Using pyAgrum¶

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In [1]:

%matplotlib inline
from pylab import *
import matplotlib.pyplot as plt

import os

Initialisation¶

importing pyAgrum
importing pyAgrum.lib tools
loading a BN

In [2]:

import pyAgrum as gum
import pyAgrum.lib.notebook as gnb
gnb.configuration()

Library	Version
OS	posix [linux]
Python	3.11.3 (main, Jun 5 2023, 09:32:32) [GCC 13.1.1 20230429]
IPython	8.14.0
Matplotlib	3.7.2
Numpy	1.25.1
pyDot	1.4.2
pyAgrum	1.8.3.9

Tue Jul 25 09:17:20 2023 CEST

In [3]:

bn=gum.loadBN("res/alarm.dsl")
gnb.showBN(bn,size='9')

No description has been provided for this image

Visualisation and inspection¶

In [4]:

print(bn.variableFromName('SHUNT'))

SHUNT:Labelized({NORMAL|HIGH})

In [5]:

print(bn.cpt(bn.idFromName('SHUNT')))

             ||  SHUNT            |
PULMEM|INTUBA||NORMAL   |HIGH     |
------|------||---------|---------|
TRUE  |NORMAL|| 0.1000  | 0.9000  |
FALSE |NORMAL|| 0.9500  | 0.0500  |
TRUE  |ESOPHA|| 0.1000  | 0.9000  |
FALSE |ESOPHA|| 0.9500  | 0.0500  |
TRUE  |ONESID|| 0.0100  | 0.9900  |
FALSE |ONESID|| 0.0500  | 0.9500  |

In [6]:

gnb.showPotential(bn.cpt(bn.idFromName('SHUNT')),digits=3)

		SHUNT
INTUBATION	PULMEMBOLUS	NORMAL	HIGH
NORMAL	TRUE	0.100	0.900
NORMAL	FALSE	0.950	0.050
ESOPHAGEAL	TRUE	0.100	0.900
ESOPHAGEAL	FALSE	0.950	0.050
ONESIDED	TRUE	0.010	0.990
ONESIDED	FALSE	0.050	0.950

Results of inference¶

It is easy to look at result of inference

In [7]:

gnb.showPosterior(bn,{'SHUNT':'HIGH'},'PRESS')

In [8]:

gnb.showPosterior(bn,{'MINVOLSET':'NORMAL'},'VENTALV')

Overall results

In [9]:

gnb.showInference(bn,size="10")