Fixes in message tree calculations, plots for the paper, started work on BW plots for the paper

bw_interop/process_bw_output.py

@@ -0,0 +1,45 @@
+import pandas as pd
+import tables as tb
+import numpy as np
+
+
+def bytes_str(bytes):
+    if bytes >= 1024**2:
+        return f"{bytes/(1024**2):.2f} MiB"
+    if bytes >= 1024:
+        return f"{bytes/1024:.2f} KiB"
+    return f"{bytes:.0f} B"
+
+
+def get_topic_messages(h5_filename: str):
+    topic_messages = {}
+
+    with tb.open_file(h5_filename, root_uep="/messages") as f:
+        for node in f.list_nodes("/"):
+            topic = node.title
+            messages = pd.DataFrame.from_records(node[:])
+            topic_messages[topic] = messages
+            # if len(messages) >= 2:
+            #     total_data = np.sum(messages["size"])
+            #     print(f'{len(messages):>5d}m, {bytes_str(total_data):>10s}, '
+            #     f'{bytes_str(total_data / (np.max(messages["timestamp"]) - np.min(messages["timestamp"]))):>10s}/s, '
+            #     f'{topic}')
+
+    return topic_messages
+
+
+def get_topic_stats(topics_dict: dict):
+    records = []
+    for topic, messages in topics_dict:
+        total_data = np.sum(messages["size"])
+        records.append({
+                "topic": topic,
+                "count": len(messages),
+                "total_data": total_data,
+                "bandwidth": total_data / (np.max(messages["timestamp"]) - np.min(messages["timestamp"])),
+                "min_size": np.min(messages["size"]),
+                "avg_size": np.mean(messages["size"]),
+                "max_size": np.max(messages["size"])
+        })
+
+    return pd.DataFrame.from_records(records)