def interpolate(self, time):
"""."""
# Handle boundary conditions for matrix interpolation
if (not self.actually_animated or time <= self.start_time):
return Transform.from_transform(self.start_transform)
if (time >= self.endTime):
return self.end_transform
dt = (time - self.start_time) / (self.end_ime - self.start_time)
# Interpolate translation at _dt_
trans = (1.0 - dt) * self.t_0 + dt * self.t_1
# Interpolate rotation at _dt_
rotate = slerp(dt, self.r_0, self.r_1)
# Interpolate scale at _dt_
scale = Matrix4x4()
for i in range(3):
for j in range(3):
scale.m[i][j] = lerp(dt, self.s_o.m[i][j], self.s_1.m[i][j])
# Compute interpolated matrix as product of interpolated components
return translate(trans) * \
rotate.to_transform() * \
Transform(scale)
def interpolate(self, time):
"""."""
# Handle boundary conditions for matrix interpolation
if (not self.actually_animated or time <= self.start_time):
return Transform.from_transform(self.start_transform)
if (time >= self.endTime):
return self.end_transform
dt = (time - self.start_time) / (self.end_ime - self.start_time)
# Interpolate translation at _dt_
trans = (1.0 - dt) * self.t_0 + dt * self.t_1
# Interpolate rotation at _dt_
rotate = slerp(dt, self.r_0, self.r_1)
# Interpolate scale at _dt_
scale = Matrix4x4()
for i in range(3):
for j in range(3):
scale.m[i][j] = lerp(dt, self.s_o.m[i][j], self.s_1.m[i][j])
# Compute interpolated matrix as product of interpolated components
return translate(trans) * \
rotate.to_transform() * \
Transform(scale)
def test_slerp(self):
transform1 = rotate_z(30.0)
q1 = Quaternion.from_transform(transform1)
transform2 = rotate_z(90.0)
q2 = Quaternion.from_transform(transform2)
q_interp = slerp(0.5, q1, q2)
transform3 = rotate_z(60)
q3 = Quaternion.from_transform(transform3)
self.assertEqual(q_interp, q3)
self.assertEqual(q_interp.to_transform(), transform3)
