I am trying to iterate through every pixel coordinate, starting at (0, 0), in order to fuse two pixelated shapes at the closest offset where they don't overlap.
Until now, I was using concentric squares, which are really easy to do but can end up placing the grafted image further than it could be. I then implemented Bresenham's Circle Algorithm as follows :
def generate_offsets(maxRadius : int):
"""Generate x and y coordinates in concentric circles around the origin
Uses Bresenham's Circle Drawing Algorithm
"""
for radius in range(maxRadius):
x = 0
y = radius
d = 3 - (2 * radius)
while x < y:
yield x, y
yield y, x
yield y, -x
yield x, -y
yield -x, -y
yield -y, -x
yield -y, x
yield -x, y
if d < 0:
d += (4 * x) + 6
else:
d += (4 * (x-y)) + 10
y -= 1
x += 1
However, this has the disadvantage of leaving some pixel offsets unchecked. All the solutions I have found for filling the holes propose tracing the entire line from 0,0 to the pixel, which would be extremely wasteful here.
How can I fix the holes, without revisiting any pixels ?
Here is an example showing said holes, this represents every circle or radius 1-9. Explored pixels are #
, while unexplored pixels are .
:
....................
....................
........#####.......
......#########.....
.....###########....
....#..#######..#...
...##..#.###.#..##..
...####.#####.####..
..####.#.###.#.####.
..#######.#.#######.
..########.########.
..#######.#.#######.
..####.#.###.#.####.
...####.#####.####..
...##..#.###.#..##..
....#..#######..#...
.....###########....
......#########.....
........#####.......
....................
Update : Here is my current solution, which does fill the whole circle but is stores a lot more state than I would like :
import itertools
def generate_offsets(minRadius : int = 0, maxRadius : int = 3_750_000):
"""Generate x and z coordinates in concentric circles around the origin
Uses Bresenham's Circle Drawing Algorithm
"""
def yield_points(x, y):
yield x, y
yield x, -y
yield -x, -y
yield -x, y
if x != y:
yield y, x
yield y, -x
yield -y, -x
yield -y, x
def yield_circle(radius, previousCircle):
x = 0
y = radius
d = 3 - (2 * radius)
while x < y:
for point in yield_points(x, y):
if point not in previousCircle:
yield point
if d < 0:
d += (4 * x) + 6
else:
d += (4 * (x-y)) + 10
for point in itertools.chain(yield_points(x + 1, y), yield_points(x, y - 1)):
if point not in previousCircle:
yield point
y -= 1
x += 1
previousCircle = [(0,0)]
for radius in range(minRadius, maxRadius):
circle = set()
for point in yield_circle(radius, previousCircle):
if point not in circle:
yield point
circle.add(point)
previousCircle = circle
This is the most balanced solution I have found so far in terms of memory and processing. It only remembers the previous circle, which lowers the redundancy rate (rate of pixels visited twice) from around 50% without any memory to around 1.5%
Off the top of my head.....
Generate a set of coordinates once. While exploring, keep a set of coordinates visited. The difference between the sets will be the un-visited coordinates. Maybe keep track of the x and y extrema for comparison if you don't want to process pixels outside of the circle - maybe something like a dictionary: {each_row_visited:max_and_min_col_for that row,}
.
I would prefer a solution that doesn't expand in memory as time progresses !
Instead of making progressively larger circles hoping to fill a disc:
Use the Bresenham algorithm to determine the points with your desired radius
find the min and max y value for each x (or vis versa)
use those extrema to yield all points between the extrema
from pprint import pprint from operator import itemgetter from itertools import groupby
X = itemgetter(0) Y = itemgetter(1)
This function modified from question in a different forum
def circle(radius):
'''Yield (x,y) points of a disc
Uses Bresenham complete circle algorithm
'''
# init vars
switch = 3 - (2 * radius)
# points --> {x:(minY,maxY),...}
points = set()
x = 0
y = radius
# first quarter/octant starts clockwise at 12 o'clock
while x <= y:
# first quarter first octant
points.add((x,-y))
# first quarter 2nd octant
points.add((y,-x))
# second quarter 3rd octant
points.add((y,x))
# second quarter 4.octant
points.add((x,y))
# third quarter 5.octant
points.add((-x,y))
# third quarter 6.octant
points.add((-y,x))
# fourth quarter 7.octant
points.add((-y,-x))
# fourth quarter 8.octant
points.add((-x,-y))
if switch < 0:
switch = switch + (4 * x) + 6
else:
switch = switch + (4 * (x - y)) + 10
y = y - 1
x = x + 1
circle = sorted(points)
for x,points in groupby(circle,key=X):
points = list(points)
miny = Y(points[0])
maxy = Y(points[-1])
for y in range(miny,maxy+1):
yield (x,y)
That should minimize the state. There is going to be some duplication/revisits when creating the disc from the circle - I didn't try to quantify that.
Result...
def display(points,radius):
''' point: sequence of (x,y) tuples, radius: int
'''
not_visited, visited = '-','█'
# sort on y
points = sorted(points,key=Y)
nrows = ncols = radius * 2 + 1 + 2
empty_row = [not_visited for _ in range(ncols)] # ['-','-',...]
# grid has an empty frame around the circle
grid = [empty_row[:] for _ in range(nrows)] # list of lists
# iterate over visited points and substitute symbols
for (x,y) in points:
# add one for the empty row on top and colun on left
# add offset to address negative coordinates
y = y + radius + 1
x = x + radius + 1
grid[y][x] = visited
grid = '\n'.join(' '.join(row) for row in grid)
print(grid)
return grid
for r in (3,8):
points = circle(r) # generator/iterator
grid = display(points,r)
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