def factor_sum(A, B):
"""Same as factor_product, but sums instead of multiplies
"""
if A.is_empty():
return B
if B.is_empty():
return A
# Create output factor. Variables should be the union between of the
# variables contained in the two input factors
out = Factor()
out.var = np.union1d(A.var, B.var)
# Compute mapping between the variable ordering between the two factors
# and the output to set the cardinality
out.card = np.zeros(len(out.var), np.int64)
mapA = np.argmax(out.var[None, :] == A.var[:, None], axis=-1)
mapB = np.argmax(out.var[None, :] == B.var[:, None], axis=-1)
out.card[mapA] = A.card
out.card[mapB] = B.card
# For each assignment in the output, compute which row of the input factors
# it comes from
out.val = np.zeros(np.prod(out.card))
assignments = out.get_all_assignments()
idxA = assignment_to_index(assignments[:, mapA], A.card)
idxB = assignment_to_index(assignments[:, mapB], B.card)
""" YOUR CODE HERE
You should populate the .val field with the factor sum. The code for this
should be very similar to the factor_product().
"""
out.val = A.val[idxA] + B.val[idxB]
return out
def factor_product(A, B):
"""Compute product of two factors.
Suppose A = phi(X_1, X_2), B = phi(X_2, X_3), the function should return
phi(X_1, X_2, X_3)
"""
if A.is_empty():
return B
if B.is_empty():
return A
# Create output factor. Variables should be the union between of the
# variables contained in the two input factors
out = Factor()
out.var = np.union1d(A.var, B.var)
# Compute mapping between the variable ordering between the two factors
# and the output to set the cardinality
out.card = np.zeros(len(out.var), np.int64)
mapA = np.argmax(out.var[None, :] == A.var[:, None], axis=-1)
mapB = np.argmax(out.var[None, :] == B.var[:, None], axis=-1)
out.card[mapA] = A.card
out.card[mapB] = B.card
# For each assignment in the output, compute which row of the input factors
# it comes from
out.val = np.zeros(np.prod(out.card))
assignments = out.get_all_assignments()
idxA = assignment_to_index(assignments[:, mapA], A.card)
idxB = assignment_to_index(assignments[:, mapB], B.card)
out.val = A.val[idxA] * B.val[idxB]
""" YOUR CODE HERE
You should populate the .val field with the factor product
Hint: The code for this function should be very short (~1 line). Try to
understand what the above lines are doing, in order to implement
subsequent parts.
"""
return out
def factor_product(A, B):
"""
Computes the factor product of A and B e.g. A = f(x1, x2); B = f(x1, x3); out=f(x1, x2, x3) = f(x1, x2)f(x1, x3)
Args:
A: first Factor
B: second Factor
Returns:
Returns the factor product of A and B
"""
out = Factor()
""" YOUR CODE HERE, HINT: copy from lab2 part 1! """
if A.is_empty():
return B
if B.is_empty():
return A
out = Factor()
# Set the variables of the output
out.var = np.union1d(A.var, B.var)
# Set the cardinality of the output
out.card = np.zeros(len(out.var), np.int64)
mapA = np.argmax(out.var[None, :] == A.var[:, None], axis=-1)
mapB = np.argmax(out.var[None, :] == B.var[:, None], axis=-1)
out.card[mapA] = A.card
out.card[mapB] = B.card
# Initialize the factor values to zero
out.val = np.zeros(np.prod(out.card))
assignments = out.get_all_assignments()
idxA = assignment_to_index(assignments[:, mapA], A.card)
idxB = assignment_to_index(assignments[:, mapB], B.card)
# Populate the factor values
out.val = A.val[idxA] * B.val[idxB]
""" END YOUR CODE HERE """
return out
