From e43d9d3be1437823c89e473cf09346b8d30fd947 Mon Sep 17 00:00:00 2001
From: Francisco Coelho <fc@uevora.pt>
Date: Thu, 4 May 2023 15:41:12 +0100
Subject: [PATCH] AMartins | Tarefa 01 | 01

---
 students/amartins/tarefas/asia2.bif       | 60 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 students/amartins/tarefas/graph_asia2.png | Bin 0 -> 33454 bytes
 students/amartins/tarefas/tarefa1a.py     | 38 ++++++++++++++++++++++++++++++++++++++
 students/amartins/tarefas/tarefa1b.py     | 35 +++++++++++++++++++++++++++++++++++
 students/amartins/tarefas/v01-tarefa1a.py | 31 +++++++++++++++++++++++++++++++
 5 files changed, 164 insertions(+), 0 deletions(-)
 create mode 100644 students/amartins/tarefas/asia2.bif
 create mode 100644 students/amartins/tarefas/graph_asia2.png
 create mode 100644 students/amartins/tarefas/tarefa1a.py
 create mode 100644 students/amartins/tarefas/tarefa1b.py
 create mode 100644 students/amartins/tarefas/v01-tarefa1a.py

diff --git a/students/amartins/tarefas/asia2.bif b/students/amartins/tarefas/asia2.bif
new file mode 100644
index 0000000..1543625
--- /dev/null
+++ b/students/amartins/tarefas/asia2.bif
@@ -0,0 +1,60 @@
+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;
+}
diff --git a/students/amartins/tarefas/graph_asia2.png b/students/amartins/tarefas/graph_asia2.png
new file mode 100644
index 0000000..5f3d141
Binary files /dev/null and b/students/amartins/tarefas/graph_asia2.png differ
diff --git a/students/amartins/tarefas/tarefa1a.py b/students/amartins/tarefas/tarefa1a.py
new file mode 100644
index 0000000..a6c2fc4
--- /dev/null
+++ b/students/amartins/tarefas/tarefa1a.py
@@ -0,0 +1,38 @@
+import bnlearn as bn
+
+asia = bn.import_DAG("asia2.bif")
+
+model = asia['model'] # Cria um objeto BayesianModel
+
+
+
+nos = model.nodes()
+print("Número de nós:", len(nos))        #resposta à pergunta "quantos nós tem a rede?"
+
+print("Lista de nós:", nos)
+
+asc = 0
+des = 0
+nos_in = 0
+nos_out = 0
+
+for x in nos:
+    # Obtem os nós pais e filhos de cada nós
+    parents = model.get_parents(x)
+    children = model.get_children(x)
+    
+    if len(parents) != 0:
+        asc += 1
+    if len(children) != 0:
+        des += 1
+    nos_in += len(children)
+    nos_out += len(parents)
+    
+#resposta à pergunta "quantos nós são descendentes? quantos são ascendentes?"
+print("Nós ascendentes: ", asc)
+print("Nós descendentes: ", des)
+# resposta à pergunta "qual é o número médio de arestas "in"? e "out"?"
+nos_in = nos_in/len(nos)
+nos_out = nos_out/len(nos)
+print("Número médio de arestas in: ", nos_in)
+print("Número médio de arestas out: ", nos_out)
\ No newline at end of file
diff --git a/students/amartins/tarefas/tarefa1b.py b/students/amartins/tarefas/tarefa1b.py
new file mode 100644
index 0000000..f0ddec1
--- /dev/null
+++ b/students/amartins/tarefas/tarefa1b.py
@@ -0,0 +1,35 @@
+import bnlearn as bn
+import networkx as nx
+import pydot
+from networkx.drawing.nx_pydot import graphviz_layout
+
+asia = bn.import_DAG("asia2.bif")
+model = asia['model']
+
+# DiGraph do networkx
+G = nx.DiGraph()
+
+for node in model.nodes:
+    G.add_node(node)
+
+for edge in model.edges:
+    G.add_edge(edge[0], edge[1])
+
+# objeto pydot
+dot = pydot.Dot(graph_type='digraph')
+
+for node in model.nodes:
+    dot.add_node(pydot.Node(node))
+
+for edge in model.edges:
+    dot.add_edge(pydot.Edge(edge[0], edge[1]))
+
+# defina o layout do grafo
+pos = graphviz_layout(G, prog='dot')
+
+# desenhe o grafo usando o networkx
+nx.draw(G, pos, with_labels=True)
+
+# renderize o grafo com o pydot
+graph = pydot.graph_from_dot_data(dot.to_string())[0]
+graph.write_png('graph_asia2.png')
diff --git a/students/amartins/tarefas/v01-tarefa1a.py b/students/amartins/tarefas/v01-tarefa1a.py
new file mode 100644
index 0000000..bac9ca2
--- /dev/null
+++ b/students/amartins/tarefas/v01-tarefa1a.py
@@ -0,0 +1,31 @@
+import bnlearn as bn
+
+asia = bn.import_DAG("asia2.bif")
+
+model = asia['model'] # Cria um objeto BayesianModel
+
+
+
+nos = model.nodes()
+print("Número de nós:", len(nos))        #resposta à pergunta "quantos nós tem a rede?"
+
+print("Lista de nós:", nos)
+
+nos_in = 0
+nos_out = 0
+
+for x in nos:
+    # Obtem os nós pais e filhos de cada nós
+    parents = model.get_parents(x)
+    children = model.get_children(x)
+    #resposta à pergunta "quantos nós são descendentes? quantos são ascendentes?"
+    print("Pais de ", x, ": ", parents)
+    print("Filhos de ", x, " :", children)
+    nos_in += len(children)
+    nos_out += len(parents)
+
+# resposta à pergunta "qual é o número médio de arestas "in"? e "out"?"
+nos_in = nos_in/len(nos)
+nos_out = nos_out/len(nos)
+print("Número médio de arestas in: ", nos_in)
+print("Número médio de arestas out: ", nos_out)
\ No newline at end of file
--
libgit2 0.21.2