I've changed my answer a bit to address your follow-up question about whether it could be modified to instead generate random non-colliding squares rather than arbitrarily rectangles. I did this in the simplest way I could that would work, which was to post-process the rectangular output of my original answer and turn its contents into square sub-regions. I also updated the optional visualization code to show both kinds of output. Obviously this sort of filtering could be extended to do other things like insetting each rectangle or square slightly to prevent them from touching one another.
My answer avoids doing what many of the answers already posted do -- which is randomly generating rectangles while rejecting any that collide with any already created -- because it sounds inherently slow and computationally wasteful. My approach concentrates instead on only generating ones that don't overlap in the first place.
That makes what needs to be done relatively simple by turning it into a simple area subdivision problem which can be performed very quickly. Below is one implementation of how that can be done. It starts with a rectangle defining the outer boundary which it divides into four smaller non-overlapping rectangles. That is accomplished by choosing a semi-random interior point and using it along with the four existing corner points of the outer rectangle to form the four subsections.
Most of the action take place in the quadsect() function. The choice of the interior point is crucial in determining what the output looks like. You can constrain it any way you wish, such as only selecting one that would result in sub-rectangles of at least a certain minimum width or height or no bigger than some amount. In the sample code in my answer, it's defined as the center point ±1/3 of the width and height of the outer rectangle, but basically any interior point would work to some degree.
Since this algorithm generates sub-rectangles very rapidly, it's OK to spend some computational time determining the interior division point.
To help visualize the results of this approach, there's some non-essential code at the very end that uses the PIL (Python Imaging Library) module to create an image file displaying the rectangles generated during some test runs I made.
Anyway, here's the latest version of the code and output samples:
import random
from random import randint
random.seed()
NUM_RECTS = 20
REGION = Rect(0, 0, 640, 480)
class Point(object):
def __init__(self, x, y):
self.x, self.y = x, y
@staticmethod
def from_point(other):
return Point(other.x, other.y)
class Rect(object):
def __init__(self, x1, y1, x2, y2):
minx, maxx = (x1,x2) if x1 < x2 else (x2,x1)
miny, maxy = (y1,y2) if y1 < y2 else (y2,y1)
self.min, self.max = Point(minx, miny), Point(maxx, maxy)
@staticmethod
def from_points(p1, p2):
return Rect(p1.x, p1.y, p2.x, p2.y)
width = property(lambda self: self.max.x - self.min.x)
height = property(lambda self: self.max.y - self.min.y)
plus_or_minus = lambda v: v * [-1, 1][(randint(0, 100) % 2)] # equal chance +/-1
def quadsect(rect, factor):
""" Subdivide given rectangle into four non-overlapping rectangles.
'factor' is an integer representing the proportion of the width or
height the deviatation from the center of the rectangle allowed.
"""
# pick a point in the interior of given rectangle
w, h = rect.width, rect.height # cache properties
center = Point(rect.min.x + (w // 2), rect.min.y + (h // 2))
delta_x = plus_or_minus(randint(0, w // factor))
delta_y = plus_or_minus(randint(0, h // factor))
interior = Point(center.x + delta_x, center.y + delta_y)
# create rectangles from the interior point and the corners of the outer one
return [Rect(interior.x, interior.y, rect.min.x, rect.min.y),
Rect(interior.x, interior.y, rect.max.x, rect.min.y),
Rect(interior.x, interior.y, rect.max.x, rect.max.y),
Rect(interior.x, interior.y, rect.min.x, rect.max.y)]
def square_subregion(rect):
""" Return a square rectangle centered within the given rectangle """
w, h = rect.width, rect.height # cache properties
if w < h:
offset = (h - w) // 2
return Rect(rect.min.x, rect.min.y+offset,
rect.max.x, rect.min.y+offset+w)
else:
offset = (w - h) // 2
return Rect(rect.min.x+offset, rect.min.y,
rect.min.x+offset+h, rect.max.y)
# call quadsect() until at least the number of rects wanted has been generated
rects = [REGION] # seed output list
while len(rects) <= NUM_RECTS:
rects = [subrect for rect in rects
for subrect in quadsect(rect, 3)]
random.shuffle(rects) # mix them up
sample = random.sample(rects, NUM_RECTS) # select the desired number
print '%d out of the %d rectangles selected' % (NUM_RECTS, len(rects))
#################################################
# extra credit - create an image file showing results
from PIL import Image, ImageDraw
def gray(v): return tuple(int(v*255) for _ in range(3))
BLACK, DARK_GRAY, GRAY = gray(0), gray(.25), gray(.5)
LIGHT_GRAY, WHITE = gray(.75), gray(1)
RED, GREEN, BLUE = (255, 0, 0), (0, 255, 0), (0, 0, 255)
CYAN, MAGENTA, YELLOW = (0, 255, 255), (255, 0, 255), (255, 255, 0)
BACKGR, SQUARE_COLOR, RECT_COLOR = (245, 245, 87), (255, 73, 73), (37, 182, 249)
imgx, imgy = REGION.max.x + 1, REGION.max.y + 1
image = Image.new("RGB", (imgx, imgy), BACKGR) # create color image
draw = ImageDraw.Draw(image)
def draw_rect(rect, fill=None, outline=WHITE):
draw.rectangle([(rect.min.x, rect.min.y), (rect.max.x, rect.max.y)],
fill=fill, outline=outline)
# first draw outlines of all the non-overlapping rectanges generated
for rect in rects:
draw_rect(rect, outline=LIGHT_GRAY)
# then draw the random sample of them selected
for rect in sample:
draw_rect(rect, fill=RECT_COLOR, outline=WHITE)
# and lastly convert those into squares and re-draw them in another color
for rect in sample:
draw_rect(square_subregion(rect), fill=SQUARE_COLOR, outline=WHITE)
filename = 'square_quadsections.png'
image.save(filename, "PNG")
print repr(filename), 'output image saved'
Output Sample 1
Output Sample 2
