Network Generator

.gitignore

@@ -8,3 +8,4 @@ __pycache__
 **/.scannerwork
 **/build
 test.py
+test_1.py

PyCTBN/PyCTBN/structure_graph/network_generator.py

@@ -0,0 +1,54 @@
+from .structure import Structure
+from .network_graph import NetworkGraph
+from .conditional_intensity_matrix import ConditionalIntensityMatrix
+from .set_of_cims import SetOfCims
+import numpy as np
+
+class NetworkGenerator(object):
+    def __init__(self, labels, vals):
+        self._labels = labels
+        self._vals = vals
+        self._indxs = np.array([i for i, l in enumerate(labels)])
+        self._graph = None
+        self._cims = None
+
+    def generate_graph(self):
+        edges = [(i, j) for i in self._labels for j in self._labels if np.random.binomial(1, 0.5) == 1 and i != j]
+        indxs = np.array([i for i, l in enumerate(self._labels)])
+        s = Structure(self._labels, self._indxs, self._vals, edges, len(self._labels))
+        self._graph = NetworkGraph(s)
+        self._graph.add_nodes(s.nodes_labels)
+        self._graph.add_edges(s.edges)
+
+    def generate_cims(self, min_val, max_val):
+        self._cims = {}
+
+        for i, l in enumerate(self._labels):
+            p_info = self._graph.get_ordered_by_indx_set_of_parents(l)
+            combs = self._graph.build_p_comb_structure_for_a_node(p_info[2])
+
+            node_cims = []
+            for comb in combs:
+                cim = np.empty(shape=(self._vals[i], self._vals[i]))
+                cim[:] = np.nan
+                
+                for i, c in enumerate(cim):
+                    diag = (max_val - min_val) * np.random.random_sample() + min_val
+                    row = np.random.rand(1, len(cim))[0]
+                    row /= (sum(row) - row[i])
+                    row *= diag
+                    row[i] = -1 * diag
+                    cim[i] = row
+
+                node_cims.append(ConditionalIntensityMatrix(cim = cim))
+                
+            self._cims[l] = SetOfCims(node_id = l, parents_states_number = p_info[2], node_states_number = self._vals[i], p_combs = combs, 
+                cims = np.array(node_cims))
+
+    @property
+    def graph(self) -> NetworkGraph:
+        return self._graph
+
+    @property
+    def cims(self) -> NetworkGraph:
+        return self._cims   

PyCTBN/tests/structure_graph/test_trajectorygenerator.py

@@ -1,11 +0,0 @@
-import unittest
-
-from ...PyCTBN.structure_graph.trajectory_generator import TrajectoryGenerator
-
-class TestTrajectoryGenerator(unittest.TestCase)
-    @classmethod
-    def setUpClass(cls) -> None:
-        
-
-if __name__ == '__main__':
-    unittest.main()

test_trajectorygenerator.py

@@ -22,10 +22,10 @@ class TestTrajectoryGenerator(unittest.TestCase):
         tg = TrajectoryGenerator(self.j1)
         end_time = random.randint(5, 100)
         sigma = tg.CTBN_Sample(end_time)
-        self.assertLessEqual(sigma.loc[len(sigma) - 1].at["Time"], end_time)
+        self.assertLessEqual(sigma.times.loc[len(sigma) - 1].at["Time"], end_time)
         for index, row in sigma.iterrows():
             if index > 0:
-                self.assertLess(sigma.loc[index - 1].at["Time"], row.at["Time"])
+                self.assertLess(sigma.times.loc[index - 1].at["Time"], row.at["Time"])
                 diff = abs(sum(sigma.loc[index - 1, sigma.columns != "Time"]) - 
                     sum(sigma.loc[index, sigma.columns != "Time"]))
                 self.assertEqual(diff, 1)