def create_axis(self, range_terms: Sequence[float], axis_config: dict[str],
length: float) -> NumberLine:
new_config = merge_dicts_recursively(self.axis_config, axis_config)
new_config["width"] = length
axis = NumberLine(range_terms, **new_config)
axis.shift(-axis.n2p(0))
return axis
def get_lines_parallel_to_axis(self, axis1: NumberLine,
axis2: NumberLine) -> tuple[VGroup, VGroup]:
freq = axis2.x_step
ratio = self.faded_line_ratio
line = Line(axis1.get_start(), axis1.get_end())
dense_freq = (1 + ratio)
step = (1 / dense_freq) * freq
lines1 = VGroup()
lines2 = VGroup()
inputs = np.arange(axis2.x_min, axis2.x_max + step, step)
for i, x in enumerate(inputs):
new_line = line.copy()
new_line.shift(axis2.n2p(x) - axis2.n2p(0))
if i % (1 + ratio) == 0:
lines1.add(new_line)
else:
lines2.add(new_line)
return lines1, lines2
def create_axis(self, *args):
if args[2] is not None and not isinstance(args[2], (int, float)):
min_val, max_val, axis_config = args
new_config = merge_dicts_recursively(
self.number_line_config,
{
"x_min": min_val,
"x_max": max_val
},
axis_config,
)
return NumberLine(**new_config)
else:
range_terms, axis_config, length = args
new_config = merge_dicts_recursively(self.axis_config, axis_config)
new_config["width"] = length
axis = NumberLine(range_terms, **new_config)
axis.shift(-axis.n2p(0))
return axis
def create_axis(self, range_terms, axis_config, length):
new_config = merge_dicts_recursively(self.axis_config, axis_config)
new_config["width"] = length
axis = NumberLine(range_terms, **new_config)
axis.shift(-axis.n2p(0))
return axis
