WIP: Plot data with pandas.

analyse_udp.py

+#!/usr/bin/env python3
+import os
+from argparse import ArgumentParser
+from datetime import datetime
+
+import matplotlib
+import pandas as pd
+import matplotlib.pyplot as plt
+
+matplotlib.use('TkAgg')
+
+
+def plot_packet_arrivals(csv_file):
+    direction = "uplink" if "uplink" in csv_file else "downlink"
+    bitrate = csv_file.split("bitrate")[1].split("_")[0]
+    transmission_df = pd.read_csv(csv_file)
+    transmission_df["departure_time"] = transmission_df["departure_time"] - transmission_df["departure_time"].iloc[0]
+    transmission_df["arrival_time"] = transmission_df["arrival_time"] - transmission_df["arrival_time"].iloc[0]
+
+    transmission_df["data.len_send_cum"] = transmission_df[
+        "data.len_send"
+    ].cumsum()
+    transmission_df["data.len_received_cum"] = transmission_df[
+        "data.len_received"
+    ].cumsum()
+
+    lossed_packets = transmission_df[transmission_df['delay'].isna()]
+
+    print("Packetloss: {}%".format((len(lossed_packets.departure_time) / len(transmission_df.departure_time)) * 100 ))
+
+
+
+    #axes = transmission_df.plot(x="arrival_time", y="data.len_received_cum")
+
+    fig, all_axes = plt.subplots(2, 1)
+    fig.suptitle("CBR {} {}".format(bitrate, direction))
+    fig.subplots_adjust(hspace=0.3)
+    axes = all_axes[0]
+    axes_boxplot = all_axes[1]
+
+    transmission_df.plot(ax=axes, x="departure_time", y="data.len_send_cum")
+    transmission_df.plot(ax=axes, x="arrival_time", y="data.len_received_cum")
+    lossed_packets.plot.scatter(ax=axes, x="departure_time", y="data.len_send_cum", color="y", marker="X")
+    #axes = transmission_df.boxplot(column="delay")
+
+    axes.legend(["D(t)", "A(t)"])
+    axes.set_ylabel("Byte")
+    axes.set_xlabel("t [s]")
+
+    delay_axes = axes.twinx()
+    delay_axes.set_ylabel("delay [s]")
+    transmission_df.plot(ax=delay_axes, x="arrival_time", y="delay", color="g", linestyle="dotted")
+
+    transmission_df.boxplot(ax=axes_boxplot, column="delay", vert=False)
+    axes_boxplot.set_xlabel("[s]")
+
+    #fig = axes.get_figure()
+    #fig.suptitle("CBR {} {}".format(bitrate, direction))
+    #fig.show()
+    fig.savefig(csv_file.replace(".csv", ".pdf"))
+
+
+if __name__ == "__main__":
+    start_time = datetime.now()
+    parser = ArgumentParser()
+
+    parser.add_argument("-f", "--folder", required=True, help="Folder with csv files.")
+    parser.add_argument(
+        "-o",
+        "--output",
+        required=False,
+        default=None,
+        help="Destination for plots as pdf.",
+    )
+    parser.add_argument(
+        "--name_contains", required=False, default=".csv", help="Substring in filename."
+    )
+    parser.add_argument(
+        "--use_subdirs", required=False, default=False, help="Use csvs in subdirs."
+    )
+
+    args = parser.parse_args()
+
+    csv_list = list()
+
+    if args.use_subdirs:
+        sub_dirs = os.listdir(args.folder)
+        for d in sub_dirs:
+            filenames = os.listdir("{}{}".format(args.folder, d))
+            for filename in filenames:
+                if filename.endswith(".csv") and args.name_contains in filename:
+                    csv_list.append("{}/{}".format(d, filename))
+    else:
+        filenames = os.listdir(args.folder)
+        for filename in filenames:
+            if filename.endswith(".csv") and args.name_contains in filename:
+                csv_list.append(filename)
+
+    for csv in csv_list:
+        plot_packet_arrivals("{}/{}".format(args.folder, csv))