Fix connection graph and truncate

README.md

@@ -27,14 +27,18 @@ Currently `qgym` has support for Python 3.7, 3.8, 3.9, 3.10 and 3.11.
 
 ## Publication
 The paper on `qgym` has been presented in the [1st International Workshop on Quantum Machine Learning: From Foundations to Applications (QML@QCE'23)](https://qml.lfdr.de/2023/).
+The publication can be found on [computer.org](https://www.computer.org/csdl/proceedings-article/qce/2023/432302a026/1SuQRWR5uCI)
 You can find the preprint of the paper on [arxiv](https://arxiv.org/pdf/2308.02536.pdf).
 
 ```terminal
-@article{van2023qgym,
+@inproceedings{van2023qgym,
   title={qgym: A Gym for training and benchmarking RL-based quantum compilation},
-  author={van der Linde, Stan and de Kok, Willem and Bontekoe, Tariq and Feld, Sebastian},
-  journal={arXiv preprint arXiv:2308.02536},
-  year={2023}
+  author={Van Der Linde, Stan and De Kok, Willem and Bontekoe, Tariq and Feld, Sebastian},
+  booktitle={2023 IEEE International Conference on Quantum Computing and Engineering (QCE)},
+  volume={2},
+  pages={26--30},
+  year={2023},
+  organization={IEEE}
 }
 ```
 ## Team
@@ -46,6 +50,6 @@ Building qgym is a joint effort.
 - [Tariq Bontekoe](https://nl.linkedin.com/in/tariq-bontekoe-53214817a)
 - [Sebastian Feld](https://nl.linkedin.com/in/sebastian-feld?)
 
-### Power users
-- Joris Henstra
-- Rares Oancea 
+### Contributors and Power Users
+- [Joris Henstra](https://www.linkedin.com/in/jorishenstra/)
+- [Rares Oancea](https://www.linkedin.com/in/rares-adrian-oancea-8a67b0204/)

docs_files/templates/root_doc.rst_t

@@ -45,15 +45,19 @@ Currently :obj:`~qgym` has support for Python 3.7, 3.8, 3.9, 3.10 and 3.11.
 Publication
 ============
 The paper on :obj:`~qgym` has been presented in the `1st International Workshop on Quantum Machine Learning: From Foundations to Applications (QML@QCE'23) <https://qml.lfdr.de/2023/>`_.
+The publication can be found on `computer.org <https://www.computer.org/csdl/proceedings-article/qce/2023/432302a026/1SuQRWR5uCI>`_.
 You can find the preprint of the paper on `arxiv <https://arxiv.org/pdf/2308.02536.pdf>`_.
 
 .. code-block:: console
 
-   @article{van2023qgym,
+   @inproceedings{van2023qgym,
    title={qgym: A Gym for training and benchmarking RL-based quantum compilation},
-   author={van der Linde, Stan and de Kok, Willem and Bontekoe, Tariq and Feld, Sebastian},
-   journal={arXiv preprint arXiv:2308.02536},
-   year={2023}
+   author={Van Der Linde, Stan and De Kok, Willem and Bontekoe, Tariq and Feld, Sebastian},
+   booktitle={2023 IEEE International Conference on Quantum Computing and Engineering (QCE)},
+   volume={2},
+   pages={26--30},
+   year={2023},
+   organization={IEEE}
    }
 
 Team
@@ -67,11 +71,10 @@ Core developers
 - `Tariq Bontekoe <https://nl.linkedin.com/in/tariq-bontekoe-53214817a>`_
 - `Sebastian Feld <https://nl.linkedin.com/in/sebastian-feld?>`_
 
-Power users
-------------
-- Joris Henstra
-- Rares Oancea 
-
+Contributors and Power Users
+-----------------------------
+- `Joris Henstra <https://www.linkedin.com/in/jorishenstra/>`_
+- `Rares Oancea <https://www.linkedin.com/in/rares-adrian-oancea-8a67b0204/>`_ 
 
 .. toctree::
    :maxdepth: {{ mastertocmaxdepth }}

qgym/__init__.py

@@ -25,4 +25,4 @@
 
 """
 
-__version__ = "0.2.0"
+__version__ = "0.2.1"

qgym/envs/initial_mapping/initial_mapping_state.py

@@ -210,7 +210,7 @@ def is_truncated(self) -> bool:
             is truncated if the number of steps in the current episode is more than 10
             times the number of nodes in the connection graph.
         """
-        return bool(self.steps_done < self.n_nodes * 10)
+        return bool(self.steps_done > self.n_nodes * 10)
 
     def obtain_info(self) -> dict[str, Any]:
         """Obtain additional information.

qgym/utils/input_parsing.py

@@ -1,7 +1,7 @@
 """This module contains function which parse user input.
 
 With parsing we mean that the user input is validated and transformed to a predictable
-format. In this way, user can give different input formats, but internally we are 
+format. In this way, user can give different input formats, but internally we are
 assured that the data has the same format."""
 
 from __future__ import annotations
@@ -105,7 +105,11 @@ def parse_connection_graph(
 
     if grid_size is not None:
         # Generate connection grid graph
-        return nx.grid_graph(grid_size)
+        graph = nx.grid_graph(grid_size)
+
+        # Relabel the nodes to be integers
+        graph = nx.convert_node_labels_to_integers(graph)
+        return graph
 
     raise ValueError("No valid arguments for a connection graph were given")
 

qgym/utils/input_validation.py

@@ -206,8 +206,8 @@ def check_adjacency_matrix(adjacency_matrix: ArrayLike) -> NDArray[Any]:
 
 
 def check_graph_is_valid_topology(graph: nx.Graph, name: str) -> None:
-    """Check if `graph` with name 'name' is an instance of ``networkx.Graph`` and check
-    if the graph is valid topology graph.
+    """Check if `graph` with name 'name' is an instance of ``networkx.Graph``, check
+    if the graph is valid topology graph and check if the nodes are integers.
 
     Args:
         graph: Graph to check.
@@ -226,6 +226,9 @@ def check_graph_is_valid_topology(graph: nx.Graph, name: str) -> None:
     if len(graph) == 0:
         raise ValueError(f"'{name}' has no nodes")
 
+    if any(not isinstance(node, int) for node in graph):
+        raise TypeError(f"'{name}' has nodes that are not integers")
+
 
 def check_instance(x: Any, name: str, dtype: type) -> None:
     """Check if `x` with name 'name' is an instance of dtype.

tests/envs/initial_mapping/test_initial_mapping_env.py

@@ -29,11 +29,32 @@ def small_env(small_graph: nx.Graph) -> InitialMapping:
     return InitialMapping(0.5, connection_graph=small_graph)
 
 
-def test_validity(small_env: InitialMapping) -> None:
-    check_env(
-        small_env, warn=True
-    )  # todo: maybe switch this to the gymnasium env checker
-    assert True
+class TestEnvironment:
+
+    def test_validity(self, small_env: InitialMapping) -> None:
+        # todo: maybe switch this to the gymnasium env checker
+        check_env(small_env, warn=True)
+
+    def test_episode(self, small_env: InitialMapping):
+        obs, reward, is_done, truncated, _ = small_env.step(np.array([0, 1]))
+        np.testing.assert_array_equal(obs["mapping"], [1, 2])
+        assert reward == 0
+        assert not is_done
+        assert not truncated
+
+        obs, reward, is_done, truncated, _ = small_env.step(np.array([1, 0]))
+        np.testing.assert_array_equal(obs["mapping"], [1, 0])
+        assert is_done
+        assert not truncated
+
+    def test_truncation(self, small_env: InitialMapping):
+        truncated = False
+        for _ in range(10000):
+            _, _, is_done, truncated, _ = small_env.step(np.array([0, 0]))
+            if is_done or truncated:
+                break
+        assert not is_done
+        assert truncated
 
 
 @pytest.mark.parametrize(

tests/envs/routing/test_routing_env.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import numpy as np
 import pytest
 from stable_baselines3.common.env_checker import check_env
 
@@ -19,6 +20,12 @@
         },
     ],
 )
-def test_validity(kwargs: dict[str, tuple[int, int] | bool]) -> None:
-    env = Routing(**kwargs)  # type: ignore[arg-type]
-    check_env(env, warn=True)  # todo: maybe switch this to the gym env checker
+class TestEnvironment:
+    def test_validity(self, kwargs: dict[str, tuple[int, int] | bool]) -> None:
+        env = Routing(**kwargs)  # type: ignore[arg-type]
+        check_env(env, warn=True)  # todo: maybe switch this to the gym env checker
+
+    def test_step(self, kwargs):
+        env = Routing(**kwargs)  # type: ignore[arg-type]
+        obs = env.step(0)[0]
+        np.testing.assert_array_equal(obs["mapping"], [2, 1, 0, 3])

tests/utils/test_input_validation.py

@@ -153,19 +153,31 @@ def test_check_adjacency_matrix_errors(self, arg: Any) -> None:
             check_adjacency_matrix(arg)
 
 
-def test_check_graph_is_valid_topology() -> None:
-    graph = nx.Graph()
-    msg = "'test' has no nodes"
-    with pytest.raises(ValueError, match=msg):
+class TestGraphValidTopology:
+    def test_empty_graph(self) -> None:
+        graph = nx.Graph()
+        msg = "'test' has no nodes"
+        with pytest.raises(ValueError, match=msg):
+            check_graph_is_valid_topology(graph, "test")
+
+    def test_line_graph(self) -> None:
+        graph = nx.cycle_graph(2)
         check_graph_is_valid_topology(graph, "test")
 
-    graph.add_edge(1, 2)
-    check_graph_is_valid_topology(graph, "test")
+    def test_self_loop(self) -> None:
+        graph = nx.Graph()
+        graph.add_edge(1, 1)
+        msg = "'test' contains self-loops"
+        with pytest.raises(ValueError, match=msg):
+            check_graph_is_valid_topology(graph, "test")
+
+    def test_non_int_label(self) -> None:
+        graph = nx.Graph()
+        graph.add_node((0, 0))
 
-    graph.add_edge(1, 1)
-    msg = "'test' contains self-loops"
-    with pytest.raises(ValueError, match=msg):
-        check_graph_is_valid_topology(graph, "test")
+        msg = "'test' has nodes that are not integers"
+        with pytest.raises(TypeError, match=msg):
+            check_graph_is_valid_topology(graph, "test")
 
 
 class TestCheckInstance: