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test_image_func2.py
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import unittest
import numpy as np
from typing import List, Tuple
from arclang.function import *
class TestImageFunctions2(unittest.TestCase):
def setUp(self):
self.img1 = Image(0, 0, 5, 5, np.array([
[1, 1, 0, 2, 2],
[1, 1, 0, 2, 2],
[0, 0, 0, 0, 0],
[3, 3, 0, 4, 4],
[3, 3, 0, 4, 4]
]))
self.img2 = Image(0, 0, 5, 5, np.array([
[1, 1, 1, 1, 1],
[1, 2, 2, 2, 1],
[1, 2, 3, 2, 1],
[1, 2, 2, 2, 1],
[1, 1, 1, 1, 1]
]))
def test_swap_template(self):
in_img = Image(0, 0, 5, 5, np.array([
[1, 1, 1, 1, 1],
[1, 2, 2, 2, 1],
[1, 2, 2, 2, 1],
[1, 2, 2, 2, 1],
[1, 1, 1, 1, 1]
]))
a = Image(0, 0, 3, 3, np.full((3, 3), 2))
b = Image(0, 0, 3, 3, np.full((3, 3), 3))
result = swap_template(in_img, a, b)
expected = np.array([
[1, 1, 1, 1, 1],
[1, 3, 3, 3, 1],
[1, 3, 3, 3, 1],
[1, 3, 3, 3, 1],
[1, 1, 1, 1, 1]
])
self.assertTrue(np.array_equal(result.mask, expected))
def test_spread_cols(self):
img = Image(0, 0, 5, 5, np.array([
[1, 0, 2, 0, 3],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]
]))
result = spread_cols(img)
expected = np.array([
[1, 1, 2, 2, 3],
[1, 1, 2, 2, 3],
[1, 1, 2, 2, 3],
[1, 1, 2, 2, 3],
[1, 1, 2, 2, 3]
])
self.assertTrue(np.array_equal(result.mask, expected))
def test_split_columns(self):
result = split_columns(self.img1)
self.assertEqual(len(result), 5)
for i, col in enumerate(result):
self.assertEqual(col.w, 1)
self.assertEqual(col.h, 5)
self.assertTrue(np.array_equal(col.mask, self.img1.mask[:, i:i+1]))
def test_split_rows(self):
result = split_rows(self.img1)
self.assertEqual(len(result), 5)
for i, row in enumerate(result):
self.assertEqual(row.w, 5)
self.assertEqual(row.h, 1)
self.assertTrue(np.array_equal(row.mask, self.img1.mask[i:i+1, :]))
def test_half(self):
for i in range(4):
result = half(self.img1, i)
if i < 2: # Vertical split
self.assertEqual(result.w, 2)
self.assertEqual(result.h, 5)
else: # Horizontal split
self.assertEqual(result.w, 5)
self.assertEqual(result.h, 2)
if i % 2 == 0: # Left or top half
self.assertEqual(result.x, 0)
self.assertEqual(result.y, 0)
else: # Right or bottom half
self.assertEqual(result.x, 3 if i == 1 else 0)
self.assertEqual(result.y, 3 if i == 3 else 0)
def test_smear(self):
img = Image(0, 0, 5, 5, np.array([
[1, 0, 0, 0, 2],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0],
[3, 0, 0, 0, 4]
]))
result = smear_each(img, 6) # All directions
expected = np.array([[1, 2, 2, 2, 2],
[3, 0, 0, 0, 4],
[3, 0, 0, 0, 4],
[3, 0, 0, 0, 4],
[3, 4, 4, 4, 4]])
self.assertTrue(np.array_equal(result.mask, expected))
def test_mirror2(self):
img = Image(0, 0, 3, 3, np.array([
[1, 2, 3],
[4, 5, 6],
[7, 8, 9]
]))
line = Image(0, 0, 3, 1) # Horizontal line
result = mirror2(img, line)
expected = np.array([
[7, 8, 9],
[4, 5, 6],
[1, 2, 3]
])
self.assertTrue(np.array_equal(result.mask, expected))
self.assertEqual(result.y, -2) # Mirrored upwards
def test_gravity(self):
img = Image(0, 0, 5, 5, np.array([
[0, 0, 1, 0, 0],
[0, 0, 0, 0, 0],
[2, 0, 0, 0, 3],
[0, 0, 0, 0, 0],
[0, 4, 0, 5, 0]
]))
result = gravity(img, 2) # Downwards
self.assertEqual(len(result), 5) # 5 components
bottom_row = np.zeros(5)
for component in result:
y = component.y + component.h - 1
x = component.x
bottom_row[x] = component.mask[-1, 0]
self.assertTrue(np.array_equal(bottom_row, [2, 4, 1, 5, 3]))
def test_my_stack(self):
imgs = [
Image(0, 0, 2, 2, np.full((2, 2), 1)),
Image(0, 0, 3, 3, np.full((3, 3), 2)),
Image(0, 0, 4, 4, np.full((4, 4), 3))
]
result = my_stack_l(imgs, 0) # Horizontal stacking
self.assertEqual(result.w, 9)
self.assertEqual(result.h, 4)
self.assertTrue(np.all(result.mask[:2, :2] == 1))
self.assertTrue(np.all(result.mask[:4, 5:] == 3))
def test_stack_line(self):
imgs = [
Image(0, 0, 2, 2, np.full((2, 2), 1)),
Image(3, 0, 2, 2, np.full((2, 2), 2)),
Image(6, 0, 2, 2, np.full((2, 2), 3))
]
result = stack_line(imgs)
self.assertEqual(result.w, 6)
self.assertEqual(result.h, 2)
def test_stack_line_v(self):
imgs = [
Image(0, 0, 2, 2, np.full((2, 2), 1)),
Image(3, 0, 2, 2, np.full((2, 2), 2)),
Image(6, 0, 2, 2, np.full((2, 2), 3))
]
result = stack_line_v(imgs)
self.assertEqual(result.w, 2)
self.assertEqual(result.h, 6)
def test_compose_growing_slow(self):
imgs = [
Image(0, 0, 3, 3, np.full((3, 3), 1)),
Image(1, 1, 3, 3, np.full((3, 3), 2)),
Image(2, 2, 3, 3, np.full((3, 3), 3))
]
result = compose_growing_slow(imgs)
expected = np.array([
[1, 1, 1, 0, 0],
[1, 2, 2, 2, 0],
[1, 2, 3, 3, 3],
[0, 2, 3, 3, 3],
[0, 0, 3, 3, 3]
])
self.assertTrue(np.array_equal(result.mask, expected))
def test_compose_growing(self):
imgs = [
Image(0, 0, 3, 3, np.full((3, 3), 1)),
Image(1, 1, 3, 3, np.full((3, 3), 2)),
Image(2, 2, 3, 3, np.full((3, 3), 3))
]
result = compose_growing(imgs)
expected = np.array([
[1, 1, 1, 0, 0],
[1, 2, 2, 2, 0],
[1, 2, 3, 3, 3],
[0, 2, 3, 3, 3],
[0, 0, 3, 3, 3]
])
self.assertTrue(np.array_equal(result.mask, expected))
def test_pick_unique(self):
imgs = [
Image(0, 0, 2, 2, np.full((2, 2), 1)),
Image(0, 0, 2, 2, np.full((2, 2), 2)),
Image(0, 0, 2, 2, np.array([[3, 3], [3, 4]]))
]
result = pick_unique(imgs)
self.assertTrue(np.array_equal(result.mask, np.array([[3, 3], [3, 4]])))
def test_greedy_fill(self):
ret = Image(0, 0, 4, 4, np.zeros((4, 4), dtype=int))
pieces = [(2, [1, 1, 1, 1])]
done = np.zeros((4, 4), dtype=int)
donew = 1000
result = greedy_fill(ret, pieces, done, 2, 2, donew)
expected = np.array([
[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]
])
self.assertTrue(np.array_equal(result.mask, expected))
def test_greedy_fill_black(self):
img = Image(0, 0, 4, 4, np.array([
[1, 1, 0, 0],
[1, 1, 0, 0],
[0, 0, 0, 0],
[0, 0, 0, 0]
]))
result = greedy_fill_black(img, N=2)
expected = np.array([
[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]
])
self.assertTrue(np.array_equal(result.mask, expected))
def test_greedy_fill_black2(self):
img = Image(0, 0, 4, 4, np.array([
[1, 1, 0, 0],
[1, 1, 0, 0],
[0, 0, 0, 0],
[0, 0, 0, 0]
]))
result = greedy_fill_black2(img, N=2)
expected = np.array([
[0, 0, 1, 1],
[0, 0, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]
])
self.assertTrue(np.array_equal(result.mask, expected))
def test_extend2(self):
img = Image(0, 0, 3, 3, np.array([
[1, 1, 1],
[1, 2, 1],
[1, 1, 1]
]))
room = Image(0, 0, 5, 5)
result = extend2(img, room)
expected = np.array([
[1, 1, 1, 1, 1],
[1, 1, 1, 1, 1],
[1, 1, 2, 1, 1],
[1, 1, 1, 1, 1],
[1, 1, 1, 1, 1]
])
self.assertTrue(np.array_equal(result.mask, expected))
def test_connect(self):
img = Image(0, 0, 5, 5, np.array([
[1, 0, 1, 0, 1],
[0, 0, 0, 0, 0],
[2, 0, 2, 0, 2],
[0, 0, 0, 0, 0],
[3, 0, 3, 0, 3]
]))
result = connect(img, 0) # Horizontal
expected = np.array([
[1, 1, 1, 1, 1],
[0, 0, 0, 0, 0],
[2, 2, 2, 2, 2],
[0, 0, 0, 0, 0],
[3, 3, 3, 3, 3]
])
self.assertTrue(np.array_equal(result.mask, expected))
def test_replace_template(self):
in_img = Image(0, 0, 5, 5, np.array([
[1, 1, 1, 1, 1],
[1, 2, 2, 2, 1],
[1, 2, 2, 2, 1],
[1, 2, 2, 2, 1],
[1, 1, 1, 1, 1]
]))
need = Image(0, 0, 3, 3, np.array([
[2, 2, 2],
[2, 2, 2],
[2, 2, 2]
]))
marked = Image(0, 0, 3, 3, np.array([
[3, 3, 3],
[3, 3, 3],
[3, 3, 3]
]))
result = replace_template(in_img, need, marked)
expected = np.array([
[1, 1, 1, 1, 1],
[1, 3, 3, 3, 1],
[1, 3, 3, 3, 1],
[1, 3, 3, 3, 1],
[1, 1, 1, 1, 1]
])
self.assertTrue(np.array_equal(result.mask, expected))
if __name__ == '__main__':
unittest.main()