

from typing import Dict

import numpy as np
import torch

from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map

def 			lowerCamelCase__			(       _a):
	SCREAMING_SNAKE_CASE :   Any					  =							[]
	SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							[]
	SCREAMING_SNAKE_CASE :   str					  =							[]

	for rt in rc.restypes:
		SCREAMING_SNAKE_CASE :   Tuple					  =							rc.restype_name_to_atomaa_names[rc.restype_atoa[rt]]
		restype_atomaa_to_atomaa_list.append([(rc.atom_order[name] if name else 0) for name in atom_names])
		SCREAMING_SNAKE_CASE :   Dict					  =							{name: i for i, name in enumerate(_a)}
		restype_atomaa_to_atomaa_list.append(
		    [(atom_name_to_idxaa[name] if name in atom_name_to_idxaa else 0) for name in rc.atom_types])

		restype_atomaa_mask_list.append([(1.0 if name else 0.0) for name in atom_names])

	# Add dummy mapping for restype 'UNK'
	restype_atomaa_to_atomaa_list.append([0] * 14)
	restype_atomaa_to_atomaa_list.append([0] * 37)
	restype_atomaa_mask_list.append([0.0] * 14)

	SCREAMING_SNAKE_CASE :   Tuple					  =							torch.tensor(
	    _a				,      dtype=torch.intaa				,      device=protein["aatype"].device				,      )
	SCREAMING_SNAKE_CASE :   List[Any]					  =							torch.tensor(
	    _a				,      dtype=torch.intaa				,      device=protein["aatype"].device				,      )
	SCREAMING_SNAKE_CASE :   List[str]					  =							torch.tensor(
	    _a				,      dtype=torch.floataa				,      device=protein["aatype"].device				,      )
	SCREAMING_SNAKE_CASE :   Optional[Any]					  =							protein["aatype"].to(torch.long)

	# create the mapping for (residx, atom14) --> atom37, i.e. an array
	# with shape (num_res, 14) containing the atom37 indices for this protein
	SCREAMING_SNAKE_CASE :   Any					  =							restype_atomaa_to_atomaa[protein_aatype]
	SCREAMING_SNAKE_CASE :   int					  =							restype_atomaa_mask[protein_aatype]

	SCREAMING_SNAKE_CASE :   List[str]					  =							residx_atomaa_mask
	SCREAMING_SNAKE_CASE :   Tuple					  =							residx_atomaa_to_atomaa.long()

	# create the gather indices for mapping back
	SCREAMING_SNAKE_CASE :   str					  =							restype_atomaa_to_atomaa[protein_aatype]
	SCREAMING_SNAKE_CASE :   str					  =							residx_atomaa_to_atomaa.long()

	# create the corresponding mask
	SCREAMING_SNAKE_CASE :   List[Any]					  =							torch.zeros([21, 37]				,      dtype=torch.floataa				,      device=protein["aatype"].device)
	for restype, restype_letter in enumerate(rc.restypes):
		SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							rc.restype_atoa[restype_letter]
		SCREAMING_SNAKE_CASE :   Optional[int]					  =							rc.residue_atoms[restype_name]
		for atom_name in atom_names:
			SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							rc.atom_order[atom_name]
			SCREAMING_SNAKE_CASE :   Optional[Any]					  =							1

	SCREAMING_SNAKE_CASE :   Optional[int]					  =							restype_atomaa_mask[protein_aatype]
	SCREAMING_SNAKE_CASE :   int					  =							residx_atomaa_mask

	return protein


def 			lowerCamelCase__			(       _a):
	SCREAMING_SNAKE_CASE :   List[Any]					  =							tree_map(lambda _a: torch.tensor(_a				,      device=batch["aatype"].device)				,      _a				,      np.ndarray)
	SCREAMING_SNAKE_CASE :   int					  =							tensor_tree_map(lambda _a: np.array(_a)				,      make_atomaa_masks(_a))
	return out


from __future__ import annotations

import math






class _UpperCamelCase				:
			'''simple docstring'''







			def __init__(      self				:			Dict   ,   a				:			int						)				->							None:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Dict					  =							size
				# approximate the overall size of segment tree with given value
				SCREAMING_SNAKE_CASE :   Any					  =							[0 for i in range(0   ,   4 * size						)]
				# create array to store lazy update
				SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							[0 for i in range(0   ,   4 * size						)]
				SCREAMING_SNAKE_CASE :   Any					  =							[0 for i in range(0   ,   4 * size						)]  # flag for lazy update
			def 				__UpperCamelCase			(      self				:			Tuple   ,   a				:			int						)				->							int:

				"""simple docstring"""

				return idx * 2
			def 				__UpperCamelCase			(      self				:			str   ,   a				:			int						)				->							int:

				"""simple docstring"""

				return idx * 2 + 1
			def 				__UpperCamelCase			(      self				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			list[int]						)				->							None:

				"""simple docstring"""

				if left_element == right_element:
					SCREAMING_SNAKE_CASE :   int					  =							a[left_element - 1]
				else:
					SCREAMING_SNAKE_CASE :   Optional[int]					  =							(left_element + right_element) // 2
					self.build(self.left(a						)   ,   a   ,   a   ,   a						)
					self.build(self.right(a						)   ,   mid + 1   ,   a   ,   a						)
					SCREAMING_SNAKE_CASE :   List[Any]					  =							max(
					    self.segment_tree[self.left(a						)]   ,   self.segment_tree[self.right(a						)]						)
			def 				__UpperCamelCase			(      self				:			Optional[Any]   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int						)				->							bool:

				"""simple docstring"""

				if self.flag[idx] is True:
					SCREAMING_SNAKE_CASE :   Any					  =							self.lazy[idx]
					SCREAMING_SNAKE_CASE :   List[str]					  =							False
					if left_element != right_element:
						SCREAMING_SNAKE_CASE :   Optional[Any]					  =							self.lazy[idx]
						SCREAMING_SNAKE_CASE :   int					  =							self.lazy[idx]
						SCREAMING_SNAKE_CASE :   Any					  =							True
						SCREAMING_SNAKE_CASE :   List[Any]					  =							True

				if right_element < a or left_element > b:
					return True
				if left_element >= a and right_element <= b:
					SCREAMING_SNAKE_CASE :   Optional[Any]					  =							val
					if left_element != right_element:
						SCREAMING_SNAKE_CASE :   str					  =							val
						SCREAMING_SNAKE_CASE :   str					  =							val
						SCREAMING_SNAKE_CASE :   Tuple					  =							True
						SCREAMING_SNAKE_CASE :   Optional[Any]					  =							True
					return True
				SCREAMING_SNAKE_CASE :   int					  =							(left_element + right_element) // 2
				self.update(self.left(a						)   ,   a   ,   a   ,   a   ,   a   ,   a						)
				self.update(self.right(a						)   ,   mid + 1   ,   a   ,   a   ,   a   ,   a						)
				SCREAMING_SNAKE_CASE :   Optional[int]					  =							max(
				    self.segment_tree[self.left(a						)]   ,   self.segment_tree[self.right(a						)]						)
				return True
			def 				__UpperCamelCase			(      self				:			Dict   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int						)				->							int | float:

				"""simple docstring"""

				if self.flag[idx] is True:
					SCREAMING_SNAKE_CASE :   int					  =							self.lazy[idx]
					SCREAMING_SNAKE_CASE :   List[Any]					  =							False
					if left_element != right_element:
						SCREAMING_SNAKE_CASE :   Optional[Any]					  =							self.lazy[idx]
						SCREAMING_SNAKE_CASE :   Optional[Any]					  =							self.lazy[idx]
						SCREAMING_SNAKE_CASE :   Optional[Any]					  =							True
						SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							True
				if right_element < a or left_element > b:
					return -math.inf
				if left_element >= a and right_element <= b:
					return self.segment_tree[idx]
				SCREAMING_SNAKE_CASE :   Dict					  =							(left_element + right_element) // 2
				SCREAMING_SNAKE_CASE :   Tuple					  =							self.query(self.left(a						)   ,   a   ,   a   ,   a   ,   a						)
				SCREAMING_SNAKE_CASE :   Tuple					  =							self.query(self.right(a						)   ,   mid + 1   ,   a   ,   a   ,   a						)
				return max(a   ,   a						)






			def __str__(      self				:			str						)				->							str:

				"""simple docstring"""

				return str([self.query(1   ,   1   ,   self.size   ,   a   ,   a						) for i in range(1   ,   self.size + 1						)]						)


if __name__ == "__main__":
			a_      =     [1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
			a_      =     15
			a_      =     SegmentTree(size)
			segt.build(1, 1, size, A)
			print(segt.query(1, 1, size, 4, 6))
			print(segt.query(1, 1, size, 7, 11))
			print(segt.query(1, 1, size, 7, 12))
			segt.update(1, 1, size, 1, 3, 111)
			print(segt.query(1, 1, size, 1, 15))
			segt.update(1, 1, size, 7, 8, 235)
			print(segt)