def __init__(self, condition=(lambda x, y: True), **kwargs):
"""
Condition must be a function which takes in two real
arrays (representing x and y values of space respectively)
and return a boolean array. This can essentially look like
a function from R^2 to {True, False}, but & and | must be
used in place of "and" and "or"
"""
Mobject.__init__(self, **kwargs)
self.condition = condition
def __init__(self, condition=(lambda x, y: True), **kwargs):
"""
Condition must be a function which takes in two real
arrays (representing x and y values of space respectively)
and return a boolean array. This can essentially look like
a function from R^2 to {True, False}, but & and | must be
used in place of "and" and "or"
"""
Mobject.__init__(self, **kwargs)
self.condition = condition
def __init__(self, **kwargs):
if not hasattr(self, "args"):
self.args = serialize_args([])
if not hasattr(self, "config"):
self.config = serialize_config({
**kwargs,
})
digest_config(self, kwargs)
self.epsilon = 1.0 / self.density
Mobject.__init__(self, **kwargs)
def __init__(self, value=0, **kwargs):
if not hasattr(self, "args"):
self.args = serialize_args([])
if not hasattr(self, "config"):
self.config = serialize_config({
'value': value,
**kwargs,
})
Mobject.__init__(self, **kwargs)
self.points = np.zeros((1, 3))
self.set_value(value)
def __init__(self, filename, **kwargs):
digest_config(self, kwargs)
Mobject.__init__(self, **kwargs)
path = get_full_video_path(filename)
self.cap = cv2.VideoCapture(path)
self.is_start = False
self.fps = self.cap.get(cv2.CAP_PROP_FPS)
# Total frame num of the video
self.frame_count = int(self.cap.get(cv2.CAP_PROP_FRAME_COUNT))
self.duration = self.frame_count / self.fps
self.start_time = 0
self.current_time = 0
self.offset = 0
r, i = self.cap.read()
self.img = ImageMobject(i, **kwargs)
self.add_updater(lambda v, dt: v.update_pixel())
self.add(self.img)
def __init__(self, **kwargs):
digest_config(self, kwargs)
self.epsilon = 1.0 / self.density
Mobject.__init__(self, **kwargs)
def __init__(self, filename, **kwargs):
path = get_full_raster_image_path(filename)
self.image = Image.open(path)
self.texture_path = path
Mobject.__init__(self, **kwargs)
def __init__(self, value=0, **kwargs):
Mobject.__init__(self, **kwargs)
self.points = np.zeros((1, 3))
self.set_value(value)
def __init__(self, mobject):
Mobject.__init__(self)
self.expand(mobject)
def __init__(self, **kwargs):
digest_config(self, kwargs)
self.epsilon = 1.0 / self.density
Mobject.__init__(self, **kwargs)
