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136 lines
3.5 KiB
Python
136 lines
3.5 KiB
Python
from PIL import Image
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from colour import Color
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import numpy as np
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import warnings
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import time
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import os
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import progressbar
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import inspect
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from copy import deepcopy
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from helpers import *
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from mobject import Mobject
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class Animation(object):
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CONFIG = {
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"run_time" : DEFAULT_ANIMATION_RUN_TIME,
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"rate_func" : smooth,
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"name" : None,
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#Does this animation add or remove a mobject form the screen
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"remover" : False,
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#Options are lagged_start, smoothed_lagged_start,
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#one_at_a_time, all_at_once
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"submobject_mode" : "lagged_start",
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"lag_factor" : 2,
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}
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def __init__(self, mobject, **kwargs):
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mobject = instantiate(mobject)
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assert(isinstance(mobject, Mobject))
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digest_config(self, kwargs, locals())
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self.starting_mobject = self.mobject.copy()
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if self.rate_func is None:
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self.rate_func = (lambda x : x)
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if self.name is None:
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self.name = self.__class__.__name__ + str(self.mobject)
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self.update(0)
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def update_config(self, **kwargs):
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digest_config(self, kwargs)
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if "rate_func" in kwargs and kwargs["rate_func"] is None:
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self.rate_func = (lambda x : x)
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return self
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def __str__(self):
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return self.name
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def copy(self):
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return deepcopy(self)
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def update(self, alpha):
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if alpha < 0:
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alpha = 0.0
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if alpha > 1:
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alpha = 1.0
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self.update_mobject(self.rate_func(alpha))
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def update_mobject(self, alpha):
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families = self.get_all_families_zipped()
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for i, mobs in enumerate(families):
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sub_alpha = self.get_sub_alpha(alpha, i, len(families))
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self.update_submobject(*list(mobs) + [sub_alpha])
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return self
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def update_submobject(self, submobject, starting_sumobject, alpha):
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#Typically ipmlemented by subclass
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pass
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def get_all_families_zipped(self):
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"""
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Ordering must match the ording of arguments to update_submobject
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"""
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return zip(
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self.mobject.submobject_family(),
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self.starting_mobject.submobject_family()
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)
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def get_sub_alpha(self, alpha, index, num_submobjects):
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if self.submobject_mode in ["lagged_start", "smoothed_lagged_start"]:
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prop = float(index)/num_submobjects
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if self.submobject_mode is "smoothed_lagged_start":
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prop = smooth(prop)
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lf = self.lag_factor
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return np.clip(lf*alpha - (lf-1)*prop, 0, 1)
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elif self.submobject_mode == "one_at_a_time":
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lower = float(index)/num_submobjects
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upper = float(index+1)/num_submobjects
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return np.clip((alpha-lower)/(upper-lower), 0, 1)
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elif self.submobject_mode == "all_at_once":
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return alpha
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raise Exception("Invalid submobject mode")
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def filter_out(self, *filter_functions):
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self.filter_functions += filter_functions
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return self
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def set_run_time(self, time):
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self.run_time = time
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return self
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def get_run_time(self):
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return self.run_time
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def set_rate_func(self, rate_func):
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if rate_func is None:
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rate_func = lambda x : x
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self.rate_func = rate_func
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return self
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def get_rate_func(self):
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return self.rate_func
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def set_name(self, name):
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self.name = name
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return self
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def is_remover(self):
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return self.remover
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def clean_up(self):
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self.update(1)
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