Added BIFParser.

models/bif/asia.bif

@@ -0,0 +1,61 @@
+// source: https://www.bnlearn.com/bnrepository/discrete-small.html#asia
+network unknown {
+}
+variable asia {
+  type discrete [ 2 ] { yes, no };
+}
+variable tub {
+  type discrete [ 2 ] { yes, no };
+}
+variable smoke {
+  type discrete [ 2 ] { yes, no };
+}
+variable lung {
+  type discrete [ 2 ] { yes, no };
+}
+variable bronc {
+  type discrete [ 2 ] { yes, no };
+}
+variable either {
+  type discrete [ 2 ] { yes, no };
+}
+variable xray {
+  type discrete [ 2 ] { yes, no };
+}
+variable dysp {
+  type discrete [ 2 ] { yes, no };
+}
+probability ( asia ) {
+  table 0.01, 0.99;
+}
+probability ( tub | asia ) {
+  (yes) 0.05, 0.95;
+  (no) 0.01, 0.99;
+}
+probability ( smoke ) {
+  table 0.5, 0.5;
+}
+probability ( lung | smoke ) {
+  (yes) 0.1, 0.9;
+  (no) 0.01, 0.99;
+}
+probability ( bronc | smoke ) {
+  (yes) 0.6, 0.4;
+  (no) 0.3, 0.7;
+}
+probability ( either | lung, tub ) {
+  (yes, yes) 1.0, 0.0;
+  (no, yes) 1.0, 0.0;
+  (yes, no) 1.0, 0.0;
+  (no, no) 0.0, 1.0;
+}
+probability ( xray | either ) {
+  (yes) 0.98, 0.02;
+  (no) 0.05, 0.95;
+}
+probability ( dysp | bronc, either ) {
+  (yes, yes) 0.9, 0.1;
+  (no, yes) 0.7, 0.3;
+  (yes, no) 0.8, 0.2;
+  (no, no) 0.1, 0.9;
+}

models/bif/cancer.bif

@@ -0,0 +1,38 @@
+// source: https://www.bnlearn.com/bnrepository/discrete-small.html#cancer
+network unknown {
+}
+variable Pollution {
+  type discrete [ 2 ] { low, high };
+}
+variable Smoker {
+  type discrete [ 2 ] { True, False };
+}
+variable Cancer {
+  type discrete [ 2 ] { True, False };
+}
+variable Xray {
+  type discrete [ 2 ] { positive, negative };
+}
+variable Dyspnoea {
+  type discrete [ 2 ] { True, False };
+}
+probability ( Pollution ) {
+  table 0.9, 0.1;
+}
+probability ( Smoker ) {
+  table 0.3, 0.7;
+}
+probability ( Cancer | Pollution, Smoker ) {
+  (low, True) 0.03, 0.97;
+  (high, True) 0.05, 0.95;
+  (low, False) 0.001, 0.999;
+  (high, False) 0.02, 0.98;
+}
+probability ( Xray | Cancer ) {
+  (True) 0.9, 0.1;
+  (False) 0.2, 0.8;
+}
+probability ( Dyspnoea | Cancer ) {
+  (True) 0.65, 0.35;
+  (False) 0.3, 0.7;
+}

models/bif/earthquake.bif

@@ -0,0 +1,38 @@
+// source: https://www.bnlearn.com/bnrepository/discrete-small.html#earthquake
+network unknown {
+}
+variable Burglary {
+  type discrete [ 2 ] { True, False };
+}
+variable Earthquake {
+  type discrete [ 2 ] { True, False };
+}
+variable Alarm {
+  type discrete [ 2 ] { True, False };
+}
+variable JohnCalls {
+  type discrete [ 2 ] { True, False };
+}
+variable MaryCalls {
+  type discrete [ 2 ] { True, False };
+}
+probability ( Burglary ) {
+  table 0.01, 0.99;
+}
+probability ( Earthquake ) {
+  table 0.02, 0.98;
+}
+probability ( Alarm | Burglary, Earthquake ) {
+  (True, True) 0.95, 0.05;
+  (False, True) 0.29, 0.71;
+  (True, False) 0.94, 0.06;
+  (False, False) 0.001, 0.999;
+}
+probability ( JohnCalls | Alarm ) {
+  (True) 0.9, 0.1;
+  (False) 0.05, 0.95;
+}
+probability ( MaryCalls | Alarm ) {
+  (True) 0.7, 0.3;
+  (False) 0.01, 0.99;
+}

models/bif/sachs.bif

@@ -0,0 +1,147 @@
+// source: https://www.bnlearn.com/bnrepository/discrete-small.html#sachs
+network unknown {
+}
+variable Akt {
+  type discrete [ 3 ] { LOW, AVG, HIGH };
+}
+variable Erk {
+  type discrete [ 3 ] { LOW, AVG, HIGH };
+}
+variable Jnk {
+  type discrete [ 3 ] { LOW, AVG, HIGH };
+}
+variable Mek {
+  type discrete [ 3 ] { LOW, AVG, HIGH };
+}
+variable P38 {
+  type discrete [ 3 ] { LOW, AVG, HIGH };
+}
+variable PIP2 {
+  type discrete [ 3 ] { LOW, AVG, HIGH };
+}
+variable PIP3 {
+  type discrete [ 3 ] { LOW, AVG, HIGH };
+}
+variable PKA {
+  type discrete [ 3 ] { LOW, AVG, HIGH };
+}
+variable PKC {
+  type discrete [ 3 ] { LOW, AVG, HIGH };
+}
+variable Plcg {
+  type discrete [ 3 ] { LOW, AVG, HIGH };
+}
+variable Raf {
+  type discrete [ 3 ] { LOW, AVG, HIGH };
+}
+probability ( Akt | Erk, PKA ) {
+  (LOW, LOW) 0.6721176592, 0.3277794919, 0.0001028489;
+  (AVG, LOW) 0.3349505840, 0.6648697215, 0.0001796945;
+  (HIGH, LOW) 7.682262e-05, 1.183068e-01, 8.816163e-01;
+  (LOW, AVG) 0.62038586, 0.37950262, 0.00011152;
+  (AVG, AVG) 0.8214081840, 0.1782019687, 0.0003898473;
+  (HIGH, AVG) 0.177105936, 0.813732581, 0.009161483;
+  (LOW, HIGH) 0.9750859107, 0.0240549828, 0.0008591065;
+  (AVG, HIGH) 9.483619e-01, 5.154733e-02, 9.075234e-05;
+  (HIGH, HIGH) 0.1703412073, 0.8293963255, 0.0002624672;
+}
+probability ( Erk | Mek, PKA ) {
+  (LOW, LOW) 0.85051343, 0.13872433, 0.01076224;
+  (AVG, LOW) 0.3870326, 0.4836913, 0.1292761;
+  (HIGH, LOW) 0.008682883, 0.187958884, 0.803358233;
+  (LOW, AVG) 0.1177122, 0.6919357, 0.1903521;
+  (AVG, AVG) 0.04895789, 0.72823961, 0.22280250;
+  (HIGH, AVG) 0.001153403, 0.748558247, 0.250288351;
+  (LOW, HIGH) 0.07405991, 0.70044614, 0.22549395;
+  (AVG, HIGH) 0.003663004, 0.102564103, 0.893772894;
+  (HIGH, HIGH) 0.03333333, 0.03333333, 0.93333333;
+}
+probability ( Jnk | PKA, PKC ) {
+  (LOW, LOW) 0.2899262, 0.2457641, 0.4643097;
+  (AVG, LOW) 5.766701e-01, 4.232872e-01, 4.271314e-05;
+  (HIGH, LOW) 9.961240e-01, 3.806755e-03, 6.921373e-05;
+  (LOW, AVG) 0.5794436587, 0.4203206035, 0.0002357379;
+  (AVG, AVG) 6.129037e-01, 3.870808e-01, 1.543138e-05;
+  (HIGH, AVG) 0.8623005877, 0.1368597817, 0.0008396306;
+  (LOW, HIGH) 0.00456621, 0.99086758, 0.00456621;
+  (AVG, HIGH) 0.04468980, 0.93495569, 0.02035451;
+  (HIGH, HIGH) 0.155367232, 0.841807910, 0.002824859;
+}
+probability ( Mek | PKA, PKC, Raf ) {
+  (LOW, LOW, LOW) 0.7451772095, 0.2545984747, 0.0002243158;
+  (AVG, LOW, LOW) 7.576915e-01, 2.422767e-01, 3.181572e-05;
+  (HIGH, LOW, LOW) 9.977281e-01, 2.244485e-03, 2.737176e-05;
+  (LOW, AVG, LOW) 0.7066581578, 0.2931291215, 0.0002127207;
+  (AVG, AVG, LOW) 7.148153e-01, 2.851753e-01, 9.338376e-06;
+  (HIGH, AVG, LOW) 0.9689835575, 0.0306427504, 0.0003736921;
+  (LOW, HIGH, LOW) 0.854385965, 0.143859649, 0.001754386;
+  (AVG, HIGH, LOW) 8.256463e-01, 1.743254e-01, 2.831337e-05;
+  (HIGH, HIGH, LOW) 0.725950783, 0.272930649, 0.001118568;
+  (LOW, LOW, AVG) 0.3846008, 0.1231368, 0.4922624;
+  (AVG, LOW, AVG) 0.343172087, 0.649403298, 0.007424615;
+  (HIGH, LOW, AVG) 0.9996370895, 0.0001814553, 0.0001814553;
+  (LOW, AVG, AVG) 0.2692763938, 0.7304863582, 0.0002372479;
+  (AVG, AVG, AVG) 0.27465766, 0.72002723, 0.00531511;
+  (HIGH, AVG, AVG) 0.854385965, 0.143859649, 0.001754386;
+  (LOW, HIGH, AVG) 0.01190476, 0.97619048, 0.01190476;
+  (AVG, HIGH, AVG) 0.1054112554, 0.8943722944, 0.0002164502;
+  (HIGH, HIGH, AVG) 0.006060606, 0.987878788, 0.006060606;
+  (LOW, LOW, HIGH) 0.262181426, 0.001450275, 0.736368299;
+  (AVG, LOW, HIGH) 0.8652899, 0.1010029, 0.0337072;
+  (HIGH, LOW, HIGH) 0.9361046959, 0.0007698229, 0.0631254811;
+  (LOW, AVG, HIGH) 0.85065617, 0.10656168, 0.04278215;
+  (AVG, AVG, HIGH) 0.2814957, 0.5851161, 0.1333882;
+  (HIGH, AVG, HIGH) 0.498470948, 0.498470948, 0.003058104;
+  (LOW, HIGH, HIGH) 0.3333333, 0.3333333, 0.3333333;
+  (AVG, HIGH, HIGH) 0.3333333, 0.3333333, 0.3333333;
+  (HIGH, HIGH, HIGH) 0.3333333, 0.3333333, 0.3333333;
+}
+probability ( P38 | PKA, PKC ) {
+  (LOW, LOW) 0.30691159, 0.06458648, 0.62850193;
+  (AVG, LOW) 0.919186742, 0.078464036, 0.002349223;
+  (HIGH, LOW) 0.80737818, 0.09163898, 0.10098283;
+  (LOW, AVG) 0.6558227251, 0.3439415370, 0.0002357379;
+  (AVG, AVG) 8.149777e-01, 1.850069e-01, 1.543138e-05;
+  (HIGH, AVG) 0.3862301, 0.1595298, 0.4542401;
+  (LOW, HIGH) 0.86757991, 0.12785388, 0.00456621;
+  (AVG, HIGH) 0.80313955, 0.19272946, 0.00413099;
+  (HIGH, HIGH) 0.765536723, 0.231638418, 0.002824859;
+}
+probability ( PIP2 | PIP3, Plcg ) {
+  (LOW, LOW) 9.967915e-01, 3.169817e-03, 3.865631e-05;
+  (AVG, LOW) 9.867112e-01, 1.326991e-02, 1.887612e-05;
+  (HIGH, LOW) 0.872401162, 0.120070734, 0.007528104;
+  (LOW, AVG) 0.997890295, 0.001054852, 0.001054852;
+  (AVG, AVG) 0.9571651090, 0.0424454829, 0.0003894081;
+  (HIGH, AVG) 0.52180956, 0.46245517, 0.01573528;
+  (LOW, HIGH) 0.2218092, 0.4936493, 0.2845415;
+  (AVG, HIGH) 0.07672787, 0.39110315, 0.53216898;
+  (HIGH, HIGH) 0.02641691, 0.05235351, 0.92122959;
+}
+probability ( PIP3 | Plcg ) {
+  (LOW) 0.2184310, 0.4473238, 0.3342453;
+  (AVG) 0.07796694, 0.21120158, 0.71083148;
+  (HIGH) 0.4237055, 0.4396535, 0.1366411;
+}
+probability ( PKA | PKC ) {
+  (LOW) 0.3864255, 0.3794243, 0.2341501;
+  (AVG) 0.06039638, 0.92264651, 0.01695712;
+  (HIGH) 0.01577014, 0.95873839, 0.02549147;
+}
+probability ( PKC ) {
+  table 0.42313152, 0.48163920, 0.09522928;
+}
+probability ( Plcg ) {
+  table 0.81213356, 0.08337962, 0.10448682;
+}
+probability ( Raf | PKA, PKC ) {
+  (LOW, LOW) 0.06232176, 0.14724878, 0.79042946;
+  (AVG, LOW) 0.4475056, 0.3125747, 0.2399197;
+  (HIGH, LOW) 0.84288483, 0.12714563, 0.02996955;
+  (LOW, AVG) 0.3694012, 0.3312117, 0.2993871;
+  (AVG, AVG) 0.55082326, 0.39291391, 0.05626283;
+  (HIGH, AVG) 0.74895046, 0.15952981, 0.09151973;
+  (LOW, HIGH) 0.86757991, 0.12785388, 0.00456621;
+  (AVG, HIGH) 8.842572e-01, 1.156677e-01, 7.510891e-05;
+  (HIGH, HIGH) 0.841807910, 0.155367232, 0.002824859;
+}

src/main/java/ch/idsia/crema/model/io/bif/BIFAttribute.java

@@ -0,0 +1,16 @@
+package ch.idsia.crema.model.io.bif;
+
+/**
+ * Author:  Claudio "Dna" Bonesana
+ * Project: crema
+ * Date:    25.01.2021 10:41
+ */
+class BIFAttribute {
+	String name;
+	String value;
+
+	@Override
+	public String toString() {
+		return "  " + name + " " + value;
+	}
+}

src/main/java/ch/idsia/crema/model/io/bif/BIFBlock.java

@@ -0,0 +1,23 @@
+package ch.idsia.crema.model.io.bif;
+
+import java.util.ArrayList;
+import java.util.List;
+import java.util.stream.Collectors;
+
+/**
+ * Author:  Claudio "Dna" Bonesana
+ * Project: crema
+ * Date:    25.01.2021 10:41
+ */
+class BIFBlock {
+	String type;
+	String name;
+	List<BIFAttribute> attributes = new ArrayList<>();
+
+	@Override
+	public String toString() {
+		return type + " " + String.join(" ", name) + " {\n" +
+				attributes.stream().map(Object::toString).collect(Collectors.joining("\n  ")) +
+				"\n}";
+	}
+}

src/main/java/ch/idsia/crema/model/io/bif/BIFObject.java

@@ -0,0 +1,24 @@
+package ch.idsia.crema.model.io.bif;
+
+import ch.idsia.crema.factor.bayesian.BayesianFactor;
+import ch.idsia.crema.model.graphical.BayesianNetwork;
+
+import java.util.HashMap;
+import java.util.Map;
+
+/**
+ * Author:  Claudio "Dna" Bonesana
+ * Project: crema
+ * Date:    25.01.2021 09:38
+ */
+public class BIFObject {
+
+	public String name;
+	public BayesianNetwork network = new BayesianNetwork();
+	public BayesianFactor[] factors = null;
+
+	public Map<String, Integer> variableName = new HashMap<>();
+	public Map<String, Integer> variableStates = new HashMap<>();
+	public Map<String, BayesianFactor> variableFactors = new HashMap<>();
+
+}