def fast_odf(self,s):
odf = np.zeros(self.odfn)
Eq=np.zeros((self.sz,self.sz,self.sz))
#for i in range(self.dn):
# Eq[self.q[i][0],self.q[i][1],self.q[i][2]]+=s[i]/s[0]
Eq[self.q[:,0],self.q[:,1],self.q[:,2]]=s[:]/np.float(s[0])
#self.Eqs.append(Eq)
if self.operator=='laplacian':
LEq=laplace(Eq)
sign=-1
if self.operator=='laplap':
LEq=laplace(laplace(Eq))
sign=1
if self.operator=='signal':
LEq=Eq
sign=1
#LEs=map_coordinates(LEq,self.Ys.T,order=1)
#"""
LEs=np.zeros(self.Ysn)
strides=np.array(LEq.strides,'i8')
map_coordinates_trilinear_iso(LEq,self.Ys,
strides,self.Ysn, LEs)
#LEs=map_coordinates(LEq,self.zoom*self.Ys,order=1)
LEs=LEs.reshape(self.odfn,self.radiusn)
LEs=LEs*self.radius
#LEs=LEs*self.radius*self.zoom
LEsum=np.sum(LEs,axis=1)
#This is what the following code is doing
#for i in xrange(self.odfn):
# odf[i]=np.sum(LEsum[self.eqinds[i]])/self.eqinds_len[i]
#odf2=odf.copy()
LES=LEsum[self.eqinds_com]
sum_on_blocks_1d(LES,self.eqinds_len,odf,self.odfn)
odf=odf/self.eqinds_len
return self.angular_weighting(sign*odf)
def fast_odf(self, s):
odf = np.zeros(self.odfn)
Eq = np.zeros((self.sz, self.sz, self.sz))
#for i in range(self.dn):
# Eq[self.q[i][0],self.q[i][1],self.q[i][2]]+=s[i]/s[0]
Eq[self.q[:, 0], self.q[:, 1], self.q[:, 2]] = s[:] / np.float(s[0])
#self.Eqs.append(Eq)
if self.operator == 'laplacian':
LEq = laplace(Eq)
sign = -1
if self.operator == 'laplap':
LEq = laplace(laplace(Eq))
sign = 1
if self.operator == 'signal':
LEq = Eq
sign = 1
#LEs=map_coordinates(LEq,self.Ys.T,order=1)
#"""
LEs = np.zeros(self.Ysn)
strides = np.array(LEq.strides, 'i8')
map_coordinates_trilinear_iso(LEq, self.Ys, strides, self.Ysn, LEs)
#LEs=map_coordinates(LEq,self.zoom*self.Ys,order=1)
LEs = LEs.reshape(self.odfn, self.radiusn)
LEs = LEs * self.radius
#LEs=LEs*self.radius*self.zoom
LEsum = np.sum(LEs, axis=1)
#This is what the following code is doing
#for i in xrange(self.odfn):
# odf[i]=np.sum(LEsum[self.eqinds[i]])/self.eqinds_len[i]
#odf2=odf.copy()
LES = LEsum[self.eqinds_com]
sum_on_blocks_1d(LES, self.eqinds_len, odf, self.odfn)
odf = odf / self.eqinds_len
return self.angular_weighting(sign * odf)
def test_trilinear_interp_cubic_voxels():
A=np.ones((17,17,17))
B=np.zeros(3)
strides=np.array(A.strides, np.intp)
A[7,7,7]=2
points=np.array([[0,0,0],[7.,7.5,7.],[3.5,3.5,3.5]])
map_coordinates_trilinear_iso(A,points,strides,3,B)
assert_array_almost_equal(B,np.array([ 1. , 1.5, 1. ]))
def test_trilinear_interp_cubic_voxels():
A=np.ones((17,17,17))
B=np.zeros(3)
strides=np.array(A.strides, np.intp)
A[7,7,7]=2
points=np.array([[0,0,0],[7.,7.5,7.],[3.5,3.5,3.5]])
map_coordinates_trilinear_iso(A,points,strides,3,B)
assert_array_almost_equal(B,np.array([ 1. , 1.5, 1. ]))
def test_trilinear_interp_cubic_voxels():
A = np.ones((17, 17, 17))
B = np.zeros(3)
strides = np.array(A.strides, np.intp)
A[7, 7, 7] = 2
points = np.array([[0, 0, 0], [7., 7.5, 7.], [3.5, 3.5, 3.5]])
map_coordinates_trilinear_iso(A, points, strides, 3, B)
assert_array_almost_equal(B, np.array([1., 1.5, 1.]))
# All of the input array, points array, strides array and output array must
# be C-contiguous. Check by passing in versions that aren't C contiguous
assert_raises(ValueError, map_coordinates_trilinear_iso, A.copy(order='F'),
points, strides, 3, B)
assert_raises(ValueError, map_coordinates_trilinear_iso, A,
points.copy(order='F'), strides, 3, B)
assert_raises(ValueError, map_coordinates_trilinear_iso, A, points,
stepped_1d(strides), 3, B)
assert_raises(ValueError, map_coordinates_trilinear_iso, A, points,
strides, 3, stepped_1d(B))
def test_trilinear_interp_cubic_voxels():
A = np.ones((17, 17, 17))
B = np.zeros(3)
strides = np.array(A.strides, np.intp)
A[7, 7, 7] = 2
points = np.array([[0, 0, 0], [7., 7.5, 7.], [3.5, 3.5, 3.5]])
map_coordinates_trilinear_iso(A, points, strides, 3, B)
assert_array_almost_equal(B, np.array([1., 1.5, 1.]))
# All of the input array, points array, strides array and output array must
# be C-contiguous. Check by passing in versions that aren't C contiguous
assert_raises(ValueError, map_coordinates_trilinear_iso,
A.copy(order='F'), points, strides, 3, B)
assert_raises(ValueError, map_coordinates_trilinear_iso,
A, points.copy(order='F'), strides, 3, B)
assert_raises(ValueError, map_coordinates_trilinear_iso,
A, points, stepped_1d(strides), 3, B)
assert_raises(ValueError, map_coordinates_trilinear_iso,
A, points, strides, 3, stepped_1d(B))
