X-Git-Url: https://git.saurik.com/wxWidgets.git/blobdiff_plain/f6342fb5e6524edffa219d5843536ea279bba4df..0b0849b5a5d530095bc0da325d0a7a2101ddb0d6:/wxPython/wx/lib/floatcanvas/Utilities/BBox.py?ds=inline

diff --git a/wxPython/wx/lib/floatcanvas/Utilities/BBox.py b/wxPython/wx/lib/floatcanvas/Utilities/BBox.py
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+"""
+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__(BBox, 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 ( (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 Merge(self, BB):
+        """
+        Joins this bounding box with the one passed in, maybe making this one bigger
+
+        """ 
+
+        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]
+    
+    ### 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
+
+        """
+        return N.all(self.Array__eq__(BB))
+        
+
+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
+
+    """
+
+    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
+   
+   
+   
+