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Problem C. Minimum Path in Triangle | Solutions
Dynamic Programming
course content

Contenido del Curso

Dynamic Programming

Dynamic Programming

1. Intro to Dynamic Programming
2. Problems
3. Solutions

Problem C. Minimum Path in Triangle

The key to the solution is forming all possible minimum-cost paths from top to bottom row. You can not be sure which one will have minimum cost, so let's traverse a triangle and update values in the cells:

  • triangle[i][j] += min(triangle[i-1][j-1], triangle[i-1][j]: thats how you can reach cell [i, j]` with min cost
  • triangle[i][0] += triangle[i-1][0], triangle[i][i-1] += triangle[i-1][i-1] : extreme cases (number of columns in each row is equal to number of row).

After updating, choose the minimum path cost, which is in the last row.

1234567891011121314151617181920
def minPath(triangle): for i in range(1, len(triangle)): for j in range(i+1): small = 10000000 if j > 0: small = triangle[i-1][j-1] if j < i: small = min(small, triangle[i-1][j]) triangle[i][j] += small return min(triangle[-1]) triangle = [[90], [72, 6], [3, 61, 51], [90, 70, 23, 100], [79, 92, 72, 14, 1], [7, 97, 29, 100, 93, 93], [52, 95, 21, 36, 69, 69, 14], [33, 82, 20, 37, 79, 83, 21, 45]] print(minPath(triangle))
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¿Todo estuvo claro?

Sección 3. Capítulo 3
toggle bottom row

Problem C. Minimum Path in Triangle

The key to the solution is forming all possible minimum-cost paths from top to bottom row. You can not be sure which one will have minimum cost, so let's traverse a triangle and update values in the cells:

  • triangle[i][j] += min(triangle[i-1][j-1], triangle[i-1][j]: thats how you can reach cell [i, j]` with min cost
  • triangle[i][0] += triangle[i-1][0], triangle[i][i-1] += triangle[i-1][i-1] : extreme cases (number of columns in each row is equal to number of row).

After updating, choose the minimum path cost, which is in the last row.

1234567891011121314151617181920
def minPath(triangle): for i in range(1, len(triangle)): for j in range(i+1): small = 10000000 if j > 0: small = triangle[i-1][j-1] if j < i: small = min(small, triangle[i-1][j]) triangle[i][j] += small return min(triangle[-1]) triangle = [[90], [72, 6], [3, 61, 51], [90, 70, 23, 100], [79, 92, 72, 14, 1], [7, 97, 29, 100, 93, 93], [52, 95, 21, 36, 69, 69, 14], [33, 82, 20, 37, 79, 83, 21, 45]] print(minPath(triangle))
copy

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Sección 3. Capítulo 3
toggle bottom row

Problem C. Minimum Path in Triangle

The key to the solution is forming all possible minimum-cost paths from top to bottom row. You can not be sure which one will have minimum cost, so let's traverse a triangle and update values in the cells:

  • triangle[i][j] += min(triangle[i-1][j-1], triangle[i-1][j]: thats how you can reach cell [i, j]` with min cost
  • triangle[i][0] += triangle[i-1][0], triangle[i][i-1] += triangle[i-1][i-1] : extreme cases (number of columns in each row is equal to number of row).

After updating, choose the minimum path cost, which is in the last row.

1234567891011121314151617181920
def minPath(triangle): for i in range(1, len(triangle)): for j in range(i+1): small = 10000000 if j > 0: small = triangle[i-1][j-1] if j < i: small = min(small, triangle[i-1][j]) triangle[i][j] += small return min(triangle[-1]) triangle = [[90], [72, 6], [3, 61, 51], [90, 70, 23, 100], [79, 92, 72, 14, 1], [7, 97, 29, 100, 93, 93], [52, 95, 21, 36, 69, 69, 14], [33, 82, 20, 37, 79, 83, 21, 45]] print(minPath(triangle))
copy

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

The key to the solution is forming all possible minimum-cost paths from top to bottom row. You can not be sure which one will have minimum cost, so let's traverse a triangle and update values in the cells:

  • triangle[i][j] += min(triangle[i-1][j-1], triangle[i-1][j]: thats how you can reach cell [i, j]` with min cost
  • triangle[i][0] += triangle[i-1][0], triangle[i][i-1] += triangle[i-1][i-1] : extreme cases (number of columns in each row is equal to number of row).

After updating, choose the minimum path cost, which is in the last row.

1234567891011121314151617181920
def minPath(triangle): for i in range(1, len(triangle)): for j in range(i+1): small = 10000000 if j > 0: small = triangle[i-1][j-1] if j < i: small = min(small, triangle[i-1][j]) triangle[i][j] += small return min(triangle[-1]) triangle = [[90], [72, 6], [3, 61, 51], [90, 70, 23, 100], [79, 92, 72, 14, 1], [7, 97, 29, 100, 93, 93], [52, 95, 21, 36, 69, 69, 14], [33, 82, 20, 37, 79, 83, 21, 45]] print(minPath(triangle))
copy

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
Sección 3. Capítulo 3
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
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