def research_question_1_figure_11_utility_function(wl='a'):
# df = gu.calculate_summary(input_csv_file_name='experiment_12_wireless_tests',
# read_from_csv=True,
# dataframe=None,
# measurement_of_interest='[OVERALL] RunTime(ms)',
# series_to_group_by=['ram', 'nm', 'nt', 'rf', 'wl', 'nn'],
# return_series_not_data_frame=False,
# reset_index_before_returning_data_frame=True,
# summary_statistic_of_interest='median'
# )
df = pd.read_csv('combined_results_revised.csv')
for i in [wl]:
gu.generate_filtered_graph(df=df,
csv_with_main_results='combined_results_revised.csv',
read_from_csv=False,
d={'wl': i, 'nt': 'rp'},
x_column='nn',
y_column='[OVERALL] RunTime(ms)',
s_column=None,
show_zero_line_on_y_axis=True,
title='Execution Time, Workload {}'.format(i),
filename='figures/wl{}_fig11.html'.format(wl),
image_filename='figures/wl{}_fig11'.format(wl),
image_type='svg',
type='boxplot',
save_image_as_svg=True)
return 0
def research_question_figure_4_utility_function(workload='a',
):
csv_file='combined_results_revised.csv'
title='Execution Time, Workload {}'.format(workload.capitalize())
df = pd.read_csv(csv_file)
new_column_name = 'NumberOfNodes'
df[new_column_name] = df['nn'].map(str) + ' Nodes' # add column
for i in [workload]:
for j in [1]:
gu.generate_filtered_graph(df,
d={'nm': 'nodal',
'nt': 'vm',
'wl': i,
't': range(10, 31)},
x_column=new_column_name,
y_column='[OVERALL] RunTime(ms)',
s_column='ram',
title=title,
type='boxplot',
read_from_csv=False,
filename='figures/wl{}_fig4.html'.format(i),
image_filename='figures/wl{}_fig4'.format(i),
image_type='svg',
save_image_as_svg=True,
boxmean=True)
return 0
def research_question_1_figure_9_utility_fn(workload='a',
research_question='1'):
df = gu.calculate_summary(input_csv_file_name='combined_results_revised.csv',
read_from_csv=True,
dataframe=None,
measurement_of_interest='[OVERALL] RunTime(ms)',
series_to_group_by=['ram', 'nm', 'nt', 'rf', 'wl', 'nn'],
return_series_not_data_frame=False,
reset_index_before_returning_data_frame=True,
summary_statistic_of_interest='stdev'
)
for i in [workload]:
gu.generate_filtered_graph(df=df,
read_from_csv=False,
d={'wl': i, 'nt': 'rp'},
x_column='nm',
y_column='[OVERALL] RunTime(ms)',
s_column='nn',
title='Workload {} Execution Time'.format(workload.capitalize()),
mode='marker',
show_zero_line_on_y_axis=True,
filename='figures/wl{}_fig9.html'.format(i),
image_filename='figures/wl{}_fig9'.format(i),
type='bar',
save_image_as_pdf=False,
save_image_locally_as_png_=False,
save_image_as_svg=True)
return 0
def research_question_1_figure_6_utility_function(wl='a'):
df = gu.calculate_summary(input_csv_file_name='combined_results_revised.csv',
read_from_csv=True,
dataframe=None,
measurement_of_interest='[OVERALL] RunTime(ms)',
series_to_group_by=['ram', 'nm', 'nt', 'rf', 'wl', 'nn'],
return_series_not_data_frame=False,
reset_index_before_returning_data_frame=True,
summary_statistic_of_interest='median',
)
df_ref = pd.read_csv('abramova_results.csv')
df_ref = gu.return_filtered_dataframe(df_ref, {'wl': wl})
df = df.append(df_ref, ignore_index=True)
df['nt-ram'] = df['nt'].map(str) + '-' + df['ram'].map(str) # for the series name
for i in [wl]:
gu.generate_filtered_graph(df=df,
read_from_csv=False,
d={'wl': i, 'nt-ram': ['vm-1GB', 'ref-2GB', 'rp-1GB'], 'nm': ['eth','nodal','unk']},
x_column='nn',
y_column='[OVERALL] RunTime(ms)',
s_column='nt-ram',
title='Execution Time, Workload {}'.format(i.capitalize()),
mode='marker',
filename='figures/wl{}_fig6.html'.format(wl),
image_filename='figures/wl{}_fig6'.format(wl),
image_type='svg',
save_image_as_svg=True)
return 0
def test_generate_filtered_graph():
sg.generate_filtered_graph(csv_with_main_results='test_data.csv',
d=None,
x_column='Year',
y_column='UFOSightings',
s_column='City',
title='UFO Sightings in Various Cities',
mode='line',
image_filename='results/ufosightings.png')
def research_question_1_figure_1_utility_function(wl='a'):
gu.generate_filtered_graph(csv_with_main_results='abramova_results.csv',
d={
'wl': wl
},
x_column='nn',
y_column='[OVERALL] RunTime(ms)',
s_column=None,
title='Execution Time, Workload {}'.format(wl.capitalize()),
mode='markers',
filename='figures/wl{}_fig1.html'.format(wl),
image_filename='figures/wl{}_fig1'.format(wl),
image_type='svg',
save_image_as_svg=True,
type='bar')
def research_question_1_figure_8_utility_function(wl='a'):
df = pd.read_csv('combined_results_revised.csv')
for i in [wl]:
gu.generate_filtered_graph(df=df,
read_from_csv=False,
d={'wl': i,
'nm': 'wlan'},
x_column='nn',
y_column='[OVERALL] RunTime(ms)',
s_column=None,
show_zero_line_on_y_axis=True,
title='Execution Time, Workload {}'.format(i),
filename='figures/wl{}_fig8.html'.format(wl),
image_filename='figures/wl{}_fig8'.format(wl),
image_type='svg',
type='boxplot',
save_image_as_svg=True)
return 0
def research_question_1_figure_2_3_utility_fn(csv_file, title,
d={'nm': 'nodal',
'nt': 'vm',
'nn': 1,
'wl': 'a'},
filename='figures/wl{}_fig23.html'.format('a'),
image_filename='figures/wla_fig23',
image_type='svg',
save_image_as_svg=True):
for i in ['a']:
for j in [1]:
gu.generate_filtered_graph(csv_with_main_results=csv_file,
d=d,
x_column='t',
y_column='[OVERALL] RunTime(ms)',
s_column='ram',
title=title,
mode='line',
filename=filename,
image_filename=image_filename,
save_image_as_svg=save_image_as_svg,
image_type=image_type)
def generate_cassandra_stress_graphs(graph_of_choice='none'):
if graph_of_choice == '1':
sg.generate_filtered_graph(
df=None,
read_from_csv=True,
csv_with_main_results=
'results/exp0_cstress/cassandra_stress_results_compression_strategy.csv',
d={'op': 'writes_only'},
x_column='network_type',
y_column='op/s',
s_column='compression',
title='Operations Per Second - Writes Only',
mode='markers',
boxmean='sd',
boxpoints='all',
filename='figures/cs1_fig1.html',
image_filename='figures/cs1_fig1',
image_type='svg',
type='boxplot',
show_zero_line_on_y_axis=False,
verbose=True,
html_filename='cs1_fig1.html',
save_image_locally_as_png_=False,
save_image_as_html=True,
save_image_as_svg=True,
save_image_as_pdf=False)
elif graph_of_choice == '2':
sg.generate_filtered_graph(
df=None,
read_from_csv=True,
csv_with_main_results=
'results/exp0_cstress/cassandra_stress_results_compression_strategy.csv',
d={'op': 'reads_only'},
x_column='network_type',
y_column='op/s',
s_column='compression',
title='Operations Per Second - Reads Only',
mode='markers',
boxmean='sd',
boxpoints='all',
filename='figures/cs1_fig2.html',
image_filename='figures/cs1_fig2',
image_type='svg',
type='boxplot',
show_zero_line_on_y_axis=False,
verbose=True,
html_filename='cs1_fig1.html',
save_image_locally_as_png_=False,
save_image_as_html=True,
save_image_as_svg=True,
save_image_as_pdf=False)
elif graph_of_choice == '3':
csv_file = 'results/exp0_cstress/cassandra_stress_results_compression_strategy.csv'
df = pd.read_csv(csv_file)
new_column_name = 'Compression-Operations'
df[new_column_name] = df['compression'].map(str) + '-' + df[
'op'] # add column
sg.generate_filtered_graph(df=df,
read_from_csv=False,
csv_with_main_results=csv_file,
d={'network_type': 'wired'},
x_column=new_column_name,
y_column='op/s',
s_column=None,
title='Operations Per Second',
mode='markers',
boxmean='sd',
boxpoints='all',
filename='figures/cs1_fig3.html',
image_filename='figures/cs1_fig3',
image_type='svg',
type='boxplot',
show_zero_line_on_y_axis=False,
verbose=True,
html_filename='cs1_fig1.html',
save_image_locally_as_png_=False,
save_image_as_html=True,
save_image_as_svg=True,
save_image_as_pdf=False,
sort_by_means=True)
elif graph_of_choice == '4':
csv_file = 'results/exp0_cstress/cassandra_stress_results_compression_strategy.csv'
df = pd.read_csv(csv_file)
new_column_name = 'Compression-Operations'
df[new_column_name] = df['compression'].map(str) + '-' + df[
'op'] # add column
sg.generate_filtered_graph(
df=df,
read_from_csv=False,
csv_with_main_results=
'results/exp0_cstress/cassandra_stress_results_compression_strategy.csv',
d={'network_type': 'wireless'},
x_column=new_column_name,
y_column='op/s',
s_column='compression',
title='Operations Per Second',
mode='markers',
boxmean='sd',
boxpoints='all',
filename='figures/cs1_fig4.html',
image_filename='figures/cs1_fig4',
image_type='svg',
type='boxplot',
show_zero_line_on_y_axis=False,
verbose=True,
html_filename='cs1_fig1.html',
save_image_locally_as_png_=False,
save_image_as_html=True,
save_image_as_svg=True,
save_image_as_pdf=False,
sort_by_means=True)
