Ejemplo n.º 1
0
   def testDiv(self):
       """ test division """
       a  = Table(['a','b','c','d'],[2,3,4,5],range(2*3*4*5))
       b = Table(['c','b','e'],[4,3,6],range(12*6))
       c = Table(['a','b','c','d','e'],[2,3,4,5,6],range(2*3*4*5*6))
   
       acpt = copy(a.cpt)[...,na.NewAxis]
       bcpt = copy(b.cpt)[...,na.NewAxis,na.NewAxis]
       bcpt.transpose([3,1,0,4,2])
       
       ab = a/b
       cc = c/c
       bb = b/b

       cres = na.ones(2*3*4*5*6)
       cres[0] = 0
       bres = na.ones(12*6)
       bres[0] = 0
       ares = acpt/bcpt
       ares[getnan(ares)] = 0.0

       assert (ab == Table(['a','b','c','d','e'],[2,3,4,5,6],ares) and \
               cc == Table(['a','b','c','d','e'],[2,3,4,5,6],cres) and \
               bb == Table(['c','b','e'],[4,3,6],bres) ), \
              " Division does not work"
Ejemplo n.º 2
0
def evaluate(c, y, x):
	"Evaluates c in the context of _UFuncs, x, and y."
	x,y = (x - SIZE/2) * RATIO, (SIZE/2 - y) * RATIO
	# Misalign some math errors
	x += 1e-10
	y += 1e-10
	result = eval(c, ufunc._UFuncs, dict(x=x,y=y))
	try:
		len(result)
	except TypeError:
		# Idiot c evaluated to a float. This is because the random tree
		# generator picked all constants, without any x or y. Let's be
		# nice and turn it into a bunch of that result.
		result *= ones(type=Float64, shape=(SIZE, SIZE))

	# Normalize the data to interval[0,255]. Do this by finding the
	# minimum and maximum values.
	copy = ravel(result.copy())
	copy.sort()

	for minv in copy:
		if not is_special(minv): break
	else: raise ValueError("Ack! No numbers!")

	for maxv in copy[::-1]:
		if not is_special(maxv): break
		else: break
	else: raise ValueError("Ack! No numbers!")

	print "Min, max:", (minv,maxv)
	diff = maxv-minv+1

	result[ieee.getnan(result)] = minv
	result[ieee.getneginf(result)] = minv
	result[ieee.getposinf(result)] = maxv

	result -= minv
	result /= diff
	result *= 255

	result[ieee.getnan(result)] = 0
	result[ieee.getinf(result)] = 0
	return result.astype(UInt32)
Ejemplo n.º 3
0
   def testIDiv(self):
       """ test inplace division """
       b = Table(['c','b','e'],[4,3,6],range(12*6))
       c = Table(['a','b','c','d','e'],[2,3,4,5,6],range(2*3*4*5*6))
   
       bcpt = b.cpt[...,na.NewAxis,na.NewAxis]
       bcpt.transpose([3,1,0,4,2])
       res = c.cpt/bcpt
       res[getnan(res)] = 0.0

       c /= b

       assert (na.all(c.cpt == res)), \
              " InPlace Division does not work"
Ejemplo n.º 4
0
    def __div__(a, b):
        """
        multiplication
        PRE:
            a=Pr(A); A = {'a','b','c'}
            b=Pr(B); B = {'c','a','d','e'}

        usage:
        c = a/b
        c is a NEW Table instance

        POST:
            c=Pr(A U B) = Pr(a,b,c,d,e)

        Notes :
        -   c keeps the order of the variables in a
        -   any new variables in b (d and e) are added at the end of c in the
            order they appear in b
        -   a and b are not touched during this operation
        -   return a NEW Table instance
        """
        #########################################
        #---TODO: add division with a number
        #########################################
        
        # prepare dimensions in a and b for multiplication
        new, cptb = a.union(b)

        # multiply
        #new.cpt /= cptb  # this does not work correctly for some reason...
        #na.divide(new.cpt,cptb,new.cpt) # does not work either
        new.cpt = new.cpt / cptb    #this one works fine
                                #is this a numarray BUG????        


        ## WARNING, division by zero, avoided using na.Error.setMode(invalid='ignore')
        # replace INFs by 0s
        new.cpt[getnan(new.cpt)] = 0
        #---TODO: replace this very SLOW function with a ufunc

        return new
Ejemplo n.º 5
0
    def __idiv__(a,b):
        """
        in place division
        PRE:
            - B must be a subset of A!!!
            eg.
                a=Pr(A); A = {'a','b','c'}
                b=Pr(B); B = {'c','a'}

        usage:
        a/=b 

        POST:
            a=Pr(A)/Pr(B) = Pr(a,b,c)


        Notes :
        -   a keeps the order of its existing variables
        -   b is not touched during this operation
        -   operation is done in-place for a, a is not the same after the operation
        """
        # prepare dimensions in b for multiplication
        cptb = a.prepareOther(b)

        # multiply in place, a's values are changed
        #a.cpt /= cptb  # this does not work correctly for some reason...
        #na.divide(a.cpt,cptb,a.cpt) # does not work either
        a.cpt = a.cpt / cptb    #this one works fine
                                #is this a numarray BUG????

        ## WARNING, division by zero, avoided using na.Error.setMode(invalid='ignore')
        # replace INFs by 0s
        a.cpt[getnan(a.cpt)] = 0
        #---TODO: replace this very SLOW function with a ufunc
        
        return a