def get_mean_displacement(self,
index,
method='box',
box_min=BOX_MIN,
box_max=BOX_MAX):
mat = self.get_motion_affine(index)
mat = Transform_Affine(mat)
if method == 'box':
b = box_min
B = box_max
corners = numpy.asarray([[b[0], b[1], b[2], 1],
[B[0], b[1], b[2], 1],
[b[0], B[1], b[2], 1],
[B[0], B[1], b[2], 1],
[b[0], b[1], B[2], 1],
[B[0], b[1], B[2], 1],
[b[0], B[1], B[2], 1],
[B[0], B[1], B[2], 1]]).transpose()
corners_t = mat.left_multiply(corners)
corners_t[3, :] = 0
corners[3, :] = 0
#print "CORNERS: ", corners_t
#dist = numpy.sqrt(((corners-corners_t)**2).sum(0))
dist = (corners - corners_t).sum(0)
mean_displ = numpy.mean(dist)
else:
raise "Method to compute mean displacement is unknown. "
return mean_displ
def get_mean_displacement(self, index, method='box', box_min=BOX_MIN, box_max=BOX_MAX):
mat = self.get_motion_affine(index)
mat = Transform_Affine(mat)
if method=='box':
b = box_min
B = box_max
corners = numpy.asarray([ [b[0],b[1],b[2],1], [B[0],b[1],b[2],1], [b[0],B[1],b[2],1], [B[0],B[1],b[2],1], [b[0],b[1],B[2],1], [B[0],b[1],B[2],1], [b[0],B[1],B[2],1], [B[0],B[1],B[2],1] ]).transpose()
corners_t = mat.left_multiply(corners)
corners_t[3,:]=0
corners[3,:] =0
#print "CORNERS: ", corners_t
#dist = numpy.sqrt(((corners-corners_t)**2).sum(0))
dist = (corners-corners_t).sum(0)
mean_displ = numpy.mean(dist)
else:
raise "Method to compute mean displacement is unknown. "
return mean_displ
def get_mean_displacement_variation_since_time(self, index_new, index_old, method='box', box_min=BOX_MIN, box_max=BOX_MAX):
mat = self.get_motion_affine(index_new)
mat0 = self.get_motion_affine(index_old)
mat = Transform_Affine(mat)
mat0 = Transform_Affine(mat0)
if method=='box':
b = box_min
B = box_max
corners = numpy.asarray([ [b[0],b[1],b[2],1], [B[0],b[1],b[2],1], [b[0],B[1],b[2],1], [B[0],B[1],b[2],1], [b[0],b[1],B[2],1], [B[0],b[1],B[2],1], [b[0],B[1],B[2],1], [B[0],B[1],B[2],1] ]).transpose()
corners_t = mat.left_multiply(corners)
corners_t[3,:]=0
corners_t0 = mat0.left_multiply(corners)
corners_t0[3,:]=0
dist = numpy.sqrt(((corners_t-corners_t0)**2).sum(0))
#dist = (corners-corners_t).sum(0)
mean_displ = numpy.mean(dist)
else:
raise "Method to compute mean displacement is unknown. "
return mean_displ
def get_mean_displacement_variation_since_time(self,
index_new,
index_old,
method='box',
box_min=BOX_MIN,
box_max=BOX_MAX):
mat = self.get_motion_affine(index_new)
mat0 = self.get_motion_affine(index_old)
mat = Transform_Affine(mat)
mat0 = Transform_Affine(mat0)
if method == 'box':
b = box_min
B = box_max
corners = numpy.asarray([[b[0], b[1], b[2], 1],
[B[0], b[1], b[2], 1],
[b[0], B[1], b[2], 1],
[B[0], B[1], b[2], 1],
[b[0], b[1], B[2], 1],
[B[0], b[1], B[2], 1],
[b[0], B[1], B[2], 1],
[B[0], B[1], B[2], 1]]).transpose()
corners_t = mat.left_multiply(corners)
corners_t[3, :] = 0
corners_t0 = mat0.left_multiply(corners)
corners_t0[3, :] = 0
dist = numpy.sqrt(((corners_t - corners_t0)**2).sum(0))
#dist = (corners-corners_t).sum(0)
mean_displ = numpy.mean(dist)
else:
raise "Method to compute mean displacement is unknown. "
return mean_displ
