


from __future__ import annotations

import time
from collections.abc import Sequence
from random import randint

from matplotlib import pyplot as plt



def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase     ):
							if not arr:
														return None, None, 0
							if low == high:
														return low, high, arr[low]

							__snake_case		:      Optional[int]										=       (low + high) // 2
							__snake_case		:      Union[str, Any]										=       max_subarray(__lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase     )
							__snake_case		:      int										=       max_subarray(__lowerCamelCase							,     mid + 1							,     __lowerCamelCase     )
							__snake_case		:      List[Any]										=       max_cross_sum(__lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase     )
							if left_sum >= right_sum and left_sum >= cross_sum:
														return left_low, left_high, left_sum
							elif right_sum >= left_sum and right_sum >= cross_sum:
														return right_low, right_high, right_sum
							return cross_left, cross_right, cross_sum



def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase     ):
							__snake_case		:      int										=       float("-inf"     ), -1
							__snake_case		:      Tuple										=       float("-inf"     ), -1

							__snake_case		:      int | float										=       0
							for i in range(__lowerCamelCase							,     low - 1							,     -1     ):
														summ += arr[i]
														if summ > left_sum:
																					__snake_case		:      int										=       summ
																					__snake_case		:      str										=       i

							__snake_case		:      Dict										=       0
							for i in range(mid + 1							,     high + 1     ):
														summ += arr[i]
														if summ > right_sum:
																					__snake_case		:      Any										=       summ
																					__snake_case		:      Dict										=       i

							return max_left, max_right, (left_sum + right_sum)



def     lowerCAmelCase_					( __lowerCamelCase     ):
							__snake_case		:      Union[str, Any]										=       [randint(1							,     __lowerCamelCase     ) for _ in range(__lowerCamelCase     )]
							__snake_case		:      Dict										=       time.time()
							max_subarray(__lowerCamelCase							,     0							,     input_size - 1     )
							__snake_case		:      Dict										=       time.time()
							return end - start



def     lowerCAmelCase_					( ):
							__snake_case		:      Dict										=       [1_0, 1_0_0, 1_0_0_0, 1_0_0_0_0, 5_0_0_0_0, 1_0_0_0_0_0, 2_0_0_0_0_0, 3_0_0_0_0_0, 4_0_0_0_0_0, 5_0_0_0_0_0]
							__snake_case		:      Optional[Any]										=       [time_max_subarray(__lowerCamelCase     ) for input_size in input_sizes]
							print("No of Inputs\t\tTime Taken"     )
							for input_size, runtime in zip(__lowerCamelCase							,     __lowerCamelCase     ):
														print(__lowerCamelCase							,     "\t\t"							,     __lowerCamelCase     )
							plt.plot(__lowerCamelCase							,     __lowerCamelCase     )
							plt.xlabel("Number of Inputs"     )
							plt.ylabel("Time taken in seconds"     )
							plt.show()


if __name__ == "__main__":
			from doctest import testmod

			testmod()





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_					( __lowerCamelCase     ):
							__snake_case		:      Any										=       []
							__snake_case		:      Optional[Any]										=       []
							__snake_case		:      List[Any]										=       []

							for rt in rc.restypes:
														__snake_case		:      Any										=       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]     )
														__snake_case		:      Tuple										=       {name: i for i, name in enumerate(__lowerCamelCase     )}
														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] * 1_4     )
							restype_atomaa_to_atomaa_list.append([0] * 3_7     )
							restype_atomaa_mask_list.append([0.0] * 1_4     )

							__snake_case		:      int										=       torch.tensor(
							    __lowerCamelCase							,     dtype=torch.intaa							,     device=protein["aatype"].device							,     )
							__snake_case		:      List[str]										=       torch.tensor(
							    __lowerCamelCase							,     dtype=torch.intaa							,     device=protein["aatype"].device							,     )
							__snake_case		:      Optional[Any]										=       torch.tensor(
							    __lowerCamelCase							,     dtype=torch.floataa							,     device=protein["aatype"].device							,     )
							__snake_case		:      Optional[int]										=       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
							__snake_case		:      Optional[Any]										=       restype_atomaa_to_atomaa[protein_aatype]
							__snake_case		:      Tuple										=       restype_atomaa_mask[protein_aatype]

							__snake_case		:      Optional[Any]										=       residx_atomaa_mask
							__snake_case		:      Union[str, Any]										=       residx_atomaa_to_atomaa.long()

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

							# create the corresponding mask
							__snake_case		:      List[str]										=       torch.zeros([2_1, 3_7]							,     dtype=torch.floataa							,     device=protein["aatype"].device     )
							for restype, restype_letter in enumerate(rc.restypes     ):
														__snake_case		:      List[str]										=       rc.restype_atoa[restype_letter]
														__snake_case		:      List[Any]										=       rc.residue_atoms[restype_name]
														for atom_name in atom_names:
																					__snake_case		:      Union[str, Any]										=       rc.atom_order[atom_name]
																					__snake_case		:      str										=       1

							__snake_case		:      List[str]										=       restype_atomaa_mask[protein_aatype]
							__snake_case		:      List[str]										=       residx_atomaa_mask

							return protein







def     lowerCAmelCase_					( __lowerCamelCase     ):
							__snake_case		:      str										=       tree_map(lambda __lowerCamelCase     : torch.tensor(__lowerCamelCase							,     device=batch["aatype"].device     )							,     __lowerCamelCase							,     np.ndarray     )
							__snake_case		:      str										=       tensor_tree_map(lambda __lowerCamelCase     : np.array(__lowerCamelCase     )							,     make_atomaa_masks(__lowerCamelCase     )     )
							return out

