def get_graph(
self,
func,
color=None,
x_min=None,
x_max=None,
):
if color is None:
color = self.default_graph_colors_cycle.next()
if x_min is None:
x_min = self.x_min
if x_max is None:
x_max = self.x_max
def parameterized_function(alpha):
x = interpolate(x_min, x_max, alpha)
y = func(x)
if not np.isfinite(y):
y = self.y_max
return self.coords_to_point(x, y)
graph = ParametricFunction(
parameterized_function,
color=color,
num_anchor_points=self.num_graph_anchor_points,
)
graph.underlying_function = func
return graph
def __init__(self, mob, iterations=5, radius=10, alpha=30, camera=None):
if camera is None:
from camera.camera import Camera
camera = Camera()
arr = mob.get_binary_array()
arr = ndimage.binary_dilation(
arr,
structure=circular_binary_structure(radius),
iterations=iterations,
)
pixel_list = np.column_stack(np.where(arr == 1)).astype("float64")
concave_hull = list(
alpha_shape(pixel_list, alpha=alpha, only_outer=True))
# sort edges
for i, first in enumerate(concave_hull):
loop = True
for j, second in enumerate(concave_hull[i + 1:]):
j += i + 1
if first[1] == second[0]:
loop = False
concave_hull[i + 1], concave_hull[j] = \
concave_hull[j], concave_hull[i + 1]
if loop and i != len(concave_hull) - 1:
warnings.warn(
"the alpha shape in split into different parts. This can "
"be fixed by increasing alpha.")
print(i, len(concave_hull))
# breakpoint(context=9)
pass
temp = np.zeros((len(concave_hull) + 1, 2))
for i, pair in enumerate(concave_hull):
temp[i] = pixel_list[pair[0]]
temp[-1] = pixel_list[concave_hull[0][0]]
pixel_list = temp
point_list = np.zeros((pixel_list.shape[0], pixel_list.shape[1] + 1))
point_list[:,
0] = pixel_list[:,
0] * camera.frame_height / camera.pixel_height
point_list[:,
1] = -pixel_list[:,
1] * camera.frame_width / camera.pixel_width
# TODO: figure out optimal num_anchor_points
ParametricFunction.__init__(
self,
lambda t, point_list=point_list: point_list[int(t)],
t_min=0,
t_max=len(point_list) - 1,
scale_handle_to_anchor_distances_after_applying_functions=False,
)
self.move_to(mob.get_center())
def get_graph(self,
function,
num_graph_points=None,
x_min=None,
x_max=None,
**kwargs):
kwargs["fill_opacity"] = kwargs.get("fill_opacity", 0)
kwargs["num_anchor_points"] = \
num_graph_points or self.default_num_graph_points
x_min = x_min or self.x_min
x_max = x_max or self.x_max
graph = ParametricFunction(
lambda t: self.coords_to_point(t, function(t)),
t_min=x_min,
t_max=x_max,
**kwargs)
graph.underlying_function = function
return graph
def get_graph(
self, function, num_graph_points=None,
x_min=None,
x_max=None,
**kwargs
):
kwargs["fill_opacity"] = kwargs.get("fill_opacity", 0)
kwargs["num_anchor_points"] = \
num_graph_points or self.default_num_graph_points
x_min = x_min or self.x_min
x_max = x_max or self.x_max
graph = ParametricFunction(
lambda t: self.coords_to_point(t, function(t)),
t_min=x_min,
t_max=x_max,
**kwargs
)
graph.underlying_function = function
return graph