Notebook’s tools for causality¶
This file defines some helpers for handling causal concepts in notebooks
- pyAgrum.causal.notebook.getCausalImpact(model, on, doing, knowing=None, values=None)¶
return a HTML representing of the three values defining a causal impact : formula, value, explanation :type model:
CausalModel
:param model: the causal model :type on:Union
[str
,Set
[str
]] :param on: the impacted variable(s) :type doing:Union
[str
,Set
[str
]] :param doing: the variable(s) of intervention :type knowing:Optional
[Set
[str
]] :param knowing: the variable(s) of evidence :param values : values for certain variables- Return type
Tuple
[str
,Potential
,str
]- Returns
a triplet (CausalFormula representation (string), pyAgrum.Potential, explanation)
- Parameters
values (
Optional
[Dict
[str
,int
]]) –
- pyAgrum.causal.notebook.getCausalModel(cm, size=None)¶
return a HTML representing the causal model :type cm:
CausalModel
:param cm: the causal model :param size: passd :param vals: :rtype:str
:return:
- pyAgrum.causal.notebook.showCausalImpact(model, on, doing, knowing=None, values=None)¶
display a HTML representing of the three values defining a causal impact : formula, value, explanation :type model:
CausalModel
:param model: the causal model :type on:Union
[str
,Set
[str
]] :param on: the impacted variable(s) :type doing:Union
[str
,Set
[str
]] :param doing: the variable(s) of intervention :type knowing:Optional
[Set
[str
]] :param knowing: the variable(s) of evidence :param values : values for certain variables- Parameters
values (
Optional
[Dict
[str
,int
]]) –
- pyAgrum.causal.notebook.showCausalModel(cm, size='4')¶
Shows a graphviz svg representation of the causal DAG
d
- Parameters
cm (
CausalModel
) –size (
str
) –