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#!/usr/bin/env python
"""
A Bounding Box object and assorted utilities , subclassed from a numpy array
"""
import numpy as N
class BBox(N.ndarray):
"""
A Bounding Box object:
Takes Data as an array. Data is any python sequence that can be turned into a
2x2 numpy array of floats:
[[MinX, MinY ],
[MaxX, MaxY ]]
It is a subclass of numpy.ndarray, so for the most part it can be used as
an array, and arrays that fit the above description can be used in its place.
Usually created by the factory functions:
asBBox
and
fromPoints
"""
def __new__(subtype, data):
"""
Takes Data as an array. Data is any python sequence that can be turned into a
2x2 numpy array of floats:
[[MinX, MinY ],
[MaxX, MaxY ]]
You don't usually call this directly. BBox objects are created with the factory functions:
asBBox
and
fromPoints
"""
arr = N.array(data, N.float)
arr.shape = (2,2)
if arr[0,0] > arr[1,0] or arr[0,1] > arr[1,1]:
# note: zero sized BB OK.
raise ValueError("BBox values not aligned: \n minimum values must be less that maximum values")
return N.ndarray.__new__(subtype, shape=arr.shape, dtype=arr.dtype, buffer=arr)
def Overlaps(self, BB):
"""
Overlap(BB):
Tests if the given Bounding Box overlaps with this one.
Returns True is the Bounding boxes overlap, False otherwise
If they are just touching, returns True
"""
if N.isinf(self).all() or N.isinf(BB).all():
return True
if ( (self[1,0] >= BB[0,0]) and (self[0,0] <= BB[1,0]) and
(self[1,1] >= BB[0,1]) and (self[0,1] <= BB[1,1]) ):
return True
else:
return False
def Inside(self, BB):
"""
Inside(BB):
Tests if the given Bounding Box is entirely inside this one.
Returns True if it is entirely inside, or touching the
border.
Returns False otherwise
"""
if ( (BB[0,0] >= self[0,0]) and (BB[1,0] <= self[1,0]) and
(BB[0,1] >= self[0,1]) and (BB[1,1] <= self[1,1]) ):
return True
else:
return False
def PointInside(self, Point):
"""
Inside(BB):
Tests if the given Point is entirely inside this one.
Returns True if it is entirely inside, or touching the
border.
Returns False otherwise
Point is any length-2 sequence (tuple, list, array) or two numbers
"""
if Point[0] >= self[0,0] and \
Point[0] <= self[1,0] and \
Point[1] <= self[1,1] and \
Point[1] >= self[0,1]:
return True
else:
return False
def Merge(self, BB):
"""
Joins this bounding box with the one passed in, maybe making this one bigger
"""
if self.IsNull():
self[:] = BB
elif N.isnan(BB).all(): ## BB may be a regular array, so I can't use IsNull
pass
else:
if BB[0,0] < self[0,0]: self[0,0] = BB[0,0]
if BB[0,1] < self[0,1]: self[0,1] = BB[0,1]
if BB[1,0] > self[1,0]: self[1,0] = BB[1,0]
if BB[1,1] > self[1,1]: self[1,1] = BB[1,1]
return None
def IsNull(self):
return N.isnan(self).all()
## fixme: it would be nice to add setter, too.
def _getLeft(self):
return self[0,0]
Left = property(_getLeft)
def _getRight(self):
return self[1,0]
Right = property(_getRight)
def _getBottom(self):
return self[0,1]
Bottom = property(_getBottom)
def _getTop(self):
return self[1,1]
Top = property(_getTop)
def _getWidth(self):
return self[1,0] - self[0,0]
Width = property(_getWidth)
def _getHeight(self):
return self[1,1] - self[0,1]
Height = property(_getHeight)
def _getCenter(self):
return self.sum(0) / 2.0
Center = property(_getCenter)
### This could be used for a make BB from a bunch of BBs
#~ def _getboundingbox(bboxarray): # lrk: added this
#~ # returns the bounding box of a bunch of bounding boxes
#~ upperleft = N.minimum.reduce(bboxarray[:,0])
#~ lowerright = N.maximum.reduce(bboxarray[:,1])
#~ return N.array((upperleft, lowerright), N.float)
#~ _getboundingbox = staticmethod(_getboundingbox)
## Save the ndarray __eq__ for internal use.
Array__eq__ = N.ndarray.__eq__
def __eq__(self, BB):
"""
__eq__(BB) The equality operator
A == B if and only if all the entries are the same
"""
if self.IsNull() and N.isnan(BB).all(): ## BB may be a regular array, so I can't use IsNull
return True
else:
return self.Array__eq__(BB).all()
def asBBox(data):
"""
returns a BBox object.
If object is a BBox, it is returned unaltered
If object is a numpy array, a BBox object is returned that shares a
view of the data with that array. The numpy array should be of the correct
format: a 2x2 numpy array of floats:
[[MinX, MinY ],
[MaxX, MaxY ]]
"""
if isinstance(data, BBox):
return data
arr = N.asarray(data, N.float)
return N.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
def fromPoints(Points):
"""
fromPoints (Points).
reruns the bounding box of the set of points in Points. Points can
be any python object that can be turned into a numpy NX2 array of Floats.
If a single point is passed in, a zero-size Bounding Box is returned.
"""
Points = N.asarray(Points, N.float).reshape(-1,2)
arr = N.vstack( (Points.min(0), Points.max(0)) )
return N.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
def fromBBArray(BBarray):
"""
Builds a BBox object from an array of Bounding Boxes.
The resulting Bounding Box encompases all the included BBs.
The BBarray is in the shape: (Nx2x2) where BBarray[n] is a 2x2 array that represents a BBox
"""
#upperleft = N.minimum.reduce(BBarray[:,0])
#lowerright = N.maximum.reduce(BBarray[:,1])
# BBarray = N.asarray(BBarray, N.float).reshape(-1,2)
# arr = N.vstack( (BBarray.min(0), BBarray.max(0)) )
BBarray = N.asarray(BBarray, N.float).reshape(-1,2,2)
arr = N.vstack( (BBarray[:,0,:].min(0), BBarray[:,1,:].max(0)) )
return asBBox(arr)
#return asBBox( (upperleft, lowerright) ) * 2
def NullBBox():
"""
Returns a BBox object with all NaN entries.
This represents a Null BB box;
BB merged with it will return BB.
Nothing is inside it.
"""
arr = N.array(((N.nan, N.nan),(N.nan, N.nan)), N.float)
return N.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
def InfBBox():
"""
Returns a BBox object with all -inf and inf entries
"""
arr = N.array(((-N.inf, -N.inf),(N.inf, N.inf)), N.float)
return N.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
class RectBBox(BBox):
"""
subclass of a BBox that can be used for a rotated Rectangle
contributed by MArco Oster (marco.oster@bioquant.uni-heidelberg.de)
"""
def __new__(self, data, edges=None):
return BBox.__new__(self, data)
def __init__(self, data, edges=None):
''' assume edgepoints are ordered such you can walk along all edges with left rotation sense
This may be:
left-top
left-bottom
right-bottom
right-top
or any rotation.
'''
BBox.BBox(data)
self.edges = np.asarray(edges)
print "new rectbbox created"
def ac_leftOf_ab(self, a, b, c):
ab = np.array(b) - np.array(a)
ac = np.array(c) - np.array(a)
return (ac[0]*ab[1] - ac[1]*ab[0]) <= 0
def PointInside(self, point):
print "point inside called"
for edge in xrange(4):
if self.ac_leftOf_ab(self.edges[edge],
self.edges[(edge+1)%4],
point):
continue
else:
return False
return True
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