unit.quit()
#------------------------------------------------------------------------------
#------------------------------------------------------------------------------
# Load results reads the log_file, and creates feature vectors
def load_results():
pass
def test_stat(observed_values, unit_assignments):
pass
adfisher.do_experiment(make_unit=make_browser,
treatments=[control_treatment, exp_treatment],
measurement=measurement,
end_unit=cleanup_browser,
load_results=load_results,
test_stat=test_stat,
ml_analysis=True,
num_blocks=13,
num_units=4,
timeout=2000,
log_file=log_file,
exp_flag=True,
analysis_flag=False,
treatment_names=["control", "experimental"])
unit.visit_sites(site_file)
# Measurement - Collects ads
def measurement(unit):
unit.collect_ads(reloads=10, delay=5, site='bbc')
# Shuts down the browser once we are done with it.
def cleanup_browser(unit):
unit.quit()
# Load results reads the log_file, and creates feature vectors
def load_results():
collection, names = converter.reader.read_log(log_file)
return converter.reader.get_feature_vectors(collection, feat_choice='ads')
# If you choose to perform ML, then test_stat is redundant. By default, correctly_classified is used,
# If not, then you can choose something, and that will be used to perform the analysis.
def test_stat(observed_values, unit_assignments):
return analysis.statistics.difference(observed_values, unit_assignments)
# return statistics.correctly_classified(observed_values, unit_assignments)
adfisher.do_experiment(make_unit=make_browser, treatments=[control_treatment, exp_treatment],
measurement=measurement, end_unit=cleanup_browser,
load_results=load_results, test_stat=test_stat, ml_analysis=True,
num_blocks=20, num_units=4, timeout=2000,
log_file=log_file,
treatment_names=["control (null)", "experimental (substance abuse)"])
def exp_treatment(unit):
pass
# Measurement - Collects ads
# checks all the sites that adfisher could previously collect on
# (~10 minutes for src and href)
def measurement(unit):
sites = ['toi','bbc','guardian','reuters','bloomberg']
for site in sites:
unit.collect_ads(site=site, reloads=2, delay=5)
# Shuts down the browser once we are done with it.
def cleanup_browser(unit):
unit.quit()
# Blank analysis
def load_results():
pass
# Blank analysis
def test_stat(observed_values, unit_assignments):
pass
adfisher.do_experiment(make_unit=make_browser, treatments=[control_treatment, exp_treatment],
measurement=measurement, end_unit=cleanup_browser,
load_results=load_results, test_stat=test_stat, ml_analysis=False,
num_blocks=1, num_units=4, timeout=2000,
log_file=log_file, exp_flag=True, analysis_flag=False,
treatment_names=["control", "experimental"])
treatments = [exp_treatment2, control_treatment]
treatment_names = [
"experimental (TOPIC queries)",
"control (null)",
]
if sys.argv[1] == 'measure':
# CAN change parameters below
adfisher.do_experiment(
make_unit=make_browser,
treatments=treatments,
treatment_names=treatment_names,
measurement=measurement,
end_unit=cleanup_browser,
exp_flag=True,
analysis_flag=False,
num_blocks=10,
num_units=6,
timeout=2000,
log_file=log_file
)
if sys.argv[1] == 'analyze':
# CAN change parameters below
adfisher.do_experiment(
treatments=treatments,
treatment_names=treatment_names,
load_results=load_results,
