002 • Response

puzzle_id:: 3-1e0a9b12
description:: example_2
timestamp:: 24.356.195518
call_count:: 2
model:: gemini-2.0-flash-thinking-exp-1219

The user wants me to analyze a new example pair from the same ARC task. I need to follow the same process as before: describe the input and output grids, use code to analyze them, and develop a natural language program explaining the transformation.

Plan:

Describe the input and output grids.
Use code to analyze the grids and identify differences.
Formulate a natural language program.
Create YAML blocks to summarize the input and the differences between input and output.

Review Example

The input grid is a 6x6 grid. There are yellow (4) pixels in the first column of the last three rows. There is an orange (7) pixel in the third column of the last two rows. There is an azure (8) pixel in the fourth column of the second row and the fourth column of the fifth row. There is a maroon (9) pixel in the last column of the first row.

The output grid is also a 6x6 grid. The yellow (4) and orange (7) pixels in the last three rows are in the same positions as the input grid. The azure (8) pixel from the second row is no longer present, and the azure (8) pixel from the fifth row has moved to the fifth column of the last row. The maroon (9) pixel from the first row has moved to the last column of the last row.

import numpy as np

input_grid = np.array([[0, 0, 0, 0, 0, 9],
                       [0, 0, 0, 8, 0, 0],
                       [0, 0, 0, 0, 0, 0],
                       [4, 0, 0, 0, 0, 0],
                       [4, 0, 7, 8, 0, 0],
                       [4, 0, 7, 0, 0, 0]])

output_grid = np.array([[0, 0, 0, 0, 0, 0],
                        [0, 0, 0, 0, 0, 0],
                        [0, 0, 0, 0, 0, 0],
                        [4, 0, 0, 0, 0, 0],
                        [4, 0, 7, 8, 0, 0],
                        [4, 0, 7, 8, 0, 9]])

input_colors, input_counts = np.unique(input_grid, return_counts=True)
output_colors, output_counts = np.unique(output_grid, return_counts=True)

print("Input grid shape:", input_grid.shape)
print("Input color counts:", dict(zip(input_colors, input_counts)))
print("Output grid shape:", output_grid.shape)
print("Output color counts:", dict(zip(output_colors, output_counts)))

changed_pixels = np.where(input_grid != output_grid)
print("Indices of changed pixels (input coordinates):", list(zip(changed_pixels[0], changed_pixels[1])))

input_color_coords = {}
for color in np.unique(input_grid):
    coords = np.where(input_grid == color)
    input_color_coords[color] = list(zip(coords[0], coords[1]))
print("Input color coordinates:", input_color_coords)

output_color_coords = {}
for color in np.unique(output_grid):
    coords = np.where(output_grid == color)
    output_color_coords[color] = list(zip(coords[0], coords[1]))
print("Output color coordinates:", output_color_coords)

input:
  width: 6
  height: 6
  colors:
    0: 28
    9: 1
    8: 2
    4: 3
    7: 2
  objects:
    - size: 1, position: (0, 5), color: maroon
    - size: 1, position: (1, 3), color: azure
    - size: 1, position: (4, 3), color: azure
    - size: 1, position: (3, 0), color: yellow
    - size: 1, position: (4, 0), color: yellow
    - size: 1, position: (5, 0), color: yellow
    - size: 1, position: (4, 2), color: orange
    - size: 1, position: (5, 2), color: orange

differences:
  cells_changed: 3
  colors_changed:
    - from maroon at (0, 5) to white at (0, 5)
    - from azure at (1, 3) to white at (1, 3)
    - from white at (5, 4) to azure at (5, 4)
    - from white at (5, 5) to maroon at (5, 5)

  transformation:
    - The maroon pixel at (0, 5) moved to (5, 5).
    - The azure pixel at (1, 3) disappeared.
    - The azure pixel at (4, 3) moved to (5, 4).

Natural Language Program:

Create an output grid with the same dimensions as the input grid, initialized with the input grid.
Identify the maroon pixel in the input grid. Move this pixel to the last column of the last row in the output grid.
Identify all azure pixels in the input grid. Move these pixels to the last row of the output grid, placing them from left to right in the available empty cells.

time
response time	total elapsed
10.895	48.612

usage
token type	call count	total used
Prompt	8202	10820
Response	1324	6263
Total	9526	17083
Cached	0	0