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492 lines
16 KiB
Python
492 lines
16 KiB
Python
from __future__ import annotations
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from abc import ABC, abstractmethod
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import itertools as it
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import re
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from manimlib.constants import WHITE
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from manimlib.mobject.svg.svg_mobject import SVGMobject
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from manimlib.mobject.types.vectorized_mobject import VGroup
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from manimlib.utils.color import color_to_rgb
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from manimlib.utils.color import rgb_to_hex
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from manimlib.utils.config_ops import digest_config
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from manimlib.utils.iterables import remove_list_redundancies
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from typing import TYPE_CHECKING
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if TYPE_CHECKING:
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from colour import Color
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from typing import Iterable, Union
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ManimColor = Union[str, Color]
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Span = tuple[int, int]
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Selector = Union[
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str,
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re.Pattern,
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tuple[Union[int, None], Union[int, None]],
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Iterable[Union[
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str,
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re.Pattern,
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tuple[Union[int, None], Union[int, None]]
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]]
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]
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class LabelledString(SVGMobject, ABC):
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"""
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An abstract base class for `MTex` and `MarkupText`
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"""
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CONFIG = {
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"height": None,
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"stroke_width": 0,
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"stroke_color": WHITE,
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"path_string_config": {
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"should_subdivide_sharp_curves": True,
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"should_remove_null_curves": True,
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},
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"base_color": WHITE,
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"isolate": [],
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}
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def __init__(self, string: str, **kwargs):
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self.string = string
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digest_config(self, kwargs)
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if self.base_color is None:
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self.base_color = WHITE
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self.base_color_int = self.color_to_int(self.base_color)
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self.string_len = len(self.string)
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self.full_span = (0, self.string_len)
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self.parse()
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super().__init__()
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self.labelled_submobject_items = [
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(submob.label, submob)
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for submob in self.submobjects
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]
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def get_file_path(self) -> str:
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return self.get_file_path_(is_labelled=False)
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def get_file_path_(self, is_labelled: bool) -> str:
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content = self.get_content(is_labelled)
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return self.get_file_path_by_content(content)
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@abstractmethod
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def get_file_path_by_content(self, content: str) -> str:
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return ""
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def generate_mobject(self) -> None:
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super().generate_mobject()
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num_labels = len(self.label_span_list)
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if num_labels:
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file_path = self.get_file_path_(is_labelled=True)
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labelled_svg = SVGMobject(file_path)
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submob_color_ints = [
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self.color_to_int(submob.get_fill_color())
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for submob in labelled_svg.submobjects
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]
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else:
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submob_color_ints = [0] * len(self.submobjects)
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if len(self.submobjects) != len(submob_color_ints):
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raise ValueError(
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"Cannot align submobjects of the labelled svg "
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"to the original svg"
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)
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unrecognized_color_ints = remove_list_redundancies(sorted(filter(
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lambda color_int: color_int > num_labels,
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submob_color_ints
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)))
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if unrecognized_color_ints:
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raise ValueError(
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"Unrecognized color label(s) detected: "
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f"{','.join(map(self.int_to_hex, unrecognized_color_ints))}"
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)
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for submob, color_int in zip(self.submobjects, submob_color_ints):
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submob.label = color_int - 1
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def parse(self) -> None:
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self.skippable_indices = self.get_skippable_indices()
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self.entity_spans = self.get_entity_spans()
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self.bracket_spans = self.get_bracket_spans()
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self.extra_isolated_items = self.get_extra_isolated_items()
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self.specified_items = self.get_specified_items()
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self.specified_spans = self.get_specified_spans()
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self.check_overlapping()
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self.label_span_list = self.get_label_span_list()
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if len(self.label_span_list) >= 16777216:
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raise ValueError("Cannot handle that many substrings")
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def copy(self):
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return self.deepcopy()
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# Toolkits
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def get_substr(self, span: Span) -> str:
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return self.string[slice(*span)]
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def match(self, pattern: str | re.Pattern, **kwargs) -> re.Pattern | None:
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if isinstance(pattern, str):
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pattern = re.compile(pattern)
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return re.compile(pattern).match(self.string, **kwargs)
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def find_spans(self, pattern: str | re.Pattern, **kwargs) -> list[Span]:
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if isinstance(pattern, str):
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pattern = re.compile(pattern)
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return [
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match_obj.span()
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for match_obj in pattern.finditer(self.string, **kwargs)
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]
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def find_indices(self, pattern: str | re.Pattern, **kwargs) -> list[int]:
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return [index for index, _ in self.find_spans(pattern, **kwargs)]
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@staticmethod
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def is_single_selector(selector: Selector) -> bool:
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if isinstance(selector, str):
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return True
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if isinstance(selector, re.Pattern):
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return True
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if isinstance(selector, tuple):
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if len(selector) == 2 and all([
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isinstance(index, int) or index is None
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for index in selector
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]):
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return True
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return False
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def find_spans_by_selector(self, selector: Selector) -> list[Span]:
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if self.is_single_selector(selector):
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selector = (selector,)
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result = []
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for sel in selector:
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if not self.is_single_selector(sel):
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raise TypeError(f"Invalid selector: '{sel}'")
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if isinstance(sel, str):
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spans = self.find_spans(re.escape(sel))
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elif isinstance(sel, re.Pattern):
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spans = self.find_spans(sel)
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else:
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span = tuple([
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(
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min(index, self.string_len)
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if index >= 0
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else max(index + self.string_len, 0)
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)
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if index is not None else default_index
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for index, default_index in zip(sel, self.full_span)
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])
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spans = [span]
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result.extend(spans)
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return sorted(filter(
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lambda span: span[0] < span[1],
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remove_list_redundancies(result)
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))
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@staticmethod
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def get_neighbouring_pairs(iterable: list) -> list[tuple]:
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return list(zip(iterable[:-1], iterable[1:]))
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@staticmethod
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def span_contains(span_0: Span, span_1: Span) -> bool:
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return span_0[0] <= span_1[0] and span_0[1] >= span_1[1]
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@staticmethod
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def get_complement_spans(
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interval_spans: list[Span], universal_span: Span
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) -> list[Span]:
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if not interval_spans:
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return [universal_span]
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span_ends, span_begins = zip(*interval_spans)
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return list(zip(
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(universal_span[0], *span_begins),
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(*span_ends, universal_span[1])
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))
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@staticmethod
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def compress_neighbours(vals: list[int]) -> list[tuple[int, Span]]:
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if not vals:
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return []
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unique_vals = [vals[0]]
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indices = [0]
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for index, val in enumerate(vals):
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if val == unique_vals[-1]:
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continue
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unique_vals.append(val)
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indices.append(index)
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indices.append(len(vals))
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spans = LabelledString.get_neighbouring_pairs(indices)
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return list(zip(unique_vals, spans))
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@staticmethod
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def generate_span_repl_dict(
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inserted_string_pairs: list[tuple[Span, tuple[str, str]]],
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repl_items: list[tuple[Span, str]]
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) -> dict[Span, str]:
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result = dict(repl_items)
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if not inserted_string_pairs:
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return result
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indices, _, _, _, inserted_strings = zip(*sorted([
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(
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item[0][flag],
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-flag,
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-item[0][1 - flag],
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(1, -1)[flag] * item_index,
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item[1][flag]
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)
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for item_index, item in enumerate(inserted_string_pairs)
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for flag in range(2)
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]))
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result.update({
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(index, index): "".join(inserted_strings[slice(*item_span)])
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for index, item_span
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in LabelledString.compress_neighbours(indices)
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})
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return result
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def get_replaced_substr(
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self, span: Span, span_repl_dict: dict[Span, str]
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) -> str:
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repl_spans = sorted(filter(
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lambda repl_span: self.span_contains(span, repl_span),
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span_repl_dict.keys()
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))
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if not all(
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span_0[1] <= span_1[0]
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for span_0, span_1 in self.get_neighbouring_pairs(repl_spans)
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):
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raise ValueError("Overlapping replacement")
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pieces = [
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self.get_substr(piece_span)
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for piece_span in self.get_complement_spans(repl_spans, span)
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]
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repl_strs = [span_repl_dict[repl_span] for repl_span in repl_spans]
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repl_strs.append("")
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return "".join(it.chain(*zip(pieces, repl_strs)))
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@staticmethod
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def color_to_int(color: ManimColor) -> int:
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hex_code = rgb_to_hex(color_to_rgb(color))
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return int(hex_code[1:], 16)
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@staticmethod
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def int_to_hex(rgb_int: int) -> str:
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return "#{:06x}".format(rgb_int).upper()
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# Parsing
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@abstractmethod
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def get_skippable_indices(self) -> list[int]:
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return []
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@staticmethod
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def shrink_span(span: Span, skippable_indices: list[int]) -> Span:
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span_begin, span_end = span
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while span_begin in skippable_indices:
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span_begin += 1
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while span_end - 1 in skippable_indices:
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span_end -= 1
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return (span_begin, span_end)
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@abstractmethod
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def get_entity_spans(self) -> list[Span]:
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return []
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@abstractmethod
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def get_bracket_spans(self) -> list[Span]:
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return []
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@abstractmethod
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def get_extra_isolated_items(self) -> list[tuple[Span, dict[str, str]]]:
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return []
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def get_specified_items(self) -> list[tuple[Span, dict[str, str]]]:
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span_items = list(it.chain(
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self.extra_isolated_items,
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[
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(span, {})
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for span in self.find_spans_by_selector(self.isolate)
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]
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))
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result = []
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for span, attr_dict in span_items:
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shrinked_span = self.shrink_span(span, self.skippable_indices)
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if shrinked_span[0] >= shrinked_span[1]:
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continue
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if any([
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entity_span[0] < index < entity_span[1]
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for index in shrinked_span
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for entity_span in self.entity_spans
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]):
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continue
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result.append((shrinked_span, attr_dict))
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return result
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def get_specified_spans(self) -> list[Span]:
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return remove_list_redundancies([
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span for span, _ in self.specified_items
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])
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def check_overlapping(self) -> None:
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spans = remove_list_redundancies(list(it.chain(
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self.specified_spans,
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self.bracket_spans
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)))
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for span_0, span_1 in it.product(spans, repeat=2):
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if not span_0[0] < span_1[0] < span_0[1] < span_1[1]:
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continue
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raise ValueError(
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"Partially overlapping substrings detected: "
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f"'{self.get_substr(span_0)}' and '{self.get_substr(span_1)}'"
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)
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@abstractmethod
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def get_label_span_list(self) -> list[Span]:
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return []
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@abstractmethod
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def get_content(self, is_labelled: bool) -> str:
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return ""
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# Selector
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@abstractmethod
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def get_cleaned_substr(self, span: Span) -> str:
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return ""
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def get_group_part_items(self) -> list[tuple[str, VGroup]]:
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if not self.labelled_submobject_items:
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return []
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labels, labelled_submobjects = zip(*self.labelled_submobject_items)
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group_labels, labelled_submob_spans = zip(
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*self.compress_neighbours(labels)
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)
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ordered_spans = [
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self.label_span_list[label] if label != -1 else self.full_span
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for label in group_labels
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]
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interval_spans = [
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(
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next_span[0]
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if self.span_contains(prev_span, next_span)
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else prev_span[1],
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prev_span[1]
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if self.span_contains(next_span, prev_span)
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else next_span[0]
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)
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for prev_span, next_span in self.get_neighbouring_pairs(
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ordered_spans
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)
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]
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group_substrs = [
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self.get_cleaned_substr(span) if span[0] < span[1] else ""
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for span in self.get_complement_spans(
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interval_spans, (ordered_spans[0][0], ordered_spans[-1][1])
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)
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]
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submob_groups = VGroup(*[
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VGroup(*labelled_submobjects[slice(*submob_span)])
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for submob_span in labelled_submob_spans
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])
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return list(zip(group_substrs, submob_groups))
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def get_specified_part_items(self) -> list[tuple[str, VGroup]]:
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return [
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(
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self.get_substr(span),
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self.select_part_by_span(span, substring=False)
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)
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for span in self.specified_spans
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]
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def find_span_components(
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self, custom_span: Span, substring: bool = True
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) -> list[Span]:
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shrinked_span = self.shrink_span(custom_span, self.skippable_indices)
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if shrinked_span[0] >= shrinked_span[1]:
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return []
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if substring:
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indices = remove_list_redundancies(list(it.chain(
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self.full_span,
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*self.label_span_list
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)))
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span_begin = max(filter(
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lambda index: index <= shrinked_span[0], indices
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))
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span_end = min(filter(
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lambda index: index >= shrinked_span[1], indices
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))
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else:
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span_begin, span_end = shrinked_span
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span_choices = sorted(filter(
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lambda span: self.span_contains((span_begin, span_end), span),
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self.label_span_list
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))
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# Choose spans that reach the farthest.
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span_choices_dict = dict(span_choices)
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result = []
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while span_begin < span_end:
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if span_begin not in span_choices_dict.keys():
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span_begin += 1
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continue
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next_begin = span_choices_dict[span_begin]
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result.append((span_begin, next_begin))
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span_begin = next_begin
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return result
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def select_part_by_span(self, custom_span: Span, **kwargs) -> VGroup:
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labels = [
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label for label, span in enumerate(self.label_span_list)
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if any([
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self.span_contains(span_component, span)
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for span_component in self.find_span_components(
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custom_span, **kwargs
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)
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])
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]
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return VGroup(*[
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submob for label, submob in self.labelled_submobject_items
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if label in labels
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])
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def select_parts(self, selector: Selector, **kwargs) -> VGroup:
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return VGroup(*filter(
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lambda part: part.submobjects,
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[
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self.select_part_by_span(span, **kwargs)
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for span in self.find_spans_by_selector(selector)
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]
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))
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def select_part(
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self, selector: Selector, index: int = 0, **kwargs
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) -> VGroup:
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return self.select_parts(selector, **kwargs)[index]
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def set_parts_color(
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self, selector: Selector, color: ManimColor, **kwargs
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):
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self.select_parts(selector, **kwargs).set_color(color)
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return self
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def set_parts_color_by_dict(
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self, color_map: dict[Selector, ManimColor], **kwargs
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):
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for selector, color in color_map.items():
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self.set_parts_color(selector, color, **kwargs)
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return self
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def get_string(self) -> str:
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return self.string
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