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https://github.com/Telecominfraproject/wlan-lanforge-scripts.git
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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
This commit is contained in:
anil-tegala
0
py-scripts/lf_csv.py
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0
py-scripts/lf_csv.py
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@@ -25,6 +25,7 @@ import pandas as pd
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import pdfkit
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import math
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from matplotlib.colors import ListedColormap
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from lf_csv import LfCSV
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# internal candela references included during intial phases, to be deleted at future date
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@@ -36,7 +37,8 @@ class lf_bar_graph():
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_yaxis_name="y-axis",
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_xaxis_categories=[1, 2, 3, 4, 5],
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_xaxis_label=["a", "b", "c", "d", "e"],
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_step_size=5,
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_graph_title="",
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_title_size=16,
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_graph_image_name="image_name",
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_label=["bi-downlink", "bi-uplink", 'uplink'],
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_color=None,
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@@ -49,14 +51,17 @@ class lf_bar_graph():
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_xaxis_step=5,
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_xticks_font = None,
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_grp_title = "",
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_dpi=96):
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_dpi=96,
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_enable_csv=True):
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>>>>>>> 6dd9cef... lf_csv - creates csv for graph data
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self.data_set = _data_set
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self.xaxis_name = _xaxis_name
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self.yaxis_name = _yaxis_name
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self.xaxis_categories = _xaxis_categories
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self.xaxis_label = _xaxis_label
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self.step_size = _step_size
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self.title = _graph_title
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self.title_size = _title_size
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self.graph_image_name = _graph_image_name
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self.label = _label
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self.color = _color
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@@ -69,6 +74,8 @@ class lf_bar_graph():
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self.xaxis_step = _xaxis_step
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self.xticks_font = _xticks_font
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self.grp_title = _grp_title
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self.enable_csv = _enable_csv
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self.lf_csv = LfCSV()
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def build_bar_graph(self):
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if self.color is None:
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@@ -106,24 +113,27 @@ class lf_bar_graph():
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i = i + 1
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plt.xlabel(self.xaxis_name, fontweight='bold', fontsize=15)
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plt.ylabel(self.yaxis_name, fontweight='bold', fontsize=15)
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"""plt.xticks([r + self.bar_width for r in range(len(self.data_set[0]))],
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self.xaxis_categories)"""
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plt.xticks(np.arange(0, len(self.xaxis_categories), step=self.step_size), labels=self.xaxis_label)
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plt.legend()
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if self.xaxis_categories[0] == 0:
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plt.xticks(np.arange(0, len(self.xaxis_categories), step=self.xaxis_step),fontsize = self.xticks_font)
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else:
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plt.xticks(np.arange(0, len(self.data_set[0]), step=self.xaxis_step), self.xaxis_categories,
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fontsize = self.xticks_font)
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plt.legend()
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plt.suptitle(self.title, fontsize=self.title_size)
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plt.title(self.grp_title)
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fig = plt.gcf()
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plt.savefig("%s.png" % self.graph_image_name, dpi=96)
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plt.close()
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print("{}.png".format(self.graph_image_name))
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if self.enable_csv:
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if self.data_set is not None:
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self.lf_csv.columns = self.label
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self.lf_csv.rows = self.data_set
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self.lf_csv.filename = f"{self.graph_image_name}.csv"
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self.lf_csv.generate_csv()
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else:
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print("No Dataset Found")
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print("{}.csv".format(self.graph_image_name))
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return "%s.png" % self.graph_image_name
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@@ -135,9 +145,10 @@ class lf_scatter_graph():
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_xaxis_name="x-axis",
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_yaxis_name="y-axis",
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_label=["num1", "num2"],
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_graph_image_name="image_name",
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_graph_image_name="image_name1",
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_color=["r", "y"],
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_figsize=(9, 4)):
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_figsize=(9, 4),
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_enable_csv=True):
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self.x_data_set = _x_data_set
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self.y_data_set = _y_data_set
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self.xaxis_name = _xaxis_name
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@@ -147,6 +158,8 @@ class lf_scatter_graph():
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self.color = _color
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self.label = _label
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self.values = _values
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self.enable_csv = _enable_csv
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self.lf_csv = LfCSV()
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def build_scatter_graph(self):
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if self.color is None:
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@@ -171,6 +184,11 @@ class lf_scatter_graph():
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plt.savefig("%s.png" % self.graph_image_name, dpi=96)
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plt.close()
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print("{}.png".format(self.graph_image_name))
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if self.enable_csv:
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self.lf_csv.columns = self.label
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self.lf_csv.rows = self.y_data_set
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self.lf_csv.filename = f"{self.graph_image_name}.csv"
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self.lf_csv.generate_csv()
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return "%s.png" % self.graph_image_name
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@@ -181,9 +199,10 @@ class lf_stacked_graph():
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_xaxis_name="Stations",
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_yaxis_name="Numbers",
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_label=['Success', 'Fail'],
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_graph_image_name="image_name",
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_graph_image_name="image_name2",
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_color=["b", "g"],
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_figsize=(9, 4)):
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_figsize=(9, 4),
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_enable_csv=True):
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self.data_set = _data_set # [x_axis,y1_axis,y2_axis]
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self.xaxis_name = _xaxis_name
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self.yaxis_name = _yaxis_name
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@@ -191,6 +210,8 @@ class lf_stacked_graph():
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self.graph_image_name = _graph_image_name
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self.label = _label
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self.color = _color
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self.enable_csv = _enable_csv
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self.lf_csv = LfCSV()
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def build_stacked_graph(self):
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fig = plt.subplots(figsize=self.figsize)
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@@ -208,7 +229,11 @@ class lf_stacked_graph():
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plt.savefig("%s.png" % (self.graph_image_name), dpi=96)
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plt.close()
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print("{}.png".format(self.graph_image_name))
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if self.enable_csv:
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self.lf_csv.columns = self.label
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self.lf_csv.rows = self.data_set
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self.lf_csv.filename = f"{self.graph_image_name}.csv"
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self.lf_csv.generate_csv()
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return "%s.png" % (self.graph_image_name)
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@@ -221,10 +246,11 @@ class lf_horizontal_stacked_graph():
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_unit="%",
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_xaxis_name="Stations",
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_label=['Success', 'Fail'],
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_graph_image_name="image_name",
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_graph_image_name="image_name3",
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_color=["success", "Fail"],
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_figsize=(9, 4),
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_disable_xaxis=False):
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_disable_xaxis=False,
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_enable_csv=True):
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self.unit = _unit
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self.seg = _seg
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self.xaxis_set1 = _xaxis_set1
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@@ -236,6 +262,8 @@ class lf_horizontal_stacked_graph():
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self.label = _label
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self.color = _color
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self.disable_xaxis = _disable_xaxis
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self.enable_csv = _enable_csv
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self.lf_csv = LfCSV()
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def build_horizontal_stacked_graph(self):
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def sumzip(items):
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@@ -277,7 +305,11 @@ class lf_horizontal_stacked_graph():
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plt.savefig("%s.png" % self.graph_image_name, dpi=96)
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plt.close()
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print("{}.png".format(self.graph_image_name))
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# if self.enable_csv:
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# self.lf_csv.columns = self.label
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# self.lf_csv.rows = self.data_set
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# self.lf_csv.filename = f"{self.graph_image_name}.csv"
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# self.lf_csv.generate_csv()
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return "%s.png" % self.graph_image_name
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@@ -146,6 +146,8 @@ class lf_report():
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print("graph_src_file: {}".format(graph_src_file))
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print("graph_dst_file: {}".format(graph_dst_file))
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shutil.move(graph_src_file, graph_dst_file)
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def move_csv_file(self):
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csv_src_file = str(self.fil)
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def set_path(self,_path):
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self.path = _path
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@@ -96,7 +96,7 @@ if __name__ == "__main__":
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_xaxis_categories=x_axis_values,
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_graph_image_name="Bi-single_radio_2.4GHz",
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_label=["bi-downlink", "bi-uplink", 'uplink'],
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_color=None,
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_color=['darkorange', 'forestgreen','blueviolet'],
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_color_edge='red')
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graph_png = graph.build_bar_graph()
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@@ -1,142 +0,0 @@
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'''
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------------------------------------------------------------------------------------
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Throughput QOS report evaluates the throughput for a number of clients which are running
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traffic with a particular type of service Video | Voice | BE | BK
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------------------------------------------------------------------------------------
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'''
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import matplotlib.pyplot as plt
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import matplotlib as mpl
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import numpy as np
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import pandas as pd
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import pdfkit
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from lf_report import lf_report
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from lf_graph import lf_bar_graph
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def table(report, title, data):
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# creating table
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report.set_table_title(title)
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report.build_table_title()
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report.set_table_dataframe(data)
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report.build_table()
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def grph(report, data_set=None, xaxis_name="stations", yaxis_name="Throughput 2 (Mbps)",
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xaxis_categories=None, label=None, graph_image_name=""):
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# creating bar graph
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report.set_graph_title(graph_image_name)
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report.build_graph_title()
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graph = lf_bar_graph(_data_set=data_set,
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_xaxis_name=xaxis_name,
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_yaxis_name=yaxis_name,
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_xaxis_categories=xaxis_categories,
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_graph_image_name=graph_image_name,
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_label=label,
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_color=None,
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_color_edge='red')
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graph_png = graph.build_bar_graph()
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print("graph name {}".format(graph_png))
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report.set_graph_image(graph_png)
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report.move_graph_image()
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report.build_graph()
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def generate_report(util, sta_num, bps_rx_a, bps_rx_b, tbl_title, grp_title, upload=1000000, download=1000000):
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# report generation main function
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rx_a = []
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rx_b = []
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pas_fail_up = []
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pas_fail_down = []
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thrp_b = upload * len(sta_num) # get overall upload values
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thrp_a = download * len(sta_num) ## get overall download values
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print(f"given upload--{thrp_b} and download--{thrp_a} values")
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index = -1
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for a in bps_rx_a:
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index += 1
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if len(a):
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rx_a.append(f'min: {min(a)} | max: {max(a)} | avg: {sum(a) / len(a)}')
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if thrp_a:
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print(
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f"getting overall download values '{index}'----- {sum(a)} \n {(thrp_a / 100) * (100 - int(util[index]))}")
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if (thrp_a / 100) * (100 - int(util[index])) <= sum(a):
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pas_fail_down.append("PASS")
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else:
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pas_fail_down.append("FAIL")
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else:
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pas_fail_down.append("NA")
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rx_a.append(0)
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if len(bps_rx_b[index]):
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rx_b.append(f'min: {min(bps_rx_b[index])} | max: {max(bps_rx_b[index])} | '
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f'avg: {(sum(bps_rx_b[index]) / len(bps_rx_b[index])):.2f}')
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if thrp_b:
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print(
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f"getting overall upload values '{index}'----- {sum(bps_rx_b[index])} \n {(thrp_b / 100) * (100 - int(util[index]))}")
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if (thrp_b / 100) * (100 - int(util[index])) <= sum(bps_rx_b[index]):
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pas_fail_up.append("PASS")
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else:
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pas_fail_up.append("FAIL")
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else:
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pas_fail_up.append("NA")
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rx_b.append(0)
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util[index] = f'{util[index]}%' # append % to the util values
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overall_tab = pd.DataFrame({
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'Channel Utilization (%)': util, "No.of.clients": [len(sta_num)] * len(util),
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'Speed (mbps)': [f'upload: {upload} | download: {download}'] * len(util),
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'Upload (mbps)': rx_b, 'Download (mbps)': rx_a
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})
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print(f"overall table \n{overall_tab}")
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pasfail_tab = pd.DataFrame({
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'Channel Utilization (%)': util,
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'Upload': pas_fail_up,
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'Download': pas_fail_down
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})
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print(f"pass-fail table \n {pasfail_tab}")
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report = lf_report()
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report_path = report.get_path()
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report_path_date_time = report.get_path_date_time()
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print("path: {}".format(report_path))
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print("path_date_time: {}".format(report_path_date_time))
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report.set_title(tbl_title)
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report.build_banner()
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# objective title and description
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report.set_obj_html(_obj_title="Objective",
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_obj="Through this test we can evaluate the throughput for given number of clients which"
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"are running the traffic with a particular TOS i.e BK,BE,VI,VO")
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report.build_objective()
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table(report, "Overall throughput", overall_tab)
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table(report, "Throughput Pass/Fail", pasfail_tab)
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if download:
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grph(report,
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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]],
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xaxis_name="Load", yaxis_name="Throughput (Mbps)",
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xaxis_categories=util, label=["min", "max", 'avg'], graph_image_name="Throughput_download")
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if upload:
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grph(report,
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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]],
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xaxis_name="Load", yaxis_name="Throughput (Mbps)",
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xaxis_categories=util, label=["min", "max", 'avg'], graph_image_name="Throughput_upload")
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for i in range(len(util)):
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if download:
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grph(report, data_set=[bps_rx_a[i]], xaxis_name="stations",
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yaxis_name="Throughput (Mbps)", xaxis_categories=range(0, len(sta_num)),
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label=[util[i]], graph_image_name=f"client-Throughput-download_{i}")
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if upload:
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grph(report, data_set=[bps_rx_b[i]], xaxis_name="stations",
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yaxis_name="Throughput (Mbps)", xaxis_categories=range(0, len(sta_num)),
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label=[util[i]], graph_image_name=f"client-Throughput-upload_{i}")
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html_file = report.write_html()
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print("returned file {}".format(html_file))
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report.write_pdf()
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# report.generate_report()
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