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https://github.com/3b1b/manim.git
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602809758e
* Enable setting points to a null list, and adding one point at a time.
* Add refresh_locked_data
* Add presenter mode to scenes with -p option
* Allow for an embed by hitting e during interaction
* Add set_min_height, etc.
* Make sure null parametric curve has at least one point
* Account for edge case where \{ is used in Tex
* Allow for logging notes in wait calls, useful for presenter mode
* Simplify choose, and add gen_choose for fractional amounts
* Default to no top on axes
* Allow match_x, match_y, etc. to take in a point
* Allow wait calls to ignore presenter mode
* Just use math.combo, no caching with choose(n, r)
* Use generator instead of list in bezier
* Bubble init_colors should override
* Account for "px" values read in from an svg
* Stop displaying when writing is happening
* Update the way Bubble override SVG colors
111 lines
3.5 KiB
Python
111 lines
3.5 KiB
Python
from isosurfaces import plot_isoline
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from manimlib.constants import *
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from manimlib.mobject.types.vectorized_mobject import VMobject
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from manimlib.utils.config_ops import digest_config
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class ParametricCurve(VMobject):
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CONFIG = {
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"t_range": [0, 1, 0.1],
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"epsilon": 1e-8,
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# TODO, automatically figure out discontinuities
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"discontinuities": [],
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"use_smoothing": True,
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}
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def __init__(self, t_func, t_range=None, **kwargs):
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digest_config(self, kwargs)
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if t_range is not None:
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self.t_range[:len(t_range)] = t_range
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# To be backward compatible with all the scenes specifying t_min, t_max, step_size
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self.t_range = [
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kwargs.get("t_min", self.t_range[0]),
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kwargs.get("t_max", self.t_range[1]),
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kwargs.get("step_size", self.t_range[2]),
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]
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self.t_func = t_func
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VMobject.__init__(self, **kwargs)
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def get_point_from_function(self, t):
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return self.t_func(t)
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def init_points(self):
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t_min, t_max, step = self.t_range
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jumps = np.array(self.discontinuities)
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jumps = jumps[(jumps > t_min) & (jumps < t_max)]
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boundary_times = [t_min, t_max, *(jumps - self.epsilon), *(jumps + self.epsilon)]
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boundary_times.sort()
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for t1, t2 in zip(boundary_times[0::2], boundary_times[1::2]):
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t_range = [*np.arange(t1, t2, step), t2]
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points = np.array([self.t_func(t) for t in t_range])
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self.start_new_path(points[0])
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self.add_points_as_corners(points[1:])
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if self.use_smoothing:
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self.make_approximately_smooth()
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if not self.has_points():
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self.set_points([self.t_func(t_min)])
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return self
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class FunctionGraph(ParametricCurve):
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CONFIG = {
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"color": YELLOW,
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"x_range": [-8, 8, 0.25],
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}
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def __init__(self, function, x_range=None, **kwargs):
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digest_config(self, kwargs)
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self.function = function
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if x_range is not None:
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self.x_range[:len(x_range)] = x_range
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def parametric_function(t):
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return [t, function(t), 0]
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super().__init__(parametric_function, self.x_range, **kwargs)
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def get_function(self):
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return self.function
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def get_point_from_function(self, x):
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return self.t_func(x)
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class ImplicitFunction(VMobject):
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CONFIG = {
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"x_range": [-FRAME_X_RADIUS, FRAME_X_RADIUS],
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"y_range": [-FRAME_Y_RADIUS, FRAME_Y_RADIUS],
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"min_depth": 5,
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"max_quads": 1500,
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"use_smoothing": True
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}
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def __init__(self, func, x_range=None, y_range=None, **kwargs):
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digest_config(self, kwargs)
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self.function = func
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super().__init__(**kwargs)
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def init_points(self):
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p_min, p_max = (
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np.array([self.x_range[0], self.y_range[0]]),
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np.array([self.x_range[1], self.y_range[1]]),
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)
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curves = plot_isoline(
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fn=lambda u: self.function(u[0], u[1]),
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pmin=p_min,
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pmax=p_max,
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min_depth=self.min_depth,
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max_quads=self.max_quads,
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) # returns a list of lists of 2D points
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curves = [
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np.pad(curve, [(0, 0), (0, 1)]) for curve in curves if curve != []
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] # add z coord as 0
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for curve in curves:
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self.start_new_path(curve[0])
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self.add_points_as_corners(curve[1:])
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if self.use_smoothing:
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self.make_smooth()
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return self
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