003 • Response

puzzle_id:: 5-150deff5
description:: example_3
timestamp:: 24.329.071439
call_count:: 3
model:: models/gemini-exp-1114

observations This example presents a gray (5) shape that looks somewhat like a distorted “7”. The output transforms this shape by changing the horizontal parts to azure (8) and the vertical parts to red (2), maintaining the overall structure. This is consistent with the previous examples.

input:
  width: 9
  height: 8
  colors:
    - 0: 58
    - 5: 14
  objects:
    - irregular shape - distorted 7 in gray (5)

output:
  width: 9
  height: 8
  colors:
    - 0: 58
    - 2: 6
    - 8: 8
  objects:
    - irregular shape - distorted 7 with azure (8) horizontal sections and red (2) vertical sections

differences:
  cells_changed: 14
  colors_changed: gray (5) to azure (8) and red (2)
  transformation:
    - Change color of horizontal segments to azure (8)
    - Change color of vertical segments to red (2)

code_execution:

import numpy as np

input_grid = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
 [0, 5, 5, 5, 5, 5, 0, 0, 0],
 [0, 0, 0, 0, 5, 5, 0, 0, 0],
 [0, 0, 0, 5, 0, 0, 0, 0, 0],
 [0, 0, 0, 5, 5, 5, 0, 0, 0],
 [0, 0, 0, 5, 5, 5, 0, 0, 0],
 [0, 0, 0, 0, 0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0, 0, 0, 0, 0]])

output_grid = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
 [0, 2, 2, 2, 8, 8, 0, 0, 0],
 [0, 0, 0, 0, 8, 8, 0, 0, 0],
 [0, 0, 0, 2, 0, 0, 0, 0, 0],
 [0, 0, 0, 2, 8, 8, 0, 0, 0],
 [0, 0, 0, 2, 8, 8, 0, 0, 0],
 [0, 0, 0, 0, 0, 0, 0, 0, 0],
 [0, 0, 0, 0, 0, 0, 0, 0, 0]])

def find_color_changes(input_grid, output_grid):
    changes = []
    for y in range(input_grid.shape[0]):
        for x in range(input_grid.shape[1]):
            if input_grid[y, x] != output_grid[y, x]:
                changes.append(((y, x), input_grid[y, x], output_grid[y, x]))
    return changes

changes = find_color_changes(input_grid, output_grid)
print(changes)

def is_horizontal(grid, y, x):
    if grid[y,x] == 0:
        return False
    neighbors = []
    if x > 0: neighbors.append(grid[y, x-1])
    if x < grid.shape[1] -1: neighbors.append(grid[y, x+1])
    return any(n == grid[y,x] for n in neighbors)

def is_vertical(grid, y, x):
    if grid[y, x] == 0:
        return False
    neighbors = []
    if y > 0 : neighbors.append(grid[y-1,x])
    if y < grid.shape[0] -1 : neighbors.append(grid[y+1,x])
    return any(n == grid[y,x] for n in neighbors)

horizontal_changes = []
vertical_changes = []
for (y, x), old_color, new_color in changes:
    if is_horizontal(input_grid, y, x):
        horizontal_changes.append(((y,x), old_color, new_color))
    elif is_vertical(input_grid, y, x):
        vertical_changes.append(((y,x), old_color, new_color))

print("Horizontal changes:", horizontal_changes)
print("Vertical changes:", vertical_changes)

code_execution_result: 1

[((1, 1), 5, 2), ((1, 2), 5, 2), ((1, 3), 5, 2), ((1, 4), 5, 8), ((1, 5), 5, 8), ((2, 4), 5, 8), ((2, 5), 5, 8), ((3, 3), 5, 2), ((4, 3), 5, 2), ((4, 4), 5, 8), ((4, 5), 5, 8), ((5, 3), 5, 2), ((5, 4), 5, 8), ((5, 5), 5, 8)]
Horizontal changes: [((1, 1), 5, 2), ((1, 2), 5, 2), ((1, 3), 5, 2), ((1, 4), 5, 8), ((1, 5), 5, 8), ((2, 4), 5, 8), ((2, 5), 5, 8), ((4, 4), 5, 8), ((4, 5), 5, 8), ((5, 4), 5, 8), ((5, 5), 5, 8)]
Vertical changes: [((3, 3), 5, 2), ((4, 3), 5, 2), ((5, 3), 5, 2)]

The code analysis confirms the transformation. All gray (5) cells are transformed to either azure (8) or red (2) based on whether they’re part of a horizontal or vertical segment respectively.

The natural language program remains consistent: “For each gray pixel in the input grid, determine if it is part of a horizontal or vertical segment of the overall shape. If it is part of a horizontal segment, change its color to azure (8). If it is part of a vertical segment, change its color to red (2).”

time
response time	total elapsed
37.648	174.254

usage
token type	call count	total used
Prompt	8892	17406
Response	1651	3875
Total	10543	21281
Cached	0	0