updated i-15 scenario

Author: Isaac Peterson

matsimAI/run_gradient_flow_matching.py

@@ -6,6 +6,8 @@
 from torch.utils.tensorboard import SummaryWriter
 import datetime
 from tqdm import tqdm
+import xml.etree.ElementTree as ET
+from xml.dom import minidom
 
 def main(args):
 
@@ -16,9 +18,33 @@ def main(args):
     network_name = Path(args.network_path).stem
     save_path = Path(output_path, f"{unique_time_string}_nclusters_{args.num_clusters}_{network_name}")
     tensorboard_path = Path(save_path, "logs")
+    writer = SummaryWriter(tensorboard_path)
+
+
     os.makedirs(tensorboard_path)
+    
+    tree = ET.parse(args.config_path)
+    root = tree.getroot()
+    for module in root.findall("module"):
+        if module.attrib.get("name") == "counts":
+            for param in module.findall("param"):
+                if param.attrib.get("name") == "countsScaleFactor":
+                    param.attrib["value"] = str(args.percent_pop)
+            else:
+                ET.SubElement(module, "param", {"name": "countsScaleFactor", "value": str(args.percent_pop)})
 
-    writer = SummaryWriter(tensorboard_path)
+    temp_path = "temp_output.xml"
+    tree.write(temp_path, encoding="utf-8", xml_declaration=False)
+
+    with open(temp_path, "r", encoding="utf-8") as f:
+        xml_content = f.read()
+
+    with open(args.config_path, "w", encoding="utf-8") as f:
+        f.write('<?xml version="1.0"?>\n')
+        f.write('<!DOCTYPE config SYSTEM "http://www.matsim.org/files/dtd/config_v2.dtd">\n')
+        f.write(xml_content)
+
+    os.remove(temp_path)
 
     if not os.path.exists(output_path):
         os.makedirs(output_path)
@@ -45,7 +71,8 @@ def main(args):
     parameters = [W]
 
     TAM = TAM.reshape(-1, Z_2)
-    TARGET = dataset.target_graph.edge_attr.to(device).to(torch.float32)
+    percent_pop_float = float(args.percent_pop) / 100
+    TARGET = dataset.target_graph.edge_attr.to(device).to(torch.float32) * percent_pop_float
 
     optimizer = torch.optim.Adam(parameters, lr=0.001)
     pbar = tqdm(range(args.training_steps))
@@ -70,7 +97,7 @@ def main(args):
         if step % args.log_interval == 0:
             pbar.set_description(f"Loss: {loss.item()}")
             writer.add_scalar("Loss/mse", loss.item(), step)
-            writer.add_scalar("Logs/mad", torch.abs(R[sensor_idxs] - TARGET[sensor_idxs]).sum() / target_size, step)
+            writer.add_scalar("Logs/mad", torch.abs(R[sensor_idxs] - (TARGET[sensor_idxs])).sum() / target_size, step)
 
         if step != 0 and \
         args.save_interval > 0 and \
@@ -95,7 +122,7 @@ def main(args):
     if args.best_plans_save_path is not None:
         dataset.save_plans_from_flow_res(
             best_model.reshape(args.num_clusters, args.num_clusters, 24),
-            Path(args.best_plans_save_path, "best_plans.xml")
+            Path(args.best_plans_save_path)
         )
 
 if __name__ == "__main__":
@@ -104,6 +131,8 @@ def main(args):
     parser.add_argument("results_path", help="path to the output folder for the results of the algorithm")
     parser.add_argument("network_path", help="path to matsim xml network")
     parser.add_argument("counts_path", help="path to matsim xml counts")
+    parser.add_argument("config_path", help="path to matsim xml config path")
+    parser.add_argument("--percent_pop", type=str, default=100, help="The percentage of the population to match to between 0-100.")
     parser.add_argument("--num_clusters", type=int, required=True, help="number of clusters for the network")
     parser.add_argument("--training_steps", type=int, required=True, help="number of training iterations")
     parser.add_argument("--log_interval", type=int, required=True, help="tensorboard logging interval")

scenarios/i-15-scenario/i-15-config.xml

@@ -1,4 +1,4 @@
-<?xml version="1.0" ?>
+<?xml version="1.0"?>
 <!DOCTYPE config SYSTEM "http://www.matsim.org/files/dtd/config_v2.dtd">
 <config>
     <module name="global">
@@ -18,10 +18,10 @@
         <param name="inputCountsFile" value="i-15-counts.xml" />
         <param name="writeCountsInterval" value="1" />
         <param name="averageCountsOverIterations" value="1" />
-    </module>
+    <param name="countsScaleFactor" value="5" /></module>
 
     <module name="controller">
-        <param name="outputDirectory" value="./output" />
+        <param name="outputDirectory" value="./i-15-output" />
         <param name="firstIteration" value="0" />
         <param name="lastIteration" value="100" />
         <param name="eventsFileFormat" value="xml" />
@@ -49,7 +49,7 @@
         <param name="marginalUtilityOfMoney" value="0" />
 
         <parameterset type="modeParams">
-            <param name="mode" value="car"/>
+            <param name="mode" value="car" />
             <param name="marginalUtilityOfTraveling_util_hr" value="-6.0" />
         </parameterset>
 
@@ -153,4 +153,4 @@
 	</module>
 
 
-</config>
+</config>