Potential and Instantiation

pyAgrum.Potential is a multi-dimensional array with a pyAgrum.DiscreteVariable associated to each dimension. It is used to represent probabilities and utilities tables in aGrUMs’ multidimensional (graphical) models with some conventions.

  • The data are stored by iterating over each variable in the sequence.
>>> a=gum.RangeVariable("A","variable A",1,3)
>>> b=gum.RangeVariable("B","variable B",1,2)
>>> p=gum.Potential().add(a).add(b).fillWith([1,2,3,4,5,6]);
>>> print(p)
<A:1|B:1> :: 1 /<A:2|B:1> :: 2 /<A:3|B:1> :: 3 /<A:1|B:2> :: 4 /<A:2|B:2> :: 5 /<A:3|B:2> :: 6

>>> print(p.normalizeAsCPT())
<A:1|B:1> :: 0.166667 /<A:2|B:1> :: 0.333333 /<A:3|B:1> :: 0.5 /<A:1|B:2> :: 0.266667 /<A:2|B:2> :: 0.333333 /<A:3|B:2> :: 0.4
  • For addressing and looping in a pyAgrum.Potential structure, pyAgrum provides Instantiation class which represents a multi-dimensionnal index.
>>> I=gum.Instantiation(p)
>>> print(I)
<A:1|B:1>
>>> I.inc();print(I)
<A:2|B:1>
>>> I.inc();print(I)
<A:3|B:1>
>>> I.inc();print(I)
<A:1|B:2>
>>> I.setFirst();print("{} -> {}".format(I,p.get(I)))
<A:1|B:1> -> 0.16666666666666666
>>> I["B"]="2";print("{} -> {}".format(I,p.get(I)))
<A:1|B:2> -> 0.26666666666666666

>>> c=gum.RangeVariable("C","variable C",1,5)
>>> q=gum.Potential().add(a).add(c).fillWith(1)
>>> print(p+q)
<A:1|C:1|B:1> :: 2 /<A:2|C:1|B:1> :: 3 /<A:3|C:1|B:1> :: 4 /<A:1|C:2|B:1> :: 2 /<A:2|C:2|B:1> :: 3 /<A:3|C:2|B:1> :: 4 /<A:1|C:3|B:1> :: 2 /<A:2|C:3|B:1> :: 3 /<A:3|C:3|B:1> :: 4 /<A:1|C:4|B:1> :: 2 /<A:2|C:4|B:1> :: 3 /<A:3|C:4|B:1> :: 4 /<A:1|C:5|B:1> :: 2 /<A:2|C:5|B:1> :: 3 /<A:3|C:5|B:1> :: 4 /<A:1|C:1|B:2> :: 5 /<A:2|C:1|B:2> :: 6 /<A:3|C:1|B:2> :: 7 /<A:1|C:2|B:2> :: 5 /<A:2|C:2|B:2> :: 6 /<A:3|C:2|B:2> :: 7 /<A:1|C:3|B:2> :: 5 /<A:2|C:3|B:2> :: 6 /<A:3|C:3|B:2> :: 7 /<A:1|C:4|B:2> :: 5 /<A:2|C:4|B:2> :: 6 /<A:3|C:4|B:2> :: 7 /<A:1|C:5|B:2> :: 5 /<A:2|C:5|B:2> :: 6 /<A:3|C:5|B:2> :: 7
>>> print((p*q).margSumOut(["B","C"])) # marginalize p*q over B and C(using sum)
<A:1> :: 25 /<A:2> :: 35 /<A:3> :: 45

Instantiation

class pyAgrum.Instantiation(*args)

Class for assigning/browsing values to tuples of discrete variables.

Instantiation is designed to assign values to tuples of variables and to efficiently loop over values of subsets of variables.

Instantiation() -> Instantiation
default constructor
Instantiation(aI) -> Instantiation
Parameters:
  • aI (pyAgrum.Instantiation) – the Instantiation we copy
Returns:
  • pyAgrum.Instantiation – An empty tuple or a copy of the one in parameters
  • Instantiation is subscriptable therefore values can be easily accessed/modified.

Examples

>>> ## Access the value of A in an instantiation aI
>>> valueOfA = aI['A']
>>> ## Modify the value
>>> aI['A'] = newValueOfA
add(Instantiation self, DiscreteVariable v)

Adds a new variable in the Instantiation.

Parameters:v (pyAgrum.DiscreteVariable) – The new variable added to the Instantiation
Raises:DuplicateElement – If the variable is already in this Instantiation
chgVal(Instantiation self, DiscreteVariable v, int newval)

chgVal(Instantiation self, DiscreteVariable v, int newval) -> Instantiation chgVal(Instantiation self, int varPos, int newval) -> Instantiation chgVal(Instantiation self, str var, int newval) -> Instantiation chgVal(Instantiation self, str var, str newval) -> Instantiation

Assign newval to v (or to the variable at position varPos) in the Instantiation.

Parameters:
  • v (pyAgrum.DiscreteVariable or string) – The variable whose value is assigned (or its name)
  • varPos (int) – The index of the variable whose value is assigned in the tuple of variables of the Instantiation
  • newval (int or string) – The index of the value assigned (or its name)
Returns:

The modified instantiation
Return type:

pyAgrum.Instantiation
Raises:
  • NotFound – If variable v does not belong to the instantiation.
  • OutOfBound – If newval is not a possible value for the variable.
clear(Instantiation self)

Erase all variables from an Instantiation.

contains(Instantiation self, DiscreteVariable v)

contains(Instantiation self, str name) -> bool contains(Instantiation self, DiscreteVariable v) -> bool

Indicates whether a given variable belongs to the Instantiation.

Parameters:v (pyAgrum.DiscreteVariable) – The variable for which the test is made.
Returns:True if the variable is in the Instantiation.
Return type:bool
dec(Instantiation self)

Operator –.

decIn(Instantiation self, Instantiation i)

Operator – for the variables in i.

Parameters:i (pyAgrum.Instantiation) – The set of variables to decrement in this Instantiation
decNotVar(Instantiation self, DiscreteVariable v)

Operator – for vars which are not v.

Parameters:v (pyAgrum.DiscreteVariable) – The variable not to decrement in this Instantiation.
decOut(Instantiation self, Instantiation i)

Operator – for the variables not in i.

Parameters:i (pyAgrum.Instantiation) – The set of variables to not decrement in this Instantiation.
decVar(Instantiation self, DiscreteVariable v)

Operator – for variable v only.

Parameters:v (pyAgrum.DiscreteVariable) – The variable to decrement in this Instantiation.
Raises:NotFound – If variable v does not belong to the Instantiation.
domainSize(Instantiation self)
Returns:The product of the variable’s domain size in the Instantiation.
Return type:int
empty(Instantiation self)
Returns:True if the instantiation is empty.
Return type:bool
end(Instantiation self)
Returns:True if the Instantiation reached the end.
Return type:bool
erase(Instantiation self, DiscreteVariable v)

erase(Instantiation self, str name)

Parameters:v (pyAgrum.DiscreteVariable) – The variable to be removed from this Instantiation.
Raises:NotFound – If v does not belong to this Instantiation.
fromdict(Instantiation self, PyObject * dict)

Change the values in an instantiation from a dict (variable_name:value) where value can be a position (int) or a label (string).

If a variable_name does not occur in the instantiation, nothing is done.

Warning

OutOfBounds raised if a value cannot be found.

hamming(Instantiation self)
Returns:the hamming distance of this instantiation.
Return type:int
inOverflow(Instantiation self)
Returns:True if the current value of the tuple is correct
Return type:bool
inc(Instantiation self)

Operator ++.

incIn(Instantiation self, Instantiation i)

Operator ++ for the variables in i.

Parameters:i (pyAgrum.Instantiation) – The set of variables to increment in this Instantiation.
incNotVar(Instantiation self, DiscreteVariable v)

Operator ++ for vars which are not v.

Parameters:v (pyAgrum.DiscreteVariable) – The variable not to increment in this Instantiation.
incOut(Instantiation self, Instantiation i)

Operator ++ for the variables not in i.

Parameters:i (Instantiation) – The set of variable to not increment in this Instantiation.
incVar(Instantiation self, DiscreteVariable v)

Operator ++ for variable v only.

Parameters:v (pyAgrum.DiscreteVariable) – The variable to increment in this Instantiation.
Raises:NotFound – If variable v does not belong to the Instantiation.
isMutable(Instantiation self)
nbrDim(Instantiation self)
Returns:The number of variables in the Instantiation.
Return type:int
pos(Instantiation self, DiscreteVariable v)
Returns:the position of the variable v.
Return type:int
Parameters:v (pyAgrum.DiscreteVariable) – the variable for which its position is return.
Raises:NotFound – If v does not belong to the instantiation.
rend(Instantiation self)
Returns:True if the Instantiation reached the rend.
Return type:bool
reorder(Instantiation self, pyAgrum.Sequence< pyAgrum.DiscreteVariable * > v)

reorder(Instantiation self, Instantiation i)

Reorder vars of this instantiation giving the order in v (or i).

Parameters:
  • i (pyAgrum.Instantiation) – The sequence of variables with which to reorder this Instantiation.
  • v (list) – The new order of variables for this Instantiation.
setFirst(Instantiation self)

Assign the first values to the tuple of the Instantiation.

setFirstIn(Instantiation self, Instantiation i)

Assign the first values in the Instantiation for the variables in i.

Parameters:i (pyAgrum.Instantiation) – The variables to which their first value is assigned in this Instantiation.
setFirstNotVar(Instantiation self, DiscreteVariable v)

Assign the first values to variables different of v.

Parameters:v (pyAgrum.DiscreteVariable) – The variable that will not be set to its first value in this Instantiation.
setFirstOut(Instantiation self, Instantiation i)

Assign the first values in the Instantiation for the variables not in i.

Parameters:i (pyAgrum.Instantiation) – The variable that will not be set to their first value in this Instantiation.
setFirstVar(Instantiation self, DiscreteVariable v)

Assign the first value in the Instantiation for var v.

Parameters:v (pyAgrum.DiscreteVariable) – The variable that will be set to its first value in this Instantiation.
setLast(Instantiation self)

Assign the last values in the Instantiation.

setLastIn(Instantiation self, Instantiation i)

Assign the last values in the Instantiation for the variables in i.

Parameters:i (pyAgrum.Instantiation) – The variables to which their last value is assigned in this Instantiation.
setLastNotVar(Instantiation self, DiscreteVariable v)

Assign the last values to variables different of v.

Parameters:v (pyAgrum.DiscreteVariable) – The variable that will not be set to its last value in this Instantiation.
setLastOut(Instantiation self, Instantiation i)

Assign the last values in the Instantiation for the variables not in i.

Parameters:i (pyAgrum.Instantiation) – The variables that will not be set to their last value in this Instantiation.
setLastVar(Instantiation self, DiscreteVariable v)

Assign the last value in the Instantiation for var v.

Parameters:v (pyAgrum.DiscreteVariable) – The variable that will be set to its last value in this Instantiation.
setMutable(Instantiation self)
setVals(Instantiation self, Instantiation i)

Assign the values from i in the Instantiation.

Parameters:i (pyAgrum.Instantiation) – An Instantiation in which the new values are searched
Returns:a reference to the instantiation
Return type:pyAgrum.Instantiation
todict(Instantiation self, bool withLabels=False)

Create a dict (variable_name:value) from an instantiation

Parameters:withLabels (boolean) – The value will be a label (string) if True. It will be a position (int) if False.
Returns:The dictionary
Return type:Dict
unsetEnd(Instantiation self)

Alias for unsetOverflow().

unsetOverflow(Instantiation self)

Removes the flag overflow.

val(Instantiation self, int i)

val(Instantiation self, DiscreteVariable var) -> int val(Instantiation self, str name) -> int

Parameters:
  • i (int) – The index of the variable.
  • var (pyAgrum.DiscreteVariable) – The variable the value of which we wish to know
Returns:

the current value of the variable.
Return type:

int
Raises:

NotFound – If the element cannot be found.
variable(Instantiation self, int i)

variable(Instantiation self, str name) -> DiscreteVariable

Parameters:i (int) – The index of the variable
Returns:the variable at position i in the tuple.
Return type:pyAgrum.DiscreteVariable
Raises:NotFound – If the element cannot be found.
variablesSequence(Instantiation self)
Returns:the sequence of DiscreteVariable of this instantiation.
Return type:List

Potential

class pyAgrum.Potential(*args)

Class representing a potential.

Potential() -> Potential
default constructor
Potential(src) -> Potential
Parameters:
  • src (pyAgrum.Potential) – the Potential to copy
KL(Potential self, Potential p)

Check the compatibility and compute the Kullback-Leibler divergence between the potential and.

Parameters:

p (pyAgrum.Potential) – the potential from which we want to calculate the divergence.
Returns:

The value of the divergence
Return type:

float
Raises:
  • gum.InvalidArgument – If p is not compatible with the potential (dimension, variables)
  • gum.FatalError – If a zero is found in p or the potential and not in the other.
abs(Potential self)

Apply abs on every element of the container

Returns:a reference to the modified potential.
Return type:pyAgrum.Potential
add(Potential self, DiscreteVariable v)

Add a discrete variable to the potential.

Parameters:

v (pyAgrum.DiscreteVariable) – the var to be added
Raises:
argmax(Potential self)
argmin(Potential self)
contains(Potential self, DiscreteVariable v)
Parameters:v (pyAgrum.Potential) – a DiscreteVariable.
Returns:True if the var is in the potential
Return type:bool
draw(Potential self)

draw a value using the potential as a probability table.

Returns:the index of the drawn value
Return type:int
empty(Potential self)
Returns:Returns true if no variable is in the potential.
Return type:bool
entropy(Potential self)
Returns:the entropy of the potential
Return type:double
extract(Potential self, Instantiation inst)

extract(Potential self, PyObject * dict) -> Potential

create a new Potential extracted from self given a partial instantiation.

Parameters:
  • inst (pyAgrum.instantiation) – a partial instantiation
  • dict (dict) – a dictionnary containing discrete variables (?)
Returns:

the new Potential
Return type:

pyAgrum.Potential
fill(v)

Deprecated method in pyAgrum>0.12.0. See fillWith instead.

fillWith(Potential self, Potential src)

fillWith(Potential self, Potential src, Vector_string mapSrc) -> Potential fillWith(Potential self, Vector v) -> Potential fillWith(Potential self, double v) -> Potential

Automatically fills the potential with v.

Parameters:v (number or list or pyAgrum.Potential the number of parameters of the Potential) – a value or a list/pyAgrum.Potential containing the values to fill the Potential with.

Warning

if v is a list, the size of the list must be the if v is a pyAgrum.Potential. It must to contain variables with exactly the same names and labels but not necessarily the same variables.

Returns:a reference to the modified potentia
Return type:pyAgrum.Potential
Raises:gum.SizeError – If v size’s does not matches the domain size.
fillWithFunction(s, noise=None)

Automatically fills the potential as a (quasi) deterministic CPT with the evaluation of the expression s.

The expression s gives a value for the first variable using the names of the last variables. The computed CPT is deterministic unless noise is used to add a ‘probabilistic’ noise around the exact value given by the expression.

Examples

>>> import pyAgrum as gum
>>> bn=gum.fastBN("A[3]->B[3]<-C[3]")
>>> bn.cpt("B").fillWithFunction("(A+C)/2")
Parameters:
  • s (str) – an expression using the name of the last variables of the Potential and giving a value to the first variable of the Potential
  • noise (list) – an (odd) list of numerics giving a pattern of ‘probabilistic noise’ around the value.

Warning

The expression may have any numerical values, but will be then transformed to the closest correct value for the range of the variable.

Returns:a reference to the modified potential
Return type:pyAgrum.Potential
Raises:gum.InvalidArgument – If the first variable is Labelized or if the len of the noise is not odd.
findAll(Potential self, double v)
get(Potential self, Instantiation i)
Parameters:i (pyAgrum.Instantiation) – an Instantiation
Returns:the value in the Potential at the position given by the instantiation
Return type:double
inverse(Potential self)
isNonZeroMap(Potential self)
Returns:a boolean-like potential using the predicate isNonZero
Return type:pyAgrum.Potential
log2(Potential self)

log2 all the values in the Potential

Warning

When the Potential contains 0 or negative values, no exception are raised but -inf or nan values are assigned.

loopIn()

Generator to iterate inside a Potential.

Yield an gum.Instantiation that iterates over all the possible values for the gum.Potential

Examples

>>> import pyAgrum as gum
>>> bn=gum.fastBN("A[3]->B[3]<-C[3]")
>>> for i in bn.cpt("B").loopIn():
      print(i)
      print(bn.cpt("B").get(i))
      bn.cpt("B").set(i,0.3)
margMaxIn(Potential self, PyObject * varnames)

Projection using max as operation.

Parameters:varnames (set) – the set of vars to keep
Returns:the projected Potential
Return type:pyAgrum.Potential
margMaxOut(Potential self, PyObject * varnames)

Projection using max as operation.

Parameters:varnames (set) – the set of vars to eliminate
Returns:the projected Potential
Return type:pyAgrum.Potential
Raises:gum.InvalidArgument – If varnames contains only one variable that does not exist in the Potential
margMinIn(Potential self, PyObject * varnames)

Projection using min as operation.

Parameters:varnames (set) – the set of vars to keep
Returns:the projected Potential
Return type:pyAgrum.Potential
margMinOut(Potential self, PyObject * varnames)

Projection using min as operation.

Parameters:varnames (set) – the set of vars to eliminate
Returns:the projected Potential
Return type:pyAgrum.Potential

Warning

InvalidArgument raised if varnames contains only one variable that does not exist in the Potential

margProdIn(Potential self, PyObject * varnames)

Projection using multiplication as operation.

Parameters:varnames (set) – the set of vars to keep
Returns:the projected Potential
Return type:pyAgrum.Potential
margProdOut(Potential self, PyObject * varnames)

Projection using multiplication as operation.

Parameters:varnames (set) – the set of vars to eliminate
Returns:the projected Potential
Return type:pyAgrum.Potential
Raises:gum.InvalidArgument – If varnames contains only one variable that does not exist in the Potential
margSumIn(Potential self, PyObject * varnames)

Projection using sum as operation.

Parameters:varnames (set) – the set of vars to keep
Returns:the projected Potential
Return type:pyAgrum.Potential
margSumOut(Potential self, PyObject * varnames)

Projection using sum as operation.

Parameters:varnames (set) – the set of vars to eliminate
Returns:the projected Potential
Return type:pyAgrum.Potential
Raises:gum.InvalidArgument – If varnames contains only one variable that does not exist in the Potential
max(Potential self)
Returns:the maximum of all elements in the Potential
Return type:double
maxNonOne(Potential self)
Returns:the maximum of non one elements in the Potential
Return type:double
Raises:gum.NotFound – If all value == 1.0
min(Potential self)
Returns:the min of all elements in the Potential
Return type:double
minNonZero(Potential self)
Returns:the min of non zero elements in the Potential
Return type:double
Raises:gum.NotFound – If all value == 0.0
nbrDim(Potential self)
Returns:the number of vars in the multidimensional container.
Return type:int
newFactory(Potential self)

Erase the Potential content and create a new empty one.

Returns:a reference to the new Potential
Return type:pyAgrum.Potential
noising(Potential self, double alpha)
normalize(Potential self)

Normalize the Potential (do nothing if sum is 0)

Returns:a reference to the normalized Potential
Return type:pyAgrum.Potential
normalizeAsCPT(Potential self)

Normalize the Potential as a CPT

Returns:a reference to the normalized Potential
Return type:pyAgrum.Potential
Raises:gum.FatalError – If some distribution sums to 0
populate(v)

Deprecated method in pyAgrum>0.12.0. See fillWith instead.

pos(Potential self, DiscreteVariable v)
Parameters:v (pyAgrum.DiscreteVariable) – The variable for which the index is returned.
Returns:
Return type:Returns the index of a variable.
Raises:gum.NotFound – If v is not in this multidimensional matrix.
product(Potential self)
Returns:the product of all elements in the Potential
Return type:double
putFirst(Potential self, PyObject * varname)
Parameters:v (pyAgrum.DiscreteVariable) – The variable for which the index should be 0.
Returns:a reference to the modified potential
Return type:pyAgrum.Potential
Raises:gum.InvalidArgument – If the var is not in the potential
random(Potential self)
randomCPT(Potential self)
randomDistribution(Potential self)
remove(Potential self, DiscreteVariable var)
Parameters:v (pyAgrum.DiscreteVariable) – The variable to be removed
Returns:a reference to the modified potential
Return type:pyAgrum.Potential

Warning

IndexError raised if the var is not in the potential

reorganize(Potential self, vector< pyAgrum.DiscreteVariable *, allocator< pyAgrum.DiscreteVariable * > > vars)

reorganize(Potential self, PyObject * varnames) -> Potential

Create a new Potential with another order.

Returns:varnames – a list of the var names in the new order
Return type:list
Returns:a reference to the modified potential
Return type:pyAgrum.Potential
scale(Potential self, double v)

Create a new potential multiplied by v.

Parameters:v (double) – a multiplier
Returns:
Return type:a reference to the modified potential
set(Potential self, Instantiation i, double value)

Change the value pointed by i

Parameters:
  • i (pyAgrum.Instantiation) – The Instantiation to be changed
  • value (double) – The new value of the Instantiation
sq(Potential self)

Square all the values in the Potential

sum(Potential self)
Returns:the sum of all elements in the Potential
Return type:double
toarray()
Returns:the potential as an array
Return type:array
tolist()
Returns:the potential as a list
Return type:list
translate(Potential self, double v)

Create a new potential added with v.

Parameters:v (double) – The value to be added
Returns:
Return type:a reference to the modified potential
var_dims
Returns:a list containing the dimensions of each variables in the potential
Return type:list
var_names
Returns:a list containing the name of each variables in the potential
Return type:list

Warning

Listed in reverse from the variable enumeration order

variable(Potential self, int i)

variable(Potential self, str name) -> DiscreteVariable

Parameters:i (int) – An index of this multidimensional matrix.
Returns:
Return type:the varible at the ith index
Raises:gum.NotFound – If i does not reference a variable in this multidimensional matrix.
variablesSequence()
Returns:a list containing the sequence of variables
Return type:list