"""simple docstring"""
import os







def 		__a  (      )      ->Tuple:
  a__:	Any     				=      os.path.dirname(os.path.realpath(_SCREAMING_SNAKE_CASE  )  )
  a__:	Tuple     				=      os.path.join(_SCREAMING_SNAKE_CASE						,	'triangle.txt'  )

  with open(_SCREAMING_SNAKE_CASE  ) as f:
    a__:	Dict     				=      f.readlines()

  a__:	Tuple     				=      [[int(_SCREAMING_SNAKE_CASE  ) for y in x.rstrip('\r\n'  ).split(' '  )] for x in triangle]

  for i in range(1						,	len(_SCREAMING_SNAKE_CASE  )  ):
    for j in range(len(a[i]  )  ):
      a__:	Tuple     				=      a[i - 1][j] if j != len(a[i - 1]  ) else 0
      a__:	List[str]     				=      a[i - 1][j - 1] if j > 0 else 0
      a[i][j] += max(_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )
  return max(a[-1]  )


if __name__ == "__main__":
 print(solution())






import logging

# standard libraries
import sys

import numpy as np
import pytest  # type: ignore

# Custom/local libraries
from matrix import matrix_operation as matop

_snake_case				=			[[1_2, 1_0], [3, 9]]
_snake_case				=			[[3, 4], [7, 4]]
_snake_case				=			[[3, 0, 2], [2, 0, -2], [0, 1, 1]]
_snake_case				=			[[3, 0, -2], [2, 0, 2], [0, 1, 1]]
_snake_case				=			[[3, 0, 2], [2, 0, -2], [0, 1, 1], [2, 0, -2]]
_snake_case				=			[1]
_snake_case				=			[2]

_snake_case				=			logging.getLogger()
_snake_case				=			logging.DEBUG
_snake_case				=			logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







@pytest.mark.mat_ops
@pytest.mark.parametrize(
    ("mat1", "mat2")		,		[(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]			)
def 	A (		A__		,		A__			):
     if (np.array(A__			)).shape < (2, 2) or (np.array(A__			)).shape < (2, 2):
          with pytest.raises(A__			):
               logger.info(f'\n\t{test_addition.__name__} returned integer'			)
               matop.add(A__		,		A__			)
     elif (np.array(A__			)).shape == (np.array(A__			)).shape:
          logger.info(f'\n\t{test_addition.__name__} with same matrix dims'			)
          UpperCAmelCase    :					Tuple			=      (np.array(A__			) + np.array(A__			)).tolist()
          UpperCAmelCase    :					Optional[Any]			=      matop.add(A__		,		A__			)
          assert theo == act
     else:
          with pytest.raises(A__			):
               logger.info(f'\n\t{test_addition.__name__} with different matrix dims'			)
               matop.add(A__		,		A__			)







@pytest.mark.mat_ops
@pytest.mark.parametrize(
    ("mat1", "mat2")		,		[(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]			)
def 	A (		A__		,		A__			):
     if (np.array(A__			)).shape < (2, 2) or (np.array(A__			)).shape < (2, 2):
          with pytest.raises(A__			):
               logger.info(f'\n\t{test_subtraction.__name__} returned integer'			)
               matop.subtract(A__		,		A__			)
     elif (np.array(A__			)).shape == (np.array(A__			)).shape:
          logger.info(f'\n\t{test_subtraction.__name__} with same matrix dims'			)
          UpperCAmelCase    :					Tuple			=      (np.array(A__			) - np.array(A__			)).tolist()
          UpperCAmelCase    :					Optional[int]			=      matop.subtract(A__		,		A__			)
          assert theo == act
     else:
          with pytest.raises(A__			):
               logger.info(f'\n\t{test_subtraction.__name__} with different matrix dims'			)
               assert matop.subtract(A__		,		A__			)







@pytest.mark.mat_ops
@pytest.mark.parametrize(
    ("mat1", "mat2")		,		[(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]			)
def 	A (		A__		,		A__			):
     if (np.array(A__			)).shape < (2, 2) or (np.array(A__			)).shape < (2, 2):
          logger.info(f'\n\t{test_multiplication.__name__} returned integer'			)
          with pytest.raises(A__			):
               matop.add(A__		,		A__			)
     elif (np.array(A__			)).shape == (np.array(A__			)).shape:
          logger.info(f'\n\t{test_multiplication.__name__} meets dim requirements'			)
          UpperCAmelCase    :					List[str]			=      (np.matmul(A__		,		A__			)).tolist()
          UpperCAmelCase    :					int			=      matop.multiply(A__		,		A__			)
          assert theo == act
     else:
          with pytest.raises(A__			):
               logger.info(
                   f'\n\t{test_multiplication.__name__} does not meet dim requirements'			)
               assert matop.subtract(A__		,		A__			)







@pytest.mark.mat_ops
def 	A (		):
     UpperCAmelCase    :					int			=      (3.5 * np.array(A__			)).tolist()
     UpperCAmelCase    :					Optional[int]			=      matop.scalar_multiply(A__		,		3.5			)
     assert theo == act







@pytest.mark.mat_ops
def 	A (		):
     UpperCAmelCase    :					List[Any]			=      (np.identity(5			)).tolist()
     UpperCAmelCase    :					Optional[int]			=      matop.identity(5			)
     assert theo == act







@pytest.mark.mat_ops
@pytest.mark.parametrize("mat"		,		[mat_a, mat_b, mat_c, mat_d, mat_e, mat_f]			)
def 	A (		A__			):
     if (np.array(A__			)).shape < (2, 2):
          with pytest.raises(A__			):
               logger.info(f'\n\t{test_transpose.__name__} returned integer'			)
               matop.transpose(A__			)
     else:
          UpperCAmelCase    :					Dict			=      (np.transpose(A__			)).tolist()
          UpperCAmelCase    :					List[str]			=      matop.transpose(A__		,		return_map=A__			)
          assert theo == act



