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.
>>> import pyAgrum as gum
>>> 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 |
B ||1 |2 |3 |
------||---------|---------|---------|
1 || 1.0000 | 2.0000 | 3.0000 |
2 || 4.0000 | 5.0000 | 6.0000 |
If a
pyAgrum.Potential
with the sequence ofpyAgrum.DiscreteVariable
X,Y,Z represents a conditional probability Table (CPT), it will be P(X|Y,Z).
>>> print(p.normalizeAsCPT())
|| A |
B ||1 |2 |3 |
------||---------|---------|---------|
1 || 0.1667 | 0.3333 | 0.5000 |
2 || 0.2667 | 0.3333 | 0.4000 |
For addressing and looping in a
pyAgrum.Potential
structure, pyAgrum providesInstantiation
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(f"{I} -> {p.get(I)}")
<A:1|B:1> -> 0.16666666666666666
>>> I["B"]="2";print(f"{I} -> {p.get(I)}")
<A:1|B:2> -> 0.26666666666666666
pyAgrum.Potential
include tensor operators (see for instance this notebook).
>>> c=gum.RangeVariable("C","variable C",1,5)
>>> q=gum.Potential().add(a).add(c).fillWith(1)
>>> print(p+q)
|| A |
C |B ||1 |2 |3 |
------|------||---------|---------|---------|
1 |1 || 1.1667 | 1.3333 | 1.5000 |
2 |1 || 1.1667 | 1.3333 | 1.5000 |
3 |1 || 1.1667 | 1.3333 | 1.5000 |
4 |1 || 1.1667 | 1.3333 | 1.5000 |
5 |1 || 1.1667 | 1.3333 | 1.5000 |
1 |2 || 1.2667 | 1.3333 | 1.4000 |
2 |2 || 1.2667 | 1.3333 | 1.4000 |
3 |2 || 1.2667 | 1.3333 | 1.4000 |
4 |2 || 1.2667 | 1.3333 | 1.4000 |
5 |2 || 1.2667 | 1.3333 | 1.4000 |
>>> print((p*q).sumOut(["B","C"])) # marginalize p*q over B and C(using sum)
A |
1 |2 |3 |
---------|---------|---------|
2.1667 | 3.3333 | 4.5000 |
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(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
- Return type:
None
- addVarsFromModel(model, names)
From a graphical model, add all the variable whose names are in the iterable
- Parameters:
model (pyAgrum.GraphicalModel)
network (a (discrete) graphical model such as Bayesian)
field (Markov random)
Diagram (Influence)
etc.
names (iterable of strings)
string) (a list/set/etc of names of variables (as)
- Returns:
pyAgrum.Instantiation
the current instantiation (self) in order to chain methods.
- chgVal(*args)
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:
- Raises:
NotFound – If variable v does not belong to the instantiation.
OutOfBounds – If newval is not a possible value for the variable.
- clear()
Erase all variables from an Instantiation.
- Return type:
None
- contains(*args)
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()
Operator –.
- Return type:
None
- decIn(i)
Operator – for the variables in i.
- Parameters:
i (pyAgrum.Instantiation) – The set of variables to decrement in this Instantiation
- Return type:
None
- decNotVar(v)
Operator – for vars which are not v.
- Parameters:
v (pyAgrum.DiscreteVariable) – The variable not to decrement in this Instantiation.
- Return type:
None
- decOut(i)
Operator – for the variables not in i.
- Parameters:
i (pyAgrum.Instantiation) – The set of variables to not decrement in this Instantiation.
- Return type:
None
- decVar(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.
- Return type:
None
- domainSize()
- Returns:
The product of the variable’s domain size in the Instantiation.
- Return type:
int
- empty()
- Returns:
True if the instantiation is empty.
- Return type:
bool
- end()
- Returns:
True if the Instantiation reached the end.
- Return type:
bool
- erase(*args)
- Parameters:
v (pyAgrum.DiscreteVariable) – The variable to be removed from this Instantiation.
- Raises:
NotFound – If v does not belong to this Instantiation.
- Return type:
None
- fromdict(dict)
Change the values in an instantiation from a dictionary {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.
- Parameters:
dict (
object
)- Return type:
- hamming()
- Returns:
the hamming distance of this instantiation.
- Return type:
int
- inOverflow()
- Returns:
True if the current value of the tuple is correct
- Return type:
bool
- inc()
Operator ++.
- Return type:
None
- incIn(i)
Operator ++ for the variables in i.
- Parameters:
i (pyAgrum.Instantiation) – The set of variables to increment in this Instantiation.
- Return type:
None
- incNotVar(v)
Operator ++ for vars which are not v.
- Parameters:
v (pyAgrum.DiscreteVariable) – The variable not to increment in this Instantiation.
- Return type:
None
- incOut(i)
Operator ++ for the variables not in i.
- Parameters:
i (Instantiation) – The set of variable to not increment in this Instantiation.
- Return type:
None
- incVar(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.
- Return type:
None
- isMutable()
- Return type:
bool
- nbrDim()
- Returns:
The number of variables in the Instantiation.
- Return type:
int
- pos(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()
- Returns:
True if the Instantiation reached the rend.
- Return type:
bool
- reorder(*args)
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.
- Return type:
None
- setFirst()
Assign the first values to the tuple of the Instantiation.
- Return type:
None
- setFirstIn(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.
- Return type:
None
- setFirstNotVar(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.
- Return type:
None
- setFirstOut(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.
- Return type:
None
- setFirstVar(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.
- Return type:
None
- setLast()
Assign the last values in the Instantiation.
- Return type:
None
- setLastIn(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.
- Return type:
None
- setLastNotVar(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.
- Return type:
None
- setLastOut(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.
- Return type:
None
- setLastVar(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.
- Return type:
None
- setMutable()
- Return type:
None
- setVals(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:
- todict(withLabels=False)
Create a dictionary {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. Default is False
- Returns:
The dictionary
- Return type:
Dict[str,int]
- unsetEnd()
Alias for unsetOverflow().
- Return type:
None
- unsetOverflow()
Removes the flag overflow.
- Return type:
None
- val(*args)
- 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(*args)
- Parameters:
i (int) – The index of the variable
- Returns:
the variable at position i in the tuple.
- Return type:
- Raises:
NotFound – If the element cannot be found.
- variablesSequence()
- Returns:
a list containing the sequence of variables
- 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(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:
pyAgrum.InvalidArgument – If p is not compatible with the potential (dimension, variables)
pyAgrum.FatalError – If a zero is found in p or the potential and not in the other.
- abs()
Apply abs on every element of the container
- Returns:
a reference to the modified potential.
- Return type:
- add(v)
Add a discrete variable to the potential.
- Parameters:
v (pyAgrum.DiscreteVariable) – the var to be added
- Raises:
DuplicateElement – If the variable is already in this Potential.
InvalidArgument – If the variable is empty.
- Returns:
a reference to the modified potential.
- Return type:
- argmax()
- Returns:
the list of positions of the max and the max of all elements in the Potential
- Return type:
Tuple[Dict[str,int],float]
- argmin()
- Returns:
the list of positions of the min and the min of all elements in the Potential
- Return type:
Tuple[Dict[str,int],float]
- contains(v)
- Parameters:
v (pyAgrum.Potential) – a DiscreteVariable.
- Returns:
True if the var is in the potential
- Return type:
bool
- domainSize()
- Return type:
int
- draw()
draw a value using the potential as a probability table.
- Returns:
the index of the drawn value
- Return type:
int
- empty()
- Returns:
Returns true if no variable is in the potential.
- Return type:
bool
- entropy()
- Returns:
the entropy of the potential
- Return type:
float
- static evEq(v, val)
- Parameters:
v (
DiscreteVariable
)val (
float
)
- Return type:
- static evGt(v, val)
- Parameters:
v (
DiscreteVariable
)val (
float
)
- Return type:
- static evIn(v, val1, val2)
- Parameters:
v (
DiscreteVariable
)val1 (
float
)val2 (
float
)
- Return type:
- static evLt(v, val)
- Parameters:
v (
DiscreteVariable
)val (
float
)
- Return type:
- expectedValue(*args)
Calculate the mathematical expected value of a (joint) random variable using the given function as an argument.
- Parameters:
func (function(Dict[str,int])->float) – A function that takes a single argument, representing the value of a python representation of a pyAgrum.Instantiation (as a dictionary), and returns a float.
Warning
The pyAgrum.Potential is assumed to contain a joint distribution.
Examples
>>> def log2cptA(x): ... return -math.log2(bn.cpt('A')[x]) >>> entropy_of_A=bn.cpt('A').expectedValue(log2cptA) # OK it A has no parents.
- Returns:
The mathematical expected value of the random variable calculated using the given function as an argument.
- Return type:
float
- extract(*args)
create a new Potential extracted from self given a partial instantiation.
- Parameters:
inst (pyAgrum.instantiation) – a partial instantiation
dict (Dict[str,str|int]) – a dictionnary containing values for some discrete variables.
Warning
if the dictionnary contains a key that is not the name of a variable in the pyAgrum.Potential, this key is just not used without notification. Then pyAgrum.Potential.extract concerns only the variables that both are in the Potential and in the dictionnary.
- Returns:
the new Potential
- Return type:
- fillFromDistribution(distribution, **s_fns)
Automatically fills the potential as a familly of distributions whose parameters are found using evaluation of the expressions s_fns.
The symbolic expressions s_fns gives a value for the named parameters of the distributions.
Examples
>>> import pyAgrum as gum >>> bn=pyAgrum.fastBN('A[3]->B[3]<-C[3]') >>> bn.cpt('B').fillFromFunction('(A+C)/2')
- Parameters:
s_fns (a list of named arguments (str)) – the named arguments with an evaluation of the expressions in s_fns are passed as argument for the chosen distribution.
- Returns:
a reference to the modified potential
- Return type:
- Raises:
pyAgrum.InvalidArgument – If the first variable is Labelized.
- fillFromExpression(s_fn)
Automatically fills the potential with the evaluation of the expression s_fn (no matter if is a CPT or not).
The symbolic expression s_fn gives a value for each parameters of the Potential
Examples
>>> import pyAgrum as gum >>> bn=pyAgrum.fastBN('A[3]->B[3]<-C[3]') >>> bn.cpt('B').fillFromFunction('(B+A+C)/2')
- Parameters:
s_fn (str) – a symbolic expression using the name of the variables of the Potential and giving a value to the first variable of the Potential. This evaluation is done in a context that inclides ‘math’ module.
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:
- fillFromFunction(s_fn)
Automatically fills the potential as a deterministic CPT with the evaluation of the expression s_fn.
The symbolic expression s_fn gives a value for the first variable, depending on the following variables. The computed CPT is deterministic.
Examples
>>> import pyAgrum as gum >>> bn=pyAgrum.fastBN('A[3]->B[3]<-C[3]') >>> bn.cpt('B').fillFromFunction('(A+C)/2')
- Parameters:
s_fn (str) – a symbolic expression using the name of the second and following variables of the Potential and giving a value to the first variable of the Potential. This evaluation is done in a context that inclides ‘math’ module.
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:
- Raises:
pyAgrum.InvalidArgument – If the first variable is Labelized.
- fillWith(*args)
Automatically fills the potential with v.
- Parameters:
v (number or list of values or pyAgrum.Potential) – a value or a list/pyAgrum.Potential containing the values to fill the Potential with.
mapping (list|tuple|dict)
Warning
if v is a list, the size of the list must be the size of the potential
if v is a ref:pyAgrum.Potential, it must contain variables with exactly the same names and labels but not necessarily the same variables. If
If the second argument mapping is given, mapping explains how to map the variables of the potential source to the variables of the potential destination.
If mapping is a sequence, the order follows the same order as destination.names. If mapping is a dict, the keys are the names in the destination and the values are the names in the source.
- Returns:
a reference to the modified potentia
- Return type:
- Raises:
pyAgrum.SizeError – If v size’s does not matches the domain size.
pyAgrum.ArgumentError – If anything wrong with the arguments.
- 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=pyAgrum.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
Warning
The expression may have any numerical values, but will be then transformed to the closest correct value for the range of the variable.
Note
Deprecated. Please use pyAgrum.Potential.fillFromFunction instead.
- Returns:
a reference to the modified potential
- Return type:
- Raises:
pyAgrum.InvalidArgument – If the first variable is Labelized or Integer, or if the len of the noise is not odd.
- findAll(v)
- Parameters:
v (
float
)- Return type:
List
[Dict
[str
,int
]]
- get(i)
- Parameters:
i (pyAgrum.Instantiation) – an Instantiation
- Returns:
the value in the Potential at the position given by the instantiation
- Return type:
float
- isEvidence()
- Return type:
bool
- isNonZeroMap()
- Returns:
a boolean-like potential using the predicate isNonZero.
- Return type:
- log2()
log2 all the values in the Potential :rtype:
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 pyAgrum.Instantiation that iterates over all the possible values for the pyAgrum.Potential
Examples
>>> import pyAgrum as gum >>> bn=pyAgrum.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(V)
- margMaxOut(V)
- margMinIn(V)
- margMinOut(V)
- margProdIn(V)
- margProdOut(V)
- margSumIn(V)
- margSumOut(V)
- max()
- Returns:
the maximum of all elements in the Potential
- Return type:
float
- maxIn(*args)
Projection using max as operation.
- Parameters:
varnames (set) – the set of vars to keep
- Returns:
the projected Potential
- Return type:
- maxNonOne()
- Returns:
the maximum of non one elements in the Potential
- Return type:
float
- Raises:
pyAgrum.NotFound – If all value == 1.0
- maxOut(*args)
Projection using max as operation.
- Parameters:
varnames (set) – the set of vars to eliminate
- Returns:
the projected Potential
- Return type:
- Raises:
pyAgrum.InvalidArgument – If varnames contains only one variable that does not exist in the Potential
- memoryFootprint()
get the size (in byte) of the Potential representation in memory
- Returns:
the size in byte of the representation of the Potential in memory.
- Return type:
int
- min()
- Returns:
the min of all elements in the Potential
- Return type:
float
- minIn(*args)
Projection using min as operation.
- Parameters:
varnames (set) – the set of vars to keep
- Returns:
the projected Potential
- Return type:
- minNonZero()
- Returns:
the min of non zero elements in the Potential
- Return type:
float
- Raises:
pyAgrum.NotFound – If all value == 0.0
- minOut(*args)
Projection using min as operation.
- Parameters:
varnames (set) – the set of vars to eliminate
- Returns:
the projected Potential
- Return type:
Warning
InvalidArgument raised if varnames contains only one variable that does not exist in the Potential
- property names
- Returns:
a list containing the name of each variables in the potential
- Return type:
list
Warning
listed in the reverse order of the enumeration order of the variables.
- nbrDim(*args)
- Returns:
the number of vars in the multidimensional container.
- Return type:
int
- newFactory()
Erase the Potential content and create a new empty one.
- Returns:
a reference to the new Potential
- Return type:
- normalize()
Normalize the Potential (do nothing if sum is 0)
- Returns:
a reference to the normalized Potential
- Return type:
- normalizeAsCPT(varId=0)
Normalize the Potential as a CPT
- Returns:
a reference to the normalized Potential
- Return type:
- Raises:
pyAgrum.FatalError – If some distribution sums to 0
- Parameters:
varId (
int
)
- pos(v)
- Parameters:
v (pyAgrum.DiscreteVariable) – The variable for which the index is returned.
- Return type:
int
- Returns:
Returns the index of a variable.
- Raises:
pyAgrum.NotFound – If v is not in this multidimensional matrix.
- prodIn(*args)
Projection using multiplication as operation.
- Parameters:
varnames (set) – the set of vars to keep
- Returns:
the projected Potential
- Return type:
- prodOut(*args)
Projection using multiplication as operation.
- Parameters:
varnames (set) – the set of vars to eliminate
- Returns:
the projected Potential
- Return type:
- Raises:
pyAgrum.InvalidArgument – If varnames contains only one variable that does not exist in the Potential
- product()
- Returns:
the product of all elements in the Potential
- Return type:
float
- putFirst(varname)
- Parameters:
v (pyAgrum.DiscreteVariable) – The variable for which the index should be 0.
varname (
str
)
- Returns:
a reference to the modified potential
- Return type:
- Raises:
pyAgrum.InvalidArgument – If the var is not in the potential
- remove(var)
- Parameters:
v (pyAgrum.DiscreteVariable) – The variable to be removed
- Returns:
a reference to the modified potential
- Return type:
Warning
IndexError raised if the var is not in the potential
- Parameters:
var (
DiscreteVariable
)
- reorganize(*args)
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:
- scale(v)
Create a new potential multiplied by v.
- Parameters:
v (float) – a multiplier
- Return type:
- Returns:
a reference to the modified potential
- set(i, value)
Change the value pointed by i
- Parameters:
i (pyAgrum.Instantiation) – The Instantiation to be changed
value (float) – The new value of the Instantiation
- Return type:
None
- property shape
- Returns:
a list containing the dimensions of each variables in the potential
- Return type:
list
Warning
p.shape and p[:].shape list the dimensions in different order
- sum()
- Returns:
the sum of all elements in the Potential
- Return type:
float
- sumIn(*args)
Projection using sum as operation.
- Parameters:
varnames (set) – the set of vars to keep
- Returns:
the projected Potential
- Return type:
- sumOut(*args)
Projection using sum as operation.
- Parameters:
varnames (set) – the set of vars to eliminate
- Returns:
the projected Potential
- Return type:
- Raises:
pyAgrum.InvalidArgument – If varnames contains only one variable that does not exist in the Potential
- property thisown
The membership flag
- toarray()
- Returns:
the potential as an array
- Return type:
array
- toclipboard(**kwargs)
Write a text representation of object to the system clipboard. This can be pasted into spreadsheet, for instance.
- tolatex()
Render object to a LaTeX tabular.
Requires to include booktabs package in the LaTeX document.
- Returns:
the potential as LaTeX string
- Return type:
str
- tolist()
- Returns:
the potential as a list
- Return type:
list
- topandas()
- Returns:
the potential as an pandas.DataFrame
- Return type:
pandas.DataFrame
- translate(v)
Create a new potential added with v.
- Parameters:
v (float) – The value to be added
- Return type:
- Returns:
a reference to the modified potential
- property var_dims
- Returns:
a list containing the dimensions of each variables in the potential
- Return type:
list
Warning
This methods is deprecated. Please use pyAgrum.Potential.shape and note the change in the order !
var_dims return a list in the reverse order of the enumeration order of the variables.
- property var_names
- Returns:
a list containing the name of each variables in the potential
- Return type:
list
Warning
This methods is deprecated. Please use pyAgrum.Potential.names and note the change in the order !
var_names return a list in the reverse order of the enumeration order of the variables.
- variable(*args)
- Parameters:
i (int) – An index of this multidimensional matrix.
- Return type:
- Returns:
the varible at the ith index
- Raises:
pyAgrum.NotFound – If i does not reference a variable in this multidimensional matrix.
- variablesSequence()
- Returns:
a list containing the sequence of variables
- Return type:
list