Fix observation representation in transactions

src/primaite/environment/observations.py

@@ -29,6 +29,7 @@ class AbstractObservationComponent(ABC):
         self.env: "Primaite" = env
         self.space: spaces.Space
         self.current_observation: np.ndarray  # type might be too restrictive?
+        self.structure: list[str]
         return NotImplemented
 
     @abstractmethod
@@ -36,6 +37,11 @@ class AbstractObservationComponent(ABC):
         """Update the observation based on the current state of the environment."""
         self.current_observation = NotImplemented
 
+    @abstractmethod
+    def generate_structure(self) -> List[str]:
+        """Return a list of labels for the components of the flattened observation space."""
+        return NotImplemented
+
 
 class NodeLinkTable(AbstractObservationComponent):
     """Table with nodes and links as rows and hardware/software status as cols.
@@ -79,6 +85,8 @@ class NodeLinkTable(AbstractObservationComponent):
         # 3. Initialise Observation with zeroes
         self.current_observation = np.zeros(observation_shape, dtype=self._DATA_TYPE)
 
+        self.structure = self.generate_structure()
+
     def update(self):
         """Update the observation based on current environment state.
 
@@ -131,6 +139,40 @@ class NodeLinkTable(AbstractObservationComponent):
                 protocol_index += 1
             item_index += 1
 
+    def generate_structure(self):
+        """Return a list of labels for the components of the flattened observation space."""
+        nodes = self.env.nodes.values()
+        links = self.env.links.values()
+
+        structure = []
+
+        for i, node in enumerate(nodes):
+            node_id = node.node_id
+            node_labels = [
+                f"node_{node_id}_id",
+                f"node_{node_id}_hardware_status",
+                f"node_{node_id}_os_status",
+                f"node_{node_id}_fs_status",
+            ]
+            for j, serv in enumerate(self.env.services_list):
+                node_labels.append(f"node_{node_id}_service_{serv}_status")
+
+            structure.extend(node_labels)
+
+        for i, link in enumerate(links):
+            link_id = link.id
+            link_labels = [
+                f"link_{link_id}_id",
+                f"link_{link_id}_n/a",
+                f"link_{link_id}_n/a",
+                f"link_{link_id}_n/a",
+            ]
+            for j, serv in enumerate(self.env.services_list):
+                link_labels.append(f"node_{node_id}_service_{serv}_load")
+
+            structure.extend(link_labels)
+        return structure
+
 
 class NodeStatuses(AbstractObservationComponent):
     """Flat list of nodes' hardware, OS, file system, and service states.
@@ -179,6 +221,7 @@ class NodeStatuses(AbstractObservationComponent):
 
         # 3. Initialise observation with zeroes
         self.current_observation = np.zeros(len(shape), dtype=self._DATA_TYPE)
+        self.structure = self.generate_structure()
 
     def update(self):
         """Update the observation based on current environment state.
@@ -205,6 +248,30 @@ class NodeStatuses(AbstractObservationComponent):
             )
         self.current_observation[:] = obs
 
+    def generate_structure(self):
+        """Return a list of labels for the components of the flattened observation space."""
+        services = self.env.services_list
+
+        structure = []
+        for _, node in self.env.nodes.items():
+            node_id = node.node_id
+            structure.append(f"node_{node_id}_hardware_state_NONE")
+            for state in HardwareState:
+                structure.append(f"node_{node_id}_hardware_state_{state.name}")
+            structure.append(f"node_{node_id}_software_state_NONE")
+            for state in SoftwareState:
+                structure.append(f"node_{node_id}_software_state_{state.name}")
+            structure.append(f"node_{node_id}_file_system_state_NONE")
+            for state in FileSystemState:
+                structure.append(f"node_{node_id}_file_system_state_{state.name}")
+            for service in services:
+                structure.append(f"node_{node_id}_service_{service}_state_NONE")
+                for state in SoftwareState:
+                    structure.append(
+                        f"node_{node_id}_service_{service}_state_{state.name}"
+                    )
+        return structure
+
 
 class LinkTrafficLevels(AbstractObservationComponent):
     """Flat list of traffic levels encoded into banded categories.
@@ -268,6 +335,8 @@ class LinkTrafficLevels(AbstractObservationComponent):
         # 3. Initialise observation with zeroes
         self.current_observation = np.zeros(len(shape), dtype=self._DATA_TYPE)
 
+        self.structure = self.generate_structure()
+
     def update(self):
         """Update the observation based on current environment state.
 
@@ -295,6 +364,21 @@ class LinkTrafficLevels(AbstractObservationComponent):
 
         self.current_observation[:] = obs
 
+    def generate_structure(self):
+        """Return a list of labels for the components of the flattened observation space."""
+        structure = []
+        for _, link in self.env.links.items():
+            link_id = link.id
+            if self._combine_service_traffic:
+                protocols = ["overall"]
+            else:
+                protocols = [protocol.name for protocol in link.protocol_list]
+
+            for p in protocols:
+                for i in range(self._quantisation_levels):
+                    structure.append(f"link_{link_id}_{p}_traffic_level_{i}")
+        return structure
+
 
 class ObservationsHandler:
     """Component-based observation space handler.
@@ -312,11 +396,15 @@ class ObservationsHandler:
     def __init__(self):
         self.registered_obs_components: List[AbstractObservationComponent] = []
 
-        # need to keep track of the flattened and unflattened version of the space (if there is one)
+        # internal the observation space (unflattened version of space if flatten=True)
-        self.space: spaces.Space
+        self._space: spaces.Space
-        self.unflattened_space: spaces.Space
+        # flattened version of the observation space
+        self._flat_space: spaces.Space
+
+        self._observation: Union[Tuple[np.ndarray], np.ndarray]
+        # used for transactions and when flatten=true
+        self._flat_observation: np.ndarray
 
-        self.current_observation: Union[Tuple[np.ndarray], np.ndarray]
         self.flatten: bool = False
 
     def update_obs(self):
@@ -326,17 +414,11 @@ class ObservationsHandler:
             obs.update()
             current_obs.append(obs.current_observation)
 
-        # If there is only one component, don't use a tuple, just pass through that component's obs.
         if len(current_obs) == 1:
-            self.current_observation = current_obs[0]
+            self._observation = current_obs[0]
-        # If there are many compoenents, the space may need to be flattened
         else:
-            if self.flatten:
+            self._observation = tuple(current_obs)
-                self.current_observation = spaces.flatten(
+        self._flat_observation = spaces.flatten(self._space, self._observation)
-                    self.unflattened_space, tuple(current_obs)
-                )
-            else:
-                self.current_observation = tuple(current_obs)
 
     def register(self, obs_component: AbstractObservationComponent):
         """Add a component for this handler to track.
@@ -363,15 +445,28 @@ class ObservationsHandler:
         for obs_comp in self.registered_obs_components:
             component_spaces.append(obs_comp.space)
 
-        # If there is only one component, don't use a tuple space, just pass through that component's space.
+        # if there are multiple components, build a composite tuple space
         if len(component_spaces) == 1:
-            self.space = component_spaces[0]
+            self._space = component_spaces[0]
         else:
-            self.unflattened_space = spaces.Tuple(component_spaces)
+            self._space = spaces.Tuple(component_spaces)
-            if self.flatten:
+        self._flat_space = spaces.flatten_space(self._space)
-                self.space = spaces.flatten_space(spaces.Tuple(component_spaces))
+
-            else:
+    @property
-                self.space = self.unflattened_space
+    def space(self):
+        """Observation space, return the flattened version if flatten is True."""
+        if self.flatten:
+            return self._flat_space
+        else:
+            return self._space
+
+    @property
+    def current_observation(self):
+        """Current observation, return the flattened version if flatten is True."""
+        if self.flatten:
+            return self._flat_observation
+        else:
+            return self._observation
 
     @classmethod
     def from_config(cls, env: "Primaite", obs_space_config: dict):
@@ -417,3 +512,17 @@ class ObservationsHandler:
 
         handler.update_obs()
         return handler
+
+    def describe_structure(self):
+        """Create a list of names for the features of the obs space.
+
+        The order of labels follows the flattened version of the space.
+        """
+        # as it turns out it's not possible to take the gym flattening function and apply it to our labels so we have
+        # to fake it. each component has to just hard-code the expected label order after flattening...
+
+        labels = []
+        for obs_comp in self.registered_obs_components:
+            labels.extend(obs_comp.structure)
+
+        return labels

src/primaite/environment/primaite_env.py

@@ -318,7 +318,8 @@ class Primaite(Env):
             datetime.now(), self.agent_identifier, self.episode_count, self.step_count
         )
         # Load the initial observation space into the transaction
-        transaction.set_obs_space_pre(copy.deepcopy(self.env_obs))
+        transaction.set_obs_space_pre(self.obs_handler._flat_observation)
+
         # Load the action space into the transaction
         transaction.set_action_space(copy.deepcopy(action))
 
@@ -400,7 +401,7 @@ class Primaite(Env):
         # 7. Update env_obs
         self.update_environent_obs()
         # Load the new observation space into the transaction
-        transaction.set_obs_space_post(copy.deepcopy(self.env_obs))
+        transaction.set_obs_space_post(self.obs_handler._flat_observation)
 
         # 8. Add the transaction to the list of transactions
         self.transaction_list.append(copy.deepcopy(transaction))

src/primaite/main.py

@@ -325,6 +325,7 @@ def run(training_config_path: Union[str, Path], lay_down_config_path: Union[str,
         transaction_list=transaction_list,
         session_path=session_dir,
         timestamp_str=timestamp_str,
+        obs_space_description=env.obs_handler.describe_structure(),
     )
 
     print("Updating Session Metadata file...")

src/primaite/transactions/transactions_to_file.py

@@ -22,24 +22,12 @@ def turn_action_space_to_array(_action_space):
         return [str(_action_space)]
 
 
-def turn_obs_space_to_array(_obs_space, _obs_assets, _obs_features):
+def write_transaction_to_file(
-    """
+    transaction_list,
-    Turns observation space into a string array so it can be saved to csv.
+    session_path: Path,
-
+    timestamp_str: str,
-    Args:
+    obs_space_description: list,
-        _obs_space: The observation space
+):
-        _obs_assets: The number of assets (i.e. nodes or links) in the observation space
-        _obs_features: The number of features associated with the asset
-    """
-    return_array = []
-    for x in range(_obs_assets):
-        for y in range(_obs_features):
-            return_array.append(str(_obs_space[x][y]))
-
-    return return_array
-
-
-def write_transaction_to_file(transaction_list, session_path: Path, timestamp_str: str):
     """
     Writes transaction logs to file to support training evaluation.
 
@@ -56,13 +44,13 @@ def write_transaction_to_file(transaction_list, session_path: Path, timestamp_st
     # This will be tied into the PrimAITE Use Case so that they make sense
     template_transation = transaction_list[0]
     action_length = template_transation.action_space.size
-    obs_shape = template_transation.obs_space_post.shape
+    # obs_shape = template_transation.obs_space_post.shape
-    obs_assets = template_transation.obs_space_post.shape[0]
+    # obs_assets = template_transation.obs_space_post.shape[0]
-    if len(obs_shape) == 1:
+    # if len(obs_shape) == 1:
-        # bit of a workaround but I think the way transactions are written will change soon
+    # bit of a workaround but I think the way transactions are written will change soon
-        obs_features = 1
+    # obs_features = 1
-    else:
+    # else:
-        obs_features = template_transation.obs_space_post.shape[1]
+    # obs_features = template_transation.obs_space_post.shape[1]
 
     # Create the action space headers array
     action_header = []
@@ -70,12 +58,8 @@ def write_transaction_to_file(transaction_list, session_path: Path, timestamp_st
         action_header.append("AS_" + str(x))
 
     # Create the observation space headers array
-    obs_header_initial = []
+    obs_header_initial = [f"pre_{o}" for o in obs_space_description]
-    obs_header_new = []
+    obs_header_new = [f"post_{o}" for o in obs_space_description]
-    for x in range(obs_assets):
-        for y in range(obs_features):
-            obs_header_initial.append("OSI_" + str(x) + "_" + str(y))
-            obs_header_new.append("OSN_" + str(x) + "_" + str(y))
 
     # Open up a csv file
     header = ["Timestamp", "Episode", "Step", "Reward"]
@@ -98,12 +82,8 @@ def write_transaction_to_file(transaction_list, session_path: Path, timestamp_st
             csv_data = (
                 csv_data
                 + turn_action_space_to_array(transaction.action_space)
-                + turn_obs_space_to_array(
+                + transaction.obs_space_pre.tolist()
-                    transaction.obs_space_pre, obs_assets, obs_features
+                + transaction.obs_space_post.tolist()
-                )
-                + turn_obs_space_to_array(
-                    transaction.obs_space_post, obs_assets, obs_features
-                )
             )
             csv_writer.writerow(csv_data)