pysal#47 :

Changed mbr to minimum_bounding_rectangle,
Added opencv minimum_area_rectangle,
Removed loop in mbr and substituted with in-built max and min functions

doc/api.rst

@@ -34,8 +34,8 @@ Centrography
 
 .. autosummary::
    :toctree: generated/
-
-    mbr
+    minimum_area_rectangle
+    minimum_bounding_rectangle
     hull
     mean_center
     weighted_mean_center

pointpats/centrography.py

@@ -9,7 +9,7 @@
 """
 
 __author__ = "Serge Rey [email protected]"
-__all__ = ['mbr', 'hull', 'mean_center', 'weighted_mean_center',
+__all__ = ['minimum_area_rectangle', 'minimum_bounding_rectangle', 'hull', 'mean_center', 'weighted_mean_center',
            'manhattan_median', 'std_distance', 'euclidean_median', 'ellipse',
            'skyum', 'dtot',"_circle"]
 
@@ -18,6 +18,7 @@
 import numpy as np
 import warnings
 import copy
+import cv2 as cv
 from math import pi as PI
 from scipy.spatial import ConvexHull
 from libpysal.cg import get_angle_between, Ray, is_clockwise
@@ -27,10 +28,36 @@
 not_clockwise = lambda x: not is_clockwise(x)
 
 MAXD = sys.float_info.max
-MIND = sys.float_info.min
+MIND = sys.float_info.minz
 
+def minimum_area_rectangle(points):
+    """
+    Find minimum area rectangle of a point array.
+
+    Parameters
+    ----------
+    points : arraylike
+             (n,2), (x,y) coordinates of a series of event points.
+
+    Returns
+    -------
+    min_x  : float
+             leftmost value of the vertices of minimum bounding rectangle.
+    min_y  : float
+             downmost value of the vertices of minimum bounding rectangle.
+    max_x  : float
+             rightmost value of the vertices of minimum bounding rectangle.
+    max_y  : float
+             upmost value of the vertices of minimum bounding rectangle.
+
+    """
+    points = np.array(points)
+    points = np.float32(points[:, np.newaxis, :])
+    rect = cv.minAreaRect(points)
+    min_x, min_y, max_x, max_y = cv.boxPoints(rect)
+    return min_x, min_y, max_x, max_y
 
-def mbr(points):
+def minimum_bounding_rectangle(points):
     """
     Find minimum bounding rectangle of a point array.
 
@@ -54,16 +81,11 @@ def mbr(points):
     points = np.asarray(points)
     min_x = min_y = MAXD
     max_x = max_y = MIND
-    for point in points:
-        x, y = point
-        if x > max_x:
-            max_x = x
-        if x < min_x:
-            min_x = x
-        if y > max_y:
-            max_y = y
-        if y < min_y:
-            min_y = y
+    x, y = zip(*points)
+    min_x = min(x)
+    min_y = min(y)
+    max_x = max(x)
+    max_y = max(y)
     return min_x, min_y, max_x, max_y
 
 

pointpats/tests/test_centrography.py

@@ -15,8 +15,15 @@ def setUp(self):
                        [79.26,  7.68], [8.23, 39.93], [98.73, 77.17],
                        [89.78, 42.53], [65.19, 92.08], [54.46, 8.48]]
 
+    def test_centrography_mar(self):
+        min_x, min_y, max_x, max_y = minimum_area_rectangle(self.points)
+        np.testing.assert_array_almost_equal(min_x, [36.40165, 104.61744])
+        np.testing.assert_array_almost_equal(min_y, [ 4.0872803, 30.417528 ])
+        np.testing.assert_array_almost_equal(max_x, [75.599075,  -0.7261505])
+        np.testing.assert_array_almost_equal(max_y, [107.913445,  73.47376 ])
+
     def test_centrography_mbr(self):
-        min_x, min_y, max_x, max_y = mbr(self.points)
+        min_x, min_y, max_x, max_y = minimum_bounding_rectangle(self.points)
         np.testing.assert_allclose(min_x, 8.2300000000000004, RTOL)
         np.testing.assert_allclose(min_y, 7.6799999999999997, RTOL)
         np.testing.assert_allclose(max_x, 98.730000000000004, RTOL)