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 | 3.10.10 (main, Mar 5 2023, 22:26:53) [GCC 12.2.1 20230201] |
| IPython | 8.13.2 |
| Matplotlib | 3.7.1 |
| Numpy | 1.24.3 |
| pyDot | 1.4.2 |
| pyAgrum | 1.8.1 |
Wed May 24 14:46:05 2023 CEST
In [3]:
bn=gum.loadBN("res/alarm.dsl")
gnb.showBN(bn,size='9')
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)
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|---|---|---|---|
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| 0.100 | 0.900 | |
| 0.950 | 0.050 | ||
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| 0.100 | 0.900 | |
| 0.950 | 0.050 | ||
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| 0.010 | 0.990 | |
| 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")