001 • Response

puzzle_id:: 4-0d3d703e
description:: example_1
timestamp:: 24.357.081407
call_count:: 1
model:: gemini-2.0-flash-thinking-exp-1219

The user wants me to analyze the first example of an ARC task and describe the transformation from the input to the output grid. I need to observe the grids, identify differences, and then formulate a natural language program that explains the transformation rule.

Plan:

Describe the input and output grids.
Use code to analyze the grids and identify specific changes.
Document the findings in YAML format.
Develop a natural language program to describe the transformation.

Okay, let’s examine the first example pair.

The input grid is a 3x3 grid. The leftmost column is green (3), the middle column is blue (1), and the rightmost column is red (2).

The output grid is also a 3x3 grid. The leftmost column is yellow (4), the middle column is gray (5), and the rightmost column is magenta (6).

import numpy as np

input_grid = np.array([[3, 1, 2], [3, 1, 2], [3, 1, 2]])
output_grid = np.array([[4, 5, 6], [4, 5, 6], [4, 5, 6]])

input_colors = {}
for row in input_grid:
    for pixel in row:
        color = int(pixel)
        input_colors[color] = input_colors.get(color, 0) + 1

output_colors = {}
for row in output_grid:
    for pixel in row:
        color = int(pixel)
        output_colors[color] = output_colors.get(color, 0) + 1

changed_pixels = []
for r in range(input_grid.shape[0]):
    for c in range(input_grid.shape[1]):
        if input_grid[r, c] != output_grid[r, c]:
            changed_pixels.append(((r, c), int(input_grid[r, c]), int(output_grid[r, c])))

print("Input grid shape:", input_grid.shape)
print("Output grid shape:", output_grid.shape)
print("Input color counts:", input_colors)
print("Output color counts:", output_colors)
print("Changed pixels (coordinates, old_color, new_color):", changed_pixels)

input:
  width: 3
  height: 3
  colors:
    3: 3 (green)
    1: 3 (blue)
    2: 3 (red)
  objects:
    - size: 3, position: column 1, color: green
    - size: 3, position: column 2, color: blue
    - size: 3, position: column 3, color: red

differences:
  cells_changed: 9
  colors_changed:
    green to yellow in the first column
    blue to gray in the second column
    red to magenta in the third column
  transformation:
    - Each column's color is transformed into a new color.
    - The transformation seems to be consistent across all rows within a column.

Natural Language Program:

The input grid is a 3x3 grid with three distinct vertical columns of color. The leftmost column is entirely green, the middle column is entirely blue, and the rightmost column is entirely red.

To create the output grid, initialize a new 3x3 grid.

Determine the new color for each column based on the input column’s color. The green color in the first column of the input is transformed to yellow in the first column of the output. The blue color in the second column of the input is transformed to gray in the second column of the output. The red color in the third column of the input is transformed to magenta in the third column of the output.

Assign the transformed color to every pixel within the corresponding column in the output grid.

time
response time	total elapsed
7.264	7.322

usage
token type	call count	total used
Prompt	2135	2135
Response	887	887
Total	3022	3022
Cached	0	0