Start icosagon.

requirements.txt

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+numpy
+torch
+dataclasses

src/icosagon/__init__.py

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+from .data import Data

src/icosagon/data.py

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+from collections import defaultdict
+from dataclasses import dataclass
+import torch
+
+
+@dataclass
+class NodeType(object):
+    name: str
+    count: int
+
+
+@dataclass
+class RelationType(object):
+    name: str
+    node_type_row: int
+    node_type_column: int
+    adjacency_matrix: torch.Tensor
+    is_autogenerated: bool
+
+
+class Data(object):
+    def __init__(self) -> None:
+        self.node_types = []
+        self.relation_types = defaultdict(lambda: defaultdict(list))
+
+    def add_node_type(self, name: str, count: int) -> None:
+        name = str(name)
+        count = int(count)
+        if not name:
+            raise ValueError('You must provide a non-empty node type name')
+        if count <= 0:
+            raise ValueError('You must provide a positive node count')
+        self.node_types.append(NodeType(name, count))
+
+    def add_relation_type(self, name: str, node_type_row: int, node_type_column: int,
+        adjacency_matrix: torch.Tensor, adjacency_matrix_backward: torch.Tensor = None,
+        two_way: bool = True) -> None:
+
+        name = str(name)
+        node_type_row = int(node_type_row)
+        node_type_column = int(node_type_column)
+
+        if node_type_row < 0 or node_type_row > len(self.node_types):
+            raise ValueError('node_type_row outside of the valid range of node types')
+
+        if node_type_column < 0 or node_type_column > len(self.node_types):
+            raise ValueError('node_type_column outside of the valid range of node types')
+
+        if not isinstance(adjacency_matrix, torch.Tensor):
+            raise ValueError('adjacency_matrix must be a torch.Tensor')
+
+        if adjacency_matrix_backward and not isinstance(adjacency_matrix_backward, torch.Tensor):
+            raise ValueError('adjacency_matrix_backward must be a torch.Tensor')
+
+        if adjacency_matrix.shape != (self.node_types[node_type_row].count,
+            self.node_types[node_type_column].count):
+            raise ValueError('adjacency_matrix shape must be (num_row_nodes, num_column_nodes)')
+
+        if adjacency_matrix_backward is not None and \
+            adjacency_matrix_backward.shape != (self.node_types[node_type_column].count,
+                self.node_types[node_type_row].count):
+            raise ValueError('adjacency_matrix shape must be (num_column_nodes, num_row_nodes)')
+
+        two_way = bool(two_way)
+
+        if node_type_row == node_type_column and \
+            adjacency_matrix_backward is not None:
+            raise ValueError('Relation between nodes of the same type must be expressed using a single matrix')
+
+        self.relation_types[node_type_row][node_type_column].append(
+            RelationType(name, node_type_row, node_type_column,
+                adjacency_matrix, False))
+
+        if node_type_row != node_type_column and two_way:
+            if adjacency_matrix_backward is None:
+                adjacency_matrix_backward = adjacency_matrix.transpose(0, 1)
+            self.relation_types[node_type_column][node_type_row].append(
+                RelationType(name, node_type_column, node_type_row,
+                    adjacency_matrix_backward, True))
+
+    def __repr__(self):
+        n = len(self.node_types)
+        if n == 0:
+            return 'Empty Icosagon Data'
+        s = ''
+        s += 'Icosagon Data with:\n'
+        s += '- ' + str(n) + ' node type(s):\n'
+        for nt in self.node_types:
+            s += '  - ' + nt.name + '\n'
+        if len(self.relation_types) == 0:
+            s += '- No relation types\n'
+            return s.strip()
+
+        s_1 = ''
+        count = 0
+        for i in range(n):
+            for j in range(n):
+                if i not in self.relation_types or \
+                    j not in self.relation_types[i]:
+                    continue
+
+                s_1 += '  - ' + self.node_types[i].name + ' -- ' + \
+                    self.node_types[j].name + ':\n'
+
+                for r in self.relation_types[i][j]:
+                    if r.is_autogenerated:
+                        continue
+                    s_1 += '    - ' + r.name + '\n'
+                    count += 1
+
+        s += '- %d relation type(s):\n' % count
+        s += s_1
+
+        return s.strip()
+
+        # n = sum(map(len, self.relation_types))
+        #
+        # for i in range(n):
+        #     for j in range(n):
+        #         key = (i, j)
+        #         if key not in self.relation_types:
+        #             continue
+        #         rels = self.relation_types[key]
+        #
+        #         for r in rels:
+        #
+        # return s.strip()

tests/icosagon/test_data.py

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+from icosagon import Data
+import torch
+import pytest
+
+
+def test_data_01():
+    d = Data()
+    d.add_node_type('Gene', 1000)
+    d.add_node_type('Drug', 100)
+    dummy_0 = torch.zeros((100, 1000))
+    dummy_1 = torch.zeros((1000, 100))
+    dummy_2 = torch.zeros((100, 100))
+    dummy_3 = torch.zeros((1000, 1000))
+    d.add_relation_type('Target', 1, 0, dummy_0)
+    d.add_relation_type('Interaction', 0, 0, dummy_3)
+    d.add_relation_type('Side Effect: Nausea', 1, 1, dummy_2)
+    d.add_relation_type('Side Effect: Infertility', 1, 1, dummy_2)
+    d.add_relation_type('Side Effect: Death', 1, 1, dummy_2)
+    print(d)
+
+
+def test_data_02():
+    d = Data()
+    d.add_node_type('Gene', 1000)
+    d.add_node_type('Drug', 100)
+    dummy_0 = torch.zeros((100, 1000))
+    dummy_1 = torch.zeros((1000, 100))
+    dummy_2 = torch.zeros((100, 100))
+    dummy_3 = torch.zeros((1000, 1000))
+    with pytest.raises(ValueError):
+        d.add_relation_type('Target', 1, 0, dummy_1)
+    with pytest.raises(ValueError):
+        d.add_relation_type('Interaction', 0, 0, dummy_2)
+    with pytest.raises(ValueError):
+        d.add_relation_type('Side Effect: Nausea', 1, 1, dummy_3)
+    with pytest.raises(ValueError):
+        d.add_relation_type('Side Effect: Infertility', 1, 1, dummy_3)
+    with pytest.raises(ValueError):
+        d.add_relation_type('Side Effect: Death', 1, 1, dummy_3)
+    print(d)
+
+
+def test_data_03():
+    d = Data()
+    d.add_node_type('Gene', 1000)
+    d.add_node_type('Drug', 100)
+    with pytest.raises(ValueError):
+        d.add_relation_type('Target', 1, 0, None)
+    print(d)