docs fixes:

http->https on jquery address
fix paths in performance job
add separator between creating and using performance data

Signed-off-by: Yaroslav Brustinov <ybrustin@cisco.com>

1 files changed, 99 insertions, 101 deletions

diff --git a/doc/TRexDataAnalysis.py b/doc/TRexDataAnalysis.py
index 3561b0f1..8f991dc3 100755
--- a/doc/TRexDataAnalysis.py
+++ b/doc/TRexDataAnalysis.py
@@ -6,131 +6,129 @@ matplotlib.use('Agg')
 from matplotlib import pyplot as plt

 import os

 

-PATH_FOR_GRAPHS = 'Z:/trex/trex-doc/images/'

-

 

 def convert_dict_to_dframe(data, categories, index=''):

-	data_input = {}

-	for category in categories:

-		data_input[category] = data[category]

-	if index:

-		df = pd.DataFrame(data_input, index=data[index])

-	else:

-		df = pd.DataFrame(data_input)

-	return df

+    data_input = {}

+    for category in categories:

+        data_input[category] = data[category]

+    if index:

+        df = pd.DataFrame(data_input, index=data[index])

+    else:

+        df = pd.DataFrame(data_input)

+    return df

 

 

 def plot_bar_by_category(data_frame, category, index='', graph_name='graph.png', show='', gtitle='', save_path=''):

-	if index:

-		data_frame = data_frame.sort_index(by=index)

-		print data_frame[index]

-	else:

-		print data_frame

-	data_frame = pd.DataFrame(data_frame[category], columns=category).astype(float)

-	data_frame.plot(kind='bar')

-	plt.xticks(rotation='horizontal')

-	plt.title(gtitle)

-	if save_path:

-		plt.savefig(save_path + graph_name)

-	if show:

-		plt.show()

-

-

-def generate_csv(data_frame, file_name, save_path=(os.getcwd() + "/")):

-	f = open(save_path + file_name, 'w')

-	data_frame.to_csv(f)

-	f.close()

+    if index:

+        data_frame = data_frame.sort_index(by=index)

+        print data_frame[index]

+    else:

+        print data_frame

+    data_frame = pd.DataFrame(data_frame[category], columns=category).astype(float)

+    data_frame.plot(kind='bar')

+    plt.xticks(rotation='horizontal')

+    plt.title(gtitle)

+    if save_path:

+        plt.savefig(os.path.join(save_path, graph_name))

+    if show:

+        plt.show()

+

+

+def generate_csv(data_frame, file_name, save_path=os.getcwd()):

+    f = open(os.path.join(save_path, file_name), 'w')

+    data_frame.to_csv(f)

+    f.close()

 

 

 # category is an array of category names that will appear as metrics

 def plot_bar_by_test_name(data_frame, test_name, category, graph_name='graph.png', show='', gtitle='', save_path=''):

-	data_frame = data_frame[data_frame['Test_name'] == test_name]

-	plot_bar_by_category(data_frame, category, 'Test_name', graph_name, show, gtitle=test_name, save_path=save_path)

+    data_frame = data_frame[data_frame['Test_name'] == test_name]

+    plot_bar_by_category(data_frame, category, 'Test_name', graph_name, show, gtitle=test_name, save_path=save_path)

 

 

 def generate_dframe_for_test(test_name, test_data):

-	test_results = []

-	test_mins = set()

-	test_maxs = set()

-	for query in test_data:

-		test_results.append(float(query[3]))

-		test_mins.add(float(query[4]))

-		test_maxs.add(float(query[5]))

-	df = pd.DataFrame({test_name: test_results})

-	stats = tuple([float(df.mean()), min(test_mins), max(test_maxs)])  # stats = (avg_mpps,min,max)

-	return df, stats

+    test_results = []

+    test_mins = set()

+    test_maxs = set()

+    for query in test_data:

+        test_results.append(float(query[3]))

+        test_mins.add(float(query[4]))

+        test_maxs.add(float(query[5]))

+    df = pd.DataFrame({test_name: test_results})

+    stats = tuple([float(df.mean()), min(test_mins), max(test_maxs)])  # stats = (avg_mpps,min,max)

+    return df, stats

 

 

 def generate_dframe_arr_and_stats_of_tests_per_setup(date, setup_name, setup_dict):

-	dframe_arr_trend = []

-	stats_arr = []

-	dframe_arr_latest = []

-	test_names = setup_dict.keys()

-	for test in test_names:

-		df, stats = generate_dframe_for_test(test, setup_dict[test])

-		dframe_arr_trend.append(df)

-		stats_arr.append(stats)

-		df_latest = float(setup_dict[test][-1][3])

-		dframe_arr_latest.append(df_latest)

-	dframe_arr_latest = pd.DataFrame({'Date': [date] * len(dframe_arr_latest),

-									  'Setup': [setup_name],

-									  'Test Name': test_names,

-									  'MPPS': dframe_arr_latest},

-									 index=range(1, len(dframe_arr_latest) + 1))

-	stats_df = pd.DataFrame(stats_arr, index=setup_dict.keys(), columns=['Avg MPPS', 'Golden Min', 'Golden Max'])

-	stats_df.index.name = 'Test Name'

-	return dframe_arr_trend, stats_df, dframe_arr_latest

+    dframe_arr_trend = []

+    stats_arr = []

+    dframe_arr_latest = []

+    test_names = setup_dict.keys()

+    for test in test_names:

+        df, stats = generate_dframe_for_test(test, setup_dict[test])

+        dframe_arr_trend.append(df)

+        stats_arr.append(stats)

+        df_latest = float(setup_dict[test][-1][3])

+        dframe_arr_latest.append(df_latest)

+    dframe_arr_latest = pd.DataFrame({'Date': [date] * len(dframe_arr_latest),

+                                      'Setup': [setup_name],

+                                      'Test Name': test_names,

+                                      'MPPS': dframe_arr_latest},

+                                     index=range(1, len(dframe_arr_latest) + 1))

+    stats_df = pd.DataFrame(stats_arr, index=setup_dict.keys(), columns=['Avg MPPS', 'Golden Min', 'Golden Max'])

+    stats_df.index.name = 'Test Name'

+    return dframe_arr_trend, stats_df, dframe_arr_latest

 

 

 def create_plot_for_dframe_arr(dframe_arr, setup_name, start_date, end_date, show='no', save_path='',

-							   file_name='trend_graph'):

-	dframe_all = pd.concat(dframe_arr, axis=1)

-	dframe_all = dframe_all.astype(float)

-	dframe_all.plot()

-	plt.legend(fontsize='small', loc='best')

-	plt.ylabel('MPPS')

-	plt.title('Setup: ' + setup_name)

-	plt.tick_params(

-		axis='x',

-		which='both',

-		bottom='off',

-		top='off',

-		labelbottom='off')

-	plt.xlabel('Time Period: ' + start_date + ' - ' + end_date)

-	if save_path:

-		plt.savefig(save_path + setup_name + file_name + '.png')

-	if show == 'yes':

-		plt.show()

+                               file_name='trend_graph'):

+    dframe_all = pd.concat(dframe_arr, axis=1)

+    dframe_all = dframe_all.astype(float)

+    dframe_all.plot()

+    plt.legend(fontsize='small', loc='best')

+    plt.ylabel('MPPS')

+    plt.title('Setup: ' + setup_name)

+    plt.tick_params(

+        axis='x',

+        which='both',

+        bottom='off',

+        top='off',

+        labelbottom='off')

+    plt.xlabel('Time Period: ' + start_date + ' - ' + end_date)

+    if save_path:

+        plt.savefig(os.path.join(save_path, setup_name + file_name + '.png'))

+    if show == 'yes':

+        plt.show()

 

 

 def create_bar_plot_for_latest_runs_per_setup(dframe_all_tests_latest, setup_name, show='no', save_path=''):

-	plt.figure()

-	dframe_all_tests_latest['MPPS'].plot(kind='bar', legend=False)

-	dframe_all_tests_latest = dframe_all_tests_latest[['Test Name', 'Setup', 'Date', 'MPPS']]

-	plt.xticks(rotation='horizontal')

-	plt.xlabel('Index of Tests')

-	plt.ylabel('MPPS')

-	plt.title("Test Runs for Setup: " + setup_name)

-	if save_path:

-		plt.savefig(save_path + setup_name + '_latest_test_runs.png')

-		dframe_all_tests_latest = dframe_all_tests_latest.round(2)

-		dframe_all_tests_latest.to_csv(save_path + setup_name + '_latest_test_runs_stats.csv')

-	if show == 'yes':

-		plt.show()

+    plt.figure()

+    dframe_all_tests_latest['MPPS'].plot(kind='bar', legend=False)

+    dframe_all_tests_latest = dframe_all_tests_latest[['Test Name', 'Setup', 'Date', 'MPPS']]

+    plt.xticks(rotation='horizontal')

+    plt.xlabel('Index of Tests')

+    plt.ylabel('MPPS')

+    plt.title("Test Runs for Setup: " + setup_name)

+    if save_path:

+        plt.savefig(os.path.join(save_path, setup_name + '_latest_test_runs.png'))

+        dframe_all_tests_latest = dframe_all_tests_latest.round(2)

+        dframe_all_tests_latest.to_csv(os.path.join(save_path, setup_name + '_latest_test_runs_stats.csv'))

+    if show == 'yes':

+        plt.show()

 

 

 def create_all_data_per_setup(setup_dict, setup_name, start_date, end_date, show='no', save_path='', add_stats=''):

-	dframe_arr, stats_arr, dframe_latest_arr = generate_dframe_arr_and_stats_of_tests_per_setup(end_date, setup_name,

-																								setup_dict)

-	create_bar_plot_for_latest_runs_per_setup(dframe_latest_arr, setup_name, show=show, save_path=save_path)

-	create_plot_for_dframe_arr(dframe_arr, setup_name, start_date, end_date, show, save_path)

-	if add_stats:

-		stats_arr = stats_arr.round(2)

-		stats_arr.to_csv(save_path + setup_name + '_trend_stats.csv')

-	plt.close('all')

+    dframe_arr, stats_arr, dframe_latest_arr = generate_dframe_arr_and_stats_of_tests_per_setup(end_date, setup_name,

+                                                                                                setup_dict)

+    create_bar_plot_for_latest_runs_per_setup(dframe_latest_arr, setup_name, show=show, save_path=save_path)

+    create_plot_for_dframe_arr(dframe_arr, setup_name, start_date, end_date, show, save_path)

+    if add_stats:

+        stats_arr = stats_arr.round(2)

+        stats_arr.to_csv(os.path.join(save_path, setup_name + '_trend_stats.csv'))

+    plt.close('all')

 

 

 def create_all_data(ga_data, setup_names, start_date, end_date, save_path='', add_stats=''):

-	for setup_name in setup_names:

-		create_all_data_per_setup(ga_data[setup_name], setup_name, start_date, end_date, show='no', save_path=save_path,

-								  add_stats=add_stats)

+    for setup_name in setup_names:

+        create_all_data_per_setup(ga_data[setup_name], setup_name, start_date, end_date, show='no', save_path=save_path,

+                                  add_stats=add_stats)