Python: Defining a minimum bounding rectangle

Question

I have data in the following format, a list of 2d x,y coordinates:

[(6, 7), (2, 4), (8, 9), (3, 7), (5, 4), (9, 9)]

and I'm trying to iterate through the list to find the minimum bounding box in the format [(minx,miny),(maxx,miny),(maxx,maxy),(minx,maxy)]

Thus I've written the below code, however it doesn't appear to be working. Potentially to do with the fact that I'm not passing it an array rather a list. the input and code is below, print coords returns the list previously mentioned:

os.chdir("filepath")
with open ('file.csv') as csvfile:
    coords = [(int(x), int(y)) for x, y in csv.reader(csvfile, delimiter= ',')]
print coords


def bounding_box(coords):
    min_x, min_y = numpy.min(coords[0], axis=0)
    max_x, max_y = numpy.max(coords[0], axis=0)
    return numpy.array(
        [(min_x, min_y), (max_x, min_y), (max_x, max_y), (min_x, max_y)])

Could anyone point me in the right direction? feel free to disregard the entire code above if its not helping.

Answer 1

Why don't you just iterate through the list with four counters: min_x, min_y, max_x, and max_y

def bounding_box(coords):

  min_x = 100000 # start with something much higher than expected min
  min_y = 100000
  max_x = -100000 # start with something much lower than expected max
  max_y = -100000

  for item in coords:
    if item[0] < min_x:
      min_x = item[0]

    if item[0] > max_x:
      max_x = item[0]

    if item[1] < min_y:
      min_y = item[1]

    if item[1] > max_y:
      max_y = item[1]

  return [(min_x,min_y),(max_x,min_y),(max_x,max_y),(min_x,max_y)]

Using your example input:

bounding_box([(6, 7), (2, 4), (8, 9), (3, 7), (5, 4), (9, 9)])
>> [(2, 4), (9, 4), (9, 9), (2, 9)]

Answer 2

The issue you're having is that you are searching for a vector min/max and instead you should be searching by each of the verctor dimensions (two in your case). so you should look for the min for X and the min for Y and the same for the max.

The correct approach would be:

min_x, min_y = numpy.min(coords[...,0]), numpy.min(coords[...,1])
max_x, max_y = numpy.max(coords[...,0]), numpy.max(coords[...,1])
return numpy.array(
    [(min_x, min_y), (max_x, min_y), (max_x, max_y), (min_x, max_y)])

coords[...,0] and coords[...,1] means that you are selecting values from a specific dimension (X or Y respectively).

In order for all of this to work properly you should also make the list of coordinates to be a numpy twodimensional array instead of list of tuples.