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Further fixes to Succession animations

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This commit is contained in:
Sridhar Ramesh 2018-01-19 16:52:31 -08:00
parent 7bcde6713d
commit 123bae00a6
2 changed files with 18 additions and 22 deletions
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38
animation/simple_animations.py
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@ -395,13 +395,22 @@ class Succession(Animation):
mobject = Group(*[anim.mobject for anim in self.animations]) mobject = Group(*[anim.mobject for anim in self.animations])
Animation.__init__(self, mobject, run_time = run_time, **kwargs) Animation.__init__(self, mobject, run_time = run_time, **kwargs)
def rewind_to_start(self):
for anim in reversed(self.animations):
anim.update(0)
def update_mobject(self, alpha): def update_mobject(self, alpha):
self.rewind_to_start()
for i in range(len(self.animations)): for i in range(len(self.animations)):
sub_alpha = anti_interpolate( sub_alpha = inverse_interpolate(
self.critical_alphas[i], self.critical_alphas[i],
self.critical_alphas[i + 1], self.critical_alphas[i + 1],
alpha alpha
) )
if sub_alpha < 0:
return
sub_alpha = clamp(0, 1, sub_alpha) # Could possibly adopt a non-clamping convention here sub_alpha = clamp(0, 1, sub_alpha) # Could possibly adopt a non-clamping convention here
self.animations[i].update(sub_alpha) self.animations[i].update(sub_alpha)
@ -424,23 +433,10 @@ class AnimationGroup(Animation):
for anim in self.sub_anims: for anim in self.sub_anims:
anim.update(alpha) anim.update(alpha)
# Parallel animations where shorter animations are not stretched out to match the longest
class UnsyncedParallel(AnimationGroup):
def __init__(self, *sub_anims, **kwargs):
digest_config(self, kwargs, locals())
self.run_time = max([a.run_time for a in sub_anims])
everything = Mobject(*[a.mobject for a in sub_anims])
Animation.__init__(self, everything, **kwargs)

2
helpers.py
View file

@ -307,7 +307,7 @@ def interpolate(start, end, alpha):
def mid(start, end): def mid(start, end):
return (start + end)/2.0 return (start + end)/2.0
def anti_interpolate(start, end, value): def inverse_interpolate(start, end, value):
return np.true_divide(value - start, end - start) return np.true_divide(value - start, end - start)
def clamp(lower, upper, val): def clamp(lower, upper, val):