Merge pull request hyperledger#891 from NataliaDracheva/master

Created the script for building graphs from csv files for logs visual…

scripts/build_graph_from_csv

@@ -0,0 +1,76 @@
+#! /usr/bin/env python3
+
+"""This script parses csv log file and builds a graph"""
+
+from matplotlib import pyplot as plt
+import pandas as pd
+import argparse
+
+
+def build_graph():
+    parser = argparse.ArgumentParser(description='Gets file path and graph name to build a graph')
+    parser.add_argument('filepath', type=str, help='the csv file absolute path')
+    args = parser.parse_args()
+    file_path = args.filepath
+    try:
+        file = pd.read_csv(file_path)
+    except IOError:
+        assert False, "Could not find a path!"
+    subplot_value = 411
+    for i in ["Throughput", "Latency", "Queues"]:
+            multi_line_plot(i, file, subplot_value)
+            subplot_value += 1
+    separate_single_line_plots(file)
+    mng = plt.get_current_fig_manager()
+    mng.resize(*mng.window.maxsize())
+    plt.gca().grid(True)
+    plt.subplots_adjust(left=0.05, right=0.85)
+    plt.suptitle(file_path)
+    plt.show()
+
+
+def multi_line_plot(graph_name, file, subplot_value):
+    graph_data_dict = {"Throughput": ["client_stack_messages_processed_per_sec", "master_ordered_requests_count_per_sec"]
+                       , "Latency": ["avg_master_monitor_avg_latency", "avg_monitor_avg_latency"]
+                       , "Queues": ["avg_node_stack_messages_processed", "avg_client_stack_messages_processed"]
+                       }
+    timestamp = list(map(lambda x: x.replace("2018-", ""), file.timestamp))
+    numbers = range(len(timestamp))
+    looper_list = graph_data_dict[graph_name]
+    ax = plt.subplot(subplot_value)
+    for i in looper_list:
+        data_y_axis = file[i]
+        plt.plot(numbers, data_y_axis, label=i.upper())
+        plt.xticks(numbers, timestamp)
+        for label in ax.xaxis.get_ticklabels():
+            label.set_visible(False)
+        for label in list(filter(lambda x: ax.xaxis.get_major_ticks().index(x) % 10 != 0, ax.xaxis.get_major_ticks())):
+            label.set_visible(False)
+        plt.legend(bbox_to_anchor=(1, 1), loc=2, prop={'size': 8}, borderaxespad=0.)
+        plt.title(graph_name)
+        plt.gca().grid(True)
+
+
+def separate_single_line_plots(file):
+    timestamp = list(map(lambda x: x.replace("2018-", ""), file.timestamp))
+    numbers = range(len(timestamp))
+    looper_list = ["AVG_NODE_PROD_TIME", "AVG_SERVICE_REPLICAS_TIME", "AVG_SERVICE_NODE_MSGS_TIME",
+                   "AVG_SERVICE_ACTIONS_TIME", "AVG_SERVICE_ACTIONS_TIME", "AVG_SERVICE_VIEW_CHANGER_TIME"]
+    ax = plt.subplot(414)
+    ax.set_yscale("log")
+    for i in looper_list:
+        data_y_axis = file[i]
+        plt.plot(numbers, data_y_axis, label=i)
+        plt.xticks(numbers, timestamp)
+        plt.legend(bbox_to_anchor=(1, 1), loc=2, prop={'size': 8}, borderaxespad=0.)
+        for label in list(filter(lambda x: ax.xaxis.get_ticklabels().index(x) % 10 != 0, ax.xaxis.get_ticklabels())):
+            label.set_visible(False)
+        for label in list(filter(lambda x: ax.xaxis.get_major_ticks().index(x) % 10 != 0, ax.xaxis.get_major_ticks())):
+            label.set_visible(False)
+        plt.xticks(rotation=15)
+        plt.tick_params(axis='x', which='minor')
+        plt.title("Looper")
+
+
+if __name__ == '__main__':
+    build_graph()