tos values retrieved

py-scripts/throughput_qos_report.py

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+'''
+------------------------------------------------------------------------------------
+Throughput QOS report evaluates the throughput for a number of clients which are running
+traffic with a particular type of service Video | Voice | BE | BK
+------------------------------------------------------------------------------------
+'''
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+import numpy as np
+import pandas as pd
+import pdfkit
+from lf_report import lf_report
+from lf_graph import lf_bar_graph
+
+
+def table(report, title, data):
+    # creating table
+    report.set_table_title(title)
+    report.build_table_title()
+    report.set_table_dataframe(data)
+    report.build_table()
+
+
+def grph(report, data_set=None, xaxis_name="stations", yaxis_name="Throughput 2 (Mbps)",
+         xaxis_categories=None, label=None, graph_image_name=""):
+    # creating bar graph
+    report.set_graph_title(graph_image_name)
+    report.build_graph_title()
+    graph = lf_bar_graph(_data_set=data_set,
+                         _xaxis_name=xaxis_name,
+                         _yaxis_name=yaxis_name,
+                         _xaxis_categories=xaxis_categories,
+                         _graph_image_name=graph_image_name,
+                         _label=label,
+                         _color=None,
+                         _color_edge='red')
+    graph_png = graph.build_bar_graph()
+    print("graph name {}".format(graph_png))
+    report.set_graph_image(graph_png)
+    report.move_graph_image()
+    report.build_graph()
+
+
+def tos_report(util, sta_num, bps_rx_a, bps_rx_b, tbl_title, grp_title, upload=1000000, download=1000000):
+    # report generation main function
+    rx_a = []
+    rx_b = []
+    pas_fail_up = []
+    pas_fail_down = []
+    thrp_b = upload * len(sta_num)  # get overall upload values
+    thrp_a = download * len(sta_num)  ## get overall download values
+    print(f"given upload--{thrp_b} and download--{thrp_a} values")
+    index = -1
+    for a in bps_rx_a:
+        index += 1
+        if len(a):
+            rx_a.append(f'min: {min(a)} | max: {max(a)} | avg: {sum(a) / len(a)}')
+            if thrp_a:
+                print(
+                    f"getting overall download values '{index}'----- {sum(a)} \n {(thrp_a / 100) * (100 - int(util[index]))}")
+                if (thrp_a / 100) * (100 - int(util[index])) <= sum(a):
+                    pas_fail_down.append("PASS")
+                else:
+                    pas_fail_down.append("FAIL")
+        else:
+            pas_fail_down.append("NA")
+            rx_a.append(0)
+
+        if len(bps_rx_b[index]):
+            rx_b.append(f'min: {min(bps_rx_b[index])} | max: {max(bps_rx_b[index])} | '
+                        f'avg: {(sum(bps_rx_b[index]) / len(bps_rx_b[index])):.2f}')
+
+            if thrp_b:
+                print(
+                    f"getting overall upload values '{index}'----- {sum(bps_rx_b[index])} \n {(thrp_b / 100) * (100 - int(util[index]))}")
+                if (thrp_b / 100) * (100 - int(util[index])) <= sum(bps_rx_b[index]):
+                    pas_fail_up.append("PASS")
+                else:
+                    pas_fail_up.append("FAIL")
+        else:
+            pas_fail_up.append("NA")
+            rx_b.append(0)
+
+        util[index] = f'{util[index]}%'  # append % to the util values
+
+    overall_tab = pd.DataFrame({
+        'Channel Utilization (%)': util, "No.of.clients": [len(sta_num)] * len(util),
+        'Speed (mbps)': [f'upload: {upload} | download: {download}'] * len(util),
+        'Upload (mbps)': rx_b, 'Download (mbps)': rx_a
+    })
+    print(f"overall table \n{overall_tab}")
+
+    pasfail_tab = pd.DataFrame({
+        'Channel Utilization (%)': util,
+        'Upload': pas_fail_up,
+        'Download': pas_fail_down
+    })
+    print(f"pass-fail table \n {pasfail_tab}")
+
+    report = lf_report()
+    report_path = report.get_path()
+    report_path_date_time = report.get_path_date_time()
+    print("path: {}".format(report_path))
+    print("path_date_time: {}".format(report_path_date_time))
+    report.set_title(tbl_title)
+    report.build_banner()
+
+    # objective title and description
+    report.set_obj_html(_obj_title="Objective",
+                        _obj="Through this test we can evaluate the throughput  given number of clients which"
+                             "are running the traffic with a particular TOS i.e BK,BE,VI,VO")
+    report.build_objective()
+
+    table(report, "Overall throughput", overall_tab)
+    table(report, "Throughput Pass/Fail", pasfail_tab)
+
+    if download:
+        grph(report,
+             data_set=[[min(i) for i in bps_rx_a], [max(i) for i in bps_rx_a], [sum(i) / len(i) for i in bps_rx_a]],
+             xaxis_name="Utilizations", yaxis_name="Throughput (Mbps)",
+             xaxis_categories=util, label=["min", "max", 'avg'], graph_image_name="Throughput_download")
+    if upload:
+        grph(report,
+             data_set=[[min(i) for i in bps_rx_b], [max(i) for i in bps_rx_b], [sum(i) / len(i) for i in bps_rx_b]],
+             xaxis_name="Utilizations", yaxis_name="Throughput (Mbps)",
+             xaxis_categories=util, label=["min", "max", 'avg'], graph_image_name="Throughput_upload")
+
+    for i in range(len(util)):
+        if download:
+            grph(report, data_set=[bps_rx_a[i]], xaxis_name="stations",
+                 yaxis_name="Throughput (Mbps)", xaxis_categories=range(0, len(sta_num)),
+                 label=[util[i]], graph_image_name=f"client-Throughput-download_{i}")
+        if upload:
+            grph(report, data_set=[bps_rx_b[i]], xaxis_name="stations",
+                 yaxis_name="Throughput (Mbps)", xaxis_categories=range(0, len(sta_num)),
+                 label=[util[i]], graph_image_name=f"client-Throughput-upload_{i}")
+
+    html_file = report.write_html()
+    print("returned file {}".format(html_file))
+    report.write_pdf()
+
+    # report.generate_report()