nakaolab oct19

ci-scripts/yaml_files/5g_rfsimulator/plots.py

@@ -0,0 +1,144 @@
+#!/usr/bin/env python3
+"""
+UE Count Plotter
+----------------
+Parses log lines like:
+[2025-09-08 21:33:40.789676] UE RNTI=44512 ...
+Groups entries into 1-second slots (by wall-clock time) and plots the number of
+unique UEs (by RNTI) per slot for the entire file.
+
+Usage:
+  python ue_count_plot.py /path/to/log.txt [--save output.png] [--no-show]
+
+Notes:
+- Uses matplotlib for a single-line plot.
+- Does not set any colors or styles.
+- For very large logs, this streams line-by-line with O(N) memory in the number
+  of distinct seconds encountered (each holds a set of RNTIs).
+"""
+import argparse
+import datetime as dt
+import re
+import sys
+from collections import defaultdict, OrderedDict
+from typing import Dict, Set, Iterable, Tuple
+
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+
+
+TIMESTAMP_RE = re.compile(r"\[(?P<ts>\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}(?:\.\d{1,6})?)\]")
+RNTI_RE = re.compile(r"\bRNTI=(?P<rnti>\d+)\b")
+
+
+def parse_lines(lines: Iterable[str]) -> Dict[dt.datetime, Set[int]]:
+    """
+    Parse lines and bucket unique RNTIs per second.
+
+    Returns:
+        dict mapping second (datetime truncated to seconds) -> set of RNTIs
+    """
+    buckets: Dict[dt.datetime, Set[int]] = defaultdict(set)
+
+    for line in lines:
+        ts_m = TIMESTAMP_RE.search(line)
+        rnti_m = RNTI_RE.search(line)
+        if not ts_m or not rnti_m:
+            # Skip lines that don't fit the schema
+            continue
+
+        ts_str = ts_m.group("ts")
+        # Parse timestamp with or without fractional seconds
+        # Accept both "%Y-%m-%d %H:%M:%S" and with "%f"
+        if "." in ts_str:
+            ts = dt.datetime.strptime(ts_str, "%Y-%m-%d %H:%M:%S.%f")
+        else:
+            ts = dt.datetime.strptime(ts_str, "%Y-%m-%d %H:%M:%S")
+
+        # Truncate to whole-second wall time
+        ts_minute = ts.replace(second=0, microsecond=0)
+        rnti = int(rnti_m.group("rnti"))
+        buckets[ts_minute].add(rnti)
+    return buckets
+
+
+def sort_and_fill(buckets: Dict[dt.datetime, Set[int]]) -> Tuple[list, list]:
+    """
+    Sorts buckets by time and fills missing seconds with zero counts.
+
+    Returns:
+        times (list[datetime]), counts (list[int])
+    """
+    if not buckets:
+        return [], []
+
+    # Sort keys
+    sorted_times = sorted(buckets.keys())
+    start = sorted_times[0]
+    end = sorted_times[-1]
+
+    all_times = []
+    counts = []
+
+    cur = start
+    one_sec = dt.timedelta(minutes=1)
+    while cur <= end:
+        all_times.append(cur)
+        counts.append(len(buckets.get(cur, set())))
+        cur += one_sec
+
+    return all_times, counts
+
+
+def plot_counts(times: list, counts: list, title: str = "Unique UEs per minute"):
+    """
+    Render a simple matplotlib line plot (no specific colors/styles set).
+    """
+    fig, ax = plt.subplots(figsize=(10, 4))
+    ax.plot(times, counts, linestyle="-")
+    ax.set_title(title)
+    ax.set_xlabel("Time (s)")
+    ax.set_ylabel("Unique UEs")
+    ax.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M:%S"))
+    fig.autofmt_xdate()
+    plt.tight_layout()
+    return fig, ax
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Plot unique UEs (by RNTI) per minute from a log file.")
+    parser.add_argument("--save", help="Optional path to save the plot image (e.g., output.png)")
+    parser.add_argument("--no-show", action="store_true", help="Do not display the plot window")
+    args = parser.parse_args()
+
+    # Read lines
+    try:
+        lines = open("artifacts/mac_stats_20250909_231855.log", "r", encoding="utf-8")
+    except OSError as e:
+        print(f"Error opening {args.logfile}: {e}", file=sys.stderr)
+        sys.exit(1)
+
+    buckets = parse_lines(lines)
+    if lines is not sys.stdin:
+        lines.close()
+
+    times, counts = sort_and_fill(buckets)
+    if not times:
+        print("No valid entries found to plot.", file=sys.stderr)
+        sys.exit(2)
+
+    fig, _ = plot_counts(times, counts)
+
+    if args.save:
+        try:
+            fig.savefig(args.save, dpi=150, bbox_inches="tight")
+            print(f"Saved plot to: {args.save}")
+        except Exception as e:
+            print(f"Failed to save figure: {e}", file=sys.stderr)
+
+    if not args.no_show:
+        plt.show()
+
+
+if __name__ == "__main__":
+    main()