def setpot(pot, evvariables, evidstates):
#FIXME: data format needed to be unified
vars = pot.variables
#vars = np.array(pot.variables) # convert to ndarray format
#evariables = np.array(evvariables)
# convert to ndarray format
#evidstates = np.array(evidstates) # convert to ndarray format
#print "variables:", vars
table = pot.table
nstates = pot.card
#print "number of states:", nstates
#print "vars:", vars
#print "evvariables:", evvariables
intersection, iv, iev = intersect(vars, evvariables)
#iv = np.array(iv)
#iev = np.array(iev)
#print "intersection:", intersection
#print "iv:", iv
#print "iev:", iev
#print "iv type:", type(iv)
#print "number of intersection:", intersection.size
if intersection.size == 0:
newpot = copy.copy(pot)
else:
newvar = setminus(vars, intersection)
dummy, idx = ismember(newvar, vars)
newns = nstates[idx]
newpot = potential()
newpot.variables = newvar
newpot.card = newns
newpot.table = np.zeros(newns)
#print "idx:", idx
#print "iv:", iv
for i in range(np.prod(newns)):
newassign = IndexToAssignment(i, newns)
oldassign = np.zeros(nstates.size, 'int8')
oldassign[idx] = newassign
oldassign[iv] = evidstates
#print "newpot.table.shape:", newpot.table.shape
#print "newassign:", newassign
#print "newassign type:", type(newassign)
newpot.table[tuple(newassign)] = pot.table[tuple(oldassign)]
return newpot
def setpot(pot, evvariables, evidstates):
#FIXME: data format needed to be unified
vars = pot.variables
#vars = np.array(pot.variables) # convert to ndarray format
#evariables = np.array(evvariables)
# convert to ndarray format
#evidstates = np.array(evidstates) # convert to ndarray format
#print "variables:", vars
table = pot.table
nstates = pot.card
#print "number of states:", nstates
#print "vars:", vars
#print "evvariables:", evvariables
intersection, iv, iev = intersect(vars, evvariables)
#iv = np.array(iv)
#iev = np.array(iev)
#print "intersection:", intersection
#print "iv:", iv
#print "iev:", iev
#print "iv type:", type(iv)
#print "number of intersection:", intersection.size
if intersection.size == 0:
newpot = copy.copy(pot)
else:
newvar = setminus(vars, intersection)
dummy, idx = ismember(newvar, vars)
newns = nstates[idx]
newpot = potential()
newpot.variables = newvar
newpot.card = newns
newpot.table = np.zeros(newns)
#print "idx:", idx
#print "iv:", iv
for i in range(np.prod(newns)):
newassign = IndexToAssignment(i, newns)
oldassign = np.zeros(nstates.size, 'int8')
oldassign[idx] = newassign
oldassign[iv] = evidstates
#print "newpot.table.shape:", newpot.table.shape
#print "newassign:", newassign
#print "newassign type:", type(newassign)
newpot.table[tuple(newassign)] = pot.table[tuple(oldassign)]
return newpot
def condpot(pot, varargin):
#FIXME: only 1 varargin supported , use *arg in further development
newpot = potential()
y = []
x = varargin
#print "pot.variables:", pot.variables
#print "pot.table: \n", pot.table
#print "x:", x
#print "pot.variables:", pot.variables
# convert variable to idx (not consistent in Python other than MATLAB)
intersection, ix, ipot = intersect(x, pot.variables)
#print "intersection=", intersection
newpot.variables = intersection
#print "pot.variables:", pot.variables
FULL_axis = np.arange(pot.variables.size)
#print pot.variables
#print intersection
axis_intersection = ipot
#.index(intersection)
other_axis = setminus(FULL_axis, axis_intersection)
#print "axis_intersection=", axis_intersection
#print "other_axis=", other_axis
#print "Full_axis:", FULL_axis
#print "other_axis:", other_axis
newpot.table = np.apply_over_axes(np.sum, pot.table, other_axis)
#print "newpot.variables:", newpot.variables
#print "newpot.table: \n", newpot.table
SUM = potential()
SUM.variables = np.array([])
SUM.table = np.sum(newpot.table)
#print "newpot.table:", newpot.table
#print "SUM.table:", SUM.table
newpot = newpot / SUM
return newpot
def condpot(pot,varargin):
#FIXME: only 1 varargin supported , use *arg in further development
newpot = potential()
y = []
x = varargin
#print "pot.variables:", pot.variables
#print "pot.table: \n", pot.table
#print "x:", x
#print "pot.variables:", pot.variables
# convert variable to idx (not consistent in Python other than MATLAB)
intersection, ix, ipot = intersect(x, pot.variables)
#print "intersection=", intersection
newpot.variables = intersection
#print "pot.variables:", pot.variables
FULL_axis = np.arange(pot.variables.size)
#print pot.variables
#print intersection
axis_intersection = ipot
#.index(intersection)
other_axis = setminus(FULL_axis,axis_intersection)
#print "axis_intersection=", axis_intersection
#print "other_axis=", other_axis
#print "Full_axis:", FULL_axis
#print "other_axis:", other_axis
newpot.table = np.apply_over_axes(np.sum, pot.table, other_axis)
#print "newpot.variables:", newpot.variables
#print "newpot.table: \n", newpot.table
SUM = potential()
SUM.variables = np.array([])
SUM.table = np.sum(newpot.table)
#print "newpot.table:", newpot.table
#print "SUM.table:", SUM.table
newpot = newpot/SUM
return newpot
