004 • Response

puzzle_id:: 4-0d3d703e
description:: example_4
timestamp:: 24.329.071439
call_count:: 4
model:: models/gemini-exp-1114

This example follows the same pattern as the previous three, with each column containing a single color. The output grid also has three columns with each column a different single color.

input:
  width: 3
  height: 3
  colors:
    - 9: 3
    - 4: 3
    - 2: 3
  objects:
    - three columns of color
output:
  width: 3
  height: 3
  colors:
    - 8: 3
    - 3: 3
    - 6: 3
  objects:
    - three columns of color
differences:
  cells_changed: 9
  colors_changed: all colors changed to a new color
transformation:
  color value mapping 9->8, 4->3, 2->6

code_execution:

import numpy as np
input_grid = np.array([[9, 4, 2], [9, 4, 2], [9, 4, 2]])
output_grid = np.array([[8, 3, 6], [8, 3, 6], [8, 3, 6]])

def find_color_mapping(in_grid, out_grid):
    color_map = {}
    for i in range(in_grid.shape[0]):
        for j in range(in_grid.shape[1]):
            color_map[in_grid[i, j]] = out_grid[i, j]
    return color_map

color_map = find_color_mapping(input_grid, output_grid)
print(color_map)

code_execution_result: 1

{np.int64(9): np.int64(8), np.int64(4): np.int64(3), np.int64(2): np.int64(6)}

The code confirms the color mapping speculation: 9->8, 4->3, 2->6.

The natural language program for this transformation is to map the color values in the input grid to the specified color values in the output grid according to the mapping 9->8, 4->3, 2->6.

time
response time	total elapsed
18.661	85.064

usage
token type	call count	total used
Prompt	5528	15388
Response	520	1619
Total	6048	17007
Cached	0	0