

"""simple docstring"""




SCREAMING_SNAKE_CASE_  :      List[Any]							=      10**8



def 						UpperCAmelCase__ (					A__ )   ->   bool:




   """simple docstring"""
   if n % 10 == 0:
      return False
   lowerCamelCase__						       =      str(A__ )
   return s == s[::-1]



def 						UpperCAmelCase__ (					)   ->   int:




   """simple docstring"""
   lowerCamelCase__						       =      set()
   lowerCamelCase__						       =      1
   lowerCamelCase__						       =      5
   while sum_squares < LIMIT:
      lowerCamelCase__						       =      first_square + 1
      while sum_squares < LIMIT:
         if is_palindrome(A__ ):
            answer.add(A__ )
         last_square += 1
         sum_squares += last_square**2
      first_square += 1
      lowerCamelCase__						       =      first_square**2 + (first_square + 1) ** 2

   return sum(A__ )


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







"""simple docstring"""




import numpy as np
from numpy import floataa
from numpy.typing import NDArray



def 						UpperCAmelCase__ (					A__						,     A__ )   ->   NDArray[floataa]:




   """simple docstring"""
   lowerCamelCase__       ,							lowerCamelCase__						       =      np.shape(A__ )

   lowerCamelCase__						       =      np.zeros((rows, 1)						,     dtype=A__ )
   for row in reversed(range(A__ ) ):
      lowerCamelCase__						       =      0
      for col in range(row + 1						,     A__ ):
         total += coefficients[row, col] * x[col]

      lowerCamelCase__						       =      (vector[row] - total) / coefficients[row, row]

   return x



def 						UpperCAmelCase__ (					A__						,     A__ )   ->   NDArray[floataa]:




   """simple docstring"""
   lowerCamelCase__       ,							lowerCamelCase__						       =      np.shape(A__ )
   if rows != columns:
      return np.array(()						,     dtype=A__ )

   # augmented matrix
   lowerCamelCase__						       =      np.concatenate((coefficients, vector)						,     axis=1 )
   lowerCamelCase__						       =      augmented_mat.astype("float64" )

   # scale the matrix leaving it triangular
   for row in range(rows - 1 ):
      lowerCamelCase__						       =      augmented_mat[row, row]
      for col in range(row + 1						,     A__ ):
         lowerCamelCase__						       =      augmented_mat[col, row] / pivot
         augmented_mat[col, :] -= factor * augmented_mat[row, :]

   lowerCamelCase__						       =      retroactive_resolution(
       augmented_mat[:, 0:columns]						,     augmented_mat[:, columns : columns + 1] )

   return x


if __name__ == "__main__":
     import doctest

     doctest.testmod()




