001 • Response

puzzle_id:: 4-0d3d703e
description:: example_1
timestamp:: 24.329.071439
call_count:: 1
model:: models/gemini-exp-1114

This is a very straightforward transformation. The input grid has three columns with each column containing a different color. The output grid is the same size and the cell colors are changed. There appears to be a one-to-one mapping between input colors and output colors, 3->4, 1->5, 2->6.

input:
  width: 3
  height: 3
  colors:
    - 3: 3
    - 1: 3
    - 2: 3
  objects:
    - three columns of color
output:
  width: 3
  height: 3
  colors:
    - 4: 3
    - 5: 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 3->4, 1->5, 2->6

code_execution:

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]])

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(3): np.int64(4), np.int64(1): np.int64(5), np.int64(2): np.int64(6)}

The code confirms the color mapping speculation.

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 3->4, 1->5, 2->6.

time
response time	total elapsed
28.169	28.23

usage
token type	call count	total used
Prompt	2156	2156
Response	55	55
Total	2211	2211
Cached	0	0