variable elimination inference.map_query error for BayesianModel

Question

I was trying to compute the MAP Query over the variables given the evidence.

from pgmpy.inference import VariableElimination
from pgmpy.models import BayesianModel
import numpy as np
import pandas as pd
values = pd.DataFrame(np.random.randint(low=0, high=2, size=(1000, 5)),
                       columns=['A', 'B', 'C', 'D', 'E'])
model = BayesianModel([('A', 'B'), ('C', 'B'), ('C', 'D'), ('B', 'E')])
model.fit(values)
inference = VariableElimination(model)
phi_query = inference.map_query(['A', 'B'], evidence= {'B':1})

which gives me an error :

Finding Elimination Order: : 100%|██████████| 3/3 [00:00<00:00, 651.66it/s]
Eliminating: E: 100%|██████████| 3/3 [00:00<00:00, 309.08it/s]
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-22-0e47cda916c1> in <module>()
      8 model.fit(values)
      9 inference = VariableElimination(model)
---> 10 phi_query = inference.map_query(['A', 'B'], evidence= {'B':1})

/usr/local/lib/python3.6/dist-packages/pgmpy/inference/ExactInference.py in map_query(self, variables, evidence, elimination_order, show_progress)
    360             return_dict = {}
    361             for var in variables:
--> 362                 return_dict[var] = map_query_results[var]
    363             return return_dict
    364 

KeyError: 'B'

According to the documentation :

Parameters variables (list) – list of variables over which we want to compute the max-marginal.

evidence (dict) – a dict key, value pair as {var: state_of_var_observed} None if no evidence

elimination_order (list) – order of variable eliminations (if nothing is provided) order is computed automatically

So where am I going wrong, why am I getting this error?

EDIT : pgmpy version : 0.1.9

Answer 1

The problem is that you are passing the evidence variable also in the query variables and there aren't any checks to handle this case properly. You already know the state for B as 1 since it is the evidence, you need to just query for A as:

>>> phi_query = inference.map_query(['A'], evidence= {'B':1})
>>> print(phi_query)
{'A': 1}