def ray_values(v, direction): d = v.data center = [0.5*(s+1) for s in d.size] radius = 0.5*min([s*t for s,t in zip(d.size, d.step)]) steps = max(d.size) from Matrix import norm dn = norm(direction) from numpy import array, arange, float32, outer dir = array(direction)/dn spacing = radius/dn radii = arange(0, steps, dtype = float32)*(radius/steps) ray_points = outer(radii, dir) values = v.interpolated_values(ray_points) return radii, values, radius
def parse_rotation(rotation, qrotation):
if rotation:
aa = parse_floats(rotation, 'rotation', 4)
axis, angle = aa[:3], aa[3]
elif qrotation:
q = parse_floats(qrotation, 'qrotation', 4)
from Matrix import norm
from math import atan2, pi
angle = (360/pi)*atan2(norm(q[:3]), q[3])
axis = q[:3]
else:
axis = angle = None
if axis and tuple(axis) == (0,0,0):
axis = angle = None
return axis, angle
def parse_rotation(rotation, qrotation):
if rotation:
aa = parse_floats(rotation, 'rotation', 4)
axis, angle = aa[:3], aa[3]
elif qrotation:
q = parse_floats(qrotation, 'qrotation', 4)
from Matrix import norm
from math import atan2, pi
angle = (360 / pi) * atan2(norm(q[:3]), q[3])
axis = q[:3]
else:
axis = angle = None
if axis and tuple(axis) == (0, 0, 0):
axis = angle = None
return axis, angle
def rotation_step(points, point_weights, center, data_array,
xyz_to_ijk_transform, ijk_step_size, metric):
axis = torque_axis(points, point_weights, center, data_array,
xyz_to_ijk_transform, metric)
from Matrix import norm, rotation_transform
na = norm(axis)
if len(points) == 1 or na == 0:
axis = (0,0,1)
angle = 0
else:
axis /= na
angle = angle_step(axis, points, center, xyz_to_ijk_transform,
ijk_step_size)
move_tf = rotation_transform(axis, angle, center)
return move_tf
def translation_step(points, point_weights, center, data_array,
xyz_to_ijk_transform, ijk_step_size, metric):
g = gradient_direction(points, point_weights, data_array,
xyz_to_ijk_transform, metric)
from numpy import array, float, dot as matrix_multiply
tf = array(xyz_to_ijk_transform)
gijk = matrix_multiply(tf[:,:3], g)
from Matrix import norm
n = norm(gijk)
if n > 0:
delta = g * (ijk_step_size / n)
else:
delta = array((0,0,0), float)
delta_tf = ((1,0,0,delta[0]),
(0,1,0,delta[1]),
(0,0,1,delta[2]))
return delta_tf