import socialsim as ss
# Load the configuration file
config = 'data/cp4_configuration.json'
config = ss.load_config(config)
# Get metadata
metadata = ss.MetaData()
# Instantiate the task runner with the specified ground truth
ground_truth_filepath = 'data/test_dataset.json'
ground_truth = ss.load_data(ground_truth_filepath,
ignore_first_line=True,
verbose=False)
eval_runner = ss.EvaluationRunner(ground_truth, config, metadata=metadata)
# Evaluate a series of submissions that contain submission metadata as the first line of the submission file\
submission_filepaths = ['data/test_dataset.json']
for simulation_filepath in submission_filepaths:
# Run measurements and metrics on the simulation data
results, logs = eval_runner(simulation_filepath,
verbose=True,
submission_meta=True)
import socialsim as ss # Load the simulation data simulation = 'data/test_dataset.txt' simulation = ss.load_data(simulation) # Load the ground truth data ground_truth = 'data/test_dataset.txt' ground_truth = ss.load_data(ground_truth) # Load the configuration file config = 'data/cp2_configuration.json' config = ss.load_config(config) # Get metadata metadata = ss.MetaData(community_directory='data/communities/') # Instantiate the task runner task_runner = ss.TaskRunner(ground_truth, config, metadata=metadata, test=True) # Run measurements and metrics on the simulation data results = task_runner(simulation, verbose=True)
import socialsim as ss
# Load the example dataset
dataset = 'data/test_dataset.txt'
dataset = ss.load_data(dataset)
# Load the configuration file
config = 'data/recurrence_configuration.json'
config = ss.load_config(config)
# Subset the configuration for the given task
config = config
config = config['recurrence']
# load metadata
metadata = ss.MetaData(community_directory='data/communities',
content_data=True)
# Define the measurement object
# recurrence_measurements = ss.RecurrenceMeasurements(dataset, config['recurrence'], id_col='nodeID', userid_col='nodeUserID', timestamp_col='nodeTime', content_col='informationID')
recurrence_measurements = ss.RecurrenceMeasurements(dataset,
config['recurrence'],
metadata=metadata,
id_col='nodeID',
userid_col='nodeUserID',
timestamp_col='nodeTime',
content_col='platform',
time_granularity='H')
# Run all measurements in the config file
results = recurrence_measurements.run(verbose=True)
from pprint import pprint
import socialsim as ss
# Load the simulation data
simulation = 'data/test_dataset.txt'
simulation = ss.load_data(simulation, ignore_first_line=True, verbose=False)
# Load the ground truth data
ground_truth = 'data/test_dataset.txt'
ground_truth = ss.load_data(ground_truth, ignore_first_line=True, verbose=False)
# Load the configuration file
config = 'data/cp2_configuration.json'
config = ss.load_config(config)
# Get metadata
metadata = ss.MetaData(community_directory='data/communities/',
node_file='data/node_list.txt')
# Instantiate the task runner
task_runner = ss.TaskRunner(ground_truth, config, metadata=metadata, test=True)
# Run measurements and metrics on the simulation data
results, logs = task_runner(simulation, verbose=True)
# Print metrics
pprint(results['metrics'])