Add scripts to ease performance graph generation

perf/generate_graphs.py

@@ -0,0 +1,49 @@
+#!/usr/bin/python
+
+#
+# This script assumes that a CSV file produced by "generate_csv.sh" is provided as input
+#
+
+# configurable values:
+INPUT_FILE_PUSHPULL_TCP_THROUGHPUT="pushpull_tcp_thr_results.csv"
+INPUT_FILE_PUSHPULL_INPROC_THROUGHPUT="pushpull_inproc_thr_results.csv"
+INPUT_FILE_PUBSUBPROXY_INPROC_THROUGHPUT="pubsubproxy_inproc_thr_results.csv"
+INPUT_FILE_REQREP_TCP_LATENCY="reqrep_tcp_lat_results.csv"
+
+
+# dependencies
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+# functions
+
+def plot_throughput(csv_filename, title):
+    message_size_bytes, message_count, pps, mbps = np.loadtxt(csv_filename, delimiter=',', unpack=True)
+    plt.semilogx(message_size_bytes, pps / 1e6, label='PPS [Mmsg/s]', marker='x')
+    plt.semilogx(message_size_bytes, mbps / 1e3, label='Throughput [Mb/s]', marker='o')
+    
+    plt.xlabel('Message size [B]')
+    plt.title(title)
+    plt.legend()
+    plt.show()
+    plt.savefig(csv_filename.replace('.csv', '.png'))
+
+def plot_latency(csv_filename, title):
+    message_size_bytes, message_count, lat = np.loadtxt(csv_filename, delimiter=',', unpack=True)
+    plt.semilogx(message_size_bytes, lat, label='Latency [us]', marker='o')
+    
+    plt.xlabel('Message size [B]')
+    plt.title(title)
+    plt.legend()
+    plt.show()
+    plt.savefig(csv_filename.replace('.csv', '.png'))
+
+
+# main
+
+plot_throughput(INPUT_FILE_PUSHPULL_TCP_THROUGHPUT, 'ZeroMQ PUSH/PULL socket throughput, TCP transport')
+plot_throughput(INPUT_FILE_PUSHPULL_INPROC_THROUGHPUT, 'ZeroMQ PUSH/PULL socket throughput, INPROC transport')
+plot_throughput(INPUT_FILE_PUBSUBPROXY_INPROC_THROUGHPUT, 'ZeroMQ PUB/SUB PROXY socket throughput, INPROC transport')
+plot_latency(INPUT_FILE_REQREP_TCP_LATENCY, 'ZeroMQ REQ/REP socket latency, TCP transport')