Problem:
You have a list of X/Y coordinates, for example:
coords = [(6.74219, -53.57835), (6.74952, -53.57241), (6.75652, -53.56289), (6.74756, -53.56598), (6.73462, -53.57518)]
For these coordinates you want to compute the minimum bounding box.
Solution 1 (no NumPy):
class BoundingBox(object): """ A 2D bounding box """ def __init__(self, points): if len(points) == 0: raise ValueError("Can't compute bounding box of empty list") self.minx, self.miny = float("inf"), float("inf") self.maxx, self.maxy = float("-inf"), float("-inf") for x, y in points: # Set min coords if x < self.minx: self.minx = x if y < self.miny: self.miny = y # Set max coords if x > self.maxx: self.maxx = x elif y > self.maxy: self.maxy = y @property def width(self): return self.maxx - self.minx @property def height(self): return self.maxy - self.miny def __repr__(self): return "BoundingBox({}, {}, {}, {})".format( self.minx, self.maxx, self.miny, self.maxy) # Usage example: BoundingBox(coords) # BoundingBox(6.73462, 6.75652, -53.57835, -53.56289)
By using the BoundingBox
class, you can directly access bbox.width
and bbox.height
. Although you can access the coordinates at bbox[0], bbox[1], ...
, you can avoid mixing up the coordinates by accessing them using bbox.minx, bbox.maxx, bbox.miny and bbox.maxy
.
Solution 2 (NumPy):
Using numpy makes managing a large amount of coordinates much more efficient. For this example, we’ll assume you stored the coordinates in a (n,2)
-shaped array. For the example coordinates above, that’s easy:
import numpy as np coords = np.asarray(coords)
We can use numpy’s builtin min
and max
functions to compute the min/max instead of writing them ourselves. You can have a look at the source code, but for most applications it’s recommended to install UliEngineering and just use the code:
sudo pip3 install git+https://github.com/ulikoehler/UliEngineering.git
Example:
from UliEngineering.Math.Coordinates import BoundingBox # Usage example: BoundingBox(coords) # BoundingBox(6.73462, 6.75652, -53.57835, -53.56289)
You can use this on a list of coordinates without explicitly converting them to a numpy array, because
min
and max
will convert the list implicitly. However, this is inefficient, as it will be converted two times: Once in min
and once in max
.