lf_csv - creates csv for graph data

pick 6ea0cec lf_csv - creates csv for graph data

    pick 2fdb937 lf_csv - creates csv for graph data
    pick 0429552 conflicts resolved in lf_graph changes

py-scripts/lf_graph.py

@@ -25,6 +25,7 @@ import pandas as pd
 import pdfkit
 import math
 from matplotlib.colors import ListedColormap
+from lf_csv import LfCSV
 
 
 # internal candela references included during intial phases, to be deleted at future date
@@ -36,7 +37,8 @@ class lf_bar_graph():
                  _yaxis_name="y-axis",
                  _xaxis_categories=[1, 2, 3, 4, 5],
                  _xaxis_label=["a", "b", "c", "d", "e"],
-                 _step_size=5,
+                 _graph_title="",
+                 _title_size=16,
                  _graph_image_name="image_name",
                  _label=["bi-downlink", "bi-uplink", 'uplink'],
                  _color=None,
@@ -49,14 +51,17 @@ class lf_bar_graph():
                  _xaxis_step=5,
                  _xticks_font = None,
                  _grp_title = "",
-                 _dpi=96):
+                 _dpi=96,
+                 _enable_csv=True):
+>>>>>>> 6dd9cef... lf_csv - creates csv for graph data
 
         self.data_set = _data_set
         self.xaxis_name = _xaxis_name
         self.yaxis_name = _yaxis_name
         self.xaxis_categories = _xaxis_categories
         self.xaxis_label = _xaxis_label
-        self.step_size = _step_size
+        self.title = _graph_title
+        self.title_size = _title_size
         self.graph_image_name = _graph_image_name
         self.label = _label
         self.color = _color
@@ -69,6 +74,8 @@ class lf_bar_graph():
         self.xaxis_step = _xaxis_step
         self.xticks_font = _xticks_font
         self.grp_title = _grp_title
+        self.enable_csv = _enable_csv
+        self.lf_csv = LfCSV()
 
     def build_bar_graph(self):
         if self.color is None:
@@ -106,24 +113,27 @@ class lf_bar_graph():
                 i = i + 1
         plt.xlabel(self.xaxis_name, fontweight='bold', fontsize=15)
         plt.ylabel(self.yaxis_name, fontweight='bold', fontsize=15)
-        """plt.xticks([r + self.bar_width for r in range(len(self.data_set[0]))],
-                   self.xaxis_categories)"""
-        plt.xticks(np.arange(0, len(self.xaxis_categories), step=self.step_size), labels=self.xaxis_label)
-        plt.legend()
-
         if self.xaxis_categories[0] == 0:
             plt.xticks(np.arange(0, len(self.xaxis_categories), step=self.xaxis_step),fontsize = self.xticks_font)
         else:
             plt.xticks(np.arange(0, len(self.data_set[0]), step=self.xaxis_step), self.xaxis_categories,
                        fontsize = self.xticks_font)
-
         plt.legend()
+        plt.suptitle(self.title, fontsize=self.title_size)
         plt.title(self.grp_title)
         fig = plt.gcf()
         plt.savefig("%s.png" % self.graph_image_name, dpi=96)
         plt.close()
         print("{}.png".format(self.graph_image_name))
-
+        if self.enable_csv:
+            if self.data_set is not None:
+                self.lf_csv.columns = self.label
+                self.lf_csv.rows = self.data_set
+                self.lf_csv.filename = f"{self.graph_image_name}.csv"
+                self.lf_csv.generate_csv()
+            else:
+                print("No Dataset Found")
+        print("{}.csv".format(self.graph_image_name))
         return "%s.png" % self.graph_image_name
 
 
@@ -135,9 +145,10 @@ class lf_scatter_graph():
                  _xaxis_name="x-axis",
                  _yaxis_name="y-axis",
                  _label=["num1", "num2"],
-                 _graph_image_name="image_name",
+                 _graph_image_name="image_name1",
                  _color=["r", "y"],
-                 _figsize=(9, 4)):
+                 _figsize=(9, 4),
+                 _enable_csv=True):
         self.x_data_set = _x_data_set
         self.y_data_set = _y_data_set
         self.xaxis_name = _xaxis_name
@@ -147,6 +158,8 @@ class lf_scatter_graph():
         self.color = _color
         self.label = _label
         self.values = _values
+        self.enable_csv = _enable_csv
+        self.lf_csv = LfCSV()
 
     def build_scatter_graph(self):
         if self.color is None:
@@ -171,6 +184,11 @@ class lf_scatter_graph():
         plt.savefig("%s.png" % self.graph_image_name, dpi=96)
         plt.close()
         print("{}.png".format(self.graph_image_name))
+        if self.enable_csv:
+            self.lf_csv.columns = self.label
+            self.lf_csv.rows = self.y_data_set
+            self.lf_csv.filename = f"{self.graph_image_name}.csv"
+            self.lf_csv.generate_csv()
 
         return "%s.png" % self.graph_image_name
 
@@ -181,9 +199,10 @@ class lf_stacked_graph():
                  _xaxis_name="Stations",
                  _yaxis_name="Numbers",
                  _label=['Success', 'Fail'],
-                 _graph_image_name="image_name",
+                 _graph_image_name="image_name2",
                  _color=["b", "g"],
-                 _figsize=(9, 4)):
+                 _figsize=(9, 4),
+                 _enable_csv=True):
         self.data_set = _data_set  # [x_axis,y1_axis,y2_axis]
         self.xaxis_name = _xaxis_name
         self.yaxis_name = _yaxis_name
@@ -191,6 +210,8 @@ class lf_stacked_graph():
         self.graph_image_name = _graph_image_name
         self.label = _label
         self.color = _color
+        self.enable_csv = _enable_csv
+        self.lf_csv = LfCSV()
 
     def build_stacked_graph(self):
         fig = plt.subplots(figsize=self.figsize)
@@ -208,7 +229,11 @@ class lf_stacked_graph():
         plt.savefig("%s.png" % (self.graph_image_name), dpi=96)
         plt.close()
         print("{}.png".format(self.graph_image_name))
-
+        if self.enable_csv:
+            self.lf_csv.columns = self.label
+            self.lf_csv.rows = self.data_set
+            self.lf_csv.filename = f"{self.graph_image_name}.csv"
+            self.lf_csv.generate_csv()
         return "%s.png" % (self.graph_image_name)
 
 
@@ -221,10 +246,11 @@ class lf_horizontal_stacked_graph():
                  _unit="%",
                  _xaxis_name="Stations",
                  _label=['Success', 'Fail'],
-                 _graph_image_name="image_name",
+                 _graph_image_name="image_name3",
                  _color=["success", "Fail"],
                  _figsize=(9, 4),
-                 _disable_xaxis=False):
+                 _disable_xaxis=False,
+                 _enable_csv=True):
         self.unit = _unit
         self.seg = _seg
         self.xaxis_set1 = _xaxis_set1
@@ -236,6 +262,8 @@ class lf_horizontal_stacked_graph():
         self.label = _label
         self.color = _color
         self.disable_xaxis = _disable_xaxis
+        self.enable_csv = _enable_csv
+        self.lf_csv = LfCSV()
 
     def build_horizontal_stacked_graph(self):
         def sumzip(items):
@@ -277,7 +305,11 @@ class lf_horizontal_stacked_graph():
         plt.savefig("%s.png" % self.graph_image_name, dpi=96)
         plt.close()
         print("{}.png".format(self.graph_image_name))
-
+        # if self.enable_csv:
+        #     self.lf_csv.columns = self.label
+        #     self.lf_csv.rows = self.data_set
+        #     self.lf_csv.filename = f"{self.graph_image_name}.csv"
+        #     self.lf_csv.generate_csv()
         return "%s.png" % self.graph_image_name
 
 

py-scripts/lf_report.py

@@ -146,6 +146,8 @@ class lf_report():
         print("graph_src_file: {}".format(graph_src_file))
         print("graph_dst_file: {}".format(graph_dst_file))
         shutil.move(graph_src_file, graph_dst_file)
+    def move_csv_file(self):
+        csv_src_file = str(self.fil)
 
     def set_path(self,_path):
         self.path = _path

py-scripts/lf_report_test.py

@@ -96,7 +96,7 @@ if __name__ == "__main__":
                          _xaxis_categories=x_axis_values,
                          _graph_image_name="Bi-single_radio_2.4GHz",
                          _label=["bi-downlink", "bi-uplink", 'uplink'],
-                         _color=None,
+                         _color=['darkorange', 'forestgreen','blueviolet'],
                          _color_edge='red')
 
     graph_png = graph.build_bar_graph()

py-scripts/throughput_qos_report.py

@@ -1,142 +0,0 @@
-'''
-------------------------------------------------------------------------------------
-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 generate_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 for 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="Load", 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="Load", 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()