + cdef int xf = xd + a
  156 +
  157 + cdef int yi = yd - a + 1
  158 + cdef int yf = yd + a
  159 +
  160 + cdef int zi = zd - a + 1
  161 + cdef int zf = zd + a
  162 +
  163 + cdef double lx = 0.0
  164 + cdef double ly = 0.0
  165 + cdef double lz = 0.0
  166 +
  167 + cdef double[SIZE_LANCZOS_TMP][SIZE_LANCZOS_TMP] temp_x
  168 + cdef double[SIZE_LANCZOS_TMP] temp_y
  169 +
  170 + cdef int i, j, k
  171 + cdef int m, n, o
  172 +
  173 + m = 0
  174 + for k in xrange(zi, zf):
  175 + n = 0
  176 + for j in xrange(yi, yf):
  177 + lx = 0
  178 + for i in xrange(xi, xf):
  179 + lx += _G(V, i, j, k) * lanczos3_L(x - i, a)
  180 + temp_x[m][n] = lx
  181 + n += 1
  182 + m += 1
  183 +
  184 + m = 0
  185 + for k in xrange(zi, zf):
  186 + n = 0
  187 + ly = 0
  188 + for j in xrange(yi, yf):
  189 + ly += temp_x[m][n] * lanczos3_L(y - j, a)
  190 + n += 1
  191 + temp_y[m] = ly
  192 + m += 1
  193 +
  194 + m = 0
  195 + for k in xrange(zi, zf):
  196 + lz += temp_y[m] * lanczos3_L(z - k, a)
  197 + m += 1
  198 +
  199 + return lz
  200 +
  201 +
  202 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  203 +@cython.cdivision(True)
  204 +@cython.wraparound(False)
  205 +cdef image_t _G(image_t[:, :, :] V, int x, int y, int z) nogil:
  206 + cdef int dz, dy, dx
  207 + dz = V.shape[0] - 1
  208 + dy = V.shape[1] - 1
  209 + dx = V.shape[2] - 1
  210 +
  211 + if x < 0:
  212 + x = dx + x + 1
  213 + elif x > dx:
  214 + x = x - dx - 1
  215 +
  216 + if y < 0:
  217 + y = dy + y + 1
  218 + elif y > dy:
  219 + y = y - dy - 1
  220 +
  221 + if z < 0:
  222 + z = dz + z + 1
  223 + elif z > dz:
  224 + z = z - dz - 1
  225 +
  226 + return V[z, y, x]
  227 +
  228 +
  229 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  230 +@cython.cdivision(True)
  231 +@cython.wraparound(False)
  232 +cdef void calc_coef_tricub(image_t[:, :, :] V, double x, double y, double z, double [64] coef) nogil:
  233 + cdef int xi = <int>floor(x)
  234 + cdef int yi = <int>floor(y)
  235 + cdef int zi = <int>floor(z)
  236 +
  237 + cdef double[64] _x
  238 +
  239 + cdef int i, j
  240 +
  241 + _x[0] = _G(V, xi, yi, zi)
  242 + _x[1] = _G(V, xi + 1, yi, zi)
  243 + _x[2] = _G(V, xi, yi + 1, zi)
  244 + _x[3] = _G(V, xi + 1, yi + 1, zi)
  245 + _x[4] = _G(V, xi, yi, zi + 1)
  246 + _x[5] = _G(V, xi + 1, yi, zi + 1)
  247 + _x[6] = _G(V, xi, yi + 1, zi + 1)
  248 + _x[7] = _G(V, xi + 1, yi + 1, zi + 1)
  249 +
  250 + _x[8] = 0.5*(_G(V, xi+1,yi,zi) - _G(V, xi-1, yi, zi))
  251 + _x[9] = 0.5*(_G(V, xi+2,yi,zi) - _G(V, xi, yi, zi))
  252 + _x[10] = 0.5*(_G(V, xi+1, yi+1,zi) - _G(V, xi-1, yi+1, zi))
  253 + _x[11] = 0.5*(_G(V, xi+2, yi+1,zi) - _G(V, xi, yi+1, zi))
  254 + _x[12] = 0.5*(_G(V, xi+1, yi,zi+1) - _G(V, xi-1, yi, zi+1))
  255 + _x[13] = 0.5*(_G(V, xi+2, yi,zi+1) - _G(V, xi, yi, zi+1))
  256 + _x[14] = 0.5*(_G(V, xi+1, yi+1,zi+1) - _G(V, xi-1, yi+1, zi+1))
  257 + _x[15] = 0.5*(_G(V, xi+2, yi+1,zi+1) - _G(V, xi, yi+1, zi+1))
  258 + _x[16] = 0.5*(_G(V, xi, yi+1,zi) - _G(V, xi, yi-1, zi))
  259 + _x[17] = 0.5*(_G(V, xi+1, yi+1,zi) - _G(V, xi+1, yi-1, zi))
  260 + _x[18] = 0.5*(_G(V, xi, yi+2,zi) - _G(V, xi, yi, zi))
  261 + _x[19] = 0.5*(_G(V, xi+1, yi+2,zi) - _G(V, xi+1, yi, zi))
  262 + _x[20] = 0.5*(_G(V, xi, yi+1,zi+1) - _G(V, xi, yi-1, zi+1))
  263 + _x[21] = 0.5*(_G(V, xi+1, yi+1,zi+1) - _G(V, xi+1, yi-1, zi+1))
  264 + _x[22] = 0.5*(_G(V, xi, yi+2,zi+1) - _G(V, xi, yi, zi+1))
  265 + _x[23] = 0.5*(_G(V, xi+1, yi+2,zi+1) - _G(V, xi+1, yi, zi+1))
  266 + _x[24] = 0.5*(_G(V, xi, yi,zi+1) - _G(V, xi, yi, zi-1))
  267 + _x[25] = 0.5*(_G(V, xi+1, yi,zi+1) - _G(V, xi+1, yi, zi-1))
  268 + _x[26] = 0.5*(_G(V, xi, yi+1,zi+1) - _G(V, xi, yi+1, zi-1))
  269 + _x[27] = 0.5*(_G(V, xi+1, yi+1,zi+1) - _G(V, xi+1, yi+1, zi-1))
  270 + _x[28] = 0.5*(_G(V, xi, yi,zi+2) - _G(V, xi, yi, zi))
  271 + _x[29] = 0.5*(_G(V, xi+1, yi,zi+2) - _G(V, xi+1, yi, zi))
  272 + _x[30] = 0.5*(_G(V, xi, yi+1,zi+2) - _G(V, xi, yi+1, zi))
  273 + _x[31] = 0.5*(_G(V, xi+1, yi+1,zi+2) - _G(V, xi+1, yi+1, zi))
  274 +
  275 + _x [32] = 0.25*(_G(V, xi+1, yi+1, zi) - _G(V, xi-1, yi+1, zi) - _G(V, xi+1, yi-1, zi) + _G(V, xi-1, yi-1, zi))
  276 + _x [33] = 0.25*(_G(V, xi+2, yi+1, zi) - _G(V, xi, yi+1, zi) - _G(V, xi+2, yi-1, zi) + _G(V, xi, yi-1, zi))
  277 + _x [34] = 0.25*(_G(V, xi+1, yi+2, zi) - _G(V, xi-1, yi+2, zi) - _G(V, xi+1, yi, zi) + _G(V, xi-1, yi, zi))
  278 + _x [35] = 0.25*(_G(V, xi+2, yi+2, zi) - _G(V, xi, yi+2, zi) - _G(V, xi+2, yi, zi) + _G(V, xi, yi, zi))
  279 + _x [36] = 0.25*(_G(V, xi+1, yi+1, zi+1) - _G(V, xi-1, yi+1, zi+1) - _G(V, xi+1, yi-1, zi+1) + _G(V, xi-1, yi-1, zi+1))
  280 + _x [37] = 0.25*(_G(V, xi+2, yi+1, zi+1) - _G(V, xi, yi+1, zi+1) - _G(V, xi+2, yi-1, zi+1) + _G(V, xi, yi-1, zi+1))
  281 + _x [38] = 0.25*(_G(V, xi+1, yi+2, zi+1) - _G(V, xi-1, yi+2, zi+1) - _G(V, xi+1, yi, zi+1) + _G(V, xi-1, yi, zi+1))
  282 + _x [39] = 0.25*(_G(V, xi+2, yi+2, zi+1) - _G(V, xi, yi+2, zi+1) - _G(V, xi+2, yi, zi+1) + _G(V, xi, yi, zi+1))
  283 + _x [40] = 0.25*(_G(V, xi+1, yi, zi+1) - _G(V, xi-1, yi, zi+1) - _G(V, xi+1, yi, zi-1) + _G(V, xi-1, yi, zi-1))
  284 + _x [41] = 0.25*(_G(V, xi+2, yi, zi+1) - _G(V, xi, yi, zi+1) - _G(V, xi+2, yi, zi-1) + _G(V, xi, yi, zi-1))
  285 + _x [42] = 0.25*(_G(V, xi+1, yi+1, zi+1) - _G(V, xi-1, yi+1, zi+1) - _G(V, xi+1, yi+1, zi-1) + _G(V, xi-1, yi+1, zi-1))
  286 + _x [43] = 0.25*(_G(V, xi+2, yi+1, zi+1) - _G(V, xi, yi+1, zi+1) - _G(V, xi+2, yi+1, zi-1) + _G(V, xi, yi+1, zi-1))
  287 + _x [44] = 0.25*(_G(V, xi+1, yi, zi+2) - _G(V, xi-1, yi, zi+2) - _G(V, xi+1, yi, zi) + _G(V, xi-1, yi, zi))
  288 + _x [45] = 0.25*(_G(V, xi+2, yi, zi+2) - _G(V, xi, yi, zi+2) - _G(V, xi+2, yi, zi) + _G(V, xi, yi, zi))
  289 + _x [46] = 0.25*(_G(V, xi+1, yi+1, zi+2) - _G(V, xi-1, yi+1, zi+2) - _G(V, xi+1, yi+1, zi) + _G(V, xi-1, yi+1, zi))
  290 + _x [47] = 0.25*(_G(V, xi+2, yi+1, zi+2) - _G(V, xi, yi+1, zi+2) - _G(V, xi+2, yi+1, zi) + _G(V, xi, yi+1, zi))
  291 + _x [48] = 0.25*(_G(V, xi, yi+1, zi+1) - _G(V, xi, yi-1, zi+1) - _G(V, xi, yi+1, zi-1) + _G(V, xi, yi-1, zi-1))
  292 + _x [49] = 0.25*(_G(V, xi+1, yi+1, zi+1) - _G(V, xi+1, yi-1, zi+1) - _G(V, xi+1, yi+1, zi-1) + _G(V, xi+1, yi-1, zi-1))
  293 + _x [50] = 0.25*(_G(V, xi, yi+2, zi+1) - _G(V, xi, yi, zi+1) - _G(V, xi, yi+2, zi-1) + _G(V, xi, yi, zi-1))
  294 + _x [51] = 0.25*(_G(V, xi+1, yi+2, zi+1) - _G(V, xi+1, yi, zi+1) - _G(V, xi+1, yi+2, zi-1) + _G(V, xi+1, yi, zi-1))
  295 + _x [52] = 0.25*(_G(V, xi, yi+1, zi+2) - _G(V, xi, yi-1, zi+2) - _G(V, xi, yi+1, zi) + _G(V, xi, yi-1, zi))
  296 + _x [53] = 0.25*(_G(V, xi+1, yi+1, zi+2) - _G(V, xi+1, yi-1, zi+2) - _G(V, xi+1, yi+1, zi) + _G(V, xi+1, yi-1, zi))
  297 + _x [54] = 0.25*(_G(V, xi, yi+2, zi+2) - _G(V, xi, yi, zi+2) - _G(V, xi, yi+2, zi) + _G(V, xi, yi, zi))
  298 + _x [55] = 0.25*(_G(V, xi+1, yi+2, zi+2) - _G(V, xi+1, yi, zi+2) - _G(V, xi+1, yi+2, zi) + _G(V, xi+1, yi, zi))
  299 +
  300 + _x[56] = 0.125*(_G(V, xi+1, yi+1, zi+1) - _G(V, xi-1, yi+1, zi+1) - _G(V, xi+1, yi-1, zi+1) + _G(V, xi-1, yi-1, zi+1) - _G(V, xi+1, yi+1, zi-1) + _G(V, xi-1,yi+1,zi-1)+_G(V, xi+1,yi-1,zi-1)-_G(V, xi-1,yi-1,zi-1))
  301 + _x[57] = 0.125*(_G(V, xi+2, yi+1, zi+1) - _G(V, xi, yi+1, zi+1) - _G(V, xi+2, yi-1, zi+1) + _G(V, xi, yi-1, zi+1) - _G(V, xi+2, yi+1, zi-1) + _G(V, xi,yi+1,zi-1)+_G(V, xi+2,yi-1,zi-1)-_G(V, xi,yi-1,zi-1))
  302 + _x[58] = 0.125*(_G(V, xi+1, yi+2, zi+1) - _G(V, xi-1, yi+2, zi+1) - _G(V, xi+1, yi, zi+1) + _G(V, xi-1, yi, zi+1) - _G(V, xi+1, yi+2, zi-1) + _G(V, xi-1,yi+2,zi-1)+_G(V, xi+1,yi,zi-1)-_G(V, xi-1,yi,zi-1))
  303 + _x[59] = 0.125*(_G(V, xi+2, yi+2, zi+1) - _G(V, xi, yi+2, zi+1) - _G(V, xi+2, yi, zi+1) + _G(V, xi, yi, zi+1) - _G(V, xi+2, yi+2, zi-1) + _G(V, xi,yi+2,zi-1)+_G(V, xi+2,yi,zi-1)-_G(V, xi,yi,zi-1))
  304 + _x[60] = 0.125*(_G(V, xi+1, yi+1, zi+2) - _G(V, xi-1, yi+1, zi+2) - _G(V, xi+1, yi-1, zi+2) + _G(V, xi-1, yi-1, zi+2) - _G(V, xi+1, yi+1, zi) + _G(V, xi-1,yi+1,zi)+_G(V, xi+1,yi-1,zi)-_G(V, xi-1,yi-1,zi))
  305 + _x[61] = 0.125*(_G(V, xi+2, yi+1, zi+2) - _G(V, xi, yi+1, zi+2) - _G(V, xi+2, yi-1, zi+2) + _G(V, xi, yi-1, zi+2) - _G(V, xi+2, yi+1, zi) + _G(V, xi,yi+1,zi)+_G(V, xi+2,yi-1,zi)-_G(V, xi,yi-1,zi))
  306 + _x[62] = 0.125*(_G(V, xi+1, yi+2, zi+2) - _G(V, xi-1, yi+2, zi+2) - _G(V, xi+1, yi, zi+2) + _G(V, xi-1, yi, zi+2) - _G(V, xi+1, yi+2, zi) + _G(V, xi-1,yi+2,zi)+_G(V, xi+1,yi,zi)-_G(V, xi-1,yi,zi))
  307 + _x[63] = 0.125*(_G(V, xi+2, yi+2, zi+2) - _G(V, xi, yi+2, zi+2) - _G(V, xi+2, yi, zi+2) + _G(V, xi, yi, zi+2) - _G(V, xi+2, yi+2, zi) + _G(V, xi,yi+2,zi)+_G(V, xi+2,yi,zi)-_G(V, xi,yi,zi))
  308 +
  309 + for j in prange(64):
  310 + coef[j] = 0.0
  311 + for i in xrange(64):
  312 + coef[j] += (temp[j][i] * _x[i])
  313 +
  314 +
  315 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  316 +@cython.cdivision(True)
  317 +@cython.wraparound(False)
  318 +cdef double tricub_interpolate(image_t[:, :, :] V, double x, double y, double z) nogil:
  319 + # From: Tricubic interpolation in three dimensions. Lekien and Marsden
  320 + cdef double[64] coef
  321 + cdef double result = 0.0
  322 + calc_coef_tricub(V, x, y, z, coef)
  323 +
  324 + cdef int i, j, k
  325 +
  326 + cdef int xi = <int>floor(x)
  327 + cdef int yi = <int>floor(y)
  328 + cdef int zi = <int>floor(z)
  329 +
  330 + for i in xrange(4):
  331 + for j in xrange(4):
  332 + for k in xrange(4):
  333 + result += (coef[i+4*j+16*k] * ((x-xi)**i) * ((y-yi)**j) * ((z-zi)**k))
  334 + # return V[<int>z, <int>y, <int>x]
  335 + # with gil:
  336 + # print result
  337 + return result
  338 +
  339 +
  340 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  341 +@cython.cdivision(True)
  342 +@cython.wraparound(False)
  343 +cdef double cubicInterpolate(double p[4], double x) nogil:
  344 + return p[1] + 0.5 * x*(p[2] - p[0] + x*(2.0*p[0] - 5.0*p[1] + 4.0*p[2] - p[3] + x*(3.0*(p[1] - p[2]) + p[3] - p[0])))
  345 +
  346 +
  347 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  348 +@cython.cdivision(True)
  349 +@cython.wraparound(False)
  350 +cdef double bicubicInterpolate (double p[4][4], double x, double y) nogil:
  351 + cdef double arr[4]
  352 + arr[0] = cubicInterpolate(p[0], y)
  353 + arr[1] = cubicInterpolate(p[1], y)
  354 + arr[2] = cubicInterpolate(p[2], y)
  355 + arr[3] = cubicInterpolate(p[3], y)
  356 + return cubicInterpolate(arr, x)
  357 +
  358 +
  359 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  360 +@cython.cdivision(True)
  361 +@cython.wraparound(False)
  362 +cdef double tricubicInterpolate(image_t[:, :, :] V, double x, double y, double z) nogil:
  363 + # From http://www.paulinternet.nl/?page=bicubic
  364 + cdef double p[4][4][4]
  365 +
  366 + cdef int xi = <int>floor(x)
  367 + cdef int yi = <int>floor(y)
  368 + cdef int zi = <int>floor(z)
  369 +
  370 + cdef int i, j, k
  371 +
  372 + for i in xrange(4):
  373 + for j in xrange(4):
  374 + for k in xrange(4):
  375 + p[i][j][k] = _G(V, xi + i -1, yi + j -1, zi + k - 1)
  376 +
  377 + cdef double arr[4]
  378 + arr[0] = bicubicInterpolate(p[0], y-yi, z-zi)
  379 + arr[1] = bicubicInterpolate(p[1], y-yi, z-zi)
  380 + arr[2] = bicubicInterpolate(p[2], y-yi, z-zi)
  381 + arr[3] = bicubicInterpolate(p[3], y-yi, z-zi)
  382 + return cubicInterpolate(arr, x-xi)
  383 +
  384 +
  385 +def tricub_interpolate_py(image_t[:, :, :] V, double x, double y, double z):
  386 + return tricub_interpolate(V, x, y, z)
  387 +
  388 +def tricub_interpolate2_py(image_t[:, :, :] V, double x, double y, double z):
  389 + return tricubicInterpolate(V, x, y, z)
  390 +
  391 +def trilin_interpolate_py(image_t[:, :, :] V, double x, double y, double z):
  392 + return interpolate(V, x, y, z)
... ...
invesalius_cy/mips.pyx 0 → 100644
  Diff comments   View file @18c2bcd
... ... @@ -0,0 +1,379 @@
  1 +#http://en.wikipedia.org/wiki/Local_maximum_intensity_projection
  2 +import numpy as np
  3 +cimport numpy as np
  4 +cimport cython
  5 +
  6 +from libc.math cimport floor, ceil, sqrt, fabs
  7 +from cython.parallel import prange
  8 +
  9 +DTYPE = np.uint8
  10 +ctypedef np.uint8_t DTYPE_t
  11 +
  12 +DTYPE16 = np.int16
  13 +ctypedef np.int16_t DTYPE16_t
  14 +
  15 +DTYPEF32 = np.float32
  16 +ctypedef np.float32_t DTYPEF32_t
  17 +
  18 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  19 +def lmip(np.ndarray[DTYPE16_t, ndim=3] image, int axis, DTYPE16_t tmin,
  20 + DTYPE16_t tmax, np.ndarray[DTYPE16_t, ndim=2] out):
  21 + cdef DTYPE16_t max
  22 + cdef int start
  23 + cdef int sz = image.shape[0]
  24 + cdef int sy = image.shape[1]
  25 + cdef int sx = image.shape[2]
  26 +
  27 + # AXIAL
  28 + if axis == 0:
  29 + for x in xrange(sx):
  30 + for y in xrange(sy):
  31 + max = image[0, y, x]
  32 + if max >= tmin and max <= tmax:
  33 + start = 1
  34 + else:
  35 + start = 0
  36 + for z in xrange(sz):
  37 + if image[z, y, x] > max:
  38 + max = image[z, y, x]
  39 +
  40 + elif image[z, y, x] < max and start:
  41 + break
  42 +
  43 + if image[z, y, x] >= tmin and image[z, y, x] <= tmax:
  44 + start = 1
  45 +
  46 + out[y, x] = max
  47 +
  48 + #CORONAL
  49 + elif axis == 1:
  50 + for z in xrange(sz):
  51 + for x in xrange(sx):
  52 + max = image[z, 0, x]
  53 + if max >= tmin and max <= tmax:
  54 + start = 1
  55 + else:
  56 + start = 0
  57 + for y in xrange(sy):
  58 + if image[z, y, x] > max:
  59 + max = image[z, y, x]
  60 +
  61 + elif image[z, y, x] < max and start:
  62 + break
  63 +
  64 + if image[z, y, x] >= tmin and image[z, y, x] <= tmax:
  65 + start = 1
  66 +
  67 + out[z, x] = max
  68 +
  69 + #CORONAL
  70 + elif axis == 2:
  71 + for z in xrange(sz):
  72 + for y in xrange(sy):
  73 + max = image[z, y, 0]
  74 + if max >= tmin and max <= tmax:
  75 + start = 1
  76 + else:
  77 + start = 0
  78 + for x in xrange(sx):
  79 + if image[z, y, x] > max:
  80 + max = image[z, y, x]
  81 +
  82 + elif image[z, y, x] < max and start:
  83 + break
  84 +
  85 + if image[z, y, x] >= tmin and image[z, y, x] <= tmax:
  86 + start = 1
  87 +
  88 + out[z, y] = max
  89 +
  90 +
  91 +cdef DTYPE16_t get_colour(DTYPE16_t vl, DTYPE16_t wl, DTYPE16_t ww):
  92 + cdef DTYPE16_t out_colour
  93 + cdef DTYPE16_t min_value = wl - (ww / 2)
  94 + cdef DTYPE16_t max_value = wl + (ww / 2)
  95 + if vl < min_value:
  96 + out_colour = min_value
  97 + elif vl > max_value:
  98 + out_colour = max_value
  99 + else:
  100 + out_colour = vl
  101 +
  102 + return out_colour
  103 +
  104 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  105 +@cython.cdivision(True)
  106 +cdef float get_opacity(DTYPE16_t vl, DTYPE16_t wl, DTYPE16_t ww) nogil:
  107 + cdef float out_opacity
  108 + cdef DTYPE16_t min_value = wl - (ww / 2)
  109 + cdef DTYPE16_t max_value = wl + (ww / 2)
  110 + if vl < min_value:
  111 + out_opacity = 0.0
  112 + elif vl > max_value:
  113 + out_opacity = 1.0
  114 + else:
  115 + out_opacity = 1.0/(max_value - min_value) * (vl - min_value)
  116 +
  117 + return out_opacity
  118 +
  119 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  120 +@cython.cdivision(True)
  121 +cdef float get_opacity_f32(DTYPEF32_t vl, DTYPE16_t wl, DTYPE16_t ww) nogil:
  122 + cdef float out_opacity
  123 + cdef DTYPE16_t min_value = wl - (ww / 2)
  124 + cdef DTYPE16_t max_value = wl + (ww / 2)
  125 + if vl < min_value:
  126 + out_opacity = 0.0
  127 + elif vl > max_value:
  128 + out_opacity = 1.0
  129 + else:
  130 + out_opacity = 1.0/(max_value - min_value) * (vl - min_value)
  131 +
  132 + return out_opacity
  133 +
  134 +
  135 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  136 +@cython.cdivision(True)
  137 +def mida(np.ndarray[DTYPE16_t, ndim=3] image, int axis, DTYPE16_t wl,
  138 + DTYPE16_t ww, np.ndarray[DTYPE16_t, ndim=2] out):
  139 + cdef int sz = image.shape[0]
  140 + cdef int sy = image.shape[1]
  141 + cdef int sx = image.shape[2]
  142 +
  143 + cdef DTYPE16_t min = image.min()
  144 + cdef DTYPE16_t max = image.max()
  145 + cdef DTYPE16_t vl
  146 +
  147 + cdef DTYPE16_t min_value = wl - (ww / 2)
  148 + cdef DTYPE16_t max_value = wl + (ww / 2)
  149 +
  150 + cdef float fmax=0.0
  151 + cdef float fpi
  152 + cdef float dl
  153 + cdef float bt
  154 +
  155 + cdef float alpha
  156 + cdef float alpha_p = 0.0
  157 + cdef float colour
  158 + cdef float colour_p = 0
  159 +
  160 + cdef int x, y, z
  161 +
  162 + # AXIAL
  163 + if axis == 0:
  164 + for x in prange(sx, nogil=True):
  165 + for y in xrange(sy):
  166 + fmax = 0.0
  167 + alpha_p = 0.0
  168 + colour_p = 0.0
  169 + for z in xrange(sz):
  170 + vl = image[z, y, x]
  171 + fpi = 1.0/(max - min) * (vl - min)
  172 + if fpi > fmax:
  173 + dl = fpi - fmax
  174 + fmax = fpi
  175 + else:
  176 + dl = 0.0
  177 +
  178 + bt = 1.0 - dl
  179 +
  180 + colour = fpi
  181 + alpha = get_opacity(vl, wl, ww)
  182 + colour = (bt * colour_p) + (1 - bt * alpha_p) * colour * alpha
  183 + alpha = (bt * alpha_p) + (1 - bt * alpha_p) * alpha
  184 +
  185 + colour_p = colour
  186 + alpha_p = alpha
  187 +
  188 + if alpha >= 1.0:
  189 + break
  190 +
  191 +
  192 + #out[y, x] = <DTYPE16_t>((max_value - min_value) * colour + min_value)
  193 + out[y, x] = <DTYPE16_t>((max - min) * colour + min)
  194 +
  195 +
  196 + #CORONAL
  197 + elif axis == 1:
  198 + for z in prange(sz, nogil=True):
  199 + for x in xrange(sx):
  200 + fmax = 0.0
  201 + alpha_p = 0.0
  202 + colour_p = 0.0
  203 + for y in xrange(sy):
  204 + vl = image[z, y, x]
  205 + fpi = 1.0/(max - min) * (vl - min)
  206 + if fpi > fmax:
  207 + dl = fpi - fmax
  208 + fmax = fpi
  209 + else:
  210 + dl = 0.0
  211 +
  212 + bt = 1.0 - dl
  213 +
  214 + colour = fpi
  215 + alpha = get_opacity(vl, wl, ww)
  216 + colour = (bt * colour_p) + (1 - bt * alpha_p) * colour * alpha
  217 + alpha = (bt * alpha_p) + (1 - bt * alpha_p) * alpha
  218 +
  219 + colour_p = colour
  220 + alpha_p = alpha
  221 +
  222 + if alpha >= 1.0:
  223 + break
  224 +
  225 + out[z, x] = <DTYPE16_t>((max - min) * colour + min)
  226 +
  227 + #AXIAL
  228 + elif axis == 2:
  229 + for z in prange(sz, nogil=True):
  230 + for y in xrange(sy):
  231 + fmax = 0.0
  232 + alpha_p = 0.0
  233 + colour_p = 0.0
  234 + for x in xrange(sx):
  235 + vl = image[z, y, x]
  236 + fpi = 1.0/(max - min) * (vl - min)
  237 + if fpi > fmax:
  238 + dl = fpi - fmax
  239 + fmax = fpi
  240 + else:
  241 + dl = 0.0
  242 +
  243 + bt = 1.0 - dl
  244 +
  245 + colour = fpi
  246 + alpha = get_opacity(vl, wl, ww)
  247 + colour = (bt * colour_p) + (1 - bt * alpha_p) * colour * alpha
  248 + alpha = (bt * alpha_p) + (1 - bt * alpha_p) * alpha
  249 +
  250 + colour_p = colour
  251 + alpha_p = alpha
  252 +
  253 + if alpha >= 1.0:
  254 + break
  255 +
  256 + out[z, y] = <DTYPE16_t>((max - min) * colour + min)
  257 +
  258 +
  259 +
  260 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  261 +@cython.cdivision(True)
  262 +cdef inline void finite_difference(DTYPE16_t[:, :, :] image,
  263 + int x, int y, int z, float h, float *g) nogil:
  264 + cdef int px, py, pz, fx, fy, fz
  265 +
  266 + cdef int sz = image.shape[0]
  267 + cdef int sy = image.shape[1]
  268 + cdef int sx = image.shape[2]
  269 +
  270 + cdef float gx, gy, gz
  271 +
  272 + if x == 0:
  273 + px = 0
  274 + fx = 1
  275 + elif x == sx - 1:
  276 + px = x - 1
  277 + fx = x
  278 + else:
  279 + px = x - 1
  280 + fx = x + 1
  281 +
  282 + if y == 0:
  283 + py = 0
  284 + fy = 1
  285 + elif y == sy - 1:
  286 + py = y - 1
  287 + fy = y
  288 + else:
  289 + py = y - 1
  290 + fy = y + 1
  291 +
  292 + if z == 0:
  293 + pz = 0
  294 + fz = 1
  295 + elif z == sz - 1:
  296 + pz = z - 1
  297 + fz = z
  298 + else:
  299 + pz = z - 1
  300 + fz = z + 1
  301 +
  302 + gx = (image[z, y, fx] - image[z, y, px]) / (2*h)
  303 + gy = (image[z, fy, x] - image[z, py, x]) / (2*h)
  304 + gz = (image[fz, y, x] - image[pz, y, x]) / (2*h)
  305 +
  306 + g[0] = gx
  307 + g[1] = gy
  308 + g[2] = gz
  309 +
  310 +
  311 +
  312 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  313 +@cython.cdivision(True)
  314 +cdef inline float calc_fcm_itensity(DTYPE16_t[:, :, :] image,
  315 + int x, int y, int z, float n, float* dir) nogil:
  316 + cdef float g[3]
  317 + finite_difference(image, x, y, z, 1.0, g)
  318 + cdef float gm = sqrt(g[0]*g[0] + g[1]*g[1] + g[2]*g[2])
  319 + cdef float d = g[0]*dir[0] + g[1]*dir[1] + g[2]*dir[2]
  320 + cdef float sf = (1.0 - fabs(d/gm))**n
  321 + #alpha = get_opacity_f32(gm, wl, ww)
  322 + cdef float vl = gm * sf
  323 + return vl
  324 +
  325 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  326 +@cython.cdivision(True)
  327 +def fast_countour_mip(np.ndarray[DTYPE16_t, ndim=3] image,
  328 + float n,
  329 + int axis,
  330 + DTYPE16_t wl, DTYPE16_t ww,
  331 + int tmip,
  332 + np.ndarray[DTYPE16_t, ndim=2] out):
  333 + cdef int sz = image.shape[0]
  334 + cdef int sy = image.shape[1]
  335 + cdef int sx = image.shape[2]
  336 + cdef float gm
  337 + cdef float alpha
  338 + cdef float sf
  339 + cdef float d
  340 +
  341 + cdef float* g
  342 + cdef float* dir = [ 0, 0, 0 ]
  343 +
  344 + cdef DTYPE16_t[:, :, :] vimage = image
  345 + cdef np.ndarray[DTYPE16_t, ndim=3] tmp = np.empty_like(image)
  346 +
  347 + cdef DTYPE16_t min = image.min()
  348 + cdef DTYPE16_t max = image.max()
  349 + cdef float fmin = <float>min
  350 + cdef float fmax = <float>max
  351 + cdef float vl
  352 + cdef DTYPE16_t V
  353 +
  354 + cdef int x, y, z
  355 +
  356 + if axis == 0:
  357 + dir[2] = 1.0
  358 + elif axis == 1:
  359 + dir[1] = 1.0
  360 + elif axis == 2:
  361 + dir[0] = 1.0
  362 +
  363 + for z in prange(sz, nogil=True):
  364 + for y in range(sy):
  365 + for x in range(sx):
  366 + vl = calc_fcm_itensity(vimage, x, y, z, n, dir)
  367 + tmp[z, y, x] = <DTYPE16_t>vl
  368 +
  369 + cdef DTYPE16_t tmin = tmp.min()
  370 + cdef DTYPE16_t tmax = tmp.max()
  371 +
  372 + #tmp = ((max - min)/<float>(tmax - tmin)) * (tmp - tmin) + min
  373 +
  374 + if tmip == 0:
  375 + out[:] = tmp.max(axis)
  376 + elif tmip == 1:
  377 + lmip(tmp, axis, 700, 3033, out)
  378 + elif tmip == 2:
  379 + mida(tmp, axis, wl, ww, out)
... ...
invesalius_cy/transforms.pyx 0 → 100644
  Diff comments   View file @18c2bcd
... ... @@ -0,0 +1,174 @@
  1 +import numpy as np
  2 +cimport numpy as np
  3 +cimport cython
  4 +
  5 +from .cy_my_types cimport image_t
  6 +from .interpolation cimport interpolate, tricub_interpolate, tricubicInterpolate, lanczos3, nearest_neighbour_interp
  7 +
  8 +from libc.math cimport floor, ceil, sqrt, fabs, round
  9 +from cython.parallel import prange
  10 +
  11 +ctypedef double (*interp_function)(image_t[:, :, :], double, double, double) nogil
  12 +
  13 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  14 +@cython.cdivision(True)
  15 +@cython.wraparound(False)
  16 +cdef void mul_mat4_vec4(double[:, :] M,
  17 + double* coord,
  18 + double* out) nogil:
  19 +
  20 + out[0] = coord[0] * M[0, 0] + coord[1] * M[0, 1] + coord[2] * M[0, 2] + coord[3] * M[0, 3]
  21 + out[1] = coord[0] * M[1, 0] + coord[1] * M[1, 1] + coord[2] * M[1, 2] + coord[3] * M[1, 3]
  22 + out[2] = coord[0] * M[2, 0] + coord[1] * M[2, 1] + coord[2] * M[2, 2] + coord[3] * M[2, 3]
  23 + out[3] = coord[0] * M[3, 0] + coord[1] * M[3, 1] + coord[2] * M[3, 2] + coord[3] * M[3, 3]
  24 +
  25 +
  26 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  27 +@cython.cdivision(True)
  28 +@cython.wraparound(False)
  29 +cdef image_t coord_transform(image_t[:, :, :] volume, double[:, :] M, int x, int y, int z, double sx, double sy, double sz, interp_function f_interp, image_t cval) nogil:
  30 +
  31 + cdef double coord[4]
  32 + coord[0] = z*sz
  33 + coord[1] = y*sy
  34 + coord[2] = x*sx
  35 + coord[3] = 1.0
  36 +
  37 + cdef double _ncoord[4]
  38 + _ncoord[3] = 1
  39 + # _ncoord[:] = [0.0, 0.0, 0.0, 1.0]
  40 +
  41 + cdef unsigned int dz, dy, dx
  42 + dz = volume.shape[0]
  43 + dy = volume.shape[1]
  44 + dx = volume.shape[2]
  45 +
  46 +
  47 + mul_mat4_vec4(M, coord, _ncoord)
  48 +
  49 + cdef double nz, ny, nx
  50 + nz = (_ncoord[0]/_ncoord[3])/sz
  51 + ny = (_ncoord[1]/_ncoord[3])/sy
  52 + nx = (_ncoord[2]/_ncoord[3])/sx
  53 +
  54 + cdef double v
  55 +
  56 + if 0 <= nz <= (dz-1) and 0 <= ny <= (dy-1) and 0 <= nx <= (dx-1):
  57 + return <image_t>f_interp(volume, nx, ny, nz)
  58 + # if minterpol == 0:
  59 + # return <image_t>nearest_neighbour_interp(volume, nx, ny, nz)
  60 + # elif minterpol == 1:
  61 + # return <image_t>interpolate(volume, nx, ny, nz)
  62 + # elif minterpol == 2:
  63 + # v = tricubicInterpolate(volume, nx, ny, nz)
  64 + # if (v < cval):
  65 + # v = cval
  66 + # return <image_t>v
  67 + # else:
  68 + # v = lanczos3(volume, nx, ny, nz)
  69 + # if (v < cval):
  70 + # v = cval
  71 + # return <image_t>v
  72 + else:
  73 + return cval
  74 +
  75 +
  76 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  77 +@cython.cdivision(True)
  78 +@cython.wraparound(False)
  79 +def apply_view_matrix_transform(image_t[:, :, :] volume,
  80 + spacing,
  81 + double[:, :] M,
  82 + unsigned int n, str orientation,
  83 + int minterpol,
  84 + image_t cval,
  85 + image_t[:, :, :] out):
  86 +
  87 + cdef int dz, dy, dx
  88 + cdef int z, y, x
  89 + dz = volume.shape[0]
  90 + dy = volume.shape[1]
  91 + dx = volume.shape[2]
  92 +
  93 + cdef unsigned int odz, ody, odx
  94 + odz = out.shape[0]
  95 + ody = out.shape[1]
  96 + odx = out.shape[2]
  97 +
  98 + cdef unsigned int count = 0
  99 +
  100 + cdef double sx, sy, sz
  101 + sx = spacing[0]
  102 + sy = spacing[1]
  103 + sz = spacing[2]
  104 +
  105 + cdef interp_function f_interp
  106 +
  107 + if minterpol == 0:
  108 + f_interp = nearest_neighbour_interp
  109 + elif minterpol == 1:
  110 + f_interp = interpolate
  111 + elif minterpol == 2:
  112 + f_interp = tricubicInterpolate
  113 + else:
  114 + f_interp = lanczos3
  115 +
  116 + if orientation == 'AXIAL':
  117 + for z in xrange(n, n+odz):
  118 + for y in prange(dy, nogil=True):
  119 + for x in xrange(dx):
  120 + out[count, y, x] = coord_transform(volume, M, x, y, z, sx, sy, sz, f_interp, cval)
  121 + count += 1
  122 +
  123 + elif orientation == 'CORONAL':
  124 + for y in xrange(n, n+ody):
  125 + for z in prange(dz, nogil=True):
  126 + for x in xrange(dx):
  127 + out[z, count, x] = coord_transform(volume, M, x, y, z, sx, sy, sz, f_interp, cval)
  128 + count += 1
  129 +
  130 + elif orientation == 'SAGITAL':
  131 + for x in xrange(n, n+odx):
  132 + for z in prange(dz, nogil=True):
  133 + for y in xrange(dy):
  134 + out[z, y, count] = coord_transform(volume, M, x, y, z, sx, sy, sz, f_interp, cval)
  135 + count += 1
  136 +
  137 +
  138 +@cython.boundscheck(False) # turn of bounds-checking for entire function
  139 +@cython.cdivision(True)
  140 +@cython.wraparound(False)
  141 +def convolve_non_zero(image_t[:, :, :] volume,
  142 + image_t[:, :, :] kernel,
  143 + image_t cval):
  144 + cdef Py_ssize_t x, y, z, sx, sy, sz, kx, ky, kz, skx, sky, skz, i, j, k
  145 + cdef image_t v
  146 +
  147 + cdef image_t[:, :, :] out = np.zeros_like(volume)
  148 +
  149 + sz = volume.shape[0]
  150 + sy = volume.shape[1]
  151 + sx = volume.shape[2]
  152 +
  153 + skz = kernel.shape[0]
  154 + sky = kernel.shape[1]
  155 + skx = kernel.shape[2]
  156 +
  157 + for z in prange(sz, nogil=True):
  158 + for y in xrange(sy):
  159 + for x in xrange(sx):
  160 + if volume[z, y, x] != 0:
  161 + for k in xrange(skz):
  162 + kz = z - skz // 2 + k
  163 + for j in xrange(sky):
  164 + ky = y - sky // 2 + j
  165 + for i in xrange(skx):
  166 + kx = x - skx // 2 + i
  167 +
  168 + if 0 <= kz < sz and 0 <= ky < sy and 0 <= kx < sx:
  169 + v = volume[kz, ky, kx]
  170 + else:
  171 + v = cval
  172 +
  173 + out[z, y, x] += (v * kernel[k, j, i])
  174 + return np.asarray(out)
... ...
setup.py
  Diff comments   View file @18c2bcd
... ... @@ -40,25 +40,25 @@ setup(
40 40 ext_modules=cythonize(
41 41 [
42 42 Extension(
43   - "invesalius.data.mips",
44   - ["invesalius/data/mips.pyx"],
  43 + "invesalius_cy.mips",
  44 + ["invesalius_cy/mips.pyx"],
45 45 ),
46 46 Extension(
47   - "invesalius.data.interpolation",
48   - ["invesalius/data/interpolation.pyx"],
  47 + "invesalius_cy.interpolation",
  48 + ["invesalius_cy/interpolation.pyx"],
49 49 ),
50 50 Extension(
51   - "invesalius.data.transforms",
52   - ["invesalius/data/transforms.pyx"],
  51 + "invesalius_cy.transforms",
  52 + ["invesalius_cy/transforms.pyx"],
53 53 ),
54 54 Extension(
55   - "invesalius.data.floodfill",
56   - ["invesalius/data/floodfill.pyx"],
  55 + "invesalius_cy.floodfill",
  56 + ["invesalius_cy/floodfill.pyx"],
57 57 language="c++",
58 58 ),
59 59 Extension(
60   - "invesalius.data.cy_mesh",
61   - ["invesalius/data/cy_mesh.pyx"],
  60 + "invesalius_cy.cy_mesh",
  61 + ["invesalius_cy/cy_mesh.pyx"],
62 62 language="c++",
63 63 ),
64 64 ]
... ...